8 3256 104.64 –449 50,028 –171,651 409TelecomVZ–36,979 –0.09 –0.02 –623,148 355423.6142,645 –50,185 510IndicesSPX2,845–0.04 0.00 –850,971 3669 2344.0554,205 –122,371 49NDX –1,212,027 –0.18 –0.51 –1,594,825 3352 1961.44 –18 59,048 –136,820 39–446,719 –136,678 33RUT –1,422,463 –0.19 –0.48 –1,937,955 5360 5820.5265Average –206,846 –0.03 –0.05 –1,001,102 4166 361.0750,775 –118,805 462,000,0000–2,000,000–4,000,000–6,000,000–8,000,000–10,000,000–12,000,000–14,000,000
–0.26–0.85–0.77
© 2002 Lars Kestner – All Rights Reserved
FIGURE
7. 2 9 a
RSI Strategy Applied to Stocks.
174
Breakdown Statistics (Stocks)
7. 2 9 b
RSI Strategy Applied to Stocks.
FIGURE
–8,000,000
–6,000,000
–4,000,000
–2,000,000
0
2,000,0001990
Net Profit–1,125,428–2,937,9351,144,756996,4491,080,710–7,161,716
4,000,000
Year199019911992199319941995
199119921993
1994
K-ratio0.11–0.15–0.070.040.420.53
Year
1995
Average Avg. Bars Avg. BarsLossWinLoss–121,14054202–56,8444292–94,92054143–101,15944133–112,77945147–150,70949153–121,87346151–153,07745135–50,18551123–131,95641132Profitability Windows
1996
1997
1998
2000
2001
© 2002 Lars Kestner – All Rights Reserved
1999
Num. ofNumber of Profitable PercentSharpe RatioLength Windows Windows Profitable14475–0.0452.08%1 Month14278–0.3554.93%3 Months13970–0.2650.36%6 Months66–0.2649.62%12 Months133127590.7546.46%18 Months5041.32%1.6524 Months121
Net Profit by Year
Performance Breakdown by YearYearNet ProfitK-ratio Sharpe Ratio–82,598–0.361996–0.55–1,533,5161997–0.14–1.28–641,54919980.340.93–1,125,25319990.410.881,823,55720000.241.032,582,2462001–1.00–3.63
System Name:14 day RSIParameters:14 days in RSI calculationDescription:Enter long when %K falls below 35, enter short when %K rises above 65Breakdown by Market SectorRun Dates:1/1/1990 – 12/31/2001AverageAverage Average Avg. Profit AverageAverageAverageAverageMarketWinK-ratioSharpe Ratio Max DD Num Trades % Win Per ContractNet ProfitSectorEnergy–696,587118,89331–0.01700.07–3851,383Materials–398,1581,112,02844,443700.18760.531,015Industrials–548,776207,958370.04680.1360451,918Discretionary –118,122–775,98547,66040–0.0163–0.05–166Staples–789,3407,22949,19540–0.04680.00–51Healthcare–1,257,143–378,78536–0.0667–0.12–15055,701Financials932,720–198,74636–0.0565–0.07–1656,317Info. Tech.–1,529,796–858,13150,38738–0.0963–0.25–147Telecom–36,979359–0.095442,645–0.02–623,148Indices–1,461,250–877,21541–0.1360–0.33–853,324
Net Profit
CHAPTER 7 Dissecting Strategies Currently Available
FIGURE
175
7. 3 0
MACD Strategy Applied to General Electric.
The MACD strategy is applied to General Electric (GE) in Figure 7.30. Inlate December the stock begins to roll over and the MACD crosses below its nineday exponential moving average. A short position is established based on thiscross. Prices then rally in mid-January. This rally causes the MACD to rally andcross above its signal line. At this point, our short positions are exited and a longposition is established.The MACD strategy leads to interesting performance results (Figures 7.31athrough 7.32b). MACD trading signals are almost half trend-following/half oscillator. The premise is to buy on periods of strength after declines and sell periods ofweakness after rallies. This hybrid strategy performs favorably on futures markets,leading to profits in 9 of 12 years. Currencies and softs produce the strongest gains.Stock performance is awful with the MACD strategy, generating losses in all 12years of the test. Notably weak are the energy, health care, and financial sectors.
A BASELINE FOR FUTURE TRADING STRATEGIESStandard trend-following strategies appear to work well on futures markets—especially currencies, interest rates, petroleum, and softs.
