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SPA3 for NASDAQ White Paper | December 2012

SPA3 for NASDAQ White Paper

Contents 1 Executive Summary ......................................................................................................................... 4

2 Installing SPA3 for NASDAQ ............................................................................................................ 4

2.1 Global Portfolio System (GPS) ................................................................................................. 5

2.1.1 SPA3 Parameters ............................................................................................................. 5

2.1.2 SPA3 Scan ........................................................................................................................ 6

2.1.3 Actions to take ................................................................................................................ 6

2.2 SPA3 TradeMaster .................................................................................................................. 6

2.2.1 Actions to take ................................................................................................................ 6

2.3 SPA3 Public Portfolio ............................................................................................................. 11

3 Why trade the USA markets and why the NASDAQ? .................................................................... 11

4 The NASDAQ is much larger than the ASX .................................................................................... 13

5 NASDAQ’s downward bias over the research period ................................................................... 14

5.1 Why not just time the index ETF? ......................................................................................... 16

6 Trading Hours in the United States ............................................................................................... 19

7 Brokers and Fees for trading in the USA ....................................................................................... 20

7.1 Base Commission Models ..................................................................................................... 20

7.1.1 Percentage (%) of Transaction Value ............................................................................ 20

7.1.2 Flat Fee .......................................................................................................................... 21

7.1.3 Per Share ....................................................................................................................... 21

7.2 Which Base Commission Model? .......................................................................................... 21

7.2.1 Comparison of Base Commission Models ..................................................................... 21

7.3 Additional Fees (Commission and other) .............................................................................. 22

7.3.1 SEC Fee (Section 31 Transaction Fees) .......................................................................... 22

7.3.1 Trading Activity Fee (TAF) ............................................................................................. 23

7.3.2 Penny Stock Fee ............................................................................................................ 23

7.3.3 Inactivity Fee ................................................................................................................. 24

7.3.4 Order Routing ................................................................................................................ 24

7.3.5 More to consider ........................................................................................................... 24

7.4 Brokers .................................................................................................................................. 25

8 Currency Risk ................................................................................................................................. 25

Copyright Share Wealth Systems 2009 - 2012 Australian Version Page 1 of 141


8.1 Introduction .......................................................................................................................... 25

8.2 Hedging Currency Risk .......................................................................................................... 26

8.3 Currency Hedging Costs ........................................................................................................ 27

9 It all starts at the Trading Plan ...................................................................................................... 28

10 Catch 22 – the major problem all investors face ...................................................................... 28

11 Research Environment .............................................................................................................. 29

12 Risk Management and Money Management Rules in SPA3 ..................................................... 29

12.1 Position Sizing calculation ..................................................................................................... 29

13 Portfolio Limits and Boundaries ................................................................................................ 29

13.1 Different SIROC parameters .................................................................................................. 29

13.2 Understanding Box Plots ....................................................................................................... 30

13.3 Portfolio Limits using SIROC 21 8 .......................................................................................... 30

13.3.1 $25,000 Portfolios ......................................................................................................... 30

13.3.1.1 Comments ............................................................................................................. 30

13.3.2 $100,000 Portfolios ....................................................................................................... 30

13.3.2.1 Comments ............................................................................................................. 30

13.4 Portfolio Limits using SIROC 13 5 5 ....................................................................................... 31

13.4.1 $25,000 Portfolios ......................................................................................................... 31

13.4.1.1 Comments ............................................................................................................. 31

13.4.2 $100,000 Portfolios ....................................................................................................... 31

13.4.2.1 Comments ............................................................................................................. 31

13.4.3 Number of Simultaneously Open Positions .................................................................. 31

14 Exploratory Simulation .............................................................................................................. 34

14.1 Introduction .......................................................................................................................... 34

14.2 Extent of exploratory simulation research ........................................................................... 34

14.3 Research period .................................................................................................................... 35

15 Exploratory Simulation Outcomes ............................................................................................ 36

15.1 Introduction .......................................................................................................................... 36

15.2 SIROC 2108, Liquidity Multiple 10x, Brokerage $4.95, “Base” Simulation ........................... 39

15.2.1 5th, 50th & 95th Percentiles and Underwater Curves ..................................................... 43

15.3 SIROC 2108, $100,000, Liquidity Multiple 5x, Brokerage $9.95 ........................................... 45

15.3.1 5th, 50th & 95th Percentiles and Underwater Curves, 0.8% Risk % ................................ 50

15.4 SIROC 2108, $100,000 Liquidity Multiple 10x, Brokerage $9.95 .......................................... 52





15.6 SIROC 2108, $100,000, Liquidity Multiplier 10x, Brokerage $4.95 ....................................... 64





15.9 SIROC 2108, “Whole Market”, $100K, Liquidity Multiple 10x, Brok. $9.95 & $4.94 ............ 82

15.10 SIROC 130505, Liquidity Multiple 10x, Brokerage $4.95, “Base” Simulation ................... 86

15.11 SIROC 130505, $100,000, Liquidity Multiple 5x, Brokerage $9.95 ................................... 90

15.11.1 5th, 50th & 95th Percentiles and Underwater Curves, 0.6% Risk % ............................ 95

15.12 SIROC 130505, $100,000, Liquidity Multiple 10x, Brokerage $9.95 ................................. 97


15.14 SIROC 130505, $100,000, Liquidity Multiple 10x, Brokerage $4.95 ............................... 109


15.16 SIROC 130505, $25,000, Liquidity Limit 10x, Brokerage $4.95 ....................................... 121

15.16.1 5th, 50th & 95th Percentiles and Underwater Curves, 1.0% Risk % .......................... 126

16 Exploratory Simulation Summary ........................................................................................... 128

17 White Paper Summary ............................................................................................................ 128

18 Acknowledgements ................................................................................................................. 130

19 References .............................................................................................................................. 130

20 ADDENDUM 1 - Position Sizing Formula ................................................................................. 131

20.1 Determining the Trade Risk % ............................................................................................. 131

20.2 Different trades, same risk .................................................................................................. 132

20.3 Smaller Portfolio Risk, less loss. .......................................................................................... 133

20.4 Conclusion ........................................................................................................................... 133

21 ADDENDUM 2 – SPA3 Statistical Edge on the NASDAQ .......................................................... 134

21.1 SIROC 21 8 ........................................................................................................................... 134

21.2 SIROC 13 5 5 ........................................................................................................................ 136

21.3 SIROC 19 7 8 ........................................................................................................................ 138

21.4 SIROC 17 7 8 ........................................................................................................................ 139



1 Executive Summary This White Paper was released at the time of the formal release of SPA3 FOR NASDAQ in December 2012. It contains the actual SPA3 Edge statistical information in Addendum 2 and the historical portfolio exploratory simulation to determine the robustness of the SPA3 EDGE and to determine the ideal range of position sizes to deploy in trading the NASDAQ with SPA3.

Whilst the SPA3 Edge statistical information is tucked away in an Addendum some may wish to visit this section first up.

This paper provides detail on:

1. The outcomes of the risk and money management research. 2. Suggested position size boundaries for trading small ($25K) to medium ($100K) portfolio

sizes with SPA3. 3. The SPA3 Edge for the NASDAQ exchange.

Much evidence is provided to demonstrate the effectiveness and robustness of the SPA3 methodology comprising the trading system, risk management and money management rules. This is demonstrated by providing graphical equity curve and statistical outputs for a number of different portfolio scenarios with different position sizes.

Some of the information may be too detailed for some. For those you need go no further than section 13 on page 29 where the suggested position sizes boundaries are provided. And then read the summary sections, 16 and 17, at the conclusion of the paper.

For those that wish to delve deeper we have provided plenty of detail. View the detail in this paper almost as a ‘database’ of simulation results. Ultimately we believe that all active investors should grasp the type of material provided in this paper to instil the necessary belief with which to execute a chosen method in an uncertain and probabilistic environment such as the financial markets. By this we mean any method, not just SPA3.

Exploratory simulation is the backbone of the research conducted to produce this White Paper.

We believe that the type of and level of research provided in this paper is unprecedented in the arena of equities trading for private investors the world over, let alone Australia. And thus, with the release of this research, we hope to raise the standard of research that any systems provider or money manager the world over provides for their products.

We commend this White Paper and its contents to our customers.

2 Installing SPA3 for NASDAQ Before getting into the research aspects of the paper itself, we provide upfront what the SPA3 user must do to implement SPA3 FOR NASDAQ.



Firstly, to use SPA3 FOR NASDAQ an historical database and a data subscription will be required for the USA exchanges. There is an additional charge of A$27.50 if a Monthly Maintenance Fee is already being incurred for the ASX or JSE.

If the USA exchanges are the ONLY data feeds that are subscribed to then the Monthly Maintenance Fee (MMF) will be the same as the current MMF for subscribing to just the ASX from Share Wealth Systems. At time of publication this is A$71.50.

2.1 Global Portfolio System (GPS)

2.1.1 SPA3 Parameters

Within GPS you will notice a change in the Parameters panel to support the revised SPA3 risk and money management rules. These changes are:

1. SPA3 default parameter profiles have been added for the NASDAQ: a. Default XNAS SIROC 21:08 b. Default XNAS SIROC 19:07 c. Default XNAS SIROC 17:07 d. Default XNAS SIROC 13:05

Only the profiles relevant to your SPA3 product will be shown. For example, XNAS only customers won’t see the XJSE and XASX profiles, and vice versa.

All these default profiles correspond with the new Risk tables in TradeMaster.



2.1.2 SPA3 Scan

If you wish to run a SPA3 scan with a parameter profile other than ‘Default XNAS SIROC 21:08’ or one you created then you will need to change this is in your Scan profile manually.

If you change your SPA3 Scan profile to use a different default parameter profile, for example ‘Default XNAS SIROC 13:05’, ensure that your TradeMaster portfolio is using the corresponding Risk table of the same name. In TradeMaster select Portfolio, Profile, Money Management, Risk Tables. This is covered in the Trade Master steps below.

An ‘industry’ Watch List Called ‘NASDAQ Common Shares’ has been created in GPS especially for SPA3 NASDAQ that comprises only the FPO/Common Stocks that are listed on the NASDAQ. This Watch List is maintained automatically for new listings and de-listings and excludes all non ‘common shares’ such as preference shares, company options/warrants, unit trusts, ETFs and closed-end funds.

The ‘NASDAQ Common Shares’ Industry Watch List is used in the SPA3 Scan in the Securities tab. Simply drag and drop this Watch List from the Watch List Manager panel across to the Securities tab on the Scans panel.

2.1.3 Actions to take

For the immediate future, we recommend one of two actions.

1. You can continue to use your current Parameter profile settings, or 2. You can change to one of the other ‘Default XNAS SIROC XX:XX’ parameter profiles.

2.2 SPA3 TradeMaster

2.2.1 Actions to take

Stepping through each section of the Portfolio, Profile menu, these are the actions that need to be taken to implement the Revised SPA3 Risk Management and Money Management rules in an existing SPA3 portfolio:

1. In Profile, General, Portfolio, select XNAS for the Stock Exchange.



2. Decide the Risk % in Profile, Money Management, Capital Allocation. This is the most important decision that the SPA3 active investor will need to make whether setting up a new portfolio or transitioning an existing SPA3 portfolio to the revised SPA3 position sizing rules.

The Risk % ranges and limits are summarised in the tables below. These are the ultimate outputs from this White Paper.

Section 13 of this White Paper provides further detail on the Risk % ranges and limits for the different portfolio scenarios summarised below and then the actual simulation results in section 15 go into great detail.

It is recommended that a Risk % is selected in the range provided in the [Ideal] column. The start and end of the Ideal range are inclusive.



Refer to the section on how many simultaneously open positions will need to be managed for each Risk % in section 13.4.3 to assist with selecting the Risk % for your investing profile.

Portfolios using SIROC 21 8

$25,000 SIROC 21 8 8 Criteria Min

Risk % Ideal Max

Risk % Comments Chart

Sections Brokerage: $9.95, x10 Liquidity 0.5 0.8 – 1.5 1.5 1.2% can be considered 15.7 Brokerage: $4.95, x10 Liquidity 0.4 0.5 – 1.5 1.5 1.2% can be considered 15.8


Risk % Ideal Max


Sections Brokerage: $9.95, x5 Liquidity 0.3 0.3 – 1.0 1.5 15.3 Brokerage: $9.95, x10 Liquidity 0.3 0.3 – 0.8 1.5 0.9% can be considered 15.4 Brokerage: $4.95, x5 Liquidity 0.3 0.3 – 1.0 1.5 15.5 Brokerage: $4.95, x10 Liquidity 0.3 0.3 – 0.8 1.5 0.9% can be considered 15.6

Portfolios using SIROC 13 5 5


Risk % Ideal Max


Sections Brokerage: $9.95, x10 Liquidity 0.4 0.8 – 1.0 1.5 15.15 Brokerage: $4.95, x10 Liquidity 0.3 0.5 – 1.0 1.5 15.16


Risk % Ideal Max


Sections Brokerage: $9.95, x5 Liquidity 0.2 0.3 – 1.0 1.5 15.11 Brokerage: $9.95, x10 Liquidity 0.2 0.3 – 0.6 1.0 15.12 Brokerage: $4.95, x5 Liquidity 0.2 0.2 – 0.8 1.2 15.13 Brokerage: $4.95, x10 Liquidity 0.2 0.2 – 0.6 1.8 15.14

There is no wrong answer if a Risk % is selected in the ranges in the Ideal column above. If you wish to be far more specific then the portfolio simulation outcomes in section 15 should be consulted but initially this is not mandatory.

As a rule of thumb, if you wish to minimise drawdown then choose at the lower end, if you wish to maximise growth then choose at the higher end but understand that larger position sizes are more sensitive to trading errors and to randomly selecting trades with poorer outcomes.

It is likely that you have a portfolio that is between or over the two starting values of $25,000 and $100,000 chosen for simulation. A dose of common sense and erring towards a lower rather higher



Risk % within the Ideal range should keep the SPA3 active investor on the straight and narrow. The Risk % can be changed at any time during the life of a portfolio.

3. Decide Market and Sector Risk settings in Profile, Money Management, Position Sizing.

The settings above will reflect the following risk management approach:

a. Risk Profile 1 – “When Market Risk is HIGH” reduces position sizes by 100%, i.e. no trade, for High and Low sector risk trades.

b. High Sector Risk trades will get a full position size because they are reduced by 0%. This is the setting that was used during all the simulations in this White Paper.

Other settings can be selected. For example, if you wished to reduce the position size of a trade that has high sector risk, the bottom left quadrant should be changed to 33.33% of 50%, which ever you wish to reduce the position size by.

4. Decide the ATRVE volatility levels and minimum liquidity multiple that will be traded in Profile, Money Management, Trade Restrictions.

a. The default ATRVE levels of 2 to 12 for the NASDAQ that were used for the portfolio simulations in this paper are shown below.

b. To reduce portfolio equity curve volatility and hence potentially reduce drawdown the ATRVE levels could be narrowed down to, say, 1.5 – 2 for the minimum value and 4.5 – 5 for the maximum value. Refer to Addendum 2 in section 21 of this Paper for a detailed breakdown of the SPA3 raw edge by ATRVE volatility level for the NASDAQ.

c. The portfolio simulations used liquidity multiples of 5 and 10. A multiple in between can be used. A rule of thumb is that the smaller the portfolio value the higher liquidity multiple that can be used and the larger the portfolio the smaller the



liquidity multiple should be but remember that the lower the multiple the bigger the liquidity risk that the active investor takes.

