biulding robust ts

8/13/2019 Biulding Robust TS

1/35

C A S P A R M A R N E Y

TRADER MAGAZINE

BUIL DIN G ROB USTF X T R A D I N G SY S T E M S

BUILDING ROBUST

FX TR ADIN G

SYSTEMS

FIN DIN G A GO O D

HISTORICAL DATA

SO URCE

IDEN TIF YIN G AN

E D G E

EXPLO ITI N G THE

VO LU M E P RO FI LE

KNOW YOUR

CURRENCIES

MAR NEY VOLUME

AN D R AN GE

INDICATORS

PRI CE U PDATES

AS PROXY F OR

FX T RADED

VO LU ME S

Copyright 2009-2012, FX Trader Magazine, RifeBUILDING ROBUST FX TRADING SYSTEMS


2/35

A PERPETUAL UEST

here has been a perpetual quest by traders, to

identiy quantifiable trading patterns, ever sincecandlestick charts were developed, on the worldsfirst trading floor; the Dojima Rice Exchange, ounded inOsaka, Japan, in 1697.

Te advent o computers has made tquest considerably easier, but one ac

has remained constant; markets are straded by people. As long as that remathe case, they will always be driven by otwo actors, namely ear and greed. Thave been many observations made abthe predictability o crowd behaviour,

perhaps the most amous and ofen quois that o the amous German poet, a

philosopher, Friedrich von Schiller wsaid,

Anyone taken as an individual is tolerasensible and reasonable - as a member ocrowd, he at once becomes a blockhead.

THE HOLY GRAIL

However, although there is certainly non-randbehaviour in the financial markets, equally there is almcertainly no Holy Grail or secret ormula, that even

most successul quantitative unds have discovered. I twere the case, there would be no need or them to trademany instruments, over so many time rames, with mdifferent models, and to ocus so much o their resour

on efficient execution (which will covered in a later article).Afer many ailed attempts, when author finally began to post some vconsistent returns, over a two y

period, a good riend inquired whatsecret was and what he had discover

He replied that he hadnt ound secret to the markets, discoveanything new, nor stumbled upon Holy Grail. He had just identifieew small, robust, edges, which wtraded across as many crosses as possibto which the very astute response caTat is the Holy Grail.

content * content * content

Building Robust FXrading Systems

2 FX TRADER MAGAZINE Special Supplement

FX BUILDING ROBUST FX TRADING SYSTEMS


3/35

UNDERSTANDING THE ODDS

e.g. A roulette wheel typically has 38slots with 2 zeros. Tis gives the housean edge o 2/38 x 100 = 5.26%, when

players bet on red or black. Even sucha relatively small edge produces a

substantial and incredibly consistentrevenue stream or the casinos andtheir shareholders. Te more timesthe wheel is spun and the more bets aremade, the more the casinos probabilityo winning tends to 100%.

Tis is exactly what the systematictrader should be seeking to achieve identiying and exploiting a smalledge, as many times as possible; being

the casino. Tereore, the first step indeveloping a robust system has to beidentiying an edge. o do this, the

main tools o any system developerare good historical data and sofware

with which to analyse it. Tere are anumber o excellent sources o dataand sofware, readily available now.Tis is a huge advantage, compared to

even relatively recent years, when it wasvery hard to come by, particularly ororeign exchange data, with no centralexchange, the dominance o voicebrokers and a very ragmented market.Te rapid increase in computing

processor speed is also a huge advantage.

Once we have those tools in place, thenext task is to quantiy trading ideasand this is where any system developer

will soon be able to relate to the amousTomas Edison, inventor o the lightbulb, who amously said,

I would construct a theory and work onits lines until I ound it was untenable.Ten it would be discarded at once and

another theory evolved. Tis was theonly possible way or me to work out the

problem... I speak without exaggeratwhen I say that I have constructed 3,0different theories in connection with electric light, each one o them reasona

and apparently likely to be true. Yet oin two cases did my experiments prove

truth o my theory.

SUCCESSFUL TRADINGSYSTEMSUnlike Edison, we have the advantagknowing that profitable trading systecan be developed, as there are a numo proven systems already in existen

which one can easily test, such as Channel Break Out (CBO) syst

made amous by the urtle Experimewhere Richard Dennis and WilliEckhardt had a wager about whetsuccessul trading could be taught (a

proved that it could). Tose sachannel break out/trend ollowtechniques have been exploited by msuccessul unds. Te Opening RaBreak

FX TRADER MAGAZINE Special Suppleme

FXBUILDING ROBUST FX TRADING SYSTEMS


4/35

Out (ORB) is another system,which has been proven to havea consistent edge, perhaps mostamously exploited by oby Crabel.

he reason that these systemshave proven to be robust is almostcertainly because there is a soundrationale behind why they work.he CBO system relies on the actthat markets trend. It has beenshown that they oten have largertrends than would be expectedin a random walk or normal

distribution, oten displaying attails; examples o which are almostcountless, with many Black Swanevents happening as recently as last

year.

he ORB system has worked wellin the utures markets, as they havea ixed open, rom which to deinean opening range, and all uturesmarkets display similar volume

characteristics; as illustrated by theollowing sample o S&P volume onthe CME, taken over several monthsin 2008 (Local Exchange ime).his has remained constant overtime and is something that thelegendary Monroe rout alsoobserved. In Jack Schwager s book,he New Market Wizards, irst

published in 1992, he is quoted , assaying,

Te most liquid period is the opening.Liquidity starts alling off pretty quicklyafer the opening. Te second most liquidtime o day is the close. rading olume

orms a U-shaped curve throughout theday Generally speaking, this patternholds in almost every market. Its

actually pretty amazing.

FOREIGN EXCHANGE VS.FUTURES MARKETS

However, to develop robust FX trading

systems, we have to take into accountthat FX behaves differently to a typicalutures market, and unortunatelythere is no fixed open or close; Asiais already trading as Europe comes in,ollowed by London. Similarly withthe closes; New York and Chicagoare still trading, while London andEurope are going home.

Tis is probably why it is consideredmore challenging to build successulFX trading systems: Te opens andcloses o utures markets are notrandom events and have distinct, non-random characteristics.However, the FX markets have theirown non-random behaviour. Itsgenerally accepted among traders thateach currency cross is different, witheach having its own particular nuances.

o some extent, this is true, athereore, i one finds that a certaino parameters work well or EURUbut not or GBPJPY, then its easy

find arguments to explain why the tcrosses may behave differently, weconomic data and news events bereported in different time zones etc

Tere are also moves specific to certcurrency pairs, as FX is involvedevery cross-border transaction acrthe world. As a spot trader, I re

a certain, oil oriented, corporcustomer always selling a markmoving amount o GBPNOK aspecific time every Friday.Historic price data analysis m

well have revealed that non-randbehaviour, but without knowing wit occurred, it would have been oolto trade it, as one may have lost a huamount o money i the corporcustomer changed its trading habit




5/35

Tere are also much broadercharacteristics o the FX markets.It is very well known that Europe is

the largest trading centre by volume,ollowed by the US, with a very illiquidtrading period, as the sun crosses thePacific, until Asia comes in.

Although genuine FX volume datais impossible to quantiy exactly,being so ragmented, and with nocentral exchange, we can use theCME currency utures as a proxy. Wefind that their volume distribution is

very different to the distribution o atypical utures market, as discussedabove. Te chart above shows asimilar average hourly volume or theCanadian Dollar Futures contract,over a three-month trading period(UK ime).

Just as with the utures markets,although volume analysis may not

produce a robust trading system, it doesillustrate that FX clearly isnt entirelyrandom and there is a very predictable,robust pattern, repeated by tradersevery day.

FOOLS GOLD

With all o that in mind, its relatively

easy to find systems that work well orspecific instruments, on historic data,

which would appear to have huge edgesand to come up with explanations as to

why those parameters would work ora certain cross.

When testing enough parametersthough, one will always find parametersthat work or any indicator on agiven market. ake, or example, justtesting a simple two moving averagecrossover combination, between 1 and50. Tis will return 2,450 differentequity curves (assuming we count the10 event crossing above the 20 eventmoving average, as a buy, and vice versaor a counter trend trade).

By pure statistical probability, a largenumber o those combinations willbe profitable, and statistically someo those will also be profitable outo sample. In act, it is a statisticalcertainty that, i you look at enough

parameters, some o them will test

well, both in and out o sampHowever, without any rationthe resulting systems would not

reliable trading systems, being sola product o statistical probability

hereore, one has to be very careand appreciate that just becaussystem works in simulations, it dnot mean that one has discovea robust, or even remotely reliabtrading system - another one o countless errors the author has pan expensive price to learn.

It is better to identiy even jussmall, quantiiable, edge that yunderstand and which has a sourationale. o quote Monroe ragain,

Make sure you have an edge. Knwhat your edge is... Basically, wh

you get down to it, to make money, y

need to have an edge and employ gomoney management.

