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CONTENTS 1 FEATURES

Interview Aaron Brown of Morgan Stanley

talks poker and the markets

Trading Time In an excerpt from his new book, Shaun

Downey explains the importance of using timeas part of an effective trading strategy

SoftwareJohn Bates of Progress explains the

requirements, challenges and approaches thatshould be considered in backtesting

algorithmic trading

JULY/AUG

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WELCOMEThe importance of being aware of the technical picture in all time frames is often

emphasised by successful traders. For example, if you are trading short termthen major technical levels may exist out of your time frame that should be con-sidered. In this issue, we look at one approach taken by Shaun Downey at CQG

as to how best to use ‘Time’ as part of an effective trading strategy.

We hope you enjoy this edition of the magazine

Matthew Clements, Editor.

July/August 2007 THE TECHNICAL ANALYST 1

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INDUSTRY NEWS

MARKET VIEWS Euro STOXX 50: Bull trend remains intactEUR/USD: Bearish reversal signals?US Interest Rates: Changing perceptions

ROUNDTABLEBond market outlook

TECHNIQUES Technical analysis by numbersTrading timeCandlestick signals: The J-hook patternPortfolio testing

INTERVIEWAaron Brown, Morgan Stanley

SOFTWAREAlgorithm backtesting, Progress Software

BOOKSTrading Time by Shaun Downey

RESEARCH UPDATE

AUTOMATED TRADING SYSTEMSProgramming and InteroperabilityStrategy spotlight: Stein Investment Management

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CONTENTS 2 REGULARS>


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4 THE TECHNICAL ANALYST July/August 2007

Industry News

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Market Views

EURO STOXX 50 BULL TREND REMAINS INTACT by Cyril Baudrillart

The goal of this analysis is not simplyto study the index's trend and targetsbut also to evaluate the current shapeof European equity markets via inter-market analysis and market breadthindicators. But let's start with a basictrend analysis.

Trend following methodsOver the last few years, I have beenmonitoring developments of the bullmarket through objective trend-track-ing methods using weekly and monthlyprices. The methods include point &figure charts, Ichimoku, Daryl Guppy'smultiple moving averages and, ofcourse, classical simple moving aver-ages such as 200, 100 and 50-day mov-ing averages. According to most ofthese methods, the primary trendturned from bearish to bullish in thesecond half of 2003 and, so far, thisbull trend has remained intact (Figure1).

These trend following indicators areintended to help us trade in the direc-tion of the primary trend. They willnever identify market peaks, but that isnot their goal. Before studying a few

market-timing indicators, let's focus onthe next upside targets for the mediumterm. The index has now retraced morethan 76.4% of the 2000-2003 down-trend on a semi-log scale. This increas-es the probability of retesting the all-time high of 5522, attained in March2000. According to some point & fig-ure charts, the next short-term targetcould be in the 4758-4800 area. A breakthrough the 4560-area, which corre-sponds to the upper end of the ascend-ing triangle forming since early June,would increase the probability ofreaching this zone. Another potentialtarget is located at 5332 points, which is2.618 times 1847 points, the intradaylow of March 2003 (the next TomDeMark Absolute Retracement™).

TD Combo™Now let us focus on market-timingindicators. As markets never move instraight lines, technicians must alwayshold a few contrarian indicators in theirtoolbox to identify overbought zones.

In sustained bull trends, classicaloscillators such as RSI and stochasticsdo not help as they can stay overboughtor build multiple bearish divergencesfor a long time. In such trends, mostcontrarian indicators give mixed results;the exceptions include Tom DeMark'sTD Combo™ and TD Sequential™,which help to identify low-risk sellareas, or at least to limit losses on con-trarian trades. The daily TD Combo™correctly identified the peaks ofNovember 2006 and February

Figure 1.

Back in October 2006 theconsensual technical out-look for the equity markets

was for a continuation of the bulltrend which later proved to bepretty good advice. The technicaloutlook today is not very different.The trend remains our friend andinvestors have continued to buythe dips quite aggressively duringsetbacks.

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Market Views

2007. A new TD Combo™ 13-sellcountdown was completed on 31 May.This signal has not been disqualified asit would require a daily close above4576, followed by an open above theprevious day's close. As long as a breakthrough this level does not occur, acontinuation of the current consolida-tion period will be favoured accordingto this method.

Weaker dollar and bondsA deterioration of the macro environ-ment supports the possibility of mixedperformances on the equity markets inthe coming months. First, the mid-termtrend on bond yields has reversed sig-nificantly worldwide. In Germany, 10-year government bond yields may reach4.90% in the coming months.

Second, more recently European cor-porate spreads have been widening.The technical bounce of the iTraxxEurope index (Figure 2) is now moresignificant than that of late-Februarybut, unlike in March, this rise has nottriggered a significant correction ofequities. Nevertheless, the trend ofimplied volatility indices such as theVDAX and VSTOXX in Europe hasalready turned upwards. For the first

time since the late-1990s, stock marketsare advancing with implied volatility ris-ing, an indication that they have entereda speculative phase.

Third, the euro dollar's trend remainspositive and the odds are still in favourof an upside breakout through the1.3680-resistance zone with a possibletarget in the 1.40-area.

Oil and gas support equitiesIn light of this mixed macro outlook,we have to admit that the recent stabil-ity of the Euro STOXX 50 index isquite impressive. A study of sectortrends helps to explain the absence of asharp reaction by the index to therecent rise in corporate spreads.

This robustness is mainly due to thestrong re-rating of the oil & gas sector,which has fully overshadowed theweakness of financials. It is also worthnoting the persistent weakness of thehealthcare sector. We have to go backto the late-1990s, i.e., near the end ofthe TMT bubble, to find a similar sus-tained under-performance of thisdefensive sector. Investors are capitu-lating again.

Excluding commodity-sensitivestocks and a few other cyclical sectors

such as auto and chemicals, the index'smarket breadth has deteriorated signifi-cantly since early June. The percentageof Euro STOXX 50 stocks tradingabove their 200-day MA has declined to70%, from 90% a month ago. TheBullish Percent Index calculated onSTOXX 600 stocks also highlights thisdeterioration. This indicator measuresthe percentage of the index's compo-nents that are bullish according to a 1%x 3 point & figure chart, i.e., where the

last signal is at least a double top buy.According to this index, the percentageof stocks that are on a bull trend hasdeclined sharply, from 85% in May tobelow 60% in early-July. Nevertheless,the index is holding above 50%, whichsignals that the overall trend remainsbullish.

ConclusionThe index has entered a short-termconsolidation period that may eventual-ly continue through the summer in theevent of weak bond markets and dollar.However, a drop below the 4330-sup-port zone would be required to con-firm the risk of a more pronouncedsetback between 4200 and 4100.Alternatively, a break through 4560-4576, which includes the upper end ofan ascending triangle, could restore thebull trend with the next targets ataround 4800 in the near term andmaybe 5332-5522 in the long term.

As the overall trend remains positive,we cannot anticipate a major reversal inthe trend at this stage, even though theequity markets have probably entered amore speculative phase.

Cyril Baudrillart is European equi-ties technical analyst at Exane BNP

Figure 2.

“…THE PRIMARY TRENDTURNED FROM BEARISHTO BULLISH IN THE SEC-OND HALF OF 2003 ANDHAS REMAINED INTACT.”


Market Views

EUR/USDELLIOTT WAVE SUGGESTS BULL MARKET IS NEARING COMPLETION by Andrew Chaveriat

Elliott wave analysis suggests theOctober 2000 EUR/USD bullmarket is drawing to an end.

The bull market appears in its final fifthwave, targeting completion ideallybetween 1.3925-1.4225 during lateAugust to mid-September 2007. Thiswave five high should complete the bullmarket and mark the beginning of anew bear market targeting a long-termdecline towards the 1.2485 October2006 low and eventually the 1.1640November 2005 low, representing sup-port from the fourth wave of one less-

er degree (wave IV low). See Figure 1.The current wave V rally off the

1.1640 November 2005 low is sub-dividing into the requisite five wave pat-tern. The wave 3 of V rally ended at the1.2980 June 2006 high. Wave 4 of Vconsisted of the June-October 2006horizontal trading band between1.2980-1.2485. Wave 5 of V originatedoff the 1.2485 October 2006 low and isforming a fifth wave extension. Wavesi of 5 (1.2485-1.3370), ii of 5 (1.3370-1.2865), iii of 5 (1.2865-1.3685) and ivof 5 (1.3685-1.3265) are finished.

The wave v of 5 of V rally is now inprogress (off the 1.3265 June 2007low). Overlap between the wave iv low(1.3265) and wave i high (1.3370) indi-cates the October 2006 rally (wave 5 ofV) is forming a diagonal fifth wave tri-angle. This pattern, also known as ris-ing wedge, portends a swift declineonce the current wave v of 5 of V rallyends. As Frost and Prechter* note, "Arising wedge… is usually followed by asharp decline retracing at least back tothe level where the diagonal trianglebegan"; in this case the 1.2485

Figure 1. EUR/USD Weekly - Long-term Elliott wave count

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Market Views

October 2006 low (see Figure 2).

The market topAs noted earlier, the probable targetzone for completing the wave v of 5 ofV rally is 1.3925-1.4225 during lateAugust to mid-September 2007. ThisElliott price target zone includes pro-jections from waves of three differentdegrees including the 127.2% retrace-ment of wave IV (1.4220), 423.6%retracement of wave 2 of V by waves3-5 of V (1.3945), and the wave iii of 5= wave v of 5 measured move (1.4085).Finding targets from multiple timeframes grouped closely togetherbetween 1.3925-1.4225 increases theprobability that the 2000 bull marketwill terminate in this area.

The 1.3925-1.4225 target zoneincludes testing the top of the October2006 rising wedge now near 1.3850 andprojected to lie between 1.4015/50 dur-ing late August to mid-September 2007when wave v of 5 of V is expected topeak. That includes seeing the June2007 wave v of 5 rally persist until it

measures 161.8% of the duration ofwave i of 5, and 100% of the durationof wave iii of 5.

Weekly momentumWeekly momentum is surging followingits bullish crossover during late June.The strength of bullish weekly momen-tum is reminiscent of that during thepowerful October-November 2006rally (8-weeks/+8.85-cents; wave i of5). This implies scope for a sizablemedium-term spot advance: if the cur-rent June rise off 1.3265 matches theOctober-November 2006 advance,EUR/USD will hit 1.4150 in August2007 reaching the 1.3925-1.4225 Elliotttarget zone.

We suspect weekly momentum -- nowat 74% on the 8-week modified sto-chastic -- will rival the overbought con-ditions of December 2006 (84%) andform bearish divergence with the April2007 extreme (90%) in the weeks aheadas EURUSD posts a major top.

Bearish reversal pointsGiven EUR/USD has been rallying fornearly seven years, it will take a cleanbreak of key support in order to con-firm that a bear market is underway.Initial signs of a bear market will likelyinclude a bearish weekly reversal signaloccurring in the favoured 1.3925-1.4225/late August to mid-September2007 target zone, sparking a declinethat breaks daily support from therecent 1.3415 June 27 low. Additionalconfirmation of a bear market wouldinclude a sustained break of theFebruary 2006 uptrend (now near1.3250) triggering a long-term bearishtrend reversal and a break of pivotalweekly support from the 1.3265 June2007 low.

Andrew Chaveriat is a technicalanalyst in the foreign exchangedepartment of BNP Paribas in NewYork.* Frost and Prechter: Elliott Wave Principle,New York: New Classics Library, 1985 (5thed.), pp 30.