5. Select the SIROC default profile for your portfolio in Profile, Money Management, Risk Tables. Note the instructions in the Description box.

This must match the Default SPA3 Parameters that are selected in the SPA3 Scan, as noted above.



2.3 SPA3 Public Portfolio A SPA3 FOR NASDAQ Public Portfolio will be established using the following Profile:

• US$50,000 starting portfolio. • SIROC 21 08 • Brokerage $4.95 • Liquidity multiple of 8x • Risk Profile 1, i.e. move 100% into cash during a SPA3 High Risk market period.

A specific SPA3 FOR NASDAQ Trading Plan will be published.

The SPA3 FOR NASDAQ Public Portfolio will be displayed on the SWS USA website. The start date for the portfolio will be the next Low Risk Market signal on the NASDAQ Composite Index after 17th December 2012.

3 Why trade the USA markets and why the NASDAQ? The USA equity markets are the largest in the world from a market capitalisation and liquidity point of view. However, this is not reason enough for traders outside of the United States to take their trading there. In fact, the size of the markets can be a disadvantage in trying the work one’s way through hundreds of potential trades to include in a portfolio.

The offer of additional profits needs to be proven is some way or another to take on the:

1. effort of trading during hours that are out of sync with Australian business hours and many other countries,

2. currency risk, 3. effort of managing a trading account with a broker that may be off-shore in the United

States.

One of the objectives of this White Paper is to put forward detailed research of the potential returns that are on offer by trading the NASDAQ so that active investors can decide for themselves whether to make the effort.

At a big picture level consider the performance of the respective USA indices compared to the All Ordinaries Index. The DJIA and S&P500 were both up around 1100% during the secular bull market from October 1982 to January 2000 while the NASDAQ Composite was up around 2200%. Over the same period the All Ordinaries was up around 530%, around ½ that of the DJIA and S&P500 and ¼ of the NASDAQ. January – March 2000 was when the secular bull market ended and the secular bear market stated. This is summarised in the table below:



During the secular bear market period from January – March 2000 and measured to 28 September 2012, the All Ordinaries Index was up around 37% whilst the USA indices were up 16%, down -5% and down -24% for the DJIA, S&P500 and NASDAQ Composite, respectively.

During the current secular bear market there have been two primary bull, from Oct 2002 – October 2007 and March 2009 – March 2012, and two primary bear markets. It may be argued that the second primary bull market on the USA indices is not yet over at time of writing and that it ended in Australia in April 2011. Measured from troughs to peaks the two primary bull markets across the four markets in question have risen as follows:

This shows that investing in the United States equity markets should be considered very seriously as a long term investing strategy for active investors.

But why the NASDAQ and not the NYSE?

The other metric to use as a benchmark is overall equity market volatility. Volatility can be an indication of opportunity to profit. Using ATRVE (Average True Range Exponentially smoothed) expressed as a percentage of the stock price at time of entry to a SPA3 signal we can determine that the average overall market volatility is as follows between 1990 and 2012:

This shows that the NASDAQ is approximately 50% more volatile than the NYSE which presents better medium term trading growth opportunities for trading, provided risk can be managed effectively.

Having said this, Share Wealth Systems will research the NYSE as another equities market to trade at some stage in the future. Given the amount of research that needs to be completed we decided to split the effort and made the decision to first release SPA3 for NASDAQ. It is anticipated that stock volatilities will be lower on the NYSE which may present an opportunity of trading with larger positions sizes.

10/1982 to 3/2000

DJIA 1100%S&P500 1100%NASDAQ Comp 2200%ASX 530%

10/2002 to 10/2007 3/2009 to 9/2012DJIA 88% 105%S&P500 96% 113%NASDAQ Comp 155% 150%ASX 151% 60% (to 4/2011)

ASX NASDAQ NYSE

Whole Market 3.775 4.538 2.966$50K - $2.0M Liq 4.098 4.683 3.103



In summary, the big picture evidence, since 1982, shows that the USA equity markets have offered more potential for growth that the ASX. The NASDAQ appears to offer more opportunity than the NYSE from a volatility viewpoint. Going forward this should remain the case, especially when the next secular bull market comes around again. There is no apparent reason yet that this will change.

Therefore, in preparation for the next secular bull market, active investors should consider exposure to the USA equity markets.

4 The NASDAQ is much larger than the ASX The biggest problem with trading the NASDAQ with a short or medium term methodology is the size of the market compared to the ASX, and other markets, which can lead to an enormous number of trade opportunities.

A characteristic of SPA3 is that it presents opportunities for a large number of users to manage portfolios of differing sizes with differing objectives. To do this it needs to present a number of opportunities that is sufficient but not too large a list such that trade selection becomes unmanageable for each individual investor.

The NASDAQ has 2694 currently listed companies at time of research. Of these, 2400 were Fully Paid Ordinary listings the others being ETFs, Warrants, company options, Unit Trusts and Preference Shares. The ASX has 1887 Fully Paid Ordinary stocks.

The total Market Cap of the NASDAQ Fully Paid Ordinary stocks is approximately US$4.76 trillion as at November 2012 whereas the ASX is around A$1.38 trillion.

There are 2145 on the NASDAQ with greater than US$20M market cap whereas there are just 1005 listed stocks with greater than A$20M market cap on the ASX, as at November 2012. The exact number of stocks that exceed this threshold will change depending on market conditions.

No matter which way you look at it the NASDAQ exchange is far larger than the ASX. However, what interests us as medium term active investors is whether we have an edge and how simple or difficult it is to execute that edge. One of the criteria that determine the degree of difficulty is the number of opportunities that we are presented with on a day to day basis from which to select trades.

Addendum 2, Section 21, at the end of this White Paper provides tables that show the SPA3 Edge from a statistical point of view. You can peruse these tables and compare the number of trades and the actual SPA3 Edge statistics. There are far more SPA3 trades generated on the NASDAQ than the ASX.

This left the SWS research team with a dilemma to solve but in solving could also present an opportunity. With far greater choice we had the liberty to zoom into a sub-portion of the NASDAQ

ASX NASDAQ (as at November 2012)

Total Market Cap A$1.38 Trillion US$4.76 Trillion No. of FPO Stocks 1887 2400No. of stocks > $20M Market Cap 1005 2145



that could reduce the sheer number of trades from which to select portfolio trades and simultaneously improve SPA3 performance relative to trying to scan the entire NASDAQ for trading opportunities.

The end result is that we were able to hone in on a sub-portion of the NASDAQ as defined by liquidity. Specifically we were able to define the hemisphere of stocks on which to focus as those between $50,000 and $2,000,000 liquidity as defined by the average daily traded value in the 3 months leading up to the SPA3 signal. The exploratory simulations conducted in this paper will show both the whole market and the $50,000 and $2,000,000 liquidity bracket of stocks.

5 NASDAQ’s downward bias over the research period The research period from the first trading day in 2000 to 2012 was very different for the ASX and NASDAQ. The ASX had an upward bias over this period whereas the NASDAQ had a downward bias.

Any trading methodology, no matter how short term its focus, indeed even an intraday system, must be able to make profits and then protect them over many years regardless of the long term bias of the given market in which it operates.

It is important therefore that that the SPA3 methodology, a long only methodology, be able to generate and protect profits in a market that has a downward bias over a long period.

Compare the two markets, the ASX and the NASDAQ from January 2000 to September 2012.



The extent of the market declines and subsequent rises may be more evident in a semi-log chart.

$100,000 invested in the ASX index would have achieved finished the 12.8 year period at $139,770, excluding dividends, whereas the same amount invested in the NASDAQ would have finished the period at $76,580, excluding dividends. These are the respective benchmarks.



5.1 Why not just time the index ETF? This is an interesting question given the huge growth in ETFs around the world over the last 5 or so years. Well let’s research this scenario.

Investing in the STW (the SPDR ASX 200 ETF) or the QQQ (the NASDAQ 100 ETF) on a buy and hold basis would have yielded almost the same return as the ‘cash’ index returns highlighted above, i.e. A$139,770 and US$76,580, respectively, excluding dividends.

Including re-investment of all dividends would provide a return similar to the ASX 200 Accumulation which would have the portfolio finishing at A$239,750. We know from the exploratory simulation of SPA3 portfolios from the September 2012 White Paper a buy and hold strategy of the STW with dividends re-invested would well underperform the managing of a SPA3 stocks portfolio excluding dividends.

But what if we timed the respective index ETFs? This would mean that we could avoid the primary bear market periods and take advantage of the primary bull market periods. And only trade a single ETF without the effort to manage a whole portfolio of stocks. Would just trading the ETF outperform remaining in the index ETF? Would timing the ETF outperform managing a portfolio of stocks from the respective markets?

We used 6 different long only timing ‘systems’ on the Nasdaq Composite and the All Ordinaries. The four different SIROC settings of 21 8, 19 7, 17 7, 13 5, a 75 day EMA crossover system, a 75 day EMA ‘modified system’ and a 200 day EMA ‘modified system’. The ‘modified system’ attempts to reduce the number of trades by minimising whipsawing when the Index is moving sideways. The latter enters when the Index has two consecutive closes above the 200 day EMA and exits when the Index has 5 consecutive closes below the 200 day EMA.

Firstly, the NASDAQ Composite Index. Timing the QQQ ETF would definitely outperform the Index even without dividends being re-invested.

The ‘% Invested / Exposure’ has been shown to indicate how many dividends would have been re-invested if included. This shows that around half would be re-invested.

Timing mechanism NASDAQ Composite SIROC 21 8 SIROC 19 7 SIROC 17 7 SIROC 13 5 75 Day EMA 75 Day (mod) 200 Day (mod)

% Invested / Exposure 100% 48.7% 50.4% 49.2% 48.9% 58.3% 56.4% 59.7%Max Drawdown -77.9% -34.7% -29.8% -28.8% -33.1% -29.5% -36.3% -32.4%

No of Trades 1 29 29 28 43 93 41 25Return (excl divs) -23.42% 48.94% 92.76% 82.97% 37.10% 107.68% 63.54% 48.40%



Using a 75 day EMA would have doubled one’s starting capital in a market that fell 23%. Not bad. However, there were 93 ‘low risk’ market periods using the 75 day EMA due to plenty of whipsawing in sideways markets. Using it as a timing mechanism to trade a single ETF would be acceptable but it certainly would not be acceptable to use as a market timing mechanism to manage Systematic Risk, or Market Risk. There would simply too much starting up and closing down of portfolios. Over such a period about half of 93 would be acceptable but less even better.

A semi-log version of the above chart is shown below.



Secondly, the All Ordinaries Index. Timing the STW ETF would outperform the Index even without dividends being re-invested. From the chart below the main reason for this is avoiding the 2008 bear market through some timing mechanism.

Again, the 75 day EMA fares quite well but again with 94 ‘low risk’ market periods. The SIROC 21 8 was towards the bottom of the list in both markets however the SIROC 17 7 were better across both markets.

Timing mechanism All Ordinaries SIROC 21 8 SIROC 19 7 SIROC 17 7 SIROC 13 5 75 Day EMA 75 Day (mod) 200 Day (mod)

% Invested / Exposure 100% 54.9% 55.6% 55.9% 55.7% 58.2% 58.8% 60.7%Max Drawdown -54.6% -31.4% -27.8% -22.1% -21.4% -18.4% -23.3% -17.5%

No of Trades 1 27 29 26 35 94 46 21Return (excl divs) 40.2% 41.33% 63.57% 91.90% 93.60% 72.22% 56.84% 91.46%



The point is that outperforming the Index by timing the Index itself is not that difficult however to achieve large outperformance one needs to expose investment capital to individual instruments that actually outperform the index.

The exploratory simulation of historical portfolios on the NASDAQ and ASX demonstrate quite conclusively that portfolios of stocks that are risk and money managed according to a process that has a statistical edge perform much much better than timing the ETF of an index.

One might argue that trading the index can be leveraged. Well so can equities via CFDs for those that reside outside the United States and via 2x or 4x leverage if elected via a standard brokerage account in the United States. Share Wealth Systems will be releasing exploratory simulation research on leveraged trading with SPA3 later in 2013.

6 Trading Hours in the United States The normal trading hours for the NYSE and NASDAQ are 9.30am to 4pm, Eastern Standard Time (EST). However, the NASDAQ does also have pre-market and after-market trading from 8.00am to 9.30am and 4pm to 8pm, respectively.

The end of day close for stock prices is based on the 4pm close.

In Australia the opening and closing times in local Australian times change depending on daylight saving.

In the Australian winter the NASDAQ and NYSE trading hours are 23h30 to 06h00 AEDT and in our summer 01h30 to 08h00 AEDT. There is a two hour shift because New York also has daylight saving



where one time zone goes forward and hour and the other goes back an hour. There is also a ‘shoulder’ period for a week or two between seasons when trading hours are 12h30 to 07h00 AEDT.

Depending on which time zone you live in, it may suit you to use the pre-market and after-market trading hours in which to execute your NASDAQ trades so that you do not need to be awake in the wee hours of the morning. Not all brokers make this available on their trading platforms so ensure that you check before opening an account.

There are some aspects and risks to be aware of when doing so. View this straightforward and useful webpage and video on information for trading during pre-market and after-market hours on the NASDAQ. Like most things you will become more au fait when you engage the market and gain experience in these matters.

7 Brokers and Fees for trading in the USA Trading the NASDAQ not only has you stepping into a new market, it has you dealing with a foreign broker, a new trading environment, new regulations and more directly, new fees. Luckily, thanks to the internet, the world is becoming smaller and many of these perceived barriers are transformed into standard issues that simply need to be investigated as part of any financial investment process.

This section of the white paper will focus on three aspects of trading the USA markets:

• The Base Commission models available and which one is best for you. • Additional fees. • List of brokers that allow international investor accounts.

7.1 Base Commission Models The term “base commission”, as used in this paper, refers to only the fee charged by brokers for executing a standard trade through their platform. It does not include any penalties for special conditions such as large orders, small priced stocks or frequent trading discounts.

There are 3 distinct models that brokers implement to charge a base commission; Percentage of transaction value, Flat fee or Per share. Each is briefly explained here with general comments.

7.1.1 Percentage (%) of Transaction Value

This model charges a percentage of the transaction value as the base commission. Example:

0.1% of a $20,000 transaction is $20.

Typically, a minimum fee applies. In Australia, this is part of the standard broker commission model and is therefore widely accepted as the norm. We did not find any US broker that offered this as a base commission. With flat fee or very small per share commissions on offer, which are significantly cheaper, the reason is extremely obvious.


http://www.learningmarkets.com/understanding-pre-market-and-after-hours-stock-trading/


7.1.2 Flat Fee

In a flat fee model the broker charges a fixed amount per transaction (trade). In most cases this is regardless of the transaction value or quantity of shares. Example:

$4.95

Nearly, every US broker offers a flat fee as one of their base commission models. Interactive Brokers are the clear exception, offering only per share fee models.

