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How stock splits can multiply profits p. 50
Uncovered: A critical look at the covered call p. 40
trAding trend trAnsitions:getting in early p. 28
Finding tHe best gAp trAdes p. 34
risk and reward: catching the stock market’s big swings p. 14
welcome to the (systems) mAtrix p. 20
Decem
ber 2010
Active Trader
Trends, trends, trends
$4.95 Printed in the U.S.A. www.activetradermag.com
• TRADING STRATEGIES FOR THE FINANCIAL MARKETS •
December 2010 • Volume 11, No. 12
®
®
2 www.activetradermag.com • December 2010 • ACTIVE TRADER
CONTENTSDecember 2010 • VOLUME 11, NO. 12
6 Contributors
8 Opening TradesTrends and events moving
the markets.
64 Trading Calendar
68 Stocks SnapshotVolume, volatility, and momentum
statistics for stocks.
69 ETF SnapshotVolume, volatility, and momentum
statistics for exchange-traded funds.
70 Futures SnapshotVolume, volatility, and momentum
statistics for futures.
73 Trader’s Bookshelf
74 Trader’s Marketplace Classified Advertising
76 Upcoming Events
76 Advertising Index
78 Key Concepts
In every issue
Trading Strategies14 Catching longer-term market swings
Buying sell-offs in the stock market provides an edge,
but it takes money, nerves, and persistence.
By Active Trader Staff
20 Gauging performance with the system matrix
How do you know if your trend-following system —
or trend-following CTA — is pulling its weight or
underperforming? Compare it to the benchmark
strategies in the “system matrix.”
By Thomas Stridsman
28 Trading trend transitions
Recognizing a few simple patterns can help you get
into new trends early.
By Dave Landry
34 Trading gaps with the most potential
Filtering for tradable up gaps with volatility and
volume.
By Chris Kacher & Gil Morales
40 Uncovering the covered call
A review of the most misunderstood and overused
strategy in the options business.
By Larry Shover
toc1210 10/13/10 8:06 AM Page 2
Advanced Strategies44 Not all carry trades are alike
More analysis of the consequences of free
money shows that in the battle between
Main Street and Wall Street, Wall Street
won.
By Howard L. Simons
Trading System Lab50 Profiting with stock splits
Trading splits can offer a longer-term edge
for stock traders.
By Robert Sucher Jr.
The Face of Trading 55 Finding a niche
This full-time stock trader relies solely on
technical analysis.
By Active Trader Staff
Trading Basics56 The subjectivity trap
Vague concepts and ambiguous guidelines
are impossible to translate into real-world
trading ideas. Start with market facts and
build from there.
By Active Trader Staff
4 www.activetradermag.com • December 2010 • ACTIVE TRADER
The Business of Trading60 Trader tax reporting strategies
Sort through the various trader tax forms
and review important strategies for your 2010
return.
By Robert A. Green, CPA
The Economy66 U.S. economic briefing
Updates on economic numbers and the
market’s reaction to them.
Trade Diary80 One bad trade is all it takes to ruin a day of
careful trading.
Contact Active Trader:Editorial inquiries: [email protected]
Comments, suggestions:[email protected]
For advertising or subscription information, log on to: www.activetradermag.com
Contents
toc1210 10/13/10 8:06 AM Page 4
For all subscriber services: Active Trader Magazine
P.O. Box 17015 N. Hollywood, CA 91615
•(800) 341-9384
•www.activetradermag.com
This Month’s
CONTRIBUTORS®
Editor-in-chief:
Mark Etzkorn
Managing editor:
Molly Goad
Contributing editor:
Howard L. Simons
Contributing writers:
Marc Chandler, Keith Schap,
Robert A. Green, Chris Peters
Editorial assistant and webmaster:
Kesha Green
President:
Phil Dorman
Publisher, ad sales:
Bob Dorman
Classified ad sales:
Mark Seger
6 www.activetradermag.com • December 2010 • ACTIVE TRADER
Howard Simons is president of Rosewood Trading Inc. and astrategist for Bianco Research. He writes and speaks frequently on awide range of economic and financial market issues.
Thomas Stridsman is a private trader, trading-strategy developer,and lecturer. Previously, he was the senior researcher for RotellaCapital in Chicago, and a systems-developer specialist for CQG inDenver. He also is a long-time contributing editor for Active Tradermagazine and a former editor at Futures magazine. He has authoredtwo books: Trading Systems that Work (McGraw-Hill, 2000) and TradingSystems and Money Management (McGraw-Hill, 2003). He has a degreein macroeconomics from Uppsala University, Sweden.
Larry Shover has been a firm and proprietary options trader formore than 25 years and taught courses at a variety of exchangesincluding the Chicago Mercantile Exchange (CME) for more than 20years. A large part of his career has been dedicated to developing hisown proprietary trading firm, and he has also served as director ofeducation, senior vice president of trading, and director of global trad-er development at several commodities and options firms. Shover is amember of the CME and the Chicago Board Options Exchange
(CBOE) and holds several Financial Industry Regulatory Authority (FINRA) licenses.He most recently published a book: Trading Options in Turbulent Markets(Bloomberg/Wiley).
Chris Kacher and Gil Morales are managing directors of MoKa Investors, LLC,and authors of the book Trade Like an O’Neil Disciple: How We Made 18,000 percent inthe Stock Market. They are also the authors of www.VirtueofSelfishInvesting.com.
Dave Landry has been actively trading the markets since the early90s. In 1995 he founded Sentive Trading, LLC (www.davelandry.com)— a trading and consulting firm. He is author of Dave Landry on SwingTrading (2000), Dave Landry’s 10 Best Swing Trading Patterns & Strategies(2003), and The Layman’s Guide to Trading Stocks (2010). His books havebeen translated into many languages including Russian, Italian, French,and Chinese (pending 2010). He has made several television appear-ances, has written articles for several publications including Active
Trader and Traders Journal-Singapore. He has been publishing daily web-based com-mentary on technical trading since 1997. He has spoken at trading conferences bothnationally and internationally. He holds a bachelor’s in computer science and has anMBA.
Robert Sucher holds a M.S.E.E. in signal processing from C.S.U. Northridge(1992). After working 12 years in the military aircraft industry, he moved to theCanary Islands (Spain) where he began actively trading stocks and futures in 1999. In2002, he started an ongoing journey with Wealth-Lab.com, assisting customers withtrading tools and solutions.
Robert A. Green, CPA, is CEO of Green & Company(GreenTraderTax.com), a CPA firm focused on traders and investment-management businesses. Green is also founder and CEO of theGreenTraderTax Traders Association. He is the author of The Tax Guidefor Traders (McGraw-Hill, 2004) and Green’s 2010 Trader Tax Guide.GreenTrader provides tax preparation, accounting, consulting, entity,and retirement-plan formation services; IRS/state tax exam representa-tion; and trade-accounting software. For more information or to par-
ticipate in free conference calls, visit www.greencompany.com or call (877) 662-2014or (646) 216-8061.
Jim Kharouf is editor of Environmental Markets Newsletter and a freelancereporter who has covered the derivatives markets since 1996.
Volume 11, Issue 12 Active Trader is published month-ly by TechInfo, Inc., PO Box 487, Lake Zurich, IL60047-0487. Copyright © 2010 TechInfo, Inc. All rightsreserved. Information in this publication may not bestored or reproduced in any form without written per-mission from the publisher. Annual subscription rate is$59.40.
The information in Active Trader magazine is intendedfor educational purposes only. It is not meant to rec-ommend, promote or in any way imply the effective-ness of any trading system, strategy or approach.Traders are advised to do their own research and test-ing to determine the validity of a trading idea. Tradingand investing carry a high level of risk. Past perform-ance does not guarantee future results.
contributors1210 10/14/10 12:13 PM Page 6
OPENING Trades
8 www.activetradermag.com • December 2010 • ACTIVE TRADER
In late September and early October,
U.S. equities pushed decisively out
of the roughly four-month consoli-
dation that followed the early 2010
sell-off. The S&P 500 (SPX) punc-
tured the resistance represented by
the June and August highs around
1130 and, having reached 1180 by
Oct. 3, had no remaining chart bar-
rier between it and the April high
around 1220. The upside breakout
was aided by mostly positive earn-
ings announcements as the Q2
reporting period got underway.
The move padded the year’s gains
for the major U.S. indices, some of
which, after spending much of the
year underwater or barely afloat,
pushed into double-digit territory.
By Oct. 13 the Russell 2000 index of
small-cap stocks was up more than
13 percent, the Nasdaq 100 was up
nearly 11 percent, and the Dow and S&P 500 were up around 6
and 7 percent, respectively.
Meanwhile, the CBOE volatility index (VIX) dropped below
18 by Oct. 13, the lowest it had been since the April high.
Despite the recent rally and the continued growth in high-fre-
quency trading, volume continued to sag: The week ending Oct.
15 was the 14th consecutive week with S&P 500 volume below
the 52-week median.�
U.S. stocks break out of range
Bullish September carries over into mid-October as earnings seasons begins.
Treasuries rocket into OctoberDecember 10-year T-note futures (TYZ10) traded up to 127-22/32 on
Oct. 12 — more than four full points above the September pullback low, and
approaching levels not seen since the depths of the 2008 financial panic when
T-note prices briefly topped
130. Yields on the 10-year
Treasuries dipped below
2.4 percent.
Dollar poised to challenge 2009 lowsIn mid-October the U.S.
dollar index (DXY) closed
at its lowest level in nearly
a year, extending the sell-
off that began in June and
setting itself up for a challenge to last year’s bottom below 75.00.
opening_trades1210 10/18/10 8:06 AM Page 8
ACTIVE TRADER • December 2010 • www.activetradermag.com 9
Commodity indices challenge 2010 highsCommodity futures rallied close to their highest levels of the year, driven by
blistering moves in a handful of markets. The Deutsche Bank Liquid
Commodity Index (DBL-
CIX) hurdled above its
spring highs in October,
marking its seventh con-
secutive week of higher
highs and higher closes
as of Oct. 15.
Besides big runs in
metals, especially silver
(see “Gold’s golden run,” p. 10), continued strength in grain markets and
select soft commodities spurred commodities higher as a group. In grains,
corn (C) continued to assert its domi-
nance over former front-runner wheat
(W), while soybeans (S), which had
lagged the other two markets much of the
year, made a push of their own.
The rally in December coffee futures
(KC) would have been eye-catching
despite their pullback from highs just
below 200, but sugar’s continued recovery
from the massive sell-off that ended in the
spring has grabbed most of the attention
in the softs. As of Oct. 13, December
sugar (SBZ10) had jumped nearly 56 per-
cent from its August low close — and
more than 100 percent since June.
Cotton remained kingly into mid-
October, tricking many traders who bet
the end-of-September sell-off was the bull
move’s death-knell. After dipping below
100, however, December cotton (CTZ10)
leaped above 110, reaching 114 by
Oct. 14 — more than 52 percent above
July levels. �
BBaarrccllaayy TTrraaddiinngg GGrroouupp’’ss mmaannaaggeedd ffuuttuurreess ppeerrffoorrmmaannccee aass ooff AAuugg.. 3311
TToopp 1100 ttrraaddeerrss mmaannaaggiinngg mmoorree tthhaann $$1100 mmiilllliioonn
AAuugg.. 22001100 YYTTDD $$ UUnnddeerr
TTrraaddiinngg aaddvviissoorr rreettuurrnn rreettuurrnn mmggmmtt..
1. Clarke Cap’l Mgmt. (Gl. Basic) 24.46% 7.90% 19.0
2. Clarke Cap’l Mgmt. (Millennium) 17.27% 5.54% 29.3
3. DUNN Capital Mgmt. (WMA) 16.96% 21.04% 254.0
4. Clarke Cap’l Mgmt. (Gl. Magnum) 16.56% 26.65% 17.9
5. Commodity Fut. Services (IPATS) 16.00% 33.23% 21.4
6. Mulvaney Capital Mgmt. (Gl. Markets) 14.59% -20.12% 115.0
7. Global Ag 13.07% 36.50% 42.0
8. Superfund Trading Mgmt (Gold C) 12.30% -12.58% 65.2
9. Quicksilver Trading, Inc. 11.78% 3.38% 211.7
10. Brummer & Partners (Lynx) 10.38% 14.47% 2267.1
TToopp 1100 ttrraaddeerrss mmaannaaggiinngg lleessss tthhaann $$1100 mmiilllliioonn aanndd aatt lleeaasstt $$11 mmiilllliioonn
1. Clarke Cap’l Mgmt. (Jupiter) 21.26% 11.15% 9.0
2. Persistent Cap Mgmt (Perseverance 2X) 19.46% 1.98% 2.9
3. Clarke Cap’l Mgmt. (FX-Plus) 14.73% 35.06% 4.0
4. Valu-Trac Invest. Mgmt (Strat. 2.5) 14.28% 3.45% 1.9
5. Clarke Cap’l Mgmt. (Orion) 13.27% 11.03% 2.0
6. Persistent Cap Mgmt (Perseverance) 10.00% 1.94% 4.2
7. IMFC (Multi-Strategy) 9.60% 3.86% 4.1
8. Vermillion Asset Mgmt (Indigo) 9.53% -1.49% 9.0
9. Pardo Capital Ltd. (XT99 Divers.) 9.50% 25.60% 7.6
10. Bayside Pacific Advisors (Futures) 9.42% 7.17% 1.1
Based on estimates of the composite of all accounts or the fully funded subset method. Does not reflect theperformance of any single account. PAST RESULTS ARE NOT NECESSARILY INDICATIVE OF FUTURE PERFOR-MANCE. Source: Barclay Hedge (www.barclayhedge.com)
opening_trades1210 10/18/10 8:06 AM Page 9
Opening Trades
10 www.activetradermag.com • December 2010 • ACTIVE TRADER
Gold topped $1,300/ounce for the first time in its history in late
September after a nearly uninterrupted two-month/13-percent
rally took the metal well past its December 2009 and June 2010
record highs. As of Oct. 15, gold futures had strung together 11
consecutive weeks of higher highs, and 10 out of 11 higher clos-
es (Figure 1).
December gold futures (GCZ10) hit an intraday high of
$1,388 on Oct. 14, eclipsing the June high by approximately
$120. As of Oct. 15, the run of 11 higher weekly highs had
been equaled or exceeded just two other times over the past 31
years, with all instances occurring during the current gold bull
market or at the end of the last gold explosion in 1979-1980, as
shown in Table 1. Twenty-three years separated the 10-week run
ending the week of Jan. 25, 1980 (that bull market’s all-time
high) and the first 10-week run of the current bull in February
2003.
One of the more interesting but overlooked aspects of the
current gold bull is that over the past several months, as well as
over most of the past decade, gold has failed to keep pace with
silver on a percentage basis, and trails copper by an even wider
margin. The Oct. 14 high marked a 400-percent increase from
the December 2001 gold futures closing price of $277 — a
major rally, certainly, but less than silver’s 459-percent gain over
the same period, and much less than the 472-percent jump in
copper, which was trading around 68 cents/pound in December
2001 and in mid-October was around $3.85/pound. (Also,
crude oil gained 365 percent between December 2001 and early
October 2010 — and that was after a more than 50-percent sell-
off from its 2008 bubble peak, at which point it had gained 731
percent in less than seven years.)
More recently, the December gold and copper futures con-
tracts both gained a little more than 17 percent from their July
28 closes and their early October highs, while December silver
gained more than 50 percent.
More room on the upside?Each new gold high has brought out more gold bugs calling for
$2,000 (or $3,000) gold, as well as more market watchers warn-
ing of a collapse in the market. “The market with the golden
arm” (Active Trader, February 2010) noted that gold rallied more
than 420 percent on a closing basis from 1974 to the beginning
TABLE 1: 10 WEEKS OF HIGHER HIGHS
Week ending
No. consecutive weekly highs
Oct. 15, 2010 11
Nov. 9, 2007 11
Feb. 7, 2003 10
Jan. 25, 1980 10
July 27, 1979 14
Gold futures have put together runs of 10 or more
consecutive higher weekly highs just five times over the
past three decades.
Gold’s golden runMetal reaches for $1400 in mid-October; $1500 now in sights.
Gold (top) established another milestone in September,
but silver (middle) and copper have outgained it during
the recent rally.
FIGURE 1: PEDALS TO THE METALS
““ The bubble is in money-printing,
not in gold.””
— Howard Simons, president of Rosewood Trading
continued on p. 12
opening_trades1210 10/18/10 8:06 AM Page 10
Opening Trades
12 www.activetradermag.com • December 2010 • ACTIVE TRADER
BY JIM KHAROUF
Chicago Board Options Exchange announced it will launch its
second options market, the C2 Options Exchange in late
October. The new exchange will use a form of the “maker-taker”
pricing model designed to compete with other options
exchanges, such as NYSE Arca, the Nasdaq Options Market, and
BATS Options Exchange, that use a similar pricing structure.
Other exchanges have also adopted maker-taker models at vari-
ous levels, including the International Securities Exchange (ISE)
and the Boston Options Exchange (BOX). The maker-taker pric-
ing model, first introduced in the equity markets, give rebates to
those who provide liquidity to the exchange and charges cus-
tomers who take liquidity from it.
CBOE president and chief operating officer Ed Joyce says the
new electronic market is designed to be complementary to the
CBOE, which offers a traditional pro-rata pricing model.
“It provides CBOE with more flexibility by offering customers
different market models and different choices,” Joyce says. “It
expands the menu and complements what we do.”
Joyce says the new exchange, which operates separately from
CBOE, will start slowly by offering a few multiple-listed names
and expand from there. C2 may also offer the CBOE’s exclusive
anchor contract, S&P 500 options, although Joyce says “we will
be very careful how we roll that out.”
Maker-taker pricing models are considered more user-friendly
to high-speed, high-frequency traders looking for the best prices
across multiple markets, and who are responsible for an increas-
ingly large portion of volume.
“You need the right systems and the right price,” Joyce says.
“We’re adding another line on our menu for that business we’re
not getting a shot at right now.”
The CBOE has reason to address the ongoing competition
from maker-taker pricing models. The CBOE’s option market
share in August was 30 percent, down from 32.4 percent a year
earlier. Chief rival ISE, which is still largely a traditional pro-rata
pricing model, has watched its market share erode to 18.2 per-
cent in August, down from 27.3 percent a year earlier.
Meanwhile, maker-taker options market NYSE Arca watched
its market share rise to 11.6 percent from 10.9 percent, and the
Nasdaq Options Exchange increased its share from 3.25 to 4.61
percent.
The CBOE has not provided the details of its maker-taker
pricing, but sources say it will likely be a mix of traditional pro-
rata pricing and maker-taker.
“Overall, CBOE is looking at C2 as almost a hedge on maker-
taker,” says Paul Zubulake, senior analyst, futures and options,
at Aite Group. “They want to keep their customer priority model
in place but they also want to pay for order flow. So it’s not just
a pure, cut-and-dried maker-taker model going forward.”
Some market participants see potential for C2 going forward,
especially for firms and customers looking for platforms that fea-
ture speed and a pricing structure that suits their trading styles.
“C2 looks interesting to us,” says Jeff Wecker, president and
CEO of Lime Brokerage, which specializes in high-frequency
trading and broke into the options brokerage business in
September with the launch of a low-latency service. “It’s the kind
of market active traders like. And it has the model that would
attract the kind of traders we tend to work most closely with —
high-volume, black-box, and gray-box traders.” �
CBOE looks to double upExchange launches new trading centering catering to high-frequency sector.
of 1980. On an inflation-adjusted basis, it’s still valued well
below its 1980 high of $850 — roughly $2,230 in today’s dol-
lars when adjusted with the Consumer Price Index (CPI).
Howard Simons, president of Rosewood Trading and Active
Trader contributing editor, argues those using the word “bubble”
to describe the gold market are off base, but not for the reason
you might expect. There is, he says, a very simple fuel driving
the market: The extraordinary steps many countries, including
the U.S., continue to take in their efforts to jolt life into their
still-struggling economies — specifically, slashing interest rates
and engaging in so-called “quantitative easing” programs.
“As central banks around the world try to reflate by printing
paper money without a link to underlying economic value-
added, the value of that paper is zero,” he says. “Gold is not ris-
ing — paper is falling. This is not — I repeat, not — a bubble
so long as money is being printed. The bubble is in money-
printing, not in gold.”
Which means the question looming for gold traders is, when
will the money presses be switched off? �
GOLD continued from p. 10
opening_trades1210 10/18/10 8:07 AM Page 12
The U.S. stock market’s direc-
tionless, volatile trajectory
in much of the second half
of 2010 has been a wash for
trend followers and buy-and-hold
investors — the market ulti-
mately went nowhere between
May and early October — and
it has likely been challenging for
shorter-term traders of all
stripes.
The gyrations that have dominated the
market recently have typically lasted between
two and six weeks, falling somewhere between swing-trading
and position-holding time frames. Sharp sell-offs (aside from the
anomalous May 6 flash crash) have been followed by rela-
tively brisk rallies, scaring many traders as the market tested
supported and cheating the hope of bulls as it reached resist-
ance (Figure 1, p. 16). Riding these waves is easier said than
done, but let’s see if we can model this price action in fairly sim-
ple terms and test it historically. For example, the late-August
low would have, with hindsight, been an excellent buying
opportunity. How could you have identified it proactively?
Pattern experimentationThere are many ways to define the
price action that preceded this bot-
tom, but let’s begin with two broad
characterizations: In late August
the market reached its lowest
level in more than 20 days
and it suffered a sharp decline
over the preceding one to two
weeks. At a glance, the early July
bottom appears to have had similar qualities.
Studying similar patterns in the S&P 500
ETF (SPY) led to the following general descrip-
tion, which will be referred to as Pattern 1:
1. Today’s low is lower than the previous 15 lows.
2. Price has dropped at least 5 percent from the highest high
of six to eight days ago to today’s low.
Although this definition is extremely basic, it is also objective
and specific — a good starting point for the analysis.
Not surprisingly, Pattern 1 formed relatively frequently. From
Jan. 1, 2000, through Oct. 4, 2010, there were 213 instances; in
BY ACTIVE TRADER STAFF
Buying sell-offs in the stock market provides an edge,
but it takes money, nerves, and persistence.
