Ultimate Algorithmic Trading System

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A Low < = Pivot1Hi by 2%STARTBar Count = 1High Pivot Point ofStrength 1 OccurredHi > Pivot1HiSTATE1StorePivot1HiBar Count > =30Low > Pivot1Hi - 2%STATE 2High Pivot Point ofStrength 1 >Pivot1HiNo High Pivot PointSTATE3StorePivot2Hi=Max(Pivot2Hi,Hi)Bar Count =Bar Count + 1Another Higher HighPivot Occurred / OrLow > Pivot Hi - 2%FSM Diagram for Pivot PointAlgorithmACCEPTPlace OrderA Low < Pivot2Hi by 2%FIGURE 1.4An FSM that models the pivot-point long-entry algorithm described in this chapter.18INTRODUCTION TO TRADINGcombination lock FSM there was only one connector connecting the different statestogether and the machine never went backward. Once a state was attained, themachine stayed there until the criteria were met to advance to the next state. Thispivot-point FSM can move forward and backward.Stepping through this diagram will help make it less scary. Keep in mind that allof these machines gobble up one bar at a time and then make a decision. Startingat the START state the machine looks for a pivot high of strength one. Once themachine finds this pivot point it then moves to STATE1 and starts looking for a lowprice that is 2 percent or less than the pivot high found in the START state. Thereare four paths out of STATE1: (1) a low is found that fits the criteria, (2) a lowprice fitting the criteria is not found, stay in STATE1, (3) 30 bars have occurredsince the pivot high is found, and (4) a high exceeds the pivot high price. Only onepath leads to STATE2. All other paths either return to the START state or loopback to the current state. Once the machine attains STATE2 it starts analyzing thedata by gobbling each bar and searches for a higher pivot high point. Unlike STATE1there are only three paths coming out of this state: (1) a higher pivot high is found,(2) a higher pivot high is not found, and (3) 30 bars have occurred since the pivothigh was found in the START state. There is only one path to STATE3 and that is ahigher pivot high. All other paths either loop or return the machine to the STARTstate. Assuming a higher pivot high is found the machine moves to STATE3. Oncein STATE3 the machine will only return to the START state if 30 bars have comeand gone before the machine can attain the ACCEPT state. If new highs are found,the machine continues to stay in STATE3 and keeps track of the new highs, all thewhile looking for that particular low that is 2 percent or lower than the most recentpivot high. Eventually things fall into place and the machine attains the ACCEPTstate and a buy order is placed. You can now refer back to Figure 1.2 and see whenthe machine attains the various states.www.rasabourse.com
The diagram in Figure 1.4 looks clean and neat, but that’s not how it started out.When I diagram a trading algorithm, I use pen/pencil and paper. A pencil is greatif you don’t want to waste a lot of paper. Also, you don’t have to have a completediagram to move onto the pseudocode step. Trust me when I say a diagram canhelp immensely. Something that seems impossible to program can be conquered bydrawing a picture and providing as much detail on the picture as possible. Box 1.7contains the pseudocode for the pivot point entry algorithm using the FSM diagram.Box 1.7 Pivot Point Entry Algorithm for Figure 1.4If initialize thenState = StartHiPivotFound = High of yesterday > High of today andHigh of yesterday > High of prior dayIf State = Start and HiPivotFound thenState = 1BarCount = 1Pivot1Hi = High price of HiPivotFoundIf State <> Start then BarCount = BarCount + 1If State = 1 thenIf Low of today < Pivot1Hi * 0.98 thenState = 2If High of today > Pivot1Hi thenState = StartIf State = 2 thenIf HiPivotFound thenPivot2Hi = High Price of HiPivotFoundIf Pivot2Hi > Pivot1Hi thenState = 3If State = 3 thenIf Low of today < Pivot2Hi * 0.98 thenState = AcceptIf High of today > Pivot2Hi thenPivot2Hi = High of today19INTRODUCTION TO TRADINGIf State = Accept thenBuy this market on closeState = Start {start over}If BarCount = 30 thenState = StartBarCount = 0www.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 and 30: One BarStrengthTwo BarStrengthThree
Page 31 and 32: and inexperienced trading system pr
Page 33: Input = 6StartInput = 4Input <> 6In
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
Page 81 and 82: TABLE 2.8 Performance of Bollinger
Page 83 and 84: 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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