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2

Bloomberg BRIEF: Technical

Strategies Quarter in Brief

Contributors

Eoghan Leahy, CMT, MSTA

eleahy6@bloomberg.net

Ph: +44-20-7392-0599

Maurizio Pietrini, MSTA

mpietrini1@bloomberg.net

Ph: +44-20-7073-3666

Guido Riolo, MSTA

guidoriolo@bloomberg.net

Ph: +44-20-7330-7211

Oliver Woolf, CAIA, MSTA

owoolf@bloomberg.net

Ph: +44-20-7073-3148

Paul Ciana, CMT

pciana@bloomberg.net

Ph: +1-212-617-8229

Greg Bender, CMT

gbender1@bloomberg.net

Ph: +1-646-324-3169

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OVERVIEW EQUITIES 3

1. Blue/red signals from Volstall indicator 2. Painted bars from triple moving average crossover 3. Lower panel is Fisher Transform with Squeeze

Chart 1 Chart 2

Chart 3 Chart 4

Long Term uptrend still intact. Currently testing the top of the channel.

We are seeing divergence on the Fisher at extreme levels.

Fisher Divergence and recent Volstall signal suggest loss of upside

momentum. Volatility is still low but upside from current levels may be

limited.

Short term momentum remains positive and trend is still bullish

however the Fisher is at extreme levels.

LT Trend remains up as TEMA is still bullish however divergence on

the Fisher Transform suggest momentum is waning.

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OVERVIEW FIXED INCOME 4

1. Blue/red signals from Volstall indicator 2. Painted bars from triple moving average crossover 3. Lower panel is Fisher Transform with Squeeze

Chart 1 Chart 2

Chart 3 Chart 4

TEMA is clearly negative as uptrend support has been broken and

tested as resistance. Squeeze signal suggests potential trend move

lower has begun.

Clear descending price channel that halted the recent bounce higher.

TEMA is clearly negative however mean reversion from extreme reading

on Fisher suggests short term exhaustion of downside momentum.

TEMA is negative once more as downward sloping channel continues

to provide resistance. Break of horizontal support could see an

accelerated move to the downside.

Downtrend resistance contained the recent bounce higher. Currently

testing key support. Fisher levels remaining low on recent moves

higher.

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OVERVIEW FX 5

1. Blue/red signals from Volstall indicator 2. Painted bars from triple moving average crossover 3. Lower panel is Fisher Transform with Squeeze

Chart 1 Chart 2

Chart 3 Chart 4

Clear rising trend channel and TEMA remains bullish. Price failed at 52

week high resistance with divergence on the Fisher Transform.

Prices managed to break to new 52 week highs but have since pulled

back. TEMA is now negative. Squeeze breakout suggests potential

deeper correction if uptrend support breaks.

TEMA on GBP remains positive as new 52 week highs have been

reached. Fisher at three year extreme yet no bearish divergence

present.

Volstall signals and Fisher divergence suggest near term exhaustion of

momentum. Uptrend support still intact.

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OVERVIEW COMMODITIES 6

1. Blue/red signals from Volstall indicator 2. Painted bars from triple moving average crossover 3. Lower panel is Fisher Transform with Squeeze

Chart 1 Chart 2

Chart 3 Chart 4

Volstall signal at resistance marked beginning of the recent decline.

TEMA is now negative and uptrend support is currently being tested. Crude is testing uptrend support however recent Volstall signal

suggest temporary loss of downside momentum. TEMA still negative.

Copper is testing the downtrend resistance that has contained price

action for several years now. Squeeze setup suggests sharp trend

move may lie ahead but direction of move is not yet clear.

Copper failed at horizontal resistance with a Volstall and extreme

Fisher reading highlighting the loss of momentum. TEMA has turned

negative, short term pullback likely.

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OVERVIEW PRECIOUS METALS 7

1. Blue/red signals from Volstall indicator 2. Painted bars from triple moving average crossover 3. Lower panel is Fisher Transform with Squeeze

Chart 1 Chart 2

Chart 3 Chart 4

TEMA remains negative as Gold trends lower. However, recent

Volstall signal at $1200 level may support price.