Figure 2. EUR/USD Daily - Medium-term Elliott wave count


Market Views

INTEREST RATESCHANGING PERCEPTIONS by Ron William

Interest rate fever swept the marketafter the yield on 10-year US gov-ernment bonds registered its

biggest jump in years. The sharp risehas now pushed above a twenty-yeardowntrend and signaled a potentiallong-term advance in rates. Technicalprojections offer an initial target of5.50%, followed by the psychological6% level. Such a move could have glob-al implications as other key governmentyields also climb higher, fuelled bystrong economic data, and in places,fear of inflation. Moreover, historicaltrends in the supply of money and astudy of the relationship between com-modity prices and interest rates providefurther evidence for a sustained periodof rising inflation.

Long-term trendsIn 1981 US interest rates peaked near16%, after an extended period of risinginflation. Following this peak, interestrates declined for just over twentyyears. These alternating long-termtrends, otherwise known as secularmoves, reflect generational economicand social changes in society, (usuallylasting a minimum of two businesscycles). The low in 2003, at 3.10%, tookplace in a deflationary bond buyingpanic and marked the lowest level inyields since the mid-1950s. It alsoended the secular decline. Since then,rates have advanced and recentlypushed above the major trend-channel.A sustained break above this areawould fuel a secular advance.

Money supplyWhen central banks grow the supply ofmoney faster than the general economy

is growing (measured by GDP growth),relatively more money chases fewergoods and services, producing infla-tion. The chart below illustrates histor-ical trends in the annual growth rate ofmoney supply - (measured using M3 -the broadest definition of money). Inthe 1970s the western world experi-enced double digit rates of inflationand money growth, associated with a

rising commodity bull-market. This wasthen followed by a major decline as thethen Fed chairman Paul Volkerattempted to curb inflation by targetingM3. The result was massive disinfla-tion, with M3 rising, but at a slowerrate, relative to the growth of the1970s. The 1990s was a period of defla-tion, registering a negative growth ofM3. Thereafter a new uptrend in

Figure 1. US Long-term interest rates advance from overstretched half a century lowsand break above the major trend-channel. Source: Bloomberg L.P.

Figure 2. Historical trends in the supply of money, highlighting the most recent rise.Source: Bloomberg L.P.

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M3 began to reflate financial assets andthe stock market boom, runningthrough to 2000. Recently, the trendhas altered direction and risen higherinto April of 2006, which is when theFed stopped reporting M3.

Rising commodity pricesFigure 3 illustrates the unique relation-ship between the CRB CommodityIndex and US interest rates up to 2001.Since 2001, however - during the thirdgreatest commodity bull market inmodern history - the CRB CommodityIndex and US Interest Rates havediverged significantly. This is almostcertainly unsustainable. Traditionally,commodities are the basic source forgoods and services produced in theeconomy and higher prices eventuallylead to a rise in the general cost of liv-ing.

The last time there was a strong neg-ative correlation between the CRB and10-year yields was more than twodecades ago in the early 1980s, whenthese two markets shared a low correla-tion of -0.34. Interestingly, the only twostrong negative correlations occurredaround major long-term trend changeson the CRB Index. Psychologicalchanges in perception could explain

why interest rates lagged commodityprices during these two instances. Atwenty-year secular trend is such a largefraction of an adult's professional lifethat investors have a tendency tobelieve that prices only ever move inone direction. This rear view mirrorconditioning tends to be strongest atmajor turning points, when the long-term view is being challenged.

The negative correlation in the early1980s happened after the CRB Indexreached its all-time high of 335, follow-ing a decade-long advance in commodi-ties. Most investors viewed this periodas the wave of the future and very fewbelieved that a change in trend was pos-sible. Interest rates continued to riseafter the peak in commodity prices andit was only after a 20% drop in the CRBthat inflationary fears started to recedeand interest rates finally began declin-ing. Today we are faced with an evenlarger psychological change in percep-tion as most investors continue toexpect interest rates to hold aroundoverstretched half century lows,despite the fact that commodity pricesalmost doubled by early 2006.

ConclusionInterest rates have broken above the

long-term trend-channel, favouring anadvance to 5.50% and the psychologi-cal 6% level. It is worth rememberingthe move originated from over-stretched half century lows and stillmaintains significant divergence fromcommodity prices. Once a critical massof investors realize the economicimpact of a secular bull-trend in com-modities and rising inflation, this psy-chological perception will be overcome.

The most recent phase has seen a sixyear lag between the upturn in the com-modity trend and interest rates. Onekey reason for this is the disinflationeffect of low priced goods manufac-tured from emerging markets, notablyIndia and China. However, this global-ization dividend and the cyclical impactfrom excess capacity are now startingto unwind and with central banks vigi-lant on inflation, interest rates will like-ly continue to rise.

Ron William is a Technical AnalysisSpecialist at Bloomberg, LP.

The views and analysis presented here is not a rec-ommendation to buy, sell or hold any security norare they to be relied upon for any investment deci-sion. The views and analysis expressed here aresolely those of the author and do not neccesarilyreflect those of Bloomberg, L.P.

Figure 3 – CRB Commodity Index shares a unique relationship with US Long-term interest rates. However since 2001, the third great-est commodity bull-market in modern history has generated significant divergence with interest rates. (KEY: White – CRB Index,Orange – US Long-term interest rates) Source: Bloomberg L.P. {Type HS <GO> to analyze the spread and correlation of two select-ed securities}.

Market Views

INTERMARKET ANALYSISFollowing the recent rise in longer end US bond yields, we bring togeth-er four leading market analysts to discuss the technical outlook for bondsand the likely impact of higher yields on the global markets.

Chair: Matthew ClementsEEddiittoorr,The Technical Analyst

David SneddonDDiirreeccttoorr iinn tthhee FFiixxeedd IInnccoommee ddiivviissiioonn aanndd TTeecchhnniiccaall AAnnaallyysstt ffoorr tthhee gglloobbaall ffiixxeedd iinnccoommee mmaarrkkeettss,,Credit Suisse

Clive LambertDDiirreeccttoorr,,FuturesTechs

Tom HobsonCChhiieeff GGlloobbaall TTeecchhnniiccaall AAnnaallyysstt aanndd HHeeaadd ooff EEMMEEAA FFiixxeedd IInnccoommee SSttrraatteeggyy,,Merrill Lynch

Max Knudsen DDiirreeccttoorr,PIA-First

Sponsored by:


Is the recent breakout of the 10 year US Treasury yield from its longterm downtrend the real thing or could it still be a false break?

Max Knudsen: If you look at the price action it's pretty con-vincing. The cash market is hovering around 5.25% and thisreflects the fact that real money knows yields are going high-er. The breakout in the futures market is basically a continu-ation of what has been happening for the past four years.There has been a sharp decline in bearish momentum duringthe past two weeks but this has been prop traders picking upcheap paper.

Tom Hobson: I think it's all a continuation of the priceaction since 2003. We are in the middle of a correctiveprocess from very low yields that's accelerating. Therefore, Ido think it's a sustainable breakout and that we are now in alonger trend towards higher yields. The era of low yields isover. For me twos and fives have already reversed over a yearago. It's the long end that is important now and directionalleadership in bonds is also about to switch back to the US.

What are the main price projections that can be made from this break-out and what are they based on?

David Sneddon: For the 10 year Treasury, there is a wholecluster of key levels around 5.40%-5.50% and how these aredealt with will be the next big test for the US bond markets.These level projections are based upon retracements fromthe yield base at 4.91%-4.40% and a weekly resistance linegoing along the top of the highs of the last few years at5.43%. I expect to see buyers trying to defend this area so theoutcome from this level will be a key signal. Also importantare old yields highs from 2001 and 2002 and Fibonacciretracements. It could turn out that the rise in yields since2003 is a continuation wedge and so the upward move inyields will stall. However, my projection is for yields to go to6.0% by the end of the year followed by the possibility of a

The 10 year US Treasury

“[BUND TRADERS] USE CANDLESTICK AND MARKETPROFILE CHARTS AND SO

PRODUCE VERY ‘WELL BEHAVED’TECHNICAL SIGNALS”

- CLIVE LAMBERT


Clive Lambert


long sideways move.What we need to look out for in the fixed income markets

which will bring our consolidation phase to an abrupt end isa rise in 10 year JGB yields about 2.05%. Beyond that theycould go explosively higher in the long end and there is nosupport after that until 2.50%. A big sell off in Japan willbring consolidation to an end in the US and Europe.

Tom Hobson: It depends on the time frame. My retrace-ment target from the high is 7.94% and so it's difficult tocome up with a technical reason why yields shouldn't go to7% in the next five years. I'm targeting 5.75% to 6.0% by theend of the year.

The interest rate bubble that began in the early sixties andtopped in 1981 and bottomed in 2003 is a historical event ofhuge magnitude whether you look at it from a technical orfundamentals perspective. Does this mean however that weare going to go back to yields above 10%? I think it's veryunlikely.

Do bonds remain a leading indicator of the stock market and howshould the dollar be reacting?

David Sneddon: Trying to find a stock market sell signalusing the bond market just isn't working at the moment. Theevidence for changing sentiment in the equity markets justisn't there now. Also, it should be remembered that the 2 yearTreasury hasn't moved much and even long end yields are nothigh enough to dent equities at the moment. The stock mar-ket has had plenty of opportunity to go down over the pastmonth but has been supported

The resilience of US stocks is extraordinary and I believethere is plenty of way to go even taking into account higher10 year yields. But the dollar is reacting although not in theway that may have been expected. Dollar weakness can beseen against the yen, euro and Swiss. Dollar/Swiss is interest-ing because we may be approaching levels below 1.20 that aremajor supports and if these fail to hold then we will seemuch more entrenched dollar weakness.

Max Knudsen: I look a lot at the dollar index future and thelast few weeks have seen further entrenchment of bearishdollar sentiment, despite higher yields. Importantly, key sup-port levels continue to be broken including the previous 2004low of 80.48 following an evening star pattern formation inJune. The next major level is the 1995 low of 80.14. I'm oncalm alert at the moment because if 80.14 were breachedthen we are looking at 78.95, the 1992 low. Following eachbounce in the index, the sell off has been progressively moreaggressive so the significance of 80.14 should not be under-estimated. However, we may see some short term profit tak-ing soon.

Clive Lambert: The gorilla in the room is equity markets.While there's no sign of a turnaround at present, if things did

suddenly turn it would surely be swift and nasty and therewould be a flight to quality into bonds. This relationship isn'tas hard and fast as it used to be, but in these kinds of 'event'situations it always comes to the fore again.

Tom Hobson: US stocks haven't had a 10% correction yetwhich is what all the equity guys in the US are still worriedabout as European stocks have already corrected last year.

On the currencies side of things, yen weakness and thestrength of European currencies is a bigger issue than thedollar. The yen is going to get crushed in the months aheadas it begins to capitulate against the European currencies andAustralian and New Zealand dollars. Whilst this might soundlike a fundamental view, it's actually technical in naturebecause of the way central banks have responded.

Tom Hobson


Intervention has taken place against channel resistance so aswe see the yen move to 177-180 verses the euro, the pressurefor intervention will become severe and this in turn will forcethe Bank of Japan to raise rates.

What about the European bond markets? Are bund prices still follow-ing Treasuries?

Clive Lambert: If Bunds are not following the Treasurymarket in the way they once used to, it is probably becausethe ECB is now producing a clearer outlook on rates wherewith the Fed, things remain very uncertain. Now many of thebig moves in the bund market happen in the morning beforeT bonds open.

First of all can I point out my clients are all short termtraders so I very much concentrate on the price and don'tspend much time at all looking at yields and cross-marketcomparisons. Bunds have been behaving very well lately froma technical point of view. In December, again in March, andonce more in mid May we came out of a period of consoli-dation by breaking a short term uptrend line, then soon afterwe saw the breaking the bottom of the Bollinger Bands on aclosing basis. On each occasion this signalled an extendedperiod of weakness. Bunds are in a consolidation phase at themoment between 109.66 and 111.31. The next move I expectis through the lower level.