7.1.3 Per Share

In a per share model, the base commission is based on the number of shares in each transaction. In most cases this is regardless of the transaction value or price. Example:

$0.01 x 2,000 shares = $20

So, the more shares you purchase the more you pay. At first a per share fee, typically in single cents or portions of a cent, seems attractive and it is for small quantities. However, once the quantity of shares starts to rise, the fee can be significantly more than any other commission model.

7.2 Which Base Commission Model? For every trade, every Base Commission model will most likely produce a different fee. Which model is the best? More pertinently, which model will produce the lowest fee for your style of trading and position size? It is very difficult to make this decision based on only a few trade examples. Trades within a portfolio are rarely of a fixed value or quantity. Portfolios change, stock selection changes and stock prices change. To understand the impact a variety of trades and fees would have on your portfolio, a number of simulated portfolios need to be created.

A simulated portfolio will generate a cumulative Base Commission value based on the trades that the portfolio entered. The portfolio starting value, position size and fees will dictate how many trades are taken over any portfolio period and which trades are actually taken. The variety of trades makes it necessary to measure the fee as a percentage of the transaction value. This normalises all the fees to a value that is proportional to the amount of money that you transact through the markets regardless of the model.

The portfolio starting value is now the remaining influential variable. By running a number of simulations starting at different equity levels, the impact of each Base Commission model can be seen. In section 2.3.1 we have done exactly this.

7.2.1 Comparison of Base Commission Models

Each portfolio in the table below utilised the same list of available trades generated from an XNAS SIROC 21:08 profile. The table values show the total Base Commission fees paid as a percentage of the transacted value.



Total Base Commission as Percentage of Transacted Value Portfolio Value Flat

$4.95 Flat

$9.95 Per Share

$0.005 Min $1

Per Share $0.01

Min $10

Per Share $0.02

Min $15

% Transaction Value 0.1%

Min $9.90 $25k to ~$45k 0.408% 0.904% 0.109% 0.926% 1.526% 0.887% $65k to ~$120k 0.165% 0.305% 0.090% 0.334% 0.560% 0.302% $100k to ~$180k 0.098% 0.197% 0.090% 0.245% 0.439% 0.196% $250k to ~$470k 0.037% 0.077% 0.082% 0.167% 0.332% 0.103% $400k to ~750k 0.024% 0.046% 0.075% 0.157% 0.310% 0.098%

It can be clearly seen that for small portfolios, below $100k, a very small per share fee is the best choice. Beyond $200k a small flat fee fast becomes the better choice.

For smaller portfolios the primary issue appears to be the minimum fee level. For instance, even though the Per Share fee may only double, the final fee % could be 9 times larger because the minimum is 10 times larger.

For larger portfolios the flat fee is favourable because the fee doesn’t scale in line with the increased position size.

7.3 Additional Fees (Commission and other) Regardless of what broker you use, there are always additional fees that may be applied to a trade or your account from several sources. The following are the main additional fees we found listed on variety of broker’s sites. Some are broker specific but most are common to all; most of the fees are very small. The list is by no means exhaustive, so please investigate any prospective broker completely before opening an account.

7.3.1 SEC Fee (Section 31 Transaction Fees)

When you sell a stock on a US exchange the SEC charge the exchange a transaction fee. This small fee is usually passed onto the broker and subsequently onto you the customer. The initial fee is set by the SEC and it appears that brokers do not inflate this fee for the customer.

“When you sell a stock, you may have noticed that a small transaction fee, often just a few pennies, appears on your confirmation slip. Although some broker-dealers have described this charge as an "SEC Fee," the SEC does not actually impose this fee on individual investors.

The SEC does not impose or set any of the brokerage fees that investors must pay. Instead, under Section 31 of the Securities Exchange Act of 1934… all of national securities exchanges.... must pay transaction fees to the SEC based on the volume of securities that are sold on their markets. These fees recover the costs incurred by the government, including the SEC, for supervising and regulating the securities markets and securities professionals.”

Source: http://www.sec.gov/answers/sec31.htm


http://www.sec.gov/answers/sec31.htm


As of November 2012 the current SEC fee is 0.00224% of the transaction value. The fee is reviewed regularly and may be increased or decreased in order for the SEC to achieve its budget requirements.

7.3.1 Trading Activity Fee (TAF)

The Financial Industry Regulatory Authority (FINRA) levies the TAF on covered securities and option sales.

“The trading activity fee (TAF) is one of the regulatory fees FINRA assesses to recover the costs of supervising and regulating firms. This includes costs associated with performing examinations, financial monitoring, and FINRA’s policy, rulemaking, interpretive and enforcement activities.

Each member shall be assessed a Trading Activity Fee for the sale of covered securities.”

Source: http://www.finra.org/Industry/Regulation/Guidance/P122376

As of November 2012, the FINRA TAF for covered stock sales is currently $0.000119 per share (rounded up) and with a minimum charge of $0.01 and a maximum charge of $5.95.

7.3.2 Penny Stock Fee

The SEC defines a “penny stock” as any security that trades below $5 and stipulates stricter trading regulations which brokers must adhere to before allowing a customer to trade in them. However, securities traded on a national stock exchange, regardless of price, are exempt from regulatory designation as a penny stock1. In this case, it is up to the exchange or broker to define a penny stocks and what rules or fees apply to them.

Many brokers charge an additional fee for trading in penny stocks. These fees are typically in the form of an additional per share or percentage of transaction value fee. For example:

“For orders where the stock price is under $1.00, add 1/2 cent per share for the entire order.”

Source: Firstrade

“For stocks priced under $1, add ½% of the principal value to the commissions shown.”

Source: Scottrade

A penny stock fee may actually double the total fee you pay for the security

1 http://www.sec.gov/rules/final/34-51983.pdf


http://www.investopedia.com/terms/c/coveredsecurity.asp

http://www.finra.org/Industry/Regulation/Guidance/P122376

http://www.sec.gov/answers/penny.htm

http://www.firstrade.com/content/en-us/pricing

http://www.scottrade.com/online-brokerage/trading-fees-commissions.html

http://www.sec.gov/rules/final/34-51983.pdf


7.3.3 Inactivity Fee

An inactivity fee is charged for accounts that have extremely low trading activity in any year or that have a very low account balance.

Inactivity Fee: $50.00 Annually An account is considered inactive when there are less than 2 trades in the past 12 months or if there are less than $10,000 in credit or debit balances.

Source: eOption

For a SPA3 trader or investor this shouldn’t be an issue.

7.3.4 Order Routing

In Australia, until recently2, orders created for an ASX listed security are generally sent directly to the ASX for placement in the order queue and are then executed when matched. In the USA, there are several order routing systems selectable by the trader, which attempt to match the order against existing orders on different Exchanges, ECNs, Market Makers, Dark Pools, Extended Hours sources and the like. The SEC provides an overview of these trade execution paths. It appears that the primary aim is to fill your order at the best price available, not matter where it resides. Some of these routing paths incur an additional fee. For example:

NASDAQ-SOLV $0.003 per share

ECN $0.0027 per share

Source: Just2Trade

7.3.5 More to consider

A number of other trading fees and environmental issues were encountered during our investigation. The following is a short list of items that require your consideration, primarily because many of them aren’t standard in Australia, are broker specific or result from dealing with a foreign broker. If they become more relevant or impact a portfolio performance directly, we shall expand the information within a revision of this white paper or another suitable location. Once again, this list is by no means exhaustive, so please investigate any prospective broker completely before opening an account.

• Market Data Fee and Type: Level 1, Level 2, Course of Sales and Live or delayed • Platform access: Fee, Installed (Windows®, Mac®), Web, Mobile platform. • Wire Transfers: International incoming and outgoing • Margin requirements: initial and maintenance. • Margin interest rates: fixed or based on proprietary rate. • Accounts: e-Statements. • Customer service: Call centre, email response, hours of operation and costs. • Order execution: Modifying a partially executed order.

2 ASX Best powered by Fidessa (13/07/11)


http://www.eoption.com/misc_fees.html

http://www.sec.gov/investor/pubs/tradexec.htm

http://nasdaqtrader.com/TraderNews.aspx?id=ETA2011-14

http://en.wikipedia.org/wiki/Electronic_communication_network

http://www.just2trade.com/fees/other_fees

http://www.asxgroup.com.au/media/PDFs/110713mr_asx_best_and_fidessa.pdf


• Local or international tax: Australian GST, international tax. • Dividends: Reinvestment, cash or cheque delivery. • Broker security: Financial memberships and licensing, regulations, investor protection for

your open positions and cash funds, the recovery process.

7.4 Brokers The list below is a list of USA based brokers that allow international investors to open a trading account. It also includes a few locally based brokers that allow trading on global markets including the USA. This list is not exhaustive, is not any particular order and is in no way a recommendation for any broker. Please investigate any prospective broker completely before opening an account.

You may click on the broker name to open their web page.

Options Express (AU) Charles Schwab Interactive Brokers Saxo Capital Markets (Australia) MarketTrade.com Investrade Trading Direct TD Ameritrade E*Trade (USA) TradingBlock Scottrade Firstrade MB Trading Zecco Lowtrades eOption Just2trade.com

8 Currency Risk

8.1 Introduction For traders that reside outside the United States that use SPA3 FOR NASDAQ to trade equities on the NASDAQ an additional risk will need to be managed, that of currency risk or exchange rate risk.

This section is written from an Australian perspective. The same logic can be applied to the ZAR or any other non-USD currency.

Currency risk is the risk that exists while your trading capital resides in a foreign currency. The risk is that the foreign currency weakens against your home currency. Consequently, when you return your trading capital to your home currency you will get less capital back. Of course, the foreign currency could strengthen in which case you will get more capital back in your home. Let’s look at an example. All spreads and costs are excluded to keep things simple to begin with.

If you deposit A$100,000 into a USD account and the Australian dollar rises in strength from buying US$1 to US$1.1, you would lose 9.1% of your investment in AUD terms without even trading. When the AUD strengthens, the USD weakens, for this currency pair. AUDUSD = 1 : 1 Deposit money into a USD account -AUD$100,000 +USD$100,000 AUD strengthens such that AUDUSD = 1 : 1.1


http://www.optionsxpress.com.au/

https://www.schwab.com/

http://interactivebrokers.com.au/

http://au.saxomarkets.com/

http://www.marketrade.com/

http://www.investrade.com/

http://www.tradingdirect.com/

https://www.tdameritrade.com/home.page

https://us.etrade.com/home

http://www.tradingblock.com/

http://www.scottrade.com/

http://www.firstrade.com/content/en-us/welcome

http://www.mbtrading.com/

https://www.zecco.com/

http://www.lowtrades.com/

http://www.eoption.com/

http://www.just2trade.com/


Equivalent -AUD$90,909 +USD$100,000 An FX loss of ~A$9,091 Mathematics is US$100,000 ÷ 1.1 = A$90,909. Let’s look at this the other way around where the AUD weakens by 10%, that is, the USD strengthens by 11.1%. AUDUSD = 1 : 1 Deposit money into a USD account -AUD$100,000 +USD$100,000 AUDUSD = 1 : 0.9 Equivalent -AUD$100,000 USD$111,111 An FX gain of ~A$11,111 Mathematics is US$100,000 ÷ 0.9 = A$111,111.

8.2 Hedging Currency Risk The risk is that the AUD strengthens against the USD, not that it weakens. What you do about currency risk will depend on a number things including:

1. What your view is of the direction of the AUD vs the USD during the term that your capital will be in USD.

2. Whether you wish to diversify your home currency by spreading some of your investment capital into a foreign currency, or not. This is a big picture long term decision that is typically taken to protect your wealth due to your home currency weakening over the long term.

3. Whether your USD trading capital will be in USD all the time or whether it is in USD only for the hold-period of each trade, or just during SPA3 High Risk market periods.

As such there are a number of avenues open to active investors that trade the US equity markets. One way to minimise currency risk from your home currency strengthening is to hedge against a potential rise in your home currency. Let’s look at how this can be achieved using the AUD. To protect against the AUD strengthening you can sell the USD equivalent of your AUD capital. This is a hedge against the strengthening of your home currency. Let’s look at an example. At the time that you deposit your AUD into a USD account assume that AUDUSD = 1:1. AUDUSD = 1 : 1 Deposit money into a USD account -AUD$100,000 +USD$100,000 Sell USD, buy AUD (= Short USD = hedge) +AUD$100,000 -USD$100,000 The hedge is achieved via the FX markets and hence you do not need to have the entire USD100,000 in the first place to be able to ‘sell’ it for the equivalent AUD. Typically a 1% margin is required to put the hedge in place, that is USD1,000 per USD100,000 that is being sold. So the hedge line will now look like this. Sell USD, buy AUD (= Short USD = hedge) +AUD$100,000 -USD$1,000 (1% margin)



The margin doesn’t actually get deducted from your account but the cash equivalent must be in your account to cover the margin. However, the costs associated with the transaction are deducted from your account. This is dealt with in the next subsection. Now let’s assume that the AUD strengthens by roughly 10% such that AUD1.00 = USD 1.10. AUDUSD = 1 : 1.1 Equivalent (capital) -AUD$90,909 +USD$100,000 Hedge value +AUD$10,000 -USD$1,000 (1% margin) P/L (Before costs) +AUD$ 909 Of course, if the AUD weakens then the hedge will decrease in value. If it decreases in value by more than the margin amount then be aware that if there is not sufficient cash in the account a ‘margin call’ will is issued. Remember though that the AUD value of the USD account will have increased in value by a similar amount.

8.3 Currency Hedging Costs You must also consider that there is a small spread to pay for the FX hedge and that there are ongoing holding costs, because the position is leveraged. The spread is a one-off commission cost at time of putting the hedge in place. This is typically in the range of 2 to 4 pips, or between USD20 and USD40 per USD100,000. If hedging smaller amounts then some FX providers will have a minimum of USD10 commission. The spread cost occurs at both ends of the transaction, that is, when it is opened and when it is closed again. The holding costs are the ones that you need to be aware of. These are called Tom/Next Rollover. Active investors that are not well versed with currency trading should gain an understanding of all the costs associated with holding open FX positions over a period of time. It is possible to have positive holding costs, that is, the trader is paid a fee. This occurs when interest rates in the county of the home currency are much higher than interest rates in the country of the foreign currency. For more information on these costs please refer to this webpage on the Saxo Bank website: http://www.saxobank.com/prices/forex/tom-next-rollover . Other FX providers provide similar information. Their costs will differ from one provider to the next. In particular, review the “Historic Swap Points”. You will see that the holding cost for being long the AUD (i.e. short the USD), which is what is required to hedge the USD position as per the explanation above, for 12 December 2012 was -0.000056. The holding cost for being short the AUD (i.e. long the USD) was -0.000099. Therefore, there is a $5.60 holding cost per day per USD100,000 that the trader is long the AUD against the USD (i.e. short the USD). The Tom/Next Rollover will change every day as interest rates fluctuate. The holding cost for the USDZAR on 12 December 2012 was +0.001386 and +0.000984, for long and short, respectively. This means that the FX account will be credited every day. The positive differential is due to the high interest rates in South Africa compared to the USA.


http://www.saxobank.com/prices/forex/tom-next-rollover


As the interest rate differential between countries narrows the Tom/Next Rollover increases. For instance, as the difference between interest rates in Australia and the USA narrows the Tom/Next Rollover cost increases and it decreases if the gap in interest rates widens. Notice that the weekend Tom/Next Rollers are roughly 3x those for weekdays, that is, holding costs apply to elapsed days not business days. Assume, therefore, that a SPA3 Low Risk market lasts around 3 months, or 90 days, for a fully hedged USD100,000 trading account. The ongoing Tom/Next Rollover costs, at around $6 a day, will be approximately USD540 for the 3 months. These costs will be deducted from your account on a daily basis and converted to AUD. When a High Risk market signal occurs and all open trades are closed, the trading capital that is in USD can be converted back into AUD at the then exchange rate for a spread cost of between 2 and 4 pips, depending on the FX provider that is used. At this time the hedge trade should also be closed. Alternatively, trading capital can be left in USD and the hedge trade left open. This scenario would continue to incur Tom/Next Rollover costs. A last word on this is that as one’s USD trading account increases in value the hedge can be topped up in, say, USD10,000 increments. Each top up will incur costs.