THE EDGE EFFECT

An oten-used ratio or quantiywhether a system is good is ProFactor (PF), being the gross prodivided by the gross loss i.e. i sum o all the proitable trades osystem, over a given period, was $

mio, and the gross losses o all losing trades was $1.0 mio, the ProFactor would be 1.1/1 = 1.10

o put this in perspective, to use roulette analogy: i a player bet on each time, the player would win average, 18 out o 38 spins o a wh(with a double zero table). he ho




6/35

would win 20 time s out o 38 (i.e.every non-red slot). For illustrative

purp oses , let us assume the payout

is equal to the odds. his givesthe house a PF o20/18 = 1.111

With a sing le zerotable, the housePF is just 1.055(19/18).

he importantpo int is that the

house edge is a verysmall one, thoughstill incredibly

proitab le . Lo okedat a dierent way,the odds o thehouse winningon any singlespin o the wheelare only slightlybetter than evens,being 20/38x100= 52.63% ora double zerotable and 51.35%(19/37x100) or asingle zero table.

Even with onlythat slight edge,as Albert Einstein

said,

No one can possibly win at roulette,unless he steals money rom thetable, whe n the deale r isnt looking.

rading is no di erent. All atrader has to d o, to be consistently

proitab le , is to id entiy anedge, and apply good moneymanagement. Unortunately,

that is much easier said than

done. Just as the casinos edge isin knowing certain acts, a trulyrobust trading system, can onlybe built on known, quantiiable,non-random, market behaviour.

I a trading system enters a los ing

streak, a statistical certainthat it (oten) will , it is th

possible to identi y wheth er

is just an expected statistirun, or wheths o m e t h i nhas chang u n d a m e n t a lin markbehaviour. casino knows theach o its tab

wil l have malosing runs a

it also kn ows this a statisticertainty. is where monm a n a g e m e

plays a virole. Withou n d e r s t a n d iits edge, a

with out beable to quantit, a casino wounot be able operate.

As we have sewith an arbitrtrading systand an arbitrset o parameteno matter h

good the and out o sample results aa system is very unlikely to robust. Equally impor tantly

wo uld be imp os sible to knowthe system had degrade d, withounderstanding the underlyireason why it worked .




7/35

Finding a good historical data source

Reminiscences o a Forex Operator

In the last article, we introducedthe idea o building robust tradingsystems or oreign exchange, andcompared some o the characteristicso the FX and Futures markets, with

FX having its own unique, but alsonon-random, behaviour. Tis articlenow explores the first major challengeo actually building a system, namely,building a reliable historical database:I we were discussing uturesmarkets, this would be relativelystraightorward, as there is only one

price traded at any given time witha specific volume, which is readily

available, direct rom almost all o therelevant utures exchanges as well asthird parties. Te FX market is ratherunique though:

While being by ar the most liquidmarket in the world, its also themost ragmented. With no centralexchange, each bank makes its own

price, or each currency pair. Tereore,at any given moment, EURUSD maytheoretically be quoted as 1.3340/42

at one bank, 1.3339/41 at another and1.3341/43 at a third, each with theirown white labelled, or proprietary,electronic trading platorm, otherwiseknown as an ECN (ElectronicCommunication Network). Tereare also a growing number o ECNscompeting or liquidity, where buy

side counterparties can submit theirown prices into the systems. Tismakes it impossible to get a trulycomplete, clean and accurate pictureo intraday FX prices. However, even

the current, ragmented, electronicmarket is a quantum leap orwards,rom only relatively recent years:

IN THE BEGINNING VOICEBROKERS

Beore ECNs existed, most FX tradingwas done over the phone, with a tradersitting on a spot desk, as the author

once was, with hal a dozen brokerboxes, all shouting out prices. Forexample a Dollar Mark (US Dollar

v German Deutsche Mark) sdealer (the author pre-dates the Eumight have one broker box calling othirty, thirty-five, in five and anoththirty, thirty-our, three by five e

with the three by five denoting size, in millions, that the price wgood in and the big figure not quoas that was known by all involved.Each trader, or each currency p

would have a number o boxes shoutout similar prices and hence the claimage o a banks trading floor, bea cacophony o sound. Te realitmuch different these days, with

voice brokers having been almentirely replaced by ECNs, particulain the major currency pairs.




8/35

In the days o voice brokers, part othe spot traders art was to recognisethe brokers voice with the best price,

good in the size he wanted to execute,which as a junior dealer, was probablythe hardest skill to master; particularly

when the broker at each institutionwouldnt always be the same person,as they would need to go to lunch, beaway on holiday, or just step off the deskor a ew moments. A junior on a desk

would usually cover several dealers,when they similarly stepped off the desk,so may have had over twenty voices torecognise and remember which boxthey were on. All the deals were alsoentered manually, unlike todays ECNs,

where the deals automatically go in thetrading blotter. On this occasion itis probably very air to say that juniortraders today really do have it easy bycomparison.

I an order was too large to executewith just one counterparty, a call out

would be made, where the dealer wouldstand up and shout, Get me calls!Every other dealer on the desk, wouldthen either call up several banks on, TeReuters (an inter-bank chat system)and/or the telephone. Each dealer

would then shout out the prices he wasbeing made and the dealer initiating theactivity would make hand signals andshout yours or mine, to indicate i he

wanted to buy or sell. Tere was a great

deal o spoofing that went on, whichwas part o the art o good executionand mastering the art o spot trading:

For example, i a dealer at onebank took a call rom another, andound they were a seller, he might alsosell, believing a large order was goingthrough and expecting the price to all,as the other bank continued to execute

their order. Tis meant that one wouldofen buy rom the first ew calls,hoping this would prompt the other

banks to believe you were a buyer, drivethe price up, quoting higher prices, into

which you could then sell. Hence it wasalways a game o bluff, counter-bluffand spoo.

One anecdote worth recounting, inwhich the author was involved, is a spotdesk o a first tier bank, making a hugereturn in the space o a ew minutes,solely by a simple, but beautiullyexecuted spoo:

Te bank was known to be one thathad a good relationship with the Banko Japan (BoJ) and through which theyhad intervened in the market beore, tostrengthen their currency, occasionallycoming into the market and selling acollosal, market-moving amount oUSDJPY and DEMJPY. Tis alwayskept dealers wary o being the other wayaround, lest they got caught the wrong

way on an intervention, and hence keptthe Yen supported.

Tereore the chie dealer and number two, the Yen trader, knew ti the bank was to be seen selling a h

amount o DEMJPY and USDJPY,market may well think that the BoJ intervening and would then also sselling, to capture the pending mdown. One day they stood up shouted Get me calls!, which in it

wasnt unusual, as this happened most large orders:

As each o the other traders, assistants, all started getting prices rbanks and shouting them out, tshouted, yours! together with hand gesture o pushing an open hdown and away rom the body the avoidance o any doubt as to instruction) until theyd sold literseveral hundred million US Doland German Deutsche Marks, agathe Yen.

Nobody knew what was going but everyone did his or her job and

the order executed. Te sales desk asking what was happening,




9/35

as customers called up to ask whatthe reason was or the big move, aseverybody saw and heard the huge

commotion coming rom the spotdesk and the inevitable rumour spreadthat it was BoJ intervention. Nobodyon the desk said a word to confirm ordeny the rumour, as nobody else on thedesk, knew what was really going on.

Just tallying the total amount sold andreconciling the now huge position thedesk had, was not an easy task.

As the rumour spread and speculationmounted, USDJPY and DEMJPYcontinued to all rapidly. Ten came thesecond wave, or so everybody thought.Again the Chie Dealer shouted, Getme calls! and started to sell USDJPYand DEMJPY again. Te marketthought it was the start o a second waveo selling by the BoJ, as this was theirtypical style and accordingly markedtheir prices much lower and again soldthemselves. Ten came the stroke o

genius they started to buy, and buyeverything, shouting, Mine, mine,mine with the accompanying handgesture o bring the palm o the hand uptowards the shoulder, to the still alling

prices, as other banks initially thoughtit was just part o a spoo to sell into.

Beore the market realized whatwas going on, theyd covered the entireposition and locked in a massive profit,literally in the space o a ew minutes.

Everybody on the desk was given aslice o the pie, or a job very well doneand its the type o trading that we willunlikely see again such were the daysbeore the dominance o ECNs.

Tere is o course a point to thisanecdote o course, other than torecord it or posterity:

Although a huge amount o

transactions went through in those ewminutes, none were recorded by exacttime. Te author himsel probablyexecuted trades, with more than hala dozen banks, but the most that

would have been recorded was either aconversation on Reuters or a hurriedscribble on a deal ticket afer a phonetransaction, later reconciled with thecounterparty.

Tereore, although an extremeexample, it illustrates the point very

well; there simply isnt a completelyreliable source o accurate, historic FXdata available beore the dominanceo ECNs and the situation hasntimproved significantly since:

THE ADVENT OF ELECTRONICTRADING PLATFORMS

As electronic platorms beganto dominate more and more o the

volume, so accurate data has becomemore readily available, as computersare easily able to capture the exact

time, price and volume o every traHowever, there is still no central ECand rather than one becoming

dominant player, as some expectthe market has continued to ragmeTis means that at every minute o day, each currency pair is tradingdifferent prices, bid/ask spreads a

volume.Only i one could aggregate all

the prices made on every ECN andevery bank and broker, could a traccurate record be built. Even ththough, a bank may provide a rateseveral ECNs, good in $10mio, busoon as one o its prices is hit, it wimmediately pull that rate rom other ECNs. Tereore, even thoua 40 bid may appear to be good$50mio, i one could aggregate o the prices at a given moment, reality is, that it may well not be ci you tried to execute a trade o tsize.