Daily Volstall reinforces weekly Volstall signal. TEMA has now turned

positive and Fisher is advancing higher.

TEMA also negative on Silver as downtrend channel continues to

contain upward moves. Fisher exhibiting less volatility than was the

case at previous low.

Silver has been in a tight range for the past few months highlighted by

Squeeze setup which suggest potential for sharp move as volatility

picks up. Direction of this move still unclear but trend still clearly down.

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OVERVIEW VOLATILITY 8

4. Volatility bands

Chart 1 Chart 2

Chart 3 Chart 4

The VIX peaking in early October at the upper 3SD Bollinger Band.

Despite a brief spike in mid-December, implied volatility has trended

lower as the S&P 500 rallied over 13%.

After falling since June 2013, currency implied volatility rose to the

upper 1SD band in December but has since given up those gains.

Implied volatility, which bottomed in October at the recent peak in

Treasury prices, is above the upper 1SD band for the first time since

September.

The implied volatility of options on the United States Oil Fund ETF

made an all-time low in December below the lower 3SD band but has

rallied over 30% in 3 weeks as WTI crude futures have declined almost

$10 a barrel.

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OVERVIEW VOLATILITY 9

4. Volatility bands

Comments…

Conclusions

Chart 1

Chart 3

The implied volatility of options on the SPDR Gold Trust ETF has

traded in a tight range for Q4. The Bollinger Bands are tightening

as volatility drifts to lower levels.

Below is a normalized chart of the past quarter of the relative

implied volatility of all five asset classes covered in this section.

The trend is clear – lower implied volatility across all asset classes

as the macro environment has been ‘risk on’.

The decline of volatility in crude oil and gold has been apparent as

funds have exited the commodity complex for equities. The “lull”

in Treasury implied volatility has caught many by surprise that

believed the Taper would cause price volatility in bonds and the

U.S. Dollar.

The drift higher in equities and the lack of Taper volatility created a

tough environment for option buyers in Q4.

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OVERVIEW ASSET CLASS TRENDS 10

The beginning of Q1 2014 has seen resurgent signs for safety in the form of precious metals and bonds as the EUR and GBP

give back some of their recent gains. Copper and Oil look weak while the divergent fortunes of the S&P and the SXXP

suggest the New Year is seeing investors continue to favour European equities over US as highlighted in our Q4 2013 issue.

5. World Trends Graph

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OVERVIEW ASSET CLASS TRENDS 11

The weekly Relative Rotation Graph (RRG <GO>) clearly shows equities to be the dominant asset class despite a recent drop

in momentum. Treasuries have also lost some relative momentum but, significantly, failed to break into the outperforming

segment. EUR and GBP are comfortably rotating well within the outperforming zone. Oil continues to underperform but with

decreasing acceleration. 6. Relative Rotation GraphsTM

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GLOBAL EQUITY MARKETS 12

6. Relative Rotation GraphsTM

European Peripheral markets such as Italy, Spain, Greece despite a drop in relative momentum continue to outperform with

other European markets like Portugal and Ireland now following suit. BRICs and LATAM emerging markets are weakening on a

relative basis while most major Western markets have been trading in line with the MSCI World Index. Japan and Dubai

continue to show strong relative outperformance.

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GLOBAL EQUITY MARKETS 13

Of all the equity markets here displayed, Dubai has both the strongest 3 month and 1 year performance. This has been achieved

in a relatively stable manner as its blue sphere indicates that its volatility is not high. This contrasts with Argentina and Greece,

particularly good performers over 1 year and 3 months respectively, but with greater volatility, highlighted by the pink to purple

hues. The S&P, EURO STOXX and FTSE 100 have all performed well with relatively low volatility. The sphere size is based on

a 14 day RSI thus we can infer that Portugal has particularly strong momentum whereas that of China and Poland is weak. It is

interesting to note the positive linear regression through the chart, denoted, though not precisely, by the dotted red line. This

implies momentum persistence as in performance of most countries in the previous 9 months generally proved to be indicative of

how they fared over the most recent quarter. 7. Scatter plot chart

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GLOBAL EQUITY MARKETS (BREADTH) 14

The total return of the Russell 2000 in 2013 was about 38%. Throughout this rally, the average percentage of stocks making

new 52 week highs was 8% and overbought on RSI was 10%. Expect these levels to be exceeded in the next

market rally. The cumulative advance decline line continues to support the uptrend while price is finding support at shorter

term moving averages.

