41.51–142 52,154 –25,243 86 19XOM –447,922 –0.02 –0.26 –541,961Materials721,9660.12 0.40 –250,884 235 40 48.106135,536 –18,836 208AA–265,3760.02–0.14–479,546732322.97–14172,089 –26,109 95 18DD–1,112,854 –0.30 –0.65 –1,148,649 7915 17.70–795 61,491 –27,615 97 22IPIndustrials4,8600.00 0.00 –385,8085927 20.20475,617 –28,024 99 26BA349,7660.10 0.20 –364,8516434 79.637171,585 –28,926 94 14GE23 12.79 –1,066 41,279 –30,389 83 19MMM –1,016,660 –0.24 –0.57 –1,068,669 77Consumer326,8900.12 0.17 –191,9976333 36.7714170,385 –27,409 89 19DIS522,1450.15 0.30 –131,9605048 12.5183546,691 –23,017 87 20Discretionary GM425,1470.05 0.21 –407,1046821 61.5598123,029 –24,306 117 18HD216,9020.040.12–367,950622935.197376,994 –27,854 101 17WMTConsumer53,6860.08 0.03 –263,3385834 38.31268,186 –35,745 98 15G–202,2560.03 –0.09 –693,084 6620 23.79–129 121,941 –33,726 129 18KOStaples362,9900.12 0.19 –387,8175927 24.75253 101,668 –29,226 109 21MO–197,343 –0.01 –0.09 –546,0697722 22.92–143 88,192 –29,195 93 17PGHealthcare AMGN 1,300,388 0.13 0.52 –369,2045328 48.35510 152,821 –25,916 111 25331,1510.11 0.18 –411,9105726 32.0516797,871 –27,691 115 22BMY199,0630.05 0.09 –728,3866325 35.589498,255 –28,959 104 20JNJ4931 59.60475 146,145 –23,650 119 26PFE 1,398,474 0.22 0.62 –393,704Financials3,8850.04 0.00 –380,1187021 39.631197,927 –26,134 108 18AIG20 19.19–486 67,667 –29,156 95 16FNM –779,473 –0.06 –0.43 –1,076,581 83817,5970.13 0.38 –284,8525629 49.81297 122,951 –28,487 110 21MERInformation0.16 0.30 –192,7955332 18.4162885,244 –23,229 88 29AAPL 639,9495730 547.3169191,668 –27,503 115 17Technology DELL 2,171,902 0.17 0.45 –345,975198,5920.08 0.10 –453,0186028 18.3812081,820 –29,265 90 24IBM6526 84.70202 132,157 –23,686 98 19INTC 1,148,675 0.21 0.50 –348,9566130 56.31343 140,155 –31,254 108 16MSFT 1,191,043 0.17 0.46 –393,3570.10 0.32 –418,1195733 214.8461100,118 –30,413 95 19SUNW 746,5281,105,3340.200.47–275,614563697.2620499,957 –24,606 97 19TXNTelecom–441,685–0.01–0.27–508,096612821.47–38150,430 –30,815 96 22VZIndices0.04 –0.06 –569,651 7323 2275.32–185,035 –27,627 105 16SPX –110,761987,2730.27 0.46 –201,9435240 1610.301297,629 –33,229 100 19NDX6127,551 –29,641 90 205338 5270.06RUT 1,582,679 0.24 0.56 –168,2910.07 0.13 –444,6086829 323.924392,666 –27,708 98 19Average 360,14020,000,000Equity
15,000,00010,000,0005,000,000
Net Profit:Drawdown:K-ratio:
Portfolio Statistics12,244,768Sharpe ratio:–5,487,815Correlation to breakout:0.18Correlation to 10-40 MA:
Dec-01
Jan-01
Jan-00
Jan-99
Jan-98
Jan-97
Jan-96
Jan-95
Jan-94
Jan-93
Jan-92
Jan-90
Jan-91
0–5,000,000
0.440.850.75
© 2002 Lars Kestner – All Rights Reserved
FIGURE
8.4a
Kestner’s Moving Average System Applied to Stocks.