9 It all starts at the Trading Plan This is an extremely important section but at the expense of being too repetitive I have elected to steer readers in the direction of what was written in the September White Paper rather than just repeating the same information here.

Refer to the section entitled “Begin with the end in mind” in the Share Wealth Systems September 2012 White Paper.

10 Catch 22 – the major problem all investors face What position sizing approach a trader uses to trade is directly linked to the trader’s risk objective and reward objective that they state in their Trading Plan.

The Catch 22: how does a trader know in advance what position sizing approach to use to remain within their risk objective while also have a high probability of achieving their reward objective?

Answer: they don’t. Well, nearly every trader doesn’t.

Stating a risk objective is easy enough, just state a number, like 20% maximum drawdown. Now what? Too large a position size will probably rush the trader to a maximum drawdown limit very quickly thereby taking the trader out of the opportunity flow that the market offers. Too small a position size might ensure that the maximum drawdown limit is never reached but also ensure that the reward objective is also never met.



How is this Catch 22 resolved? Using exploratory simulation.

11 Research Environment The Share Wealth Systems September 2012 White Paper describes the research environment used for conducting exploratory simulation.

12 Risk Management and Money Management Rules in SPA3

12.1 Position Sizing calculation See the Share Wealth Systems September 2012 White Paper and Addendum 1 to this Paper.

The topic “Portfolio Risk and a Master Control” is also covered in the September 2012 White Paper.

13 Portfolio Limits and Boundaries This section provides the range of SWS suggested position sizes based on the analysis of the exploratory simulation research. The respective ‘Default XNAS Profile’ SPA3 parameters were used to generate the trades’ database that was used for the respective simulations.

13.1 Different SIROC parameters From a SPA3 Revised Edge perspective, the following SIROC parameters were researched on the NASDAQ, where the third parameter is the daily SIROC EMA setting:

• SIROC 13 5 5 • SIROC 17 7 8 • SIROC 19 7 8 • SIROC 21 8 8 • SIROC 26 9 8 • SIROC 30 10 8

Only two sets of SIROC parameter settings were researched using exploratory simulation, the SIROC 21 8 8 and SIROC 13 5 5. However SPA3 users can quite safely use SIROC 17 7 8 and SIROC 19 7 8 as well, as can any other either SIROC settings, but any of these four are recommended. The Trade Risk % risk tables are programmed into TradeMaster for all four SIROC settings.

For each of the two SIROC settings, SIROC 21 8 8 and SIROC 13 5 5, that were simulated, two portfolio starting capital amounts were researched, $25,000 and $100,000. Two different brokerage rates were also researched and different liquidity settings. A number of different Portfolio Risk % settings were researched to calculate position size, ranging from 0.3% to 2%.



13.2 Understanding Box Plots The Share Wealth Systems September 2012 White Paper provides an explanation on box-plots.

13.3 Portfolio Limits using SIROC 21 8 This section provides Portfolio Risk % boundaries for portfolios that use the SIROC 21 8 8 parameter settings, all other SPA3 settings being as per the SPA3 Parameters in the Profile panel in GPS. Trades are closed immediately when the Market Risk turns to High Risk.

HINT: View the ‘box charts’ and simulated portfolio equity curves alongside each of the tables below, so as to compare and follow the reasoning behind the

suggested limits and boundaries. The commentary below will also make more sense.

13.3.1 $25,000 Portfolios


Risk % Ideal Max


Sections Brokerage: $9.95, x10 Liquidity 0.5 0.8 – 1.5 1.5 1.2% can be considered 15.7 Brokerage: $4.95, x10 Liquidity 0.4 0.5 – 1.5 1.5 1.2% can be considered 15.8

13.3.1.1 Comments

When viewing the Chart Sections you will notice that the box-plots jump from 1.0% Risk % to 1.5% Risk %. A Risk % of, say, 1.2% can be used. The outcomes should be better than 1.5% and have less simultaneously open positions than a Risk % of 1.0%.

13.3.2 $100,000 Portfolios


Risk % Ideal Max


Sections Brokerage: $9.95, x5 Liquidity 0.3 0.3 – 1.0 1.5 15.3 Brokerage: $9.95, x10 Liquidity 0.3 0.3 – 0.8 1.5 0.9% can be considered 15.4 Brokerage: $4.95, x5 Liquidity 0.3 0.3 – 1.0 1.5 15.5 Brokerage: $4.95, x10 Liquidity 0.3 0.3 – 0.8 1.5 0.9% can be considered 15.6

13.3.2.1 Comments

The larger $100,000 portfolios are able to sustain smaller Risk %’s than the smaller $25,000 portfolios because brokerage doesn’t have as big an effect on smaller position sizes.



13.4 Portfolio Limits using SIROC 13 5 5 This section provides Portfolio Risk % boundaries for portfolios that use the SIROC 13 5 5 parameter settings, all other SPA3 settings being as per the SPA3 Parameters in the Profile panel in GPS. Trades are closed immediately when the Market Risk turns to High Risk.

HINT: View the ‘box charts’ and simulated portfolio equity curves alongside each of the tables below, so as to compare and follow the reasoning behind the

suggested limits and boundaries.

13.4.1 $25,000 Portfolios


Risk % Ideal Max


Sections Brokerage: $9.95, x10 Liquidity 0.4 0.8 – 1.0 1.5 15.15 Brokerage: $4.95, x10 Liquidity 0.3 0.5 – 1.0 1.5 15.16

13.4.1.1 Comments

The SIROC 13 5 5 performs slightly worse than the SIROC 21 8 on the NASDAQ. Hence positions sizes cannot be pushed as high as with the SIROC 21 8 setting.

13.4.2 $100,000 Portfolios


Risk % Ideal Max


Sections Brokerage: $9.95, x5 Liquidity 0.2 0.3 – 1.0 1.5 15.11 Brokerage: $9.95, x10 Liquidity 0.2 0.3 – 0.6 1.0 15.12 Brokerage: $4.95, x5 Liquidity 0.2 0.2 – 0.8 1.2 15.13 Brokerage: $4.95, x10 Liquidity 0.2 0.2 – 0.6 0.8 15.14

13.4.2.1 Comments

The SIROC 13 5 5 performs slightly worse than the SIROC 21 8 on the NASDAQ. Hence positions sizes cannot be pushed as high as with the SIROC 21 8 setting.

13.4.3 Number of Simultaneously Open Positions

The Risk % selected for any portfolio will be the main factor that determines how many simultaneously open positions a portfolio may have. The other main factor will be the volatility of trades in any particular market. SPA3 active investors can get a very good idea of how many open positions they will need to manage for any chosen Risk % for their portfolio. The following graphs provide a good insight into this.



The Open Positions charts above show the number of simultaneous open positions for a 0.2%, 0.3%, 0.4%, 0.5%, 0.6% and 0.8% Portfolio Risk % on the ASX. 0.2% and 0.3% will be a comparatively high number of positions to manage for most private active investors. 0.4% may still be a little on the high side but the risk to reward at this Risk % may make it worthwhile for some portfolio scenarios depending on starting capital and brokerage. Risk %’s of 0.5% - 0.8% should be just fine.

The following two graphs show the number of simultaneously open positions from simulating trading SPA3 on the NASDAQ with Risk % of 0.6% and 0.8%. Compare these to the corresponding Risk % for the ASX. Besides periods of volatility the number of simultaneously open positions is very similar.



The following two graphs show the number of simultaneously open positions from simulating trading SPA3 on the ASX and NASDAQ, respectively, with Risk % of 1.0%.

Using a Risk% of 1.5% will reduce the number of open positions to an average of around 8 - 9 and of 2.0% to an average of 6 - 7.

This section is provided here to assist SPA3 active investors with selecting the Risk % for their portfolio.



14 Exploratory Simulation

14.1 Introduction Please refer to the December 2011 White Paper for an introduction to exploratory simulation and the September 2012 White Paper for further detailed discussion.

Exploratory Simulation allows you to determine in advance if your objectives are achievable with a far higher degree of certainty than with not using exploratory simulation, by stress testing the variables which you are in control of in an overall environment which you are not in control of.

14.2 Extent of exploratory simulation research Detailed research for the SPA3 FOR NASDAQ project started in June 2011. It was put to one side while the exploratory simulation was completed for the ASX and resumed in October 2012. 100’s of 1000’s of portfolio simulations have been run for the SPA3 FOR NASDAQ project. With the established environment in place for the ASX, only incremental effort was required to conduct the necessary exploratory simulation for the NASDAQ. However, projects such as these are not your typical “9 – 5” type efforts as simulations run overnight and over weekends and require ongoing monitoring.

In the exploratory simulations conducted and the results of which are provided in this paper the following criteria were used:

• NASDAQ only trades from 3/1/2000 (first trading day of the century) to 28/9/2012. • All listed and delisted NASDAQ stocks during this period. This means that a stock that was

delisted after January 2000 and before the end will be included in the simulations. It should be noted that some stocks in the USA markets “drop off” their exchange and trade as a ‘pink sheet’ in the OTC environment. Unfortunately, these stocks have not been included in exploratory simulations.

• An open-ended number of simultaneously open positions per portfolio. • Randomly chosen trade selection from available trades whenever there was available capital

to be invested, according to Risk Profile 1. o This means that on any given day where there was more than one SPA3 trade

available to select from, the trade was chosen on a purely random basis, provided the trade was liquid enough. If not, then the next trade that was liquid enough was selected randomly.

o If there was insufficient capital available to fill a required position size then the position size was NOT reduced to fill the position. This means that there are times through the life of the simulations that portfolios were not fully invested. You may devise a set of common sense rules for your own Trading Plans

whereby you reduce the position size to appoint but no less to make the trade with a smaller position size.

• The Portfolio Risk % for new position sizes were not decreased or increased for each simulation, they remained the same, based on the position size calculation, throughout the research period.



• No pyramiding or lightening was used. • Risk Profile 1 was used in all simulations, that is portfolios were moved 100% into cash when

a SPA3 High Market Risk occurred. • During Low Market Risk, all High Sector Risk trades were allocated a full position, that is,

there was no reduction in position size for Sector Risk. • All positions were closed immediately on the trading day after a SPA3 High Market Risk

signal occurred. • Simulations included brokerage as shown. Additional SEC fees have not been included which

might be a few cents per transaction. • No dividends or interest have been included in the equity curves. The additional returns that

would be generated from these two sources would be substantial in absolute terms and in compounding terms over a period of 12 years.

• No tax is included in the equity curves except.

Each historical portfolio equity curve is an unrealized profit equity curve or a mark-to-market equity curve with the portfolio value being recalculated on a daily basis for the life of the portfolio.

14.3 Research period Some comment on the research period that has been used for the portfolio simulation is required.

Big picture technical analysis will show that a secular bear market in equities started on the $DJI in January 2000 and in March 2000 on the NASDAQ Composite and S&P500. However, the period chosen has the following traits:

• Two major bear markets in the NASDAQ Composite of 77% and 55%, from peak to trough. These might be termed primary bear markets within a secular bear market.

• Major geopolitical events in September 2001 in New York and July 2007 in London. • Major natural disaster events such as the tsunami in Japan in March 2011. • Primary bull markets within the secular bear market such from March 2003 of 140% and

March 2009 of 150% (may not be over yet), from trough to peak. • An overall downward bias of -24% over the research period but -38% from the highest peak

on 10/3/2003.

This is a fantastic sample research period with which to conduct exploratory simulation to demonstrate the robustness of a methodology’s timing, risk management and position sizing rules.

It is not secular bull markets such as 1982 to January 2000 that investors need worry about, it is secular bear markets such as we have experienced since 2000 and such as 1966 to 1982 that investors must prepare themselves for. If your strategy can make a decently positive headway during such periods then handling the secular bull market will be a fantastic ride.

As mentioned above, all the exploratory simulations conducted in this paper have been done with SPA3’s Risk Profile 1 risk management approach. This begs the question, is using Risk Profile 2 still a valid risk management approach? It is our considered view that it is, but probably only during secular bull markets. Another research project ……….



15 Exploratory Simulation Outcomes

15.1 Introduction

This section will show the graphical outcomes from this round of SPA3 research.

The main purpose of this section is to provide graphical output to support SPA3 users choosing what position size to use for their own respective investing scenarios.

Whilst there may seem to be plenty of pages, not all pages are relevant to everybody. The detail has been provided so that each SPA3 user can hone in on a portfolio scenario that is relevant to them. Of course, perusing all the material can be of great educational value. In the future we will investigate providing access to this information via a tool of sorts.

The other purposes of this section are to:

1. take the reader through a process of gaining understanding of what steps were taken to revise the SPA3 Money Management rules according to the objectives set for the research project,

2. understand why the SPA3 Revised Money Management rules are an improvement on the previous money management rules,

3. understand how extremely important it is to get one’s position sizing correct in harmony with their system and execution environment, and

4. importantly, build belief and trust in the methodology such that it is executed with consistency and confidence to be able to grow one’s trading capital to reach ones financial objectives.

Only the ASX research results are provided at this stage for unleveraged trading. JSE research results and the NASDAQ research results will be provided in future papers, as will leveraged trading with CFDs.

Each set of charts will be headed according to the following portfolio variables:

1. The amount of starting capital as at 3/1/2000, the first trading day of 2000. 2. The SIROC parameters used. 3. The liquidity check to ensure that there was sufficient liquidity to take the trade. 4. The brokerage rate used for the life of the simulation.

Two types of graphs will be shown for each portfolio scenario, straw-broom graphs and box plots.

Each of the straw-broom charts show 1000 unique simulated portfolio equity curves. Each straw-broom chart has been back-tested with a different position size. Each equity curve has a unique mix of SPA3 trades that have been selected randomly based on meeting the liquidity check for the simulation. This statement applies to all the straw-broom charts that are in this White Paper.

A quick scan of the straw-broom graphs will help reveal the better Portfolio Risk %’s to use for each portfolio scenario. Notes are provided for most of the portfolio scenarios.

