Ultimate Algorithmic Trading System

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CHAPTER 5Using MicrosoftExcel to BacktestYour AlgorithmThe majority of the testing that has been performed thus far in the book wascarried out using either AmiBroker or TradeStation. These are complete tradingsolutions and should be able to fulfill all the needs of a trader. However, sometraders would like to use software that they already have on their computer.Microsoft Excel has been a major player in the trading algorithm arena since thebeginning. Spreadsheets combine data with formulas, and as we have seen these arethe major ingredients to trading algorithms. Several years ago, I developed a verysimple spreadsheet to help a client generate his trading signals for the next day. Thesystem incorporated several indicators across several different markets. The Excelworkbook turned out to be quite large and required the user to type in the daily dataafter the close each day. Excel spreadsheets are very powerful but when it comes tocalculating indicators and trade signals they can become very cumbersome.This is where VBA (Visual Basic for Applications) comes in very handy. VBAcombines the power of the BASIC programming language with the power ofspreadsheets. I have created a simple single-market algorithm-testing platform forthose who wanted to use Excel and VBA. I call it the Excel System Backtester, ESBfor short. Here is a version of the Bollinger Band algorithm that has been evaluatedin the previous chapters programmed in our ESB platform.145The Ultimate Algorithmic Trading System Toolbox + Website: Using Today’s Technology to Help You Become a Better Trader. George Pruitt© 2016 by George Pruitt. Published by John Wiley & Sons, Inc.www.rasabourse.com
’****************************************************************’**** This is a good place to put all of your function calls ****’**** and system calculations. ****’****************************************************************Call BollingerBand(myClose, 60, 2, avg, upBand, dnBand,i, 1)simpleAvg = Average(myClose, 10, i, 1)rsiVal = RSI(myClose, 14, i, 1)Call Stochastic(3, 4, 7, stoK, stoD, slowD, i, 1)146USING MICROSOFT EXCEL TO BACKTEST YOUR ALGORITHM’****************************************************************’**** Put All Of Your Orders Here ****’****************************************************************prevMarketPosition = marketPositionIf marketPosition <> 1 ThenCall Trade(Buy, "BB-Buy", upBand, stp, i)End IfIf marketPosition <> -1 ThenCall Trade(Sell, "BB-Sell", dnBand, stp, i)End IfIf marketPosition = -1 ThenCall Trade(ExitShort, "ExitShortStop", entryPrice +2000 / myTickValue, stp, i)If barsShort > 10 And myClose(i) > entryPrice ThenCall Trade(ExitShort, "10dayShOut", myClose(i), moc, i)End IfEnd IfIf marketPosition = 1 ThenCall Trade(ExitLong, "ExitLongStop", entryPrice -2000 / myTickValue, stp, i)If barsLong > 10 And myClose(i) < entryPrice ThenCall Trade(ExitLong, "10dayLgOut", myClose(i), moc, i)End IfEnd If’****************************************************************’**** End of Main Traiding Loop ****’**** No orders allowed below this point ****’****************************************************************This system buys/sells short on the penetration of 60-day two-standard-deviationsBollinger Bands, then risks $2,000 per trade and exits if the trade is not profitableafter 10 days. The code is Visual Basic, so it follows that syntax. In developing thistesting software my overall objective was simplicity—I wanted a very easy slopingwww.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
Page 109 and 110: TABLE 3.8Donchian Channel Breakout
Page 111 and 112: we have, because who has the time t
Page 113 and 114: %Winners ShortLen InterLen StopDoll
Page 115 and 116: on a peak. This demonstrates a lack
Page 117 and 118: The correlation coefficients range
Page 119 and 120: TABLE 3.13The Best Results for the
Page 121 and 122: TABLE 3.17Results for the Donchian
Page 123 and 124: FIGURE 3.5AmiBroker’s walk-forwar
Page 125 and 126: direction of the 200-day moving ave
Page 127 and 128: range day and initially puts on two
Page 129 and 130: CHAPTER 4Introduction toAmiBroker
Page 131 and 132: Things All Programmers Need to Know
Page 133 and 134: expressions deal with a string of c
Page 135 and 136: AFL uses functions DateNum(), DateT
Page 137 and 138: to Short and Cover as well. If you
Page 139 and 140: FIGURE 4.2The AmiBroker Editor wind
Page 141 and 142: to the user. Instead of having to r
Page 143 and 144: This is where you can change the va
Page 145 and 146: shortMav = MA(C,avgLen1);longMav =
Page 147 and 148: code. This is a very difficult thin
Page 149 and 150: the order of the arrays. I admit th
Page 151 and 152: FIGURE 4.17The AFL Code Wizard ‘
Page 153 and 154: ■■■This time click on is grea
Page 155 and 156: This should look very similar to th
Page 157 and 158: before a single line of code is typ
Page 159: COND3 = C > MA(C,100);COND1 = cente
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 and 208: >>> c = a + b>>> cAfter you hit ent
Page 209 and 210: you don’t need to know exactly ho
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Shorting occurs when the low of the
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That was the long entry logic only
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FIGURE 6.4brackets.A Python run-tim
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prevAvg2 and today’s avg1 must be
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■ TradeStation IDE204AN INTRODUCT
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206AN INTRODUCTION TO EASYLANGUAGEt
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FIGURE 7.5The algorithm with a sing
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the Vars statement and initialize t
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TABLE 7.1EasyLanguage Keywords and
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214AN INTRODUCTION TO EASYLANGUAGEF
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standard deviations. In our example
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218AN INTRODUCTION TO EASYLANGUAGEt
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into a project makes it easier to a
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If marketPosition =-1 thenbeginend;
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or program any trading idea. Practi
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CHAPTER 8Genetic Optimization,Walk
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superfast processors, searching a l
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This equation involves four unknown
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For generation = 1 To 100 ' total g
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Converting Fitness in Terms of Slic
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'the 6 darts landedRandomizeFor l =
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roulette(i) = Rnd(1#)If roulette(i)
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selection and reproduction may even
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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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