TRADING THE CROSSES

I someone wanted to sell Swiss Franc against the JapanYen, as its not a commonly quo

pair, it has relatively little liquidon the electronic platorms anda consequence has a wider prHowever, USDCHF and USDJPYmore actively traded, so a proessio

trader would go through the lor components, buying USDCand selling USDJPY, with the Uamounts netting out to zero, leava CHFJPY position. Tis means trader actually traded CHFJPY, no price may actually have tradedany ECN or with any broker directCHFJPY.




10/35

GAPS AND SPIKES

Although FX is by ar the most liquid

market, there are still times when noprices are recorded or periods o time,particularly during the less liquid Asiansession and, as we have seen above,

particularly in the less liquid crosses.Tis means that not only do genuinegaps occur in historic data, but thereare also ofen times when a certain pairtraded on one electronic platorm, butnot on others. Tese gaps in the pricedata need to be filled, which can be done

using a simple algorithm, otherwise anyindicator, even a simple moving average,

would have an input o zero or the priceat that time, which would o coursecreate a hugely incorrect reading, whichmay well trigger anerroneous trading signalin an historic simulation.Conversely, not only arethere times when there isno price, there are times

when a spike in the dataappears:

Tis can be due toa number o actors, but ofen wheresomebody has lef an offer to take profitat, or example, 1.2580 overnight. Isomebody else has a stop order to buy i1.2520 is traded and there are no other

prices in the system until the 1.2580offer, then that would be the next price

dealt. Its market practice to cancel thesedeals the ollowing morning, when anobviously off market rate was traded,but nonetheless, it will still ofen appearin the historical data made availableand there is a grey area where it isquestionable whether the rate dealt wasoff market, or air given the time o dayand liquidity.

One o the challenges o using asimple algorithm to clean the data isthat some genuine market moves can

look a lot like a spike in a ast market,when some news, or economic data,has just been released. A way aroundthis is to confirm the rate via the othercomponents. Looking at AUDUSDand USDJPY components at the timecould check or example, a spike inAUDJPY.

HIGHS AND LOWS

One o the most commonly askedquestions in FX trading is where thehighs and lows were, as this is wherequeries occur and money is lost andmade on orders. I an order to buy

was placed at 0.9840 and the low was0.9839 offered, then the order wouldbe filled. I the low price quoted was0.9840/43 but was never traded, orgiven at 0.9840, then the order wouldnot have been filled. As its ofen hardenough to determine in a real trading

situation whether an order should havebeen filled, its impossible to be certain

with a historic simulation. In act, ia large buy order had been placed at0.9840, this could affect the price actionitsel, with market makers buying aheado the 0.9840 bid, knowing the market

will be supported there.With the market so ragmented, and

with no central exchange to determthe definitive highs, lows and

volume they traded in, order fills rem

a cause o much debate, on a daily bain the FX market.

PREDICTIVE PRICING

As there is no central price ocurrency pair, a bank or broker is to make whatever price it wants to thcustomers and the customer is equree to trade on that price, or trelsewhere.

Some traders are very predictain their trading behaviour and otrade with one counterparty. Tleaves them open to predictive pricialgorithms. For example, i so

traders sold USDJearlier in the day, thits likely that their ntrade in USDJPY wbe to cover that positand buy. Some ECthereore have the abito show each customedifferent price.

Tereore while a neutral prin USDJPY may be 98.94/96, ocustomers ECN might show a palways marked a point higher 98.95/97, until they have closed thshort position, when it will then back to a neutral price, earning

bank an extra pip on that trade and customer believing hes being showrelatively tight two point price all da

Te author has first hand experieo such pricing engines, with one oormer colleagues having built just suan engine, or a first tier investmbank. Its a perectly legitimate practas the customer has the reedom

Tere simply isnt a ully reliable sourceo accurate, historic FX data available

beore the dominance o ECNs




11/35

trade on the price, or not, but the phrase,Caveat Emptor, is just as true in todaysFX market, as it was in Roman times,

when the phrase was first coined:Consider a system, which generated

a trading signal, in USDJPY, just once aday, or 252 trading days a year. Givingone point away on each trade may wellresult in an otherwise profitable system,recording a net loss. Without knowing

why the losses were occurring, the tradermay believe a perectly robust system wasno longer perorming and even worse,i he were to run a simulation on that

years data, he might see that he shouldhave made a profit, still not knowing

where the 252pt loss was made.Tis highlights how critical efficientexecution is, no matter how robust theback testing and how clean and reliablethe historical data; something that welllook into in much more depth, in auture article.

INTEREST RATES

One extraneous actor we have totake into account, when dealing withFX, which Futures traders do nothave to account or, is the interest ratedifferential. As each currency yieldsa certain rate o interest, then oneearns interest in the purchased (long)currency and pays interest in the sold(short) currency. Tis means that i

a position was held long Kiwi Yen(NZDJPY) then the interest rate, orcarry would be approximately 3pct perannum, at current rates. Tat is to say,i the exchange rate and interest ratesremained the same in one years time,then the trade would yield a 3pct return,being the interest rate differential earnedby holding the New Zealand Dollar vs.

that paid borrowing Japanese Yen.Tat difference is accounted or by

rolling the position every night, ortom/next as its called. When a tradeis rolled, its closed out at an agreed rate

at the end o the day (called a reval.being short or revaluation) and re-instated with a small adjustment madein the price, to account or the roll (thedifference in the interest rates).

For an intra-day trading system,this isnt a actor; i the positions areflat overnight, then there is no roll.For a longer term trading system,

which holds trades overnight, thenthe interest rate differential has to betaken into consideration, to correctlycalculate the results. With somehistoric interest rate differentials being

very large, this can make a dramaticdifference, and again be the differencebetween a system being profitableor otherwise, hence the carry trades

which seek to exploit exactly thosedifferentials.

However, although the central bank

rates may be fixed and known, thecounterparty will usually charge a smallmark-up on the tom/next. Sometimes,this can be as much as several percent.Tereore its important to know boththe interest rates and the mark-uprom the broker, to negotiate them aslow as possible and actor them intoany simulations.

TIME ZONES

Probably the most overlooked ac

when dealing with FX data is tEurope, the US and Asia, all operon different time zones. I we wanto code an opening range break osystem or the London open, whichone o the most liquid times o day, th

we should use local time in London anot GM.

Although most data is providedGM, traders and thereore marbehaviour, operate on local time,daylight savings need to be taken iaccount. Unortunately the US slightly different dates when tobserve DS and most o Asia doeobserve daylight savings at all, so impossible to make one univeadjustment or local time across all sessions and days o the year.

Tereore one either has to adjthe data, to local time, or the sess

one is interested in trading, or writeadjustment into the code, dependon both the time o day, and dthat the order is being executed. example, i the data is in GM, thclosing a position at the close o the in London, at 5pm, would still be 5in November as local time is




12/35

GM. However, i the same tradewere done in June, closing at 5pmlocal time in London, would be 4pmaccording to the time stamp o thedata, as Daylight Savings would havebeen in eect.

SYNTHETIC PRICES

We know that the major currencypairs are the most liquid, with thebetter pricing; being those tradedagainst the Dollar and the Euro.hereore, i we had the data or

those, then we could derive the crossrates, such as CHFJPY, GBPCADetc.

he one challenge here o courseis that i we had 60 minute OHLC(Open, High, Low, Close) data, oreach hour o the day, and calculatedthe implied crosses, then we wouldonly know the open and closeaccurately or those hours, as we haveno way o knowing that the high or

low o each component occurred(and almost certainly didnt) at thesame time, within the hour.

However, its certainly one viablemethod to create a reliable database.I we had hourly data or the sevenmajor currency pairs i.e. 8 currencies,then we could calculate a synthetic

price rom those components orthe other 21 crosses. For example,

GBPJPY is the GBPUSD ratemultiplied by the USDJPY rate etc.his creates a relatively clean set

o data or the crosses, but only aline chart, as the crosses would notcontain accurate highs and lows. i.e.one could not plot a bar chart, which

would require the Highs and Lowso each hour.

CONCLUSION

Historic FX data is an absoluteprerequisite, beore even attempting tobuild a robust FX trading system, butit can only ever be an approximation,unlike the utures markets, which havea central exchange and no interestrates or rolls to take into accountand where the data is almost alwayssupplied in local exchange time.

Te FX market is simply tooragmented to have one universallyagreed set o historic data and the

trend is or the market to become moreragmented and not less so, with newelectronic platorms being releasedeach year, some carving a niche incertain currency pairs, or time zones.

Historic price data beore thedominance o ECNs is much lessaccurate than more recent data andis, at best, an average rate traded or acertain time period. Accurate Open,High, Low and Close (OHLC) data

simply cannot, and does not, existbeore the days o ECNs and since then(approximately late 1990s onwards) itis ar more accurate and more readilyavailable, but can still only be anapproximation. (Daily data is muchmore accurate as the OHLC rates ora given currency pair on a certain dateare generally agreed, particularly orthe majors).

As an algorithmic FX trader, thebest solution is to find a good sourceo data and then clean it as much as

possible, cross reerencing the crossesand majors, filling in any gaps andcleaning out any spikes. Ten the datamust either be offset to account ordaylight savings in the time zone oneis interested in trading, i the system

has any time input, or it can be writinto the code o a system itsel.

