Ultimate Algorithmic Trading System

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20120531 921 -40820120629 -1735 -214320120731 955 -1188One last bit of code that shows off the power of Python follows. After this, I willdemonstrate how to pull all this together and test a trading algorithm.for i in range(0,len(masterDateList)):cumuVal = 0for j in range(0,len(self.systemMarkets)):skipDay = 0try:idx = self.systemMarkets[j].equity.equityDate.index(masterDateList[i])except ValueError:skipDay = 1if skipDay == 0:cumuVal += self.systemMarkets[j].equity.dailyEquityVal[idx]combinedEquity.append(cumuVal)This snippet of code is important because two very important concepts arecovered. If you review the code, you will see the keyword try: The code controlledby try is simply finding if and where the last day of a month is located in asystemMarket’s equityDate stream. Let’s say we are trying to see if July 31,2012, is in an equityDate list. If it is, then the variable idx returns the locationin the list. If it’s not located in the list, then an error is returned. This is whereexcept comes into play. The code controlled by except is only executed if themethod index returns an error. Back to the Python Shell!Type the following and hit enter after the last line:>>> a = list()>>> a = [100,300,200,800]>>> a.index(300)1This example returns the location of the number 300 in the a list. Remember Pythonis zero based. The first element is number 0.193USING PYTHON TO BACKTEST YOUR ALGORITHM■ Getting Down to BusinessOkay, we now have somewhat of an understanding of how the PSB works. I designedit to be like one of those calculators or watches that is encased in see-through plastic.Everything is there if you just look for it. However, just like the watch or calculator,www.rasabourse.com
you don’t need to know exactly how one works to use it. This software allows theusers to do whatever they want, including looking into the future, so be careful.Our first test is going to be the ol’ Bollinger Band algorithm.194USING PYTHON TO BACKTEST YOUR ALGORITHMfor i in range(len(myDate) - numBarsToGoBack,len(myDate)):equItm += 1tempDate = myDate[i]todaysCTE = todaysOTE = todaysEquity = 0marketPosition[i] = marketPosition[i-1]mp = marketPosition[i]buyLevel,shortLevel,exitLevel = bollingerBands(myDate,myClose,60,2,i,1)print(tempDate," avg ",exitLevel," ",buyLevel - exitLevel)atrVal = sAverage(trueRanges,10,i,0)rsiVal = rsiStudy.calcRsi(myClose,10,i,0)stopAmt = 3000/myBPV# print(myDate[i],"rsi ",rsiVal," atrVal ",atrVal*myBPV," ",myBPV)# fastKVal,fastDVal,slowDVal = stochStudy.# calcStochastic(3,9,9,myHigh,myLow,myClose,i,1)# if (mp > 0 and maxPositionL < 3) : maxPositionL = mp# if (mp < 0 and maxPositionS < 3) : maxPositionS = mp#Long Entry Logic - Bolloingerif (mp == 0 or mp == -1) and myHigh[i] >= buyLevel:profit = 0price = max(myOpen[i],buyLevel)if mp <= -1:profit,trades,curShares = exitPos(price,myDate[i],"RevShrtLiq",curShares)listOfTrades.append(trades)mp = 0todaysCTE = profittradeName = "Boll Buy"mp += 1marketPosition[i] = mpnumShares = 1entryPrice.append(price)entryQuant.append(numShares)curShares = curShares + numShareswww.rasabourse.com
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THE ULTIMATEALGORITHMICTRADING SYST
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THE ULTIMATEALGORITHMICTRADING SYST
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CONTENTSAbout the authorIntroductio
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Reproduction 238Mutation 240Using G
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ABOUT THE AUTHORIt was March of 198
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Well that was 27 years ago and I di
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xivINTRODUCTION TO THE ULTIMATE ALG
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xviINTRODUCTION TO THE ULTIMATE ALG
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CHAPTER 1Introductionto TradingAlgo
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However, at this introductory stage
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completely above the tableau. If th
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Don’t get bogged down trying to u
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checking account was down the $10K,
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Short Liquidation Condition—What
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One BarStrengthTwo BarStrengthThree
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and inexperienced trading system pr
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Input = 6StartInput = 4Input <> 6In
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The diagram in Figure 1.4 looks cle
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observed. If the latter criterion i
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Start or NewBarIs C >AVG(C,200)YesN
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CHAPTER 2Stochastics andAverages an
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The basic theory behind the ADX is
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4. Divide the 14-day smoothed plus
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if myADX < 35 thenif MarketPosition