The box plots that are provided for each scenario show the following measurements:



1. Portfolio Performance Index.

Investors frequently associate risk with failure to attain a target return. The target is typically the return offered by a benchmark such as the relevant market index. For funds invested in the Australian stock market the common benchmark is the All Ordinaries Index ($XAO) or the S&P/ASX 200 Index ($XJO). Such benchmark comparisons are widespread in the investment industry, along with a fear of underperforming them. Benchmarks offer a fixed point of reference against which different market investments can be measured, in particular the expected return.

An investor expects that over a period of time that their portfolio will outperform the benchmark returns. As time passes the probability that a portfolio WILL outperform the benchmark is increased by having returns:

• that are more frequently greater than the benchmark, and • that are larger than the benchmark, including small losses.

“The Portfolio Performance Index (PPI) takes both of these into account to generate a number that measures a portfolios likelihood of outperforming the benchmark.”

This measurement can be used to rank several portfolios alongside each other. The benefits of this form of outperformance measurement are:

• The comparison can take place regardless of the starting capital of each portfolio. • Continuous outperformance over the period is ranked above short periods of large

outperformance, which create the false perception of overall outperformance. • The returns do not have to adhere to a normal statistical distribution, which would

typically interfere with the result.

2. Downside Deviation Factor

It would be generally agreed that when a portfolio has loss trades, it’s best if they aren’t too big and don’t occur too often. This statement suggests there should be two dimensions to any risk measurement; magnitude and probability. The common risk measurement of Average Loss % provides the dimension of magnitude but not probability. An alternative measurement is Downside Deviation (DSD) which measures the variation of returns below a target return. The result is a value that not only provides the dimension of magnitude in a statistical manner but also includes the second dimension, the probability of Loss.

An investor expects that over a period of time that the risk, in the form of loses, experienced by their portfolio will be less than that of the benchmark. The perceived risk is loosely assessed by the investor in terms of the actual magnitude and frequency experienced, against the benchmark. The Downside Deviation Factor (DDF) is a measurement that allows the risk experienced by several portfolios to be accurately compared against that presented by a benchmark.

The DDF, takes the Downside Deviation (DSD) for a portfolio and compares it directly against the DSD for the chosen benchmark.



“The DDF represents how much more or less risk, by a factor, a portfolio presents compared to the benchmark.”

The DDF ranges between 0 and 2, with a factor of 1 meaning that the portfolio offers the same risk as the benchmark. A factor below 1 means that the portfolio offers less risk, and a factor greater than 1 means that it offers more risk.

(Note, the DDF range is not linear so don’t interpret a DDF of 2 as twice as much risk. In fact it’s a lot more than that!)

3. Daily Geometric Mean. This the single daily growth factor for the entire life of the simulated portfolios. Use this to determine the best performing position size for any given portfolio scenario. The higher the better but it must be analysed in conjunction with the Portfolio Performance Index and Downside Deviation Factor.

4. Maximum Drawdown %. This is the single maximum drawdown that each of the unique portfolios reached during the life of that portfolio. All other drawdown levels would have been less than the maximum drawdown for the life of the portfolio. In some instances underwater equity curves have been included to provide an insight into the nature of drawdowns throughout the life of the portfolio in comparison to the single maximum drawdown.

5. Unallocated Equity Deviation. A reading of 30% means that the portfolio was unallocated for 30% of the life of the portfolio which means that it was 70% allocated. Remember that all the simulations used SPA3 Risk Profile 1 which means that the portfolio was 100% unallocated during High Risk market periods, that is, in cash.

6. Number of Transactions. This is transactions, not trades. Note, to calculate the total number of trades for the life of the portfolio divide this number by two.

7. Profit Ratio. This is the average wining trade divided by the average losing trade, including brokerage. Remember that brokerage increases the size of loss trades and reduces the size of winning trades.

8. Win Rate. This is the percentage of winning trades over the life of the portfolio. This is net of brokerage.

In this section there are two sub-sections of portfolio simulation and associated graphical outputs, which also include comments where relevant:

1. SIROC 21 8 SPA3 parameters that closed all open positions immediately when a High Market Risk signal occurred.

2. SIROC 13 5 5 SPA3 parameters that closed all open positions immediately when a High Market Risk signal occurred.



15.2 SIROC 2108, Liquidity Multiple 10x, Brokerage $4.95, “Base” Simulation This SIROC 21 8 simulation is a “base” simulation using “base” money management, that is 10 open positions with each position 10% of the current portfolio value. A “base” money management simulation is conducted each with and without Market Risk. This was done with a $25,000 starting portfolio and a $100,000 starting portfolio.

The following criteria were used for the scenarios in this section:

• SIROC 21 8 • Liquidity multiple = 10x • Brokerage of $4.95 flat rate • Only trades from liquidity of $50,000 to $2,000,000 • Volatility from ATRVE = 2 up to 12 • Position sizing: 10 positions at 10% each • With and without Market Risk (= Systematic Risk)

1. Run 1463 $100,000 with NO Market Risk 2. Run 1464 $25,000 with NO Market Risk 3. Run 1461 $100,000 with Market Risk 4. Run 1462 $25,000 with Market Risk

The simulation with “base” money management without Market Risk is used to determine a base growth and maximum drawdown simulation from to determine any improvement due to altered risk and money management conditions.



0

100

200

300

400

500

600

700

800

900

1000

100k No MR 100k MR 25k No MR 25k MR

Portfolio

Portfolio Performance Index

200101-201209, XNAS SIROC 2108 Liq10 B4.95 LiqLim[50:2000) A[2-12) PR[10%] (PV100k,25k)

0.5

0.6

0.7

0.8

0.9

1.0

1.1

1.2


Portfolio

Downside Deviation Factor


1

1.0001

1.0002

1.0003

1.0004

1.0005

1.0006

1.0007

1.0008

1.0009

1.001


Portfolio

Daily Geometric Mean


0

10

20

30

40

50

60

70

80

90

100


Portfolio

Maximum Drawdown (%)




40

42

44

46

48

50

52

54

56

58

60


Portfolio

Unallocated Equity Deviation (%)


0

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000


Portfolio

Number of Transactions


0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0


Portfolio

Profit Ratio


34

36

38

40

42

44

46

48

50

52

54

56

58


Portfolio

Win Rate (%)





SPA3 for NASDAQ White Paper | December 2012 15.2.1 5th, 50th & 95th Percentiles and Underwater Curves

The outputs below are for the following simulation:

• $100,000 starting capital. • No Market Risk, i.e. the portfolio trades through all market conditions. • No money management, that is, 10 open positions at 10% per position (from run 1463 above). • Displays charts of 5th (blue), 50th (green) and 95th (pink) percentiles as at the end of the simulation period (28th September 2012), the 2nd chart being in semi-log

mode. • The underwater equity curve is of the portfolio at the 95th percentile. • The number of open trades is of the portfolio at the 95th percentile.

This is the “starting position” for exploratory simulation. The equity curves provided here demonstrate that there is an edge because all 1000 simulated portfolio equity curves outperformed the NASDAQ benchmark equity index and all, bar many simulated portfolios in Run 1464, finished in profit. The reason that Run 1464 battled was due to a combination of a small starting capital, brokerage the smaller edge that exists for trades that are executed during adverse market conditions. Market Risk improves the outcomes dramatically in Run 1462 when Market Risk is used.

Even though this “starting position”, which excludes Market Risk (Systematic Risk) and money management using risk adjusted position sizing, makes money, the volatility of the equity curves, the maximum drawdowns experienced and the variation between the best and worst is unacceptable.

The research task is to use risk and money management techniques to greatly reduce maximum drawdown and to narrow the variation between the 5th and 95th percentiles. If this can be done it will demonstrate robustness of the methodology when all components of the trading system, risk management and money management come together.

In essence, what sound risk and money management does is not greatly improve the upside but greatly improve the downside. This means that the research task is to bring the pink line closer to the blue line, that is, make the worst scenario far better.





15.3 SIROC 2108, $100,000, Liquidity Multiple 5x, Brokerage $9.95 The following criteria were used for the scenarios in this section:

• SIROC 21 8 • Liquidity multiple = 5x • Brokerage of $9.95 flat rate • Only trades from liquidity of $50,000 to $2,000,000 • Volatility from ATRVE = 2 up to 12 • With Market Risk (= Systematic Risk) • Position sizing as follows:

1. Run 1280 0.3% Portfolio Risk %. 2. Run 1281 0.4% 3. Run 1282 0.5%. 4. Run 1283 0.6%. 5. Run 1284 0.8%. 6. Run 1285 1%. 7. Run 1286 1.5%. 8. Run 1287 2%.



0

100

200

300

400

500

600

700

800

900

1000

0.2 0.3 0.4 0.5 0.6 0.8 1.0 1.5 2.0 3.0

Risk %


200101-201209, XNAS SIROC 2108 100k Liq5 B9.95 LiqLim[50:2000) A[2-12) (Risks)

0.5

0.6

0.7

0.8

0.9

1.0

1.1

1.2

0.2 0.3 0.4 0.5 0.6 0.8 1.0 1.5 2.0 3.0

Risk %



1

1.0001

1.0002

1.0003

1.0004

1.0005

1.0006

1.0007

1.0008

1.0009

1.001

0.2 0.3 0.4 0.5 0.6 0.8 1.0 1.5 2.0 3.0

Risk %



0

10

20

30

40

50

60

0.2 0.3 0.4 0.5 0.6 0.8 1.0 1.5 2.0 3.0

Risk %





40

42

44

46

48

50

52

54

56

58

60

0.2 0.3 0.4 0.5 0.6 0.8 1.0 1.5 2.0 3.0

Risk %



0

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

0.2 0.3 0.4 0.5 0.6 0.8 1.0 1.5 2.0 3.0

Risk %



0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

0.2 0.3 0.4 0.5 0.6 0.8 1.0 1.5 2.0 3.0

Risk %

Profit Ratio


40

42

44

46

48

50

52

54

56

58

0.2 0.3 0.4 0.5 0.6 0.8 1.0 1.5 2.0 3.0

Risk %

Win Rate (%)







SPA3 for NASDAQ White Paper | December 2012 15.3.1 5th, 50th & 95th Percentiles and Underwater Curves, 0.8% Risk %


• $100,000 starting capital. • 0.8% Portfolio Risk % (Run 1284). • Displays charts of 5th (blue), 50th (green) and 95th (pink) percentiles as at the end of the simulation period (28th September 2012), the 2nd chart being in semi-log


To put the Maximum Drawdown’s into perspective the 5th, 50th and 95th percentiles for Maximum Drawdown are 20%, 23.8% and 28.7%. That is, there are just 5% of the 1000 simulated portfolios for this portfolio scenario that have a worse Maximum Drawdown of 28.7%.



25000

225000

425000

625000

825000

1025000

1225000

Mark-to-market Equity Curve

Max Drawdown:26.8%, 23.8%, 21.1%

Ending Portfolio Value:$1,176,711, $905,535, $618,895

Win Rate:50.1%, 47.3%, 48.3%

25000

250000


0

5

10

15

20

25

30

35

Open Positions



15.4 SIROC 2108, $100,000 Liquidity Multiple 10x, Brokerage $9.95 The following criteria were used for the scenarios in this section:





0

100

200

300

400

500

600

700

800

900

1000

0.2 0.3 0.4 0.5 0.6 0.8 1.0 1.5 2.0 3.0

Risk %



0.5

0.6

0.7

0.8

0.9

1.0

1.1

1.2

0.2 0.3 0.4 0.5 0.6 0.8 1.0 1.5 2.0 3.0

Risk %



1

1.0001

1.0002

1.0003

1.0004

1.0005

1.0006

1.0007

1.0008

1.0009

1.001

0.2 0.3 0.4 0.5 0.6 0.8 1.0 1.5 2.0 3.0

Risk %



0

10

20

30

40

50

60

0.2 0.3 0.4 0.5 0.6 0.8 1.0 1.5 2.0 3.0

Risk %





40

42

44

46

48

50

52

54

56

58

60

0.2 0.3 0.4 0.5 0.6 0.8 1.0 1.5 2.0 3.0

Risk %



0

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

0.2 0.3 0.4 0.5 0.6 0.8 1.0 1.5 2.0 3.0

Risk %



0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

0.2 0.3 0.4 0.5 0.6 0.8 1.0 1.5 2.0 3.0

Risk %

Profit Ratio


40

42

44

46

48

50

52

54

56

58

0.2 0.3 0.4 0.5 0.6 0.8 1.0 1.5 2.0 3.0

Risk %

Win Rate (%)













25000

225000

425000

625000

825000

1025000

Mark-to-market Equity CurveMax Drawdown:

26.2%, 23.1%, 23.2%Ending Portfolio Value:

$900,263, $728,399, $593,391Win Rate:

49.5%, 48.3%, 48%

25000

250000


-90.00

-80.00

-70.00

-60.00

-50.00

-40.00

-30.00

-20.00

-10.00

0.00

Underwater Equity Curve compared to the Nasdaq

0

5

10

15

20

25

30

35

40

45

Open Positions





1. Run 1320 0.3% Portfolio Risk %. 2. Run 1321 0.4% 3. Run 1322 0.5%. 4. Run 1323 0.6%. 5. Run 1324 0.8%. 6. Run 1325 1%. 7. Run 1326 1.5%. 8. Run 1327 2.0%.



0

100

200

300

400

500

600

700

800

900

1000

0.2 0.3 0.4 0.5 0.6 0.8 1.0 1.5 2.0 3.0

Risk %



0.5

0.6

0.7

0.8

0.9

1.0

1.1

1.2

0.2 0.3 0.4 0.5 0.6 0.8 1.0 1.5 2.0 3.0

Risk %



1

1.0001

1.0002

1.0003

1.0004

1.0005

1.0006

1.0007

1.0008

1.0009

1.001

0.2 0.3 0.4 0.5 0.6 0.8 1.0 1.5 2.0 3.0

Risk %



0

10

20

30

40

50

60

0.2 0.3 0.4 0.5 0.6 0.8 1.0 1.5 2.0 3.0

Risk %





40

42

44

46

48

50

52

54

56

58

60

0.2 0.3 0.4 0.5 0.6 0.8 1.0 1.5 2.0 3.0

Risk %



0

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

0.2 0.3 0.4 0.5 0.6 0.8 1.0 1.5 2.0 3.0

Risk %



0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

0.2 0.3 0.4 0.5 0.6 0.8 1.0 1.5 2.0 3.0

Risk %

Profit Ratio


40

42

44

46

48

50

52

54

56

58

0.2 0.3 0.4 0.5 0.6 0.8 1.0 1.5 2.0 3.0

Risk %

Win Rate (%)








15.6 SIROC 2108, $100,000, Liquidity Multiplier 10x, Brokerage $4.95 The following criteria were used for the scenarios in this section:





0

100

200

300

400

500

600

700

800

900

1000

0.2 0.3 0.4 0.5 0.6 0.8 1.0 1.5 2.0 3.0

Risk %



0.5

0.6

0.7

0.8

0.9

1.0

1.1

1.2

0.2 0.3 0.4 0.5 0.6 0.8 1.0 1.5 2.0 3.0

Risk %



1

1.0001

1.0002

1.0003

1.0004

1.0005

1.0006

1.0007

1.0008

1.0009

1.001

0.2 0.3 0.4 0.5 0.6 0.8 1.0 1.5 2.0 3.0

Risk %



0

10

20

30

40

50

60

0.2 0.3 0.4 0.5 0.6 0.8 1.0 1.5 2.0 3.0

Risk %





40

42

44

46

48

50

52

54

56

58

60

0.2 0.3 0.4 0.5 0.6 0.8 1.0 1.5 2.0 3.0

Risk %



0

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

0.2 0.3 0.4 0.5 0.6 0.8 1.0 1.5 2.0 3.0

Risk %



0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

0.2 0.3 0.4 0.5 0.6 0.8 1.0 1.5 2.0 3.0

Risk %

Profit Ratio


40

42

44

46

48

50

52

54

56

58

0.2 0.3 0.4 0.5 0.6 0.8 1.0 1.5 2.0 3.0

Risk %

Win Rate (%)

















1. Run 1421 0.4% Portfolio Risk %. 2. Run 1422 0.5%. 3. Run 1423 0.6%. 4. Run 1424 0.8%. 5. Run 1425 1%. 6. Run 1426 1.5%.