Finally, i its a system that homany positions or a number o daor requently overnight, then the romust be actored into the simulatioTere are many pieces o sofwavailable or analysing utures markthat can be adapted or FX data bnone off the shel to date providear as the author is aware, the uniqunctionality required to account such unique nuances o FX.

All o these challenges proba

contribute to the relative lack successul systematic traders in Fgiven its huge liquidity and clcapacity or systematic trading.

Better sofware and data wcertainly be more readily availablethe uture, as FX continues to gras an investment class. Te authhimsel is currently involved in betesting a number o sofware packaand working with one sofw

company to provide the uniqunctionality needed to test systems, off the shel , so its certaisomething that will be available,the near uture.In the meantime, the ollowiresources may be useul:

Historic FX Data

Olsen Data

www.olsendata.com/

EBSwww.icap.com/markets/foreign-exchange/spot-fx.a

Tradestationwww.tradestation.com

Interest Rate Data

Pinnaclewww.pinnacledata.com/


http://www.olsendata.com/http://www.icap.com/markets/foreign-exchange/spot-fx.aspxhttp://www.tradestation.com/http://www.pinnacledata.com/http://www.pinnacledata.com/http://www.tradestation.com/http://www.icap.com/markets/foreign-exchange/spot-fx.aspxhttp://www.olsendata.com/


13/35

In the previous two articles in the series, we discussed theneed to identiy a robust edge and that it must be easilyexplained, with a sound rationale and that it neednt bea significant edge, to produce incredibly significant andconsistent returns. Just as a casinos edge is very small, whenexploited many, many times, the net result is incredibly

profitable.

We then discussed the need to have good, clean historicdata, with which to test ideas, as inaccuratedata with gaps or spikes, could easily lead

to misleading or wrong results.

In this article we build on thoseoundations and explore the developmento some ideas, rom conception, throughto creating trading rules, testing them anddetermining whether they give us a robustedge.

SUBJECTIVE ANALYSIS AND HIGH SUCCESSRATE TECHNIUES

When I first became a trader, it never ceased to amazeme how subjective the vast majority o analysis was. Tenumber o ideas that are in common use, many o whichcan be proven to be flawed, or cannot be objectively tested,upon which millions is risked daily, is nothing short oastounding.

Read almost any technical analysis on the market, easily

accessible via a quick search o the web and one will ficountless examples such as, the oscillator is overbought athereore the market is a good sell here, or the market breached the 10 day or 200 day moving average, or the pris at an extreme level, testing the lower Bollinger Band.

Te reason that most o these views continue to be ollowis summed up beautiully by the legendary WilliEckhardt, o the amous urtle rading Experiment,

Since most small to moderate profits tend

vanish, the market teaches you to cash thin beore they get away. Since the mar

spends more time in consolidations thin trends, it teaches you to buy dips and rallies. Since the market trades through

same prices again and again and seemonly you wait long enough to return to prit has visited beore, it teaches you to h

on to bad trades. Te market likes to lull yinto alse security o high success rate techniques, which oflose disastrously in the long run. Te general idea is that w

works most o the time is nearly the opposite o what workthe long run.

he amount o books which also teach these hsuccess rate techniques, which oten lose disastrouin the long run is equally astounding. Let us take oo literally countless possible examples rom one o better known trading strategy platorms o a BollinBand strategy:

Identiying an Edge

o succeed as a trader, it is absolutely necessary to have an edge. You cant win withoutan edge incidentally, i you dont know what your edge is, you dont have one.

Jack Schwager




14/35

Input inormation

Name Type Default DescriptionBollingerPrice Numeric Close A bar price or other value

used to calculate theventer-line average.

estPriceLBand Numeric Close riggers placement ostop order at LowerBandwhen this price crossesover LowerBand.

Lenght Numeric 10 Number o barsused to calculate theBollinger band.

NumDevsUp Numeric 2 Number o Standard

Deviations or theBollinger BandCalculation (enter apositive number; thestrategy will calculatethe lower band).

UsageLong entry based on the low price crossing above theBollinger Band.

DescriptionBollinger Bands are generally placed two standard deviatiabove and below the market. Prices within the stand

deviation are said to be normal prices. Whenever the prmoves below the lower band, the strategy generates a bstop order or the next bar when the low price o the currbar has crossed back above the lower band. Te stop valuthe level o the lower Bollinger band.

You can change the number of bars and standard deviatused to calculate the Bollinger band.

Whenever the price moves below the lower band, this stratgenerates a buy stop order or the next bar when the low pric

the current bar has crossed back above the lower band.

Tis is a good example o a high success rate technique, whcan ofen, lose disastrously in the long run. I we appboth the long, and equivalent short, rule to AUDJPY othe last 10 years, we can see that it was indeed a high succrate technique, which then lost disastrously rom June

June 09, as shown by the chart below and the equity cuin the sub graph.

TRADING SYSTEMSFX




15/35

However, most peop le trading such a technique maywe ll bel ieve that they we re ju st unlu ck y, ra ther

than appreciating the statistical certainty that itwa s on ly a ma tt er o wh en , an d no t i, the strat eg ywo uld l os e disa stro us ly in the lo ng run.

Another one o the mistakes that one sees time andtime again in testing strategies is optimising themarkets and parameters used. While back testing,one will ind many markets where a given strategyhas perormed well and its thereore a trivial exerciseto construct a successul back tested simulation, o

va ri ou s ma rket s an d stra te gie s that ha ve per ormed

we ll in the past .

Victor Sperandeo underlines the same point in hisbook, rader Vic on Commodities,

Any system or method based on optimization willail in th e lo ng run . his is be ca us e ma rket s ch an gean d ev olve , th ey do no t re ma in co ns ta nt . So i yo ust ruc tu re a sys te m ba se d so lely on th e pas t, it ca nn otsu rvi ve th e u tu re.

As highlighted in the previous articles, any tradingrule will have periods and markets where it is

pr o it ab le , eve n bu yi ng on a ull moon and sel lin gon the ollowing ull moon, will doubtless work insome markets, over some time periods. Suice tosay, that does not make it a robust strateg y.

here are countless other subjective strategieswh ic h ha ve hu ge o llo wi ng s an d again ar e us ua llyhigh success rate techniques, which thereore

appear to be proitable but are possibly lawed inthe long run. Many o these enjoy the beneit thatthey can never be disproved, lacking objective rules

wi th wh ich to te st the theor ies , such as the in amo usElliot Wave or om DeMark studies. hough manyhave tried to write rules or them, I have yet to see asuccessul and robust translation into an objectiveand proitable trading strategy, though I would bedelighted to do so.

ROBUST STRATEGIES

So, what do we mean by a robust strategy? oundations or a robust strateg y are in havingedge and knowing what that edge i s, put very wby Jack Schwager o Market Wizards ame.

o succeed as a trader, it is absolutely necessato have an edge. You cant win without an edeven with the worlds greatest discipline and monmanagement skills. I you dont have an edge, that money management and discipline will do

you is to guara nt ee that you wil l gra dual ly bl ee d

death. Incidentally, i you dont know what yoedge is, you dont have one.An edge starts with a sound idea and then know

you ha ve an edge ca n on ly come ro m rigorotesting (as opposed to optimisation) o that idso let us start with the idea that, in the longterm, markets trend and as long as markets driven by people, ear and greed will always pla strong role and markets will thereore continto trend.

We th en need to te st th at idea and th er eor e neto develop some trading rules. his could be usa one, two or even three moving average cross osystem, a channel break out, where the markmakes a new n day hig h or low, or even breakoutside o a Bollinger Band the opposite to tstrategy shown above.

he Channel Break Out system is one that h

gained a great deal o press over the years, largethanks to it being the ba sis or the amous urExperiment by William Eckhardt and RichaDennis. It has certainly stood the test o time athere are vast quantities o research on the systeas well as sotware programs, desig ned speciicato develop such a system, such as radingBlothough it can be done in almost any sotwa

package, or even Exc el.




16/35

So why has the Channel Break Out (CBO) system stoodthe test o time and resulted in so many successul systematicunds, when other trend ollowing systems, such as a Moving

Average crossover system, have not?

Lets analyze the results side by side. I started by taking 20years o FX data or AUD, CAD, CHF, EUR, GBP, JPYagainst the US Dollar and then constructing all 21 possiblecrosses o those; AUDJPY, EURGBP, EURCHF etc., asdescribed in the previous article. I also did this or intradaydata, which was a considerably more demanding exercise, butam using daily data or the purposes o this analysis.

I broke the data down into two periods, 1993-2003 and

2003-2009, simply because 2003 was a convenient overlapbetween various data sets.

Lets start by defining the two systems:

CHANNEL BREAK OUT SYSTEM CBO

Buying or Selling on a new x day high, or low, and closing theposition out on a new y day low or high. For example, i themarket made a new 80 day high, wed enter a long positionsand i it then made a new 30 day low wed exit that position,and vice versa or a short trade, as per the example below.

TWO MOVING AVERAGE CROSSOVER SYSTEMMAX

We plot two moving averages on a chart, as per the exampleand buy when the shorter (ast) moving average crossesabove the longer (slower) moving average:

O course we could also trade the inverse o those t

systems, selling, instead o buying on a new high,selling when the shorter moving average crosse d abothe longer moving average, treating them as countrending systems, so those tests were run as well.