189
Breakdown Statistics (Stocks)
8.4b
1991
K-ratio0.210.24–0.14–0.41–0.211.20
1992
1993
1994Year
1995
1997
Sharpe Ratio0.370.700.870.11–0.55–1.87
1996
K-ratio0.000.230.21–0.15–0.30–0.49
Net Profit by Year
Performance Breakdown by YearYearNet ProfitSharpe Ratio881,73019960.293,063,86319971.861,986,8321998–0.64444,1311999–0.59–1,151,1912000–0.732001–3,309,8463.97
Kestner’s Moving Average System Applied to Stocks.
FIGURE
–4,000,000
–2,000,000
0
2,000,000
4,000,000
6,000,000
1990
Net Profit669,1564,485,590–781,404–684,393–867,5007,419,158
8,000,000
Year199019911992199319941995
System Name:Kestner’s moving average systemParameters:20 day averages, 80 day averagesDescription:Buy when 20 day and 80 day in agreement; exit on break below opposite 20 dayBreakdown by Market SectorRun Dates:1/1/2001 – 13/31/2001AverageAverage Average Avg. ProfitAverageAverageAverageMarketK-ratio Sharpe Ratio Max DD Num Trades % Win Per ContractNet ProfitSectorEnergy–217,85472260.00–72–0.13–454,182Materials–626,360–218,755129–0.0526–0.13–292Industrials–606,443–220,67867–0.0528–0.12–330Discretionary 372,771–274,753610.09330.20287Staples–472,5774,269650.06260.01–4Healthcare807,26956280.133120.35–475,801Financials–580,51714,003700.0423–0.02–59Info. Tech.1,028,86058310.162330.37–346,833Telecom–508,096–441,68561–0.0128–0.27–381Indices819,730596340.180.32–313,295
Net Profit
1998
2000
2001
© 2002 Lars Kestner – All Rights Reserved
1999
Average Avg. Bars Avg. BarsLossWinLoss9118–25,214–24,1877116–29,1139220–25,6479819–31,9731071811323–26,554–27,926104189920–27,137–30,8159622–30,1669819Profitability WindowsNum. ofNumber of Profitable PercentLength Windows Windows Profitable7350.69%1 Month1441427049.30%3 Months7352.52%6 Months1391338060.15%12 Months8667.72%18 Months1271217662.81%24 MonthsAverageWin60,27956,37262,82779,27594,997123,77396,182118,73150,430103,405
PART 2 Harnessing the Power of Quantitative Techniques to Create a Trading Program
190
ing on breakouts of prices, we create signals based on channel breakouts of theSecond Order Breakout statistic. The logic behind this strategy is as follows: Iftoday’s Second Order Breakout statistic is both the highest value over the past 40days and greater than 20, then long positions are established. If today’s SecondOrder Breakout statistic is both the lowest value over the past 40 days and less than–20, then short positions are established.The beauty of the Second Order Breakout is that price moves of varyingdegrees are assessed and ranked. If a 40-day high was recently made, then today’s20-day high is somewhat discounted. For the 20-day high not to be a 40-day high,prices must be consolidating and the trend could be changing. As such, we maywish to take a pass on a typical channel breakout buy signal because the marketappears to be consolidating, losing steam, and prone to reversal. The Second OrderBreakout helps to spot these trend changes.The chart in Figure 8.5, below, displays signals generated on Intel (INTC).In May, a rally resulted in a 20-day high, as indicated by a Second Order Breakoutstatistic value of 20. In addition, because the 20-day high was the most extremehigh over the past 40 days, we enter long. This rally had legs, extending the 20-dayhighs to 80-day highs in mid-July. Again, this is indicated by the Second Order
FIGURE
8.5
Second Order Breakout Strategy Applied to Intel.