14 www.activetradermag.com • December 2010 • ACTIVE TRADER
TRADING Strategies
Catching longer-term market swings
continued on p. 16
etzkorn1210.qxd 10/12/10 1:15 PM Page 14
Trading Strategies
many cases, several consecutive days fulfilled the pattern crite-
ria, which means multiple “patterns” were often signaled within
a single, larger down move (in other words, the pattern often
signaled several times before the market bottomed). For exam-
ple, Pattern 1 signaled completion not just on Feb. 5, 2010 (the
conspicuous spike low), but also on Jan. 22, Jan. 26, Jan. 27.
Jan 28, and Jan. 29, while the market pushed lower and lower.
Table 1 shows SPY’s gains or losses one, two, five, 10, 15, 20,
25, 30, 35, and 40 days after the pattern’s conclusion, measured
from the close of the final bar of the pattern to the closes at each
interval. The results are positive — both the median and average
moves at each interval are above zero (the averages are smaller
than the medians, reflecting the influence of a smaller number of
large losers) — but the high standard deviations and relatively
modest winning percentages indicate the post-pattern market
performance is rather volatile. The median and average gains,
total point gain/loss, and probability of gains peak 20 to 35 days
(between one and two months) after the pattern’s conclusion.
To potentially remove some of the pat-
tern’s early and repetitive signals, a third
criterion was added that required the
market to make a relatively large down
move on the final day of the pattern:
1. Today’s low is lower than the previ-
ous 15 lows.
2. Price has dropped at least 5 percent
from the highest high of six to eight
days ago to today’s low.
3. Today’s low is at least 1 percent
lower than yesterday’s close.
While observation of several patterns
suggested this might be a distinguishing
characteristic of more-successful exam-
ples, the change didn’t amount to much.
The number of signals declined only by
17 percent (to 177), but Table 2 shows
Pattern 2’s performance was very similar
to Pattern 1’s.
Studying the relationships between the
price bars within the original pattern led
the analysis in a different direction.
Pattern analysis often incorporates the
16 www.activetradermag.com • December 2010 • ACTIVE TRADER
TABLE 1: PATTERN 1
213 1 2 5 10 15 20 25 30 35 40
Median 0.45 0.69 0.65 0.52 1.03 1.46 2.48 2.82 2.25 2.01
Average 0.28 0.50 0.63 0.22 0.18 0.88 0.86 0.80 1.04 0.91
Total 60.49 107.07 134.83 46.03 38.36 186.90 183.60 170.11 218.31 189.55
StD 2.48 3.25 4.33 5.12 6.96 8.19 8.85 9.69 9.80 10.04
Max 12.85 11.35 14.64 12.48 14.31 18.85 17.01 18.28 17.86 21.96
Min -8.75 -10.31 -21.84 -17.13 -29.37 -34.81 -35.92 -36.14 -37.38 -34.65
Win % 56.34% 58.69% 56.34% 53.99% 57.28% 59.62% 60.56% 61.79% 60.95% 57.89%
Pattern 1's median price moves are positive at all intervals, but the high standard deviations and relatively modest winning
percentages indicate the post-pattern market performance is volatile.
FIGURE 1: WIDE-RANGING SWINGS
The market’s recent swings, here represented by the S&P 500 tracking stock
(SPY), have lasted roughly between two and six weeks. Buying into the
market’s sharp sell-offs can be difficult to do, especially when volatility and
uncertainty are high.
etzkorn1210.qxd 10/12/10 1:16 PM Page 16
ACTIVE TRADER • December 2010 • www.activetradermag.com 17
changes from one bar to the next or the number of consecutive
price milestones over a certain period — for example, a series of
consecutive lower lows, highs, or closes. However, such bar-to-
bar comparisons can be restrictive, especially when analyzing
longer time periods. Instead, Pattern 3’s new rule compares each
day’s low to the low two days ago:
1. Today’s low is lower than the previous 15 lows.
2. Price has dropped at least 5 percent from the highest high
of six to eight days ago to today’s low.
3. Today’s low is the ninth consecutive low that is lower than
the low two days earlier.
This time the change was more significant, as shown in Table
3. The number of signals was more than cut in half, to 100, the
median/average gain at most intervals increased (especially at
days 30 and 35), and the winning percentage was above 60 per-
cent for all intervals. Thirty-five days after pattern conclusion,
the median gain at the close was 3.50 points — 50-percent more
than Pattern 1, with the close being higher than the closing
price of the last day of the pattern nearly 69 percent of the time.
The pattern vs. the marketBefore analyzing the three pattern variations in greater detail,
let’s look at what the market did overall during the January
2000-October 2010 analysis period. SPY closed at 146.88 on
Dec. 31, 1999 and closed at 113.53 on Oct. 4, 2010, a decline
of 22.71 percent, although the market twice pushed to record
highs during that time span.
Figure 2 (p. 18) shows the analysis period began a few
months before the peak in the bull market that began in the
1990s. The 10 years and 10 months that followed were domi-
nated by the bull market that began in late-2002 or early 2003
(pick your bottom), and book-ended by the 2000-2002 bear
market and the 2008-2009 financial collapse. As of Oct. 4,
2010, the market was trading around 2004 levels after having
fallen to 1996 levels in March 2009. The horizontal line marks
the closing price on Dec. 31, 1999 — relatively close to the
highs SPY set in 2000 and 2007.
Figure 3 (p. 18) shows the median performance after the
three patterns, along with the median and average values for all
moves of the same size (one to 40 days) in the analysis period
continued on p. 18
TABLE 2: PATTERN 2
177 1 2 5 10 15 20 25 30 35 40
Median 0.17 0.47 0.63 0.65 1.21 1.89 2.90 2.48 2.25 2.01
Average 0.19 0.42 0.63 0.32 0.16 0.94 0.81 0.45 0.83 0.82
Total 33.58 75.08 111.58 56.77 27.68 165.95 143.61 78.79 143.69 141.08
StD 2.63 3.43 4.59 5.40 7.34 8.67 9.38 10.27 10.37 10.58
Max 12.85 11.35 14.64 12.48 14.31 18.85 17.01 18.28 17.86 21.96
Min -8.75 -10.31 -21.84 -17.13 -29.37 -34.81 -35.92 -36.14 -37.38 -34.65
Win % 52.54% 57.63% 55.37% 54.24% 58.19% 61.02% 61.58% 59.89% 58.19% 58.19%
The additional rule didn’t significantly alter the results from Pattern 1.
TABLE 3: PATTERN 3
100 1 2 5 10 15 20 25 30 35 40
Median 0.72 0.89 1.25 1.09 1.68 1.73 2.83 3.11 3.50 2.32
Average 0.38 0.70 0.69 0.39 0.26 0.87 1.35 1.09 1.68 1.31
Total 38.25 70.01 69.36 39.33 25.55 87.38 135.31 107.49 166.73 129.31
StD 2.26 3.13 4.21 5.04 7.21 8.23 8.54 9.76 9.04 10.14
Max 5.51 10.65 7.47 11.56 14.31 18.85 17.01 18.28 17.86 21.96
Min -6.05 -10.31 -21.84 -17.13 -23.30 -27.43 -26.24 -36.14 -30.82 -32.33
Win % 62.00% 61.00% 63.00% 61.00% 62.00% 61.00% 62.00% 65.66% 68.69% 60.61%
Requiring nine consecutive lows that are lower than the lows two days earlier dramatically reduced the number of trades,
boosted the typical gain, and increased the winning percentages.
etzkorn1210.qxd 10/12/10 1:16 PM Page 17
Trading Strategies
(dashed lines). While SPY’s overall median
moves are slightly positive, the average
moves are slightly negative, reflecting the
large, concentrated losses that occurred
during the two bear phases. Pattern 3 had
the largest median gains at most intervals,
especially at days 30, 35, and 40, but all
three patterns outperformed the market by
a wide margin.
Figure 4 compares winning percent-
ages — i.e., the percentage of times the
market closed higher than the close of a
pattern’s last day. Again, Pattern 3 had the
best performance, especially at the short-
est and longest intervals. As was the case
with the median gains, the winning per-
centages of all three-pattern variations
converge around days 20 to 25. The
dashed line shows the winning percentage
for the overall market during the analysis
period.
Reality checkThe relatively small differences between
the pattern’s winning percentages and the
market overall in Figure 4 is a reminder of
the stock market’s inherent bullish bias.
Even during a period containing the two
most severe bear moves of a generation,
the odds of a higher close at any of the
given intervals was never less than 52 per-
cent. The market’s total loss during the
past decade is simply a function of a
minority of large losses overwhelming a
majority of gains. From this perspective,
only Pattern 3 shows a dramatic improve-
ment over the market’s tendency to close
higher at any of the given intervals.
Figure 5 offers one more necessary
glimpse into the reality of trading this kind
of pattern. This chart shows equity curves
for the three patterns based on an initial
account size of $25,000 and buying
$25,000 worth of SPY at each trade signal
18 www.activetradermag.com • December 2010 • ACTIVE TRADER
FIGURE 3: PATTERN PERFORMANCE — MEDIAN GAINS
Pattern 3 had the best returns of the three pattern variations, all of which
outperformed the market.
FIGURE 2: ANALYSIS PERIOD
The period over which the pattern will be analyzed encompasses the era’s
two major bear markets, but also a multi-year uptrend. Between Dec. 31,
1999 and Oct. 4, 2010, SPY declined approximately 22 percent, despite
twice establishing record highs.
etzkorn1210.qxd 10/12/10 1:16 PM Page 18
(representing an average trade size of
approximately 210 shares). For Pattern 1
and Pattern 3, trades were exited on the
close 35 days after entry; for Pattern 2,
after 20 days. These holding periods were
selected based on the most-favorable total
profit and winning percentage figures from
Tables 1, 2, and 3. The black line toward
the bottom of the chart represents a buy-
and-hold position in SPY.
Pattern 1 had the highest ending profit,
but this is a function of it signaling more
trades than Patterns 2 or 3 (twice as many
as Pattern 3, as mentioned). All the pat-
terns outperformed buy-and-hold by a
wide margin, but this is not more impor-
tant than the risk a trader would have
been subjected to: The drawdowns during
the 2000-2002 bear market and 2008-
2009 were huge — in some cases, worse
than the overall market.
Interestingly, all three patterns carried
equity highs into early September 2008,
but they completely fell apart as the market
collapsed in October. Pattern 1’s drawdown
reached 65 percent by February 2009 —
much more than the S&P 500’s decline —
while Pattern 2 lost 54 percent. Pattern 3
suffered the least damage, declining “only”
48 percent.
A once-in-a-lifetime market event, you
say? Not for Patterns 1 and 2, which lost
even more on a percentage basis in 2002.
Only Pattern 3 managed to avoid the
calamity of the decade’s first bear market,
losing around 22 percent in 2001 (a little
less than $9,000) before treading water
through the worst of the bear move.
Figure 6 (p. 72) shows Figure 1’s price
action but highlights each pattern varia-
tion’s entry signals. Pattern 3 signaled at
the February, July, and August lows, plus
ACTIVE TRADER • December 2010 • www.activetradermag.com 19
continued on p. 72
FIGURE 5: EQUITY CURVE COMPARISON
Pattern 1 had the highest ending profit, but it was also the riskiest of the
patterns, losing more than 60 percent during the 2000-2002 and 2008-
2009 market drops. Pattern 3 had the best risk-adjusted performance.
FIGURE 4: WINNING PERCENTAGE
This chart shows the percentage of times SPY closed above the closing
price of the last day of the pattern. Pattern 3 had the best performance,
especially at the shortest and longest intervals.
etzkorn1210.qxd 10/12/10 1:16 PM Page 19
Even though all trend-following systems have the same
purpose — cut losses short and let profits run — the
results between systems can vary significantly over
shorter time periods. Differences in excess of 3 to 5
percent over any three- to 12-month period are not uncommon
among systems applied to the same markets.
This is mostly a result of the different distances between entry
and exit points from system to system. For example, if trend-fol-
lowing systems A and B usually enter at the same price, but sys-
tem A has a tighter stop than system B, then system A is likely
to marginally outperform B in the short term if the market goes
against both systems immediately. System A might also do better
in very steady, long-term trends because it will both enter and
exit trades before system B.
However, in the intermediate-term, and in more volatile mar-
ket conditions, system B will likely perform better because it
will avoid getting stopped out time and time again. (In this case,
even a relatively large loss might be preferable to several smaller
ones.) In those instances when the market takes off after having
produced a short-term loss for system A, system A will fall
behind system B not only in terms of the initial loss, but also in
how far it needs price to move before it can enter the market
again.
Other factors that can make a difference between systems
include trade frequency, position (trade) sizing, and asymmetric
rules for the long and short sides of the market.
If you plan on developing or trading a trend-following system
yourself, or if you are interested in investing with a trend-fol-
lowing commodity trading advisor (CTA), it would be immense-
ly helpful to be able to compare performance with that of cer-
tain benchmark systems. This trend-following system analysis
may also help you discover one or two secrets of the profession-
als, or perhaps provide ideas for your own strategies.
The systemsTo get a feel for what works when, we will track and analyze six
trend-following systems:
System 1: A two-standard deviation volatility breakout with a
moving-average trailing stop.
System 2: A 1.5-standard deviation volatility stop-and-reverse
breakout.
System 3: A highest-high/lowest-low (HH/LL) breakout, with
a center-line trailing stop.
System 4: A highest-high/lowest-low (HH/LL) stop-and-
reverse breakout.
System 5: A constant-period average true range (ATR) break-
out, with a median stop.
BY THOMAS STRIDSMAN
How do you know if your trend-following system — or trend-following
CTA — is pulling its weight or underperforming?
Compare it to the benchmark strategies in the system matrix.
20 www.activetradermag.com •• December 2010 •• ACTIVE TRADER
TRADING Strategies
Gauging performance with the system matrix
continued on p. 22
KC Go to “Key concepts” on p. 78
for more information about:
• Compounded Annual
Geometric Return (CAGR)
• Stop-and-reverse (SAR)
stridsman1210.qxd 10/8/10 2:26 PM Page 20
Trading Strategies
System 6: A constant-period ATR stop-and-reverse breakout.
(For more information about using the center line and medi-
an, see “Baseline primer.”)
Five versions (short term to long term) of each system will be
tracked, for a total of 30 system variations.
System parametersThere are three basic systems (1-2, 3-4, 5-6), each traded with
and without trailing stops and using different look-back periods.
The look-back periods for the volatility breakout and HH/LL
breakout systems using trailing stops (systems 1 and 3) will be
30, 60, 120, and 240 days. The look-back periods for the
volatility and the HH/LL stop-and-reverse systems (systems 2
and 4) will be 20, 40, 80, and 160 days.
The two volatility breakout systems maintain constant volatili-
ty multipliers of two and 1.5 standard deviations, respectively.
The ATR systems use constant look-back periods of 240 and 80
days, respectively. Instead of varying their look-back periods,
they vary their ATR multipliers in steps of 0.75, 1.5, three and
six ATRs. (All parameter settings were decided more or less arbi-
trarily to create similar long-term performance data and trades.)
The longest-term versions of all the systems were also tested
with a twice-monthly rebalancing (every 10 days) of all open
positions, to reset each trade’s risk as it was at the start of the
trade. This modification approximately triples the trade frequen-
cy. Regular rebalancing also shortens the average time in the
market per contract traded, and gives the system a shorter-term
character.
Test settingsWe conducted tests to see how the systems performed in the
recent past, especially this year. The amount of account equity
risked per trade for each system in 2010 was based on a back-
test on historical data from January 1990 through December
2009. The position size was set in such a way that the back-test-
ed average Compounded Annual Geometric Return (CAGR)
came as close as possible above 16 percent, net of trading costs,
management fees, and earned interest on account equity. Also,
the position size in any market could not surpass 25 percent of
the most recent average daily volume.
The initial account equity for all systems was set to $10 mil-
lion. As of December 2009, all systems had an account balance
of approximately $200 million. This is a reasonable total equity
for most trend-following CTAs to handle efficiently, so this will
also be the amount we assume is in the accounts as we conduct
quarterly analysis. As an example of the historical back-tested
performance, Figure 1 shows the equity growth of system 2,
which has performed the best so far this year.
22 www.activetradermag.com • December 2010 • ACTIVE TRADER
FIGURE 1: SYSTEM 2 EQUITY CURVE
System 2 had the best performance in 2010 as of August.
stridsman1210.qxd 10/8/10 2:34 PM Page 22
ACTIVE TRADER • December 2010 • www.activetradermag.com 23
Because slippage is a function of both
volatility and volume, shorter-term systems
and the ones with the tightest stops will have
the most slippage. Most systems will suffer
around $30 per round-turn trade because of
volatility. The the most expensive systems in
terms of estimated slippage will suffer in
excess of $20 slippage because of traded vol-
ume, while this will only affect the cheaper
ones by a few bucks. For all systems the aver-
age slippage comes out to three to five ticks
per contract traded. Slippage was also deduct-
ed for rollovers, as well as for any eventual
position-size adjustments. Commissions were
set to $5 per round turn, and were also
deducted for rollovers and position-size
adjustments.
To make comparison easier to CTA perform-
ance, the management fee was set to 1 percent
per year, deducted monthly. The incentive fee
was deducted at the end of each quarter that
ended higher than the previous highest-ending
quarter. The fee is 20 percent of the difference
between said quarters. The systems also earn a
small interest payment each day, based on the
90-day T-bill rate.
The marketsThe test portfolio contains 49 markets in seven
sectors:
CCuurrrreenncciieess:: Australian dollar, British pound,
Canadian dollar, Euro, Japanese yen,
Mexican peso, Swiss franc.
IInntteerreesstt rraatteess:: Canadian 10-year bond, Euro
German bund, Long gilt (British), Japanese
10-year bond, American 10-year T-note,
American 30-year bond, Australian 10-year
bond.
SSttoocckk iinnddiicceess:: S&P 400 Midcap, CAC 40
(France), DAX (Germany), FTSE 100
(Britain), Hang Seng (Hong Kong), Nikkei
225 (Japan), E-Mini Russell 2000.
EEnneerrggiieess:: crude oil, heating oil, Brent crude
oil, gas oil, natural gas, gasoline, EUA emis-
sion rights.
MMeettaallss:: gold, copper, aluminum (LME for-
ward), nickel (LME forward), palladium,
platinum, silver.
GGrraaiinnss:: wheat (CBOT), soybean oil, corn,
wheat (KCBT), rough rice, soybeans, soy-continued on p. 24
Baseline primerA baseline represents the best estimate of the current “equilibrium” price,
around which price should (theoretically) fluctuate. The most common
example is the moving average, but others include the center, median,
and mode.
1. Center: The center line is the midpoint of the high-low range in a look-
back period: (HighestHigh+LowestLow)/2. In most cases, the center-line
price will only be implied, and not used as an input in other calcula-
tions.
2. Median: The median is the middle value of all values in the look-back
period — half the values are above the median and the other half are
below it. If there is an even number of values, the median is the aver-
age of the middle two.
3. Mode: The mode is the most frequently occurring value in a sample of
values. For example, in the group of prices 12, 10, 12, 29, 47, 33, 25,
16, 47, 12, and 20, the mode is 12. When dealing with price data, it is
more useful to estimate the mode using the following formula:
Estimated mode = (3*median) – (2*mean)
This formula is derived from another formula that describes the relationship
between the mean, median, and mode for any skewed distribution:
Mean – mode = 3*(mean – median)
In our data sample, the estimated mode would be 12.18, which is very
close to the actual, observed mode. Figure A shows examples of the differ-
ent baseline calculations.
FIGURE A: SAMPLE BASELINES
Day Price Prices (sorted low to high)
1 12 102 10 123 12 124 29 125 47 166 33 207 25 258 16 299 47 33
10 12 4711 20 47Average: 23.90Median: 20Center: 28.5Actual mode: 12Estimated mode: 12.18
The average is
the most com-
monly used
baseline price,
but the medi-
an, center, and
mode prices all
provide addi-
tional informa-
tion about
price action
and can be
used in trading
indicators and
systems.
stridsman1210.qxd 10/8/10 2:34 PM Page 23
Trading Strategies
bean meal.
MMeeaattss aanndd ssooffttss: feeder cattle, live cattle, lean hogs, coffee,
lumber, orange juice, sugar.
Performance analysisTable 1’s system matrix shows the short-term systems have per-
formed best in 2010 overall, and also during the last three
months of the test (through July). For example, the average
return for the short-term systems for the three months ending
July was +5.65 percent, while the longer term systems lost in
excess of -13 percent over the same period (far-right column).
The same holds true for most of the systems that go flat
(those with trailing stops — systems 1, 3, and 5) rather than
automatically reversing position (systems 2, 4, and 6). This indi-
cates one of two things: Either the markets have been very
trendy, or they have been very choppy. As the negative perform-
ance of most systems indicates, the markets have been choppy
enough that even the long-term systems using the widest stops
have gotten whipsawed.