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TABLE 2.1Performance of Directional
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FIGURE 2.4Source: TradeStationExamp
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Start orNew BarIs RSI < 30YesBuy Ma
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RSI DivergenceMarket Continuing to
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If marketPosition =-1 and close > e
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TABLE 2.3Performance of RSI Failure
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Start orNew BarIs Slow %K CrossingA
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TABLE 2.4Performance of Stochastic
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it is boundless extended readings a
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TABLE 2.5Performance of CCI algorit
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FIGURE 2.11Source: TradeStationThe
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We will discuss moving averages in
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MACDAvg = XAverage( MyMACD,9)MACDDi
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FIGURE 2.13Source: TradeStationThre
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LC0_E0B −25000 −41790 398 −62
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FIGURE 2.14Source: TradeStationA 60
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TABLE 2.8 Performance of Bollinger
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If filterTrade = false thenIf close
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Keltner ChannelChester Keltner brou
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FIGURE 2.15Source: TradeStationKelt
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35000300002500020000150001000050000
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TABLE 2.12Best Parameter Sets of Ke
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CHAPTER 3Complete TradingAlgorithms
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Box 3.1 Turtle System #1Buy one tic
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TABLE 3.1Turtle System 1 without LT
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TABLE 3.3Turtle System 1 with LTLF
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TABLE 3.4Tandem Performance of Turt
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Pause the Battle—Let’s Talk Ris
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Box 3.3 Battle Royale—And the Com
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TABLE 3.5Single Moving Average (SMA
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TABLE 3.8Donchian Channel Breakout
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we have, because who has the time t
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%Winners ShortLen InterLen StopDoll
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on a peak. This demonstrates a lack
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The correlation coefficients range
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TABLE 3.13The Best Results for the
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TABLE 3.17Results for the Donchian
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FIGURE 3.5AmiBroker’s walk-forwar
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direction of the 200-day moving ave
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range day and initially puts on two
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CHAPTER 4Introduction toAmiBroker
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Things All Programmers Need to Know
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expressions deal with a string of c
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AFL uses functions DateNum(), DateT
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to Short and Cover as well. If you
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FIGURE 4.2The AmiBroker Editor wind
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to the user. Instead of having to r
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This is where you can change the va
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shortMav = MA(C,avgLen1);longMav =
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code. This is a very difficult thin
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the order of the arrays. I admit th
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FIGURE 4.17The AFL Code Wizard ‘
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■■■This time click on is grea
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This should look very similar to th
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Page 159 and 160: COND3 = C > MA(C,100);COND1 = cente
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Page 163 and 164: FIGURE 5.1trading.Once you define t
Page 165 and 166: GetDataGET DATACOMPONENTLoad Data i
Page 167 and 168: 152USING MICROSOFT EXCEL TO BACKTES
Page 169 and 170: performance of the trading system.
Page 171 and 172: 156 FIGURE 5.9 The Visual Basic Edi
Page 173 and 174: FIGURE 5.12This error message appea
Page 175 and 176: End IfIf marketPosition = -1 ThenCa
Page 177 and 178: ■■moc—Market On Close order.