Why have technical signals in the bund market been so reliable?

Clive Lambert: The great advantage of trading the bundmarket is that the technical signals have been so clean recent-ly. Up to 50% of trades done on Bund, Bobl and Schatz con-tracts along with euribor and short sterling are done by pro-prietary or 'local' traders who have a heavy reliance on tech-nicals and trade very short term timeframes. They use candle-stick and Market Profile charts and the effect is to producevery 'well behaved' technical signals and patterns. Also inChicago, profile charts are very widely used. I guess this high-lights how technically driven bond markets are!

David Sneddon and Clive Lambert are both board members at theSociety of Technical Analysts (STA).

Max Knudson

“THE 10 YEAR TREASURY CASHMARKET IS HOVERING AROUND5.25% AND THIS REFLECTS THEFACT THAT REAL MONEY KNOWS

YIELDS ARE GOING HIGHER.”

- MAX KNUDSEN

David Sneddon

TECHNICAL ANALYSIS BY NUMBERS by David Linton

The ever increasing demands ontechnical analysts and tradersare such that you need to assim-

ilate more key TA data faster and in lessspace on a screen. So you want to knowwhich instruments are doing what interms of your own technical criteriawithout having to scroll through lots ofcharts or run scans. With more andmore powerful computers and softwareyou can virtually put any value orexpression you want in a grid with a'custom column'. You can do much ofthis by writing complex formulas inyour Excel spreadsheets or utilisingfunctions within your market terminalor charting system.

Ranking the RSI Let's say you are looking at the curren-

cy majors and you want to know theRSI position of each one without hav-ing to look at all the charts. Here we seein Figure 1, that USD/GBP has thehighest RSI at 72.83 with Dollar Kiwialso above 70. So if your trading strate-gy is to sell a move below 70 on theRSI, you know these are the only twoyou have to watch. Conversely, two ofthe Scandis below 30 could provideyour next long trades. You may wantadditional information such as someconfirmation of the state of trend. Justadd in the ADX value and you couldrank this column to see the instrumentstrending from strongest to weakest. Sohere we see Euro/Danish has thestrongest trend with Euro/Swiss hav-ing the weakest.

Having the numbers in tabular form

Figure 1.


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on daily data is one thing, but if you arelooking at intraday charts where valuesare changing quickly with minute bars,tracking the TA numbers in a table likethis really counts. You could have val-ues, a trading system or indicatorsshowing in multiple columns for week-ly, daily and hourly for instance, givingyou an instant feel of the charts acrossthose time horizons without having tolook at all the charts.

Comparing stocksIn Figure 2 we see some stock marketindices with their Point and Figure tar-gets for a 1% arithmetic box with addi-tional columns for the stop level andthe risk reward ratio (RR). So rankingby RR we see that Nasdaq has the high-est upside vs. downside on this basisand the FTSE100 the lowest.

Where this sort of analysis becomesreally valuable is for lists of large datauniverses such as stocks. For instanceyou might want to know the stocks thathave the best relative strength againstan index from a given date. In Figure 3we see the Norm R/S column showingBHP Billiton has the highest relativestrength (up 43.35%) from the chosen

date. This ability to cross compare isone of the unseen advantages of nor-malising Relative Strength. Again youcan add in other values such asMomentum to further support yourtabular view of the market.

Perhaps the biggest advantage ofviewing markets in tables is the abilityto have your own signals shown, there-by hiding the complexity of the formu-lae that got you there. For instance, youcan add actions such as BUY and SELLand the number of days since the signalwas given as we see in the last twocolumns of Figure 3. If you are pro-ducing quartile style tables or spread-sheets full of data such as pivot points,watching them live in this way is reallythe way forward.

While experienced technicians will beable to visualise the charts from justlooking at the tables, there is still nosubstitute for opening the chart andseeing all the data you want in graphicalform. The real advantage of this tabu-lar view of the world is that you knowwhich charts you want to open first.

David Linton CFTe MSTA is chiefexecutive of Updata.

Figure 3.

Figure 2.


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Trading time - a double meaningalluding to actually allocatingthe time to trade and then

understanding the critical informationregarding where you are in time when atrade is placed. This facet of time hasmany definitions.

The timeframe of the chart that was usedand why?How critical is the immediate price actiondirectly after the trade is placed?How long is the trade expected to last?At what point in time is the trade withinthe trend or are we at the end of the trend?How strong is the trend based on the timeit has existed?What is the risk/reward in relation totime?

These are all important questions butin my experience of visiting thousandsof traders over the years, they are ques-tions that are rarely asked and for alarge number they are never even con-sidered. One of the first questions Iever ask a trader when we first meet is;what timeframe charts do you use? Theanswer is always a variation on thesame theme. "Oh I use a 30 min, 60min daily and weekly". Not one personhas ever said. "I use the timeframechart that is relative to my concepts ofrisk, volatility and range"

For the great trader their success withthis somewhat random method isproof enough of their inherent ability.For the not so great trader this is arecipe for disaster. Therefore obtaininga true measure of expectation in anyone period of time is critical to improv-ing the chances of success.

Volatility throughout the day When understanding variations of riskthroughout the day, there are manypotential problems. The extension oftrading hours and the ever lengtheningnumber of economic data events meanthat traditional technical analysis meth-ods that measure momentum on a con-tinual basis are facing increasing chal-lenges as markets go through periodsof low ranges and a lack of direction,followed by bursts of activity and shortterm trends. Automated trading seemsto have moved into the very low time-frame, high frequency of trades modelto tackle this problem, but this is not anoption for the human trader. In thesame fashion that timeframes of charts

are often fixed, so are the variableswithin the momentum-based indicatorsthat are used on charts. If a 10 periodmoving average is placed on 30 minutechart on Bunds at 11am the average islikely to have flattened due to lack ofactivity. This would be the same case onthe opening when it would have reflect-ed the activity or lack of it in theevening session of the day before.However, come 4pm, the average coulddisplay completely different behaviourbased on the number of statistics pro-duced that afternoon. Therefore it isvery difficult to use momentum indica-tors in a predictive manner and so wereturn to the inherent ability of thegood trader to ride the waves of

1.

2.

3.4.

5.

6.

Figure 1.

TRADING TIME by Shaun Downey

In an excerpt from his new book, Shaun Downey explains the importance of using time as part of an effective trading strategy.

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volatility. If you accept the concepts ofcontinual fluctuation in range and theoccasional mutation of a market into adifferent environment then the answermust be to make that variable of theaverage continually adjustable basednot only on the range of any particularbar, but also the time of day that thatbar was created.

Volatility time averages andbandsVolatility Time Averages treats eachindividual bar only in connection to thesame bar the previous days.

The average range is computed over

a user defined range. Then the highestand lowest value of range for that timeof day is computed over the last 1000bars. The difference between the cur-rent ranges over n bars is recordedagainst the highest range over the last1000 bars and depending on the differ-ence, an exponential moving average iscalculated. This average is given a userdefined minimum and maximum rangeof average which defaults between a 3and 21 period. The conclusion is thatif the range is narrow in relationship tothe history of that time of day then theaverage slows but if range is large, theaverage speeds up.

Removing the variable of the averageand replacing it with a variable thatlooks at each specific time of day toprevious days enables a set of bandsthat maintain their flexibility to marketchanges. They are called Volatility TimeBands. As soon as the bar opens, theaverage range for that time of day iscomputed and 1, 2 and 3 standard devi-ations are placed on either side of themarket. The use of the opening is crit-ical in that it provides a predictiveframework as the values are fixed andlead to the ability to analyze on a multi-tude of concepts.

One of the key criteria is being ableto understand what is the limit of rangewithin one aspect of time. Whilst 1timeframe can be used in isolation,extra power can be obtained with mul-tiple timeframe confirmation. Figures 1(Bunds) show a confluence ofextremes as the 30 minute chart has anextreme 3rd deviation low at 109.90,which is also the limit of range in the15 minute chart and as low as the 5minute chart. When this is used incombination with true measure of sup-port and resistance with Market Profile,not only can day trading turning pointsbe found, but also major strategic turn-ing points in trend. This is given evenmore strength when the Kase PeakOscillator is showing an oversold sce-nario as seen in the 15 minute chart. Atsuch times for both the short termtrader and strategic players, risk can bedefined as low as 3 ticks on Bunds. Thisis due to the connection betweenmacro picture supports and resistanceand micro picture limits of range. Itallows for far higher volume to be trad-ed as position sizing and subsequentlyrisk reward ratios explode upwards.

Figure 2.→→


Stochastic StepsOnce a trade has confirmed a majorturning point, the next major difficultyis in knowing how to switch such amicro timeframe trade into a positionthat can be held if the trend then devel-ops. This is one of the hardest skills intrading and the development of what Icall Stochastic Steps logic attempts tosolve this problem. Past analysis showsthat there are some trends in stockindex's that began in a 15 minute chartand are still valid 3 years later and for aweekly chart, many thousands ofpoints later.

Stochastic Steps records eachcrossover of the stochastic and stateswhether it was confirming the continu-ation of the trend by doing so in ahigher or lower contract value than theprevious crossover. ThereforeStochastic Steps will either step up ordown each time the stochastic crossesdepending on the comparison in priceto the last time the stochastic crossed.

Trend definition and divergenceHowever, closer examination of howthe Steps interact between the contract

value and the Slow Stochastic valueitself reveals how new concepts ofdivergence can be built based on thepatterns and connections betweenthem. This remains beyond the scopeof this article but it is an importantconsideration for those who want toinvestigate the relationships betweenthe Stochastic Steps with that theory inmind. This becomes clearer if twomore Step studies are created recordingthe value of the stochastic itself whenthey cross over.

Crucially, they also tell us what thefocus timeframe is when a trend beginsand if it develops, whether the focustimeframe is moving higher. Thisenables a trade that may have begunwith a short-term bias to become along-term trade. This is describedbelow.

Confirming the trendEach time the market steps in the direc-tion of the trend, the trend itself isbeing confirmed. Once the relevantindicator has stepped in the same direc-tion 4 times consecutively - this is thetrending and focus timeframe - the

market is in a strong trend. When 6steps are in place we are in a megatrend.

The mega trendIf both Stochastic Steps are above 6this indicates the strongest trend of all.Figures 2 and 3 show the 15-minuteentering a mega trend. This is followedby the 30 minute doing the same laterin the trend. This is an example of howthe focus timeframe can be moved upand allow for trends to be ridden forlonger.

This is critical to trends developing asthey must move up timeframes in acontinuous fashion or the trend willsimply die. Most trends with low begin-nings will often end long before thefocus timeframe moves up to a dailychart. This is normally true of bondand FX markets which rarely gobeyond a half day chart. Even so thiswould entail a trend lasting for morethan 6 months in most cases. The realpower comes in stock markets wheretrends can last years. The Dax rallybegan in 2005 and Figure 2 shows howit began with a mega trend in the 15minute before moving up to the 30minute. This trend moved up all thesubsequent timeframes and now is aweekly trend in spite of the recent cor-rection (Figure 3). Whilst these dips canseem large, the fact that the trade hadsuch humble beginnings means thatrisks can be wider. For those whowould want to maintain tighter risk,they can use the many methods shownin my book ‘Trading Time’ which look atunique ways of qualifying swing pat-terns.

Shaun Downey is head of researchat CQG.

Figure 3.

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CANDLESTICK SIGNALSTHE J-HOOK PATTERN by Steve Bigalow


Techniques

One of the most powerful can-dlestick patterns is the J-hook.A J-hook pattern is a variation

of a wave 1-2-3 price move and is aneasy pattern to identify with the use ofcandlestick signals. A common chal-lenge for traders is in knowing when tosell after a price has made a strong upmove. For this, the J-hook patterndemonstrates some easily identifiableattributes. First, it starts with a stronguptrend that usually produces strongerthan normal returns in a very shortperiod of time. This strong up move issignificant enough to create the normalwave pattern, a reversal caused by prof-it taking followed by a declining trajec-tory of the pullback, then the continu-ation of the uptrend. The J-hook pat-tern is the description of the pullbackinvolving a rounding out of the pull-back low followed by a move back upforming a hook (Figure 1).