In short, mastering market volatility — as opposed to catch-
ing trends — has been the key issue over the past year. This is
indicated by the relatively small losses suffered by the volatility
breakout systems (1 and 2) relative to the larger losses of the
two ATR systems (5 and 6). Thus, the systems that have per-
formed the best are the ones with short look-back periods and a
high sensitivity to volatility. This makes sense because the more
frequently a system trades, the more precise its position sizing
will be over the lifetime of a trade, which should result in better
24 www.activetradermag.com • December 2010 • ACTIVE TRADER
TABLE 1: SYSTEM MATRIX
System 1 System 2 System 3 System 4 System 5 System 6
2-StD breakout w/mean stop
1.5-StD breakoutreversal
HH/LL breakout w/center stop
HH/LL breakout reversal
240-day ATRbreakout w/median stop
80-day ATR breakout
reversal
Avg. per-tradereturn & risk, all systems
Look-back (days) 30 20 30 20 0,75 ATR 0,75 ATR
Risk / trade 0.25 0.3 0.35 0.5 0.15 0.25 0.3
Return, 09 -21.2 -16.6 -29.8 -13.2 0.4 -14 -15.73
Return, YTD 7.6 11.9 5.9 -1.6 -16.6 -9.7 -0.42
Return, 3 months 14.38 18.2 12.19 11.96 -18.82 -4.01 5.65
Look-back (days) 60 40 60 40 1,5 ATR 1,5 ATR
Risk / trade 0.45 0.5 0.5 1.2 0.25 0.45 0.56
Return, 2009 -13.2 -14.9 -4.8 -32.7 -5.1 -9.5 -13.37
Return, YTD -2.1 7.2 -9.8 -16 -11.5 -12.3 -7.42
Return, 3 months 3.27 9.01 -4.86 3.28 -15.9 -7.68 -2.15
Look-back (days) 120 80 120 80 3 ATR 3 ATR
Risk / trade 0.6 0.6 0.75 1 0.45 0.9 0.72
Return, 2009 1.1 3.4 -1.9 2.6 -3.3 4.3 1.03
Return, YTD -10.1 -13.4 -10.2 -20.9 -9.6 -24 -14.7
Return, 3 months -7.59 -9.7 -12.67 -13.89 -16.4 -17.7 -12.99
Look-back (days) 240 160 240 160 6 ATR 6 ATR
Risk / trade 0.85 0.9 1 1.6 1 2.2 1.26
Return, 2009 -18.9 -2.9 -13.2 -6.8 -7.4 -13 -10.37
Return, YTD -4.5 -14.8 -3.9 -7.5 -5.7 -10.2 -7.77
Return, 3 months -8.6 -15.4 -9.81 -16.3 -10.64 -17.65 -13.07
Longest period systems, with twice monthly rebalancing of open positions
Risk / trade 1.1 1.1 1.2 1.7 1.2 2.4 1.45
Return, 2009 -9.6 -0.3 -11.2 -6.5 -1.7 -12.8 -7.02
Return, YTD -9.6 -17.5 -2.4 -10.7 -8.2 -11.1 -9.92
Return, 3 months -11.7 -17.54 -8.83 -16.91 -12.52 -16.29 -13.97
Average of all look-back periods per system
Return, 2009 -12.36 -6.26 -12.18 -11.32 -3.42 -9 -9.09
Return, YTD -3.74 -5.32 -4.08 -11.34 -10.32 -13.46 -8.04
Return, 3 months -2.048 -3.086 -4.796 -6.372 -14.856 -12.666 -7.30
The short-term systems have performed best in 2010, a reflection of the prevailing choppiness in many markets. In contrast, these
systems underperformed in 2009.
stridsman1210.qxd 10/8/10 2:34 PM Page 24
risk-reward characteristics for the system.
Unfortunately, this isn’t always the case, as viewing last year’s
returns reveals. The situation was almost the opposite in 2009:
Again, most of the systems lost money, but the short-term,
volatility-sensitive systems were the worst performers, while the
longer-term ones (look-back periods in the 80- to 120-day
range) fared best.
The performance of the longest-term systems that also rebal-
ance their trades biweekly fell somewhere between the 40- to
60-day systems and the 80- to 120-day systems, which makes
sense because the rebalancing triples the trade frequency, mak-
ing the systems intermediate-term in nature. (By the way, it is
very hard to give exact figures for trade frequency or length, but
generally, the average trade frequency varied between one and
10 trades per market per year — approximately 500 to 1,500
round-turns per million dollars in equity — from the longest-
term to the shortest-term systems.)
So, does two years of lackluster performance for so many dif-
ferent trend-following systems prove such systems no longer
work? No, it doesn’t. We must remember that trend-following
systems are designed not only to make money in trending mar-
kets, they are in essence designed to lose money in choppy mar-
kets. From this perspective, the systems are doing just fine. The
markets are choppy and the systems are losing money — which
means they are performing exactly as intended. As soon as a
trend or two develops they will also start fulfilling the primary
design goal.
Using the matrixThat said, one interesting anomaly is the performance and per-
trade risk of the 40-day HH/LL stop-and-reverse system (system
4). Note that both its -32.7 percent loss in 2009 and its -16 per-
cent loss this year are way out of proportion to the same system’s
performance using different look-back periods, as well as the
performance of different systems with similar look-back periods.
Its 1.2 percent per-trade risk means it is also risking significantly
more than almost all the other systems to reach the desired
return target. Higher-high/lower-low stop-and-reverse breakout
systems with look-back periods of roughly 30 to 60 days proba-
bly are the most common systems used in trading, so maybe this
truly is a case of a system that has ceased to work optimally
because everyone is using it. Figure 2 shows its back-tested
equity growth.
When the trends return, the systems will still produce vastly
different results, even though most of them will be profitable in
the long run. But if you’re like most investors, you will feel the
pain or joy in the short run. Therefore, before you start trading a
system or invest with your first CTA, it’s a good idea to decide
on a system type that best fits with how you’d like to experience
your pain and joy. Start by comparing your system or CTA with
the systems in the matrix to get a feel for its trading style and
volatility, then decide whether its reward-risk profile fits your
investment style. Or, if you’re looking to diversify into several
systems or CTAs, compare them with all systems in the matrix
ACTIVE TRADER • December 2010 • www.activetradermag.com 25
continued on p. 26
FIGURE 2: 40-DAY HH/LL SAR SYSTEM
The exceptionally poor performance of the 40-day breakout system could be a case of a strategy that has
ceased to work optimally because everyone is using it.
stridsman1210.qxd 10/8/10 2:34 PM Page 25
Trading Strategies
26 www.activetradermag.com • December 2010 • ACTIVE TRADER
to make sure you will cover several reward-risk profiles.
Other factorsHowever, keep in mind that CTAs can alter their individual
reward-risk profiles by using different proprietary money man-
agement (i.e., position sizing) rules, and by incorporating factors
such as macroeconomic trends as well as trade and sector-alloca-
tion rules.
For example, Figure 3 shows the performance of the same
system on the same markets as Figure 2, except this time it used
a CTA’s proprietary position-sizing algorithm. (For 2009 it had a
loss of -6.8 percent, for 2010 the loss was -0.1 percent through
the end of July). Perhaps we can figure out what’s at work here
in upcoming articles, in which we will start tracking the per-
formance of a group of trend-following CTAs, and also examine
how some of the systems in this article have performed going
long and short in different market sectors.�
Related reading
Books and articles by Thomas Stridsman:
Trading Systems That Work (2000, McGraw-Hill)
Trading Systems and Money Management(2003, McGraw-Hill)
““Building a volatility-momentum system””Active Trader, October 2010
Systematizing volatility and momentum concepts
produces compelling test results.
““New approaches to volatility””Active Trader, September 2010
Just as there are alternatives to the moving aver-
age when defining trends, there are better ways
to measure volatility than the tools you may be
used to relying on.
““A baseline trend strategy””Active Trader, August 2010
Experimenting with moving medians, modes, and
center lines — in addition to moving averages —
in a robust trend system.
For information on the author, see p. 6.
All tests were done with TradingBlox system-testing software
(www.tradingblox.com) using Unfair Advantage data by CSI
(www.csidata.com), with the kind and invaluable help of Roger Rines
([email protected]), independent trader and system-developer
consultant.
FIGURE 3: THE IMPACT OF POSITION SIZING
Applying a position-sizing rule to the same system and markets represented in Figure 2 produced a much
more stable equity curve.
stridsman1210.qxd 10/8/10 2:34 PM Page 26
Although trends don’t last forever, they often last
much longer and go much further than most peo-
ple anticipate, which makes trying to buy a stock
because it’s low or short a stock because it’s high a
loser’s game.
Fortunately, a stock will often leave clues the trend is turning
and will usually make a minor correction before resuming its
new trend. Entering after that minor correction — and only if
the new trend shows signs of resuming — is the goal of “transi-
tional” patterns, as shown in Figure 1.
When you catch a new trend early, the payoff can be huge.
Unfortunately, since you are trading what could turn out to be a
correction in a longer-term trend, this approach will also have a
higher failure rate than trading pullbacks in established trends.
Let’s look at three transitional patterns: First Thrusts,
Gatekeepers, and Bow Ties.
First ThrustsMarkets in major trend transitions often begin with a bang,
making a sharp thrust in the new direction. This tends to catch
traders off guard. Trapped on the wrong side of the market, they
find themselves waiting for the market to reverse so they can get
BY DAVE LANDRY
Recognizing a few simple patterns — and trading
them correctly — can help you get into new trends early.
28 www.activetradermag.com •• December 2010 •• ACTIVE TRADER
TRADING Strategies
Trading trend transitions
FIGURE 1: TRANSITIONAL PATTERNS
Trading trend transitions requires identifying a correc-
tion as the market appears to be making a major turn.continued on p. 30
Uptrend
Downtrend
begins
Uptrend
begins
Uptrend
continues
Downtrend
resumes
First correction
First
correction
Downtrend
Shorts
Longs
KC Go to “Key concepts” on p. 78
for more information about:
• Fibonacci numbers
• Weighted and exponential
moving averages
landry1210.qxd 10/12/10 7:23 AM Page 28
Trading Strategies
off the hook. Bottom pickers and top pickers who missed the
top or bottom and do not want to pay up are also waiting for
some sort of meaningful correction.
Unfortunately, a meaningful correction may never come for
these traders. Often, markets making a sharp thrust in a new
direction pull back only briefly before resuming their new trend.
The old market participants will soon be forced out at unfavor-
able prices and the bottom or top pickers must pay up or risk
being left behind. By waiting for the market to make a sharp
thrust in the new direction, you avoid the pitfalls associated
with trying to pick highs or lows. By entering at the first signs of
a correction rather than waiting for something more substantial,
there is the potential for the position to be helped along by the
predicament of the aforementioned traders.
Let’s look at the pattern. Figure 2 shows how after making a
significant new low (1), the market should make a sharp thrust
in the new direction (2) followed by a lower low and a lower
high — in other words a one-bar pullback (3). Entry occurs
above the high of the pullback bar (4).
The best transitional patterns form in markets making major
new lows (for longs) or major new highs (for shorts). This helps
ensure the maximum number of people are on the wrong side of
the market when the trend turns. In Figure 3 the stock was at its
lowest level in more than a decade (1) when it thrust higher in
March 2009 (2). The stock made a lower low and a lower high
at point 3; in this case, entry would occur at point 4, above the
high of the pullback.
In Figure 4 the stock made multi-year highs in late-April (1)
and then began to sell off (2). It made a higher high and higher
low at point 3 to complete the setup. A short was triggered
when the stock turned back down at point 4. Notice the stock
made two more higher highs and
higher lows after point 3 before
turning lower. Entry occurs only
when price makes a lower low (for
a short setup) or a higher high (for
a long setup) after an initial pull-
back bar completes.
Notice that the retracement in
this example is fairly sharp. This is
similar in vein to another transi-
tional pattern, the Gatekeeper.
GatekeepersMarkets forming tops after a strong
trend often sell-off sharply before
making one last attempt to resume
their uptrends. This resumption is
caused by bargain hunters buying
at what they perceive to be low lev-
els and by shorts taking profits.
(Also, the move can be accelerated
30 www.activetradermag.com • December 2010 • ACTIVE TRADER
FIGURE 3: LONG FIRST THRUST
After making its lowest low in more than a decade, the stock made a sharp up
move.
FIGURE 2: FIRST-THRUST PATTERN
First Thrusts begin with a sharp move that reverses the
previous trend. A long trade would occur after the
initial pullback in the new up move.
(4)
(3)
(2)
(1)
landry1210.qxd 10/12/10 7:24 AM Page 30
ACTIVE TRADER • December 2010 • www.activetradermag.com 31
by shorts being squeezed.)
However, this move often exhausts
itself before price makes it back to
the old high. When this occurs, a
true top is then formed.
The Gatekeeper is a Fibonacci-
retracement reversal pattern
designed to identify when a market
has completed this “final gasp.”
Fibonacci trader and author Derrik
Hobbs refers to 78.6 percent as the
“gatekeeper” of Fibonacci numbers,
claiming that markets often stop
(and reverse) at that number. After
big downthrusts, markets often
stall after retracing between 61.8
percent and 78.6 percent of the
move. In some cases, the market
will reverse right at the 78.6-per-
cent retracement level.
The advantage of this pattern is
that its risk is well-defined (at worst, the trade is stopped out on
a move above the old high), while the potential reward of cap-
turing the occasional major top or bottom can be great. The pat-
tern is especially helpful for determining when an extended rally
could be topping out. Let’s look at the rules for short sales.
As shown in Figure 5, the market should make a new high
(1) followed by a sharp sell-off (2). It should then make a move
back toward the old high but stall somewhere between the 61.8-
percent and 78.6-percent (3) retracement levels of the sell-off
(i.e., the move from point 1 to point 2). Ideally, the sell-off and
retracement should unfold over 10 to 11 days, giving the move
a sharp “V” appearance (a reverse check mark). Entry occurs
when the market turns back down (4).
Figure 6 (p. 32) shows the S&P 500 during before and after
the May 6 “flash crash.” After making one-year-plus highs at
point 1, the index sold off hard to point 2, the day of the crash.
It then retraced sharply (3), giving players trapped on the wrong
(long) side of the market false hope. However, notice price
FIGURE 4: SHORT FIRST THRUST
The short trade is triggered only when the stock turns back down after making an
initial bar with a higher high and higher low.
continued on p. 32
FIGURE 5: GATEKEEPER PATTERN
The Gatekeeper pattern looks to enter after the
market retraces the move away from a major top
or bottom by a certain percentage.
(4)
78.6%
61.8%
(3)
(2)
(1)
10-11 days
landry1210.qxd 10/12/10 7:24 AM Page 31
Trading Strategies
stalled just shy of the 78.6-percent
retracement. Short entry occurs
when the market turned back
down at point 4.
Bow TiesFirst Thrusts and Gatekeepers are
fairly abrupt patterns that form rel-
atively quickly and accompany
new trends that begin with a bang.
Sometimes, though, new trends
start more gradually; price will
accelerate in the new direction only
after the market goes through a
distribution phase.
The Bow-Tie pattern uses a
series of moving averages to signal
such transitions. Although all indi-
cators are prone to lag, the Bow-Tie
moving averages can often alert
you to a trend change in markets
that have been going through
extended consolidations, especially
those that have recently made a
major high or low.
For this pattern, you can use a
10-day simple moving average
(SMA) and 20-day and 30-day
exponential moving averages
(EMAs). These averages often come
together and then spread out in the
opposite direction right before a
market makes a major transition.
That is, they go from “proper”
downtrend order (the faster mov-
ing average lengths below the slow-
er moving average lengths) to
proper uptrend order (the faster
moving averages above the slower
moving averages).
When this happens over a short
32 www.activetradermag.com • December 2010 • ACTIVE TRADER
FIGURE 6: GATEKEEPER: AFTER THE FLASH CRASH
A Gatekeeper pattern formed after the May 6 “flash crash” when price sold off
and the subsequent rally retraced only between 61.8 and 78.6 percent of the
sell-off before turning down.
FIGURE 7: BOW-TIE PATTERN
Bow Ties form when the three moving averages reverse their order, signaling a turn
in the market.
(3)
(2)
(1)30-day EMA
20-day EMA
20-day EMA
30-day EMA
10-day SMA
10-day SMA
landry1210.qxd 10/12/10 7:24 AM Page 32
time period, it gives the appearance of a Bow Tie, as shown in
Figure 7. Notice the moving averages are in proper downtrend
order (10-bar SMA < 20-bar EMA < 30-bar EMA), but quickly
invert after point 1 to proper uptrend order (10-bar SMA > 20-
bar EMA > 30-bar EMA). Ideally, this should happen over a peri-
od of three to four days. The inversion suggests the market has
made a major trend shift.
However, the market is still prone to correct in this situation.
Therefore, wait for the market to make at least a one-bar pull-
back (2) and then enter above it (3).
Like all transitional patterns, those that follow major highs or
lows are preferable. For example, in Figure 8, as the stock made
a six-year-plus low the moving averages were in proper down-
trend order (10-bar SMA < 20-bar EMA < 30-bar EMA). As the
stock began to bottom, the moving averages came together and
then inverted to proper uptrend order (10-bar SMA > 20-bar
EMA > 30-bar EMA) over just a few days, forming the Bow Tie
(1). The stock then made three consecutive lower lows and
lower highs (2). A long trade was triggered when price took out
the high of this pullback (3).
Staying on the right side of the marketTransitional patterns can often alert you that an old trend is
coming to an end and a new one is emerging, especially when
the market is making a longer-term
high or low. If you study major
market turning points — such as
the stock tops in 2000 and 2007,
or the bottoms in 2003 and 2009
— you’ll notice transitional setups
occurred on many time frames as
the market turned.
Trying to pick tops or bottoms is
a loser’s game. You’re much better
off waiting for the market to show
signs the trend is turning and then
look to enter after the first correc-
tion. First Thrusts, Gatekeepers,
and Bow-Tie patterns can be used
to catch new trends early. The best
setups occur after major highs and
lows — multi-year or even lifetime
highs or lows work best — because
it increases the odds that many
traders are trapped on the wrong
side of the market. Not every transitional pattern will turn into a
major top or bottom, but all major tops or bottoms will have
some sort of transitional pattern — that’s what makes watching
for them so worthwhile. �
ACTIVE TRADER • December 2010 • www.activetradermag.com 33
FIGURE 8: BOW-TIE: MOVING AVERAGE INVERSION
The reversal of the moving averages that forms the Bow Tie should unfold relatively
quickly (just a few bars).
Related reading““Trading the Bow-Tie pattern”” by Dave Landry
Active Trader, November 2000
Illustration of the bow-tie setup in the stock market.
““Bow-Tie variation””Active Trader, February 2008
A Trading System Lab article that tests a version of the
Bow-Tie pattern with a filter that requires the shortest
and longest moving averages to be within a certain dis-
tance of each other when an entry is triggered, and
extends the trade’s default holding period.
For information on the author, see p. 6.
Some of the strategies in this article are applied to the forex market in
Dave Landry’s article in the October issue of Currency Trader maga-
zine (www.currencytradermag.com).
landry1210.qxd 10/12/10 7:24 AM Page 33
When investors see a stock gapping to new
high ground on huge volume they immedi-
ately think, “Well, I can’t buy that now – the
train has left the station.” However, up-gaps
that occur on massive volume can be some of the most poten-
tially profitable price-volume signals you will come across.
When a stock gaps higher — and exhibits certain characteris-
tics — the train is, in fact, often just leaving the station.
Although the crowd is afraid of buying up-gaps because the
sudden jump gives the stock the illusion of being “too high,”
massive-volume up-gaps are exactly the type of rocket-fueled
move that signals big money is moving into a stock — particu-
larly if it occurs in the earlier stages of a leading stock’s larger
potential price move. In essence, massive-volume up-gaps work
because the crowd doesn’t believe them.
Two simple rules, based on volume and volatility when an
up-gap occurs, help identify the trade setups with the most
potential.
Identifying viable gapsYou can use some simple rules to screen for tradable up-gaps.
First, the up-gap must be at least 75 percent (0.75) of the stock’s
40-day Average True Range (ATR).
Figure 1 (p. 36) shows Apple’s (AAPL) 40-day ATR at the
time of its big earnings-related up-gap on Oct. 14, 2004, was
0.51; 75 percent of this ATR is 0.75*0.51 = .3825. The stock
more than exceeded this number when it gapped up 1.605 on
open of that day.
Another prerequisite for a valid up-gap is strong volume,
which in this case is defined as volume that is at least 1.5 times
the 50-day average daily volume. On Oct. 14, around 98.9 mil-
lion shares traded on the up-gap day — nearly seven times the
50-day average volume of 14.14 million shares on the previous
day. (Note how AAPL also made another buyable up-gap as the
stock made its big rally into the end of 2004.)
When most investors watch one of their favorite stocks gap
higher on a favorable earnings announcement, they usually
assume the stock has simply rallied too far to buy. However,
buying a stock aggressively prior to an earnings announcement
with the intention of participating in a possible up is simply
spinning the roulette wheel. The true high-probability buy point
occurs when the up-gap takes place, because price and volume
parameters can be determined and well-defined risk manage-
ment boundaries established.
In AAPL, the October 2004 major up-gap was the starting
point for a long-term price move that has continued to this day,
as AAPL remains at or near all-time highs, some 27 times higher
today than the price it hit on Oct. 14, 2004.
Although gap size and volume are key factors in determining
BY CHRIS KACHER & GIL MORALES
Screening stocks with volume and volatility
criteria can help make trading up-gaps less of a guessing game.
34 www.activetradermag.com • December 2010 • ACTIVE TRADER
TRADING Strategies
Trading gaps with the most potential
continued on p. 36
KC Go to “Key concepts” on p. 78
for more information about:
• Simple moving average
• True range (average true
range)
morales1210.qxd 10/8/10 1:54 PM Page 34
Trading Strategies
36 www.activetradermag.com • December 2010 • ACTIVE TRADER
whether a gap is tradable, there are other qualitative factors to
consider in the stock’s chart pattern. For example, confirm from
a quick check of the price chart that the stock is an uptrend or
coming out of a roughly sideways price consolidation several
days or weeks long. up-gaps that occur in downtrends are typi-
cally not high-probability buy points because they are often tem-
porary, news-related countertrend moves that eventually give
way to the stock’s overall macro trend. In general, the up-gap
should occur in a constructive, fundamentally sound, leading
stock.
The AAPL example might seem part of remote market history,
but the up-gap rules were still working in August 2010 when
Priceline.com (PCLN) rocketed higher after announcing earnings
(Figure 2). This up-gap move met the trade guidelines, and the
chart shows the gap was followed by a price move that took
PCLN above $300 for the first time.
Selling rulesFigure 3 shows another big earnings-related up-gap that fulfilled
the pattern criteria in mid-July 2009. Figures 1, 2, and 3 all
show how the stocks held well above the up-gap day’s low (dot-
ted line in Figure 3). Failure to do so is a potential sell signal.
However, you can wait for the stock to close before deciding
whether to sell on an intraday move below the up-gap day’s low.
Higher-volatility stocks can be given a little more room to fluctu-
ate intraday than lower-volatility ones. Sometimes a stock will
undercut the gap day’s low in subsequent trading days by a
small amount (e.g., less than 2 percent), in which case the posi-
tion could possibly be held.