We ra n them in rade station 2 000i, as thats a prodmany will be amiliar with and into which one ceasily import ASCII data iles, but we could hrun it in many other sotware packages such as ExcMathcad or Mathematica etc.

An exhaustive test o every CBO system and MAsystem was run on each o the 21 currency pairs, othe 20 years o data, or every combination o valubetween 5 and 200, in increments o 5 i.e. 40x401,600 tests.

We have approximately 20yrs x 252 trading days xcurrency pairs o daily data = 105,840 days o daMultiply each day by the 1,600 tests, gives us mothan 169 million potential trades, which is statisticaa airly signiicant sample.

Incidentally, this is another major mistake otmade, which one see in orums all o the tim

pe ople having claimed to have o und the ho ly grbecause they ound a system which perormed wover the last three months on a certain instrumehis is clearly o no statistical signiicance athereore such a small samp le will oten be extremmisleading.

TRADING SYSTEMSFX




17/35

ANALYSING THE RESULTS

Afer taking all o the results or each currency pair andconverting them into US Dollars (as USDJPY producesresults in JPY, USDCHF produces results in CHF etc.)

we can create a 3D chart to analyze the results (using RinaFinancials 3D Smart View).

Te results o the two tests are below:

For ease o viewing only the trending hal o the resultsshown and what is striking is that most CB O parametare proitable, whereas the MAX system has a disti

peak, surrounded by many losing parameters .

I the results were always stable, around that same pethen perhaps wed have a robust MAX system too,now lets look at how the two systems perormed ro2003-2009:

Channel Break Out 1993-2003

Moving Average Cross Over 1993-2003

Channel Break Out 2003-2009

Moving Average Crossover 2003-2009




18/35

Again we see the CBO system having the majority o parametersbeing profitable but this time the profitable parameters or theMAX system have completely shifed to the right and the best

parameters, which looked robust or the test rom 1993-2003

became losing parameters in the ollowing years.

I we look closer at the CBO system, we also see that the greaterthe CBO Entry value, the more profitable the results. Goingback to our initial premise, that or any system to be trulyrobust, it must be easily explained and have a sound rationale,this intuitively makes sense. Te act that a market has made anew 100 day high, is much more significant than i its made anew 10 day high and this is born out by the result.

Also we can see that in both CBO tests that a shorter Exitsignal is more robust and profitable in almost all cases, with adistinct high in the 0 to 30 day region. Again this is intuitivelycorrect, as it allows profits to run, but cuts losses:

I the market made a new 100 Day high and we entered a longposition, with an exit at a new 15 day low, its going to exit thetrade relatively quickly i it went against us, but it will have theability to re-enter the long position, should the market thencontinue to rally and make a new high.

So lets now look at the CBO results a little closer. WilliamEckhardt in his interview in Jack Schwagers Market Wizardstold us:Te general idea is that what works most o the time is nearly

the opposite o what works in the long run.

Above is a 3D plot o the percentage o trades that wprofitable with the CBO system, using the 2003-20

results or illustrative purposes.

Here we can see that the majority o trades are losing tra in act, at best, only 30-40% o the trades are profitaand this is again similar or the previous 10 years o da

We can also look at the Profit Factor, which we touchon in the first article o the series. Te Profit Factor is Gross Profits o all winning trades divided by the GrLosses o all the losing trades. For example, i all

winning trades made $1.1mio and all o the losing tralost $1mio, we would have a Profit Factor (PF) o 1.= 1.1Again using the 2003-2009 results, we can see that although

system produces robust results, the edge is only in the rangeto 1.2, at best. I we recall the casino comparison though, a casiedge, when a player bets on red, or a roulette wheel with tzeros, is 20/18 = 1.1111 (where the casino wins on any black slots), plus the zeros (2 slots).

By contrast, i we look at the MAX System or the two periodssee much better results in terms o both profitability and PrFactor, with the Profit Factor exceeding 2.5 or some resin the 2003-2009 test.

TRADING SYSTEMSFX




19/35

However, remember that had we have chosen what looked

to be the most robust results and started trading in 2003,those same parameters would have actually lost moneyin the ollowing years. As Victor Sperandeo observedabove,

Any system or method based on optimization will ail in thelong run. Tis is because markets change and evolve, theydo not remain constant. So i you structure a system based

solely on the past, it cannot survive the uture.

CONCLUSION

Intuitively, the results o this analysis are logiand rational, as there is very little importan

psychologically, or other wise, that two arbitrmoving averages have crossed, no matter how gothe results may look or a given currency pair, ovegiven time period. his is true o an ininite numbo systems, as almost any system can be show

proitable over a g iven time period on certain marke

his uels the belie that systematic trading doeswork consistently and that systems work or shperiods and then stop working . hat is absolut

true in the vast majority o cases, but there are cleaa number o ideas, as we have seen, which are robuas Jim Simons (Renaissance echnologies), Monrout and oby Crabel would all certainly ag

with and to which their returns stand as irreutatestament.

When testing the CB O strateg y, we hconirmed our initial theory that, the longer term, markets trend. For robust application o that idea one would not

to pick the best results rom the simulations, bsimply to apply some robust rules and sound monmanagement principles.

hat the market has made a new high or low apar ticularly a new long term high or low is importaand will likely always remain important, bo

psychologically and in terms o being the ver y deinito a trend, that the market is making higher highs.

hereore, next time you hear someone talk abohow important it is that a market has crossed a certmoving average, that the Elliott Wave is about to maan abc correction, or a om DeMark reversa l has bemade, ask whether theyve done the maths, and i thhavent, or have only done so with small samples, speciic markets, with limited time rames, or hoptimised the results, then probably best to just sm

politely, say many thanks and ask whether the marhas also made a sig niicant new high or low.

MAX System 1993-2003

MAX System 2003-2009




20/35

In the last article in the series, we discussed robusttrading ideas, comparing moving averages with a channelbreakout strategy, showing how the latter is o muchgreater value and how using a moving average systemmay show great results in back testing but can be atallylawed in actual trading.

he channel breakout strategy, while having lessimpressive perormance statistics during in sampletesting, showed robust perormance over time, with thesame parameters providing a robust edge, over time.

he reason that channelbreakout systems havestood the test o time islikely because marketstrend in the long term anda new multi-month highis always going to havemuch more psychologicalsigniicance than thecrossing o two arbitrarymoving averages. heindings stronglysupport the argumentthat any system basedon predictable market

behaviour, is likely to be much more robust than onebased on arbitrary mathematical algorithms.

hereore, in this article we are going to explore anotherexploitable aspect o predictable behaviour in themarkets, which is much shorter term in nature; namely

when traders start and end their trading day. his hasbeen exploited in the utures markets with strategiessuch as the opening range breakout.

VOLUME AND TIME OF DAY

Monroe rout, who amously made billions out systematic trading, made some interesting observatiabout the utures markets when asked about the mliquid times o day, in his interview in Te New Mar

Wizard by Jack Schwager.

Te most liquid period is the opening. Liquidity starts alloff pretty quickly afer the opening. Te second most liquid to day is the close. rading olume typically orms a U-shap

curve throughout the daGenerally speaking th

patterns hold in almevery market. Its actua

pretty amazing.

While the oreexchange markets hno fixed open, nclose, being ragmenbetween banks, brokelectronic trad

platorms and time zonthey too still display v

predictable behaviour.

I have never seen similar analysis done on the oreexchange markets beore, nor seen a strategy publishbeore to exploit the phenomenon.

Tis is probably because it is impossible to get accurahistoric, or real-time volume data or oreign exchanHowever, it is possible to sample the market and compthe findings with other known volume inormation,determine the volume profile or oreign exchange:

Exploiting the Volume Profile




21/35

he EBS (Electronic Broking Service) tradingplatorm is the larg est liqu id it y provid er an d wecan compare this to data also kindly provided byBarclays, rom their BARX trading platorm. heirst two graphs below show the percentage o daily

volume trad ed or e ac h h our o the day, or the maj orcurrency pairs.

In both cases, we can see a very similar patternemerging. Aggreg ating the results shows thedistribution much more clearly:

Just as Monroe rout ob serve d or the u turesmarkets, although the oreign exchange marketshave no ixed open, nor close and are traded twenty-our hours a day, they too ollow a very predictable

pattern every da y.

When the ag gregated vo lume a cross all c urrenc y pa ir sis plotted as a single graph, we can clearly see three

distinct, ascending peaks o volume as irst Asia athen Continental Europe, London and then the Utrading sessions start. Many surveys have been doto determine the major turnover or oreign exchanby trading centre, most n otably the riennial Sur vrom the Bank o International Settlements, l

publ ishe d in 20 07.

hereore, we know that the three largest tradcentres are London, Continental Europe and ththe US. Its thereore not surprising to see that largest volume o the day is during those ew ho

between 1pm and 4pm, during the London aternowhen the thre e trad in g centres are ac tive . his evholds true or major Asian currencies such as t

Jap anese Yen that are no t native ly ac tive during thtime.

EXPL OITATION OF VOLUME

It is a very well proven and accepted principle trading that volume conirms a trend. I one wlocked in room, without access to any news and wonly able to see price and volume, any major eve

woul d be rel ec te d in that inormatio n. I there wa sudden move but little volume then its unlikthat move was genuine. I however, an event suas 9/11 occurred, one would have seen both a larange in the price as well as a signiicant increasetrading volume. his type o volume conirmatallows a trader to know whether a move is o g enusigniicance.




