Ultimate Algorithmic Trading System

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Step 3: Wait for another pivot high bar that exceeds the price in Step 1. Once ahigh bar pivot occurs that fits the criteria, mark the high price.Step 4: Once the subsequent pivot high bar is found, then wait for another lowprice that is 2 percent below the high marked in Step 3. When a bar’s lowprice fulfills the criteria buy that bar’s close. If the market moves above thehigh marked in Step 3, then go back to Step 3 and wait for another pivothigh bar. The new high that just occurred may turn out to be the pivot highbar that you are looking for in Step 3.14INTRODUCTION TO TRADINGAdditional notes: If 30 days transpire before proceeding from Step 1 to Step 4,then reset.Figure 1.2 illustrates the sequence the above description is trying to capture.Ignore the state designations for now. They will become apparent in the followingdiscussion.It is easy to see the designer/trader of this entry signal is trying to buy after twopivot highs are separated and followed by a pullback of 2 percent. In addition, thereare a couple of conditions that must also be met before a buy signal is triggered:(1) the second pivot high price must be higher than the first, and (2) the wholesequence must take less than 30 bars to complete. When a system allows its entrycriteria to work across an unknown number of days or price levels, conditions mustbe used to keep the integrity of the entry signal and limit the duration of the sequence.Since there is variability in the instruction set, the programming of this paradigm isdefinitely more difficult. However, as mentioned earlier, it is very doable. As a youngState 1State 3Buy HereState 1State 3State 1State 2State 3State 4State 2State 4State 2State 4Pivot Point Finite StateMachineShowing ProgressionThrough Different States21 28 Jun4 11 18 25 Jul 9 16 23 30 Aug 6 13 20 27 Sep 10 17FIGURE 1.2A depiction of the variable-bar sequence described by the long entry signal.www.rasabourse.com
and inexperienced trading system programmer, I tried to program these variablesequences using a bunch of true/false Boolean flags. Box 1.6 shows an initial attemptusing this method to describe the pivot point sequence. The flags are bolded so you caneasily see how they are turned on and off. Comments are enclosed in brackets {}.Box 1.6 Using Boolean Flags to Program a Trading AlgorithmHighPivotFound = High of yesterday > High of today and Highof yesterday > High of two days agoIf HPivot1 = False and HighPivotFound then {first Pivot high found}HPivot1 = TrueHPivot1Price = high of yesterdayHPivot1Cnt = currentBarIf HPivot1 = True and Low < HPivot1Price * 0.98 then{2% retracement after first Pivot high}LRetrace = TrueIf HPivot1 = True and LRetrace = False and High of today >HighPivot1Price thenHPivot1Price = High of yesterday {another higher high butnot a 2% retracement – start over}HPivot1Cnt = currentBarIf LRetrace = True and HighPivotFound and High of yesterday> HPivot1Price thenHPivot2 = True {second Pivot high > first Pivot high and2% retracement between the two}HPivot2Price = High of yesterdayIf HPivot2 = True and High of today > HPivot2Price thenHPivot2Price = High of today {another higher high > secondPivot High – keep track of it}If HPivot2 = True and Low < HPivot2Price * 0.98 thenBuy this bar on close {Buy Order Placed – entry criteriahas been met}HPivot1 = False {Start Over}LRetrace = FalseHPivot2 = False15INTRODUCTION TO TRADINGHPivot1Cnt = HPivot1Cnt + 1If HPivot1Cnt >= 30 then {reset all Boolean flags – start over}HPivot1 = FalseLRetrace = FalseHPivot2 = Falsewww.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 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: One BarStrengthTwo BarStrengthThree
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
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
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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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