Also, see if the gap day’s low is close to major support, such
FIGURE 1: VALID UP-GAP BUY OPPORTUNITY
The Oct. 14, 2004 up-gap was a valid buy opportunity because the gap more was than 75 percent of the 40-day
ATR, and volume was greater than the 50-day average volume the day before.
Source for all figures: eSignal
morales1210.qxd 10/8/10 1:56 PM Page 36
as the 10-day or 50-day moving
average. These moving averages
may “catch up” to the price pat-
tern and function as support.
The idea is to keep in-line with a
maximum stop loss, while avoid-
ing selling prematurely if the
stock undercuts the gap day’s
low by just a small amount. This
is Selling Rule No. 1. Figure 4
(p. 38) shows another recent
example of a viable up-gap in
Salesforce.com (CRM). As of
early October the stock has con-
tinued to trade above the up-gap
day’s low, thus avoiding Selling
Rule No. 1.
If a stock has gapped up and
is trending higher, you can
implement Selling Rule No. 2,
which uses two moving averages
as guides for unloading a posi-
tion, depending on the stock’s
“character.” Powerful up-gaps
often generate strong trends that
follow, or “obey,” the 10-day
moving average for at least seven
weeks at a time. Once a stock
has obeyed its 10-day moving
average for at least seven weeks,
a violation of the average consti-
tutes a sell signal. (A violation of
a moving average is defined here
as a close below the moving
average, followed in the next few
days by an intraday drop below
the low of the day that first
closed below the moving aver-
age.) This is called the Seven-
Week Rule. There are three
exceptions to this rule:
1. The stock, prior to the up-gap, has tended to violate the
10-day moving average in intervals of less than seven
weeks as a matter of course in its price history;
2. The stock is in one of the following industry groups: semi-
conductors, retailers, or commodities (including oils and
precious metals);
3. The stock has a market capitalization greater than
$5 billion.
In these cases it is better to use a violation of the 50-day mov-
ing average as a sell signal — i.e., if the stock doesn’t obey its
10-day moving average for at least seven weeks, use a 50-day
moving average violation. A violation of the 10-day moving aver-
age can be used to sell at least half the position for stocks that
meet the Seven-Week Rule. A subsequent violation of the 50-day
moving average can be used to sell the balance of the position.
Let’s look at two examples to see how all this works. Figure 5
(p. 38) shows Chinese Internet leader Baidu (BIDU) formed a
viable up-gap in early January 2010, but that move quickly
ACTIVE TRADER • December 2010 • www.activetradermag.com 37
continued on p. 38
FIGURE 2: SPARKING THE MOMENTUM
After this up-gap the stock pushed above $300 for the first time.
FIGURE 3: STAYING ABOVE THE GAP-DAY’S LOW
After a valid signal, price should not violate the low of the day immediately after the
gap.
morales1210.qxd 10/8/10 1:56 PM Page 37
Trading Strategies
38 www.activetradermag.com • December 2010 • ACTIVE TRADER
failed when the stock dropped
below the low of the up-gap
day and violated the 50-day
moving average. But in the first
half of February BIDU came
right back and staged another
tradable up-gap, and this time
the stock rallied without look-
ing back. As BIDU continued to
trend higher, it never violated
its 10-day moving average
(pink). As the stock reached the
mid-$60s in April, it twice
closed below its 10-day moving
average, but in each instance
the stock failed to subsequently
trade below lows of each of the
days that closed below average.
As a result, they never met the
definition of a moving-average
violation.
In Figure 6, a tradable up-
gap in late-July 2010 took F5
Networks, Inc. (FFIV) up and
out of an up-trending price
channel. Notice that once the
stock gapped up and began to
move higher, the stock broke
down through the 10-day mov-
ing average a couple of weeks
later, which means it did not
obey its 10-day moving average
for seven weeks or more. Based
on this, you would ignore the
10-day average and instead use
the 50-day moving average as a
selling guide. One other point:
Although it fell below the 10-
day moving average, FFIV never
fell below the gap day’s low, so
it didn’t trigger Selling Rule No.
1. Nor did it trigger Selling Rule
No. 2, since it also remained
well above the 50-day moving
average (blue). Three weeks
later the stock had completely
recovered and moved to new
FIGURE 4: STAYING ABOVE THE AVERAGE
The stock should also remain above the 10-day moving average.
FIGURE 5: AVOIDING VIOLATION
The stock quickly failed after the first gap, but it rallied strongly after the second.
Although it closed below its 10-day moving average twice in April, in both cases the
stock did not subsequently penetrate the low the day that closed below average.
morales1210.qxd 10/8/10 1:56 PM Page 38
highs.
In practice, big-volume up-
gaps, which often appear to be
out-of-reach trade opportunities,
are often the first cannon shots
marking the start of a strong
upside price move. Having a
methodology in place for identify-
ing and capitalizing on these
trades is critical for success.
The approach outlined here is
fairly straightforward, and pro-
vides traders with an edge that is
likely to be overlooked by the
crowd. Using a few simple rules
makes such trades less risky, and
helps skew the reward-risk equa-
tion in your favor. �
ACTIVE TRADER • December 2010 • www.activetradermag.com 39
For information on the authors,
see p. 6.
FIGURE 6: USING THE 50-DAY MOVING AVERAGE
Approximately two weeks after gapping higher the stock traded below the 10-day
moving average, which means it failed to “obey” the average for seven weeks or more.
As a result, the 50-day moving average would be used as a selling guide.
Related reading
Book:
Trade Like an O’Neil Disciple: How We Made 18,000percent in the Stock Market by Gil Morales and ChrisKacher.
Website:
www.VirtueofSelfishInvesting.comIncludes more information from the authors on buyableup-gaps and other technical methods.
Other articles:
““Opening gap locations””Active Trader, December 2008Historical testing attempts to identify the best setups forfading the opening gap.
““Double gaps””Active Trader, March 2008Analysis of the performance of double (and triple) pricegaps.
““Opening gap trader”” Active Trader, August 2007Further analysis points to a new direction for trading anopening-gap signal.
““Gauging gap opportunities””Active Trader, January 2007A different look at an “old” pattern offers insights intoprice behavior in the S&P 500.
““Gap trading techniques: Five-article set””A discounted collection of the following five ActiveTrader articles, published between 2001 and 2004:
1. “Morning reversal strategy” by Bryan C. Babcock andArthur Agnelli (May 2003). A strategy that takes itscue from historical tests revealing the tendency of themajor stock indices to revert to the previous day’s clos-ing price in the early minutes of the trading session.
2. “Trading the overnight gap” by David Nassar (March2001). Learn how to spot the early warning signs ofopening gaps and how to take advantage of them.
3. “Trading the opening gap” by John Carter (December2004). Watching pre-market volume is a good way todetermine whether to trade or fade the openingmove.
4. “Trading System Lab: Gap closer (stocks)” by DionKurczek (May 2003). This system test is designed tosee if the “all gaps are eventually closed” axiom holdswater (tested on a portfolio of stocks).
5. “Trading System Lab: Gap closer (futures)” by DionKurczek (May 2003). The above gap-based systemtested on a portfolio of futures markets.
morales1210.qxd 10/8/10 1:56 PM Page 39
The covered call is the one option strategy people
seem to grasp. New brokers with freshly minted
Series 7 licenses eagerly take their enhanced-
income investment approach to their client bases.
It’s plain to see that using the covered call offers the possibility
for immediate income — something investors are so attracted
to. It is heralded as a safe investment choice, from the perspec-
tive of both a brokerage house and the investor who is clamor-
ing to generate additional income for his portfolio.
Yet for all the history and salesmanship, it’s worthwhile to
step back and take another look at the covered call. Option
traders agree there is a season for any strategy. But is the invest-
ing public being duped with a short-sighted method, or is the
covered call truly a four-season strategy?
The covered call definedIn its most basic form, a covered call position is created when a
trader who owns an underlying security sells a near at-the-
money or slightly out-of-the-money call. The strategy is “cov-
ered” if the trader sells enough calls to cover the existing long
position in case of assignment of the short call.
Although the covered call is often referred to as a “buy-write,”
it’s important to recognize they differ in implementation.
Generally speaking, a covered call applies when a trader, for
whatever reason, simply sells an equivalent number of calls
against an already existing underlying position; buy-write
applies when the trader simultaneously buys the underlying
market and sells the call — as a package. Either way, the trader
typically holds the underlying in the same account from which
he sells the calls. The underlying provides collateral for the trad-
er’s requirement to deliver the stock if he gets assigned on the
option position.
For example, let’s say a trader buys 1,000 shares of XYZ stock
at $40 per share. He wants to sell a call option that offers him a
satisfactory amount of premium within a specific time horizon.
He finds a three-month $45 call trading for $2 per share and
decides to sell 10 of these $45 three-month call options, receiv-
ing a $2 premium for the 10 contracts ($2,000) sold against his
long position:
$2 premium per stock share *
100 shares per options contract
* 10 contracts = $2,000
This position is considered covered in that the trader sold 10
call options against the thousand shares of stock he holds in his
BY LARRY SHOVER
Market realities make the popular covered call strategy
more difficult to pull off than most people think.
40 www.activetradermag.com • December 2010 • ACTIVE TRADER
TRADING Strategies
Uncovering the covered call
• At the money
• Call option
• Implied volatility
• In the money
• Naked put
• Out of the money
• Premium
• Skew
• Strike price
KC Go to “Key concepts” on p. 78 for more
information about:
shover1210.qxd 10/8/10 12:47 PM Page 40
ACTIVE TRADER • December 2010 • www.activetradermag.com 41
account. The premium received from
the options sale ($2 per share) effective-
ly lowers the stock’s cost basis from $40
per share to $38 per share.
There are three possible outcomes for
this example. First, the stock could
close above $45 per share at expiration.
In this case, the short $45 call will auto-
matically exercise, resulting in the stock
being delivered to an exerciser of a long
$45 call at $45 per share. The maxi-
mum profit in this situation is:
Strike price – purchase price +
option premium received, or
$45.00 - $40.00 + $2 = $7
Second, the stock could close at $45 per share at expiration.
In this case, the call will expire worthless, leaving the trader
with the original stock holding and $2,000 in realized option
premium profit.
Finally, if the stock closes below $45 per share at expiration,
the call will expire worthless and the trader will enjoy both the
original stock position and $2,000 in premium profit. However,
the strategy offers no protection below the original cost basis of
$38 per share (the $40 per share purchase price of the stock
minus the $2 in premium received). Table 1 summarizes cov-
ered call performance across a range of stock prices at expira-
tion.
Reviewing the construction of the covered call strategy and its
possible outcomes, it’s easy to see why the strategy is a starting
point for both trader and investors: It’s simple and the risk asso-
ciated with it is both defined and limited. But keep these risks
in mind.
The four realities of the covered call strategyFirst, don’t assume you can consistently pick stocks (or futures)
that have both a high amount of option premium and a stable
price. In fact, the opposite is generally true. Only volatile instru-
ments are likely to have large option premiums. In the case of
stocks, the truly safe, stable, established blue-chip issues are the
ones with relatively low option premiums, and there’s a very
good reason for that. A relatively high implied volatility suggests
the underlying share price is or will soon be extremely volatile
and, therefore, quite risky for a short-term investment strategy.
Second, using a covered call position as a long-term trading
approach usually results in poor performance. A trader invests
in a variety of stocks and, hoping to generate extra income, sells
near at-the-money call options against them. After several
months some of the stocks have gone up, some have gone
down, and some have remained unchanged. The stocks that
went up were, unfortunately, called away. The ones that have
gone down are more than likely well below the option’s strike
price. What remains is a portfolio that is worth far less than
before the covered call strategy was attempted, because a trader
is always forced to sell the best-performing stocks. In short, the
covered call strategy can be a painfully effective way of sorting
out the good from the bad — and keeping the bad.
Third, covered call writing is not necessarily safe — even in a
bull market. First, diagnosing exactly what the market is doing
sometimes involves pure guesswork. For example, when a bear
market ends and a new bull market (or at least an upward
TABLE 1: COVERED CALL PROFIT/LOSS AT EXPIRATION
Covered call trade:Bought 1,000 shares XYZ at $40/share: ($40,000)
Sold 10 XYZ 3-month $45 calls at $2/share: $2,000
Result at expiration
Stock price Stock P/L$45 call
valuePremium received
Net P/L
$100 $60,000 ($55,000) $2,000 $7,000
$75 $35,000 ($30,000) $2,000 $7,000
$65 $25,000 ($20,000) $2,000 $7,000
$47 $7,000 ($2,000) $2,000 $7,000
$40 $0.00 $0.00 $2,000 $2,000
$38 ($2,000) $0.00 $2,000 $0.00
$25 ($15,000) $0.00 $2,000 ($13,000)
$10 ($30,000) $0.00 $2,000 ($28,000)
$0 ($40,000) $0.00 $2,000 ($38,000)
The covered call caps profit in the event of a rising stock price, but offers only
partial downside protection.
continued on p. 42
shover1210.qxd 10/8/10 12:47 PM Page 41
Trading Strategies
trend) begins, it takes time before it clearly is considered a bull
market. Who exactly decides a bull market is a bull market, any-
way? It can take a lifetime for everyone to agree a long-term
market trend has developed, and by the time unanimity is
achieved, the up move has ended. Second, there will always be
stocks that underperform in a rising market and vice versa. To
base a covered call strategy solely on broad market assumptions
is nothing short of living by faith.
Finally, covered call writing is not as simple as it appears. The
complexity is not so much in the strategy itself but rather in
addressing the two primary challenges the strategy presents:
downside risk is reduced but not eliminated, and potential profit is
capped. Given those challenges, it would appear this strategy
could potentially violate the fundamentals of conservative
options trading, the primary objectives of which are maximizing
income while using leverage to limit portfolio risk. There are
stocks and various circumstances for which the covered call
makes sense, but you must apply the strategy correctly and be
fully aware of its risks.
Three reasons to reconsider the covered call strategy Would you sell a put option naked? A covered call’s risk profile
looks a lot like selling a naked put. The only difference is that
the underlying will not expire. As a result, as the underlying
price begins to fall, agony is prolonged, and losses are increased.
Table 2 compares covered call and naked put positions.
42 www.activetradermag.com • December 2010 • ACTIVE TRADER
TABLE 2: RISK PROFILE COMPARISON: NAKED PUT VS. COVERED CALL
Stock price = $30 Naked put trade: Covered call trade:
2-month $30 call = $1Buy 1,000 shares at
$30,000
2-month $30 put = $1Sell 10 two-month
$30 puts at $1
Sell 10 two-month $30
calls $1.00
Naked put P/L at expiration
Stock price Stock P/L2-month $30 put
valuePut premium
receivedNet P/L
$80 N/A $0.00 $1,000 $1,000
$70 N/A $0.00 $1,000 $1,000
$60 N/A $0.00 $1,000 $1,000
$50 N/A $0.00 $1,000 $1,000
$40 N/A $0.00 $1,000 $1,000
$30 N/A $0.00 $1,000 $1,000
$20 N/A ($10,000) $1,000 ($9,000)
$10 N/A ($20,000) $1,000 ($19,000)
$0 N/A ($30,000) $1,000 ($29,000)
Covered call P/L at expiration
Stock price Stock P/L2-month $30
call valueCall premium
receivedNet P/L
$80 $50,000 ($50,000) $1,000 $1,000
$70 $40,000 ($40,000) $1,000 $1,000
$60 $30,000 ($30,000) $1,000 $1,000
$50 $20,000 ($20,000) $1,000 $1,000
$40 $10,000 ($10,000) $1,000 $1,000
$30 $0.00 $0.00 $1,000 $1,000
$20 ($10,000) $0.00 $1,000 ($9,000)
$10 ($20,000) $0.00 $1,000 ($19,000)
$0 ($30,000) $0.00 $1,000 ($29,000)
The risk profile of a covered call is essentially the same as that for a naked put.
shover1210.qxd 10/8/10 12:47 PM Page 42
ACTIVE TRADER • December 2010 • www.activetradermag.com 43
Why cap the upside? All active traders will at some point
wistfully tell the same story of the great stock that got away
because they bought it to cover a short options position and
the contract was exercised against them. Many professionals
feel picking market direction, option strategies, or stocks is
rocket science; to succeed one needs to be as brainy as a
nuclear physicist. Sorry. Some trading firms these days do, in
fact, employ engineers and people with math and physics
Ph.D.s to build computer models, and many traders like to
think of themselves as brilliant.
But this is not the case. The beautiful notion of random-
ness means that much what goes on in the world of choosing
stocks is nothing more than luck. The reality is we are very poor
decision makers, and to think we can consistently pick success-
ful stocks is foolhardy at best. To be consistent, traders need to
ride winners and cut losses. The problem with the covered call
is there will always be the one stock that got away.
Why sell an option into the hole? “Skew” is the contour, or
the unevenness, in a distribution of values. The negative skew
seen in equity and index options reflects the reality that the
prospect of losing money, maybe a great deal of money, is much
more likely than taking home large gains (Table 3). In a theoreti-
cally precise, ideal, normal distribution, the probability of enjoy-
ing strong gains or suffering large losses is the same. Equity
options, however, typically have a built-in negative skew. Out-
of-the-money call options cost less than equally out-of-the-
money put options, and more often than not, at-the-money
options have implied volatility somewhere in between, for two
reasons. First, the market always insists a trader is more likely to
lose money with any strategy or position. More important, the
investing public joins the investment distress. People panic, or at
least get uneasy — even financial analysts with Ph.D.s in
physics. That means that the public normally sells out-of-the-
money calls and buys of out-of-the-money puts to protect
against potential losses.
Effective call writingVolatile stocks with high option premiums are needed to get the
kind of returns covered call investors are looking for. But that’s
the problem. A low-priced, highly volatile stock is needed to
make this strategy work from a cash-flow perspective. The share
prices for these stocks, however, tend to go up and down, some-
times in stunning fashion. When the share price rises, traders
miss out on profiting from that increase by putting a cap on the
strike price for the options they sold.
In the end, why buy a stock and then cap its upside poten-
tial? When looking at a long-term investment, if a stock’s price
isn’t likely to go up soon, why tie up cash to buy it now?
Keep in mind human frailty. Trading is all about possible loss
that can’t be predicted and controlled. It’s the result of living in
an imperfect world with imperfect people who become greedy
and short-sighted, who panic, who make blunders and then try
to hide them, who try to protect their jobs, who have more con-
fidence than experience, or who have too much experience and
grow complacent. Trading rises from an unpredictable world
with too many human factors to count. And nothing is more
unpredictable in markets and trading than the humans who are
behind it all. �
TABLE 3: TYPICAL IMPLIED STRIKE VOLATILITY FOR 30-DAY SPX CASH-SETTLED OPTIONS
SPX = $1,064.00
Interest rate = 1.75%
Strike price Call value Put value Strike volatility$1,170 $0.80 $106.50 18.50%
$1,150 $1.75 $87.50 19.00%
$1,130 $3.60 $69.40 19.50%
$1,110 $7.25 $53.00 20.00%
$1,090 $12.95 $39.00 20.50%
$1,070 $21.80 $27.80 21.50%
$1,050 $33.35 $19.35 23.00%
$1,030 $47.00 $13.05 24.50%
$1,010 $63.00 $8.85 26.00%
$990 $80.00 $6.00 27.50%
$970 $98.00 $4.00 29.00%Because of negative skew, the out-of-the-money equity call
option cost less than the equally out-of-the-money put option.
For information on the author, see p. 6.
shover1210.qxd 10/8/10 12:47 PM Page 43
44 www.activetradermag.com • December 2010 • ACTIVE TRADER
All professions develop a
shorthand sooner or
later. Not only does it
facilitate communication
amongst those with a shared knowl-
edge (or ignorance) base, it excludes
outsiders. For years, bond traders
have referred to “the yield curve” as
the spread between 10- and two-year
Treasury notes. The choice of a two-
year note may seem a little odd to
outsiders, which suits the pros just
fine. The two-year represents a one-
year forward rate agreement stacked
on the end of a one-year money mar-
ket strip, and is thus linked to the
cost of rolling a one-year money mar-
ket strip forward for another year.
The global drive toward zero per-
cent interest rates in 2008-2010 com-
pressed the yield on the two-year note
down to a limit where lenders found
resistance. Moreover, as low as the
two-year note yields got (below 55
basis points in July 2010), they could
not compete with short-term strips of
federal funds in what is known as the
overnight index swap (OIS) market. A
three-month OIS hovered below 20
basis points in July 2010. As the
Federal Reserve kept promising to
keep short-term rates low for “an
extended period,” carry traders found
it increasingly attractive to switch
their funding source from the more
traditional two-year note to the three-
month OIS.
We can compare the two yield
curves by their forward rate ratios
(FRR) over time.
This is the rate at
which we can lock
in borrowing for
either 9.75 years
(OIS) or eight years
(two-year note)
starting either three
months or two years
from now, divided
by the 10-year note
yield. The more
these FRRs exceed
1.00, the steeper the
yield curve.
Figure 1 shows
the OIS-based FRR
is both flatter and
smoother than the
FRR2,10. The period-
ADVANCED Concepts
Not all carry trades are alike
Much of the free money in the aftermath of the financial crisis fattened the balance
sheets of investment banks, regional banks, and asset managers rather than
flowing into the economy as job-creating credit.
BY HOWARD L. SIMONS
FIGURE 1: TWO DIFFERENT YIELD CURVES
The OIS-based FRR is both flatter and smoother than the FRR2,10.
simons1210 10/11/10 4:29 PM Page 44
ic outbursts of fear regard-
ing short-term rates tend
to make the highly expec-
tational two-year note
yield jump around vio-
lently, while the OIS rate
stayed anchored by the
Federal Reserve.
Stock market impactThe federal government
made the financial sector
its special project during
and after the financial cri-
sis of 2008. The low bor-
rowing costs it created
allowed banks and other
financial institutions to
rebuild their balance
sheets by borrowing low
at the short end and lend-
ing high at the long end.