8. Market breadth indicators

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GLOBAL EQUITY MARKETS (BREADTH) 15

8. Market breadth indicators

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RATES AND INFLATION 16

The outlook from the forward implied curves is that interest rates shall continue to rise in both US (left) and EU (right).

However, the anticipated rise over 3 months (spread between the red and green curves) is more aggressive for US. The black

curve represents the projected shift over the next 12 months, with the central tenors seemingly to be the most affected.

9. Implied forward curves 10. Historical curves

As has been the case for the last 2 years the benchmark US (black) and European (orange) CDS indices are continuing to

drop lower, reflecting the increased confidence in credit risk. Interestingly the spread between the two (lower panel) has

narrowed to its lowest level since early 2011. European credit protection has not been cheaper than US since 2010.

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RATES AND INFLATION 17

The inflation picture from the US, German and UK Breakevens was a mixed bag in Q4, the beginning of which is marked by

the vertical dotted line. Following on from a decent rise from the latter half of 2012, the UK breakeven has remained stable just

above 3%. The US breakeven has also maintained its level but the German rate dropped slightly to just over 1.5%

11. Inflation indicators

Of the inflation gauges above, most had negative performance in Q4 with the exception of Copper. However, Copper dipped in

the latter half of December along with WTI crude. Only gold showed any signs of stabilisation as the quarter drew to a close.

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FX 18

LEFT: EUR sentiment (top) has dampened over the last quarter as reflected by the fall in Risk Reversal. This is echoed by the net large

speculator position although, importantly, that does remain positive. As for GBP (bottom), the Risk Reversal has flattened but the net

speculator position is even more positive than it was for the last report at the start of October.

RIGHT: As was the case last quarter the analyst outlook through to the end of Q1 is rather more negative than the option implied probabilities

for both EUR (top) and GBP (bottom). For EUR the analyst consensus is over 3 big figures below the current spot with a significant number of

forecasts below the negative 1 standard deviation of the implied histogram. Whilst the GBP consensus is also two big figures below the spot,

the modal forecast is actually above the current spot. In both cases the implied histogram is fairly normally distributed.

12. Sentiment and positioning 13. Implied probability forecast

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FX 19

The chart above uses the Bloomberg Correlation Weighted Indices from the BCWI page. The GBP index exhibits the clearest sign

of an uptrend, over 4.4% up over 3 months (X axis) and 6.8% over 1 year (Y axis). The EUR index has the best 1 year

performance and its turquoise colour implies that it has the lowest 60D volatility of the group as was the case last quarter. The

JPY index shows the strongest downward trend, being the worst performer over both periods. Its pink hue also tells that it has the

highest volatility along with the NZD index. The large size of the NZD sphere, along with the GBP and USD indices, symbolizes

strong short term momentum, based on a 14D RSI. Given such momentum it is unsurprising that the USD index is the biggest

mover over 1 quarter on the horizontal axis. Interestingly, the small size of the CHF sphere indicates that it is oversold despite

positive performance over both time frames, perhaps suggesting a temporary dip in an upward trend.

7. Scatter plot chart

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COMMODITIES 20

Natural Gas (NG1) has been a strong relative outperformer whilst Gasoline (XB1) is strengthening, however WTI Crude (CL1)

has been a relative laggard. Of the foodstuffs Cocoa (CC1) has been a major outperformer but is losing momentum. Meanwhile

Coffee(KC1), Soy(S1), and Corn (C1), have been gaining relative strength, although Corn (C1) is still the weakest CRB

component on a relative price basis. Frozen orange juice is showing the strongest relative momentum versus the CRB Index

whilst Sugar (SB1) has been the weakest.

