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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 3.6 presents the backtested portfolio results from December 31, 1992, to December 31, 2002, for this system.
Although these results are mildly encouraging, most people do not have the patience and fortitude to sit with a trade for an average of 143 days, and doing so is an absolute prerequisite for successful implementation of this particular system. Obviously various filters could be introduced to modify this characteristic; however, it is highlighted here to illustrate considerations in trading a system beyond mere analysis of risk versus return on investment or total net profit.
DMI
This simple modification of the stop and reverse systems employed above minimizes whipsaws as the market oscillates above and below the zero level. Instead of entries triggered around the zero level, I set the long entry criteria to +20 or greater and short entry to -20 or lower. (Note: Altering trigger points away from the zero level to reduce whipsaws is also applicable to all of the trend-following conditional trading systems, including the two moving average crossovers, MACD, momentum, and ROC.)
Using CQG, the programming code for our DMI trading system is written in this way:
Long Entry:
DDIF(@,10)[-1] XABOVE 20
Trend-Following Systems
57
Long Exit:
DDIF(@,10[-1] XBELOW 0
Short Entry:
DDIF(@,10)[-1] XBELOW -20
Short Exit:
DDIF(@,10[-1] XABOVE 0
Table 3.7 presents the backtested portfolio results from December 31, 1992, to December 31, 2002, for this system.
A quick glance at the numbers shows this system’s backtested portfolio results are inferior to almost all of those examined earlier. Readers are encouraged to experiment with adding filters, such as implied volatility of options on the underlying asset breaking above the upper/lower Bollinger bands as confirming entry criteria. If implied volatility were trending up, a filter might improve our probability of participating in a sustainable trending market, thereby transforming a marginally profitable system into a viable one.5
DMI WITH ADX

Because Wilder’s original presentation of DMI was linked with ADX, next I present readers the results from the addition of this filter to our original DMI system.
TABLE 3.7 DMI.
Asset Profit # Trades # Days Max Draw MDD MCL P:MD P:L Ratio %W Time %
ES -25911 87 17 -33251 1424 15 -0.78 0.62 29.89 53.99
TY 1037 84 19 -13309 2393 6 0.08 1.02 33.33 58.70
ED 3287 73 24 -4319 1878 7 0.76 1.28 34.25 67.69
SF 6700 79 19 -20412 1325 7 0.33 1.10 44.30 55.11
JY 43325 87 18 -20675 460 6 2.10 1.47 41.38 58.85
CL 22160 73 20 -8190 610 6 2.71 1.54 45.21 56.03
GC -18170 99 15 -24600 2402 13 -0.74 0.57 26.26 55.05
S -6962 79 18 -12487 1292 9 -0.56 0.85 31.65 52.58
LH 24230 72 22 -10640 694 8 2.28 1.77 44.44 60.06
CT 9105 74 19 -29480 1948 7 0.31 1.15 40.54 53.18
Total 58801 807 18.9 - -30459 1239 17 1.93 1.11 36.68 57.00
Note: All trade summaries include $100 round-turn trade deductions for slippage
and commissions. Data source: CQG, Inc.
58
MECHANICAL TRADING SYSTEMS
Using CQG, the programming code for a simple DMI trading system with an ADX filter is written in this way:
Long Entry:
DDIF(@,10)[-1] XABOVE 20 AND ADX(@,9)[-1] > 2C Long Exit:
DDIF(@,1C)[-1] XBELOW C OR ADX(@,9)[-1] < 2C Short Entry:
DDIF(@,1C)[-1] XBELOW -20 AND ADX(@,9)[-1] > 2C Short Exit:
DDIF(@,1C)[-1] XABOVE C OR ADX(@,9)[-1] < 2C
Table 3.8 presents the backtested portfolio results from December 31, 1992, to December 31, 2002, for this system.
Notice that addition of the ADX filter worsened overall performance. Although one example does not prove that an indicator should be discarded (as proved by our examination of Ichimoku), it does suggest that combining of indicators simply because data vendors or indicator developers link them will not necessarily increase profitability.
TABLE 3.8 DMI with ADX filter.
Asset Profit # Trades # Days Max Draw MDD MCL P:MD P:L Ratio %W Time %
ES -18652 86 16 -30243 1424 12 -0.62 0.69 31.4 52.40
TY -1431 84 18 -18406 2466 9 -0.08 0.97 32.14 56.72
ED 1556 76 23 -4181 2056 7 0.37 1.13 30.26 66.23
SF -2537 81 17 -21850 1324 5 -0.12 0.96 41.98 52.99
JY 41825 85 17 -18300 952 3 2.29 1.46 41.18 55.61
CL 7490 73 19 -15170 623 6 0.49 1.16 38.36 54.00
GC -18080 97 15 -25020 2401 22 -0.72 0.57 23.71 52.90
S -8925 80 17 -14525 2378 10 -0.61 0.80 31.25 51.63
LH 25470 73 21 -9940 689 7 2.56 1.78 46.58 59.07
CT 18195 73 19 -21280 1947 7 0.85 1.35 42.47 52.10
Total 44911 808 18 -27256 885 17 1.65 1.07 35.52 55.25
Note: All trade summaries include $100 round-turn trade deductions for slippage
and commissions. Data source: CQG, Inc.
Trend-Following Systems
59
CHANNEL BREAKOUT

As stated in Chapter 2, channel breakout is a purely price-triggered trend-following system. Although our backtest will employ Donchian’s original 20-day stop and reverse parameters, readers are encouraged to experiment with modifications, including lengthening the parameter (e.g., setting n period to 70) to reduce false breakouts, as well as changing the exit condition (e.g., entry when market breaks 20-day highs/lows and exit when it breaks 10-day highs/low) to transform the stop and reverse system into one that allows for neutrality.
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