PART 2 Harnessing the Power of Quantitative Techniques to Create a Trading Program
176
Trading Strategy Evaluation (Futures)
Net Profit:Drawdown:K-ratio:
Portfolio Statistics5,052,672Sharpe ratio:–2,371,700Correlation 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-91
Jan-90
Equity
Strategy Name: MACDParameters:12 day minus 26 day exponential moving averages; 9 day EMA for signal lineDescription:Buy when MACD crosses above signal line, sell when MACD crosses below signal lineRun Dates:1/1/1990 – 12/31/2001#Avg.Avg. Avg.Sharpe%Avg.Avg.Avg.ofProfitBar BarsMarket Net Profit K-ratio Ratio Max DD Trades Win Contracts Per Con. WinLossWin LossFXAD499,1000.05 0.28 –347,580 234 4125.108332,449 –18,691 217BP994,7000.15 0.59 –376,750 234 4218.4622033,947 –17,849 198CD1,217,070 0.32 0.62 –196,410 230 4346.6511137,889 –19,956 208JY683,0880.14 0.35 –365,288 207 4113.7720339,742 –22,946 239SF202,9630.10 0.11 –276,350 229 3616.106239,256 –20,756 219RatesED–60,0250.00 –0.02 –516,775 230 3581.71–346,250 –25,480 219TY–593,688 –0.07 –0.28 –764,016 253 3629.36–8033,672 –22,584 207US–132,250 –0.04 –0.07 –555,156 251 3520.74–2536,660 –20,601 217StockSP–464,725 –0.16 –0.25 –670,450 252 368.64–20930,665 –20,159 217MetalsGC146,4500.00 0.07 –560,360 238 3545.181338,750 –20,242 218HG733,6750.23 0.39 –228,488 223 3832.289838,099 –18,363 209PL–978,775 –0.15 –0.49 –1,236,220 229 3347.57–9033,042 –22,851 229SL–286,210 –0.03 –0.17 –688,155 246 3535.40–4230,761 –18,830 208EnergyCL39,3600.10 0.02 –507,140 226 3727.74639,706 –23,237 228HO234,7050.14 0.11 –417,526 252 3323.033943,251 –19,902 217HU993,3500.23 0.44 –320,107 224 4022.5519342,116 –21,018 227GrainsC872,8880.23 0.43 –287,738 224 3876.854943,037 –19,804 219S313,0380.01 0.18 –424,700 218 4331.574231,604 –21,619 218W–309,400 0.02 –0.13 –569,363 256 3551.82–2436,157 –21,527 207MeatsFC-290,030 –0.03 –0.15 –510,045 246 3441.45–2937,891 –21,084 218LC–1,176,116 –0.16 –0.58 –1,288,976 266 2950.55–9031,242 –19,367 208LH166,7920.08 0.08 –612,732 231 3932.411739,172 –24,093 227PB100,016 –0.05 0.05 –542,488 246 3521.081640,168 –21,463 208SoftsCC-77,8500.00 –0.04 –584,930 247 3951.73–528,137 –18,325 198CT–301,615 –0.15 –0.14 –768,190 238 3224.69–5442,303 –21,419 219JO53,453–0.03 0.02 –667,253 221 3736.32534,447 –20,008 219KC1,002,731 0.16 0.43 –372,690 228 4113.4532938,259 –18,879 208LB1,436,816 0.19 0.54 –381,496 217 4134.8618949,938 –23,001 219SB33,162–0.03 0.02 –551,287 240 3653.93233,926 –18,795 218Average 168,4220.04 0.08 –519,622 228 3633.833436,085 –20,095 2088,000,0007,000,0006,000,0005,000,0004,000,0003,000,0002,000,0001,000,0000-1,000,000
0.390.340.29
© 2002 Lars Kestner – All Rights Reserved
FIGURE
7. 31 a
MACD Strategy Applied to Futures.
177
Net Profit854,0031,856,272147,20686,160–446,822–850,935
Year199019911992199319941995
7. 31 b
199119921993
1994
Year
1995
Net Profit by Year
AverageWin36,65729,14630,66535,16341,69136,93237,11837,835
Average Avg. Bars Avg. BarsLossWinLoss–20,040218–17,166166217–20,159–20,0722188–21,38622–20,984218218–21,502–20,071218
1997
1998
2000
2001
© 2002 Lars Kestner – All Rights Reserved
1999
Num. ofNumber of Profitable PercentSharpe RatioLength Windows Windows Profitable732.0450.69%1 Month144142811.0857.04%3 Months139861.1661.87%6 Months133903.8667.67%12 Months127950.1574.80%18 Months12189–1.5373.55%24 Months
Avg. ProfitPer Contract136–22–209–57922–2178
1996
K-ratio0.540.240.540.43–0.17–0.80
AverageAverage Average AverageSharpe Ratio Max DD Num Trades % Win–312,476227410.39–458,98718427–0.0925236–0.25–670,45023435–0.05–678,306–414,924234370.19–427,267233390.1624734–0.15–738,560–554,308232370.14
Performance Breakdown by YearYearNet ProfitK-ratio Sharpe Ratio1,792,44419960.370.8019971,310,5690.241.111,094,2600.0219980.17823,63719990.140.09155,987–0.222000–0.422001–1,787,280–0.60–1.20
AverageK-ratio0.15–0.03–0.160.020.160.09–0.040.02
MACD Strategy Applied to Futures.