Page 179 and 180: Simple Moving Average Crossover usi
Page 181 and 182: Call Trade(ExitShort, "S-ATR Prof",
Page 183 and 184: 168USING PYTHON TO BACKTEST YOUR AL
Page 185 and 186: It works well on both Unix and Wind
Page 187 and 188: function modules and some are a lit
Page 189 and 190: inclusive, the number of iterations
Page 191 and 192: 176This indicator is programmed as
Page 193 and 194: if prices[curBar - offset] < prices
Page 195 and 196: All these files deal with opening a
Page 197 and 198: entryPrice,fileList,entryPrice,entr
Page 199 and 200: Python has a ton of reusable code a
Page 201 and 202: 186USING PYTHON TO BACKTEST YOUR AL
Page 203 and 204: portfolioClass. These classes are n
Page 205 and 206: percent wins, number of trades, and
Page 207: >>> c = a + b>>> cAfter you hit ent
Page 211 and 212: Shorting occurs when the low of the
Page 213 and 214: That was the long entry logic only
Page 215 and 216: FIGURE 6.4brackets.A Python run-tim
Page 217 and 218: prevAvg2 and today’s avg1 must be
Page 219 and 220: ■ TradeStation IDE204AN INTRODUCT
Page 221 and 222: 206AN INTRODUCTION TO EASYLANGUAGEt
Page 223 and 224: FIGURE 7.5The algorithm with a sing
Page 225 and 226: the Vars statement and initialize t
Page 227 and 228: TABLE 7.1EasyLanguage Keywords and
Page 229 and 230: 214AN INTRODUCTION TO EASYLANGUAGEF
Page 231 and 232: standard deviations. In our example
Page 233 and 234: 218AN INTRODUCTION TO EASYLANGUAGEt
Page 235 and 236: into a project makes it easier to a
Page 237 and 238: If marketPosition =-1 thenbeginend;
Page 239 and 240: or program any trading idea. Practi
Page 241 and 242: CHAPTER 8Genetic Optimization,Walk
Page 243 and 244: superfast processors, searching a l
Page 245 and 246: This equation involves four unknown
Page 247 and 248: For generation = 1 To 100 ' total g
Page 249 and 250: Converting Fitness in Terms of Slic
Page 251 and 252: 'the 6 darts landedRandomizeFor l =
Page 253 and 254: roulette(i) = Rnd(1#)If roulette(i)
Page 255 and 256: selection and reproduction may even
Page 257 and 258: This is just one possible solution.
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history of each market. This test w
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Crossover RateThe rate that determi
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TradeStation’s and AmiBroker’s
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TABLE 8.3In-Sample Testing TA2Le Se
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Here are the various calculations t
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1. movAvgLen { 50 to 150 by 10 incr
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TABLE 8.6The Out-of-Sample (OOS) Re
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your algorithm are each written on
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That’s it! These seven lines of c
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[Equity]350003000025000200001500010
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Calculating Start Trade Drawdown Wi
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A loop is used to flow through each
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The maximum drawdown of this algori
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■ Fixed Fractional272PORTFOLIO AN
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FIGURE 9.2Add a strategy to your st
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276FIGURE 9.6The UGTATS markets and
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278FIGURE 9.9 How to adjust the set
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FIGURE 9.12 The Trade Analysis wind
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282PORTFOLIO ANALYSISFIGURE 9.15thi
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FIGURE 9.18 Profit and drawdown are
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FIGURE 9.20 To set the portfolio st
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FIGURE 9.24Source: TradeStationThe
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count makes sense; trades are turne
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APPENDIX AAmiBrokerHere is a brief
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switchbreak (part of the switch sta
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Here is the source code from Chapte
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PctSize = PositionRisk * MarginDepo
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■ KeywordsprevMarketPositionmarke
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upSumAvg = upSum / lengthdnSumAvg =
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Sub BollingerBand(dataList, length,
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308EXCEL SYSTEM BACKTESTERIf (kVal
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■ Keywords and Identifierscurrent
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312PYTHON SYSTEM BACKTESTERdef calc
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sysMark =self.systemMarkets[i]avgLo
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class stochClass(object):class stoc
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318PYTHON SYSTEM BACKTESTERfor i in
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■ Python-Specific Keywordsandasas
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Monte Carlo Analysis# Monte Carlo A
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FIGURE D.1324TRADESTATION AND EASYL
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Simple RSI with Profit Objective an
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If condition1 and condition2 then b
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330TRADESTATION AND EASYLANGUAGEIf(
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if lastTradeLoser thenbeginif curre
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Value1 = swingHighBar(1,h,pivotHiSt
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■■■■■■■Statistically
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INDEXNote: Page references followed
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calculation2 standard deviations, u
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ES. See Exhaustive searchESB. See E
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Mini Russell day trading system, na
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PPO. See Percentage price oscillato
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Time-based market order (MOC), exit
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Ultimate Algorithmic Trading System

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