22/35

his is one o the edges I enjoyed as a trader, while sittingon the oreign exchange desk at a major investment bank.

We could physically see the customer low going through

and literally elt it, with the increase in noise. Whetherconsciously or not, a trader at a major investment bankcannot help but be aware o an increase in trading

volume, just as a trader on the loor o an exchange issimilarly aware.

It is actually almost impossible not to be aware o theinterest building in a certain currency pair and this issomething that almost certainly contributes to whattraders oten reer to as their eel, or gut instinct. Its alsolikely the reason why so many traders ind the transition

rom a banks dealing room to trading successullyoutside it, to be so diicult.

One o the major challenges or an FX trader, outsidea banks dealing room, is that actual traded volumeis not available in real-time across such a ragmentedmarket, so it is very diicult to know when the volumeis increasing. However, what the FX trader does know, isthat any move occurring between 1pm and 4pm is verylikely taking place on increasing volume, at the highest

volume time o day. hereore going with a move duringthose ew hours is likely to provide a signiicant edge,over time.

TRADING STRATEGY

here are many ways to deine a move, such as a changein momentum, expansion o the range, the divergence otwo moving averages, the RSI crossing through the 50%level, or even standard deviations. However, let us takethe simplest deinition o a trend, being that o a new

high or low.

We know that the lowest volume time o day is the NewYork close, or 10pm in London and highest volume isbetween 1pm and 4pm. hereore, i we consider theNew York close to be the end o one trading day and thebeginning o the next, we can apply a simple trading ruleto test our theory:

Buy i th e ma rket ma kes a ne w hi gh or se ll i it maa ne w low, be tw ee n 1p m an d 4pm .

his simple strategy, without any monmanagement, or stops, produces the ollowireturns, based on a 100,000 account, with t

por t ol io bei ng an aver age o the thre e equcurves.

Slippage, c osts and interest have not been includas these will vary rom account to account, thou

these actors are more than oset by the additionsome basic money and risk management principl

We ca n see that the tradin g rule do es nt mamoney in all currency pairs in all years and hsigniicant drawdowns, as well as extended perioto new equity highs . However, going with a moduring the London aternoon clearly providesrobust trading edge, whether used in isolation, as a ilter to be used in combination with othtrading strategies.

Again, as with the other behaviour discussed in tseries o articles, we can see that while there acountless trading strategies that may work or sh

periods o time, base d on ar bi trar y ma th emat ialgorithms, there are some trading strategies thare genuinely robust, based on sound, predictamarket behaviour.




23/35

In the last article we looked at the commonality o volumedistribution and ranges across currency pairs. We examinedhow similar they are throughout the 24 hour trading day,

with even currencies such as the Australian Dollar andJapanese Yen having the largest volumes and hourly rangesduring the London afernoon, when the three major tradingcentres o Europe, London and the US are all active, as

opposed to their own native time zones.Having explored the commonality, this article now exploresthe key differences between each currency pair, which canbe broadly categorized into: time zones, liquidity, volatilityand interest rates.An understanding o these differences, that give eachcurrency pair its unique characteristics, is important indetermining whether using different parameters is curvefitting or genuinely taking account o the unique andquantifiable characteristics o each market.I the data during a back test was trending, then different

parameters will likely appear to be better than a currencypair that was moving sideways during the test period.However, that is no indication that the currency pairs willcontinue trending, or moving sideways in real trading, soa good understanding o why a system works is vital, i itsgoing to be robust and continue to work in the uture.All times are expressed in local London time, unless statedotherwise.

TIME ZONES

We know that the London aternoon has the largranges and volumes or all currency pairs; however, also know that news events and economic data aecta certain currency will almost always occur during tcurrencys native time zone.

We also know that currencies are traded in pairs, smove in GBPJPY at 2am is more likely to be a Yen mand a move at 10am is more likely to be a Sterling moCurrency pairs can thereore be broadly broken dointo three categories:

Know Your Currencies




24/35

1/ Currencies sharing the same native time zone:Currency pairs such as EURSEK, EURNOK, EURCHF,USDCAD, and within an hour o each other; GBPCHF,AUDJPY and USDMXN, all share the same native tradinghours.Tis gives these currency pairs particularly good liquidityduring their native trading sessions, particularly those

whose native trading sessions occur during the Londonafernoon.2/ Currencies with overlapping native time zones:Currency pairs such as GBPUSD, EURCAD,USDCHF, EURUSD, AUDUSD andNZDUSD have native time zones that overlap.

Tereore a move occurring at 5am in EURCAD ismore likely to be order driven, as there is little volume,news, nor economic data likely to have come outaffecting that pair during those hours and would makesuch a move less likely to be a genuine market move.3/ Currencies with separate time zones:Currency pairs such as EURAUD, GBPJPY andCHFJPY operate in two very distinct sessions, withtheir native trading hours not overlapping at all.

Local ime in London

Currency GM Start End

New Zealand (NZD) +13 18:00 04:00

Australia (AUD) +10 21:00 07:00

Japan (JPY) +9 22:00 08:00

Hong Kong (HKH) +8 23:00 09:00

Singapore (SGD) +8 23:00 09:00

urkey (RL) +2 05:00 15:00

Europe (EUR) +1 06:00 16:00

Switzerland (CHF) +1 06:00 16:00

Norway (NOK) +1 06:00 16:00

Sweden (SEK) +1 06:00 16:00

Great Britain (GBP) +0 07:00 17:00

Canada (CAD) -5 12:00 22:00

United States (USD) -5 12:00 22:00

Mexico (MXN) -6 13:00 23:00Figure 1

I one were to express a view in Sterling 10am against the US Dollar, or Japanese Ythat position would be ar less likely to aected by news in the other currency, thtrading against the Euro or Swiss Franc, whimay have their own news, or economic dareleased during that time, aecting the positioSimilarly, taking a view on the Pound at 3against the Japanese Yen is more likely to aected by news or economic data in Japan that time o day and has more o a Yen exposuhereore, any trading system malso take into account the time it

being executed or each currency paFigure 1 illustrates the native trading hours each currency expressed in GM.

LIUIDITYSome pairs are more actively traded than othand this has a direct relation not only to thspreads, but also their behaviour. Although ea

pair ma y ha ve th e highest volum e dur ing tLondon aternoon, as we saw in the last artic

some currency pairs are still ar more liquid thothers, throughout the day.Figure 2 lists the currency pairs in approximorder o liquidity, with EURUSD, USDJPY aGBPUSD accounting or 52% o all FX volu(source: Bank o International Settlemenriennial Central Bank Survey o Foreign Exchanand Derivatives Market Activity, April 2007).his makes the spreads, and thereore slippaand cost o execution, much smaller in the moliquid currency pairs. hereore a strategy this equally proitable in EURUSD and AUDCA

wi th out slippage wil l not be nearly as pro itain AUDCAD in live trading, when spreaand slippage are actored in, due to the mu

wi der spre ads and rel at ive lack o l iquidity AUDCAD.Its also usually better to trade an illiqui d cross its components. For example, selling AUDUS




25/35

and selling USDCAD results in a net shortAUDCAD position. rading via the componentsin this way usually captures a better spread than

the trade being done direct in relatively illiquidcrosses.

urnover in Billions (USD) % Share

EURUSD 840 27

USDJPY 397 13

GBPUSD 397 12

AUDUSD 175 6

USDCHF 143 5

USDCAD 115 4

USDSEK 56 2

USD/Other 572 19

EURJPY 70 2

EURGBP 64 2

EURCHF 54 2

EUR/Other 112 4

Other Pairs 122 4

otal 3 081 100 Source, BIS riennial Survey 2007

Figure 2

Unortunately that also doubles the brokerage costsper mi ll io n, versus beingable to execute the tradedirect in AUDCAD, as twotrades are done instead oone. his eect is even more

pronounc ed i the strateg ywas exec uted during relatively

illiquid times o day.Further exacerbating thesituation is the act that stoploss orders can only be letdirect, without the use oan API, usually resulting inmuch more slippage whenorders are executed in themarket .

VOLATILITYVolat i l ity is a measure o how much a curren

p a ir i s mo ving , usua l l y me a sure d by ta kin g tstandard deviat ion o movement , over a g ivt ime period and expressed as a percentaraders wil l oten reer to 1 month vol . astandard measure o volat i l ity .Essent ial ly it expresses how much a marketmoving over a g iven t ime period . A mark

with a low vo lati l i t y i s e xp e cte d to have sma lmo ve s o n a g ive n d a y t ha n t ho se w it h a hi

vo lati l i t y.For the trader , higher volat i l ity is usual l y goo

as proit s tend to be made rom movemenwith a e w exc ep tions su ch a s s ome op tiost r a t e g ie s .Volat i l ity a l so has a direct impact on whetha s t r at e g y i s v ia b l e . I a c u r r e nc y p a ir ha s average slippage per trade o 3pts but an averareturn per trade o 10pts , then s l ippage wour e d u c e t he p r o i t s b y 3 0 %.I the same strategy were traded on a curren

p a ir with a t wic e the vo lat i l i t y, b ut the saslippage o 3pts, it may yield an average return

20pts per trade , as the average dai ly movemewou ld b e h ig her. S l ip p a g e wo u l d th en onr e d u c e t he p r o i t s b y 1 5 %; ha l t he a mo u n t .




