Ultimate Algorithmic Trading System

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Simple RSI system using 3 X ATR stop and 5 X ATR profit objective’****************************************************************’**** This is a good place to put all of your function calls ****’**** and system calculations. A simple RSI system ****'**** that buys when RSI < 20 and sells when RSI > 80. ****'**** Utilizes a 5 ATR Profit and a 3 ATR Protective Stop ****’****************************************************************Call BollingerBand(myClose, 60, 2, avg, upBand, dnBand,i, 1)simpleAvg = Average(myClose, 19, i, 1)atr = Average(myTrueRange, 20, i, 1)rsiVal = RSI(myClose, 14, i, 0)Call Stochastic(3, 4, 7, stoK, stoD, slowD, i, 1)’****************************************************************’**** Put All Of Your Orders Here ****’****************************************************************prevMarketPosition = marketPositionIf marketPosition <> 1 And rsiVal < 20 ThenCall Trade(Buy, "RSIBuy", myClose(i), moc, i)End IfIf marketPosition <> -1 And rsiVal > 80 ThenCall Trade(Sell, "RSISell", myClose(i), moc, i)End IfIf marketPosition = 1 ThenIf myClose(i) < entryPrice - 3 * atr ThenCall Trade(ExitLong, "L-ATR Stop", myClose(i), moc, i)End IfIf myClose(i) > entryPrice + 5 * atr ThenCall Trade(ExitLong, "L-ATR Prof", myClose(i), moc, i)End IfEnd IfIf marketPosition = -1 ThenIf myClose(i) > entryPrice + 3 * atr ThenCall Trade(ExitShort, "S-ATR Stop", myClose(i),End Ifmoc, i)If myClose(i) < entryPrice - 5 * atr Then165USING MICROSOFT EXCEL TO BACKTEST YOUR ALGORITHMwww.rasabourse.com
Call Trade(ExitShort, "S-ATR Prof", myClose(i),moc, i)End IfEnd If’****************************************************************’**** End of Main Trading Loop ****’**** No orders allowed below this point ****’****************************************************************166USING MICROSOFT EXCEL TO BACKTEST YOUR ALGORITHMwww.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
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 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
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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: Simple Moving Average Crossover usi
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
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
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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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Ultimate Algorithmic Trading System

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