6. Relative Rotation GraphsTM

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COMMODITIES 21

In line with the interpretation of the Relative Rotation Graph, the scatter plot suggests that Frozen Orange Juice (JO1) is

performing particularly well having posted the most positive returns amongst the CRB constituents over both a 3 month and 1

year period. However, this belies its high volatility, characterised by its purple sphere, which implies that it has been fluctuating.

In contrast, cocoa (CC1), despite a negative 3 month return, has performed very well over 1 year with a much lower volatility,

denoted by its blue colour, thus suggesting that its general movement has been more stable. Sugar (SB1) and Wheat (W 1),

have poor records over both periods. Their colour also suggests consistency in their trends and the small size of their spheres

implies weak short term momentum, measured using the 14 day RSI.

7. Scatter plot chart

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BRIEF MARKET SPOTLIGHT 22

The charts on the left side depict the relationship between the S&P 500 (blue) and 10 year US Treasury Futures (red). The lower panels show

a rolling 250 day correlation. In the upper chart we can see how this correlation has narrowed significantly over the last year, almost to the

point of zero correlation from markedly inverse levels previously. The lower chart highlights the last time this correlation was positive in early

2007. This evolving relationship is brought into sharp focus through the regression diagrams on the right hand side. Both exhibit an entire

calendar year of daily regression observations between the S&P and the Treasury Futures, the upper representing 2013 and the lower 2014.

The scattering of the observations has become far more random in recent month resulting in a flattening of the regression line which hitherto

was clearly negative. The range of the Treasury observations has also become more dispersed, hence the widening of the X axis scale.

14. Historical Regression Analysis

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23

On December 17th Bloomberg hosted the first annual technical analysis summit, in the London headquarters. During

the course of the event we disseminated a questionnaire on views of the financial world going forward one quarter.

The questionnaire was broken down by assets and regions, with six of each. In detail we asked participants to give

their views for the quarter to follow: Risk (on or off), and then up or down for the S&P500, oil, gold, dollar index and

10 year rates, without specifying the currency, leaving people to decide what was the most important rate in their

mind.

In total we got 141 answers,

which we later aggregated in

charts and tables. Clearly 141

observations from a universe

selected without any statistical

filter can hardly be considered a

meaningful analysis, but we still

thought it could be of

observational interest to some

of the “Quarterly Review”

readers.

The first picture is a breakdown

of the view of the markets. The

highest conviction was on

bearish gold, with just over 78%

suggesting a possible downturn.

Risk on and SPX up followed

with just over 70%. Between

60% and 70% we find oil down,

dollar up and long rates up.

BLOOMBERG QUARTERLY BRIEF (BQB) SENTIMENT SURVEY

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BLOOMBERG QUARTERLY BRIEF (BQB) SENTIMENT SURVEY 24

We then asked respondents what

region or regions were, in their minds,

going to be most appealing in the

following quarter: US, Europe, Japan,

BRICs, Emerging markets and Frontier

markets.

The geographic breakdown saw the

established markets being the ones

defined as the most likely to be the

investment of choice.

The US was the most voted region,

with almost 42% of selections, followed

by Europe (36%), Japan (20%),

Emerging Markets (15%), BRICs

(6.4%) and the Frontier Markets last

with just 4.3%. Obviously the sum is

not meant to equal 100, as multiple

selections were allowed.

Those attendees who thought the dollar would display strength picked the US as their main choice (41%), followed by

Europe (24%), Japan (20%), EM (10%), Frontier (3%) and only 1% for the BRICs.

The only group which didn’t select the US as their top choice was formed by those who thought rates were going to go

up (see charts overleaf). In this case Europe scored highest (30%), followed by the US (27%), Japan (20%), EM (12%),

BRICs (6%) and Frontier markets (5%). This scenario seems to fly in the face of logic, which would want the European

periphery suffering from an increase debt-servicing burden if rates were to go up, but maybe this scenario includes

more special measures to support the weaker European markets.

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25

Dollar Up Rates Up

Risk On Risk Off

The next level of analysis was done by qualifying the regional choice based on the views on risk and assets: 31% of the

respondents with a risk-on view chose the US, followed by 27% choosing Europe, 18% Japan, 15% EM and 5% each for

BRICs and Frontier. The opposite view on risk, risk-off, still picked the US as their main region, with 39%, Europe 36%,

Japan 11%,BRICs and EM selected by 7% each while no risk off respondents saw the Frontier markets as an opportunity

for the next three months.

