Profit–3,285,612–651,258–2,427,188–2,175,495453,143–816,567
3,000,000
Year199019911992199319941995
MarketSectorFXRatesStockMetalsEnergyGrainsMeatsSofts
Breakdown Statistics (Futures)
Normalized envelope indicator50 days compared to 50 day average, NEI uses #10 and #40 ranksEnter long when close < lower NEI band, enter short when close > upper NEI band1/1/1990 – 12/31/2001Breakdown by Market SectorAverageAverage Avg. ProfitAverageAverageAverageAverage AverageWinK-ratio Sharpe Ratio Max DD Num Trades % Win Per ContractNet Profit–1,014,543–548,22336,28779–0.0855–0.26–315–221,47266–0.0642–168–0.1232,117–868,368–278,988838,98831,5331000.23710.48997–652,498–27,684850.0058–0.01–235,499–670,969105,67746,118860.05560.0559–830,742–386,19280–0.0455–0.17–8138,06339,74689590.05–160.0336,265–601,271–918,976–328,32586–0.0460–0.15–19535,041
System Name:Parameters:Description:Run Dates:
Net Profit
216
CHAPTER 8 New Ideas on Entries, Exits, and Filters
217
Trading Strategy Evaluation (Stocks)
Avg. Avg.Avg. Bars BarsLoss Win Loss–48,842 22 44–42,872 21 43–14,000 124–59,147 24 51–42,355 21 48–48,380 26 40–37,138 25 36–44,352 28 43–43,495 23 45–57,309 26 46–51,174 25 37–53,920 28 50–43,529 23 43–55,925 27 47–61,285 26 51–50,165 29 48–62,631 26 47–46,869 23 39–50,982 22 48–60,972 25 45–49,657 22 41–42,478 18 38–59,622 24 45–53,761 28 49–70,242 22 48–69,198 31 48–71,319 23 45–65,493 27 43–70,760 24 50–52,052 23 41–50,562 21 47–42,651 25 41–58,110 24 44–89,788 26 49–53,560 24 44
Net Profit:Drawdown:K–ratio:
Portfolio Statistics–8,034,193Sharpe ratio:–10,324,072Correlation to breakout:–0.22Correlation to 10–40 MA:
–0.38–0.23–0.24
© 2002 Lars Kestner – All Rights Reserved
FIGURE
8.19a
Normalized Envelope Indicator Strategy Applied to Stocks.
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: Normalized envelope indicatorParameters:50 days compared to 50 day average, NEI uses #10 and #40 ranksDescription:Enter long when close < lower NEI band, enter short when close > upper NEI bandRun Dates:1/1/1990 – 12/31/2001#Avg.ofSharpe%Avg.ProfitAvg.Market Net Profit K–ratio RatioMax DD Trades Win hrs (000) Per Con. WinEnergySLB–114,139 –0.01 –0.06 –544,36998 6216.14–31 28,810XOM –687,879 –0.22 –0.45 –905,06899 5843.12 –165 19,259MaterialsAA–1,455,002 –0.12 –0.13 –4,844,244 2293 3512.37–56 24,012DD–103,561 –0.08 –0.06 –784,45888 6520.45–39 30,923IP141,2810.03 0.07 –383,52598 6416.39110 26,330IndustrialsBA305,0880.06 0.18 –493,96494 6121.37170 37,387GE670,1710.14 0.35 –358,230103 5877.2280 37,247MMM –444,449 –0.09 –0.24 –691,45386 5513.71 –319 28,791ConsumerDIS329,4460.01 0.17 –361,68794 5936.11100 37,001–892,065 –0.25 –0.48 –1,004,65286 5313.64 –763 30,373Discretionary GMHD139,237 –0.02 0.07 –440,269102 6276.3221 34,271WMT–4,4410.05 0.00 –635,95383 6137.79–7 33,391ConsumerG–281,908 –0.04 –0.16 –518,22294 5636.15–71 29,128KO–221,412 –0.03 –0.12 –656,13885 6028.08 –102 32,530StaplesMO–693,692 –0.18 –0.34 –936,62479 5225.11 –341 40,322PG–310,1360.00 –0.16 –497,05980 5819.96 –179 30,870Healthcare AMGN 235,565 –0.02 0 .10 –658,79889 6275.3937 43,215BMY–407,594 –0.02 –0.25 –728,39099 5832.55 –108 