Indeed, this engineered
carry trade allowed the
Federal Reserve to mone-
tize Treasury debt by let-
ting member banks buy
Treasuries at auction
rather than having the
Federal Reserve do more
than its $300 billion of
Treasury and $1.25 trillion
of mortgage security pur-
chases financed out of thin
air.
Not that this free
money led to stock market
ACTIVE TRADER • December 2010 • www.activetradermag.com 45
continued on p. 46
FIGURE 2: FINANCIAL INDUSTRY GROUP TOTAL RETURNS NOV. 20, 2008 – JULY 30, 2010
Of the 12 S&P 1500 financial sector industry groups, the favored groups of the banking sector
underperformed, and the mortgage-finance group most of all.
FIGURE 3: RELATIVE PERFORMANCE & TWO CARRY TRADES: OTHER DIVERSIFIED FINANCIAL SERVICES
For most of 2010, the OIS carry was more important for big banks, suggesting the major banks have
fattened up somewhat on their ability to borrow at a term federal funds rate.
simons1210 10/11/10 4:29 PM Page 45
Advanced Concepts
46 www.activetradermag.com • December 2010 • ACTIVE TRADER
outperformance. If we
go back to the day in
November 2008 when
Timothy Geithner (pres-
ent at the creation dur-
ing his stay as president
of the Federal Reserve
Bank of New York) was
appointed to be
Secretary of the Treasury
and Citigroup got back-
stopped once again by
the Paulson Treasury,
and compare the total
returns for the 12 indus-
try groups of the S&P
1500 financial sector,
the favored groups of
the banking sector have
underperformed, with
the mortgage-finance
group underperforming
the most (Figure 2,
p. 45).
Which carry, the OIS-
based or the two-year
note-based, was the bet-
ter explanatory variable
for some of these key
banking groups? We can
answer this by modeling
the total return of each
financial group relative
to the S&P 1500
Supercomposite on a
log-linear basis:
ln(Rel.Perf) = f(FRR).
Let’s take the big
banks first (Figure 3,
p. 45). Here the behavior
FIGURE 4: RELATIVE PERFORMANCE & TWO CARRY TRADES: REGIONAL BANKS
The relative performance of regional banks has not been a strong function of either carry trade.
FIGURE 5: RELATIVE PERFORMANCE & TWO CARRY TRADES: INVESTMENT BANKS & BROKERAGES
For the investment bank and brokerage group the OIS carry produces the better statistical fit, but
the investment banks’ reliance on free money started to wear off after the financial crisis began to
dissipate.
simons1210 10/11/10 4:29 PM Page 46
ACTIVE TRADER • December 2010 • www.activetradermag.com 47
of the industry was so
dominated by external
factors, such as the
question of national-
ization and the repay-
ment of TARP funds,
the actual answer to
which carry trade was
more important must
be, for most of 2010,
the OIS carry. This
does suggest the major
banks have fattened
up somewhat on their
ability to borrow at a
term federal funds
rate.
The answer is different
for the regional banks,
however (Figure 4).
These banks have had
greater exposure to real
estate portfolios and
depend more on their
loan portfolios as
opposed to trading and
fee income than the
major banks do. Their
relative performance is
not at all a strong func-
tion of either carry trade.
What about the invest-
ment bank and brokerage
group (Figure 5)? Here
the answer lies in
between. The OIS carry
clearly produces the bet-
ter statistical fit, but the
investment banks’
reliance on free money
started to wear off after
the financial crisis began
to dissipate. In retrospect,
the best thing that hap-
pened to the investment
continued on p. 48
FIGURE 6: RELATIVE PERFORMANCE & TWO CARRY TRADES: CONSUMER FINANCE
The consumer finance group is almost a mirror-image of the investment bank group.
simons1210 10/11/10 4:29 PM Page 47
Advanced Concepts
banks was their post-2008 status as com-
mercial banks and members of the
Federal Reserve system, which gave them
direct access to federal funds. As an aside,
the pattern for asset managers and custo-
dial banks is similar to that seen for the
investment banks.
The final group we will discuss directly
is consumer finance (Figure 6, p. 47).
This group is almost a mirror image of
the investment banks. Its relative per-
formance turned into a close function of
the FRR in the Treasury market, while its
link to the OIS carry disappeared in early
2010. They are yield curve-dependent, to
be sure, but as they are not a direct player
in the federal funds market, they have to
rely on a different carry trade.
It must be emphasized the variable
being modeled here is the relative stock
market performance of financial groups,
not their profitability. A stock can rise in
the face of poor earnings if there is a rea-
sonable belief business will improve or
the firm will be rescued. Conversely, a
stock with strong earnings can do poorly
if the earnings derive from special cir-
cumstances, such as free money and gov-
ernment protection. The simple fact of
the matter is modeling anything in the
financial sector based on earnings was
impossible during this period; you had to
account for massive operating losses, cap-
ital raised, assets written off, government
capital infusions, all manner of extraordi-
nary items, the elimination of FAS 157
mark-to-market accounting, etc. A stock
price, in contrast, is observable and more
or less beyond dispute.
We can infer from the observations
above of relative stock performance the
carry based on the much shorter and
much more dangerous OIS (because the
funding must be rolled over every three
months instead of every two years)
became more important than the tradi-
tional yield curve spread between the two
and 10-year note. Recent evidence sug-
gests the one-month OIS rate has become
more important now than the three-
month OIS rate. Such dependence on
ever-shorter funding is reminiscent of the
overnight funding employed by the late,
great Bear Stearns and Lehman Brothers.
What did we fail to learn, besides every-
thing?
We can also infer much of the free
money went to fatten the balance sheets
of investment banks, regional banks and
asset managers as opposed to flowing into
the economy as job-creating credit. In the
battle between Main Street and Wall
Street, Wall Street won. Where is the
adage, “Don’t fight the Fed” better
known? �
48 www.activetradermag.com • December 2010 • ACTIVE TRADER
For information on the author, see p. 6.
A stock can rise in
the face of poor
earnings if there is a
reasonable belief
business will improve
or the firm will be
rescued.
““Investing under a constant expectation””Active Trader, November 2010
Will 2010 be remembered as Year
One of America’s “Lost Decade”?
““The risks of risk-free bonds””Active Trader, October 2010
History shows governments cannot
indefinitely abuse their currencies and
creditors through irresponsible poli-
cies.
““How Japan lost more than a decade””Active Trader, September 2010
A warning to countries that adopted
Japanese policies during the 2008-
2009 financial crisis: The end result of
20 years of monetary and fiscal excess
is failure.
““Which stocks and what dollar?””Active Trader, August 2010
Watch as the U.S. dollar index is
deconstructed and the relationship
between currencies and U.S. stocks is
clarified.
““Natural gas and contango limits””Active Trader, July 2010
Explore the relationship between
different contract months in the ener-
gy futures market.
““China starts setting the pace””Active Trader, June 2010
Data is beginning to suggest China is
leading global financial markets, not
reacting to developments elsewhere.
““Financial markets and inflation””Active Trader, May 2010
As we attempt to grapple with the
risk of inflation and its implication for
markets, we find we are working with
outdated concepts.
““Inflation’s macro myths””Active Trader, April 2010
Everything you think you know about
inflation is wrong.
Related readingOther Howard Simons articles:
simons1210 10/11/10 4:29 PM Page 48
This Trading System Lab focuses on determining if
stock splits are useful in identifying stocks likely to
outperform in the future. The system idea is derived
from a 1996 Rice University study by David
Ikenberry, who showed that a group of stocks that had split
between 1975 and 1990 performed significantly better (up to
three years following splits) than a control group of comparable
stocks that had not split. (The study, and this test, uses standard
“forward” splits, not reverse splits.)
This result might seem somewhat surprising since a stock
split does not create value for investors. If a stock splits two for
one (2:1), a corporation doubles the number of outstanding
shares while simultaneously halving the share price. The result-
ing market capitalization is the same before and after the split
(although the costs of this corporate action must be absorbed).
If splitting stock shares doesn’t create value and it costs
money to do it, why split? Because splits reduce share price, it
makes the stock easier (less expensive) to trade round lots (mul-
tiples of 100 shares). More so in the past than today, higher fees
or commissions associated with “odd-lot” transactions could
influence an investor’s decision.
Also, lower stock prices are gener-
ally accompanied by tighter bid-
ask spreads. On the other hand, if
price is too low, the shares will
not attract institutional invest-
ment.
In short, for our purposes it’s
interesting to consider that a com-
pany can essentially manage (per-
haps even optimize) the range of
its stock price to make it attractive
to the maximum number of mar-
ket participants, even though
recent high-flying examples such
as AAPL, BIDU, GOOG, and
PCLN would seem to contradict
the theory that an optimum range
exists.
The system’s basic strategy is
simple: Each month, it gathers a
list of symbols that have split with
a ratio 1.5 (a 3:2 split) or higher.
The list is ranked by current ratio
TRADING System Lab
50 www.activetradermag.com • December 2010 • ACTIVE TRADER
Profiting with stock splits
KC Go to “Key concepts” on p. 78
for more information about:
• Current ratio BY ROBERT SUCHER JR.
FIGURE 1: EQUITY CURVE
As the worst of the financial crisis approached, the strategy had already increased its
cash position, which served to cushion the blow. The S&P 500 index, by compari-
son, declined approximately 58 percent.
Source for all figures: Fidelity Wealth-Lab Developer 6.0
tsl1210 10/8/10 12:58 PM Page 50
ACTIVE TRADER • December 2010 • www.activetradermag.com 51
and 4 percent of the account equity is
allocated to buy the top two stocks
each month. Any viable ranking strat-
egy could be used; current ratio was
selected for this test to give priority to
companies with stronger capital posi-
tions.
The maximum holding period is
three years, but once a position has
attained a 25-percent gain on an intra-
day basis, a 5-percent “profit stop” is
placed below the market (i.e., 5-per-
cent above the entry price). While the
strategy doesn’t use stops after open-
ing positions, the idea behind the
profit stop is straightforward: Prevent
a solid gain from turning into a loss.
Note that entering two positions
each month (when candidates exist)
with 4 percent of equity will result in
approximately 100-percent invest-
ment with 25 positions just after the
end of the first two years of trading.
Thereafter, the strategy will naturally
make room for new split candidates as
the oldest positions are exited or
when a profit stop is hit. This phase-
in approach forces you to not commit
to 100-percent exposure all at once,
something that could make it difficult
to stick with the strategy during
volatile periods.
System entry rules:1. EEnntteerr lloonngg on the first trading day
of the month following a split with
a ratio of 1.5 (3:2 split) or higher.
2. When multiple candidates existcontinued on p. 52
FIGURE 2: ANNUAL RETURNS
Having a large exposure during the cyclical bull that started in 2003 helped the
system outperform the market, but the strategy was not entirely immune to the
2008 sell-off.
FIGURE 3: TRADE EXAMPLE
This highly profitable trade came less than two years after a reverse split, which
generally occur in struggling stocks.
tsl1210 10/8/10 12:58 PM Page 51
(the usual case), priority is given to the two stocks with the
highest current ratio.
System exit rules:1. SSeellll after three years or,
2. When the stock achieves a 25-percent gain, set a stop 5 per-
cent above the entry price.
Starting equity: $100,000. Deduct $8 per trade in commis-
sions.
Test data: The system was tested on all S&P 500 component
stocks that were in the index as of Sept. 8, 2010. Dividend-
adjusted price data provided by Yahoo.com (an important man-
ual correction to FHM’s split on 9/10/08 is required). Current
52 www.activetradermag.com • December 2010 • ACTIVE TRADER
PERIODIC RETURNS
Avg. Sharpe Best Worst % profitable Max. consec. Max. consec. return ratio return return periods profitable unprofitable
Monthly 1.11% 3.89 10.63% -11.66% 56.0 7 9
Quarterly 3.0% 0.80 14.85% -12.31% 65.9 9 3
Annually 12.02% 0.67 40.91% -20.69% 72.7 5 1
Trading System Lab
STRATEGY SUMMARY
Profitability Original Enter before ex-date Trade statistics Original Enter before ex-date
Net profit: $199,948 $264,735 No. trades: 89 85
Net profit: 200% 265% Win/loss: 85.4% 88.2%
Profit factor: 5.54 7.48 Avg. profit/loss: 43.7% 52.2%
Payoff ratio: 1.31 1.75 Avg. hold time, months: 25.1 24.5
Recovery factor: 2.28 2.33 Avg. winners: 58.9% 64.1%
Exposure: 73% 72.2% Avg. hold time (winners): 23 months 23.4 months
Longest flat period: 28 months 36 months Avg. loss: -44.9% -36.7%
Max. DD: -26.5% -27.5% Avg. hold time (losers): 37.3 months 32.4 months
Commissions: $1,328 $1,272 Max consec. win/loss: 26 / 2 40 / 2
LEGENDNet profit — Profit at end of test period, less commission.
Profit factor — Gross profit divided by gross loss.
Payoff ratio — Average profit of winning trades divided by average loss
of losing trades.
Recovery factor — Net profit divided by maximum drawdown.
Exposure — The area of the equity curve exposed to long or short posi-
tions, as opposed to cash.
Max. drawdown (DD) — Largest percentage decline in equity.
Longest flat period — Longest period, in days, the system is between
two equity highs.
No. trades — Number of trades generated by the system.
Win/loss — The percentage of trades that were profitable.
Avg. profit/loss — The average profit/loss for all trades.
Avg. hold time (bars) — The average holding period for 30-minute
bars.
Avg. winning trade — The average profit for winning trades.
Avg. hold time (winners) — The average holding time for winning
trades.
Avg. losing trade — The average loss for losing trades.
Avg. hold time (losers) — The average holding time for losing trades.
Max. consec. win/loss — The maximum number of consecutive win-
ning and losing trades.
Avg. return — The average percentage for the period.
Sharpe ratio — Average return divided by standard deviation of returns
(annualized).
Best return — Best return for the period.
Worst return — Worst return for the period.
Percentage profitable periods — The percentage of periods that
were profitable.
Max. consec. profitable — The largest number of consecutive prof-
itable periods.
Max. consec. unprofitable — The largest number of consecutive
unprofitable periods.
tsl1210 10/8/10 12:58 PM Page 52
ratio data provided by YCharts.com.
Test period: September 2000 to
September 2010.
Test resultsAlthough the 2000s were a lost decade for
the broader index (see the blue buy-and-
hold equity line of the S&P 500 in Figure 1,
p. 50), the split system’s 12-percent annual-
ized gain suggests the 1996 study still has
teeth more than a decade later — and in a
secular bear market, too. The system did
have two losing years (Figure 2, p. 51), but
the drawdown was capped at only -26.5 per-
cent. (The strategy almost seemed to sense
the impending market debacle by increasing
its cash holdings to nearly 35 percent by the
time September 2008 rolled around.)
The system’s attractive annualized profit
was driven primarily by exploiting a small
number of outsized gains. One of the stocks
in this category that was responsible for a
significant portion of the total net profit is
shown in Figure 3 (p. 51). The extraordinary
trajectory of Titanium Metals (TIE), which
split three additional times after entry during
the course of the holding period, produced
26 percent of the system’s total profit (Figure
4). While it’s easy to write off this trade as a
“white swan” event and exclude it from the
results, it’s not at all uncommon to expect at
least one trade like this in a decade. (In the
previous decade, for example, DELL and
YHOO share prices increased by 25 and 30
times, respectively, in the three years after
their splits in the mid- to late 1990s.)
Regardless, even without TIE, the system’s
net profit was still 135 percent, or 9 percent
annualized.
It should be noted the very high win rate,
85.4 percent, is not truly indicative of how
most of the trades would have ended had
they been held for the entire three-year peri-
od. Just more than half the 89 total trades hit
the 5-percent profit stop after attaining a 25-
ACTIVE TRADER • December 2010 • www.activetradermag.com 53
FIGURE 5: MONTE CARLO ANALYSIS
Monte Carlo analysis of all trade candidates (excluding the original test’s
largest gainer, TIE) gets robust marks, producing a minimum decade-long
return of approximately 66 percent.
FIGURE 4: PROFIT BY INSTRUMENT
The secret to the strategy’s return is collecting huge profits on a relatively
few trades. A single trade in TIE accounted for more than a quarter of the
system’s profits.
continued on p. 54
tsl1210 10/14/10 12:35 PM Page 53
percent open profit, and thus fell into the
“win” category. As is usually the case, the
stop sacrificed some return (0.2 percent
annualized) in exchange for reducing
risk. Without the stop, the total number
of trades was reduced to 68, of which 49
(72 percent) were winners.
Although it’s impossible to be certain
without a rigorous back-test using a rotat-
ing list of S&P 500 components, it’s
unlikely survivorship bias significantly
influenced the test results. A little more
than one-fifth of the stocks in the S&P
500 split during the test period, and
because stocks that split are generally
trading at or near all-time highs, it’s
improbable (but not impossible) these
stocks would disappear soon after a split.
Certainly, splits can and do mark peaks of
optimism in a stock’s trading history:
Look no further than GLW on Oct. 4,
2000, the test’s worst trade, with a -86.10
percent loss. Nonetheless, system risk is
controlled in large part by the money-
management rule of allocating 4 percent
of account equity per symbol; the per-
symbol risk can easily be further reduced
(likely at the expense of performance) to
3 percent or less, which would also
increase the number of positions.
Monte Carlo (MC) analysis provides a
better picture of the system’s dynamics
and potential using all 243 raw trades.
Excluding the TIE trade from the analysis,
1,000 MC simulations generated profits
ranging from 65.9 percent to 226 percent
and maximum drawdowns of -12.7 per-
cent to -46.2 percent. Figure 5 (p. 53)
shows the net profit distribution for the
MC simulations, which identified an aver-
age return of about 137 percent. As
expected, this is somewhat less than the
original test results, which include TIE’s
big gain.
With respect to holding period, Figure
6’s optimization results unambiguously
demonstrate that time works to the strate-
gy’s advantage, supporting the suggestion
from the Rice University study that stocks
that split tend to outperform their coun-
terparts for up to three years.
SuggestionsCompanies typically announce stock
splits three or more weeks prior to the ex-
date (the day the split actually takes
place). Following the announcement and
the initial price bump that often accom-
panies the announcement, the excitement
around the upcoming event tends to draw
prices even higher. Because the system
buys at the beginning of the month after a
split, the test results do not reflect partici-
pation in the announcement phase.
To simulate entering trades during this
phase, we conducted a second test that
allowed the strategy to “peek” at splits
occurring the following month. The addi-
tional columns in the Strategy Summary
table (p. 52) show the net profit increased
another 65 percent, or an additional 2.5
percent annualized.
Dividend-adjusted data was used to
produce the test results, but it is interest-
ing to note dividends produced more
than 7.5 percent of the net profit, or
$15,000. With the long holding periods
required by the system, it could make
sense to give priority to an income-pro-
ducing stock over one that generates no
dividends at all.
Bottom lineAlthough this might not be a strategy that
makes the blood surge in the veins of a
die-hard active trader, a strategy of
buying stocks that split shows evidence it
can beat the market in both secular bull
and bear markets over a three-year time
horizon.
Trading System Lab
54 www.activetradermag.com • December 2010 • ACTIVE TRADER
For information on the author, see p. 6.
Trading System Lab strategies are testedon a portfolio basis (unless otherwisenoted) using Wealth-Lab Inc.’s testing plat-form. If you have a system you’d like to seetested, please send the trading andmoney-management rules [email protected].
Disclaimer: The Trading System Lab isintended for educational purposes only toprovide a perspective on different marketconcepts. It is not meant to recommend orpromote any trading system or approach.Traders are advised to do their ownresearch and testing to determine thevalidity of a trading idea. Past performancedoes not guarantee future results; histori-cal testing may not reflect a system’sbehavior in real-time trading.
FIGURE 6: RETURNS FOR DIFFERENT HOLDING PERIODS
An optimization of the system’s holding period shows that it’s generally bet-
ter to give positions plenty of time to accumulate profits.
tsl1210 10/8/10 12:58 PM Page 54
ACTIVE TRADER •• December 2010 •• www.activetradermag.com 55
MM any people get into trad-ing after years in anotherbusiness, but MichaelMarroquin got in early.
Using money saved from odd jobs, heopened a custodial trading account whenhe was just 15 years old, reading the WallStreet Journal and always dabbling insmall-scale stock positions.
In college, he studied finance, but did-n’t necessarily envision a trading career. “Ialways had the interest, but I neverthought I could make a career out of itbecause I didn’t know it was possible,”Marroquin says. He remembers havingonly one class on technical analysis. “Theprofessor basically said, ‘Don’t learn anyof this — it’s all hogwash,’” he remem-bers.
Now a full-time stock trader who reliessolely on technical analysis, Marroquinsays “You have to rewire yourself tounlearn everything you learned inschool.”
After college and some time in gradu-ate school, Marroquin worked at a finan-cial planning firm and earned severalNASD, insurance and real estate licenses.He studied for the certified financialplanner (CFP) designation but realized itwas not the career he wanted to pursue.He realized he wanted to be a trader.
In 2006 he began focusing on bothtrading and real estate. “I had a day-trad-ing account and churned away in 2006and 2007,” he says. “I thought I wasgoing to be a millionaire really fast. Isoon realized that wasn’t going to hap-pen. I was scattered, all over the place, acomplete rookie.”
At that time, Marroquin also startedworking as a residential real estate broker,helping clients purchase distressed andinvestment properties.
“The two careers work well together,”he notes. “I’m a morning trader and haveto have something else to fill my day. Itactually helps me because if I don’t have
something else to do I will become tiredand less focused,” he explains.
Marroquin turned a net profit in 2008,and recalls he thought he was “invinci-ble” after experiencing his first five-figureweek in January of that year.” Lookingback, he says he now sees “it was toomuch, too quick. I started to realize theimportance of working on myself — thepsychological aspects. That was thebeginning of me realizing what real trad-ing is. It is all a giant self-discoveryprocess.”
Trading method: Marroquin typicallyputs on one to 10 trades in a day. Heusually trades the first two hours of theregular day session, which means he’sdone trading by 8:30 a.m. Pacific Time.“My performance goes down the longerI’m sitting there,” he says.
