Drawdown:K-ratio:
Portfolio Statistics3,639,699Sharpe ratio:–5,379,816Correlation to breakout:0.04Correlation 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: 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#Avg.Avg. Avg.Sharpeof%Avg.ProfitAvg.Avg. Bars BarsMarket Net Profit K-ratio Ratio Max DD Trades Win hrs (000) Per Con. WinLossWin LossEnergySLB –1,114,709 –0.37 –0.62 –1,176,491 98 29 16.21–711 41,766 –32,846 4818XOM –341,848 –0.02 –0.21 –548,860 85 33 40.05–101 44,676 –27,983 5617MaterialsAA483,842 –0.01 0 .23 –- 627,908 67 61 55.76129 52,430 –64,112 2970DD–747,099 –0.19 –0.44 –851,999 93 25 21.41–369 57,175 –29,289 5218IP-578,611 –0.17 –0.34 –690,728 92 27 16.59–379 51,162 –27,726 4721IndustrialsBA149,321 –0.03 0 .08 –376,877 84 42 21.0078 45,739 –29,857 4919GE–327,028 –0.12 –0.19 –559,866 92 33 74.67–48 57,257 –32,979 4918MMM –792,741 –0.23 –0.48 –941,071 88 32 13.61–715 36,187 –31,163 4819ConsumerDIS–128,991 –0.07 –0.07 –640,885 87 37 36.48–48 54,328 –34,355 4819252,861 –0.03 0.13 –615,757 83 39 13.32201 55,063 –30,195 5218Discretionary GMHD176,280 –0.04 0.09 –771,980 82 34 59.7526 66,958 –32,345 5721WMT–22,740 –0.02 –0.01 –357,383 86 35 38.75–7 54,557 –29,639 5221ConsumerG–163,065 0.03 -0.09 –397,452 85 36 35.83–64 47,650 –30,977 4818KO–298,659 –0.07 –0.15 –616,407 92 34 25.82–126 55,421 –33,061 4817StaplesMO411,3800.12 0.21 –310,160 84 37 25.15185 63,691 –29,865 5517PG–315,105 –0.13 –0.17 –582,421 90 37 21.12–162 43,930 –30,832 4519Healthcare AMGN 1,012,277 0.11 0.43 –325,099 80 41 53.68237 78,990 –33,771 5320BMY–297,121 0.01 –0.16 –545,138 81 38 34.62–111 44,567 –33,880 5519JNJ–521,220 –0.09 –0.29 –901,286 89 36 38.24–153 44,004 –33,848 4720PFE–351,876 –0.04 –0.20 –567,932 94 34 81.17–49 48,965 –31,296 4717FinancialsAIG–639,405 –0.22 –0.37 –862,952 91 32 43.01–164 47,742 –32,672 5318FNM–471,699 –0.06 –0.27 –629,878 87 26 24.26–221 61,779 –29,486 5220MER39,0300.03 0.02 –410,838 87 38 51.280 59,889 –36,628 5115Information AAPL861,8430.15 0.51 –225,794 80 51 17.60570 47,403 –29,266 452226 71,740 –38,505 4820Technology DELL 1,163,746 0.14 0.48 –433,897 77 48 563.09IBM1,187,433 0.24 0.64 –310,699 84 44 20.00627 64,563 –28,403 4917INTC 1,491,884 0.28 0.64 –262,090 81 38 118.87147 94,360 –30,197 5319MSFT686,0180.10 0.30 –421,110 80 36 71.35109 85,942 –36,619 5618SUNW 773,9870.11 0.39 –243,662 80 43 229.3642 63,387 –30,060 5320TXN–252,623 0.02 –0.13 –435,710 92 34 85.06–35 58,237 –34,026 5118TelecomVZ–661,033 –0.20 –0.41 –794,355 93 38 21.86–334 32,253 –31,156 4718IndicesSPX–640,292 –0.08 –0.34 –831,995 93 31 2414.95–3 56,553 –35,630 5119NDX659,2420.12 0.33 –349,981 85 36 1704.794 79,842 –34,411 53188 107,004 –35,050 5618RUT 2,956,420 0.37 1.13 –177,565 72 53 5224.70Average 107,050 –0.01 0.02 –552,830 86 37 332.75–41 58,094 –33,004 50209,000,0008,000,0007,000,0006,000,0005,000,0004,000,0003,000,0002,000,0001,000,0000–1,000,000
0.160.960.89
© 2002 Lars Kestner – All Rights Reserved
FIGURE
8.7a
Second Order Breakout Strategy Applied to Stocks.