The pattern set-up and criteriaThe first uptrend, which is usually apowerful move, will show clear candle-stick sell signals when the initial up-move comes to an end. The top will beformed with the stochastics (or othertrend indicators) in the overboughtarea. Because of the strong initialuptrend, the first evidence of sell sig-nals should be acknowledged. Even ifit is suspected that the uptrend could beforming a J-hook pattern, why riskremaining in the trade? When a sell sig-nal becomes evident, take your profits.

What criterion makes a candlesticktrader suspect a J-hook pattern will

form? Analysis of the market trends ingeneral will provide that information.For example, if a stock price had astrong run up while the market indexeshad a steady uptrend and did notappear to be ready for a significant pull-back, then a strong stock move couldwarrant some profit taking before thenext move up. The benefit of beingable to identify candlestick signals isbeing prepared for buy signals after afew days of pullback. These signalswould also alter the trajectory of thestochastics that will be pulling back.

Witnessing Doji, Hammers, InvertedHammers or Bullish Harami after a fewdays of a pullback becomes an alertthat the selling is starting to wane. Ifthe stochastics are flattening out duringthat same timeframe then a set-up for aJ-hook pattern is taking place. Takingprofits when the first sell signals occurin the initial uptrend eliminates thedownside risk with the sell signals indi-cating that it is time to get out of thetrade. Even though the strength of theinitial move would warrant suspecting aJ-hook pattern to form, there is noguarantee that the pullback could notretrace 20%, 40%, 60% or even greaterof the initial move up.

If after four days small candlestickbuy signals start forming, there is noth-ing wrong with buying back into theposition. The second entry of thistrade now has some targets that can beclearly defined: the first target shouldbe the test of the recent high. This caninduce taking quick profits and gettingback out of the trade. On the otherhand if strong signals are seen as therecent high is breached, that would be aclear indication the high was not goingto act as a resistance level. A new leg ofthe trend may be in progress.

ExamplesFigure 2 shows that after the uptrend,the J-hook formed when the pricepulled back for a few days. However,the stochastics never reached the over-sold area and they came down only partway before hooking back up. The sig-nals indicated buying before it pulled

back too much showing that buyerswere going to test the high of the pre-vious week. The gap above the recenthigh indicated that the buyers were veryanxious to see prices go higher.Recognizing this pattern and the ele-ments that form it allows traders tomove decisively at the right points of atrend.

Where will the pullback move to?Sometimes that is obvious, sometimesit is not. Yet there are indicators thatcan at least provide a target for a J-hookpullback.

In Figure 3 the 8-day moving averagebecomes the obvious support level.Although the stochastics have notmoved back down to the oversold con-dition, it becomes apparent with theMorning Star pattern that the potentialof a J-hook pattern is starting. Buy sig-nals occurring at a major technical sup-port level, (even though the stochasticsare only part way down toward theoversold area), should be recognizedfor their potential. Buying in the 47.50area should be done with the anticipa-tion that the price could reasonably testthe recent high in the 50 area. Onceagain, the benefit of candlestick signalsis being able to determine whether the50 level will become a resistance levelor not. A break through that area thenbecomes the next evaluation.

J-hook and position taking The benefit of candlestick signals isthat they reveal when a pullback is notoccurring with great enthusiasm.Seeing minor candlestick buy signals afew days after a pullback has occurredat least provides the inkling that thepullback may just be profit taking. Asthe downward trajectory of the pull-back starts flattening out, watch formore buy signals. When the trendstarts moving up, a new position can beestablished.

After a strong rally a profit-takingperiod is to be expected but a full-scalereversal may have occurred. A candle-stick strategy should involve decidingwhether to short heavily the marketor be prepared to re-establish long →→Figure 1.


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positions. Once candlestick buy signalsstart appearing in a market index chart,giving the indication that a J-hook pat-tern could appear, these prepare tradersmentally to move one way or the other.If short positions were established at

the first sell signals in the trend, beingprepared for the covering of thosepositions can be better executed when aJ-hook pattern formation is anticipated.

Individual stock positions have theadditional benefit of the market trend

itself in evaluating the potential J-hookpattern. If during the market uptrend astock price has moved up with greatermagnitude than the market trend ingeneral, then that becomes the firstalert. Simply, the stock trend is verystrong. A pullback occurring in thatstock, when the market trend appearsto be continuing, also gives rise towatching for a J-hook pattern to occur.

Stephen W. Bigalow is the author ofseveral books on candlestick chart-ing and is the principal of thewww.candlestickforum.com, a lead-ing website on candlestick trading.

Figure 2. Garmin Ltd.

Figure 3. Inverness Medical Tech. Inc.

“THE J HOOK IS A ROUNDING OUTOF THE PULLBACKLOW FOLLOWED

BY A MOVE BACK UP

FORMING AHOOK.”

Techniques


PORTFOLIO TESTING by Thomas Dorsey

Preparation in portfolio manage-ment means designing a tradingplan and testing it. Without test

results over a long period of time thattake into consideration all types ofmarkets you've got nothing. You mustevaluate the program in up, down, side-ways, large cap, small cap, mid cap,equal weighted, cap weighted, growth,and value markets. If the market canthrow it at you, you better have testedfor it. Without this work you have a 10high poker hand at a table of cardsharks. It may be the winning hand, butwhat are the odds and how would youknow?

With test results, you've got peace ofmind and proof that you're trading planhas a high probability of working asyou expect. Test results also make itmuch easier to execute your planbecause you aren't racked with doubton each trade - you know it works onenough trades to make up for the badones. A brief period of unfavourableresults does not rattle you becauseyou've got conviction that can't beshaken. You've got the data to backyour trading plan and you have effec-tively taken out the biggest deterrent toprofits in investing; "emotion".

Testing at Dorsey, Wright &AssociatesWe spent a lot of time on portfolio-level testing when developing thePowerShares DWA Technical LeadersIndex (PDP) - an Exchange TradedFund (ETF) that trades on the NewYork Stock Exchange (NYSE) - and theArrow DWA Balanced Fund(DWAFX), an open-end mutual fundthat we developed. We also spent manytireless hours testing our SystematicRelative Strength accounts, which arerun exclusively in accounts that we

manage at Dorsey, Wright, &Associates Money Management.

In the PowerShares DWA TechnicalLeaders Index (PDP) we complete astock to stock comparison to pull outthe strongest stocks. I'll use an exampleof a comparison between Home Depot(HD) and Lowe (LOW) to give you anidea of how we might accomplish this.Here are two companies which are inthe same industry group, but yet haveprovided very different returns toinvestors over the years. Using a Point& Figure relative strength chart, we candiscern when it is best to buy HomeDepot (HD) and when it is best to buy

Lowes. To create this relative strengthchart, the price of one stock is dividedinto that of another, then multiplied by100 and the resulting value is plotted ona Point & Figure chart (see Figure 1). Itis really only once it is plotted on thePoint & Figure chart that these readingscome to life and provide us with mean-ingful guidance. In this example we willuse HD as the numerator, and LOW asthe denominator. When the chart is ona buy signal we would expect thenumerator (HD in this case) to outper-form. When the chart is on a sell signal,we would expect the denominator tooutperform (LOW in this case). At

Figure 1.

Techniques for evaluating the robustness of a stock portfolio.

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the bottom of the chart historic signaldates are listed so that you can easilyuse the performance function to seehow effective those signals have been.In the case of HD versus LOW, fromJuly 16th 1996 to October 12th 2000,HD was clearly the place to be as it wasup 217%, versus 149% for LOW. SinceOctober 2000 however, HD has been asubstantial laggard, returning only14.37% while LOW is up an astounding235%.

An investor who has been in one ofthese stores has likely been in the other,and despite encountering differentcolor schemes the results of each visitwere probably very similar. You walk inlooking for a box of nails and you walkout with a $400 nail-gun and a truck fullof lumber. In this sense we are all thesame, but in investing things are not allthe same. Using the powerful Point &Figure relative strength tool, we canclearly show when the tide turned infavor of an investment in LOW at theexpense of HD shares. This compari-son is multiplied thousands of timesover to achieve a final index of 100stocks that comprises the PowerSharesDWA Technical Leaders Index (PDP).We begin our process with a universesimilar to that of the Russell 3000Index components, and finish ourprocess with a portfolio of 100 stocksthat we know provide us with goododds of outperforming the broadermarket.

Fund of fundsIn the Arrow / DWA Balanced Fund(DWAFX) we take a similar approachutilizing relative strength comparisons,however this fund is unique in that itwas the first "fund of funds" construct-ed exclusively with ETFs. As this is atrue Global Balanced fund there areessentially four pieces that make up thefund; US market based and sectorETFs, Fixed Income ETFs, AlternativeAsset ETFs, and international (Non-U.S.) ETFs. The first step in managingthis fund is a relative strength compari-son process that allows us to determinethe size of each "slice," and thus

whether we overweight alternativeassets (commodities, currencies, REITs,etc.), or International equities. Forinstance, we can perform a relativestrength comparison of bonds to USequities to determine which has theupper hand. This type of comparisonwould have had you overweight bondsin the portfolio during several criticaljunctures over the past seven years, butlargely underweight outside of thosestretches. Bonds would have beenoverweighted in the portfolio fromApril 2000 to April 2001 and then againfrom July 2001 to November 2001. Therelative strength chart would haveswitched once again to suggest an over-weighting in bonds in April 2002 to July2002, when the iShares LehmanAggregate Bond Index (AGG) was up2.45% while the S&P 500 Index (SPX)was down 16.5%. Perhaps moreimportantly, however, is that sinceMarch 2003 this relative strength com-parison has had the portfolio moveaway from bonds (within the confinesof a minimum weighting of 25% inbonds because this it is a "BalancedFund"), and into overweighted expo-sure within equities. Since March 2003,bonds have been essentially flat whilethe SPX is up 70%.

Relative strengthIn the second step, we focus on relativestrength analysis within each slice, soonce we've determined that a largerequity slice is recommended, the ques-tion becomes how to gain that equityexposure. We take this step with thecomfort of knowing that we have doneour homework. Extensive testing usingcomparisons such as that between HDand LOW as well as that of comparingmajor asset classes to one another, overa long period of time was vital becausewe discovered a lot of things we didn'texpect to find, namely:

The best portfolio performancecomes from buying the highest rela-tive strength (RS) stocks. Thosestocks can be volatile, but the datashows that is where the best returns

are.A portfolio of high RS stocks hassmaller drawdowns than the market.We thought that because high RSstocks are volatile then drawdownsmight be higher, but the data showsthey are not.A portfolio of high RS stocks has alow R-squared. Most fund portfolioshave an R-Squared around 0.9. Wedidn't expect to find R-squares below0.6!A portfolio of high RS stocks has abeta that is less than the market.Because of the volatility, we thoughtthe beta might be high but it turnsout that because the portfolio canoften move opposite to the market,the beta is under 1.0.The long-term alpha on a portfolio ofhigh RS stocks is surprisingly high.The data shows that very high alphascan be generated because out-per-formance is so large and the beta is somoderate.Tax efficiency is good. We figuredthat cutting losses and letting winnersrun would be fairly efficient, but wewere still surprised when data proved85% of profits were categorized aslong-term capital gains and thus qual-ified for preferential tax treatment.Turnover is very manageable. Wethought a high RS portfolio mightgenerate a lot of transactions, but thedata shows turnover is not much dif-ferent than the average equity mutualfund.