For the first 30 minutes of the sessionhe puts on scalp trades that last five to 15minutes. For the remainder of his tradingtime, he puts on position trades thatmight last 15 minutes to an hour. Hetrades mostly Nasdaq stocks and moni-tors approximately 25 names using five-minute charts, which is his typical entrytimeframe.
Over the years Marroquin has identi-fied several technical patterns he likes touse, including gaps, opening range break-outs or breakdowns, and trend reversals.“I trade each pattern a specific way andmanage each pattern a specific way,” hesays.
Although he has detailed rules,Marroquin admits for him trading is both“an art and a science” and “a lot is subjec-tive and gut,” especially when it comes tohis exit points.
One setup he trades is to identify atrend on a longer timeframe chart (e.g.,15- or 30-minute, or daily) than look fora pullback on the five-minute timeframe.“I look for the pullback to basicallyexhaust,” he says. “I find that momentwhen that upshot (in a downtrend) is get-ting ready to reverse.”
He uses candlestick “tails” (long wicks)
to enter a trend when a pullback isexhausted. “Tails are your best attempt ata trend reversal,” he says. “I enter on thattail when it is happening.” He also moni-tors eight-period, 20-period, 50-period,and 200-period moving averages. In anuptrend, for example, if he sees a stockthat “dips and touches a rising movingaverage in an uptrend,” he’ll enter on afive-minute chart when a long tailappears. He places a stop-loss at the bot-tom of that tail. When it is clear to himthe tail did, in fact, mark the end of apullback, he’ll add to the long position.
For exits, Marroquin says he sellssurges into resistance areas. He alwaysuses a profit target, which is previoussupport or resistance on the five-minutetime frame.
Became profitable when:Marroquin’s turning point came when hestarted working from a written tradingplan. “I found my niche and wrote atrade-management plan, with all mystop-loss criteria.”
“Typically, I have one losing day amonth and it is always for one reason: Ibreak a rule,” he says. “Why do I break arule? Because I haven’t slept well, or myfocus isn’t in the right place.”
Most important lesson: “It’s a busi-ness,” he says. “You really have to learnyour niche and you have to find yourplace. You have to find something youcan be consistent with.”
Best thing about trading: “Beingyour own boss.”
When not trading: He works out atthe gym five or six times a week. “I workout like it is my job,” he says. “Keepingmyself disciplined both physically andmentally helps keep me more disciplinedin my trading.”
He also spends time with his family onthe beach and brews beer. �
The Face of TRADING Trading setup
Hardware: PC with custom-built dual quad
core extreme processors (4 GB each), 16 GB
RAM, six 22-inch LCD monitors
Software: Lightspeed
Internet: Cable modem
Brokerage: Lightspeed
Name: Michael Marroquin
Age:28
Lives in: San Diego, Calif.
Finding a nicheBY ACTIVE TRADER STAFF
face1210 10/8/10 12:06 PM Page 55
There’s an old and probably apocryphal story that
President Harry Truman once voiced a desire for a one-
armed economist so he would no longer have to hear
the words “On the other hand…”
In the world of theory, nuance and interpretation can be
engaging and even enlightening, but in the markets, with real
money at stake, traders are ill-served by anything less than com-
plete objectivity and specificity. But that is often a rare commod-
ity in market literature, for a variety of reasons.
First, while there may be a profitable discretionary trading
approach that could be reverse engineered and expressed in
quantifiable rules, good luck getting an effective explanation
from the system’s trader who doesn’t think in such terms.
Like musicians who are at the top of their profession but who
are unable to effectively communicate what they do, the more
exceptional the talent, the less likely that talent will translate
into exceptional teaching skills; statistically, superstar athletes
have made sub-par coaches. (Contrast that to Phil Jackson, who
has had far more success as the coach of the Chicago Bulls and
Los Angeles Lakers than he ever had as a player.)
Second, master traders, who are even rarer than superstar
athletes, have no incentive to teach what they do outside of,
perhaps, a select group of employees. While a coaching career is
a logical profession for the athlete who can no longer compete
physically — a way to continue earning a living in the sport
based on one’s knowledge of the game — master traders are
unlikely to be compensated as much from teaching others than
by trading directly for themselves. Hence, Steve Cohen and
George Soros do not conduct trading classes at the local com-
munity college.
Which means aspiring private traders are ultimately on their
own to decipher market action and develop profitable strategies.
It’s a difficult process, and it’s not made easier by subjectivity.
After all, what good is advice from a successful trader if it can’t
be translated into an actionable plan?
Statements such as “Take profits when the move appears to
be losing momentum” or “Where you place your stop is a mat-
ter of personal preference” can mean almost anything — or
nothing. What does “losing momentum” mean? Ten traders
might give 10 different answers. What if your “personal prefer-
ence” is to place your stop at such a level that you risk no more
than $100 on a trade, but the market’s random movement virtu-
ally assures a move of at least $200 over the course of two days?
You will have simply guaranteed you will be stopped out with a
loss of almost every trade you make. In the markets, preferences
and opinions bow to market realities.
In some cases, it’s true, such language may simply be a case
of someone who (understandably) doesn’t want to reveal the
specifics of a good technique, someone who isn’t particularly
good at expressing themselves, or the rare “intuitive” trader who
hasn’t quantified certain aspects of his trading style.
Unfortunately, such language is often used by non-trading
promoters who wish to camouflage their lack of knowledge or
practical trading experience. By using vague language and sub-
56 www.activetradermag.com • December 2010 • ACTIVE TRADER
TRADING Basics
The subjectivity trap
Vague concepts and ambiguous guidelines are impossible to translate into
real-world trading ideas. Start with market facts and build from there.
BY ACTIVE TRADER STAFF
basics1210 10/8/10 12:13 PM Page 56
jective ideas, they cannot be pinned down and, thus, they can-
not be proven wrong. Such material is typically accompanied by
chart examples that seem to illustrate the approach’s validity, but
which often give an exaggerated impression of its success by
highlighting rare but infrequent best cases while conveniently
ignoring its more common failures.
Consider a claim that the “XYZ pattern is often followed by a
large up move.” First, has the pattern itself been objectively
defined — i.e., could 100 traders read or program the pattern
rules and identify the same price formations, without exception?
Next, how often is “often”? What constitutes “large”? If you were
going to trade this setup, how do you determine when it has
failed and when to get out of the market? These details need to
accompany a trading idea to make it testable and confirmable. If
the pattern can be objectively defined, it’s relatively easy to find
answers to these questions. It might turn out “large up move”
means a 2-percent gain, on average, over the 20 days following
the pattern, and that “often” means 50.5 percent of the time.
These might not be the answers you were looking for, but an
answer that prevents taking a poor trade is better than a non-
answer that puts you in the market without any indication of a
trade’s expectations.
And while every trader or analyst may not be able to provide
answers to those questions, it is in every trader’s best interest to
look for approaches that provide that specificity. Any trader can
use subjective analysis and apply discretion, but having a foun-
dation of objective statistical information — not to mention
years of experience — will make it much more likely for a trader
to operate successfully in the markets. �
ACTIVE TRADER • December 2010 • www.activetradermag.com 57
basics1210 10/8/10 12:14 PM Page 57
Forms, forms, and more forms. Which form should you
use if you’re a forex trader? Which form is best for secu-
rities traders using the cash method? The different
reporting strategies for the various types of traders make
tax time not so cut-and-dried.
The IRS hasn’t created specialized tax forms for trading busi-
nesses as it has done for just about every other type of business.
For example, other sole-proprietorship businesses report rev-
enues, cost of goods sold, and home-office expenses on
Schedule C. But for traders, only business expenses are reported
on Schedule C. Trading gains and losses are reported on various
forms, depending on the situation (see Table 1).
Securities can be reported on Schedule D (cash method) with
capital losses limited to $3,000 per year; or Form 4797 (Section
475 MTM method) with unlimited business ordinary loss treat-
ment. Futures and forex traders (opting into Section 1256g)
should use Form 6781, unless the futures trader elected Section
475 (in that case, use Form 4797).
In the forex arena, if the trader doesn’t qualify for trader tax
status, by default without an opt-out election he should use line
21 of Form 1040; qualifying traders report on Form 4797. It
can be confusing because the Section 475 MTM and Section
988 elections don’t have tax forms; traders must figure it out on
their own. Don’t forget if you filed a 475 election statement,
existing taxpayers need to follow up with a Form 3115 filing,
too.
With these tax-reporting requirements, the IRS may automati-
cally view a trading business Schedule C as unprofitable even if
it has large net trading gains on other forms; the IRS may audit
sole-proprietorship trading-business tax returns.
Transfer trading gains to Schedule C The most important tax strategy for sole proprietorship business
traders is to transfer some trading gains, if possible, to Schedule
C to zero the income out, but not show a net profit. Showing a
profit could cause the IRS to inquire about a self-employment
(SE) tax, which is otherwise not due for traders who aren’t
60 www.activetradermag.com • December 2010 • ACTIVE TRADER
THE BUSINESS of Trading
Trader tax reporting strategies
As 2010 comes to a close, it’s high time to begin thinking about your year-end tax return.
BY ROBERT A. GREEN, CPA
bot1210 10/8/10 12:22 PM Page 60
members of a futures or options
exchange.
This special income-transfer strategy
also unlocks the home-office deduction
and Section 179 (100-percent) deprecia-
tion deduction, both of which require
income. This strategy isn’t included on
tax forms or form instructions. It’s an
industry-accepted practice to date
designed to deal with insufficient tax
forms for sole-proprietorship trading
businesses, and it must be carefully
explained in footnotes — another impor-
tant strategy for business traders.
Include footnotes Always include well-written tax-return
footnotes. They should explain trader tax
law, why and how the taxpayer qualifies
for trader tax status, whether he or she
elected Section 475 MTM and other trad-
er-tax reporting treatment, such as the
income-transfer strategy. Part-time traders
use footnotes to explain how they allocate
their time between other activities and
trading.
Separate entities can deflect IRS questions The IRS has been challenging trader tax
status more frequently lately, so it’s wise
to consider establishing a separate entity
— such as an LLC, general partnership,
or S-corporation — for your trading busi-
ACTIVE TRADER • December 2010 • www.activetradermag.com 61
continued on p. 62
TABLE 1: IN GOOD FORM
Tax form Who should use it
Schedule D Securities traders using the cash method
Form 1040Forex traders using the Section 988 method who
don’t qualify for trader tax status
Form 4797
Securities and futures traders electing section 475
MTM; forex traders who use the Section 988 method
and qualify for trader tax status
Form 6781Futures traders who did not elect Section 475;
forex traders opting into Section 1256
bot1210 10/8/10 12:24 PM Page 61
The Business of Trading
62 www.activetradermag.com • December 2010 • ACTIVE TRADER
ness. Sole-proprietor business returns
(Schedule C) are very useful after the fact
(meaning after year-end), but forming a
separate legal entity during the year will
make your case stronger. Entities have
several benefits over sole-proprietor
schedule Cs, including the “red-flag” fac-
tor. A partnership tax return Form 1065
shows trading gains, losses, and expenses
on one set of forms, plus the IRS won’t
see the taxpayer’s other activities.
A Form 1065 partnership tax return is
filed for a general partnership or multi-
member LLC choosing to be taxed as a
partnership. Form 1120S is filed for an S-
corporation and a single-member LLC
electing to be taxed as an S-corp. Forms
1065 and 1120S issue Schedule K-1s to
the owners, so taxes are paid at the owner
level rather than at entity level, thereby
avoiding double taxation. Ordinary
income or loss (mostly business expenses)
is summarized on Form 1040 Schedule E
rather than in detail on Schedule C
(hence less IRS attention). Section 179 is
broken out separately on Schedule E, along
with unreimbursed partnership expenses
(UPE) including home-office expenses.
Under the “trading rule,” these are con-
sidered “active” rather than “passive-loss”
activities, so losses are allowed in full
without restriction. Portfolio income is
passed through to Schedule B. Capital
gains and losses are passed through to
Schedule D in summary form, whereas
sole proprietorships must list portfolio
income line by line on the individual tax
return. Pass-through entities draw less IRS
attention than a detailed Schedule C fil-
ing. Net taxes don’t change; they’re still
paid on the individual level.
For more on this topic, see “An in-
depth look at trading entities” (Active
Trader, May 2010).
Don’t botch Schedule D Reporting trading gains and losses prop-
erly can also be a challenge for securities
traders. Failing to follow the tax rules can
lead to IRS questions, jeopardy assess-
ments, and exams.
In 2005, the IRS made a well-publi-
cized effort to clarify Schedule D and D-1
instructions. It reminded taxpayers that
they must list all securities trades line by
line and they could no longer follow prior
industry-accepted summary reporting and
use language including “details available
on request.” The IRS is rightfully con-
cerned that many traders are botching
their tax reporting and sometimes fudging
cost-basis information.
Form 4797 instructions for Section 475
also require line-by-line reporting, but the
IRS didn’t go out of its way to clarify
those rules. With MTM reporting, some
believe summary reporting may still be
acceptable, but play it safe and use line-
by-line reporting if you can. (The best
solution is to use up-to-date software.)
New IRS rules In 2008, the IRS passed a “close the tax
gap” initiative requiring brokerage firms
to significantly improve 1099-B tax infor-
mation reporting for securities transac-
tions starting in 2011. The IRS has been
having problems with securities traders
because many online and direct-access
brokerage firms report minimal required
tax information on 1099-Bs. They only
report proceeds on sales of securities,
ignoring cost basis, short-term vs. long-
term gain or loss, wash sales, and stock-
option sales and purchases.
Some online brokerage firms have been
issuing more complete supplemental
information and tax information reports
(which aren’t sent to the IRS), but often
this information isn’t entirely accurate or
useful for tax-reporting purposes. The
new IRS rules require 1099-Bs to include
adjusted cost basis and short-term vs.
long-term holding periods. Although this
is a big step forward, it doesn’t contain all
the tax information a trader needs. (It still
Related Reading
““Trader tax treatment options””Active Trader, September 2010
It’s not always clear how the IRS
treats the growing number of
instruments traded today. This
review can help.
““Trader tax scams””Active Trader, June 2010
“Dual-entity” trading business
setups might sound attractive, but
these expensive arrangements are
likely to land you in hot water with
the IRS.
““An in-depth look at trading entities””Active Trader, May 2010
When it comes to business entities
for traders, one size doesn’t fit all.
““Are you a trader?””Active Trader, March 2007
Qualifying for trader tax status can
save you money, but IRS rules
regarding it are vague and most
traders miss out on its potential
benefits. Learn how to build a
winning tax position in the eyes
of the IRS.
““Trading business expenses””Active Trader, April 2010
Learn which trading business
expenses are tax deductible,
and which ones aren’t.
Green’s 2010 Trader TaxGuideGreen & Company, Inc.,
January 2010.
This PDF guide includes strategies,
tips, and advice for preparing your
2009 tax return and planning
ahead for the 2010 tax season.
bot1210 10/8/10 12:24 PM Page 62
omits options and also wash sales across
all accounts, for example.)
Futures traders use summary 1099-B
reporting of net (Section 1256 MTM) gain
or loss, and it’s very easy to enter that one
summary number on Form 6781. Forex
is similar only the brokerage should not
issue a 1099.
Claiming trader tax status and preparing returns If you qualify for trader tax status and
haven’t formed a separate legal entity,
you’re classified as a “sole proprietor” or
“unincorporated business.” Report your
trading business expenses on Form 1040
Schedule C (Profit or Loss from Business).
Home-office deductions are reported on
Form 8829. Depreciation and amortiza-
tion are reported on Form 4562. Both
forms require transferring deductions to
Schedule C; income is required for home-
office deductions and Section 179 (100
percent) depreciation. You can use the
transfer strategy mentioned earlier.
Reporting large trading losses on Form 8886 If you have a large trading loss, you may
have to file a Form 8886 (Reportable
Transaction Disclosure Statement). The
instructions mention losses of $2 million
in any single tax year ($50,000 if the loss-
es are from certain foreign currency trans-
actions) or $4 million in any combination
of tax years. If your forex loss is ordinary
under Section 988, the $50,000 rule
applies; however, if your forex transac-
tions have capital gains and loss treat-
ment, the $2 million limitation may
apply.
Tax-preparation programs I recommend using good trading software
to download, match, and properly
account for your active trading in securi-
ties. Some consumer tax-preparation pro-
grams offer trade-import capability, but
many aren’t robust enough for hyperac-
tive traders and some have glitches with
short sales and other trade complications.
Shop carefully for a software program that
will meet your needs as an active trader.
The best trade-accounting programs don’t
handle tax preparation; they only handle
the Schedule D or Form 4797 tax sched-
ules. It’s best to use two different software
programs — one for trade accounting and
one for tax preparation.
It’s also wise to have a trader tax expert
review the results and help reconcile tax
matters with 1099-Bs and more.�This is adapted and updated from Green’s
2010 Trader Tax Guide, available at
www.greencompany.com. For information on
the author, see p. 6.
bot1210 10/11/10 4:05 PM Page 63
64 www.activetradermag.com • December 2010 • ACTIVE TRADER
1 October construction spending
November ISM manufacturing report
FDD: December crude oil, natural gas, gold, silver, copper, plat-
inum, palladium, corn, wheat, soybean products, and oat futures
(CME); December coffee, cocoa, and cotton futures (ICE)
2 FND: December heating oil and RBOB gasoline futures (CME)
3 October factory orders
November employment report ad ISM non-manufacturing report
LTD: January cocoa and December U.S. dollar index options (ICE)
4
5
6 FND: December live cattle futures (ICE)
7 October consumer credit
8 LTD: December cotton futures (ICE)
9 October wholesale inventories
FDD: December live cattle futures (CME)
10 October trade balance
November federal budget
December University of Michigan consumer sentiment
LTD: January coffee options (ICE)
11
12
13 LTD: December forex futures; December U.S. dollar index futures
(ICE)
14 October business inventories
November PPI and retail sales
FND: December U.S. dollar index futures (ICE)
LTD: December corn, wheat, soybean products, and oat futures
(CME); January sugar options (ICE)
15 September production and capacity utilization
November CPI
FDD: December forex futures; December U.S. dollar index futures
(ICE)
LTD: December cocoa futures (ICE); January crude oil and plat-
inum options (CME)
LEGEND
CME: Chicago Mercantile Exchange
CPI: Consumer price index
ECI: Employment cost index
FDD (first delivery day): The first
day on which delivery of a commodity
in fulfillment of a futures contract can
take place.
FND (first notice day): Also known
as first intent day, this is the first day
on which a clearinghouse can give
notice to a buyer of a futures contract
that it intends to deliver a commodity
in fulfillment of a futures contract. The
clearinghouse also informs the seller.
FOMC: Federal Open Market
Committee
GDP: Gross domestic product
ISM: Institute for Supply Management
LTD (last trading day): The final
day trading can take place in a futures
or options contract.
PMI: Purchasing managers index
PPI: Producer price index
Quadruple witching Friday: A day
where equity options, equity futures,
index options, and index futures all
expire.
TRADING CalendarDecember 2010
S M T W T F S
28 29 30 1 2 3 4
5 6 7 8 9 10 11
12 13 14 15 16 17 18
19 20 21 22 23 24 25
26 27 28 29 30 31 1
calendar1210 10/8/10 12:09 PM Page 64
16 November housing starts
December Philadelphia fed survey
17 November leading indicators
LTD: December index futures; December single stock futures (OC);
January orange juice and cotton options (ICE); January index and
equity options
18
19
20 November Chicago fed national activity index
LTD: January crude oil futures (CME); December coffee futures
(ICE)
21
22 Q3 GDP (third estimate)
November existing home sales
FND: January crude oil futures (CME)
23 November personal income, durable goods, and new home sales
LTD: January soybean and soybean product futures (CME)
24 Markets closed — Christmas holiday
25
26
27
28 December consumer confidence
LTD: January natural gas futures (CME); January heating oil, RBOB
gasoline, gold, silver, and copper options (CME)
29 FND: January natural gas futures (CME)
LTD: December gold, silver, copper, platinum, and palladium
futures (CME)
30 December Chicago PMI
31 FND: January gold, silver, copper, platinum, palladium, and soy-
bean futures (CME)
LTD: January heating oil, RBOB gasoline, and December live cattle
futures (CME)
ACTIVE TRADER • December 2010 • www.activetradermag.com 65
Report times
Economic Release release time (ET)
GDP 8:30 a.m.
CPI 8:30 a.m.
ECI 8:30 a.m.
PPI 8:30 a.m.
Productivity and costs 8:30 a.m.
Employment 8:30 a.m.
Personal income 8:30 a.m.
Business inventories 8:30 a.m.
Durable goods 8:30 a.m.
Retail sales 8:30 a.m.
Trade balance 8:30 a.m.
Housing starts 8:30 a.m.
Chicago Fed
national activity index 8:30 a.m.
Production
& capacity utilization 9:15 a.m.
Leading indicators 10 a.m.
Consumer confidence 10 a.m.
University of Michigan
consumer sentiment 10 a.m.
Wholesale inventories 10 a.m.
Philadelphia Fed survey 10 a.m.
Existing home sales 10 a.m.
Construction spending 10 a.m.
Chicago PMI report 10 a.m.
ISM report on business 10 a.m.
ISM non-manufacturing report
on business 10 a.m.
New home sales 10 a.m.
Factory orders 10 a.m.
Federal budget 2 p.m.
Consumer credit 3 p.m.
The information on this page is subject to
change. Active Trader is not responsible
for the accuracy of calendar dates beyond
press time.
calendar1210 10/14/10 2:28 PM Page 65
FIGURE 2: PAYROLLS VS. UNEMPLOYMENT RATE
Non-farm payrolls declined in September, but to a lesser extent than inAugust.
Source: Bureau of Labor Statistics Seasonally adjusted
U.S. economic briefing
FIGURE 1: QUARTERLY GDP PERFORMANCE
The third estimate of Q2 GDP extended the previous quarter's contraction.
Source: Bureau of Economic Analysis
FAMILIAR ILLS CONTINUE TO PLAGUE RECOVERY
Meeting: Federal Open Market Committee
Date and time: Sept. 21 at 2:15 p.m.