195
8.7b
199119921993
1994
Year
1995
Net Profit by Year
Performance Breakdown by YearNet ProfitK-ratio Sharpe RatioYear–727,01119960.862.081,597,36619970.091.11867,366–0.441998–0.931999–1,239,125–0.52–0.91–1,163,6812000–0.58–1.46–1,329,5260.7020012.18
Second Order Breakout Strategy Applied to Stocks.
FIGURE
–3,000,000
–2,000,000
–1,000,000
0
1,000,000
2,000,000
3,000,000
1990
Net Profit3,498,0942,616,477–1,255,023–1,003,530–1,920,8083,612,772
4,000,000
Year199019911992199319941995
AverageWin43,22153,58946,39457,72652,67354,13256,47069,37632,25381,133
1996
1997
1998
2000
2001
© 2002 Lars Kestner – All Rights Reserved
1999
Average Avg. Bars Avg. BarsLossWinLoss–30,41452174336–40,376–31,3334919–31,63352194918–31,1845019–33,1995218–32,9295119–32,439–31,1564718–35,0305318Profitability WindowsNum. ofNumber of Profitable PercentLength Windows Windows ProfitableK-ratio Sharpe Ratio144–0.0662–0.3443.06%1 Month1420.22620.6143.66%3 Months1390.14670.4648.20%6 Months133–0.5153–0.4839.85%12 Months127–0.2859–0.5846.46%18 Months121–0.1560–0.8749.59%24 Months
Breakdown Statistics (Stocks)
Second order breakoutCheck 20 to 80 day breakoutsEnter on 40 day breakout of second order indicator1/1/1990 – 12/31/2001Breakdown by Market SectorAverageAverage Avg. ProfitAverageAverageAverageMarketAverageK-ratio Sharpe Ratio Max DD Num Trades % Win Per ContractNet ProfitSectorEnergy–862,676–728,27992–0.2031–0.41–406Materials–280,6238438–0.12–206–0.19–723,545Industrials–625,938–323,48388–0.1335–0.20–228Discretionary–596,50169,35385–0.04360.0443Staples–91,3628836–0.01–42–0.05–476,610Healthcare–39,48586370.00–19–0.05–584,864Financials–357,3588832–0.09–128–0.21–634,556Info. Tech.844,61382420.152120.41–333,280Telecom–794,355–661,03393–0.2038–0.41–334Indices3–453,180991,790830.14400.37
System Name:Parameters:Description:Run Dates:
Net Profit
PART 2 Harnessing the Power of Quantitative Techniques to Create a Trading Program
196
FIGURE
8.8
MACD Histogram Retracement Strategy Applied to Coca-Cola.
