,000500,0000–500,000–1,000,000–1,500,000
Breakdown Statistics (Futures)Moving average confluence method1 day/4 day, 2 day/8 day, …, to 20 day/80 dayEnter long when MACS > 60, enter short when MACD < 401/1/1990 – 12/31/2001Breakdown by Market Sector
MarketSectorFXRatesStockMetalsEnergyGrainsMeatsSofts
System Name:Parameters:Description:Run Dates:
Net Profit
210
CHAPTER 8 New Ideas on Entries, Exits, and Filters
211
Trading Strategy Evaluation (Stocks)
Net Profit:Drawdown:K-ratio:
Portfolio Statistics12,564,561Sharpe ratio:–4,434,865Correlation to breakout:0.19Correlation 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: Moving average confluence methodParameters:1 day/4 day, 2 day/8 day, …, to 20 day/80 dayDescription:Enter long when MACS > 60, enter short when MACD < 40Run Dates:1/1/1990 – 12/31/2001#Avg.Avg. Avg.Sharpe%Avg.Avg. Bars BarsofProfitAvg.Market Net Profit K-ratio RatioMax DD Trades Win hrs (000) Per Con. WinLoss Win LossEnergySLB–299,550 –0.03 –0.16 –538,6387033 16.77–274 62,541 –37,448 86 22XOM –322,433 –0.03 –0.19 –382,7506126 40.60–130 63,697 –29,805 95 33MaterialsAA–488,370 –0.03 –0.26 –633,1946438 49.74–157 49,173 –41,963 78 28DD–481,804 0.00 –0.25 –584,9697225 21.11–321 70,925 –32,679 85 27IP–1,284,632 –0.33 –0.65 –1,334,292 7423 16.79 –1,064 44,722 –36,526 76 30IndustrialsBA21,154 –0.05 0.01 –495,4966033 19.90–4 68,349 –34,282 92 29GE397,4600.11 0.20 –244,8525638 77.5692 84,200 –39,044 101 26MMM –649,652 –0.10 –0.36 –783,5447030 13.65–740 43,558 –33,090 74 29ConsumerDIS–39,653 –0.01 –0.02 –687,3707327 39.12–11 87,676 –33,675 86 24662,2560.12 0.37 –252,1995149 12.481,033 63,114 –35,403 91 28Discretionary GMHD977,8200.08 0.43 –587,8475725 53.79303 161,195 –30,860 124 29WMT190,6320.01 0.10 –590,1175237 39.7267 79,221 –41,402 99 33G–41,842 –0.04 –0.02 –459,9405838 34.76–43 65,184 –42,219 94 24ConsumerKO–574,376 –0.11 –0.25 –946,4806929 26.40–307 76,793 –42,763 89 25StaplesMO972,2360.21 0.48 –247,2815036 23.33826 106,953 –30,049 108 33PG–118,174 –0.01 –0.06 –330,4626826 20.93–102 78,277 –31,090 85 29Healthcare AMGN 802,5970.09 0.31 –375,2396032 54.25242 120,627 –36,694 94 30BMY475,9520.11 0.24 –331,0715340 35.00241 76,531 –36,256 98 29JNJ365,6940.05 0.18 –693,0685536 38.32192 86,865 –38,060 97 31PFE568,9100.13 0.26 –458,0465831 70.93139 109,264 –34,853 103 29FinancialsAIG666,2180.16 0.41 –229,4865240 41.83306 83,861 –35,365 103 27FNM–267,295 –0.05 –0.14 –592,2857221 23.18–152 98,847 –30,473 99 27MER125,5730.03 0.06 –417,9396335 50.6431 83,984 –42,678 93 23Information AAPL611,3370.10 0.28 –325,2345949 18.12530 67,045 –45,931 78 244939 596.4698 204,924 –34,783 110 30Technology DELL 2,878,617 0.18 0.65 –357,704IBM494,5530.12 0.23 –407,1556532 18.92328 87,931 –32,801 84 27INTC 1,352,515 0.26 0.57 –277,5226035 90.64239 124,720 –33,803 90 28MSFT433,2330.05 0.18 –699,7536832 61.8697 101,309 –39,547 85 24SUNW 1,490,155 0.18 0.65 –249,0065250 217.64133 93,569 –35,876 87 28TXN525,6970.15 0.22 –482,0045730 93.8399 128,513 –41,406 109 29TelecomVZ–50,9430.06 –0.03 –467,1865937 19.57–69 47,768 –30,555 91 26IndicesSPX194,9100.08 0.11 –477,1185829 2246.081 100,979 –37,604 107 29NDX 1,154,305 0.28 0.55 –181,6215141 1695.6513 107,114 –37,519 104 276 126,067 –41,092 92 32RUT 1,821,462 0.30 0.65 –243,5485145 5278.06Average 369,5460.06 0.14 –481,3066034 328.1748 89,868 –36,400 94 2818,000,00016,000,00014,000,00012,000,00010,000,0008,000,0006,000,0004,000,0002,000,0000–2,000,000
0.510.910.89
© 2002 Lars Kestner – All Rights Reserved
FIGURE
8.16a
Moving Average Confluence Method Strategy Applied to Stocks.