0

100

200

300

400

500

600

700

800

900

1000

0.2 0.3 0.4 0.5 0.6 0.8 1.0 1.5 2.0 3.0

Risk %



0.5

0.6

0.7

0.8

0.9

1.0

1.1

1.2

0.2 0.3 0.4 0.5 0.6 0.8 1.0 1.5 2.0 3.0

Risk %



1

1.0001

1.0002

1.0003

1.0004

1.0005

1.0006

1.0007

1.0008

1.0009

1.001

0.2 0.3 0.4 0.5 0.6 0.8 1.0 1.5 2.0 3.0

Risk %



0

10

20

30

40

50

60

0.2 0.3 0.4 0.5 0.6 0.8 1.0 1.5 2.0 3.0

Risk %





40

42

44

46

48

50

52

54

56

58

60

0.2 0.3 0.4 0.5 0.6 0.8 1.0 1.5 2.0 3.0

Risk %



0

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

0.2 0.3 0.4 0.5 0.6 0.8 1.0 1.5 2.0 3.0

Risk %



0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

0.2 0.3 0.4 0.5 0.6 0.8 1.0 1.5 2.0 3.0

Risk %

Profit Ratio


40

42

44

46

48

50

52

54

56

58

0.2 0.3 0.4 0.5 0.6 0.8 1.0 1.5 2.0 3.0

Risk %

Win Rate (%)






The ideal Portfolio Risk % for this portfolio scenario is would be 08% to 1.0% but could stretch it up to 1.5% if the trader wishes to minimise the number of open simultaneously open positions.





1. Run 1431 0.4% Portfolio Risk %. 2. Run 1432 0.5%. 3. Run 1433 0.6%. 4. Run 1434 0.8%. 5. Run 1435 1%. 6. Run 1436 1.5%.

Notice in the box-plots below that the Win Rate for the larger positions size from Portfolio Risk % = 1.5% that can rise above 50%. This is because there are far fewer simultaneously open positions for large position sizes which allows luck to play more of role. The better performing portfolios were lucky enough to have randomly picked more winning trades. However, the variation of outcomes is far wider, as seen in the Daily Geometric Mean and Maximum Drawdown box-plots, meaning that the worse portfolios do worse than those with smaller position sizes.



0

100

200

300

400

500

600

700

800

900

1000

0.2 0.3 0.4 0.5 0.6 0.8 1.0 1.5 2.0 3.0

Risk %



0.5

0.6

0.7

0.8

0.9

1.0

1.1

1.2

0.2 0.3 0.4 0.5 0.6 0.8 1.0 1.5 2.0 3.0

Risk %



1

1.0001

1.0002

1.0003

1.0004

1.0005

1.0006

1.0007

1.0008

1.0009

1.001

0.2 0.3 0.4 0.5 0.6 0.8 1.0 1.5 2.0 3.0

Risk %



0

10

20

30

40

50

60

0.2 0.3 0.4 0.5 0.6 0.8 1.0 1.5 2.0 3.0

Risk %





40

42

44

46

48

50

52

54

56

58

60

0.2 0.3 0.4 0.5 0.6 0.8 1.0 1.5 2.0 3.0

Risk %



0

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

0.2 0.3 0.4 0.5 0.6 0.8 1.0 1.5 2.0 3.0

Risk %



0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

0.2 0.3 0.4 0.5 0.6 0.8 1.0 1.5 2.0 3.0

Risk %

Profit Ratio


40

42

44

46

48

50

52

54

56

58

0.2 0.3 0.4 0.5 0.6 0.8 1.0 1.5 2.0 3.0

Risk %

Win Rate (%)






15.8.1 5th, 50th & 95th Percentiles and Underwater Curves, 0.8% Risk %






6000

60000


Max Drawdown:24.3%, 25.6%, 30.2%

Ending Portfolio Value:$318,165, $200,295, $134,990



15.9 SIROC 2108, “Whole Market”, $100K, Liquidity Multiple 10x, Brok. $9.95 & $4.94 Before finishing up with the SIROC 21 8 simulation runs, let’s see how a “whole market” NASDAQ simulation compares with a limited liquidity run at the same 0.6% Portfolio Risk %. The ‘whole market’ still has a lower liquidity limit of $50,000 but no upper liquidity limit.


• SIROC 21 8 • Liquidity multiple = 10x • Brokerage of $9.95 & $4.95 flat rate • Trades from liquidity of $50,000 to $2,000,000 and “Whole Market” which is >= $50,0000 • Volatility from ATRVE = 2 up to 12 • With Market Risk (= Systematic Risk) • Position sizing of 0.6% Portfolio Risk % was used for all four simulations.

1. Run 1470, “Whole Market”, $9.95, 0.6%. 2. Run 1293, Limited Liquidity [50K-2000k], $9.95, 0.6%. 3. Run 1471, “Whole Market”, $4.95, 0.6%. 4. Run 1333, Limited Liquidity [50K-2000k], $4.95, 0.6%.

These simulations demonstrate that performance is far better trading a portion of the NASDAQ rather than the whole NASDAQ. For practical reasons of too much choice we limited the range of stocks to scan by liquidity.



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200101-201209, XNAS SIROC 2108 100k Liq10 B9.95 LiqLim[50:2000) Vs LiqLim[] A[2-12) PR[0.6%] (B)

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15.10 SIROC 130505, Liquidity Multiple 10x, Brokerage $4.95, “Base” Simulation This SIROC 13 5 5 simulation is a “base” simulation using “base” money management, that is 10 open positions with each position 10% of the current portfolio value. A “base” money management simulation is conducted each with and without Market Risk. This was done with a $25,000 starting portfolio and a $100,000 starting portfolio.


• SIROC 13 5 5 • Liquidity multiple = 10x • Brokerage of $4.95 flat rate • Only trades from liquidity of $50,000 to $2,000,000 • Volatility from ATRVE = 2 up to 12 • Position sizing: 10 positions at 10% each • With and without Market Risk (= Systematic Risk)

1. Run 1465 $100,000 with NO Market Risk 2. Run 1466 $25,000 with NO Market Risk 3. Run 1459 $100,000 with Market Risk 4. Run 1460 $25,000 with Market Risk



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• SIROC 13 5 5 • Liquidity multiple = 5x • Brokerage of $9.95 flat rate • Only trades from liquidity of $50,000 to $2,000,000 • Volatility from ATRVE = 2 up to 12 • With Market Risk (= Systematic Risk) • Position sizing as follows:

1. Run 1359 0.2% Portfolio Risk %. 2. Run 1360 0.3% 3. Run 1361 0.4% 4. Run 1362 0.5%. 5. Run 1363 0.6%. 6. Run 1364 0.8%. 7. Run 1365 1%. 8. Run 1366 1.5%. 9. Run 1367 2%. 10. Run 1368 3%.



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• $100,000 starting capital. • 0.6% Portfolio Risk % (from run 1363 above). • Displays charts of 5th (blue), 50th (green) and 95th (pink) percentiles as at the end of the simulation period (28th September 2012), the 2nd chart being in semi-log


Using 0.6% Portfolio Risk % may produce too many trades for you. You could consider using 0.7%, 0.8%, 0.9% of even 1.0% but no much larger a position than 1.0%.










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15.14 SIROC 130505, $100,000, Liquidity Multiple 10x, Brokerage $4.95






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15.16 SIROC 130505, $25,000, Liquidity Limit 10x, Brokerage $4.95 The following criteria were used for the scenarios in this section:





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• $25,000 starting capital. • 1.0% Portfolio Risk % (from run 1455 above). • Displays charts of 5th (blue), 50th (green) and 95th (pink) percentiles as at the end of the simulation period (28th September 2012), the 2nd chart being in semi-log






16 Exploratory Simulation Summary As is obvious from the above research, exploratory simulation allows detailed research and stress testing of risk and money management rules, especially during market periods that are atypical. Exploratory simulation stress tests the variables that we can control in an environment with thousands and thousands of variables that we cannot control.

As important as it is to research an edge, exploratory simulation is far more important as it helps determine the risk management rules that will protect capital, i.e. survive, and the associated money management rules that will help grow capital, i.e. thrive.

It helps the active investor see the big picture over the long term. This is especially necessary when the market gets tough in the short term.

We suggest that, over time, all the exploratory simulation information provided in this White Paper be studied. The educational value for trading in general is enormous.

17 White Paper Summary There are variables identified in this paper that interact on our portfolios that we can control. However, there are two other variables, amongst many others, that we cannot control, overall market performance and randomness of individual trade outcomes. These two variables and all the variables discussed in this paper can be controlled by avoiding them altogether, by being a market spectator.

However, this would remove us from the opportunity flow to grow our capital. And we have to grow our wealth in some fashion to overcome inflation which erodes the value of our wealth. Once in the game of investing, randomness plays a major role, especially in trade selections from day to day, or year to year for buy and holders. Our task is to narrow down the effect of this randomness on our outcomes.

We do this through:

• Subscribing to an active methodology that can remove market (systematic) risk altogether during certain market periods.

• Defining strict criteria within which to time and select trades. • Effective risk management, and • Effective money management.

If there was little or no randomness in trade selection, then the variation of portfolio equity curve outcomes would be very narrow or non-existent. One of the major strengths of exploratory simulation is that takes into account this randomness of trade selection. The determination of position size through countless iterations of exploratory simulation allows research to tell us, with the benefit of hindsight, how to minimise the effect of this randomness.

But even once we have the four points highlighted above in place, belief and trust in one’s chosen process is mandatory so that we don’t self sabotage ourselves by operating outside of the parameters that the research has delivered to us. This is where trading psychology comes in.

The information provided in this White Paper should instil confidence into users of the SPA3 methodology and inspire them to:


SPA3 for NASDAQ White Paper | December 2012 • trade the methodology according to the revised risk management and money management rules, • continue to trust the methodology even when it goes into drawdown, • minimise or preferably eliminate trading errors and mistakes.

Trust in a method is tested during tough times – it’s not tested during raging bull markets. If active investors decide to become market spectators for the rest of their investing days it can only mean that either:

1. They believe (or must know in advance) that there will never be another secular bull market, or even another primary bull market within a secular bear market. This is obviously a big call. How can anybody know this – well they can’t. This is when you hear the cries of “But this time it’s different! We are in a new era.” Due to any number of reasons, such as HFT, technology changes , terrorism etc etc.

2. They have lost trust in their methodology and no longer believe that it can work for them. 3. They have lost trust in themselves being able to execute in the environment of the market.

Whichever it is, the kind of detailed research provided in this White Paper can only assist in helping investors regain their confidence and trust in the markets, the methodology and their ability to execute to grow their capital bases using the environment of the equity markets to do so.

Spectators don’t lose, but neither do they learn or grow either. And they never get lucky. Sure, players can lose and get unlucky too but we only grow personally when we engage the game and we only grow our capital when we confront and overcome the risks and fears of the environment in which we play.

One of the major fears is drawdown. Given that drawdown is a ‘dead cert’, how do private investors that wish to do it themselves continue to outperform the market whilst not allowing drawdown to get out of hand? By smart risk and money management rules, customised according to their own requirements.

The SWS approach with SPA3 is now emphatically the following:

1. The individual trader’s Risk Objective has to be decided upon in the Objectives Statement of the Trading Plan.

2. Then Risk and Money Management rules need to be customised specifically according to the user’s Reward and Risk Objectives. What a particular user sets as their risk criteria to determine when to trade and not to trade and what position size to trade with will be done according to exploratory simulation.

Adjusting your position size according to one’s risk criteria, which, in turnn is set based on the Trading Plan Risk Objective, has become a key ingredient of SPA3.

For example, assume that a SPA3 user has a Risk Objective of 20%, i.e. will tolerate a maximum drawdown of 20%, then a position size should be selected from the information in this White Paper that has a maximum drawdown as close as possible to this Risk Objective, recognising that all other drawdowns would have been under the maximum drawdown. If the Risk Objective is reached it may be assumed that extreme negative market conditions have occurred at which time the SPA3 user can cease trading until a new Low Risk Market begins again.

As has been stated, Risk & Money Management will be the biggest determinant of portfolio outcomes regardless of how good an edge is. This is the important role that exploratory simulation has played is assisting an active investor survive in tough times and thrive in good times.

Lastly, we anticipate much discussion and questions about this paper. The SPA3 Forum will be the best place for such discussion.


SPA3 for NASDAQ White Paper | December 2012 18 Acknowledgements It first became a goal of mine in 2005 to release a SPA3 product for the USA markets. We have had a number of attempts to do so each met with some large obstacles including, but limited to, extremely poor listed and delisted USA price data from our previous data providers. This was a major showstopper and made it impossible to determine the SPA3 Edge and to research historical portfolios. To get to the point that we have now reached we had to:

• Change data providers. • This inevitably meant that we also had to change the technical analysis product that we used in which

to embed SPA3. A choice was made to develop our own. • Research the SPA3 FOR NASDAQ Edge with the revised SPA3 exit signals researched and devised

during 2011. • Search for and install exploratory simulation tools and processes. • Conduct the necessary exploratory simulation. • Make the necessary software changes in GPS.

To get all this done has been a momentous effort by all involved at Share Wealth Systems. To finally reach the point of releasing a SPA3 product for the USA equity markets is greatly satisfying. However, I do know that there is still much ahead in terms of keeping up the research and applying improvements wherever possible. I acknowledge all that have been involved in getting us to this point but especially:

David Sayer.

David has been involved across the whole research process but more specifically in the exploratory simulation using complex portfolio simulation software and ‘R’ statistical programming to generate straw-broom graphical outputs and individual portfolio equity curves.

The portfolio simulation software used is flexible in the extreme but with flexibility comes complexity requiring low level programming in C++. Such research is massively detailed and time consuming and requires enormous attention to detail.

It also requires establishing processes and building peripheral tools in Excel and elsewhere to be able to conduct and keep track of the simulations and record them in an orderly manner for retrieval and analysis. David was dedicated for over a year on this one research project. There is still more to do …….

Paper written by Gary Stone.