Our version of the MACD histogram retracement requires the histogram toexceed one-half of the standard deviation of price changes over the past 20 daysbefore taking short signals. We require the histogram to be less than negative onehalf times the standard deviation of price changes over the past 20 days before taking long signals. Long signals are entered if the histogram retraces 25 percent ofits minimum value since its last cross below zero. Short signals are entered if thehistogram retraces 25 percent of its maximum value since its last cross above zero.The chart in Figure 8.8, above, depicts MACD histogram retracement signalsapplied to Coca-Cola (KO). In early October, a rally off a short-term low causesthe MACD histogram to rise from its short term low of –0.32. When the histogramrises above 75 percent of –0.32 (75% of –0.32 is –0.23), we enter long positions.A short entry is established in mid-November as the MACD histogram retraces 25percent of its maximum value—falling from 0.40 to 0.30.Performance of the MACD retracement strategy will not get anyone excited.Although better than most oscillator-type strategies, futures markets produce profits in only 5 of the 12 years tested (Figures 8.9a and 8.9b). Stocks produce profitsin only two of the 12 years tested (Figures 8.10a and 8.10b). Note, however, thatfour out of the past five years have been profitable on futures markets. Although
CHAPTER 8 New Ideas on Entries, Exits, and Filters
197
not ready to be traded today, the MACD retracement strategy may be one to keepan eye on in later years.Divergence IndexBuying pullbacks in uptrends and selling rallies in downtrends is one of myfavorite trading techniques. I created the Divergence Index to measure the strengthof such pullbacks. I believe that strong pullbacks within the context of evenstronger trends make the best entries. The Divergence Index measures pullbacksby multiplying two momentum indicators. We divide the product of the twomomentum measures by the variance of recent price changes in order to scale theindicator so results can be compared regardless of the market studied.Divergence Index = 10 day momentum ⭈ 40-day momentum / (40-day standarddeviation of price changes)^2One feature of charting the Divergence Index is that trading opportunitiesare extremely obvious. More times than not, the 10-day and 40-day trend are thesame when measured by simple momentum. When both momentum values areof the same sign (positive or negative), it leads to positive values for theDivergence Index. If we multiply two positive numbers together, the product ispositive. Multiplying two negative numbers also leads to a positive value. Wefocus on the negative values of the Divergence Index for establishing newentries. If one momentum measure is positive while the other is negative, it suggests that a short-term divergence in the longer term trend is occurring. Whenthe Divergence Index is negative, we want to make trades in the direction of thelonger term trend.Long entries are established when the Divergence Index is less than –10 and40-day momentum is greater than zero. Sell signals are generated when theDivergence Index is less than –10 and 40-day momentum is less than zero.Figure 8.11 details signals generated on Phillip Morris (MO). In late Octoberthe uptrend begins to stall as prices trade lower. While the 10-day momentum turnsnegative, the 40-day momentum is still positive. This leads to negative values forthe Divergence Index. When the Divergence Index falls below –10, we enter long,attempting to buy the pullback in the longer term trend. This long position coincided with a short-term market bottom.It’s interesting to note that further research may also be able to identify trendexhaustion by using the Divergence Index. Large positive values might coincidewith market tops and bottoms, or, at a minimum, they may lead to market congestion. If a market is overextended, both long-term and short-term momentum measures will show extreme values, leading to large positive values of the DivergenceIndex. An example of this trend exhaustion can be seen in the above chart duringlate September, when the Divergence Index rose above 150.