28,456JNJ–83,5550.01 –0.05 –629,00295 6236.50–29 29,402PFE–767,515 –0.27 –0.43 –968,13188 5769.16 –127 30,845FinancialsAIG–610,897 –0.21 –0.34 –868,55198 5537.85 –159 29,574FNM–169,531 –0.10 –0.10 –644,898115 6022.97–69 25,666MER67,5810.05 0.04 –479,61294 6355.8417 36,895Information AAPL –199,920 –0.05 –0.10 –654,07878 5317.08 –106 45,07388 55 589.36–11 46,662Technology DELL –616,552 –0.01 –0.26 –1,142,010IBM–485,297 –0.03 –0.24 –717,49379 5720.20 –295 41,837INTC –808,817 –0.14 –0.36 –1,235,84992 55 129.06–62 42,826MSFT –378,7540.01 –0.18 –730,51788 5877.94–44 41,577SUNW –1,070,027 –0.15 –0.52 –1,314,21184 54 236.18–54 37,426TXN128,117 –0.01 0 .07 –731,43998 5984.4016 38,169TelecomVZ–282,3750.02 –0.16 –1,034,67495 6122.55 –118 27,912IndicesSPX 1,099,655 0.26 0.57 –297,99698 66 2337.275 39,180NDX–301,906 –0.12 –0.14 –958,99090 54 1448.44–2 42,4981 67,746RUT241,0900.07 0.08 –735,46884 60 5799.64Average –236,300 –0.04 –0.11 –840,765156 58 340.77–79 35,1652,000,0000–2,000,000–4,000,000–6,000,000–8,000,000–10,000,000
8.19b
1991
K-ratio–0.26–0.26–0.46–0.02–0.25–0.27
1992
Sharpe Ratio–0.63–0.21–1.22–0.34–0.72–0.72
Year199619971998199920002001
1993
Normalized Envelope Indicator Strategy Applied to Stocks.
FIGURE
1990
Net Profit–1,196,397–373,994–1,829,761–471,818–1,196,252–1,347,115
2,500,0002,000,0001,500,0001,000,000500,0000–500,000–1,000,000–1,500,000–2,000,000–2,500,000–3,000,000
Year199019911992199319941995
1994
Year
1995
1996
1997
K-ratio Sharpe Ratio0.02–0.360.020.23–0.34–0.810.512.95–0.53–1.560.260.99
Net Profit by Year
Net Profit–642,849524,114–1,594,6501,894,966–2,527,312971,527
Performance Breakdown by Year
Breakdown Statistics Stocks)
Average Avg. Bars Avg. BarsLossWinLoss–45,8572243–38,50119342640–43,2902544–51,4742647–52,726–55,3632445–50,5862141–64,6892546–50,5622147–63,5162544Profitability Windows
1998
2000
2001
© 2002 Lars Kestner – All Rights Reserved
1999
Num. ofNumber of Profitable PercentLength Windows Windows Profitable6847.22%1 Month1441425840.85%3 Months1394028.78%6 Months2518.80%12 Months1331272519.69%18 Months1211512.40%24 Months
System Name:Normalized envelope indicatorParameters:50 days compared to 50 day average, NEI uses #10 and #40 ranksDescription:Enter long when close < lower NEI band, enter short when close > upper NEI bandRun Dates:1/1/1990 – 12/31/2001Breakdown by Market SectorAverageAverageAverage Average Avg. ProfitAverageAverage AverageMarketWinK-ratioSharpe Ratio Max DD Num Trades % Win Per ContractNet ProfitSectorEnergy–724,719–401,00924,03499–0.1260–0.26–98Materials5–2,004,076–472,42727,088826–0.0655–0.04Industrials176,93794580.04–230.0934,475–514,549Discretionary –106,95691–0.0559–162–0.0633,759–610,640Staples–376,78785–0.0656–173–0.1933,213–652,011Healthcare–746,080–255,77593–0.0860–0.15–5732,980Financials–664,354–237,616102–0.0959–0.13–7030,712Info. Tech.–932,228–490,17987–0.0556–0.23–7941,939Telecom–1,034,674–282,375950.0261–0.16–11827,912Indices–664,151346,2801910.0749,808600.17
Net Profit
218
CHAPTER 8 New Ideas on Entries, Exits, and Filters
FIGURE
219
8.20
Multiple Entry Oscillator Strategy Applied to International Paper.