BLOOMBERG QUARTERLY BRIEF (BQB) SENTIMENT SURVEY

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STRATEGY IN BRIEF 26

Automated Market Breadth Strategies Market breadth is a very useful tool

for tracking the strength of the wider

global equity market indices.

Analysis of market breadth involves

studying the performance of the

individual constituents within an

equity index to assess the internal

strength or weakness of the overall

index.

Just as a sports better would study

the form of the players within a

team before placing a bet on a

match, market participants can

learn valuable information about the

strength of an equity index by

analysing the performance of the

component stocks.

Bloomberg has recently added a

new suite of market breadth tools

that can not only be used visually

on the charts but can also be

incorporated into automated

strategies and tested using the

backtesting function.

The graphic (right) shows exactly

which equity markets are covered

and what Market Breadth measures

are available. 8. Market breadth indicators

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STRATEGY IN BRIEF 27

15. Strategy creation and backtesting

Bloomberg now offers a number of traditional market

breadth studies such as cumulative advance decline

but has also added market breadth calculations on

technical indicators. For example, the chart on the right

shows the S&P 500 with the percentage of stocks that

are oversold on RSI (i.e. value <30).

Now rather than relying on a single oversold reading

when the RSI of the S&P 500 Index dips below the

threshold oversold level of 30, it is possible to track the

percentage of stocks within the index that are oversold.

Looking at the chart (right) It is clear to see how the

extreme readings naturally occur at market troughs.

Recent enhancements to the Custom

Study Manager function STDY <GO>

enable clients to build studies that

include the new market breadth

fields.

By importing the market breadth field

to the custom study builder as

supplemental data it is possible to

build a histogram of the percentage

of stocks that are oversold on RSI

and then put Bollinger bands on the

study (see the CS.Lite code – left).

The goal is to identify buying

opportunities when the percentage of

stocks that are oversold spikes above

two standard deviations from a 20

period moving average.

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STRATEGY IN BRIEF 28

15. Strategy creation and backtesting

Having built the study in the Custom Strategy Manager it is now possible to integrate it into a strategy in the

Backtesting function BT <GO>. Simply find the study amongst the User Defined Studies and add it to the selected

factors. The goal is to develop a strategy that buys the market when the percentage of RSI oversold stocks retraces

from an extreme level.

The Enter Long signal is generated when the percentage of oversold stocks crosses back inside the upper Bollinger

band after an extreme high reading that peaked above the upper Bollinger band starts to retrace. The strategy stays

long until either a 10% loss of equity occurs or a volatility based trailing stop is triggered (see the May 30th issue of

the fortnightly Technicals BRIEF for an explanation of the Chandelier Exit).

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STRATEGY IN BRIEF 29

15. Strategy creation and backtesting

Looking at the results we can

see a nice smooth upward

trending equity line. The

winning ratio of 60.6% is solid

especially as the average

winner is over three times the

size of the average loser.

The performance of 89.6% is

strong but underperformed a

buy and hold strategy over

the same period which

returned 98.4%. However, the

maximum Drawdown for the

strategy was 16.2% which is

significantly better than the

27.5% drawdown incurred by

the buy and hold strategy.

Performance potentially could

be improved by optimizing

some of the parameters such

as the stop loss percentage

and the component values for

the Bollinger bands and

Chandelier Exit.

The results below are based on the S&P 500 using daily data for a five year period from the start of 2009 until the end of

2013. It assumed a starting capital of US$100,000 and 100% of capital was employed in each trade. The results do not

include commission or slippage. No optimization was done for this example.

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STRATEGY IN BRIEF 30

15. Strategy creation and backtesting

A new feature that has recently been added to the backtesting function is the Portfolio Analysis tool which tests the

performance of the strategy across several securities at once. It is also possible to see the cumulative profit/loss for the

basket of securities.

Notice how the strategy performed

well across a large list of indices.