Breakdown Statistics (Stocks)
8.16b
199119921993
Moving Average Confluence Method Strategy Applied to Stocks.
FIGURE
1990
Net Profit1,889,8463,164,339388,988–761,218–1,384,9846,424,465
7,000,0006,000,0005,000,0004,000,0003,000,0002,000,0001,000,0000–1,000,000–2,000,000–3,000,000
Year199019911992199319941995
1994
Year
1995
1996
K-ratio0.020.250.31–0.23–0.24–0.33
Net Profit by Year
Performance Breakdown by YearYearNet ProfitK-ratio Sharpe Ratio825,69019960.561.252,678,43419970.191.492,374,95819980.020.40257,8271999–0.38–0.80–797,7072000–0.38–1.25–2,514,84120010.862.96
AverageWin63,11954,94065,36997,80281,80298,32288,897115,43047,768111,386
Average Avg. Bars Avg. BarsLossWinLoss9127–33,627–37,0568028–35,4728928–35,335100299428–36,5309830–36,466–36,1729826–37,73592279126–30,555–38,73810129Profitability Windows
1997
1998
2000
2001
© 2002 Lars Kestner – All Rights Reserved
1999
Num. ofNumber of Profitable PercentSharpe RatioLength Windows Windows Profitable144780.3454.17%1 Month700.8049.30%3 Months142139811.2958.27%6 Months750.0756.39%12 Months13312780–0.3162.99%18 Months12178–1.4064.46%24 Months
System Name:Moving average confluence methodParameters:1 day/4 day, 2 day/8 day, …, to 20 day/80 dayDescription:Enter long when MACS > 60, enter short when MACD < 40Breakdown by Market SectorRun Dates:1/1/1990 – 12/31/2001Average Average Avg. ProfitAverageAverageAverageAverageMarketSharpe Ratio Max DD Num Trades % Win Per ContractK-ratioNet ProfitSectorEnergy–310,9926630–0,03–202–0.18–460,694Materials–850,818–751,60270–0.1228–0.39–514Industrials–507,964–77,01362–0.0134–0.05–217Discretionary 447,764–529,383580.05340.22348Staples59,46161320.01930.04–496,041Healthcare553,28857350.102040.25–464,356Financials–413,237174,832620.05320.1161Info. Tech.–399,7681,112,301590.15380.40218Telecom–50,94359370.06–69–0.03–467,186Indices–300,7631,056,8927530.22390.44
Net Profit
212
CHAPTER 8 New Ideas on Entries, Exits, and Filters
213
NEI = (Close – Average of Past 50 Closes)/Standard Deviation of Past 50Price ChangesSort the NEI of the past 50 days. Then:Upper NEI band = Today’s 50-day moving average + value of 10th-ranked NEILower NEI band = Today’s 50-day moving average + value of 40th-ranked NEITo calculate the NEI we first compare today’s close to today’s 50-day moving average of closes. We divide this difference by the standard deviation of past50 price changes to arrive at today’s NEI value. This NEI value gives us a normalized measurement of where today’s price is in comparison to the past 50 days.Next, we compare yesterday’s close to yesterday’s 50-day moving average of closes. Again, we divide this difference by today’s standard deviation of past 50 pricechanges to arrive at yesterday’s NEI value. We continue this process until we have50 NEI values calculated from today’s price data and the 49 days prior.Once we have the 50 NEI values, we sort these in order, where the first valueis the greatest value and the 50th-ranked value is the smallest value. Next we create the upper NEI band by adding the 10th-sorted NEI value to today’s 50-daymoving average. We