Ultimate Algorithmic Trading System

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Box 2.4 gives a description of a simplistic version of a stochastic crossover systemutilizing the same profit-and-loss objectives as the RSI algorithms. The results of thisstochastic algorithm applied to several markets are shown in Table 2.4.Box 2.4 George Lane’s Slow Stochastic System DescriptionIf 14-day slow %K crosses below slow %D and slow %D is greater than 80, thenBuy MOCIf 14-day slow %K crosses above slow %D and slow %D is less than 20, thenSell Short MOCIf position is longTake Profit: If close > entry price + 3 ATR Sell MOCProtective Stop: If close < entry price − 1 ATR Sell MOCIf position is shortTake Profit: If close < entry price − 3 ATR BuyToCover MOCProtective Stop: If close > entry price + 1 ATR, BuyToCover MOCNote that MOC stands for market on close.46STOCHASTICS AND AVERAGES AND RSI! OH, MY!George Lane’s Slow Stochastic System p–code‘Most software will provide a function that‘provides all the components of the stochasticValue1 = stochastic(h,l,c,rawKLen,smooth1,smooth2,1,myFastK,myFastD,mySlowK,mySlowD)If mySlowK crosses above mySlowD and mySlowD < 20 then buythis bar on closeIf mySlowK crosses below mySlowD and mySlowD > 80 thensellShort this bar on closeIf marketPosition = 1 thenIf c > entryPrice + 3* avgTrueRange(10) then sell thisbar on closeif c < entryPrice - 1* avgTrueRange(10) then sell thisbar on closeIf marketPosition =-1 thenIf c < entryPrice - 3* avgTrueRange(10) then buyToCoverthis bar on closeif c > entryPrice + 1* avgTrueRange(10) then buyToCoverthis bar on closewww.rasabourse.com
TABLE 2.4Performance of Stochastic AlgorithmTicker Net Profit Max. Sys DD # Trades Avg P/L Avg Bars Held % of WinnersAD0_E0B −34820 −50330 356 −97.81 7.6 26.69BP0_E0B 41213 −40563 324 127.2 8.42 31.17C20_E0B 8400 −15675 358 23.46 7.58 29.89CC20_E0B 44010 −8170 341 129.06 8.21 35.19CL20_E0B −54320 −115190 346 −156.99 7.92 27.46CT20_E0B −5770 −51165 362 −15.94 7.81 30.11CU0_E0B −287 −53163 348 −0.83 8.01 27.87DX20_E0B 4120 −20390 362 11.38 7.33 27.9ED0_E0B −4066 −4103 255 −15.94 8.93 21.96EMD0_E0B −53730 −89300 350 −153.51 7.29 24.86ES0_E0B −52200 −75975 359 −145.4 7.15 25.07FC0_E0B −17425 −32575 369 −47.22 7.41 26.83FV0_E0B −17699 −25463 345 −51.3 7.66 25.8GC20_E0B −27470 −67650 353 −77.82 7.54 29.18HG20_E0B −48938 −106225 343 −142.67 7.65 26.82HO20_E0B 36343 −96319 340 106.89 8.07 30KC20_E0B 16838 −30375 334 50.41 8.26 28.74KW20_E0B −188 −41688 350 −0.54 7.67 30.86LB0_E0B 5302 −34562 418 12.68 6.53 28.95LC0_E0B 42500 −8750 344 123.55 7.98 34.3LH0_E0B −14110 −17640 363 −38.87 7.2 26.17MP0_E0B 1730 −10580 297 5.82 8.34 28.96NG20_E0B −193860 −199740 336 −576.96 7.95 25.3NK0_E0B 17300 −38025 375 46.13 7.34 30.4OJ20_E0B 34275 −8055 321 106.78 8.3 32.4PL20_E0B 25415 −40470 341 74.53 7.91 30.5RB0_E0B −48266 −101884 406 −118.88 5.96 28.33S20_E0B −48888 −61063 367 −133.21 7.18 26.16SB20_E0B −7045 −33309 380 −18.54 6.9 28.68SI20_E0B −122305 −186355 323 −378.65 8.44 27.86TF0_E0B −48910 −80540 333 −146.88 7.56 26.43TU0_E0B −21736 −24441 309 −70.34 8.3 24.92TY0_E0B −37139 −54734 350 −106.11 7.52 25.71US0_E0B −74827 −74859 359 −208.43 7.67 25.07W20_E0B −27838 −43613 351 −79.31 7.98 29.0647STOCHASTICS AND AVERAGES AND RSI! OH, MY!www.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
Page 11 and 12: Well that was 27 years ago and I di
Page 13 and 14: xivINTRODUCTION TO THE ULTIMATE ALG
Page 15 and 16: xviINTRODUCTION TO THE ULTIMATE ALG
Page 17 and 18: CHAPTER 1Introductionto TradingAlgo
Page 19 and 20: However, at this introductory stage
Page 21 and 22: completely above the tableau. If th
Page 23 and 24: Don’t get bogged down trying to u
Page 25 and 26: checking account was down the $10K,
Page 27 and 28: Short Liquidation Condition—What
Page 29 and 30: One BarStrengthTwo BarStrengthThree
Page 31 and 32: and inexperienced trading system pr
Page 33 and 34: Input = 6StartInput = 4Input <> 6In
Page 35 and 36: The diagram in Figure 1.4 looks cle
Page 37 and 38: observed. If the latter criterion i
Page 39 and 40: Start or NewBarIs C >AVG(C,200)YesN
Page 41 and 42: CHAPTER 2Stochastics andAverages an
Page 43 and 44: The basic theory behind the ADX is
Page 45 and 46: 4. Divide the 14-day smoothed plus
Page 47 and 48: if myADX < 35 thenif MarketPosition
Page 49 and 50: TABLE 2.1Performance of Directional
Page 51 and 52: FIGURE 2.4Source: TradeStationExamp
Page 53 and 54: Start orNew BarIs RSI < 30YesBuy Ma
Page 55 and 56: RSI DivergenceMarket Continuing to
Page 57 and 58: If marketPosition =-1 and close > e
Page 59 and 60: TABLE 2.3Performance of RSI Failure
Page 61: Start orNew BarIs Slow %K CrossingA
Page 65 and 66: it is boundless extended readings a
Page 67 and 68: TABLE 2.5Performance of CCI algorit
Page 69 and 70: FIGURE 2.11Source: TradeStationThe
Page 71 and 72: We will discuss moving averages in
Page 73 and 74: MACDAvg = XAverage( MyMACD,9)MACDDi
Page 75 and 76: FIGURE 2.13Source: TradeStationThre
Page 77 and 78: LC0_E0B −25000 −41790 398 −62
Page 79 and 80: FIGURE 2.14Source: TradeStationA 60
Page 81 and 82: TABLE 2.8 Performance of Bollinger
Page 83 and 84: If filterTrade = false thenIf close
Page 85 and 86: Keltner ChannelChester Keltner brou
Page 87 and 88: FIGURE 2.15Source: TradeStationKelt
Page 89 and 90: 35000300002500020000150001000050000
Page 91 and 92: TABLE 2.12Best Parameter Sets of Ke
Page 93 and 94: CHAPTER 3Complete TradingAlgorithms
Page 95 and 96: Box 3.1 Turtle System #1Buy one tic
Page 97 and 98: TABLE 3.1Turtle System 1 without LT
Page 99 and 100: TABLE 3.3Turtle System 1 with LTLF
Page 101 and 102: 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
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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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[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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