CHAPTER 8 New Ideas on Entries, Exits, and Filters
191
Breakout statistic value of 80. A sell-off in late July causes the market to make a20-day low and a corresponding Second Order Breakout statistic value of ⫺20.Because the Second Order Breakout statistic was the lowest value of the past 40days, we enter short.The unique idea of the Second Order Breakout does not transfer to bottomline performance. While I think there is merit in its logic, the second order strategyunderperforms standard trend-following strategies. The standard 40-day entry/20day exit channel breakout from Chapter 7 (see Figures 7.11a through 7.12b) produced a Sharpe ratio of 0.41 on futures, 0.16 on stocks, a K-ratio of 0.12 on futures,and 0.06 on stocks. Each of these reward-to-risk measures outperforms the corresponding measures of the Second Order Breakout strategy seen in Figures 8.6athrough 8.7b. We’ll have to take the Second Order Breakout back to the drawingboard for more work before employing it in our tradingMACD Histogram RetracementThe third new technique involves the widely used Moving Average Convergence/Divergence indicator (MACD), created by Gerald Appel. The MACD is itself anoscillator created by taking the difference between two exponential moving averages. An exponential moving average of the MACD—often referred to as the “signal line”—generates buy and sell signals from crossovers. When the MACDcrosses above its signal line, we buy the market. When the MACD falls below itssignal line, we sell the market. The default parameters are a 12- and 26-day EMAfor the MACD and a 9-day EMA for the signal line. The MACD histogram is plotted by subtracting the value of the MACD signal line from the MACD value.Often, the histogram will generate early warning signals when trends are about tochange.MACD = 12-day exponential moving average of close – 26-day exponentialmoving average of closeMACD Signal = 9-day exponential moving average of MACDMACD Histogram = MACD – MACD SignalThe MACD histogram retracement system uses the MACD histogram’s ability to spot trend reversal early and turns that ability into profitable trading signals.The strategy generates a buy signal when the histogram retraces x percent of itsprior trough when below zero. It generates a sell signal if the histogram retraces xpercent of its prior peak when above zero. To avoid whipsaws, we require the histogram to reach some minimum threshold above zero before taking short entrysignals, and some minimum threshold below zero before taking long entries. Weare using the early warning power of the MACD histogram, and harnessing it bytrading once it reverses a set amount from its last peak or trough.
PART 2 Harnessing the Power of Quantitative Techniques to Create a Trading Program
192
Trading Strategy Evaluation (Futures)Strategy Name: Second order breakoutParameters:Check 20 to 80 day breakoutsDescription:Enter on 40 day breakout of second order indicatorRun Dates:1/1/1990 – 12/31/2001
Net Profit:Drawdown:K-ratio:
Portfolio Statistics3,286,823Sharpe ratio:–2,627,541Correlation to breakout:0.07Correlation to 10-40 MA:
Dec-01
Jan-01
Jan-00
Jan-99
Jan-98
Jan-97
Jan-96
Jan-95
Jan-94
Jan-93
Jan-92
Jan-91
Jan-90
Equity