create the lower NEI band by adding the 40th-sorted NEIvalue to today’s 50-day moving average.I enter short when prices rise above and then fall below the upper NEI band. Longentries are initiated when prices fall below and then rise above the lower NEI band.Sample NEI signals are displayed in Figure 8.17 for ExxonMobil (XOM). The NEIseems to do well at predicting exhaustion points during trendless markets. As prices riseabove the lower NEI band in mid-August, we enter long. Profits are taken and shortsentered when prices fall below the upper NEI band just one week later.The NEI strategy generates some interesting performance quirks. Looking atthe futures data (Figures 8.18a and 8.18b), the NEI strategy produces a Sharperatio of –0.45 and a K-ratio of –0.04. At first glance, we would dismiss this performance due to a lack of profitability. But when we delve further, we see thatwhen tested on futures data, the NEI has produced profits five of the past six years.Note how the equity curve rises consistently from 1996 to the present. This characteristic suggests that perhaps performance has turned the corner and will beprofitable in the future.Stock performance is not as optimistic (Figures 8.19a and 8.19b). The NEIproduced profits when tested on stocks in just 3 of 12 years tested. Similar to thefutures performance, most of the positive performance has been recent. Three ofthe past five years were profitable.Multiple Entry Oscillator SystemOverbought/oversold indicators such as the Relative Strength Index (RSI) and stochastics are typically used to identify market tops and bottoms during exhaustion
PART 2 Harnessing the Power of Quantitative Techniques to Create a Trading Program
214
FIGURE
8.17
Normalized Envelope Indicator Strategy Applied to ExxonMobil.
phases of trends. I use the Multiple Entry Oscillator System in an entirely different manner. Using any oscillator, I add to longs as the trend becomes stronger,while I exit longs and enter shorts as the trend becomes weaker. The unique property of this strategy is that the strength of the trend determines the strength of oursignal. One sample of this method is:Oscillator crosses above 55: long one unitOscillator crosses above 70: long two unitsOscillator crosses above 85: long three unitsOscillator crosses below 45: short one unitOscillator crosses below 30: short two unitsOscillator crosses below 15: short three unitsWe utilize a 20-day Slow %K stochastic as the base oscillator for our tradingsignals. Our strategy can be long or short anywhere between one and three unitsdepending on the value of the 20-day Slow %K stochastic.The graph in Figure 8.20 details signals applied to International Paper (IP).As the market declines in the beginning of the test period, we see that longs are
CHAPTER 8 New Ideas on Entries, Exits, and Filters
215
Trading Strategy Evaluation (Futures)