26/35

Sl ippage can be such a huge actor that somehigh requency strategies , which look excel lentbeore s l ippage is taken into account , can actual ly

produce a s ig ni icant l oss i a ctua l ly t rade d u nderreal market conditions. hereore you oten seevolati l it y i lters adde d to strateg ies and theseare oten simply a unction o the minimum

volati l it y the market ne eds to b e trading at , orthe strategy to overcome costs and to be viable ;this wil l var y both rom currency pair to currency

pa ir and e ven by time o day.hereore , i a strategy is ound to be a losingone ater s l ippage is added, but was proitablebeore , then a s imple volat i l ity i l ter may be a l l

that is required, to trade only when the expectedmovement is above a certain amount .

INTEREST RATESInterest rates are another known, andquantiiable, actor aecting currency markets.able 3 shows the current interest rates o themajor currencies .

Currency Interest RateNew Zealand (NZD) 2.50%

Australia (AUD) 4.00%

Japan (JPY) 0.10%

Hong Kong (HKH) 0.50%

Singapore (SGD) 0.25%

urkey (RL) 6.50%

Europe (EUR) 1.00%

Switzerland (CHF) 0.25%

Norway(NOK) 1.75%

Sweden(SEK) 0.25%

Great Britain (GBP) 0.50%

Canada (CAD) 0.25%

United States (USD) 0.25%

Mexico (MXN) 4.50%

As o 2nd March 2010able 3

rading strategy simulation sotware has tendto overlook the eect o interest rates on currentrading, as that is not something that aects maother markets. However, or a longer-term stratethe eect can be particularly signiicant, hence tcarry trade.I one were to hold a long AUDJP Y position overnigthen that position would have a positive yield, carry, overnight as the position was rolled. tends to give carry trade currency pairs an underlytrend, oten characterized by sharp corrections, ndissimilar to the price action o a stock market.Its thereore vital to know i a strategy is workibecause o an underlying interest rate dierentas these can change dramatically over time and evinvert.




27/35

TRADING SYSTEM RO BU ST NE S S

W h e n t e s t i n g a t r a d i n g s y s t e m , o n e s i g n o r o b u s t n e s s i s t h a t i t w o r k s a c r o s s a b r o a dr a n g e o i n s t r u m e n t s . H o w e v e r , w h e n t e s t i n g

a c u r r e n c y s t r a t e g y a c r o s s a b r o a d n u m b e r o c u r r e n c y p a i r s , i t s i m p o r t a n t t o a p p r e c i a t ew h y i t m a y s h o w v e r y d i e r e n t r e s u l t s a n d t or e a l l y u n d e r s t a n d t h e s i m i l a r i t i e s , a s w e l l a st h e d i e r e n c e s b e t w e e n e a c h c u r r e n c y p a i r .F o r e x a m p l e , c u r r e n c y p a i r s w i t h s t r o n gi n t e r e s t r a t e d i e r e n t i a l s a r e m o r e l i k e l yt o s h o w t r e n d i n g c h a r a c t e r i s t i c s . H o w e v e r ,o t h e r c u r r e n c y p a i r s m a y t r e n d e v e n w i t hl i t t l e i n t e r e s t r a t e d i e r e n t i a l ; t h e u n d e r l y i n g

r e a s o n o r t h o s e t r e n d s w i l l l i k e l y b e d i e r e n ta n d n e e d s t o b e c o n s i d e r e d . h e r e o r e y o u h a v e t o l o o k a t t h e r e s u l t s o a n y s i m u l a t i o n t o d e t e r m i n e w h e t h e r t h e r e i sa v a l i d r e a s o n o r t h e r e s u l t s b e i n g d i e r e n t ,b e o r e b e i n g a b l e t o t r u l y d e c i d e w h e t h e r as y s t e m i s r o b u s t o r n o t .O n e a l s o h a s t o l o o k a t t h e p r i c e a c t i o n i t s e l a n d c o m p a r e t h e e q u i t y c u r v e o t h e s y s t e m

t o t h e p r i c e a c t i o n . m a y b e t h a t t h e s y s t e

w o r k e d p a r t i c u l a r l y w

i n a t r e n d i n g m a r k e t , a s i d e w a y s m a r k e t , i w a s m e a n r e v e r t i n g n a t u r e .

J u s t b e c a u s e a s y s tw o r k s o n o n e c u r r e np a i r a n d n o t a n o t hd o e s n o t m e a n i t i s nr o b u s t . I t m a y j um e a n t h a t o n e c u r r e n

p a i r e x h i b i t e d a s t r o

t r e n d d u r i n g t h e t ep e r i o d a n d t h e o t hd i d n o t a n d t h a t mh a v e b e e n d u e t o a s h on e w s e v e n t s u c h a s 9 / 1

a n u n d e r l y i n g i n t e r er a t e d i e r e n t i a l o r a s t e a d i e r s h i t i n m a r k u n d a m e n t a l s .C O N C L U S I O N

h e c u r r e n c y m a r k e t s s h a r e m a n y s i m i lc h a r a c t e r i s t i c s i n t e r m s o b e i n g a g l o bm a r k e t , w i t h s i m i l a r e b b s a n d l o w s i n v o l ua n d r a n g e s , a s e a c h c e n t r e o p e n s a n d c l o s eH o w e v e r , t h e y a l l h a v e t h e i r o w n i n d i v i d uc h a r a c t e r i s t i c s i n t e r m s o t i m e z o n e s w hn e w s m a y a e c t t h a t c u r r e n c y , l i q u i d i

v o l a t i l i t y a n d i n t e r e s t r a t e s . E v e n t h o ut w o c u r r e n c y p a i r s m a y s h a r e m a n y o t h ec h a r a c t e r i s t i c s , e v e n d a t a r e l e a s e s o r o

c u r r e n c y w i l l n o t a l w a y s o c c u r o n t h e s a md a t e a n d t i m e a s a n o t h e r . h e r e o r e , a t ag i v e n t i m e , h a r d l y a n y c u r r e n c y p a i r s ai d e n t i c a l i n n a t u r e b u t t h e i r d i e r e n c e s au s u a l l y q u a n t i i a b l e . h e r e o r e , w h e n t e s t i n g t r a d i n g s t r a t e g ia l l t h e s e a c t o r s s h o u l d b e t a k e n i n t o a c c o ut o b e a b l e t o d e t e r m i n e w h e t h e r a s y s t e m , aa n y g i v e n s e t o p a r a m e t e r s , i s t r u l y r o b u s t




28/35

As this is the last article in the series, Id like tointroduce the proprietary Marney Indicators,

which have helped me to create proita ble tr adingstrategies by identiying and exploiting non-random behaviour.

Having learnt a great deal rom other traders,sharing their insights on the markets, I hope thatthey wil l ser ve as a worthy contribution.

he indicator s illustrate a lot o the research thathas been discussed in the previous articles; thecommonality o currencies as well as their uniquedierences, how increasing volume and rangeconirm a trend, as well a s the importance o t imeas an indicator.

I was surprised not to have ound these indicatorsalready written elsewhere, as research and backtesting has shown that they provide a signiicantedge, in exploiting non-random and thereore

predictable behaviour.

Researc h with EBS data has sh own that the numbero price updates per unit o time, correlates veryhighly to actual volume traded. hereore, while

actual volume is not readily available or Fmany data providers now include the number

price updates, so th at they can be plotted, asprox y or volum e and th is can be exploited usithe Marney Volume Indicator (MVI).

MARNEY VOLUME INDICATOR

he MVI plots a t ime-adjusted proile o volumthroughout the twenty-our hour trading day. Aexample o the Marney Volume Indicator is sh owbelow, applied to a 60min chart o EURGBP.

I have used MultiChar ts to illustrate and co de texamples and Olsen Financial as the data souras they have one o the longest historical databaavailable or oreign exchange, together with t

number o price updates, as a proxy or volume

he histograms show the hourly volume, via tprox y o price updates . I th e corresponding howas an up event th en the bars are coloured bland red or a down event.

he vertical dashed yel low l ine is a session breashowing 0000hrs G M.

Marney Indicators




29/35

he top yellow line is the Marney VolumeIndicator (MVI) and the bottom yellow line isa simple moving average applied to the volume,showing the dramaticdierence that t ime-adjusting the average makes.

he MVI line shows thetime-adjusted average overthe previo us 50 session s. Bytime-adjusting the averages,the unique, predictable

proiles o each cur ren c ypair are revealed. i .e . th e

volume rom 0000hr s to0100hrs is taken or the

previous 50 sessions and th eaverage is plotted, ol lowedby 0100hrs to 0200hrs oreach o the twenty-ourhours in the trading day, byusing arrays in the code orthe indicator.

he Marney VoluIndicator thereo

provides a s igniicaimprovement over tclassic volume rule simply looking or aboaverage volume.

For any given time o dwe th ereore know not onwhether volume is aboor below average but how much, or that ti

o day also whether it likely going to increase decrease.

MARNEY RANGE INDICTO

A similar technique can applied to ranges, taking the true range or eahour o the day over a preceding number o daand plotting that as a t ime-adjusted average. illustration is shown below using the same




30/35

EURGBP data, showing the Marney VolumeIndicator as the top study and the MarneyRange Indicator as the bottom study.