#Avg.Avg. Avg.Sharpeof%Avg.ProfitAvg.Avg. Bars BarsMarket Net Profit K-ratio Ratio Max DD Trades Win Contracts Per Con. WinLossWin LossFXAD–431,470 –0.12 –0.24 –754,4508734 25.52–19547,617 –32,661 4721BP159,700 –0.01 0.09 –359,2508335 17.3210353,846 –26,164 5021CD–179,170 –0.03 –0.08 –487,9808733 46.03–4557,786 –31,982 4721JY978,7630.22 0.47 –234,7258138 13.9677373,932 –28,351 5519SF755,3880.22 0.40 –175,1138444 15.7359155,276 –26,913 5116RatesED2,609,000 0.28 1.09 –278,1507049 89.59416 111,070 –32,427 6217TY636,5160.11 0.30 –334,9847942 29.4525762,847 –32,063 5618US297,7500.07 0.16 –360,0008041 20.2815856,289 –34,055 5418StockSP–777,238 –0.16 –0.44 –917,85095328.99–88445,666 –32,691 4520MetalsGC115,1500.01 0.05 –566,0008538 46.952856,141 –31,810 5020HG–259,338 –0.01 –0.15 –597,7258936 31.81–9246,099 –30,430 4817PL–1,226,845 –0.21 –0.67 –1,468,055 9830 49.87–26139,921 –35,247 4517SL–858,465 –0.23 –0.48 –980,1759730 35.22–27238,691 –30,192 4718EnergyCL502,8500.06 0.21 –310,1908442 28.2121761,765 –33,640 4920HO490,1520.10 0.18 –320,5448239 23.9525570,185 –34,907 5120HU–233,835 –0.02 –0.09 –533,6109638 22.40–10351,200 –34,415 4419GrainsC695,3630.17 0.31 –345,9138345 78.0810763,417 –35,893 5217S–925–0.06 0,00 –462,7638443 31.61–639,461 –29,942 4722W202,2250.09 0.09 –429,0888638 52.284863,001 –35,191 5217MeatsFC74,9800.05 0.04 –357,7458143 40.682147,051 –34,286 4820LC–427,096 –0.05 –0.22 –617,3368731 51.22–9551,901 –30,424 5221LH–81,3640.05 –0.04 –530,7008733 31.49–3356,003 –29,557 5420PB–4,068–0.03 0.00 –425,6448339 20.99–3156,497 –36,507 5220SoftsCC–643,040 –0.17 –0.33 –1,064,280 9123 50.46–15558,096 –27,582 5721CT96,690–0.04 0.05 –561,1808928 25.044383,553 –31,127 5819JO–872,835 –0.19 –0.38 –1,397,813 9126 35.38–27654,908 –32,914 4920KC1,028,269 0.14 0.31 –303,8818435 12.221,00981,991 –24,386 5420LB1,250,184 0.11 0.42 –278,9527743 33.3848385,908 –36,231 5419SB–610,467 –0.16 –0.31 –837,7389031 54.68–11854,505 –34,006 5019Average 109,5610.01 0.02 –543,0618335 34.096557,487 –30,866 49196,000,0005,000,0004,000,0003,000,0002,000,0001,000,0000–1,000,000
0.210.950.87
© 2002 Lars Kestner – All Rights Reserved
FIGURE
8.6a
Second Order Breakout Strategy Applied to Futures.
193
Net Profit1,495,4781,028,123310,111355,555111,0991,071,309
Year199019911992199319941995
8.6b
199119921993
1994
Year
1995
Net Profit by Year
AverageWin57,69157,55145,66645,21361,05055,29352,86369,827
Average Avg. Bars Avg. BarsLossWinLoss–29,21450204313–24,636–32,6914520–31,9204718–34,3214820–33,67550195120–32,694–31,0415419
1997
1998
2000
2001
© 2002 Lars Kestner – All Rights Reserved
1999
Num. ofNumber of Profitable PercentSharpe RatioLength Windows Windows Profitable72–0.0450.00%1 Month144142780.1754.93%3 Months76–0.2254.68%6 Months13913386–0.6464.66%12 Months127800.1862.99%18 Months79–0.1365.29%24 Months121
Avg. ProfitPer Contract245208–884–14912350–34164
1996
K-ratio0.12–0.110.00–0.31–0.030.04
Average AverageAverageMax DD Num Trades % Win–402,30484375733–243,284–917,8509532–902,9899233–388,1158739–412,58884428537–482,856–740,6418731
Performance Breakdown by YearNet ProfitK-ratio Sharpe RatioYear–80,2930.3919961.01225,6700.1619970.68–282,39419980.110.27–1,147,7520.0119990.31238,8550.0720000.07–113,28320010.161.18
AverageAverageK-ratio Sharpe Ratio0.050.130.110.39–0.16–0.44–0.11–0.310.050.100.070.130.00–0,06–0.05–0.04
Second Order Breakout Strategy Applied to Futures.
FIGURE
–1,500,000
–1,000,000
–500,000
0
500,000
1,000,000
1,500,000
1990
AverageNet Profit256,642885,816–777,238–557,374253,056298,888–109,38741,467
2,000,000
Breakdown Statistics (Futures)
Second order breakoutCheck 20 to 80 day breakoutsEnter on 40 day breakout of second order indicatorBreakdown by Market Sector1/1/1990 – 12/31/2001
MarketSectorFXRatesStockMetalsEnergyGrainsMeatsSofts
System Name:Parameters:Description:Run Dates:
Net Profit
PART 2 Harnessing the Power of Quantitative Techniques to Create a Trading Program
194
Trading Strategy Evaluation (Stocks)
Net Profit: