Ultimate Algorithmic Trading System

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138FIGURE 4.20Automatic Analysis dialog box.INTRODUCTION TO AMIBROKER’S AFLbeside the Exclamation mark. This will build the formula and export it with a‘‘.afl’’extension. You can then open it with AFL Editor and add the necessary codefor testing a futures contract:PositionSize = MarginDeposit = 1;For practice, go ahead and click on the Build and Export a formula icon andsave it somewhere on your desktop or in a folder in your C: drive. You then can goto the AFL Editor and open it and add the line of code above. I did just that and myAFL Wizard designed code looks like this:PositionSize = MarginDeposit = 1;Buy = MA( Close , 15 ) > MA( Close , 30 );Sell = 0;Short = MA( Close , 15 ) < MA( Close , 30 );Cover = 0;www.rasabourse.com
This should look very similar to the code we originally typed in forMySecondAlgo. The AFL Wizard can get you up and running very quickly andcan also be used as a learning tool. It automatically builds the AFL code so you canstart your design with the Wizard and have it generate the framework and thenmove onto the AFL Editor and complete your coding of your algorithm there.■ AmiBroker Loop ProgrammingAs powerful as AmiBroker’s array programming is, there are times when you want toprogram on a bar-by-bar basis. Dr. Janeczko has built this capability into his softwareas well. With this feature you can program with your precious If constructs. Hereis a familiar algorithm utilizing loops:PositionSize = MarginDeposit = 1;mav = MA(C,20);for( i = 0; i < BarCount; i++ ){}if (C[i] >= mav[i]) {}Buy[i] = 1;if (C[i] <= mav[i]) {}Sell[i] = 1;This is the simple price crossing moving average reversal algorithm. The mavarray is set to a 20-day simple moving average of closes. This line of code is stillutilizing array programming. A for loop is then set up so that individual elementsof the different arrays can be examined. The for loop construct in AFL is verysimilar to one in the C language. The loop variables are controlled by what is insidethe parentheses.(i= 0; i < BarCount; i++ )Here the loop will start at zero and stop at BarCount and the loop variable i willincrement by one each time i++. The i++ is the same as i = i + 1; since we arenot processing arrays, we can now use if constructs. Notice how the comparison ofthe C[i] element and the mav[i] element is enclosed in parentheses. If the close isgreater than the 20-bar moving average, then the following code is executed: Buy[i]= 1; This sets the ith element in the Buy array to one. Also, notice how the curlybrackets {}are used in the code. The curly brackets inform the computer and the139INTRODUCTION TO AMIBROKER’S AFLwww.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
Page 103 and 104: Pause the Battle—Let’s Talk Ris
Page 105 and 106: Box 3.3 Battle Royale—And the Com
Page 107 and 108: 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: ■■■This time click on is grea
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
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
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percent wins, number of trades, and
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>>> c = a + b>>> cAfter you hit ent
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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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Ultimate Algorithmic Trading System

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