It's only because of the data generatedby extensive testing that we discoveredthese things. An old basketball coachonce told me, "Somewhere some kid ispracticing his shot. If you're not prac-ticing, when you go head-to-head he'sgoing to beat you." The market is nodifferent. If you're making excuses fornot doing the testing, you're looking forthe easy way to win and there is noshort cut.

Thomas J. Dorsey is president ofDorsey, Wright & Associates,www.dorseywright.com.

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Interview

TA: You are a key figure in the movement referred to inthe financial markets as 'the rise of the geeks'. Do youthink traders and fund managers need to be cleverer orbetter educated now than say 10 or 20 years ago, or doesthe same kind of person still succeed regardless?

AB: The technical bar has certainly been raised. Twenty-fiveyears ago if you could sum a geometric series and use aspreadsheet, you were a rocket scientist. Today kids come outof school and apply for entry-level jobs with far more math-ematical and technical education.

Still, the determinants of success have not changed somuch. Cleverness is more important than I.Q.; the personwho is good at solving math problems, and enjoys them, willdo better than the person who can prove deep theorems.Confidence, ambition, focus, pride, people skills and honestyare still the main ingredients. Stochastic calculus is a niceextra.

TA: Is the efficient markets hypothesis now discredited?

AB: A hypothesis is something you assume for the sake ofthe argument, to see where it leads. If you don't assume effi-cient markets, you can explain any price. "He bought it forthat price because he thought it was worth more, she sold itfor that price because she thought it was worth less." If youcan explain everything, you explain nothing.

When academics started assuming efficient markets fiftyyears ago, they had no idea how close to true the assumptionwould be. Everyone was shocked at how efficient markets

Aaron BrownAaron Brown is an executive director at MorganStanley, where he works in risk methodology, model-ling the distribution of trading P&L at the firm-widelevel. He is highly regarded as a quant, trader, aca-demic and serious poker play, and holds degrees inapplied mathematics from Harvard and finance fromthe University of Chicago. His career in the financialmarkets spans over 20 years and includes positionswith Prudential Insurance, JPMorgan, Rabobank,Citigroup and now Morgan Stanley.

In his book "The Poker Face of Wall Street", AaronBrown explores the historical and conceptual linksbetween gambling and modern finance, and explainswhy success in both depends on the art of taking"incalculable risks."

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are: how few professionals made consistent money, how hardit was to predict future price movements. What started out asa simplifying assumption, like ignoring air resistance, turnedout to be almost true.

Yes, some persistent anomalies have turned up. But no oneever found an anomaly without starting from the efficientmarket hypothesis. Without it, there are no anomalies, every-thing is consistent with theory.

The efficient markets hypothesis was always meant to bethe beginning of inquiry, not the end. It has not been dis-credited for that purpose; in fact, no one has come up with acredible alternative. The only surprise is that by starting withefficient markets, you were ahead of 99% of the profession-als who had studied finance for years.

TA: What do you think about the research coming frombehavioural finance? Have you found ways to quantifyany behavioural biases into profitable trading strate-gies?

AB: I think there is a lot of interesting work being done bysome behavioural finance researchers, but also a lot of non-sense. I am not personally interested in why people do thingsor in finding predictable "biases" or irrationalities.

When someone does something with a predictable result,I'm willing to assume they want that result. So I regardbehavioural anomalies as evidence that people want some-thing different from classical economic assumption ratherthan that people are bad at making decisions. I think behav-ioural results are a challenge to utility theory, not to financialtheory.

With regards to trading, my trading is heavily quantitative.I consider the behaviour of market participants, but as insti-tutional entities rather than psychological beings. For exam-ple, I think about how much demand there will be for a cer-tain stock at various times and prices in order to coveroptions positions, but I don't worry about what the holdersof those option positions are thinking.

In poker, I definitely think about what other players arethinking.

TA: Do you think a trader has to be able to take "incal-culable risks" to succeed?

AB: I think taking incalculable risks is the essence of realtrading. Certainly you can call yourself a "trader" and make aliving as an order-taker or by taking spreads; this has no moreincalculable risk than many other jobs. But if you wait for

every risk of a strategy to be calculated, it will have beencompeted away long before you get in the game.

TA: Can you provide an example of a trade/investmentwhereby you exploited or entered into 'incalculablerisk'?

AB: Well, you almost always enter into incalculable risk.Certainly when you trade something for the first time, there'salways the risk that you failed to understand some essential ofthe market. When you throw the switch on a program trad-ing system, you're never 100% sure it won't generate disas-trous nonsense trades. When you hire someone, or start abusiness or quit a job; there are aspects you cannot calculate.And, in a sense, when you enter into incalculable risk you'reexploiting it, because it keeps a lot of the competition away.

One example of pure exploitation of incalculable risk wasmy company eRaider.com. I started it in 1998. We were apublic mutual fund (Allied Owners Action Fund Inc.) thatbought 5% stakes in public companies, then used the website(eRaider.com) to organize all company shareholders to forcepositive change. I think in normal times we never would havegot approvals to open the fund; it posed issues to dozens ofsecurities regulations. If we did get it open, it would havebeen buried with the techniques companies use for other dis-sident shareholders.

But in those days, no one knew how the Internet wouldaffect financial regulation and equity trading, anything waspossible. eRaider.com could be part of the problem or itcould be part of the solution. We got meetings with the SECcommissioners, we announced our targets live on CNNfnfrom the floor of the New York Stock Exchange, we gotinstant media and company attention despite being a tinyfund with a nutty idea. We were influential in the Council ofInstitutional Investors, the Financial Accounting StandardsBoard, the National Association of Securities Dealers andthe New York Stock Exchange. When the future seems high-ly uncertain, anyone willing to stake a bold claim gets atten-tion.

TA: You say in your book that passive poker - most oftenseen when players tend to 'call' rather than 'raise' or'fold' - is not a winning strategy. Is passive investingsimilarly a bad idea?

AB: There are lots of passive players in the market.Obviously you have the index funds, but lots of funds thatclaim to be actively-managed are really taking what the mar-ket gives them. Many participants want to execute at volume-weighted average price rather than take a chance on trading.The difference between poker and the markets is there is nopoint to passive poker, but passive investing and passive cap-ital raising works pretty well.

TA: What kinds of trading strategies do you favour?

“IF YOU WAIT FOR EVERY RISK OF ASTRATEGY TO BE CALCULATED, IT WILL

HAVE BEEN COMPETED AWAY LONGBEFORE YOU GET IN THE GAME.”

Interview

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AB: I'm a quant. I look for patterns in historical data that Ican exploit. I don't think I have better information than otherpeople or faster execution, I think I'm smarter about how toprocess the information. I like to remove as much noise aspossible, so I tend to implement things in a market neutralway, and diversify enough to make it a risk-arbitrageapproach. I also like to be liquidity neutral, I've never likedpure momentum or pure convergence trading; I don't likecarry trades.

TA: If you were to set-up a new fund, what market(s)would you focus on and what strategies would youemploy?

AB: I think the revolution started bycredit derivatives has a long way to runyet, and there will be major opportuni-ties in that area. One idea I toyed with isto start a credit-crunch binary payofffund: the fund will be invested to stayflat until the next major credit crunch,then generate exceptional returns. Ithink the fund-of-funds business hasbeen unimaginative; there is a lot ofroom for new ideas there.

TA: Does any market offer betterarbitrage / price anomaly opportuni-ties than others?

AB: Not really. With efficient marketslike major currency FX and major equi-ties you can trade faster and better-matched, so you can generate your ownopportunities. With less efficient markets, the opportunitiesare there naturally. Traders always push markets to the pointwhere there are opportunities.

TA: Is high frequency trading seriously reducing arbi-trage opportunities?

AB: No, high frequency trading is eroding slightly less highfrequency trading opportunities. It should make long-termarbitrage and risk arbitrage opportunities better.

TA: Do you use technical analysis?

AB: I do not use standard technical tools, but I do believethat understanding how short-term supply and demand, andpotential supply and demand, work through the markets isessential for trading.

Thinking through the technicals also makes executionpleasant. In a well-crafted strategy, you find the market com-ing to you. You get good execution for what you want to doand if you miss your execution, the market will come back.

In a badly-crafted strategy, you can't get your execution andmissing it is fatal. I have never tried to make money with puretechnical analysis, but I think ignoring the technical factors iscourting disaster.

TA: Do old adages like "let your profits run and cut yourlosses short" still have any bearing on trading success?

AB: There are good strategies that involve all four permuta-tions of fast or slow profits and fast or slow losses. The keyis to have a strategy; the best way to lose money is to makeeach decision as it comes up.

Still, most people have biases to takeprofits fast and losses never. So theadage is good advice relative to instincts.

TA: What principles do you employwith regard to risk management?

AB: Once again, I'm a quant. I think youcan calculate these things. I design strate-gies very carefully to have precise returndistributions. I don't have much faith indiversification beyond seven or eight. Ihave no faith in big covariance matrices.So I look for four or five factors withlow dependence and build on them.

TA: To what extent do you think therise of automated trading and algo-rithmic execution strategies affecttechnical analysis? E.g. will chartpatterns fail more often?

AB: In theory, automated trading should drive patterns outof the market. In practice, it seems more like the opposite. Soit's still an open question.

TA: Looking ahead, in your book, you say "while ourfinancial models have become very good at pricingsecurities, they require assumptions that clearly conflictwith how security prices actually move….and when [theconflict] is solved it will reveal hidden worlds of oppor-tunity". Do you see signs of this issue being addressedand from which area of finance and/or field of study isprogress being made?

AB: No, I don't see any progress. Times are too good; peo-ple are making too much money. It will take a disaster beforepeople take this seriously again.

Aaron Brown's "The Poker Face of Wall Street" is pub-lished by John Wiley & Sons Inc. and will be available inpaperback this August.

Interview


Software

ALGORITHM BACKTESTING

Background: Why AlgorithmicTrading Needs BacktestingAlgorithmic trading is one of the mostdiscussed topics in capital markets.Initially the term was used to describethe automation of equity execution, i.e.dividing large block trades into slices,using some statistical measure, in orderto minimise market impact and achievea benchmarked price.

However, in the last few years the def-inition has expanded to include high-frequency trading, i.e. analysing marketdata in real-time against statistical mod-els in order to detect trading opportuni-ties - and then executing those oppor-tunities. An example of a high frequen-cy algorithm is pairs trading, whichmonitors correlated instrument pairs,looking for aberrations in the correlat-ed relationship that imply the ability tobuy one and sell the other at a profitbefore they return to correlation.

Algorithmic trading has also spreadinto asset classes beyond equities, suchas futures and options, fixed incomeand foreign exchange. In each assetclass, the same basic principles of mon-itoring market data for trading oppor-tunities and then automatically execut-ing on the opportunities still apply.However, each asset class differs in the

specific algorithms that are appropriate.As algorithmic trading has developed,

several imperatives have emerged. Thefirst is that you have to identify oppor-tunities first - before your competitors -and build your own custom algorithmsto capitalize on opportunities. In manycircumstances, you can't rely on pre-built algorithms purchased or leasedfrom vendors or brokers because ifeveryone has access to the same algo-rithms, there is a reduced competitiveadvantage. The second imperative is togain first-mover advantage by buildingand deploying algorithms quickly,ahead of the competition. Only thosethat can quickly deploy are likely to har-vest the benefits.

The markets are continually changingand an algorithm that was highly prof-itable yesterday may not be profitabletoday. So the third imperative is to con-tinually evaluate the effectiveness ofexisting algorithms and, if necessary,evolve or decommission them.

Algorithmic trading is both fast mov-ing and highly automated and, as aresult, is often associated withincreased risk. Many people fear thatshould things go wrong, they will gowrong so quickly that traders will beunaware and unable to intervene in

time to prevent damage. This leads toconcern that the damage may not beconstrained and that certain circum-stances may cause the entire market tospiral out of control. It is therefore ofparamount importance to ensure thatan algorithm has been tested under awide variety of circumstances and in asmany trading situations as possible tomitigate such risks.