FIGURE
–2,000,000
–1,500,000
–1,000,000
–500,000
0
500,000
1,000,000
1,500,000
2,000,000
1990
AverageNet Profit719,384–196,491–464,725–96,215422,472292,175–299,835357,783
2,500,000
Breakdown Statistics (Futures)MACD12 day minus 26 day exponential moving averages; 9 day EMA for signal lineBuy when MACD crosses above signal line, sell when MACD crosses below signal line1/1/1990 – 12/31/2001Breakdown by Market Sector
MarketSectorFXRatesStockMetalsEnergyGrainsMeatsSofts
System Name:Parameters:Description:Run Dates:
Net Profit
PART 2 Harnessing the Power of Quantitative Techniques to Create a Trading Program
178
Trading Strategy Evaluation (Stocks)
Portfolio StatisticsNet Profit: –19, 547,613Sharpe ratio:Drawdown: –22,783,630Correlation to breakout:K-ratio:–0.45Correlation 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
Strategy Name: MACDParameters:12 day minus 26 day exponential moving averages; 9 day EMA for signal lineDescription:Buy when MACD crosses above signal line, sell when MACD crosses below signal lineRun Dates:1/1/1990 – 12/31/2001#Avg.Avg. Avg.Sharpeof%Axg.ProfitAvg.Avg. Bars BarsMarket Net Profit K-ratio Ratio Max DD Trades Win hrs (000) Per Con. WinLoss Win LossEnergySLB –1,611,299 –0.38 –0.89 –1,672,655 268 2915.76–393 28,385 –20,655 208XOM –2,006,097 –0.46 –1.22 –2,068,201 289 2842.88–164 20,186 –17,804 187MaterialsAA–819,035 –0.20 –0.42 –955,868682153.17–220 58,673 –29,912 91 24DD75,572–0.03 0.04 –664,919 236 3819.1613 30,775 –18,578 218IP–558,913 –0.13 –0.31 –869,163 243 3516.53–138 30,540 –19,938 218IndustrialsBA–66,458 –0.06 –0.03 –727,796 240 3520.67–19 38,160 –20,787 218GE–480,315 –0.14 –0.25 –778,427 258 3477.75–24 33,228 –20,048 208MMM –1,071,521 –0.16 –0.54 –1,262,855 278 3213.48–283 28,942 –19,234 197ConsumerDIS–477,546 –0.10 –0.27 –881,630 264 3635.37–52 29,310 –19,349 197–482,876 –0.17 –0.25 –1,287,130 273 3213.47–130 35,623 –18,946 217Discretionary GMHD–1,060,629 –0.18 –0.48 –1,195,162 254 3467.61–62 33,712 –23,971 208WMT –633,736 –0.15 –0.34 –831,776 260 3339.34–63 33,113 –20,085 208ConsumerG–313,554 –0.06 –0.16 –775,555 247 3435.50–36 33,442 –19,182 218KO–49,826 –0.02 –0.03 –690,108 246 3627.25–7 34,756 –19,663 218StaplesMO–809,333 –0.17 –0.37 –998,070 246 3423.66–139 33,148 –22,170 208PG–1,372,431 –0.29 –0.60 –1,522,181 257 3221.20–252 30,116 –21,942 218Healthcare AMGN –217,951 –0.06 –0.10 –800,364 257 3466.20–16 36,834 –20,467 208BMY –1,895,602 –0.21 –0.98 –1,935,232 275 2733.32–206 31,566 –21,007 208JNJ–633,003 –0.08 –0.33 –1,043,705 248 3338.59–66 35,954 –21,248 218PFE –1,053,309 –0.09 –0.54 –1,196,174 266 2980.77–52 33,701 –19,874 217FinancialsAIG –1,243,293 –0.32 –0.63 –1,513,658 261 2942.37–114 37,443 –21,901 227FNM –2,517,708 –0.31 –1.31 –2,722,764 292 2722.34–386 26,169 –21,537 197MER–642,720 –0.21 –0.33 –931,673 253 3347.21–53 35,780 –21,541 208Information AAPL623,9570.22 0.32 –303,324 221 3817.22166 40,982 –20,984 238347,1170.08 0.15 –544,477 224 38 641.282 42,333 –23,464 219Technology DELLIBM2,202,199 0.47 1.26 –168,612 183 4621.22565 48,650 –19,100 24 10INTC –395,775 –0.09 –0.18 –1,089,055 249 31 102.16–16 44,438 –22,707 218MSFT –225,754 –0.07 –0.10 –1,023,672 229 3373.19–14 44,305 –23,564 238SUNW –323,229 –0.09 –0.15 –802,708 253 34 223.35–6 37,174 –21,575 217TXN–612,461 –0.10 –0.29 –894,591 251 3177.60–33 42,967 –23,051 227TelecomVZ–1,625,842 –0.25 –0.86 –1,722,823 270 3122.68–263 26,470 –20,870 197IndicesSPX–941,803 –0.20 –0.48 –1,082,298 260 30 2261.41–2 37,136 –21,361 217NDX–544,664 –0.16 –0.26 –1,055,940 255 31 1611.48–1 40,748 –21,867 2182 56,588 –25,724 228RUT 1,890,225 0.28 0.71 –357,993 224 42 5273.80Average –574,930 –0.11 –0.30 –1,069,722 247 33 328.79–72 36,216 –21,297 2385,000,0000–5,000,000–10,