As described in FX rader Magazine Jan-Mar2010 edition , by studying historic data , we knowthat both hourly volumes and range s throughoutthe trading day are both highly correlated and

pre dictable. By plotting b oth the MVI and MRItogether we can see this in real -t ime.

he chart below shows the indicators applied toAUDJPY.

As we might expect, the ranges and volumes aremuch higher during the Asian session than or

a currency such as EURGBP and the peaks aremuch more deined when Asia, Europe and thenthe US enter the market.

We a lso se e the hig hest volumes and rang es orAUDJPY during the London aternoon session,although not a natively active t ime zone orthe currency pair, a common characteristico currency pairs, previously identiied and

explained in this ser ies o art ic les .

REALTIME VOLUME AND RANGE ANALYSIS

A s i l l u st r a t e d in t he l a st a r t ic l e , p r o i t a bt r a d in g s t r a t e g ie s c a n b e d e v e l o p e d r o m b e ia b l e t o p r e d ic t w he n t he hig he st vo l u me s ar a n g e s d u r in g t he d a y a r e l ike l y t o o c c u r in in d iv id u a l ma r ke t .

B y b e in g a b l e t o p l o t e x p e c t e d vo l u me ar a n g e s in r e a l - t ime , t ho se c o n c e p t s c a n

e n ha n c e d e ve n u r t hUsin g t he M V I a n d M R

w e c a n s e e w he th er tc u r r e n t r a n g e a n d vo l u mis hig he r o r l o w e r t he x p e c t e d o r a g ive n t imo day .

I t he ma r ke t i s ma kia n e w hig h a n d b ot he r a n g e a n d vo l u me hig he r t ha n e x p e c t e d that t ime o day , then tmo ve ma y b e c o n sid e rt o b e mo r e s ig n i ic aa n d c o n ve r se l y i a moo c c u r r e d o n p a r t ic u l al o w vo l u me a n d r a n g e , t hi t mig ht b e c o n sid e rl e s s s i g n i i c a n t .

I ha ve c a r r ie d o u t a c o n s id e r a b l e a mo u n t r e se a r c h a r o u n d t his b a s ic id e a a n d o u

a n u mb e r o w a y s t ha t t he se in d ic a t o r s cb e u se d , t o p r o i t a b l y e x p l o it p r e d ic t a bb e ha vio u r in t he ma r ke t s .

he c o d e o r b o t h in d ic a t o r s i s a va i l a b o r r e e r o m my w e b si t e a n d I ho p e t ha t

p r o vi d e s r e a d e r s w i th a n a d d i t i o na l e d g e t he ir t r a d in g , w he t he r sy st e ma t ic a l l y o r a s a d d it io n a l t o o l o r d i sc r e t io n a r y d e c i s io n s .




31/35

C O N C L U S I O N

his se r ie s o a r t ic l e s ha s b e e n t he r e su l t

y e a r s o r e s e a r c h , l e a r n i n g m a n y e x p e n smistakes a long the way , such as identiy ia r b i t r a r y m a t h e m a t i c a l a l g o r i t h m s t ha p p e a r e d t o b e t h e H o l y G r a i l , i n d is y s t e m s t h a t w o r k e d p a r t i c u l a r l y w e l l s o m e m a r k e t s b u t n o t o t h e r s a n d s y s t et h a t a p p e a r e d t o w o r k w e l l b o t h i n a n d oo sa mp l e .

A l m o s t a l l o t h e s e i d e a s a n d d i s c o v e rw e r e l a w e d .

I h a v e l e a r n t t h a t e a c h m i s t a k e w a s , i n s ow a y, a r e s u l t o e i t h e r o ve r o p t i m i s a t i o n , c u r ve - i t t in g , e ve n i in a d ve r t e n t l y . I hot h a t t h e s e a r t i c l e s h e l p o t h e r s t o a v o i d m ao t h e p i t a l l s o b u i l d i n g t r a d i n g s y s t et h a t i t h a s t a k e n m e y e a r s t o l e a r n ; w i t h d o u b t m a n y l e s s o n s s t i l l t o b e l e a r n t .

o s u m m a r i s e , i n a e w s i m p l e r u l e s :

K e e p i t s i m p l e i a s y s t e m l o o k s t o o g o o db e t r u e , i t p r o b a b l y i s .

h e r e i s n o H o l y G r a i l o n l y a p p l y ia s m a l l r o b u s t e d g e w i t h c o n s i s t e n c y ad isc ip l in e , o ve r a p o r t o l io o in st r u me n

w i t h g o o d r i s k m a n a g e m e n t .

A vo i d a r b i t r a r y o r m u l a i y o u t e s t e n o up a r a m e t e r s , y o u w i l l a l w a y s i n d s o m e t h

w o r k , b o t h i n a n d o u t o s a mp l e , o r o n s oma r ke t s . ha t d o e sn t me a n t he y r e r o b up a r a m e t e r s , n o r e ve n r o b u s t i d e a s .

D o b a s e s y s t e m s o n m a r k e t b e h a v i o u r t hc a n b e e x p l a i n e d a n d u n d e r s t o o d .

R e me mb e r t ha t n o t hin g in t he w o r l d c a n t at h e p l a c e o p e r s i s t e n c e .

input:avgLen(10),mins.

in.session(1440),autobars(True),

upcolor(cyan),dncolor(red);

var:start(0),end1(0),end2(0),x(0),p(-1),count(0),avg(0),

barsinday(0),DayNumber(0);

array:xv[199,1440](0);

ifbartypeend2then

value3=1440+(value2-value1);

ifstartopenthensetplotcolor

(2,upcolor);

ifclose1thenbegin

avg=

averagefc(v,avglen);

plot2(v,ticks,default

,1);

plot1(avg,avg,yellow,

default,1);

ifclose>openthensetplotcolor

(2,upcolor);

ifcloseopenthensetplotcolor

(2,upcolor);

ifclose


32/35

INTRODUCTION

Te objective o this article is to analyse the relationshipbetween actual traded volume in the FX markets andits relationship to price updates, or tick volume, overboth time and across currency pairs, to determine

whether there is a highcorrelation between thetwo.

We do not be lieve thatthe research has been

publ is he d be ore . G iventhe conclusive results,

we hope it proves aninteresting additionto the debate, as to

whether tick volumecan be used as a proxyor traded volume inthe FX markets.

FX VERSUS FUTURESMARKETS

Volume inormation hasbeen proven in manystudies to provide an edge

in trading. FX radershave thereore been at adisadvantage to Futurestraders, as volumeinormation is not beenreadily accessible in the FX markets, let alone in real-time.As discussed in previous articles, Futures markets, bydeinition, are traded on an exchange. hereore, all

transactions or a particular instrument are traded a central exchange making deinitive, real-time, voluinormation readily available.

By contrast, the FX markets are incredibly ragmenttraded between banks, financial institutions, hedge un

proprietary tradfirms and individtraders on a twenty-hour basis through

vast array o ElectroC o m m u n i c a t iNetworks (ECNand direct inter-barelationships.Tereore, there is no w

to accurately record toFX volume in real timas there is in the finanFutures markets, hethe debate as to whetthe number o prupdates can be used a

proxy or volume.

PRICE UPDATA S A PROX

FOR VOLUM

One way that activcan be gauged in the market is by record

the number o price updates, per unit o time, as mtrades should equate to more price updates. Howethere has been a great deal o debate about the accuro price updates as a proxy or volume and there

Are price updates a good proxyor actual traded volume in FX?

Te FX markets are incrediblyragmented; thereore there

is no way to accurately recordtotal FX volume in real time




33/35

many valid reasons to suggest that there might not be a

high correlation:

Te price may move without any volume; if forexample, there has just been a news announcement. Te price may change many times on light volume, ornot at all on high volume, i a large buyer trades with a seller oequal size. If the range for a unit of time (represented by a baron a chart) is high, then the price is more likely to changemany times, to reflect the many changes in price, regardlesso volume

Similarly, if the range is small, then there will likelybe relatively ewer price changes than a bar with equal volumethat had a large change in price.

ACTUAL VOLUME VS. PRICE UPDATES ANALYSIS

With volume analysis potentially able to provide such asignificant edge to trading decisions, we were surprised that wecouldnt find the research having been done anywhere beore,to provide a definitive answer to the debate.Tereore, with data rom two o the worlds largest ECNs,HotSpot and EBS, as well as one o the leading providerso price updates, Interactive Data, we had a large database oboth actual traded volume data, as well as the respective priceupdates, to determine how high the correlation was betweenthe two, and whether it was consistent over time.In order to establish conclusive correlation between tick

volume and traded volume, it was decided that the datarom two separate vendors would be analysed across a range

o currencies, both against the tick volume provided eSignal and, in the case o HotSpot, against its own intertick volume. Te currencies chosen or this research wEURUSD, USDJPY, GBPUSD and EURCHF. We wo

look or correlation first visually, then through the usetraditional measures such as Pearsons product-momcoefficient.

Once the data provided by HotSpot and EBS had becleaned and structured, the timestamp or each tradeany currency pair was used to determine which hour o day the trade took place within. Te volume o each tr

was then placed in one o 24 buckets, creating a histogro traded volume by hour o day; readers amiliar with Marney Indicators will quickly recognise the p

biulding robust ts

Documents