Backtesting techniques provide a wayof evaluating and tuning algorithms forprofitability and testing algorithmsunder various circumstances to ensurethey perform as expected in exception-al, as well as normal, trading conditions.

Backtesting Principles,Requirements and IssuesBacktesting uses historical datasequences in order to simulate how analgorithm would have performed if itwas trading at a particular point in time.The theory is that by testing it undernormal and extreme conditions, per-formance can be ascertained and sensi-ble responses to exceptional circum-stances assured.

The most extreme example would beto test an algorithm with data fromboth a bull market year and a bear mar-ket year. Another example might be

The term 'backtesting' has been created to describe the process of using past mar-ket data as a tool to ascertain how a prospective trading strategy would performunder various circumstances, before that strategy is deployed live in the market.Backtesting algorithms can help to ensure that financial institutions are prepared,as there are a number of requirements, challenges and approaches that should becarefully considered.

by Dr John Bates


Software

testing a forex algorithm with datafrom every non-farm payroll day in2007. The sequences of data selectedmay be hours, days, weeks, months oryears, depending on the requirementsof the particular algorithm and back-testing scenario.

Identifying and BacktestingTrading PatternsIn order to create a new algorithm, his-torical data will most likely be used toresearch and identify the patterns thatan algorithm can use to make money.For example, if a strategist using histor-ical research identifies a particular pat-tern (e.g. when the moving average ofinstrument X exceeds the price bythreshold Y, the price will always rise byZ), an algorithm can be created to cap-italise upon this opportunity.

Historical data, in which the patternwas originally spotted, can then be usedto backtest and evaluate whether theprospective algorithm would identify allrelevant opportunities and take advan-tage of them.

Acquiring and Managing Yearsof DataIn order to backtest algorithms, a storeof relevant historic data must be kept.In equities, for example, this couldmean tick and quote data, with fulldepth of book, going back ten years.Where an institution is trading acrossborders, there may be a requirement tostore data from exchanges in the US,UK, Canada, Mexico and Japan.Depending on the detail of data that isstored, there could be several thousandmarket events per second on an indi-vidual exchange - equating to millionsper day, and even billions per year. Indata storage terms this equates to sev-eral terabytes per year.

This data has to be captured, stored,indexed and queried to support effi-cient backtesting. One way of acquiringthe data is to buy it from trading venuesor data vendors. However, such data isoften delivered on CDs after-the-fact.In-house data capture is required to testwith today's and yesterday's data.Market data has a temporal dimension

in which the sequence of data is mate-rial to understanding what happened.This temporal dimension must bestored and indexed as a first class prop-erty, so it can be replayed in order.

High Performance BacktestingDealing with data volume is not theonly issue in backtesting. In the questfor ever-faster deployment of newalgorithms, there is a strong desire tobacktest algorithms quickly. Traditionaldatabases are not fast enough to cap-ture or replay - in real-time - the vol-ume of events needed to support trad-ing usage and are not designed to han-dle time-series (temporally ordered)data.

A new breed of tick database hasevolved to fulfil these requirements.These databases support the temporalordering of events and can replay mar-ket data in the same order as the eventsoriginally happened. Such databasescan also handle storage and replay ofthousands of events a second. In a highperformance backtesting framework, itmay be possible to run many thousandsof algorithmic permutations againsthistoric sequences at the same time.This enables thousands of possibilitiesto be evaluated concurrently and huge-ly accelerates time-to-market for algo-rithms.

Backtesting Multiple AssetClassesAlgorithms for other asset classes mayintroduce additional requirements tothe backtesting operation. For example,foreign exchange traders may want tobacktest using data from multiple trad-ing venues e.g. EBS, Reuters, Currenex,Hotspot and a bank's own liquiditypools. In futures and options it mightbe CBOT, CME, Eurex and Liffe, whilein fixed income it might be Brokertecand eSpeed.

In addition, some algorithms arecross-asset in nature, trading multipleasset classes in the same strategy. As aresult, multiple asset-class streams mustbe replayed in order to backtest and itmay be necessary to replay a sequencecomposed of several independent →→

Figure 1. Synchronised data capture in the production and test environments: In the pro-duction environment data is sent and received via adapters to various market data feedsand trading venues. This data enters the trading engine and also the tick database forstorage. In the testing environment the engine is fed with historic sequences from thetick database and sends trades to a market simulator.

Sample Backtesting Configuration


Software

asset-class specific sequences, retainingthe temporal ordering and relationshipof the different market streams.

Backtesting with NewsA new backtesting requirement that hasemerged over the last year is the needto support algorithms that trade onnews. Certain news moves the market,particularly when it is economic newsor shock news (e.g. an unexpected waror hurricane). Traders realise that ifthey can respond before their competi-tors they can gain an advantage and areusing algorithms to monitor newsalong with other market data.

As an example, Dow Jones has madethis process more quantitative by creat-ing elementized news feeds, which usetags to identify specific elements withinnews events. In order to backtest algo-rithms that incorporate news, newsfeed events have to either be recordedor simulated. Since elementized newsfeeds are a new phenomenon, it has notbeen possible to acquire years of ele-mentized news, but as algorithms thattrade on news become more common-place more archives of unstructuredand elementized news will becomeavailable for backtesting.

Simulating Market ImpactThe most complex requirement in abacktesting framework is the challengeof simulating market impact. Replayinghistorical data and feeding it into analgorithm is one thing. But what aboutsimulating the circumstance where analgorithm wants to take advantage ofopportunities in the market? Wheredoes it place its orders? In a compre-hensive backtesting framework a mar-ket simulator is required. Algorithmscan route orders to the market simula-tor, which will respond as an externalmarket would (such as an equitiesexchange, futures exchange, forexvenue or bond venue).

The complexity of simulating marketimpact begins when you consider thatwhen backtesting with data from thepast, your algorithm wasn't actuallythere, and thus its actions will not havean impact on the historical data. If youhit a bid in the historic data, by defaultthat bid will still be there. This issue cannever be fully addressed without creat-ing a time machine that could go backto the day in question and run the algo-rithm live. However, there are certaintechniques that enable more realisticimpact simulation. One such techniqueis to use a simulator that can remember

deltas. Deltas describe cumulativechanges to the historic data. For exam-ple, if our algorithm hits a bid or offer,although in the past it was still there,the simulator should remove it fromthe order book and remember this as adelta to be applied henceforth to histo-ry.

In other circumstances, traders maywant to simplify things and assume per-fect liquidity in order to test certainrules in an algorithm. Alternatively, theymay want to use a totally simulatedworld that uses synthetic market datarather than historic market data.

Strategy TuningA key aspect to backtesting is strategytuning; running strategies in variousdifferent configurations, with the samedata, to see which permutation is themost profitable. Data on each algorith-mic permutation can be collected andcompared with the most profitableconfiguration to be used for live trad-ing. The effectiveness of a particularpermutation may change over time andthus regular tuning is required to ensurethe algorithm is being run in its optimalconfiguration.

ConclusionTo better ensure that algorithms areready for any eventuality and will actu-ally work as expected requires high per-formance time-series capture andreplay, large data storage, realistic mar-ket simulation and continuous algo-rithm tuning. The latest backtestingapproaches, including high perform-ance tick databases for capture andreplay of time-series data can helpensure there are no surprises. Thosethat use backtesting appropriately willbe well prepared to earn their 'BoyScout' algorithmic trading badge.

John Bates is Founder and VicePresident, Apama Products,Progress Software

Figure 2. Backtesting Control Panels: On the left screen a historical sequence and a strat-egy to stream it through has been selected for backtesting. On the right screen a wizardguides the user through control options including speed of playback, pause and stepcontrols.

Sample Backtesting Interface

Published by Oasis Research Ltd246 pages ISBN: 0955466806£60

Trading Time is available to orderfrom www.trading-time.com

Shaun Downey is well known on City trading floors as a technical analyst atCQG and for writing regular FX research for electronic brokers EBS. Hislong awaited first book, "Trading Time" brings together his own technical

trading ideas using CQG indicators, many of which he has developed himself.As Downey makes clear in the preface, the book is really about how best to time

your entry and exit and ensure that you trade in the 'correct' time frame. Whilstthere is more of a focus on day trading, he also emphasises the importance oflooking at longer term charts as an essential guide to getting the big picture.

The first chapter covers the author's introduction on trading time and highlightsthe importance of using indicators correctly depending on the time period beingtraded. For example, the traditional moving average treats each time period equallydespite some periods having much greater activity than others. This problem canbe cured by using a Volatility Time Average which adjusts to allow for changingrange and volatility over time. Downey has also created Volatility Time Bands,which like Bollinger Bands, place standard deviations around the average andwhich provide a better picture of market expectation and risk.

An entire chapter is also devoted to Market Profile, an indicator that emergedfrom the trading pits at the CBOT that combines price and volume data andremains an extremely effective but underutilised technique.

As the book repeatedly highlights, volume remains a neglected source of marketinformation for the trader. Afternoon trading volume is often a pre-curser to priceaction the following morning, so for short-term traders Market Profile has a lot tooffer; but it can also be used for longer time periods. Downey provides many prac-tical ideas for using Market Profile effectively because, like many TA techniques,Market Profile is often misused. He corrects many misconceptions regarding antic-ipating support and resistance levels, interpreting economic data releases and iden-tifying short-term trends.

Throughout the book Downey also makes the point about how market activityvaries throughout the day for different asset classes and how prices react different-ly to economic data releases. For example, bond prices are especially volatile ondays when inflation figures are released. Volatility Time Bands are therefore espe-cially useful in capturing intra-day trend reversals. Downey also draws attention tothe proliferation of trading arcades and their impact on volume data. Because veryfew arcades allow positions to be held overnight, greater attention should beplaced on late afternoon and early morning activity with regards to timing marketentries and exits.

The book contains countless examples (CQG screenshots) that are well annotat-ed in explaining the various techniques. However, this does mean the book is reallybest suited to CQG users as many of the indicators included are only available onthat platform. However, for traders using different systems, the various techniquesshould be programmable (with the exception of Bloomberg).

Trading Time is a unique publication within the realm of technical analysis.Many new books on TA are at once too simplistic and theoretical for the user toapply its ideas effectively in day to day trading but this is a practical trading bookwritten by someone with a proper understanding of the global markets.Recommended.

TRADING TIME


Books

New Methods in Technical Analysis

Research Update

Driven to Distraction

When a stock moves into the S&P 500index, demand from index fund man-agers will likely force the stock price torocket up, but how long are the effects ofthe inclusion felt and for how long doprofitable opportunities exist?

Researchers from the University ofReading have examined the impact of acompositional change in the S&P 500index on the stocks newly included in theindex. Perhaps not surprisingly, theyfound evidence of a significant overnightprice change that diminishes the profitsavailable to speculators. They point out,however, that there is still profit availablefrom the first day after announcement

until a few days after the actual event.They also find evidence of consistenttrading patterns during trading hoursover the inclusion event.

Kappou, Konstantina, Brooks, Chris and Ward, Charles W.R., "The S&P 500 Index Effectin Continuous Time: Evidence from Overnight,Intraday and Tick-By-Tick Stock PricePerformance" (May 2007).