Summary: The FOMC left key lending rates
unchanged, leaving the target range for the
federal funds rate untouched at 0 to 0.25 per-
cent. Unemployment continues to drag on the
economy, the committee wrote in its release:
“Household spending is increasing gradually,
but remains constrained by high unemploy-
ment, modest income growth, lower housing
wealth, and tight credit.”
The following tables compare the S&P
500’s daily and weekly responses to economic
releases, as well as historical post-announce-
ment behavior since 1997 (or earlier). The
S&P fell 0.3 percent on the date of the com-
mittee’s announcement. Historically, the S&P
has risen nearly 4 percent on FOMC rate
announcement.
66 www.activetradermag.com • December 2010 • ACTIVE TRADER
FIGURE 3: OVERALL VS. “CORE” INFLATION
Price levels stabilized more during the summer months.
Source: Bureau of Labor Statistics Not seasonally adjusted
THE Economy
REVISED SLIGHTLY HIGHER
ReportGross domestic product for
Q2 2010 (third estimate)
Date/time Sept. 30 at 8:30 a.m.
Actual 1.7%
Previous 1.6%
Consensus 1.6%
S&P 500 reaction
Historical moves since ‘94
Report day -0.31% 0.04%
Five dayslater
1.33% 0.33%
RATE CHANGES
S&P 500 reaction
Historical moves since ‘94
Report day -0.26% 0.35%
Five dayslater
-0.05% 0.43%
snapshots-1210 10/13/10 10:01 AM Page 66
The S&P rose
throughout
September, but was
somewhat subdued
on release dates.
Source: eSignal
FIGURE 6: MARKET REACTION TO ECONOMIC REPORTS
The S&P remained fairly stable on economic release dates in September andearly October.
ACTIVE TRADER • December 2010 • www.activetradermag.com 67
FIGURE 4: ISM MANUFACTURING INDEX
Manufacturing sentiment fell slightly in September but remained positive(above 50).
Source: Institute of Supply Management Seasonally adjusted
FIGURE 5: S&P 500
CONSUMER PRICES INCREASE IN AUGUSTReport Consumer Price Index (CPI)
Date/time Sept. 17 at 8:30 a.m.
Actual 0.3% (core 0.0%)
Previous 0.3% (core 0.1%)
Consensus 0.2% (core 0.1%)
S&P 500 reaction
Historical moves since ‘80
Report day 0.08% 0.08%
Five dayslater
0.02% 0.14%
Report Producer Price Index (PPI)
Date/time Sept. 16 at 8:30 a.m.
Actual 0.4% (core 0.1%)
Previous 0.2% (core 0.3%)
Consensus 0.3% (core 0.1%)
S&P 500 reaction
Historical moves since ‘94
Report day -0.04% 0.06%
Five dayslater
0.82% 0.31%
PAYROLLS TAKE A HITReport Employment
Date/time Oct. 8 at 8:30 a.m.
Non-farm payrolls
Actual -94K
Previous -57K
Consensus 0K
Unemployment rate
Actual 9.6%
Previous 9.6%
Consensus 9.7%
S&P 500 reaction
Historical moves since ‘94
Report day 0.61% 0.12%
Five dayslater
0.95% -0.09%
ISM FALLS TO 10-MONTH LOWReport ISM manufacturing index
Date/time Oct. 1 at 10 a.m.
Actual 54.4
Previous 56.3
Consensus 54.8
S&P 500 reaction
Historical moves since ‘97
Report day 0.44% 0.27%
Five dayslater
1.48% 0.22%
snapshots-1210 10/18/10 9:11 AM Page 67
68 www.activetradermag.com • December 2010 • ACTIVE TRADER
STOCKS Snapshot as of Oct. 6
1-year 10-day 20-day 60-day Volatility Stock Symbol Volume return move/rank move/rank move/rank ratio/rankPositive one-year performanceLas Vegas Sands LVS 27.04 M 97.48% 9.23% / 40% 14.31% / 45% 50.60% / 86% .34 / 40%
Ford Motor F 57.45 M 84.40% 6.95% / 94% 12.20% / 68% 13.55% / 64% .43 / 80%
SanDisk SNDK 12.97 M 75.71% 4.39% / 33% -0.51% / 3% -18.35% / 66% .20 / 8%
Apple AAPL 19.42 M 52.79% 0.50% / 0% 9.99% / 64% 14.85% / 54% .30 / 28%
Xerox XRX 12.68 M 41.13% 5.29% / 20% 20.00% / 77% 24.45% / 74% .25 / 20%
Altria Group MO 15.28 M 36.86% 2.35% / 37% 4.18% / 33% 14.48% / 80% .17 / 23%
Oracle ORCL 44.88 M 32.60% 1.40% / 0% 14.25% / 71% 16.32% / 81% .13 / 5%
Vale VALE 20.57 M 30.40% 12.66% / 82% 18.70% / 100% 27.94% / 98% .57 / 88%
Texas Instruments TXN 14.80 M 25.65% 11.28% / 94% 19.55% / 97% 11.50% / 67% .69 / 70%
Bristol Myers Squibb BMY 12.15 M 21.71% -2.26% / 33% 1.64% / 27% 7.43% / 54% .25 / 50%
Fifth Third Bancorp FITB 11.22 M 21.22% 1.99% / 15% 5.86% / 56% -10.30% / 56% .30 / 25%
Corning GLW 14.83 M 18.60% 6.99% / 70% 9.94% / 57% 3.55% / 41% .38 / 37%
The Home Depot HD 11.40 M 18.04% 2.78% / 15% 7.78% / 66% 10.82% / 33% .13 / 17%
Verizon Communications VZ 17.75 M 14.40% 2.99% / 5% 9.52% / 55% 24.06% / 98% .21 / 15%
Merck MRK 12.09 M 14.12% 0.14% / 0% 3.35% / 58% 1.54% / 22% .21 / 23%
Comcast CMCSA 22.47 M 13.48% -1.06% / 57% -0.89% / 7% -6.62% / 95% .43 / 25%
News Corp. NWSA 17.83 M 11.68% -0.15% / 0% 2.28% / 14% 1.79% / 20% .50 / 97%
EMC EMC 25.44 M 10.67% -5.11% / 100% -1.94% / 10% -1.45% / 32% .61 / 63%
AT&T T 25.84 M 10.33% 0.10% / 0% 4.49% / 36% 14.71% / 86% .16 / 5%
Marvell Technology Group MRVL 16.11 M 10.20% -4.65% / 100% -5.58% / 19% -5.36% / 14% .29 / 78%
Lowe's LOW 11.58 M 9.10% 4.18% / 53% 5.25% / 56% 7.14% / 33% .21 / 68%
American Express AXP 12.87 M 8.69% -11.15% / 100% -5.12% / 52% -13.92% / 100% 1.13 / 100%
QUALCOMM QCOM 18.19 M 7.72% 3.12% / 10% 9.12% / 52% 24.20% / 80% .12 / 3%
General Electric GE 57.27 M 4.19% 2.42% / 33% 7.64% / 46% 11.11% / 53% .30 / 73%
Taiwan Semiconductor TSM 14.53 M 3.83% 5.10% / 79% 8.19% / 90% 1.58% / 38% .75 / 98%
Pfizer PFE 42.33 M 3.35% 0.23% / 5% 4.23% / 15% 16.70% / 77% .17 / 35%
Negative one-year performance
Research In Motion RIMM 19.77 M -30.08% 0.80% / 0% 7.48% / 57% -13.64% / 21% .16 / 32%
Nokia NOK 24.79 M -27.29% 5.33% / 29% 7.94% / 26% 22.31% / 92% .39 / 93%
Petroleo Brasileiro SA PBR 23.12 M -26.03% 1.09% / 15% -3.97% / 23% -1.43% / 3% .41 / 87%
The Charles Schwab SCHW 12.08 M -25.28% 4.55% / 80% 3.79% / 33% -2.33% / 9% .23 / 80%
Adobe Systems ADBE 15.94 M -25.05% -3.52% / 0% -12.21% / 79% -8.47% / 37% .18 / 33%
NVIDIA NVDA 20.92 M -22.94% -5.36% / 100% 4.46% / 18% -1.28% / 4% .37 / 92%
Bank of America BAC 145.49 M -22.74% -0.22% / 0% 0.15% / 5% -14.55% / 53% .16 / 32%
Seagate Technology STX 14.09 M -22.47% 3.51% / 30% 4.08% / 38% -20.54% / 28% .13 / 53%
Morgan Stanley MS 13.99 M -20.54% 1.72% / 20% -2.27% / 32% -1.09% / 11% .28 / 32%
Yahoo YHOO 23.51 M -17.41% 3.42% / 58% 5.60% / 53% -6.44% / 18% .19 / 45%
Dell DELL 25.61 M -16.43% 6.79% / 94% 5.42% / 48% 0.15% / 0% .45 / 100%
Alcoa AA 25.26 M -13.80% 5.73% / 40% 11.74% / 69% 12.45% / 70% .29 / 67%
Hewlett-Packard HPQ 27.32 M -12.31% 3.01% / 50% 4.97% / 50% -12.89% / 57% .21 / 50%
JPMorgan Chase JPM 34.49 M -11.92% -0.10% / 11% 1.99% / 19% -1.43% / 11% .39 / 50%
Applied Materials AMAT 22.69 M -10.32% 5.11% / 47% 10.87% / 87% -6.31% / 22% .19 / 20%
Wells Fargo WFC 36.44 M -9.47% 1.90% / 0% 4.28% / 37% -5.87% / 17% .26 / 42%
Symantec SYMC 13.82 M -9.18% 0.13% / 0% 2.40% / 3% -0.33% / 2% .28 / 57%
Exxon Mobil XOM 20.87 M -7.40% 4.05% / 95% 5.25% / 74% 7.61% / 88% .50 / 100%
Cisco Systems CSCO 57.11 M -5.79% 2.91% / 38% 8.04% / 70% -3.42% / 9% .18 / 23%
Microsoft MSFT 61.06 M -4.83% -0.73% / 22% 2.09% / 17% -2.79% / 9% .21 / 63%
Intel INTC 67.49 M -2.87% 1.58% / 19% 7.88% / 83% -8.09% / 45% .15 / 5%
eBay EBAY 14.32 M -1.45% 0.45% / 0% -0.49% / 11% 16.37% / 75% .18 / 40%
US Bancorp USB 13.09 M -0.84% -0.49% / 0% 0.40% / 0% -8.27% / 45% .33 / 58%
United States Steel X 12.93 M -0.09% 1.36% / 0% -8.34% / 90% 3.50% / 13% .26 / 52%
Active Trader’s Snapshot tables summarize the trading activity in the most actively traded stocks, ETFs, and futures. The information does NOT con-stitute trade signals. It is intended only to provide a synopsis of each market’s liquidity, direction, and levels of momentum and volatility.
snapshots-1210 10/8/10 4:07 PM Page 68
Leverage: “2x” = double leverage; “3x” =triple leverage.
Volume: 30-day average daily volume.
1-year return: The percentage price movefrom the close one year ago (250 trading days)to today’s close.
10-day move: The percentage price movefrom the close 10 days ago to today’s close.
20-day move: The percentage price movefrom the close 20 days ago to today’s close.
60-day move: The percentage price movefrom the close 60 days ago to today’s close.
The “Rank” fields for each time window (10-daymoves, 20-day moves, etc.) show the percentilerank of the most recent move to a certain num-ber of the previous moves of the same size andin the same direction. For example, the “Rank”for 10-day move shows how the most recent10-day move compares to the past twenty 10-day moves; for the 20-day move, the “Rank”field shows how the most recent 20-day movecompares to the past sixty 20-day moves; for the60-day move, the “Rank” field shows how themost recent 60-day move compares to the pastone-hundred-twenty 60-day moves. A reading
of 100 percent means the current reading islarger than all the past readings, while a readingof 0 percent means the current reading is small-er than all previous readings. These figures pro-vide perspective for determining how relativelylarge or small the most recent price move is com-pared to past price moves.
Volatility ratio/rank: The ratio is the short-term volatility (10-day standard deviation ofprices) divided by the long-term volatility (100-day standard deviation of prices). The rank isthe percentile rank of the volatility ratio overthe past 60 days.
1-year 10-day 20-day 60-day Volatility
ETF Symbol Leverage Inverse Volume return move/rank move/rank move/rank ratio/rank
Positive one-year performanceUltra QQQ ProShares QLD 2x 6.48 M 31.13% 2.21% / 0% 13.68% / 53% 17.57% / 52% .23 / 15%
iShares DJ US Real Est. Index Trust IYR 10.86 M 29.67% 0.65% / 0% 1.69% / 14% 8.54% / 52% .28 / 12%
iShares Silver Trust SLV 11.61 M 29.51% 9.55% / 100% 16.36% / 98% 27.33% / 100% .46 / 50%
SPDR Gold Trust GLD 12.56 M 27.18% 4.45% / 100% 7.42% / 100% 11.36% / 87% .46 / 92%
S&P Select Cons. Disc. SPDR Fund XLY 7.20 M 21.72% 2.51% / 25% 5.81% / 45% 8.46% / 44% .27 / 32%
S&P Select Industrial SPDR Fund XLI 17.05 M 20.85% 3.03% / 42% 6.10% / 49% 10.38% / 56% .32 / 43%
Market Vectors Gold Miners ETF GDX 9.28 M 19.37% 3.10% / 42% 8.29% / 83% 15.34% / 77% .31 / 33%
S&P Select Retail SPDR Fund XRT 10.51 M 19.24% 3.50% / 5% 8.89% / 68% 11.84% / 41% .24 / 35%
iShares MSCI Hong Kong Index EWH 6.68 M 18.38% 4.80% / 30% 11.21% / 86% 19.99% / 92% .27 / 38%
Vanguard Emer. Markets Stock ETF VWO 12.85 M 18.37% 5.77% / 80% 10.35% / 89% 15.38% / 91% .36 / 62%
PowerShares QQQ Trust QQQQ 77.13 M 16.55% 1.11% / 0% 6.44% / 53% 8.60% / 55% .21 / 7%
ProShares Ultra S&P 500 SSO 2x 16.05 M 16.46% 4.44% / 37% 11.15% / 57% 11.70% / 49% .33 / 67%
iShares MSCI Emerging Market EEM 55.20 M 15.75% 5.71% / 75% 10.08% / 84% 14.91% / 90% .38 / 68%
iShares Russell 2000 Index Trust IWM 59.89 M 13.01% 4.21% / 58% 8.08% / 69% 6.87% / 34% .43 / 78%
Diamonds Trust DIA 6.46 M 12.11% 2.21% / 20% 5.57% / 64% 5.82% / 56% .28 / 25%
iShares MSCI Taiwan Index EWT 10.50 M 11.35% 3.94% / 45% 9.40% / 84% 14.04% / 92% .21 / 27%
Semiconductor HOLDRS SMH 14.38 M 11.12% 6.05% / 78% 10.37% / 83% -1.10% / 10% .40 / 52%
S&P Select Technology SPDR Fund XLK 10.54 M 11.02% 2.07% / 5% 6.97% / 54% 6.33% / 53% .24 / 12%
iShares MSCI Brazil Index Fund EWZ 17.49 M 9.69% 7.14% / 75% 11.56% / 84% 17.50% / 89% .44 / 90%
S&P Select Consumer Staples SPDR XLP 6.95 M 9.16% 1.36% / 26% 3.41% / 58% 5.30% / 66% .24 / 30%
S&P Select Utilities SPDR Fund XLU 6.69 M 9.01% 1.18% / 43% 1.21% / 20% 5.63% / 58% .19 / 13%
S&P Depository Receipts SPY 199.01 M 8.84% 2.30% / 37% 5.09% / 55% 5.81% / 51% .32 / 58%
S&P Select Materials SPDR Fund XLB 8.91 M 7.79% 3.19% / 53% 3.86% / 33% 10.13% / 73% .29 / 50%
iShares Barclays 20+ Year T-Bond TLT 8.53 M 7.55% 0.91% / 11% 0.67% / 8% 7.35% / 53% .21 / 17%
Small Cap Bull 3x Shares TNA 3x 13.70 M 7.50% 13.38% / 58% 25.76% / 70% 16.93% / 24% .42 / 100%
S&P Select Health Care SPDR Fund XLV 6.74 M 7.06% 0.72% / 0% 5.04% / 69% 4.90% / 64% .25 / 30%
iShares FTSE/Xinhua China 25 FXI 17.18 M 3.53% 4.81% / 80% 8.64% / 92% 8.27% / 84% .49 / 72%
S&P Select Energy SPDR Fund XLE 15.16 M 3.06% 6.41% / 85% 7.58% / 77% 9.08% / 80% .61 / 100%
iShares MSCI EAFE Index Trust EFA 19.46 M 2.50% 4.08% / 50% 8.68% / 73% 11.62% / 85% .29 / 53%
iShares MSCI Japan Index Fund EWJ 18.52 M 1.91% 3.68% / 79% 4.54% / 82% 5.63% / 88% .60 / 100%
Negative one-year performanceSmall Cap Bear 3X Shares TZA 3x yes 25.13 M -58.00% -13.89% / 60% -23.64% / 67% -28.06% / 60% .31 / 12%
United States Natural Gas Fund UNG 22.52 M -48.55% -5.80% / 55% -3.14% / 14% -16.04% / 26% .27 / 33%
Large Cap Bear 3x Shares BGZ 3x yes 7.04 M -43.00% -7.45% / 32% -16.48% / 59% -21.63% / 62% .22 / 7%
ProShares UltraPro Short S&P500 SPXU 3x yes 7.97 M -41.38% -7.26% / 32% -16.14% / 59% -20.87% / 60% .22 / 7%
UltraShort Russell 2000 ProShares TWM 2x yes 7.97 M -39.71% -9.33% / 60% -16.17% / 68% -18.12% / 54% .35 / 20%
Financial Bear 3x Shares FAZ 3x yes 47.89 M -36.80% -5.87% / 21% -11.47% / 48% -9.02% / 27% .29 / 23%
UltraShort QQQ ProShares QID 2x yes 13.64 M -36.74% -2.88% / 0% -13.02% / 56% -18.26% / 68% .16 / 2%
UltraShort 20+ Year Tr. ProShares TBT 2x yes 10.62 M -29.66% -2.88% / 30% -2.92% / 15% -17.76% / 58% .14 / 20%
UltraShort S&P 500 ProShares SDS 2x yes 33.11 M -27.71% -4.83% / 32% -11.00% / 59% -13.90% / 60% .24 / 8%
UltraShort Financials ProShares SKF 2x yes 6.56 M -21.84% -4.09% / 29% -7.80% / 46% -4.39% / 21% .32 / 27%
Financial Bull 3x Shares FAS 3x 36.01 M -19.10% 4.13% / 8% 9.45% / 38% -3.73% / 7% .31 / 92%
ProShares Ultra DJ-UBS Crude Oil UCO 2x 6.40 M -5.19% 23.56% / 100% 18.61% / 86% 10.04% / 55% 1.10 / 100%
S&P Select Financials SPDR Fund XLF 79.97 M -2.58% 1.45% / 17% 2.72% / 28% -1.14% / 8% .37 / 70%
United States Oil Fund USO 9.67 M -1.09% 11.36% / 100% 9.47% / 85% 4.43% / 53% 1.04 / 100%
ACTIVE TRADER • December 2010 • www.activetradermag.com 69
ETF Snapshot as of Oct. 6
snapshots-1210 10/8/10 4:07 PM Page 69
70 www.activetradermag.com • December 2010 • ACTIVE TRADER
Open 10-day 20-day 60-day Volatility
Market Symbol Exchange Volume interest move/rank move/rank move/rank ratio/rank
E-Mini S&P 500 ES CME 1.96 M 2.44 M 2.30% / 32% 5.14% / 58% 6.06% / 52% .31 / 57%
10-yr. T-note TY CME 1.26 M 1.57 M 1.48% / 33% 2.33% / 65% 4.80% / 77% .24 / 60%
5-yr. T-note FV CME 469.4 866.3 0.80% / 33% 1.57% / 73% 2.63% / 65% .21 / 50%
Crude oil CL CME 350.6 283.4 11.40% / 100% 11.46% / 91% 7.88% / 46% .89 / 100%
EUR/USD EC CME 318.3 190.1 4.07% / 45% 9.50% / 100% 9.66% / 96% .39 / 73%
E-Mini Nasdaq 100 NQ CME 310.6 330.8 1.25% / 0% 6.75% / 57% 8.78% / 56% .19 / 0%
30-yr. T-bond US CME 347.1 622.7 1.54% / 30% 1.66% / 30% 7.28% / 64% .20 / 33%
2-yr. T-note TU CME 204.4 660.9 0.05% / 40% 0.11% / 96% 0.15% / 39% .22 / 72%
Eurodollar* ED CME 210.8 810.0 0.09% / 38% 0.23% / 60% 0.66% / 43% .07 / 35%
Mini Dow YM CME 129.6 75.3 2.18% / 20% 4.95% / 62% 6.01% / 61% .27 / 27%
E-Mini Russell 2000 TF CME 141.1 362.8 4.45% / 65% 8.27% / 73% 7.17% / 27% .45 / 78%
JPY/USD JY CME 133.2 122.5 1.93% / 30% 1.31% / 26% 6.77% / 58% .19 / 37%
Gold 100 oz. GC CME 110.5 399.3 4.30% / 95% 7.17% / 100% 11.06% / 84% .42 / 92%
Corn C CME 185.9 694.2 -3.29% / 50% 5.62% / 20% 30.17% / 73% .30 / 20%
GBP/USD BP CME 108.5 95.6 1.44% / 47% 2.63% / 47% 4.82% / 41% .14 / 5%
AUD/USD AD CME 86.2 117.9 2.34% / 25% 5.62% / 69% 10.84% / 87% .18 / 8%
Natural gas NG CME 106.9 154.5 -2.55% / 36% 1.34% / 20% -11.23% / 17% .23 / 28%
CAD/USD CD CME 85.1 89.7 2.09% / 56% 2.51% / 63% 2.15% / 47% .55 / 75%
Soybeans S CME 73.5 260.9 -2.43% / 67% 1.28% / 16% 6.73% / 48% .52 / 80%
Sugar SB ICE 61.8 263.9 1.51% / 11% 10.10% / 37% 37.10% / 61% .24 / 32%
Wheat W CME 44.7 232.6 -8.53% / 82% -7.43% / 50% 19.85% / 33% .20 / 30%
CHF/USD SF CME 40.8 52.8 2.71% / 60% 5.43% / 89% 9.91% / 66% .17 / 33%
Soybean oil BO CME 20.4 54.7 2.12% / 5% 6.06% / 46% 15.15% / 85% .21 / 5%
Heating oil HO CME 46.4 60.5 9.53% / 100% 10.86% / 77% 12.72% / 77% .89 / 98%
RBOB gasoline RB CME 43.9 63.3 13.38% / 100% 11.16% / 96% 3.54% / 28% .95 / 100%
Silver 5,000 oz. SI CME 35.1 90.1 9.44% / 95% 15.16% / 98% 26.21% / 98% .42 / 35%
S&P 500 index SP CME 26.6 267.8 2.29% / 32% 5.13% / 58% 6.06% / 52% .31 / 57%
E-Mini S&P MidCap 400 ME CME 30.3 90.1 2.93% / 40% 6.14% / 57% 7.24% / 44% .35 / 50%
Copper HG CME 25.9 86.3 5.27% / 75% 7.21% / 63% 24.37% / 95% .20 / 35%
Soybean meal SM CME 17.0 38.4 -3.40% / 38% -2.09% / 60% -0.40% / 10% .68 / 98%
MXN/USD MP CME 29.9 91.3 1.59% / 32% 3.91% / 88% 1.98% / 27% .33 / 58%
U.S. dollar index DX ICE 20.7 25.0 -3.05% / 50% -6.36% / 100% -7.15% / 96% .29 / 64%
Coffee KC ICE 12.1 89.9 -2.45% / 0% -9.77% / 100% 5.98% / 24% .26 / 60%
Crude oil e-miNY QM CME 12.7 4.9 11.41% / 100% 11.45% / 91% 7.87% / 49% .93 / 100%
Nikkei 225 index NK CME 10.5 29.8 2.48% / 19% 6.53% / 89% 0.57% / 11% .31 / 85%
Live cattle LC CME 19.4 87.1 -1.38% / 47% -2.47% / 58% 4.29% / 14% .23 / 43%
Lean hogs LH CME 14.1 55.2 -4.35% / 86% -1.34% / 21% -5.14% / 54% .51 / 85%
Cocoa CC ICE 8.6 65.5 -0.65% / 11% 0.29% / 0% -9.89% / 82% .35 / 38%
NZD/USD NE CME 8.1 23.2 2.20% / 65% 3.61% / 67% 4.62% / 73% .32 / 47%
Mini-sized gold YG CME 3.4 4.9 4.45% / 100% 7.47% / 100% 11.39% / 87% .45 / 92%
E-Mini EUR/USD ZE CME 4.3 3.5 4.07% / 45% 9.50% / 100% 9.66% / 96% .39 / 73%
Fed Funds** FF CME 3.0 61.0 0.02% / 90% 0.02% / 22% 0.07% / 3% .08 / 85%
Mini-sized silver YI CME 2.0 2.6 9.56% / 100% 16.33% / 98% 26.98% / 99% .45 / 46%
Feeder cattle FC CME 0.9 5.0 -0.05% / 5% -2.59% / 74% -3.89% / 95% .42 / 53%
Natural gas e-miNY QG CME 1.8 2.8 -2.52% / 45% 1.31% / 27% -11.25% / 22% .23 / 25%
Nasdaq 100 ND CME 1.5 13.7 1.25% / 0% 6.75% / 54% 8.78% / 56% .19 / 0%
Dow Jones Ind. Avg. DJ CME 0.6 5.1 2.18% / 20% 5.62% / 72% 6.01% / 61% .27 / 27%
Note: Average volume and open-interest data includes both pit and side-by-side electronic contracts (where applicable). Price activity for CME
futures is based on pit-traded contracts. Volume figures are for the most-active contract month in a particular market and may not reflect total
volume for all contract months. *Average volume and open interest based on highest-volume contract (September 2011). **Average volume
and open interest based on highest-volume contract (February 2011).