exited. Our first short position is entered as the oscillator drops below 45. The second is entered as the oscillator falls below 30, and the third and final short entryis established as the oscillator drops below 15. The last signal on the chart is ashort cover of one unit as the oscillator rises back above 15.Figure 8.21 illustrates the equity curve of the Multiple Entry OscillatorSystem applied to our futures markets. Performance is good, earning just over$12,500,000 with a Sharpe ratio of 0.34 and a K-ratio of 0.23. However, theMultiple Entry Oscillator System leaves much to be desired, as performance doesnot approach the profitability of other trend-following strategies. Applied tostocks, profitability of the strategy truly deteriorates (Figure 8.22). With a loss ofover $21,000,000, a Sharpe ratio of –0.39 and a K-ratio of –0.18, stocks produceprofits in only 5 out of 12 years.Adjusted StochasticIn the March 1998 issue of Futures magazine, Mark Etzkorn and George Pruittintroduced a channel breakout system that adjusts its length based on changes inmarket volatility. In their system, as the standard deviation of closes increased,
PART 2 Harnessing the Power of Quantitative Techniques to Create a Trading Program
220
Multiple Entry Oscillator Strategy (Futures)$16,000,000$14,000,000$12,000,000
Profit
$10,000,000$8,000,000$6,000,000$4,000,000$2,000,000$01/2/00
1/2/01
1/2/00
1/2/01
1/2/99
1/2/98
1/2/97
1/2/96
1/2/95
1/2/94
1/2/93
1/2/92
1/2/91
1/2/90
–$2,000,000
Date
FIGURE
8.21
Multiple Entry Oscillator Strategy Applied to Futures.
Multiple Entry Oscillator Strategy (Stocks)$15,000,000$10,000,000$5,000,000
Profit
$0–$5,000,000–$10,000,000–$15,000,000
DateFIGURE
8.22
Multiple Entry Oscillator Strategy Applied to Stocks.
1/2/99
1/2/98
1/2/97
1/2/96
1/2/95
1/2/94
1/2/93
1/2/92
1/2/91
–$25,000,000
1/2/90
–$20,000,000
CHAPTER 8 New Ideas on Entries, Exits, and Filters
221
they also increased the look-back range of their breakout entries. More volatilemarkets would require as much as a 60-day channel breakout to initiate longs orshorts, while less volatile markets could require as small as a 20-day channelbreakout to initiate trades.This thinking sparked me to apply the idea and create a new oscillator thatwould also adjust based on market volatility. While my procedure and definitionof market volatility is different than Etzkorn and Pruitt’s, the rationale is similar.Oscillators are wonderful tools for calculating the relative price ranges over theshort term. The problem, however, is that in times when prices are less volatile andnot moving, small price changes can cause oscillator readings to exhibit overbought and oversold conditions. As prices become more volatile, indicated by alarge 14-day range, then recent price moves should have more weight than duringperiods of low volatility accompanied by small 14-day price ranges. For that reason, I introduce a new adjusted stochastic that adjusts a 14-day Slow %K stochastic using a combination of the high-to-low range of the past 14 days and the highto-low range of the past 100 days.New Stochastic = (14-day Slow %K stochastic – 50) ⭈ (highest high of past 14days – lowest low of past 14 days)/(highest high of past 100 days – lowest low ofpast 100 days) + 50Essentially, we rescale the 14-day stochastic based on the relative volatilityof the past 14 days to the volatility of the past 100 days.As expected, we see that the new stochastic measure is muted compared to atypical 14-day %K stochastic. Values of our new oscillator typically range between35 and 65, compared to more typical ranges of 20 and 80 seen by short-term oscillators. As such, we need to adjust our extreme values that generate trading signals.We will take countertrend short positions when the adjusted stochastic rises above65 and then falls back below 65. Countertrend long positions are entered when theadjusted stochastic declines below and then rises back above 35.Signals for our adjusted stochastic are applied to Texas Instruments (TXN)in the Figure 8.23 chart. The strength of the September rally causes our adjustedstochastic to rise above 80—a powerful move indeed. As prices retrace, we entershort in early October as the adjusted stochastic falls below 65. The subsequentdecline takes the adjusted stochastic below 35 in late October. We enter long on arise of the adjusted stochastic above 35 at the beginning of November.On futures markets (Figures 8.24a and 8.24b), our adjusted stochastic generates a Sharpe ratio of –1.08 and a K-ratio of –0.43. On stocks (Figures 8.25a and8.25b), our adjusted stochastic generates a Sharpe ratio of –0.97 and a K-ratio of–0.32. Among the worst performing futures sectors are interest rates, currencies,and petroleum. Among the worst performing stock sectors are health care, financials, and technology.
