Ultimate Algorithmic Trading System

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nebulous idea into something with structure. Here is the pseudocode of the client’sinitial trading idea:Algorithm Pseudocodeif close > 200 day moving average andclose < close[1] and close [1] < close [2] andclose[2] < close[3] and yesterday’s 14 day RSI < 20 andyesterday’s 14 day RSI < today’s 14 day RSI then BUYIf this looks like Latin (and you don’t know Latin), don’t worry about it. The [1]in the code just represents the number of bars back. So close [2] represents the closeprice prior to yesterday. If you are not familiar with RSI, you will be after Chapter 2.By the time you are through with this book you will be able to translate this intoEnglish, Python, EasyLanguage, AmiBroker, or Excel VBA. Here it is in English.6INTRODUCTION TO TRADINGIf today’s close is greater than the 200-day moving average of closingprices and today’s close is less than yesterday’s close and yesterday’sclose is less than the prior day’s close and the prior day’s close is lessthan the day before that and the 14-day RSI of yesterday is less than 20and the 14-day RSI of yesterday is less than the 14-day RSI of today,then buy at the market.Notice how the words downward and bottoming out were removed and replacedwith exact descriptions:downward: today’s close is less than yesterday’s close and yesterday’s close isless than the prior day’s close and the prior day’s close is less than the daybefore. The market has closed down for three straight days.bottoming out: the 14-day RSI of yesterday is less than 20 and the 14-day RSIof yesterday is less than the 14-day RSI of today. The RSI value ticked below20 and then ticked up.Also notice how the new description of the trading system is much longer than theoriginal. This is a normal occurrence of the evolution of idea into an exact tradingalgorithm.And now here it is in the Python programming language:Actual Python Codeif myClose[D0] < sAverage(myClose,200,D0,1) andmyClose[D0] < myClose[D1] and myClose[D2] < myClose[D3] andmyClose[D1] < myClose[D2] and rsiVal[D1] < 20 and rsiVal[D1]< rsiVal[D0]:buyEntryName = 'rsiBuy'entryPrice = myOpenwww.rasabourse.com
Don’t get bogged down trying to understand exactly what is going on; just noticethe similarity between pseudo and actual code. Now this is something the computercan sink its teeth into. Unfortunately, reducing a trading idea down to pseudocodeis as difficult as programming it into a testing platform. The transformation from atrader to an algo trader is very difficult and in some cases cannot be accomplished.I have worked with many clients who simply could not reduce what they saw on achart into concise step-by-step instructions. In other cases the reduction of a tradingidea removes enough of the trader’s nuances that it turned something that seemedplausible into something that wasn’t.It goes without saying that if you don’t have an algorithm, then all the softwarein the world will not make you a systematic trader. Either you have to design yourown or you have to purchase somebody else’s. Buying another person’s technologyis not a bad way to go, but unless the algorithm is fully disclosed you will not learnanything. However, you will be systematic trader. I have spent 27 years evaluatingtrading systems and have come across good and bad and really bad technology.I can say without a doubt that one single type of algorithm does not stand headand shoulders above all the others. I can also say without a doubt there isn’t acorrelation between the price of a trading system and its future profitability. Thedescription in Box 1.3 is very similar to a system that sold for over $10,000 inthe 1990s.7Box 1.3 Trading Algorithm Similar to One That Sold for $10Kin the 1990s DescriptionEntry Logic:If the 13-day moving average of closes > the 65-day moving average of closesand the 13-day moving average is rising and the 65-day moving average is risingthen buy the next day’s openIf the 13-day moving average of closes < the 65-day moving average of closesand the 13-day moving average is falling and the 65-day moving average is fallingthen sell the next day’s openINTRODUCTION TO TRADINGExit Logic:If in a long position thenset initial stop at the lowest low of the past 13 daysIf in a short position thenset initial stop at the highest high of the past 13 daysOnce profit exceeds or matches $700 pull stops to break evenwww.rasabourse.com
Page 1 and 2: THE ULTIMATEALGORITHMICTRADING SYST
Page 3 and 4: THE ULTIMATEALGORITHMICTRADING SYST
Page 5 and 6: CONTENTSAbout the authorIntroductio
Page 7 and 8: Reproduction 238Mutation 240Using G
Page 9 and 10: 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: completely above the tableau. If th
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 and 62: Start orNew BarIs Slow %K CrossingA
Page 63 and 64: TABLE 2.4Performance of Stochastic
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
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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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[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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