Given that it is a long only strategy

it is actually encouraging that the

poor performing markets have

been the indices that have

performed poorly over the test

period.

The strategy seems to be well

suited to upward trending markets

while the persistence of the profit

factor, Sharpe ratio and

drawdowns show a reasonable

level of stability.

Combining the market breadth

functions with the backtesting

functionality creates some

interesting signals, given the

robust performance of this strategy

it is worth monitoring these signals

which can now be achieved by

setting alerts on the backtesting

strategy signals across a group of

securities.

The combination of the Market Breadth fields, Custom Strategy Manager , Backtesting, Optimization feature, Portfolio

Backtesting and Strategy Alert functionality provide a nice suite of complimentary functions for developing, testing and

monitoring automated technical strategies.

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EXPERT BRIEFING 31

Riccardo Ronco is the head of

Technical Analysis at Aviate

Global in London. He follows

large- and mid-cap European

and U.S. equities, paying

attention to domestic and

foreign equity indices,

currencies, commodities and

interest rates. Prior to joining

Aviate Global in April 2010, he

worked for Credit Agricole

Indosuez, Banca Intesa Group,

Banca AntonVeneta

(MontePaschi Group) and FBR

Capital Markets.

How would you describe who you

are and what you do?

I am the head of technical analysis

research here at Aviate Global in

London. On a daily basis I use my

quantitative models for US and EU

equities to generate ideas for our

institutional clients. More traditional

technical analysis is used, instead, to

have a complete macro view of all

asset classes and to spot important

rotational moves.

What attracted you to the financial

markets?

The possibility to apply mathematics

and physics (disciplines I love) to see

patterns in investors’ behaviour.

Please describe your approach to

understanding the markets, do you

use technical analysis,

fundamental analysis or both,

please explain why?

I have never used fundamental

analysis. I have also moved away

from the more traditional technical

analysis: I would like to define myself

as “semi-quant”, something in

between a pure technician and a pure

quant. I believe no one can predict

the markets consistently in the long-

term: trends exist ex-post clearly

hence the best we can do is to

identify the beginning of a trend and

try to ride it as long as possible.

What technical analysis

techniques, if any, do you favour?

I am a trend follower and I apply this

methodology to several asset

classes: ranking with volatility

normalization is the second layer

used for indices, sectors to single

stocks. Relative strength (not the

RSI) and the OBV indicator are

extremely useful for equities.

Do you use automated systems or

rely on judgment?

I use automatic ranking models to

focus my interest on particular asset

classes/sectors: once that process is

completed, I apply a second

automatic layer to see the existence

of trends and their maturity.

Judgement is used when several

stocks are triggering the same signal

and other elements have to be

brought in to find high probability

patterns.

What timeframes do you favour,

historical, intraday or a

combination of both?

Daily for timing but, with the passing

of time, weekly and monthly models

are, in my opinion, clearly superior for

the purpose of better identifying

trends and reducing the cost of

trading. I therefore tend to move

away from daily charts whenever

possible on use longer time frames.

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EXPERT BRIEFING 32 Do you use a trading system? If

you do what are the key statistics

to consider when evaluating one?

I use several models: as discussed

in all my presentations we need to

evaluate mathematical expectancy

and the percentage of winning

trades on the overall trading activity.

I would like to suggest Nick Radge’s

book “Unholy Grail” as an excellent

initial source to understand trading

systems.

What is the least important aspect

to consider when building trading

systems?

The entry. Using higher or longer

time frames, what is crucial is getting

into the market and ride the trend as

long as possible. Focusing on the

best possible “feel good “ factor at

the entry is a waste of time if one

has chosen to be a long-term trend

follower.

Do you employ portfolio

management and/or pyramiding

techniques?

I monitor volatility a-la “Turtle”.

Partial profit taking is suggested

when volatility is above certain

threshold but no pyramiding is used.

Specifically, I never ever average

down. Ever!

How important are drawdowns

and money management in your

opinion?

Money management is the most

important element: we cannot

control the result of each single

trade however we can control the

size/exposure to certain parameters

we are comfortable with. As per

drawdowns, the longer we trade the

bigger the drawdown we will

eventually hit no matter how good

we are. The biggest drawdown is

always ahead of us.