All papers are available from the Social Science ResearchNetwork, SSRN, www.ssrn.com

Trading Changes to the S&P Index

YIELD CURVE REACTIONS TO ECONOMIC NEWS

Psychological evidence indicates that it ishard to process multiple stimuli and per-form multiple tasks at the same time.Three US-based researchers have testedthe investor distraction hypothesis, whichholds that the arrival of extraneous newscauses trading and market prices to reactsluggishly to relevant news about a firm.Their test focuses on the competition forinvestor attention between a firm's earn-ings announcements and the earningsannouncements of other firms. Theauthors find that the immediate stockprice and volume reaction to a firm'searnings surprise is weaker, and post-earnings announcement drift is stronger,when a greater number of earnings

announcements by other firms are madeon the same day. Distracting news has astronger effect on firms that receive pos-itive than negative earnings surprises.Industry-unrelated news has a strongerdistracting effect than related news. Assuch, a trading strategy that exploits post-earnings announcement drift is unprof-itable for announcements made on dayswith little competing news.

Hirshleifer, David A., Lim, Sonya S. andTeoh, Siew Hong, "Driven to Distraction:Extraneous Events and Underreaction toEarnings News" (April 16, 2007).

How do US interest rates react to macro-economic announcements? Two Frenchresearchers have investigated the shapeof the term structure reaction of swaprates to announcements. The results yieldseveral stylized facts about the bondmarket, including the observation of atleast four types of patterns in the termstructure reaction. The first type seemsto be the better known hump-shape andis likely driven my monetary policy; a sec-ond type affects mainly the short termrate positively; a third type affects nega-

tively maturities between 2 and 7 years;and a fourth one negatively affects matu-rities between 6 and 9 years. They alsofound that the existence of some outliersin the one-day changes in interest ratesusually leads to a strong underestimationof the reaction of interest rates toannouncements.

Guegan, Dominique and Ielpo, Florian,"Further Evidence on the Impact of EconomicNews on Interest Rates" (June 1, 2007).

POOR REWARDS FOR EXTRA RISKEquity investors are overpaying for riskystocks. This is the conclusion of DavidBlitz of Robeco Asset Management andPim van Vliet of Erasmus UniversityRotterdam, who have found further evi-dence that stocks with low volatility earnhigher risk-adjusted returns than highvolatility stocks. In order to exploit thevolatility effect in practice the authorsargue that investors should include lowrisk stocks as a separate asset class in thestrategic asset allocation phase of theirinvestment process.Blitz, David and van Vliet, Pim, "TheVolatility Effect: Lower Risk without LowerReturn" (April 2007).

CONFIDENT FORECASTINGJust how good are you at predictingtrends? Three researchers from theUniversity of Mannheim have testedthe trend recognition and forecastingability of two groups: i) financial pro-fessionals who work in the tradingroom of a large bank and ii) novices(i.e. students), based on the probabilitythey attached to a trend and the confi-dence they had in their own forecasts.They found evidence of simultaneousoverconfidence and underconfidence.Subjects tended to underestimate themathematically correct probability(indicating underconfidence?), butassumed confidence levels that weretoo narrow or, in other words, underes-timated the variance. They found noevidence to suggest professionals wereless prone to these biases than novices.

Glaser, Markus, Langer, Thomas and Weber,Martin, "On the Trend Recognition andForecasting Ability of Professional Traders"(June 12, 2007).


CONTENTS:PAGE 41PROGRAMMING ANDINTEROPERABILITY

PAGE 44STRATEGY SPOTLIGHT



PROGRAMMING AND INTEROPERABILITY

TA: Why is Visual C++.NET yourlanguage of choice in your book onbuilding automated trading sys-tems?

BVV: There are all kinds of trade offswhen it comes to technologies and pro-gramming languages. The UNIX sys-tem is widely considered to be the bestplatform for implementing automatedsystems. However, it's extremely expen-sive and it takes a long time to develop.The great thing about Microsoft is thatyou can literally develop a system in anafternoon on Microsoft Visual.NET asopposed to building it from the groundup. Visual C++.NET in particular is avery fast programming execution envi-ronment and you can take advantage ofthe MS tools that you need for develop-ment, so it's an excellent way to go.

Programming language and operating

system, however, are not the only deci-sions to be made, and may be not eventhe most important ones. You have toconsider many other aspects of tech-nology, including network architecture,who is your ISP, do you have a directconnection to the exchange, how farwill your server be from that exchangeand so on. If you have a trading systemwhere every microsecond is of theessence and the success of the systemdepends on speed of execution thenyou'll be much more interested inspending hundreds of thousands oreven millions of dollars in creating thefastest infrastructure you possibly can.Whereas if you're going to hold on toyour position for 30/40 minutes or 3 or4 days, then every micro second isn't asimportant and maybe what you're moreconcerned with is speed of develop-ment so you can get something up-and-

running in a couple of weeks instead ofa couple of months.

TA: Sticking to language for amoment, as this might be viewed bymany as a barrier to automation,would you advise those starting outin automated trading to learnExcel/VBA first?

BVV: There are a lot of traders whouse Excel and VBA. We're trying tomove away from Excel based systemsto be able to do more robust calcula-tions in a more robust client serverapplication environment. C++ is bestfor interoperability with other hardwaresystems but it would be difficult tomove directly to any of the C++ or C#languages without any programmingexperience in VBA or VB.NET. Iwould therefore probably recom-

Benjamin Van Vliet consults extensively onbuilding automated trading systems with profes-sional fund managers and traders and is theauthor of "Building Automated TradingSystems" (Academic Press, 2007).

He is the associate director of the MSc inFinancial Markets at the Illinois Institute ofTechnology's Stuart Graduate School ofBusiness, and is responsible for their courses oncomputer programming for automated trading.Van Vliet is also vice chairman of the Institutefor Market Technology, where he sits on theadvisory board for their Certified TradingSystem Developer (CTSD) program.

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mend learning SQL databases andstarting out in VB.NET. There areenough similarities to VBA that youwill be able to understand Excel/VBA,but it will also allow you to deal moreefficiently with time series data thanExcel/VBA, which is an important partof any automated trading system.

TA: Would you recommend that atrader or fund manager hires a pro-grammer or financial engineer toprogram their strategy, or is it some-thing they can learn to do them-selves?

BVV: Learning to program is not easyand it can take years to become profi-cient in it. Very often a trader or firmwill try and gain enough understandingto a level where they can speak the lan-guage and understand the technologicalissues involved, but then partner with aprogrammer who can take their ideasand implement them in a programminglanguage. One of the points of theCertified Trading System Developerprogram is to say if you're going to beinvolved in a project to build an auto-mated trading system, you need tounderstand enough about technologyand the language of programmers sothat you can communicate effectively.Each of the three functional areas -trading, technology, maths/quants - hastheir own language and skill set, and inorder to work well together we have tolearn enough about the other two func-tional areas to make the process work.

TA: In what circumstances wouldyou recommend using off-the-shelfsystems like those available fromPatsystems, TradeStation orTrading Technologies?

BVV: Really the only proprietary thingabout an automated trading system isthe trade selection and position man-agement logic. All of the other process-es could be substituted with commer-cial off-the-shelf software. For exam-ple, I can connect to the exchangemyself but that's very time consumingand very expensive. However, I can

probably license third party softwarelike Trading Technologies and I can runthe execution through their API. Thereare many other external pieces (such asquant libraries, accounting systems etc)that I may or may not be building in-house or licensing as third party soft-ware. Nevertheless, if I'm going toautomate my trading process my tradeselection package then becomes a kindof middleware where I'm connecting toa real-time data feed, I'm sendingorders down an API, and I'm pulling inhistorical data from another source. Soit becomes a big problem of getting allof these various packages and tech-nologies to work together, especiallyfor smaller firms who don't have theresources to spend millions of dollarsand years developing entire platformsfrom the ground up. One of the sim-plest solutions is to licence from a com-pany like TT.

As I see it, there's always an evolution.Let's just say I'm a private trader whowants to build an automated tradingsystem. Well, given the constraints oftime and expertise I can license muchof the technology, maybe TradeStation,and start doing it in my basement andhooking up TradeStation using theirEasyLanguage. An institutional traderis probably not going to be usingTradeStation execution. They may beusing it for charting, but they're proba-bly not using EasyLanguage. But never-theless, it's a good way to start. Andlet's just say you start developing sys-tems that make money. The next step isto probably move up to a more profes-sionally-focused execution package, likea Trading Technologies. Maybe thenyou read a book like mine which actual-ly describes what they call the X_TraderAPI for real-time data feeds and execu-tion, and you start programming your

own trade selection algorithm and youstart learning about the kinds of issuesthat are in my book, like multithread-ing, interoperability etc. Let's say youstart to hire people - programmers,mathematicians, more traders - andyour firm is growing. At some pointdown the road, you may even thenchoose to leave TT behind and start todevelop all of that software in-housebecause as a more mature firm you real-ly prefer to have the control to optimiseyour technology and customise it foryour own trading decisions. Any pieceof software that tries to be everythingto all its customers is not going to be asfast as possible doing the one thing youwant it to do. So the larger firms get,the more they develop their own sys-tems in-house.

TA: In your book you talk about theKV methodology for discoveringnew trading systems. What is thisand why is it important?

BVV: Discovering trading opportuni-ties and implementing them as quicklyas possible is going to be an importantissue for small hedge funds and largerinstitutions going forward. Let's sayCompany A buys out Company B.Between the time the offer is made andthe deal is consummated there is goingto be a relationship between the twostocks. That relationship may hold foronly a couple of months but if you canget your system up and running fastthen you're going to have much moreopportunity to take advantage of thatstat arb situation than someone whotakes a long time to set up. It's a shortterm opportunity and the quicker youcan jump on it the better.

One of the things we've tried todesign is a methodology that works

“IN THE GAMES WHERE PROBABILITY OF SUCCESS IS GREATEST BUT TECHNOLOGICAL

ADVANTAGE IS THE KEY, THE SMALLER PLAYERIS GOING TO BE PUSHED OUT.”


with everything from HFT systems toregular value based mutual funds. Butreally, the point of our methodology isto say that given opportunities comeand go, the speed with which one canmanage a team a developers to getsomething up and running is veryimportant and it pays to plan aheadusing a standardised process, ratherthan developing things ad hoc withprogrammers, mathematicians, andtraders reacting to all manner of inputsand discoveries. In other words, howcan we sift through thousands of ideasquickly and find the 10 or 12 good onesthat show the most promise, and spendour limited resources on developingthose, so that when we do find a goodidea we can put it in the pipeline andeverybody knows what's supposed tohappen when. Business practices arebecoming a much bigger determinantof success.

Realising when a system no longerworks is an equally important part ofthe equation. It's important to recog-nise that every strategy has a limitedshelf life. Even value and growth basedtrades tend to run in five to ten yearcycles but still nevertheless eventuallygo out of favour. The big thing is tooptimise your business processes tolook for as many opportunities as pos-sible so when the window opens youcan pounce on it but at the other end torecognise when the window is closed.

TA: Do you find that a lot of tradingsystems are built around the quanti-tative side of technical analysis?

BVV: Most automated trading systemsare built on some form of technicalanalysis. Generally when people thinkabout technical analysis they thinkabout Bollinger Bands and movingaverages, which are still quantitativemethods. If one thinks about statistical

arbitrage generally people don't thinkabout that as technical analysis.However, it's still based on past marketprices and trying to understand rela-tionships through mathematics. Sowhere you draw the line between oneand the other is sort of muddy.However, most of the systems I seebeing built are multi-instrument sys-tems where they're trading one futurescontract against another, a basket ofstocks against another basket of stocks,the options against the futures - some-thing like that - rather than being in one

instrument and trying to pick the trendup or down or trying to pick a sidewaysmarket. The markets are getting moreefficient all the time and the tradingstrategies are getting more complex.Trying to control risk and uncovershort term inefficiencies is key

TA: Will the windows of opportuni-ty continue to diminish in size,beyond even the millisecond, anddoes that mean that only the largerplayers will have the necessary

infrastructure to exploit theseopportunities?

