Ultimate Algorithmic Trading System

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FIGURE 9.22The portfolio profit target and stop loss now appear as strategies in your portfolio.Go ahead and click Set Stop and you will see the Portfolio Profit Target willbe added to the Strategies. Before we click OK, let’s review both portfolio stopsto make sure we have the parameters properly set. Expand the Portfolio ProfitTarget and the Portfolio Stop Loss strategies. The settings should look exactlylike the ones in Figure 9.22.Just to review, the Portfolio Profit Target will cause the portfolio to ceasetrading once the portfolio achieves a 4 percent profit level and the Portfolio StopLoss will cease trading if the portfolio loses 4 percent. Once stopped, the portfoliowill start trading automatically at the beginning of the next month. Go ahead andclick OK and you will be returned to the MyFirstPortfolio window. You willnotice another item has been added to the list, Portfolio Stop. Take a quick lookat Figure 9.23.If you see that Portfolio Stop has been added, then click Backtest Portfolio.All other parameters that were used in the prior Portfolio Analysis should still be set:500,000 for Initial Capital and 10 Years Back for the test period. After the testfinishes click OK to view the report now. First off, click on the Graphs tab to see if287PORTFOLIO ANALYSISFIGURE 9.23At the bottom of your screen, you should see the portfolio stop option.www.rasabourse.com
FIGURE 9.24Source: TradeStationThe equity curve of the portfolio once the stops have been added.288PORTFOLIO ANALYSISthe equity curve looks any better utilizing the Portfolio Stops. Figure 9.24 showsthe equity curve of MyFirstPortfolio using the prescribed stop trading schemes.A quick look reveals a smoother equity curve than the one from the prior portfolioanalysis. Now click on the Summary tab and let’s look at the results in a tabularform. Here are the differences between the first test and this test, which usedportfolio stops:Test 1:Total Return: $1,307,354Number of Trades: 1685% Profitable: 30.92%Average Trade: $724.27Maximum Drawdown: $1,115,228.36Test 2:Total Return: $848,197Number of Trades: 1940% Profitable: 46.96%Average Trade: $425.63Maximum Drawdown: $350,500.34www.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
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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
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)
Page 255 and 256: selection and reproduction may even
Page 257 and 258: This is just one possible solution.
Page 259 and 260: history of each market. This test w
Page 261 and 262: Crossover RateThe rate that determi
Page 263 and 264: TradeStation’s and AmiBroker’s
Page 265 and 266: TABLE 8.3In-Sample Testing TA2Le Se
Page 267 and 268: Here are the various calculations t
Page 269 and 270: 1. movAvgLen { 50 to 150 by 10 incr
Page 271 and 272: TABLE 8.6The Out-of-Sample (OOS) Re
Page 273 and 274: your algorithm are each written on
Page 275 and 276: That’s it! These seven lines of c
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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 and 284: The maximum drawdown of this algori
Page 285 and 286: ■ Fixed Fractional272PORTFOLIO AN
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: FIGURE 9.20 To set the portfolio st
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Page 305 and 306: APPENDIX AAmiBrokerHere is a brief
Page 307 and 308: switchbreak (part of the switch sta
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
Page 335 and 336: FIGURE D.1324TRADESTATION AND EASYL
Page 337 and 338: Simple RSI with Profit Objective an
Page 339 and 340: If condition1 and condition2 then b
Page 341 and 342: 330TRADESTATION AND EASYLANGUAGEIf(
Page 343 and 344: if lastTradeLoser thenbeginif curre
Page 345 and 346: Value1 = swingHighBar(1,h,pivotHiSt
Page 347 and 348: ■■■■■■■Statistically
Page 349 and 350: 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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