PART 2 Harnessing the Power of Quantitative Techniques to Create a Trading Program
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Trading Strategy Evaluation (Futures)
Net Profit:Drawdown:K-ratio:
Portfolio Statistics–3,110,671Sharpe ratio:–7,011,997Correlation to breakout:–0.04Correlation 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: MACD histogram retracementParameters:12 day/26 day/9 day MACD; retrace 25% of extremeDescription:Enter long when MACD histogram retraces 25% of extreme move; opp. for shortsRun Dates:1/1/1990 – 12/31/2001#Avg.Avg. Avg.Avg.Avg.Sharpeof%Avg.ProfitBars BarsMarket Net Profit K-ratio Ratio Max DD Trades Win Contracts Per Con. WinLossWin LossFXAD77,660 –0.02 0.04 –742,6705153 25.216656,696 –60,235 5363BP547,6500.11 0.28 –400,0005066 16.8466247,723 –59,853 4786CD–571,480 –0.18 –0.27 –936,0105744 46.78–229 49,422 –57,689 5053JY–965,038 –0.22 –0.43 –1,191,775 5349 14.28–1,447 42,796 –81,761 3378SF156,7750.00 0.08 –715,2885360 16.3320658,521 –80,698 4076RatesED–845,550 –0.19 –0.36 –1,429,175 4951 87.58–207 68,902 –108,827 5365TY–1,036,750 –0.30 –0.50 –1,504,016 5446 30.36–629 51,854 –80,271 3473US–765,094 –0.12 –0.39 –956,5005443 21.35–635 53,174 –63,074 4166StockSP270,7130.07 0.15 –489,81345589.1179256,709 –60,515 5481MetalsGC293,8500.05 0.13 –600,4405147 47.5812575,804 –56,156 4470HG10,325 –0.02 0.01 –909,8385062 33.592253,506 –85,354 5764PL810,6800.19 0.40 –323,6955564 48.5933051,191 –45,485 4859SL873,1350.15 0.48 –202,3304665 30.5557752,889 –48,488 5678EnergyCL–844,400 –0.07 –0.35 –1,487,060 5549 27.54–514 51,028 –77,000 4463HO–816,904 –0.12 –0.34 –1,089,682 5054 23.04–641 48,270 –88,769 5069HU–833,226 –0.11 –0.35 –1,113,563 6053 22.34–592 42,819 –77,272 3762GrainsC–255,750 –0.03 –0.12 –508,2135646 76.26–6560,792 –61,883 4163S120,488 –0.01 0.06 –538,7005250 29.325250,914 –47,855 4865W676,5630.14 0.35 –445,6385760 48.8123861,980 –62,783 4955MeatsFC173,005 –0.04 0.09 –509,6006260 39.675745,552 –61,828 3666LC–8,220 –0.04 0.00 –831,3244461 49.93349,835 –78,814 43 108LH–513,352 –0.22 –0.26 –833,1365450 31.67–291 44,270 –62,732 3972PB–202,960 0.04 –0.09 –531,9006053 20.72–110 47,413 –59,073 4456SoftsCC1,056,490 0.15 0.56 –316,1405060 49.4742864,446 –43,729 5269CT–664,015 –0.09 –0.38 –752,0254260 24.00–662 47,626 –109,320 48 103JO–1,2530.04 0.00 –482,2135958 33.482640,626 –53,211 4459KC384,5700.09 0.15 –641,6185066 11.9062358,052 –90,879 5565LB–596,960 –0.04 –0.20 –1,030,408 7260 32.79–239 48,822 –91,858 3058SB358,3770.09 0.19 –544,2644553 54.4314463,475 –55,785 5969Average –103,689 –0.02 –0.04 –735,2345153 33.45–6451,504 –67,040 44670–1,000,000–2,000,000–3,000,000–4,000,000–5,000,000–6,000,000–7,000,000–8,000,000
–0.23–0.49–0.51
© 2002 Lars Kestner – All Rights Reserved
FIGURE
8.9a
MACD Histogram Retracement Strategy Applied to Futures.
199
Net Profit–2,050,949348,342–780,411–2,038,258–356,741–483,338
Year199019911992199319941995
8.9b
1991199219931994
Year
1995
1996
Net Profit by Year
K-ratio–0.360.370.170.900.30–0.12
AverageWin51,03243,48356,70958,34747,37257,89546,76753,841
Average Avg. Bars Avg. BarsLossWinLoss4571–68,047–63,0433251–60,5155481–58,87051684464–81,014–57,50746614076–65,6124871–74,130
1997
1998
2000
2001
©2002 Lars Kestner – All Rights Reserved
1999
Num. ofNumber of Profitable PercentSharpe RatioLength Windows Windows Profitable77–0.8053.47%1 Month144740.5452.11%3 Months142139680.5648.92%6 Months551.9641.35%12 Months133127510.3740.16%18 Months44–0.3036.36%24 Months121
Average Average Avg. ProfitAverageAverageSharpe Ratio Max DD Num Trades % Win Per Contract5354–148–0.06–797,149–972,4233935–0.31–368–489,81345580.15792–509,07651590.252635552–582–0.35–1,230,102–497,51755520.10755556–86–0.07–676,4905359530.05–627,778
Performance Breakdown by YearYearNet ProfitK-ratio Sharpe Ratio–1,052,8151996–0.56–1.32412,5511997–0.020.32506,933–0.501998–0.762,227,3511999–0.25–1.363