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Mechanical trading systems - Weissman R.L.

Weissman R.L. Mechanical trading systems - Wiley publishing , 2005 . - 240 p.
ISBN 0-471-65435-3
Download (direct link): mechanicaltradingsystems2005.pdf
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Table 7.27’s most robust performance was produced by the RSI extremes with 200-day moving average filter applied to our mean reversion portfolio of assets (see Chapter 4 for a more detailed explanation of the system). Although this system did produce a loss in 2001, the most recent year’s performance (2002) was its most profitable. Furthermore, looking back at the year 2001 performance for the trend trading systems in Table 7.26, it is clear that the performance of RSI extremes for the mean reversion portfolio failed for all the “right” reasons. In other words, it failed because the markets were in a strong trending mode. In this type of environment we should expect a mean reversion system to experience a losing year.
TABLE 7.26 Year-by-year performance breakdown for trend-followiing systems of Chapter 3.
System 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002
2 MA Crossover (14439) 14745 78166 1 1436 27080 1 553 13750 (1862) 31692 (871)
2 MA Ichimoku 18314 33367 1 1021 (49435) 16080 (3296) (47343) (27508) 28491 45031
3 MA Crossover 10028 422 67858 1271 7 20045 11318 12396 (30198) 19088 14298
3 MA Ichimoku 10941 8794 69736 1 7769 22736 8214 18350 (32851) 1 7050 12088
MACD (5359) (2250) (2831 8) 30953 107917 3640 8766 371 3 39199 67199
DMI (13029) (4864) 20255 13943 20361 1935 (917) (1 7876) 13281 29372
DMI with ADX filter (10748) (41 74) 19921 9731 12730 (846) 1 753 (1 5781) 1 521 9 30916
Channel Breakout (17181) 8478 16026 42582 14906 30626 13813 (18640) 43025 26356
Bollinger Bands 2257 12083 28191 9469 5734 19940 (5044) (1 1906) 18385 28287
Note: All trade summaries include $ 1 00 round-turn trade deductions for slippage and commissions. Data source: CQG, Inc.
TABLE 7.27 Year-by-year performance breakdown for mean reversion systems of Chapter 4.
System 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002
RSI with 200 day MA Futures 7060 (1 1686) 9610 26221 2812 7226 (2867) (10284) (6678) 908
RSI with 200 day MA (1 1485) 30379 1 7304 1 1 724 3946 31 79 1 1995 1481 5 (22996) 43021
Bollinger Bands with 200 day MA (141 53) 4098 9043 697 26164 6706 2577 (12116) 1 5831 12248
Bollinger Bands with ADX filter (209) (1516) 4838 (3758) 4616 7883 (7702) 3082 12817 3219
Slow Stochastics & CCI (10607) 3416 (3206) (10818) (6564) 18462 1 7777 13765 (4691) 1691
Slow Stochastics & CCI with Time Exit (1 1397) 4674 (4845) (9669) (4954) 16596 1 7234 14499 (829) 231
Note: All trade summaries include $ 1 00 round-turn trade deductions for slippage and commissions. Data source: CQC, Inc.
System Development and Analysis
157
Now let us examine our worst-performing mean reversion system results. Interestingly, the worst performer (RSI extremes with 200-day moving average applied to the futures portfolio) utilized the same exact trade execution criteria as our best-performing system (RSI extremes with 200-day moving average applied to the mean reversion portfolio). This warns us that the mean reversion systems examined in Chapter 4 were not robust enough to be successful across a diversified group of asset classes. This fact is clearly highlighted by the failure of the futures portfolio from January 1, 1999, to the end of our in-sample test period on December 31, 2002.
Although this does suggest a higher degree of overall confidence in the trend-following systems of Chapter 3, the matter is not as cut and dried as might appear, due to the negative correlation between mean reversion and trend-following systems. The poor performance of RSI extremes on our mean reversion portfolio in 2001 was in stark contrast to the strong results displayed by the trend-following systems that year. Perhaps more important, a comparison of Tables 7.26 and 7.27 shows positive performance by our mean reversion system during the year 2000, which was our worst year for the trend trading systems.
Out-of-Sample Data Analysis
A case study based on one of the trading systems from Chapter 3 may be instructive. Table 7.28 is an out-of-sample data analysis for the two moving average crossover system. Table 7.22 showed in-sample data for this system. If we compare the out-of-sample data from 2003 to our in-sample
TABLE 7.28 Out-of-sample (2003) performance for two moving average
crossover system.
Asset Profit # Trades # Days Max Draw MDD MCL P:MD P:L Ratio %W Time %
ES 224 9 32 -6617 96 3 0.03 1.02 33.33 100
TY 3141 10 26 -6619 60 2 0.47 1.48 40.00 100
ED -2619 12 19 -2737 215 8 -0.96 0.02 8.33 100
SF 5000 10 23 -9162 52 2 0.55 1.70 50.00 100
JY -1662 12 22 -11537 220 7 -0.14 0.86 25.00 100
CL -2880 8 27 -9920 98 3 -0.29 0.68 37.50 100
GC 5820 6 38 -3690 63 1 1.58 4.20 66.67 100
S -2125 15 19 -10800 175 6 -0.20 0.84 13.33 100
LH 5170 8 37 -2770 51 2 1.87 3.62 75.00 100
CT 2560 9 32 -7735 183 4 0.33 1.32 44.44 100
Total 12629 99 26 -24647 70 7 0.51 1.37 35.35 100
Note: All trade summaries include $100 round-turn trade deductions for slippage
and commissions. Data source: CQG, Inc.
158
MECHANICAL TRADING SYSTEMS
calendar years (see Table 7.26), it appears that our total net profit is well within normal tolerances. But what if total net profits were dramatically different from those of our in-sample backtest? If our 2003 results were 50 percent worse than the system’s performance in 1993, the system should be abandoned because of the high probability of paradigm shift in markets as stated in our first examination of the out-of-sample study.
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