Ultimate Algorithmic Trading System

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If in a long position use the greater of:Breakeven stop—if applicableInitial stopLowest low of a moving window of the past 23 daysIf in a short position use the lesser of:Breakeven stop—if applicableInitial stopHighest high of the moving window of the past 23 days8INTRODUCTION TO TRADINGThat is the entire system, and it did in fact sell for more than $10K. Thisboils down to a simple moving-average crossover system trading in the directionof the shorter- and longer-term trend. The description also includes a completeset of trade management rules: protective, breakeven, and trailing stop. This is acomplete trading system description, but as thorough as it seems there are a coupleof problems. The first is easy to fix because it involves syntax but the second involveslogic. There are two words that describe market direction that cannot be interpretedby a computer. Do you see them? The two words in question are: rising and falling.Again, descriptive words like these have to be precisely defined. This initial problemis easy to fix—just inform the computer the exact meaning of rising and falling.Second, it has a weakness from a logical standpoint. The algorithm uses $700 as theprofit level before the stop can be moved to break even. Seven hundred dollars inthe 1990s is quite a bit different than it is today. The robustness of this logic couldbe dramatically improved by using a market-derived parameter. One could use avolatility measure like the average range of the past N-days. If the market exhibits ahigh level of volatility, then the profit objective is larger and the breakeven stop willtake longer to get activated. You may ask, ‘‘Why is this beneficial?’’ Market noise isconsidered the same as volatility, and the more noise, the higher likelihood of widemarket swings. If trading in this environment, you want to make sure you adjustyour entries and exits so you stay outside the noise bands.This algorithm was very successful in the 1980s and through a good portion the1990s. However, its success has been hit-and-miss since. Is this algorithm worth$10K? If you were sitting back in 1993 and looked at the historical equity curve, youmight say yes. With a testing platform, we can walk forward the algorithm, and applyit to the most recent data and see how it would have performed and then answerthe question. This test was done and the answer came out to be an emphatic no!Had you bought this system and stuck with it through the steep drawdownsthat have occurred since the 1990s, you would have eventually made back yourinvestment (although not many people would have stuck with it). And you wouldhave learned the secret behind the system. Once the secret was revealed and yourwww.rasabourse.com
checking account was down the $10K, you might have been a little disappointedknowing that basic tenets of the system had been around for many years and freelydisseminated in books and trade journals of that era. The system may not be all thatgreat, but the structure of the algorithm is very clean and accomplishes the tasksnecessary for a complete trading system.The most time-consuming aspect when developing a complete trading idea iscoming up with the trade entry. This seems somewhat like backward thinkingbecause it’s the exit that determines the success of the entry. Nonetheless, the lion’sshare of focus has always been on the entry. This system provides a very succincttrade entry algorithm. If you want to develop your own trading algorithm, thenyou must also provide the computer with logic just as precise and easy to interpret.Getting from the nebula of a trading idea to this point is not easy, but it is absolutelynecessary. On past projects, I have provided the template shown in Box 1.4 toclients to help them write their own entry rules in a more easily understood form.You can download this form and a similar exit template at this book’s companionwebsite:www.wiley.com/go/ultimatealgotoolbox.Box 1.4 Simple Template for Entry RulesLong / Short EntriesCalculations and/or Indicators Involved (specify lookback period). Don’t useambiguously descriptive words like rising, falling, flattening, topping or bottomingout._________________________________________________________________________________________________________________________________________________________Buy Condition—What must happen for a long signal to be issued? List stepsin chronological order. And remember, don’t use ambiguously descriptive wordslike rising, falling, flattening, topping,orbottoming out._________________________________________________________________________________________________________________________________________________________Sell Condition—What must happen for a short signal to be issued? List stepsin chronological order._________________________________________________________________________________________________________________________________________________________Here is one of the templates filled out by a one-time client:Calculations and/or Indicators Involved (specify lookback period)Bollinger Band with a 50-day lookback9INTRODUCTION TO TRADINGwww.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 and 22: completely above the tableau. If th
Page 23: Don’t get bogged down trying to u
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
Page 73 and 74: 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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