BVV: As I see it, many of the areas inwhich one can automate systems arewhat I would call a commodity system(not in the futures sense but a systemwhere the mathematics is well known),for example calendar spreading and thecarry trade. Everybody understands themathematics of the carry trade andthere's not really anything proprietarythat you can dream up about the carrytrade. Well, let's call that a sandbox.Who gets to play in that sandbox? Thebiggest bully in that sandbox is the firmthat can throw the most money atdeveloping the fastest technology. Sothe others have to ask themselveswhere the opportunities are that theycan pick off elsewhere. The fasterthings go the more expensive itbecomes to play in those sandboxes,and smaller players get pushed out andhave to look for strategies that take alonger time where milliseconds aren'tof the essence. You start to look atstrategies that may take minutes orhours to work out probabilisticallyrather than milliseconds. In the gameswhere probability of success is greatestbut technological advantage is the key,the smaller player is going to be pushedout.

Markets are always changing and thiscreates all kinds of new opportunities.But to the extent that risk is reduced byholding positions for a shorter andshorter amount of time, those kinds oftrades are going to be dominated moreand more by larger institutions that canthrow 10 million dollars at a problem.It's happening already.

For further information on theInstitute of Market Technology'sCertified Trading System Developerprogram, visit www.i4mt.org.

“ANY PIECE OF SOFTWARE THAT TRIES TO BE EVERYTHING TO ALL ITSCUSTOMERS IS NOT GOING TO BE AS FAST AS POSSIBLE DOING THE ONE

THING YOU WANT IT TO DO.”


STRATEGY SPOTLIGHTSTEIN INVESTMENT MANAGEMENT

Why do you trade only the S&P 500 IndexFutures contracts (E-mminis)?

Every market has its own personalityand I do not have time to delve into thedetails and nuances of each of them.The inefficiencies that I explore in onemarket generally do not work in othermarkets. If a trading system works inmany markets it can make only margin-al profits. I have several reasons forchoosing S&P 500 index futures overother futures: first, it is extremely liq-uid; second, I can use several uniqueindicators outside of regular price data,applicable only to stock indices (such asTICK, TRIN, etc.); third, I am muchmore knowledgeable in stocks than, say,in pork bellies or cocoa.

What is your trading strategy?

We implement a strategy called "TheTrading Edge". It is a 90% systematicand 10% discretionary program. Theprogram is designed to be as profitablein a rising stock market as in a fallingmarket, because it assumes both longand short positions. The programincorporates around 20 rigorously

designed and tested independentmechanical trading systems, all ofwhich are proprietary. I use all my 20+models in parallel and take the tradingsignals as they come, provided theirprobable outcome meets the strict cri-teria of the proprietary risk control sys-tem. I do not automate my execution. Ievaluate each signal generated by mysystems before actually entering thetrade.

How do you select which model to trade?

The two main criteria are the percent-age of winning trades and the return asa percentage of maximum drawdown.It's about choosing the 20 best systemsamong hundreds of other systems Ihave designed over the last 12 years.The number is not fixed, I may removea system if I see its performancedegrade or add a system from the"pool" of other available systems ifthey start to outperform. I re-evaluatethe systems a couple of times a month.

Are your models based on contrarian or trendfollowing strategies?

More than a half of my systems arecontra-trend, but the others work in thedirection of the most recent trend oruse seasonal indicators, where I evalu-ate the typical behavior of S&P at cer-tain times of the day, certain days ofthe month, and certain days of the year.

Which packages and systems do you use for i)data, ii) charting and analytics, iii) backtest-ing and optimization, iv) programming and v)execution?

For data, charting and back-testing/optimizing, I use TradeStation.For execution, I use TradingTechnologies X_Trader. I also have J-Trader and RanOrder as a backup. As aformer computer programmer, I alsowrite some "plug-ins" on C#.

What is the typical timeframe for your trad-ing?

The average holding period is 2 daysand I usually make just one or twotrades a day. I don't enter the market ondays when I don't get any strong trad-ing signals.

The Technical Analyst takes a closer look at the strategies and systemsemployed by Stein Investment Management LLC, a registered CommodityTrading Advisor that runs the "Trading Edge" program - a combination of

more than 20 uncorrelated mechanical trading systems, all trading the E-mini S&P500 futures.

Boris Stein graduated from Minsk University in the former Soviet republic ofBelarus with a Masters degree in physics and computer science. After working asa chief information officer for a major commercial company, he became one ofthe first foreign currency traders in the newly independent state of Belarus. In1995 he emigrated to the US as a political refugee. He formed Stein InvestmentManagement LLC in April 2006 and registered it as a Commodity Trading Advisorin May 2006.The Trading Edge program made returns of 180% in its first seven months of

trading in 2006 (from 1 June 2006) and made it into the list of Top 5 CTA pro-grams under USD 10m in April's issue of Futures magazine. Around half of theUSD 9m assets under management belong to institutional accounts and approxi-mately 20% is Boris Stein's own capital.

→→

TM

TM


Describe the logical steps in your trade decisionmaking?

1. We analyse current market condi-tions - trends, sentiments and behav-iour2. We analyse the technical signals gen-erated by our proprietary mechanicalsystems3. We analyse the trade risk and rewardaccording to our risk management sys-tem4. If all of the above meets our criteria,we enter the trade.

What kinds of data do you use?

I use intra-day price data, market senti-ment and volume data. For gaugingsentiment, I use Put/Calls ratio, VIX,

and TRIN (Arms Index). With regardto volume, it's noticeable that highervolume coincides with a wider dailyrange so there is not much help fromvolume analysis on those days. So Ilook at volume to find anomalies, i.e.those occasions when it does notmimic the daily range.

What kind of technical signals do you use?

Most of the indicators we use are in aproprietary form. They are based onmoving averages, chart patterns, proba-bility models, overbought/oversoldindicators, cycles & seasonal analysis,and reversal indicators. For over-bought/oversold indicators, I like RSI,but I also use stochastics, and %Rs.

I use Elliott Wave, Fibonacci,DeMark Indicators and Gann in orderto determine expected reversal levels,but in modified form. No popular indi-cators work in the exact form they aredescribed in books, but any of themcan become useful after modifyingthem and defining specific market con-ditions when they become applicable. I

have also used candlesticks for manyyears. The main thing here, again, is notto believe in the common rules and todo your own research.

Do you use chart patterns in your models?

I like it when a popular chart patternfails. Usually, it's a good time to enter atrade. I write some rather sophisticatedprograms in EasyLanguage forTradeStation to recognize patterns, aswell as just using my eyes.

Why do you think your models are makingmoney? What is it about the market they areexploiting?

My systems work well in all marketmodes - bull, bear, trending, or oscillat-

ing. I do not know exactly why theywork, but I think it's because they aredesigned using rigorous back-testing,and because they exploit the inertia inhuman behavior and habits. I believethat in the short term markets are emo-tionally driven. I re-evaluate all my sys-tems from time to time, because mar-kets do change. Actually, I've had a dif-ficult period for my systems lately, but Ihave learnt the lessons, made thechanges, and feel more confident thanbefore.

How does your trading system adapt tochanges in volatility?

The trading system incorporates analgorithm to track market volatility andis capable of auto-adjusting and self-tuning. Statistical volatility (standarddeviation) and average daily range aremy measures of volatility, and these areused mostly to make stop-loss and tar-get calculations.

How do you measure and manage risk?

I use the Compromise StochasticDominance method to measure risk,because I believe it solves the majorshortcomings of the Mean-Varianceapproach.

I manage risk by using a sophisticat-ed computer based risk managementsystem for adjusting trade size accord-ing to the equity in the accounts, mostrecent performance results of theemployed mechanical systems, andmarket volatility. I also widely employstop-loss orders and time stops. Itshould be noted that risk is alsoreduced because of the diversificationbetween uncorrelated mechanical sys-tems that comprise our tradingapproach.

I enter only trades with a very highprobability of winning, so it's typical torisk 10% of equity. The average cashposition is 85% of equity (minimum5%, maximum 100%).

What is your performance objective?

I target monthly returns of 12%. Iwould be surprised to see monthlyprofits in excess of 25%. The theoreti-cal maximum monthly decline is 25%.

Given the fairly limited time the Trading Edgeprogram has been operational, how confidentare you that your results are not down to luck?

I will not argue that luck is not neededwhen trading, but I am confident it isnot the main part in trading success;otherwise I would not have worked 16hours a day for the last 12 years doingmy research. I made a living by tradingmy own modest account for severalyears, having no other income excepttrading profits, and I won second prizein the futures division of the WorldCup Trading Championship in 2006,sponsored by Robbins TradingCompany. This I hope suggests luck isnot the main determinant.

Boris Stein is the managing mem-ber and president of SteinInvestment Management LLC(www.steininvestment.com).

“I LIKE IT WHEN A POPULAR CHART PATTERNFAILS. USUALLY, IT'S A GOOD TIME TO

ENTER A TRADE.”

Principal Trainer

Trevor Neil

Trevor Neil became a commodities trader at Merrill Lynch in the mid 1970’s before going on to work at LIFFE giving technical

analysis support to floor traders.

In 2000 he became head of technical analysis at Bloomberg where he was responsible for training and technical analysis software development.

Full course details can be found at: www.technicalanalyst.co.uk/training

For further information email: [email protected]

Register online at: www.technicalanalyst.co.uk or call: +44 (0) 207 833 1441

Course Details

Duration:

Courses are run from 9am to 5pm and include lunch and refreshments.

Who Should Attend:

Traders, fund managers, hedge funds, risk managers, brokers

A 2-day workshop that instructs delegates in all aspects of building an automated trading system. The course begins from an introductory level and each delegate will be equipped with a PC along with the appropriate charting, data analysis and programming software.

The essential technical analysis course providing a thorough grounding in TA techniques for traders and investment managers new to the subject.

Our very popular course for all market professionals looks at a variety of trading techniques for developing an effective short term trading strategy.

This highly regarded 2-day course provides in-depth training in the most effective technical trading strategies for more experienced market professionals.

The only course of its kind available on this unique and fascinating technique: Tom DeMark’s indicators centred on the famous, ‘Sequential Indicator’.

Training Courses

Training with The Technical Analyst

The Technical Analyst offers a range of exciting training courses for traders and investment managers. We also offer specialist in-house training on request.

AUTOMATED TRADING WORKSHOP

ADVANCED TECHNICAL ANALYSIS (2 DAYS)

SHORT TERM TRADING WORKSHOP (2 DAYS)

DEMARK INDICATORS

INTRODUCTION TO TECHNICAL ANALYSIS

04/05 October TA for the Portfolio Manager & AnalystLondon, UK

16 OctoberTrading the Yield CurveLondon, UK

18 October Introduction to Market ProfileLondon, UK

24 Sep Stockholm, Sweden22 Oct London, UK08 Nov Amsterdam, Netherlands26 Nov New York, USA03 Dec Frankfurt, Germany

26/27 Sep London, UK01/02 Oct Amsterdam, Netherlands 08/09 Oct Frankfurt, Germany 15/16 Oct Copenhagen, Denmark

25 Sep London, UK

13/14 Nov London, UK

23 Oct London, UK

Other Training Courses

48

GET QUALIFIED IN TECHNICAL ANALYSIS

For more information on how to join and what is involved in passing

the STA Diploma exam, visit our website at: www.sta-uk.org or call

us on +44 7000 710207

The Society of Technical Analysts (STA) represents and accredits professional and private Technical Analysts operating in the UK

Originally established in the 1960s, the STA provides its members:• Education Monthly lectures and regular teaching courses in technical analysis

• Research The STA Journal publishes research papers on TA techniques and approaches

• Meetings Provide members the opportunity to discuss technical approaches and markets

• Representation The STA lobbies on behalf of analysts with data vendors, exchanges and regulators.

The STA represents the UK at the International Federation of Technical Analysts (IFTA)

• Accreditation The STA Diploma Exam is internationally recognised as a professional level qualification

in Technical Analysis

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