This information is for educational purposes only. Active Trader provides this data in good faith, but it cannot guarantee its accuracy or timeliness.
Active Trader assumes no responsibility for the use of this information. Active Trader does not recommend buying or selling any market, nor does it solicit orders to buy or
sell any market. There is a high level of risk in trading, especially for traders who use leverage. The reader assumes all responsibility for his or her actions in the market.
FUTURES Snapshot as of Oct. 6
snapshots-1210 10/8/10 4:07 PM Page 70
Trading Strategies continued from p. 19
72 www.activetradermag.com • December 2010 • ACTIVE TRADER
one early signal on Jan. 27. Patterns 1 and 2 issues repeated
early signals — and, it must be noted, triggered on May 5, the
day before the flash crash. Although on a closing basis, the loss-
es would not have been disastrous, these trades would have
experienced massive intraday drawdowns on May 6.
Risk control and money managementIt is important that no attempt was made to optimize the pat-
tern, and no stop-losses or other risk controls were introduced
in testing. It is safe to assume that adding risk controls would
have reduced the patterns’ drawdowns, while also curbing their
winning percentages and total profits.
Also, the money management approach used in the test — a
fixed-dollar trade size — will exacerbate the drawdowns during
prolonged and severe market
declines. As price drops dra-
matically — as it did in late
2008, for example — more
shares are purchased per sig-
nal because of the lower
stock price. During a brief
and not-too-severe decline,
this will not present too much
of a problem, but when an
initial decline is followed by
an even greater decline, trig-
gering repeated signals and
ever-larger trades, the losses
will mount with almost geo-
metric speed. This drawback
could be countered by using a
different approach, such as
adjusting position size according to account equity: As the
account equity declines, the number of shares purchased will
decrease. However, this will also likely mitigate the patterns’
obvious tendency to bounce back quickly from losses because
trade sizes will be smaller when the market is rebounding.
The lesson of the pattern: Over time, sharp sell-offs such as
those identified by this price model are buying opportunities in
the S&P. Taking advantage of them, however, requires both
financial wherewithal and psychological fortitude. Pattern 3 had
the smallest drawdowns because it entered much more selective-
ly than the other pattern variations — it tended to avoid enter-
ing too early in most down moves, and when it did, it was less
likely to enter repeatedly, which resulted in relatively smaller
trade sizes for losing trades. Although it ended the analysis peri-
od with the lowest total equity, its return was far superior on a
risk-adjusted basis.
Pattern 3’s greater stability and relative outperformance also
hint at the benefits of incorporating comparisons of non-consec-
utive price bars. Finally, traders who don’t want to sit through
huge losses during market down swings must incorporate stop-
losses and appropriate money management. �
FIGURE 6: SIGNAL COMPARISON
Pattern 3’s superior performance can be attributed to its more selective entries. The first
two pattern variations often entered repeatedly as the market continued to decline,
resulting in exceptionally large drawdowns.
KC Go to “Key concepts” on
p. 78 for more information about:
• Average and median
• Variance and standard
deviation
etzkorn1210.qxd 10/12/10 1:17 PM Page 72
The Evolution of
Technical Analysis:
Financial Prediction
from Babylonian
Tablets to
Bloomberg
Terminals
By Andrew W. Lo
and Jasmina
Hasanhodzic
Hardcover, 212 pages
Bloomberg Press/Wiley
A history of the evolution of technical
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modity pricing methods in Babylon) to
the Internet age. The authors explore the
history of technical analysis, including:
the origins of the field, Eastern practices
of China and Japan vs. Western methods,
and the contributions of pioneers such as
Charles Dow, Munehisa Homma,
Humphrey B. Neill, and William D.
Gann. The book also traces where techni-
cal analysts failed, how they succeeded,
and what it means for today’s traders and
investors.
The Little Book of
Currency Trading:
How to Make Big
Profits in the World
of Forex
By Kathy Lien
Hardcover
192 pages
John Wiley & Sons
This book is designed to show you how
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moving foreign exchange market. The
author explains the forces that drive cur-
rencies, how to use various currencies to
reduce risk and take advantage of global
trends, and provides trading strategies
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Volatility Indicators: Techniques for
Profiting from the Market’s Moves
By Lee Leibfarth and Jean Folger
E-book (PDF format)
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In this eBook,
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volatility and
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“harness its
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book illustrates how different volatility
indicators are constructed, how to use
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Getting Started in
Hedge Funds: From
Launching a Hedge
Fund to New
Regulation, the Use
of Leverage, and Top
Manager Profiles
(3rd Edition)
By Daniel A.
Strachman
Paperback, 208 pages
December 2010
John Wiley & Sons
This is the latest edition of the book on
hedge fund basics, updated to reflect
today’s “post-crisis industry.” In the wake
of Ponzi schemes and insider trading
scandals — as well as the loss of billions
of dollars in assets under management
because of fund closures — the author
focuses on the current state of the indus-
try: how hedge funds did or did not sur-
vive the sub-prime and subsequent credit
crisis and what the future holds for
investors. This edition also includes a
brief overview of the hedge-fund indus-
try’s history, how to start a hedge fund,
and what new regulations mean for man-
agers and investors. It also profiles 10
successful hedge-fund managers.
The Universal
Principles of
Successful Trading:
Essential Knowledge
for All Traders in All
Markets
By Brent Penfold
Hardcover
256 pages
Wiley
The book’s goal is to clearly articulate
“trading principles that distinguish the
winners from the losers.” In reviewing the
commonalities of consistently profitable
traders, regardless of market, time frame,
or technique, the author explains: how to
develop a trading plan; how to identify
and create an effective methodology; suc-
cessful money-management strategies,
and trader psychology. The book also
includes interviews with a diverse group
of traders from the UK, America,
Singapore, Hong Kong, Italy, and
Australia, all of whom agreed to offer one
piece of advice that emphasizes an essen-
tial element of the universal principles.�
ACTIVE TRADER • December 2010 • www.activetradermag.com 73
Trader’s Bookshelf is a forum to announce
new trading and financial books. Listings are
adapted from company press releases and
are not endorsements or recommendations
from the Active Trader Magazine Group. E-
mail press releases to editorial@activetrader-
mag.com. Publication is not guaranteed.
TRADER’S Bookshelf
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74 www.activetradermag.com • December 2010 • ACTIVE TRADER
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78 www.activetradermag.com • December 2010 • ACTIVE TRADER
At the money (ATM): An option whose strike price is identical (orvery close) to the current underlying stock (or futures) price.
Average and median: The mean (or average) of a set of values isthe sum of the values divided by the number of values in theset. If a set consists of 10 numbers, add them and divide by 10to get the mean.A statistical weakness of the mean is that it can be distorted byexceptionally large or small values. For example, the mean of 1,2, 3, 4, 5, 6, 7, and 200 is 28.5 (228/8). Take away 200, and themean of the remaining seven numbers is 4, which is much morerepresentative of the numbers in this set than 28.5.
The median can help gauge how representative a mean reallyis. The median of a data set is its middle value (when the set hasan odd number of elements) or the mean of the middle two ele-ments (when the set has an even number of elements). Themedian is less susceptible than the mean to distortion fromextreme, non-representative values. The median of 1, 2, 3, 4, 5,6, 7, and 200 is 4.5 ((4+5)/2), which is much more in line withthe majority of numbers in the set.
Call option: An option that gives the owner the right, but not theobligation, to buy a stock (or futures contract) at a fixed price.
Compound annual growth rate (CAGR): The annualized gain repre-sented by an investment’s total return over a certain period.Unlike the average return, CAGR represents the annual gain ofan investment if it had increased at a steady rate during the timeperiod.
Suppose you bought $1,000 in stock four years ago, and theinvestment rose to $1,100 in the first year, $1,150 in the secondyear, $1,275 in the third year, and $1,425 in the fourth year.
The CAGR formula is:
(Ending value / beginning value)(1/no. of years) – 1
In this case:
($1,425 / $1,000)(1/4) – 1= 1.425(1/4) – 1= 1.0926 – 1 = .0926, or 9.26%
Current ratio: A company’s current assets divided by its currentliabilities. It is used as a rough measure of a company’s financialhealth by determining its ability to pay off short-term liabilitieswith short-term assets, such as cash and inventories. A currentratio below 1.00 means the company’s liabilities outweigh itsassets.
Exponential moving average (EMA): A type of weighted moving aver-age that uses the following formula:
EMA = SC * price + (1 - SC) * EMA(yesterday)where:SC is a “smoothing constant” between 0 and 1, andEMA(yesterday) is the previous day’s EMA value.
You can approximate a particular SMA length for an EMA by
using this formula to calculate the equivalent smoothing con-stant:
SC = 2/(n + 1)where:n = the number of days in a simple moving average ofapproximately equivalent length.
For example, a smoothing constant of 0.095 creates an expo-nential moving average equivalent to a 20-day SMA (2/(20 + 1)= 0.095). The larger n is, the smaller the constant, and thesmaller the constant, the less impact the most recent price actionwill have on the EMA. In practice, most software programs allowyou to simply choose how many days you want in your movingaverage and select either simple, weighted, or exponential calcu-lations.
Fibonacci series: A number progression in which each successivenumber is the sum of the two immediately preceding it: 1, 2, 3,5, 8, 13, 21, 34, 55, and so on. As the series progresses, theratio of a number in the series divided by the immediately pre-ceding number approaches 1.618.
A basic application is to calculate likely price targets. Forexample, if a stock broke out of a trading range and rallied from25 to 55, potential retracement levels could be calculated bymultiplying the distance of the move (30 points) by Fibonacciratios –– say, 0.382, 0.50, and 0.618 –– and then subtractingthe results from the high of the price move. In this case, retrace-ment levels of 43.60 [55 - (30 * 0.38)], 40 [55 - (30 * 0.50)],and 36.40 [55 - (30 * 0.62)] would result. The most commonlyused ratios are 0.382, 0.50, 0.618, 0.786, 1.00, 1.382, and1.618. Depending on circumstances, other ratios, such as 0.236and 2.618, are used.
While Fibonacci retracements are used to calculate the possi-ble partial correction levels of a previous price move (i.e., areversal of up to 100 percent of a previous price swing),Fibonacci extension levels are used to extrapolate moves in thesame direction as a previous price swing — for example, pro-jecting a target for a new upswing that represents a 161.8-per-cent gain from a certain price level based on the size of the pre-vious upswing.
In the money (ITM): A call option with a strike price below theunderlying instrument’s current price, or a put option with astrike price above the underlying instrument’s current price.
Naked (uncovered) puts: Selling put options to collect premiumthat contains risk. If the market drops below the short put’sstrike price, the holder may exercise it, requiring you to buystock at the strike price (i.e., above the market).
Out of the money (OTM): A call option with a strike price above theprice of the underlying instrument, or a put option with a strikeprice below the underlying instrument’s price.
Premium: The price of an option.
Stop-and-reverse (SAR): A trading system that is always in themarket, liquidating long trades and going short when a sell sig-
Key CONCEPTS
concepts-resources1110 10/8/10 3:03 PM Page 78
ACTIVE TRADER • December 2010 • www.activetradermag.com 79
nal occurs and covering shorts and going long when a buy sig-nal occurs.
Strike (“exercise”) price: The price at which an underlying instru-ment is exchanged upon exercise of an option.
True range: A measure of price movement or volatility thataccounts for the gaps that occur between price bars. This calcu-lation provides a more accurate reflection of the size of a pricemove over a given period than the standard range calculation,which is simply the high of a price bar minus the low of a pricebar. The true range calculation was developed by Welles Wilderand discussed in his book New Concepts in Technical TradingSystems (Trend Research, 1978).
True range can be calculated on any time frame or price bar— five-minute, hourly, daily, weekly, etc. Using daily price barsas an example, true range is the greatest (absolute) distance ofthe following:
1. Today’s high and today’s low.2. Today’s high and yesterday’s close.3. Today’s low and yesterday’s close.
Average true range (ATR) is simply a moving average of the truerange over a certain time period. For example, the five-day ATRwould be the average of the true range calculations over the lastfive days.
Variance and standard deviation: Variance measures how spread outa group of values are — in other words, how much they vary.Mathematically, variance is the average squared “deviation” (ordifference) of each number in the group from the group’s meanvalue, divided by the number of elements in the group. Forexample, for the numbers 8, 9, and 10, the mean is 9 and thevariance is:
{(8-9)2 + (9-9)2 + (10-9)2}/3 = (1 + 0 + 1)/3 = 0.667
Now look at the variance of a more widely distributed set ofnumbers: 2, 9, and 16:
{(2-9)2 + (9-9)2 + (16-9)2}/3 = (49 + 0 + 49)/3 = 32.67
The more varied the prices, the higher their variance — themore widely distributed they will be. The more varied a market’sprice changes from day to day (or week to week, etc.), the morevolatile that market is.
A common application of variance in trading is standard devi-ation, which is the square root of variance. The standard devia-tion of 8, 9, and 10 is: sq. rt. 0.667 = .82; the standard deviationof 2, 9, and 16 is: sq. rt. 32.67 = 5.72
Volatility: The level of price movement in a market. Historical(“statistical”) volatility measures the price fluctuations (usuallycalculated as the standard deviation of closing prices) over a cer-tain time period — e.g., the past 20 days. Implied volatility isthe current market estimate of future volatility as reflected in thelevel of option premiums. The higher the implied volatility, thehigher the option premium.
Volatility skew (“smile”): The tendency of implied option volatilityto vary by strike price. Although, it might seem logical that alloptions on the same underlying instrument with the same expi-ration would have identical (or nearly identical) implied volatili-ties. For example, deeper in-the-money and out-of-the-moneyoptions often have higher volatilities than at-the-money options.This type of skew is often referred to as the “volatility smile”because a chart of these implied volatilities would resemble aline curving upward at both ends. Volatility skews can take otherforms than the volatility smile, though.
Weighted moving average: A simple moving average (SMA) is theaverage price of a stock, future, or other market over a certaintime period. A five-day SMA is the sum of the five most recentclosing prices divided by five, which means each day’s price isequally weighted in the calculation.
The weighted moving average (WMA) — as well as the expo-nential moving average (EMA) — puts greater emphasis onrecent prices under the assumption current market activity ismore important than more distant activity, which makes theaverage more responsive to price changes.
A WMA multiplies each day’s closing price by a “weightingfactor,” with the most recent close receiving the heaviest weight-ing and the greatest impact on the moving average value. Theweighting factors are based on the number of days in the aver-age. The sum of the weighted closes is then divided by the sumof the weighting factors over the desired period to derive theweighted moving average value.
The following table shows how a basic five-day weightedmoving average would be calculated:
The most recent day is given a weight of 5, the next mostrecent day a weight of 4, and so on. The most recent day in a20-day WMA would be weighted by 20, and so on. The closesare multiplied by their respective weighting factors. Theseresults are added together (216.25) and then divided by the sumof the weighting factors (in this case, 15). The result is a five-dayweighted average value of 14.42, compared to a simple averagevalue of 13. �
Closingprice
Weightingfactor
Weighted closing price
(closing price timesweighting factor)
Day 1 10 1 10
Day 2 10.5 2 21
Day 3 11.25 3 33.75
Day 4 14.75 4 59
Day 5 (mostrecent day) 18.5 5 92.5
Sum: 15 216.25
5-day SMA (avg. of closing prices): 13
5-day WMA (sum ofweighted closing pricesdivided by sum ofweighting factors): 14.42
concepts-resources1110 10/8/10 3:03 PM Page 79
TRADE
Date: Monday, Sept. 20, 2010.
Entry: Short and long the December E-
Mini Dow futures (YMZ10).
Reason for trade: After a strong early
session rally, we decided to take intraday
swing positions based on the idea the
market was unlikely (based on daily
price-action analysis) to expand its
range significantly for the remainder of
the day. The preference for short-side
trades was also predicated on the fact
that, after a blistering rally off the late-
August low, the market was challenging
resistance (the previous day’s high, which
was around the early August high) just
above the whole-number price level of
10,600.
The first short position was established
after the market had retreated from
the morning high of 10,656.
Initial risk: 10,669, 13 points above the
intraday high.
Initial target: The goal was to look for a move back toward the
previous day’s low (around 10,500), potentially holding the
position overnight if the market closed weakly.
TRADE SUMMARY
Profit/loss: -36 points.
Outcome: The day’s trading would not have been worth men-
tioning if not for the discipline mistake on the final short trade.
Frustration built throughout the day as the market mostly wig-
gled sideways. After the market failed to follow through to the
downside after the first short trade, we flip-flopped on the mar-
ket, going long but eventually scratching the position after a lit-
tle more than a half hour. Another short trade was essentially
scratched in the next 20 minutes.
It was at this juncture — with the irritation level at its
highest — that the final short position was established at
10,644. Having gotten shaken out of the previous trades (and
not even being able to take advantage of the modest profits that
were available with each of these swings), we dug in our heels,
unwilling to believe the anticipated sell-off would not material-
ize. We held on to the trade well past the stop level, but got
bailed out by a late down swing that let us get out only 15 ticks
worse than the original stop level.
Luckily, the mistake was on a small scale, but giving in to
impatience and then compounding the problem by getting mar-
ried to a position is a certain recipe for losses. �
80 www.activetradermag.com •• December 2010 •• ACTIVE TRADER
TRADE Diary
One bad trade is all it
takes to ruin a day of
careful trading.
Source: TradeStation
Note: Initial targets for trades are typically based on things such as the historical per-formance of a price pattern or trading system signal. However, individual trades are afunction of immediate market behavior; initial price targets are flexible and are mostoften used as points at which a portion of the trade is liquidated to reduce the posi-tion’s open risk. As a result, the initial (pre-trade) reward-risk ratios are conjecturalby nature.
Trade SummaryTime (CT) Long/Short Trade price Point P/L % P/L10:59 a.m. Short 10641
2 0.02%11:12 a.m. Cover 10639
11:12 a.m. Long 106380 0.00%
11:58 a.m. Sell 10638
12:04 p.m. Short 106422 0.02%
12:18 p.m. Cover 10640
12:30 p.m. Short 10644-40 -0.38%
3:01 p.m. Cover 10684
diary80-1210 10/12/10 2:52 PM Page 80