guido riolo, msta - the technical analyst€¦ · guido riolo, msta – 14 // paul ciana ... tema...
TRANSCRIPT
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Bloomberg BRIEF: Technical
Strategies Quarter in Brief
Contributors
Eoghan Leahy, CMT, MSTA
Ph: +44-20-7392-0599
Maurizio Pietrini, MSTA
Ph: +44-20-7073-3666
Guido Riolo, MSTA
Ph: +44-20-7330-7211
Oliver Woolf, CAIA, MSTA
Ph: +44-20-7073-3148
Paul Ciana, CMT
Ph: +1-212-617-8229
Greg Bender, CMT
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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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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