19 References "Finance and Monte Carlo Simulation," Journal of Financial Planning, Nov. 2001 by David Nawrocki, Ph.D.

Van Tharp’s Definitive Guide to Position Sizing, 2008


http://www56.homepage.villanova.edu/david.nawrocki/Finance%20and%20Monte%20Carlo%20-%20Nawrocki.pdf

SPA3 for NASDAQ White Paper | December 2012 20 ADDENDUM 1 - Position Sizing Formula

Position Size Formula Addendum to ‘Revision of the SPA3 Risk Management and Money Management Rules’

Under the revised Risk and Money management rules, the Position Size equation is defined as:

Position Size ($) =Portfolio Value ($) × Portfolio Risk %

Trade Risk %

The Portfolio Risk % is the percentage of the Portfolio Value you are willing to lose if the trade results in a loss, and the Trade Risk % is the percentage loss that you may expect from this trade. It might help to think of the Trade Risk as an ‘expected loss’, not the exact loss.

The Portfolio Risk % is the only variable that a SPA3 user needs to specify. The Trade Risk % is provided by Share Wealth Systems but how is this determined?

20.1 Determining the Trade Risk % To determine the Trade Risk % for any trade the SPA3 signal and the volatility level (ATRVE) are required. From quantitative analysis of thousands of historical trades, it was established that the combination of these two characteristics provide the primary determinants of the Trade Risk %.

For each SPA3 signal there is trade risk data, which could be drawn as a chart similar to that shown in Figure 18.1. By using the ATRVE value, on the horizontal axis, the exact Trade Risk % is determined from the vertical axis. TradeMaster stores sets of trade risk data as ‘Risk Tables’ for each stock exchange and each SIROC setting. E.g., Default XASX SIROC 21:08.

Figure 18.1

When placing a trade it is more user friendly to show the Trade Risk % (percentage) as a Trade Risk $ value. The Trade Risk $ is the Trade Risk % multiplied by the specific trade Price to give you a measure in $ of the

Entry Signal

1.290 ATRVE

Trade Risk %

10.1825%


SPA3 for NASDAQ White Paper | December 2012 expected loss relative to the price. A trade example is shown in Figure 18.2. The CBA trade with an ATRVE of 1.290 and a SPA3 signal of ‘WONB4+DB’ (blue arrows), will produce a Trade Risk % of 10.1825% from the Risk Tables stored within TradeMaster. The 10.1825% multiplied by a trade Price of $55.28 produces a Trade Risk $, expected loss, of $5.6289 per share (red arrow).

Figure 18.2

20.2 Different trades, same risk To demonstrate how the Trade Risk % works to create a situation where two different trades present the same risk to a portfolio, we’ll work through an example.

Peter has a Portfolio Value of $200k and has chosen to set his Portfolio Risk at 0.8%. The SPA3 scan generates two trades. The first is for ABC and is allocated a Trade Risk % of 6% from the Risk Tables. The second is for DEF and is allocated a Trade Risk of 12% from the Risk Tables. Remember, these Trade Risk %’s are based on the different SPA3 signals and ATRVE values for each trade. The position size for each trade, according to the formula above is:

ABC Position Size ($) =200,000 × 0.8%

6%= $26,666.66

DEF Position Size ($) =200,000 × 0.8%

12%= $13,333.33

At this point it is important to note that the DEF position size is half as big as the ABC trade because its Trade Risk % is twice the size. As the Trade Risk decreases, the position size will increase and vice versa.


SPA3 for NASDAQ White Paper | December 2012 Now, if both trades were to experience their expected losses of 6% and 12% respectively, the actual effect on Peter’s portfolio would be losses of:

ABC Loss ($) = $26,666.66 × 6% = $1,600.00

DEF Loss ($) = $13,333.33 × 12% = $1,600.00

Both the losses are the same! Both trades represented the same risk in $ to Peter’s portfolio.

The Trade Risk % is an expected value, not an exact stop loss, so the variation of losses across actual trades will vary. However, the Trade Risk values have been defined such that the actual loss is more likely to be smaller than the Trade Risk %. This allows the maximum risk a portfolio may experience to be controlled.

20.3 Smaller Portfolio Risk, less loss. Mary also has a $200,000 portfolio but is more conservative and has chosen to set her Portfolio Risk % at 0.4%. What will happen when Mary takes the same two trades?

ABC Position Size ($) =200,000 × 0.4%

6%= $13,333.33

DEF Position Size ($) =200,000 × 0.4%

12%= $6,666.66

Mary’s position sizes are exactly half the size of Peter’s.

Now, if both trades were to experience their expected losses of 6% and 12% respectively, the actual effect on Mary’s portfolio would be losses of:

ABC Loss ($) = $13,333.33 × 6% = $800.00

DEF Loss ($) = $6,666.66 × 12% = $800.00

The losses are exactly half the size of Peters. When the trades are combined, Mary will experience half as much drawdown from these trades as Peter. Of course, Mary’s profits would also be half as small but she is prepared to accept this, in order to minimise the risk to her portfolio.

20.4 Conclusion The Trade Risk % adjusts your position size to standardise the risk that each trade presents to your portfolio. The Portfolio Risk % allows you to adjust your overall risk relative to suit your individual risk profile.

The Portfolio Risk % is the only variable that a SPA3 user needs to specify.


SPA3 for NASDAQ White Paper | December 2012 21 ADDENDUM 2 – SPA3 Statistical Edge on the NASDAQ This Addendum provides the statistical edge of the SPA3 methodology as researched on the NASDAQ stock exchange. It is the equivalent information provided for the NASDAQ as has been provided for the ASX and JSE. In effect, it is the SPA3 Edge for the NASDAQ.

All listed and delisted NASDAQ stocks during the period 3 January 1990 to 4 June 2012. This means that a stock that was delisted after January 2000 and before the end will be included in the simulations. It should be noted that some stocks in the USA markets “drop off” their exchange and trade as a ‘pink sheet’ in the OTC environment. Unfortunately, these stocks have not been included in any research. However, they are not a significant number and the number of delisted trades in the research for the SIROC 21 8 is significant at 43.39% of the researched trades.

The tables below have used the trades in the liquidity bracket of $50,000 to $2,000,000, as per the SPA3 calculations for determining average daily traded liquidity.

21.1 SIROC 21 8 The total number of trades for the research period for all liquidity from $50,000 upwards was 97,095 compared to 55,973 as shown below. The edge deteriorated when including the all liquidity trades.

Table 1 shows all the trades in both Low Risk and High Risk markets.

Table 1

Table 2 shows all the Low Risk trades.

% of Avg Loss HoldPeriodHoldPeriodHoldPeriodTrades ATRVE Trades Winners Losers Win Rate Avg Win Avg Loss Avg Profit Profit Ratio Expectancy Std Dev SQN Elapsed Winners Losers

All 55973 24630 31343 44.00% 18.00% -8.72% 3.04% 2.06 0.3485 2.11 1.6488 35 46 27

4.21% >= 9% 2358 938 1420 39.78% 31.26% -13.79% 4.13% 2.27 0.2995 3.42 0.8759 23 28 203.70% >= 8% 2071 926 1145 44.71% 29.32% -13.62% 5.58% 2.15 0.4094 3.45 1.1883 29 34 256.36% >= 7% 3559 1460 2099 41.02% 27.15% -12.08% 4.01% 2.25 0.3325 2.82 1.1770 31 38 279.69% >= 6% 5426 2263 3163 41.71% 23.19% -11.26% 3.11% 2.06 0.2757 2.45 1.1271 31 38 26

14.95% >= 5% 8366 3714 4652 44.39% 19.30% -9.90% 3.06% 1.95 0.3097 2.20 1.4084 31 37 2519.16% >= 4% 10722 4735 5987 44.16% 16.78% -8.54% 2.64% 1.97 0.3096 1.91 1.6174 33 42 2619.88% >= 3% 11130 4862 6268 43.68% 15.58% -7.27% 2.71% 2.14 0.3729 1.77 2.1123 38 50 2915.71% >= 2% 8794 3991 4803 45.38% 12.48% -5.51% 2.66% 2.27 0.4826 1.39 3.4614 42 56 295.70% >= 1% 3191 1571 1620 49.23% 10.62% -4.48% 2.95% 2.37 0.6596 1.23 5.3768 43 57 290.64% > 0% 356 170 186 47.75% 7.69% -3.45% 1.87% 2.23 0.5416 1.08 4.9967 41 58 25

100.00% 55973 24630 31343SPA3 Market Risk

69.60% LOW 38959 18010 20949 46.23% 18.82% -9.34% 3.68% 2.01 0.3935 2.19 1.7950 38 46 3130.40% HIGH 17014 6620 10394 38.91% 15.76% -7.46% 1.58% 2.11 0.2114 1.91 1.1060 28 41 20100.00%



Table 2

The summarised totals for the respective ATRVE ranges in Table 2 are as follows:

Notice how the SQN improves as the volatility ranges decline. Because we are spoilt by the pure volume of trades that are generated on the NASDAQ, traders of SPA3 FOR NASDAQ can become more selective of with how they slice and dice the NASDAQ exchange. At 23,076 trades there will still be ample opportunity to trade the 0% to 5% ATRVE range.

Table 3 shows all the High Risk trades.

Table 3

The breakdown of trades for the entire database of SPA3 trades, not just the $50,000 to $2,000,000, by year is as follows:

% of Avg LossTrades ATRVE Trades Winners Losers Win Rate Avg Win Avg Loss Avg Profit Profit Ratio Expectancy Std Dev SQN

SPA3 LOW Market Risk3.09% >= 9% 1730 734 996 42.43% 32.73% -14.37% 5.61% 2.28 0.3906 3.52 1.1092

1 2.67% >= 8% 1494 696 798 46.59% 30.63% -14.09% 6.74% 2.17 0.4788 3.56 1.34612 4.53% >= 7% 2535 1101 1434 43.43% 28.48% -12.63% 5.23% 2.26 0.4140 2.97 1.39393 6.87% >= 6% 3844 1700 2144 44.22% 23.56% -11.90% 3.78% 1.98 0.3178 2.49 1.27454 10.72% >= 5% 5998 2783 3215 46.40% 20.02% -10.40% 3.71% 1.92 0.3567 2.25 1.58365 13.55% >= 4% 7586 3531 4055 46.55% 17.26% -9.07% 3.18% 1.90 0.3509 1.91 1.8380

13.67% >= 3% 7649 3519 4130 46.01% 16.12% -7.87% 3.17% 2.05 0.4026 1.85 2.180810.51% >= 2% 5880 2800 3080 47.62% 12.96% -6.04% 3.00% 2.14 0.4972 1.46 3.41323.62% >= 1% 2028 1038 990 51.18% 11.19% -4.79% 3.39% 2.33 0.7063 1.27 5.58150.38% >= 0% 215 108 107 50.23% 8.24% -4.00% 2.15% 2.06 0.5364 1.17 4.6007

69.60% 38959 18010 20949 46.23%


1 66.51% 0%-9% 37229 17276 19953 46.40% 18.36% -9.03% 3.59% 2.03 0.4071 2.04 1.99592 63.84% 0%-8% 35735 16580 19155 46.40% 17.85% -8.82% 3.45% 2.02 0.4024 1.98 2.03663 59.31% 0%-7% 33200 15479 17721 46.62% 17.03% -8.53% 3.32% 2.00 0.3970 1.90 2.08934 52.45% 0%-6% 29356 13779 15577 46.94% 16.18% -8.09% 3.26% 2.00 0.4079 1.82 2.23835 41.73% 0%-5% 23358 10996 12362 47.08% 15.19% -7.50% 3.14% 2.03 0.4247 1.71 2.4809

SPA3 HIGH Market Risk1.12% >= 9% 628 204 424 32.48% 25.95% -12.42% 0.04% 2.09 0.0034 3.07 0.01121.03% >= 8% 577 230 347 39.86% 25.35% -12.56% 2.55% 2.02 0.2035 3.11 0.65391.83% >= 7% 1024 359 665 35.06% 23.06% -10.89% 1.01% 2.12 0.0930 2.39 0.38882.83% >= 6% 1582 563 1019 35.59% 22.05% -9.92% 1.46% 2.22 0.1472 2.32 0.63534.23% >= 5% 2368 931 1437 39.32% 17.16% -8.76% 1.43% 1.96 0.1629 2.04 0.79705.60% >= 4% 3136 1204 1932 38.39% 15.36% -7.41% 1.33% 2.07 0.1800 1.92 0.93886.22% >= 3% 3481 1343 2138 38.58% 14.17% -6.12% 1.71% 2.32 0.2793 1.57 1.78235.21% >= 2% 2914 1191 1723 40.87% 11.36% -4.54% 1.96% 2.50 0.4304 1.26 3.42872.08% >= 1% 1163 533 630 45.83% 9.50% -3.98% 2.20% 2.39 0.5524 1.15 4.79910.25% >= 0% 141 62 79 43.97% 6.72% -2.70% 1.44% 2.49 0.5345 0.94 5.6661

30.40% 17014 6620 10394 38.91%



Breakdown by signal across all ATRVE levels (volatility) during Low Risk markets:

The difference between the totals of 38,694 and 38,595 in Table 2, are the trades not shown for the different WONB1+DB entry signals, being too few to matter.

21.2 SIROC 13 5 5 The total number of trades for the research period for all liquidity from $50,000 upwards was 112,238 compared to 64,905 as shown below. The edge deteriorated when including the all liquidity trades.

% of Total Year Trades1.57% 1990 1,5272.93% 1991 2,8483.05% 1992 2,9633.62% 1993 3,5173.44% 1994 3,3444.63% 1995 4,4994.47% 1996 4,3435.30% 1997 5,1474.37% 1998 4,2453.67% 1999 3,5654.05% 2000 3,9325.90% 2001 5,7325.05% 2002 4,8996.66% 2003 6,4696.06% 2004 5,8815.31% 2005 5,1515.94% 2006 5,7694.82% 2007 4,6843.01% 2008 2,9244.84% 2009 4,7035.27% 2010 5,1184.49% 2011 4,3581.52% 2012 1,475

100.00% 97,093

SPA3 LOW Risk% of Avg Loss

Trades Signal Trades Winners Losers Win Rate Avg Win Avg Loss Avg Profit Profit Ratio Expectancy Std Dev SQN

32.68% WCB4 18293 8785 9508 48.02% 19.56% -10.14% 4.12% 1.93 0.4067 2.29 1.77594.48% WCB2 2508 1137 1371 45.33% 17.59% -8.15% 3.52% 2.16 0.4315 1.96 2.19733.91% WCB3 2190 942 1248 43.01% 16.35% -7.18% 2.94% 2.28 0.4089 1.80 2.2730

15.12% WONB4+DB 8465 3858 4607 45.58% 18.10% -8.57% 3.58% 2.11 0.4180 2.18 1.91664.88% WONB5+DB 2730 1223 1507 44.80% 17.22% -8.60% 2.97% 2.00 0.3447 1.89 1.81911.57% WCB1+RSC+DB 880 388 492 44.09% 22.16% -11.51% 3.34% 1.93 0.2903 2.47 1.17363.43% WONB4+RSC+DB 1918 851 1067 44.37% 18.34% -9.20% 3.02% 1.99 0.3282 2.16 1.52190.26% WONB5+RSC+DB 146 72 74 49.32% 15.26% -8.92% 3.00% 1.71 0.3364 1.82 1.84370.22% WCB2+RSC+DB 125 58 67 46.40% 18.58% -6.22% 5.29% 2.99 0.8499 1.96 4.33900.11% WCB3+RSC+DB 64 29 35 45.31% 13.97% -6.61% 2.72% 2.11 0.4112 1.53 2.69522.46% VS+DB 1375 558 817 40.58% 20.33% -9.84% 2.41% 2.07 0.2444 2.23 1.0980

69.13% 38694 17901 20793 46.26%


SPA3 for NASDAQ White Paper | December 2012 Table 4 shows all the trades in both Low Risk and High Risk markets.