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FIGURE
8.23
Adjusted Stochastic Strategy Applied to Texas Instruments.
Many traders might quickly write off this performance and move on to something profitable. Remember that some of the worst performing strategies are actually diamonds in the rough. Performance of the adjusted stochastic strategy is sobad that I would consider using the exact opposite of the rules as the basis of aprofitable strategy.Three in a RowYou might be surprised at how well very simple ideas work. The principle of threein a row sounds simple, yet the results are very powerful. We buy when three conditions are met:1. Today’s close is greater than the close five days ago.2. The close 5 days ago is greater than the close 10 days ago.3. The close 10 days ago is greater than the close 15 days ago.Short entries are similar, also requiring three conditions:
CHAPTER 8 New Ideas on Entries, Exits, and Filters
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Trading Strategy Evaluation (Futures)
Avg.BarsLoss838180119109125109101130104126931151119184110721257392103829812090908710397
Net Profit:Drawdown:K-ratio:
Portfolio Statistics–14,703,893Sharpe ratio:–15,093,668Correlation to breakout:–0.43Correlation 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: Adjusted stochasticParameters:14 day Slow %K adjusted by 100 day rangeDescription:Enter long when adjusted Stochastic < 35, enter short when adjusted Stochastic > 65Run Dates:1/1/1990 – 12/31/2001#Avg.Avg.ofProfitBarsSharpeAvg.Avg.Avg.%WinMarket Net Profit K-ratio RatioMax DD Trades Win Contracts Per Con. WinLossFXAD–691,280 –0.21 –0.38 –858,9004953 25.58–543 32,879 –66,736 41BP–357,925 0.00 –0.20 –571,3255760 18.05–323 27,727 –55,443 34CD–95,7000.02 –0.04 –623,4706062 46.54–3337,798 –64,774 32JY–1,309,588 –0.15 –0.67 –1,312,188 3644 13.54–2,398 42,937 –92,789 37SF–895,550 –0.19 –0.46 –1,037,525 3951 15.75–1,470 34,059 –83,367 35RatesED –2,579,300 –0.18 –1.12 –2,605,975 3554 90.25–424 43,863 –135,845 33TY –1,438,625 –0.21 –0.75 –1,631,141 4045 29.17–1,204 36,478 –93,704 34US –1,484,750 –0.21 –0.78 –1,586,344 4448 20.69–1,591 33,263 –93,327 32StockSP–115,538 –0.11 –0.07 –1,172,938 53748.26–253 37,245 –111,663 30MetalsGC53,110 –0.05 0.02 –896,4504659 43.283255,024 –74,788 37HG–827,200 –0.14 –0.43 –1,306,725 4055 32.68–608 39,619 –92,612 33PL–429,475 –0.07 –0.25 –693,1454661 49.32–144 29,630 –64,288 43SL486,0600.12 0.25 –397,5005173 30.7733241,135 –71,459 38EnergyCL –1,587,500 –0.39 –0.66 –1,752,940 3850 28.77–1,399 37,771 –118,260 45HO–591,641 –0.15 –0.26 –994,1575260 25.49–397 44,069 –90,136 33HU363,4390.08 0.14 –607,3456063 23.1028142,242 –55,283 29GrainsC–969,950 –0.17 –0.41 –1,265,750 4050 77.61–293 47,995 –93,484 38S113,2880.02 0.06 –591,2385859 30.057738,428 –48,811 37W–811,213 –0.12 –0.40 –1,046,488 4360 50.59–377 42,984 –113,965 33MeatsFC–475,865 –0.03 –0.23 –1,131,840 5558 39.36–212 39,616 –75,087 41LC–35,