What is your opinion/approach to

optimization?

It depends how it is used: if it is used

to over fit a market or a portfolio then

one should not be surprised when

results will eventually degrade. If we

use it to see if our model is robust

and works on several parameters,

then this is the right approach.

What advice would you give to

those who are new to the financial

markets and want to become the

next Riccardo Ronco?

Study as much as possible markets

in all time frames and in different

countries. Go back as far as

possible. History is, after all, our text

book.

Can we have the name of

someone who has impressed you

during your career?

Perry Kaufman, David Harding, all

the “Turtles”, Mebane Faber, Nick

Radge, Andreas Clenow and John J.

Murphy.

Is there anything you would do

differently, if you were given a

chance?

No.

Is the future all into algo trading

and automated systems or does

human intuition still have a role?

Human intuition (as gut feeling for

trading) has no longer a role: human

research and accurate testing of that

research have, instead, incredible

importance in my opinion. Algo and

systems are merely tools,

implementation of someone’s idea.

You still need that idea in the first

place: that idea come from

observation and research.

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APPENDIX 33 1. The red and blue signals in the Overview section are an indicator called Volstall. It is our own indicator created in STDY<GO>. It uses the rate of change of

the moving standard deviation of price to identify possible reversal points through decreasing momentum. A guide to STDY<GO> as well as a forum can be

found within red toolbar in the function.

2. In the Overview section the bars are painted according to a triple exponential moving average crossover with averages of 4, 9 and 18. The blue and red

Volstall signals and painted bars are created in the strategy events. From a chart click on the events flag ,+Add Event, Browse then select option17)

Strategies & Studies.

3. The indicator below the charts in the Overview section is the Fisher Transform with Squeeze (Indicator outlined by John F. Carter) . The indicator uses a

Gaussian probability density function (Gaussian PDF) as opposed to a more traditional bell-shaped probability density function to calculate the position of

the price compared to its range (see TECH<GO>). Squeeze signals are shown as red bars and occur when the Bollinger bandwidth is less than the Keltner

band with signalling low directional volatility.

4. On the volatility charts we have used Bollinger bands with a 60 period moving average with upside deviations of 1, 2, and 3. On the downside we have used

1,1.5 and 2 standard deviations from the average, to reflect the inherent skew in volatility indices.

5. World Trend Graph can be found at WT<GO>

6. Relative Rotation GraphsTM can be found at RRG<GO>. Relative Rotation GraphsTM of Relative Rotation Graphs Limited. See

www.RelativeRotationGraph.com . Please see DOCS 2063266<GO> for more information.

7. The scatter plot chart can be found at GS<GO> and allows for the visualisation of 4 unique sets of data.

8. More information on Bloomberg’s Market Breadth indicators across 54 different markets can be found at DOCS 2068663<GO>

9. Implied forward curves can be charted in FWCM<GO>

10. Historical curves can be charted in GC<GO>

11. An inflation indicator template and Breakeven rates can be found at ILBA<GO>

12. Sentiment and positioning data can be located at IPSP<GO>

13. Implied probability FX forecasts are derived from FX options and can be found at FXFM<GO>

14. Historical regression analysis between 2 data series can be done in HRA<GO>

15. Use BT<GO> for the creation, backtesting and optimisation of strategies. It will integrate your own custom studies built in STDY<GO> and can also

generate alerts. A guide to BT<GO> as well as a forum can be found within red toolbar in the function.

OTHER RESOURCES

• CHART<GO> is the homepage for Bloomberg charts and technical analysis with links to a variety of functions and resources including

documents on Bloomberg’s own proprietary studies.

• ‘Getting Started With Bloomberg Charts’ at DOCS 2069346<GO> for an introduction to what is possible.

• ‘A Guide to Bloomberg Charts’ at DOCS 2065187<GO> for a more thorough walkthrough how to use our charting and technical analysis

functionality.

DISCLAIMER - Read the full Bloomberg Tradebook disclaimer here: http://goo.gl/UewDb

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