Table 4

Table 5 shows all the Low Risk trades for SIROC 13 5 5.

Table 5




All 64905 28049 36856 43.22% 16.38% -7.93% 2.58% 2.07 0.3249 2.15 1.5112 30 39 23

4.19% >= 9% 2719 1044 1675 38.40% 29.53% -13.34% 3.12% 2.21 0.2339 3.46 0.6752 22 24 203.71% >= 8% 2408 998 1410 41.45% 26.17% -12.37% 3.61% 2.12 0.2916 3.10 0.9412 26 31 236.07% >= 7% 3940 1615 2325 40.99% 24.86% -11.62% 3.33% 2.14 0.2869 2.90 0.9881 29 35 249.48% >= 6% 6153 2619 3534 42.56% 21.93% -10.34% 3.39% 2.12 0.3279 2.60 1.2594 28 35 23

14.28% >= 5% 9267 4063 5204 43.84% 18.15% -9.20% 2.79% 1.97 0.3037 2.31 1.3129 28 34 2219.07% >= 4% 12380 5377 7003 43.43% 15.98% -7.89% 2.48% 2.03 0.3147 2.10 1.4984 28 36 2220.12% >= 3% 13062 5497 7565 42.08% 13.57% -6.42% 1.99% 2.11 0.3103 1.68 1.8428 31 42 2316.13% >= 2% 10469 4608 5861 44.02% 11.03% -4.94% 2.09% 2.23 0.4235 1.40 3.0349 33 46 236.26% >= 1% 4066 2013 2053 49.51% 9.30% -3.73% 2.72% 2.49 0.7282 1.21 6.0227 35 48 220.68% > 0% 441 215 226 48.75% 5.25% -2.90% 1.07% 1.81 0.3699 1.09 3.3853 36 48 23

100.00% 64905 28049 36856SPA3 Market Risk

65.97% LOW 42819 19570 23249 45.70% 17.39% -8.41% 3.38% 2.07 0.4020 2.28 1.763934.03% HIGH 22086 8479 13607 38.39% 14.06% -7.11% 1.02% 1.98 0.1429 1.87 0.7647100.00%


SPA3 LOW Market Risk2.77% >= 9% 1797 756 1041 42.07% 31.28% -14.25% 4.90% 2.20 0.3441 3.70 0.9297

1 2.39% >= 8% 1551 688 863 44.36% 28.04% -13.11% 5.14% 2.14 0.3921 3.36 1.16572 4.02% >= 7% 2607 1133 1474 43.46% 26.42% -11.96% 4.72% 2.21 0.3949 3.06 1.29143 6.37% >= 6% 4136 1883 2253 45.53% 22.89% -11.07% 4.39% 2.07 0.3968 2.73 1.45364 9.60% >= 5% 6229 2880 3349 46.24% 19.30% -9.57% 3.78% 2.02 0.3945 2.44 1.61615 12.77% >= 4% 8291 3806 4485 45.91% 16.77% -8.38% 3.17% 2.00 0.3784 2.21 1.7088

13.39% >= 3% 8690 3840 4850 44.19% 14.26% -6.77% 2.52% 2.11 0.3724 1.75 2.126010.58% >= 2% 6869 3182 3687 46.32% 11.64% -5.28% 2.56% 2.20 0.4846 1.47 3.30503.71% >= 1% 2410 1277 1133 52.99% 9.67% -3.97% 3.26% 2.44 0.8223 1.25 6.59480.37% >= 0% 239 125 114 52.30% 5.64% -3.15% 1.45% 1.79 0.4588 1.17 3.9165

65.97% 42819 19570 23249 45.70%

1 63.20% 0%-9% 41022 18814 22208 45.86% 16.94% -8.09% 3.31% 2.09 0.4192 2.11 1.98502 60.81% 0%-8% 39471 18126 21345 45.92% 16.50% -7.89% 3.24% 2.09 0.4197 2.06 2.03493 56.80% 0%-7% 36864 16993 19871 46.10% 15.80% -7.60% 3.14% 2.08 0.4190 1.99 2.10344 50.42% 0%-6% 32728 15110 17618 46.17% 14.91% -7.17% 2.98% 2.08 0.4221 1.90 2.22325 40.83% 0%-5% 26499 12230 14269 46.15% 13.87% -6.60% 2.79% 2.10 0.4318 1.77 2.4376





Table 6

Table 7 shows all the Low Risk trades for SIROC 19 7.

SPA3 LOW Risk Avg LossSignal Trades Winners Losers Win Rate Avg Win Avg Loss Avg Profit Profit Ratio Expectancy Std Dev SQN

24.42% WCB4 15851 7578 8273 47.81% 18.26% -9.24% 3.91% 1.98 0.4231 2.43 1.74285.60% WCB2 3636 1614 2022 44.39% 17.75% -7.46% 3.73% 2.38 0.5000 2.20 2.26903.53% WCB3 2289 982 1307 42.90% 16.36% -7.30% 2.85% 2.24 0.3909 2.02 1.9359


65.33% 42400 19382 23018 45.71%


All 60341 26523 33818 43.96% 17.49% -8.48% 2.93% 2.06 0.3456 2.11 1.6370 34 45 26

4.01% >= 9% 2421 953 1468 39.36% 31.71% -13.54% 4.27% 2.34 0.3155 3.59 0.8784 23 27 213.71% >= 8% 2237 963 1274 43.05% 28.17% -13.31% 4.55% 2.12 0.3416 3.27 1.0448 29 33 266.10% >= 7% 3683 1519 2164 41.24% 26.69% -12.09% 3.91% 2.21 0.3232 2.87 1.1256 31 38 279.42% >= 6% 5684 2391 3293 42.07% 22.83% -10.99% 3.24% 2.08 0.2943 2.52 1.1682 30 37 25

14.57% >= 5% 8792 3910 4882 44.47% 19.17% -9.80% 3.09% 1.96 0.3149 2.25 1.4026 30 37 2518.90% >= 4% 11403 5030 6373 44.11% 16.55% -8.31% 2.66% 1.99 0.3199 1.92 1.6678 32 41 2619.81% >= 3% 11953 5198 6755 43.49% 15.10% -7.06% 2.58% 2.14 0.3648 1.71 2.1307 37 49 2816.24% >= 2% 9802 4367 5435 44.55% 12.35% -5.49% 2.46% 2.25 0.4480 1.41 3.1748 40 55 286.44% >= 1% 3883 1958 1925 50.42% 9.83% -4.36% 2.79% 2.25 0.6401 1.19 5.3748 41 54 280.80% > 0% 483 234 249 48.45% 6.12% -4.00% 0.91% 1.53 0.2264 1.16 1.9439 42 59 27

100.00% 60341 26523 33818SPA3 Market Risk

70.14% LOW 42325 19545 22780 46.18% 18.24% -9.10% 3.53% 2.01 0.3878 2.19 1.7695 37 45 3029.86% HIGH 18016 6978 11038 38.73% 15.36% -7.21% 1.53% 2.13 0.2122 1.90 1.1173 28 40 20100.00%



Table 7






SPA3 LOW Market Risk2.97% >= 9% 1794 744 1050 41.47% 33.73% -14.37% 5.58% 2.35 0.3881 3.76 1.03142.66% >= 8% 1608 716 892 44.53% 29.42% -14.11% 5.27% 2.08 0.3734 3.33 1.12284.45% >= 7% 2688 1138 1550 42.34% 27.53% -12.50% 4.44% 2.20 0.3555 2.95 1.20556.69% >= 6% 4034 1790 2244 44.37% 23.39% -11.60% 3.92% 2.02 0.3383 2.55 1.3271

10.55% >= 5% 6364 2967 3397 46.62% 20.04% -10.29% 3.85% 1.95 0.3739 2.37 1.579313.49% >= 4% 8139 3791 4348 46.58% 16.85% -8.82% 3.14% 1.91 0.3554 1.91 1.857813.64% >= 3% 8232 3765 4467 45.74% 15.56% -7.54% 3.02% 2.06 0.4011 1.77 2.268611.06% >= 2% 6672 3152 3520 47.24% 12.88% -5.97% 2.94% 2.16 0.4919 1.48 3.32034.16% >= 1% 2510 1338 1172 53.31% 10.31% -4.65% 3.32% 2.22 0.7142 1.23 5.78330.47% >= 0% 284 144 140 50.70% 6.44% -4.98% 0.81% 1.29 0.1626 1.30 1.2457

70.14% 42325 19545 22780 46.18%

67.17% 0%-9% 40531 18801 21730 46.39% 17.81% -8.77% 3.44% 2.03 0.4063 2.03 2.005664.51% 0%-8% 38923 18085 20838 46.46% 17.33% -8.55% 3.36% 2.03 0.4069 1.97 2.063660.05% 0%-7% 36235 16947 19288 46.77% 16.58% -8.25% 3.28% 2.01 0.4071 1.90 2.143153.37% 0%-6% 32201 15157 17044 47.07% 15.73% -7.83% 3.20% 2.01 0.4155 1.82 2.285142.82% 0%-5% 25837 12190 13647 47.18% 14.66% -7.23% 3.04% 2.03 0.4287 1.68 2.5478

SPA3 LOW Risk Avg Loss HSignal Trades Winners Losers Win Rate Avg Win Avg Loss Avg Profit Profit Ratio Expectancy Std Dev SQN

31.53% WCB4 19025 9069 9956 47.67% 19.18% -9.87% 3.98% 1.94 0.4033 2.32 1.73794.98% WCB2 3002 1365 1637 45.47% 17.40% -8.02% 3.54% 2.17 0.4416 2.00 2.20413.87% WCB3 2336 1025 1311 43.88% 15.96% -7.10% 3.02% 2.25 0.4249 1.85 2.3024


69.66% 42034 19429 22605 46.22%



Table 8

Table 9 shows all the Low Risk trades for SIROC 17 7.

Table 9




All 61004 26888 34116 44.08% 17.38% -8.44% 2.94% 2.06 0.3480 2.12 1.6427 34 45 26

4.05% >= 9% 2469 958 1511 38.80% 31.46% -13.82% 3.75% 2.28 0.2712 3.56 0.7611 23 26 213.60% >= 8% 2199 961 1238 43.70% 27.44% -13.39% 4.46% 2.05 0.3329 3.24 1.0271 29 33 266.06% >= 7% 3694 1531 2163 41.45% 27.11% -12.12% 4.14% 2.24 0.3417 2.98 1.1483 31 38 269.42% >= 6% 5747 2397 3350 41.71% 23.04% -10.88% 3.26% 2.12 0.3000 2.54 1.1796 30 37 25

14.55% >= 5% 8877 3983 4894 44.87% 19.03% -9.73% 3.18% 1.96 0.3265 2.24 1.4584 30 36 2518.93% >= 4% 11546 5111 6435 44.27% 16.61% -8.26% 2.75% 2.01 0.3331 1.92 1.7330 32 41 2619.88% >= 3% 12126 5267 6859 43.44% 14.98% -7.00% 2.55% 2.14 0.3640 1.73 2.1082 36 48 2816.27% >= 2% 9923 4477 5446 45.12% 12.01% -5.46% 2.42% 2.20 0.4431 1.41 3.1460 39 53 286.46% >= 1% 3938 1971 1967 50.05% 9.80% -4.30% 2.76% 2.28 0.6411 1.18 5.4379 41 54 270.80% > 0% 485 232 253 47.84% 6.12% -3.97% 0.86% 1.54 0.2155 1.16 1.8575 41 57 27

100.00% 61004 26888 34116SPA3 Market Risk

71.05% LOW 43345 20069 23276 46.30% 18.16% -9.04% 3.55% 2.01 0.3930 2.20 1.7831 36 45 2928.95% HIGH 17659 6819 10840 38.61% 15.09% -7.16% 1.43% 2.11 0.1996 1.88 1.0619 27 40 19100.00%


SPA3 LOW Market Risk3.02% >= 9% 1845 762 1083 41.30% 32.98% -14.65% 5.02% 2.25 0.3431 3.71 0.92352.62% >= 8% 1597 730 867 45.71% 28.47% -14.12% 5.35% 2.02 0.3788 3.28 1.15614.47% >= 7% 2729 1172 1557 42.95% 27.97% -12.60% 4.82% 2.22 0.3827 3.08 1.24406.77% >= 6% 4130 1819 2311 44.04% 23.68% -11.45% 4.02% 2.07 0.3509 2.60 1.3514

10.60% >= 5% 6468 3030 3438 46.85% 19.95% -10.26% 3.89% 1.94 0.3794 2.37 1.600613.70% >= 4% 8357 3907 4450 46.75% 16.96% -8.79% 3.25% 1.93 0.3702 1.93 1.915313.96% >= 3% 8516 3893 4623 45.71% 15.48% -7.48% 3.02% 2.07 0.4033 1.79 2.251011.21% >= 2% 6837 3264 3573 47.74% 12.53% -5.89% 2.90% 2.13 0.4928 1.47 3.34604.21% >= 1% 2569 1342 1227 52.24% 10.31% -4.60% 3.19% 2.24 0.6924 1.22 5.68770.49% >= 0% 297 150 147 50.51% 6.71% -4.33% 1.24% 1.55 0.2868 1.15 2.5010

71.05% 43345 20069 23276 46.30%

68.03% 0%-9% 41500 19307 22193 46.52% 17.74% -8.70% 3.49% 2.04 0.4139 2.04 2.029765.41% 0%-8% 39903 18577 21326 46.56% 17.31% -8.48% 3.41% 2.04 0.4156 1.99 2.088760.94% 0%-7% 37174 17405 19769 46.82% 16.53% -8.18% 3.31% 2.02 0.4142 1.91 2.168654.17% 0%-6% 33044 15586 17458 47.17% 15.64% -7.77% 3.22% 2.01 0.4206 1.82 2.305843.56% 0%-5% 26576 12556 14020 47.25% 14.59% -7.17% 3.06% 2.04 0.4340 1.69 2.5664



SPA3 LOW Risk Avg Loss HSignal Trades Winners Losers Win Rate Avg Win Avg Loss Avg Profit Profit Ratio Expectancy Std Dev SQN

30.90% WCB4 18851 9049 9802 48.00% 19.12% -9.88% 4.04% 1.94 0.4095 2.34 1.75295.46% WCB2 3329 1489 1840 44.73% 17.23% -7.97% 3.30% 2.16 0.4141 1.97 2.10084.11% WCB3 2510 1100 1410 43.82% 16.15% -7.12% 3.08% 2.27 0.4324 1.85 2.3391


70.46% 42983 19921 23062 46.35%


Documents

SPA3 for NASDAQ White Paper - Charting Software, Free ... Revision of S… · SPA3 for NASDAQ White Paper | December 2012 2.1.2 SPA3 Scan If you wish to run a SPA3 scan with a parameter