Ultimate Algorithmic Trading System

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stoDList.append(tempSum/dLen)self.fastD = stoDList[len(stoDList)-1]if (i == index2):tempSum = 0lowRngBound = len(stoDList) - dSloLenhighRngBound = lowRngBound + dSloLenfor j in range(lowRngBound,highRngBound):tempSum += stoDList[j]self.slowD = tempSum / dSloLenelse:hh = 0ll = 999999lowRngBound = curBarLookBack - (kLen - 1)highRngBound = lowRngBound + 3for i in range(lowRngBound, highRngBound):if hPrices[i] > hh:hh = hPrices[i]if lPrices[i] < ll:ll = lPrices[i]self.fastK = (cPrices[curBarLookBack] - ll )/(hh - ll) * 100self.fastD = (self.fastD * (dLen - 1) +self.fastK) / dLenself.slowD = ((self.slowD * (dSloLen - 1))+ self.fastD) / dSloLenreturn(self.fastK,self.fastD,self.slowD)class rsiClass(object):class rsiClass(object):317PYTHON SYSTEM BACKTESTERoldDelta1 = 0def __init__(self):self.delta1 = 0self.delta2 = 0self.rsi = 0self.seed = 0def calcRsi(self,prices,lookBack,curBar,offset):upSum = 0.0dnSum = 0.0if self.seed == 0:self.seed = 1www.rasabourse.com
318PYTHON SYSTEM BACKTESTERfor i in range((curBar - offset) - (lookBack-1),curBar - offset +1):if prices[i] > prices[i-1]:diff1 = prices[i] - prices[i-1]upSum += diff1if prices[i] < prices[i-1]:diff2 = prices[i-1] - prices[i]dnSum += diff2self.delta1 = upSum/lookBackself.delta2 = dnSum/lookBackelse:if prices[curBar - offset] > prices[curBar - 1- offset]:diff1 = prices[curBar - offset] -prices[curBar - 1 - offset]upSum += diff1if prices[curBar - offset] < prices[curBar - 1- offset]:diff2 = prices[curBar - 1 - offset]- prices[curBar - offset]dnSum += diff2self.delta1 = (self.delta1 * (lookBack -1)+ upSum) / lookBackself.delta2 = (self.delta2 * (lookBack -1)+ dnSum) / lookBackif self.delta1 + self.delta2 != 0:self.rsi = (100.0 * self.delta1) / (self.delta1+ self.delta2)else:self.rsi = 0.0return (self.rsi)Highest Function/Moduledef highest(prices,lookBack,curBar,offset):result = 0.0maxVal = 0.00for index in range((curBar - offset) - (lookBack-1),curBar - offset +1):if prices[index] > maxVal:maxVal = prices[index]result = maxValreturn resultwww.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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before a single line of code is typ
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COND3 = C > MA(C,100);COND1 = cente
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’********************************
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FIGURE 5.1trading.Once you define t
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GetDataGET DATACOMPONENTLoad Data i
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152USING MICROSOFT EXCEL TO BACKTES
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performance of the trading system.
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156 FIGURE 5.9 The Visual Basic Edi
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FIGURE 5.12This error message appea
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End IfIf marketPosition = -1 ThenCa
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■■moc—Market On Close order.
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Simple Moving Average Crossover usi
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Call Trade(ExitShort, "S-ATR Prof",
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168USING PYTHON TO BACKTEST YOUR AL
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It works well on both Unix and Wind
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function modules and some are a lit
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inclusive, the number of iterations
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176This indicator is programmed as
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if prices[curBar - offset] < prices
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All these files deal with opening a
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entryPrice,fileList,entryPrice,entr
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Python has a ton of reusable code a
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186USING PYTHON TO BACKTEST YOUR AL
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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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Page 279 and 280: Calculating Start Trade Drawdown Wi
Page 281 and 282: A loop is used to flow through each
Page 283 and 284: The maximum drawdown of this algori
Page 285 and 286: ■ Fixed Fractional272PORTFOLIO AN
Page 287 and 288: FIGURE 9.2Add a strategy to your st
Page 289 and 290: 276FIGURE 9.6The UGTATS markets and
Page 291 and 292: 278FIGURE 9.9 How to adjust the set
Page 293 and 294: FIGURE 9.12 The Trade Analysis wind
Page 295 and 296: 282PORTFOLIO ANALYSISFIGURE 9.15thi
Page 297 and 298: FIGURE 9.18 Profit and drawdown are
Page 299 and 300: FIGURE 9.20 To set the portfolio st
Page 301 and 302: FIGURE 9.24Source: TradeStationThe
Page 303 and 304: count makes sense; trades are turne
Page 305 and 306: APPENDIX AAmiBrokerHere is a brief
Page 307 and 308: switchbreak (part of the switch sta
Page 309 and 310: Here is the source code from Chapte
Page 311 and 312: PctSize = PositionRisk * MarginDepo
Page 313 and 314: ■ KeywordsprevMarketPositionmarke
Page 315 and 316: upSumAvg = upSum / lengthdnSumAvg =
Page 317 and 318: Sub BollingerBand(dataList, length,
Page 319 and 320: 308EXCEL SYSTEM BACKTESTERIf (kVal
Page 321 and 322: ■ Keywords and Identifierscurrent
Page 323 and 324: 312PYTHON SYSTEM BACKTESTERdef calc
Page 325 and 326: sysMark =self.systemMarkets[i]avgLo
Page 327: class stochClass(object):class stoc
Page 331 and 332: ■ Python-Specific Keywordsandasas
Page 333 and 334: Monte Carlo Analysis# Monte Carlo A
Page 335 and 336: FIGURE D.1324TRADESTATION AND EASYL
Page 337 and 338: Simple RSI with Profit Objective an
Page 339 and 340: If condition1 and condition2 then b
Page 341 and 342: 330TRADESTATION AND EASYLANGUAGEIf(
Page 343 and 344: if lastTradeLoser thenbeginif curre
Page 345 and 346: Value1 = swingHighBar(1,h,pivotHiSt
Page 347 and 348: ■■■■■■■Statistically
Page 349 and 350: INDEXNote: Page references followed
Page 351 and 352: calculation2 standard deviations, u
Page 353 and 354: ES. See Exhaustive searchESB. See E
Page 355 and 356: Mini Russell day trading system, na
Page 357 and 358: PPO. See Percentage price oscillato
Page 359 and 360: Time-based market order (MOC), exit
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Ultimate Algorithmic Trading System

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