Avg. Avg.Avg. Bars BarsLoss Win Loss–57,592 28 53–44,842 29 48–65,720 24 57–75,269 29 50–56,290 29 45–51,765 29 38–67,321 26 47–63,952 25 45–46,437 26 38–46,264 28 45–57,963 35 53–43,837 25 39–47,382 25 46–62,564 29 46–44,852 31 38–56,867 27 44–64,592 29 51–47,432 29 48–63,841 25 50–40,412 28 39–50,359 27 42–52,193 34 45–60,386 24 45–46,218 23 41–76,561 30 52–44,936 26 43–65,951 26 48–82,967 31 54–55,250 24 44–54,667 27 45
Net Profit:Drawdown:K-ratio:
Portfolio Statistics–5,551,261Sharpe ratio:–9,908,916Correlation 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: 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 – 12/31/2001Avg.#Avg.Avg.Profit%ofSharpeMarket Net Profit K-ratio RatioMax DD Trades Win Contracts Per Con. Win–335 32,734FXAD–642,110 –0.18 –0.34 –1,086,750 775524.85301BP425,1630.15 0.22 –458,888825918.2841,151–241 29,995CD–900,140 –0.07 –0.41 –1,198,100 785648.61–1,001 36,681JY–1,237,250 –0.24 –0.56 –1,549,738 775514.19–297 40,876SF–386,775 –0.08 –0.19 –779,238835316.1299RatesED741,9250.04 0.32 –875,550915682.4155,148–247 38,696TY–674,094 –0.08 –0.31 –1,236,891 855630.21–525 34,624US–953,719 –0.20 –0.48 –1,361,031 895420.56997StockSP838,9880.23 0.48 –278,988 100718.9531,533–97MetalsGC–374,470 –0.03 –0.17 –646,320824946.0439,44642HG150,650 –0.04 0.07 –706,925705933.2543,404–10PL–145,350 0.02 –0.07 –790,935965950.0129,12057SL258,4350.04 0.14 –465,810916434.1730,02418EnergyCL27,680 –0.02 0.01 –837,950835727.9948,811254HO509,0940.14 0.23 –400,155865123.6254,562–96HU–219,744 0.04 –0.09 –774,803896022.5834,979–98GrainsC–576,850 0.00 –0.25 –771,575765380.6243,092–8S8250.02 0.00 –804,750805531.9538,366–138 32,730W–582,550 –0.14 –0.27 –915,900855951.0882MeatsFC364,8900.11 0.19 –431,070915441.0940,87882LC344,5800.11 0.18 –431,184926350.5436,0962LH–44,2560.04 –0.02 –629,728785832.1138,383–229 29,704PB–506,232 –0.06 –0.24 –913,100946220.9858SoftsCC276,6900.01 0.14 –483,540 1006451.1330,617–305 35,331CT–602,200 –0.04 –0.31 –1,237,920 786225.24–72JO–243,420 0.01 –0.11 –668,325895735.7829,007–696 38,604KC–808,403 –0.17 –0.34 –1,081,328 825414.16–63LB–102,528 0.03 –0.03 –1,233,944 756333.0746,095–89SB–490,090 –0.07 –0.25 –808,797925954.4930,594–85Average –185,042 –0.01 –0.08 –795,308825634.1436,3762,000,0000–2,000,000–4,000,000–6,000,000–8,000,000–10,000,000–12,000,000
–0.45–0.28–0.32
© 2002 Lars Kestner – All Rights Reserved
FIGURE
8.18a
Normalized Envelope Indicator Strategy Applied to Futures.
8.18b
1991
K-ratio–0.94–0.21–1.43–0.260.32–0.21
1992
Sharpe Ratio–3.15–0.79–2.87–1.47–0.45–0.65
1993
Year199619971998199920002001K-ratio0.64–0.040.100.230.250.03
1994
Year
1995
Average Avg. Bars Avg. BarsLossWinLoss–59,94328512033–45,760–46,4372638–48,8612946–54,7612943–58,62228492843–50,838–61,9812747
1997
1998
2000
2001
© 2002 Lars Kestner – All Rights Reserved
1999
Num. ofNumber of Profitable PercentWindows Windows ProfitableSharpe Ratio Length144661.9445.83%1 Month14265–0.7245.77%3 Months650.5546.76%6 Months139133621.0046.62%12 Months127670.2952.76%18 Months690.5157.02%24 Months121
1996
Net Profit by Year
Net Profit1,813,816–694,151331,462715,566290,649604,543
Performance Breakdown by Year
Normalized Envelope Indicator Strategy Applied to Futures.
FIGURE
–4,000,000
–3,000,000
–2,000,000
–1,000,000
0
1,000,000
2,000,000
1990
Net