Ultimate Algorithmic Trading System

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CHAPTER 9An Introductionto PortfolioMaestro, MoneyManagement, andPortfolio Analysis271It has been mentioned in many trading circles through the years that moneymanagement is as important as the algorithm that generates the trade entries. Theposition size is paramount when it comes to utilizing capital in the most efficientmanner. Thus far, we have simply tested on a one-contract basis, and that in of itselfis a money management scheme. The one contract per market scheme was utilized,because the primary focus was on developing a trade entry-and-exit algorithm. Nowthat we have spent a sufficient amount of time on algorithm development, this guidewould not be complete without a chapter on money management and portfolioanalysis. This time we will lean on TradeStation to carry out our analysis—thisplatform has the toolset necessary to apply both portfolio and money managementschemes to a trading algorithm.The Ultimate Algorithmic Trading System Toolbox + Website: Using Today’s Technology to Help You Become a Better Trader. George Pruitt© 2016 by George Pruitt. Published by John Wiley & Sons, Inc.www.rasabourse.com
■ Fixed Fractional272PORTFOLIO ANALYSISFixed Fractional is by far the most popular form of money management in theworld of futures trading. This approach allocates the same amount of capital to eachmarket. Perceived risk is usually defined as a function of a market’s average truerange calculated over the last N days. Dividing the amount of capital by marketrisk gives the position size for the next trade. This form of money managementnormalizes the markets by maintaining the same amount of perceived risk across allmarkets in the portfolio. Here is the formula:Position size =(Account capital in dollars × Risk per trade in percent)∕ATR(N) in dollarsAssume you have a $100,000 capital allocation, and you want to risk at most 1percent on any given trade. Assume the 10-day ATR in Treasury notes is $500.How many contracts should be initiated on the next trade? Plugging into the formulawe get:Position size =(100, 000 × 0.01)∕500Position size = 1000 ∕ 500 = 2So two contracts of T-notes will fit our 1 percent risk criteria. Now assume youwant to trade Eurodollars as well and need to know that position size. Let’s say the10-day ATR in Eurodollars is $125. Plugging into the formula again, we get:Position size =(100, 000)×0.01 )∕125Position size = 1000 ∕ 125 = 8Eight contracts of Eurodollars provides the same risk as two contracts of T-notes.See how the different markets are normalized to provide the same amount of risk?Utilizing a Donchian 55-day breakout with a trailing 20-day liquidation and a fixeddollar stop, let’s see how this money management formula works in practice.■ Portfolio MaestroPortfolio Maestro (PM) is an add-on to TradeStation and requires an additionalmonthly fee. If you have it you might want to follow along with this tutorial. If youdon’t, then read on and see if it might be something you may want to investigate.From TradeStation you can launch PM by clicking on the Trading Apps tab, andthen selecting Portfolio Maestro. PM will launch and you will be presented with thewindow shown in Figure 9.1.Once you get used to the interface, building and testing portfolios will becomeold hat. However, the first few analyses may take multiple attempts to get everythingthe way you want. Hopefully, this tutorial will help along the way.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
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Well that was 27 years ago and I di
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xivINTRODUCTION TO THE ULTIMATE ALG
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xviINTRODUCTION TO THE ULTIMATE ALG
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CHAPTER 1Introductionto TradingAlgo
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However, at this introductory stage
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completely above the tableau. If th
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Don’t get bogged down trying to u
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checking account was down the $10K,
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Short Liquidation Condition—What
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One BarStrengthTwo BarStrengthThree
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and inexperienced trading system pr
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Input = 6StartInput = 4Input <> 6In
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The diagram in Figure 1.4 looks cle
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observed. If the latter criterion i
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Start or NewBarIs C >AVG(C,200)YesN
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CHAPTER 2Stochastics andAverages an
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The basic theory behind the ADX is
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4. Divide the 14-day smoothed plus
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if myADX < 35 thenif MarketPosition
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TABLE 2.1Performance of Directional
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FIGURE 2.4Source: TradeStationExamp
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Start orNew BarIs RSI < 30YesBuy Ma
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RSI DivergenceMarket Continuing to
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If marketPosition =-1 and close > e
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TABLE 2.3Performance of RSI Failure
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Start orNew BarIs Slow %K CrossingA
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TABLE 2.4Performance of Stochastic
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it is boundless extended readings a
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TABLE 2.5Performance of CCI algorit
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FIGURE 2.11Source: TradeStationThe
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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
Page 233 and 234: 218AN INTRODUCTION TO EASYLANGUAGEt
Page 235 and 236: into a project makes it easier to a
Page 237 and 238: If marketPosition =-1 thenbeginend;
Page 239 and 240: or program any trading idea. Practi
Page 241 and 242: CHAPTER 8Genetic Optimization,Walk
Page 243 and 244: superfast processors, searching a l
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Page 247 and 248: For generation = 1 To 100 ' total g
Page 249 and 250: Converting Fitness in Terms of Slic
Page 251 and 252: 'the 6 darts landedRandomizeFor l =
Page 253 and 254: roulette(i) = Rnd(1#)If roulette(i)
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Page 259 and 260: history of each market. This test w
Page 261 and 262: Crossover RateThe rate that determi
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Page 265 and 266: TABLE 8.3In-Sample Testing TA2Le Se
Page 267 and 268: Here are the various calculations t
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Page 271 and 272: TABLE 8.6The Out-of-Sample (OOS) Re
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Page 279 and 280: Calculating Start Trade Drawdown Wi
Page 281 and 282: A loop is used to flow through each
Page 283: The maximum drawdown of this algori
Page 287 and 288: FIGURE 9.2Add a strategy to your st
Page 289 and 290: 276FIGURE 9.6The UGTATS markets and
Page 291 and 292: 278FIGURE 9.9 How to adjust the set
Page 293 and 294: FIGURE 9.12 The Trade Analysis wind
Page 295 and 296: 282PORTFOLIO ANALYSISFIGURE 9.15thi
Page 297 and 298: FIGURE 9.18 Profit and drawdown are
Page 299 and 300: FIGURE 9.20 To set the portfolio st
Page 301 and 302: FIGURE 9.24Source: TradeStationThe
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Page 305 and 306: APPENDIX AAmiBrokerHere is a brief
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Page 309 and 310: Here is the source code from Chapte
Page 311 and 312: PctSize = PositionRisk * MarginDepo
Page 313 and 314: ■ KeywordsprevMarketPositionmarke
Page 315 and 316: upSumAvg = upSum / lengthdnSumAvg =
Page 317 and 318: Sub BollingerBand(dataList, length,
Page 319 and 320: 308EXCEL SYSTEM BACKTESTERIf (kVal
Page 321 and 322: ■ Keywords and Identifierscurrent
Page 323 and 324: 312PYTHON SYSTEM BACKTESTERdef calc
Page 325 and 326: sysMark =self.systemMarkets[i]avgLo
Page 327 and 328: class stochClass(object):class stoc
Page 329 and 330: 318PYTHON SYSTEM BACKTESTERfor i in
Page 331 and 332: ■ Python-Specific Keywordsandasas
Page 333 and 334: 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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