Books
in black and white
Main menu
Home About us Share a book
Books
Biology Business Chemistry Computers Culture Economics Fiction Games Guide History Management Mathematical Medicine Mental Fitnes Physics Psychology Scince Sport Technics
Ads

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
Previous << 1 .. 33 34 35 36 37 38 < 39 > 40 41 42 43 44 45 .. 82 >> Next

Slow Stochastics Extremes with CCI filter and Time Exit
Here again we revisit a mean reversion system that was originally introduced in Chapter 4. Unlike the RSI extremes with moving average filter, this system has no directional bias.
Table 5.6 presents the results of this system for the Nasdaq 100 index (day session only).
As in Chapter 4, here again the removal of the trend-following prerequisite led to a deterioration in profit to maximum drawdown as well as to a
TABLE 5.5 RSI extremes with 400-hour moving average filter.
Asset # Profit Trades # Days Max Draw MDD MCL P:MD P:L Ratio %W Time %
ND 105027 138 2.75 -76043 627 5 1.38 1.20 36.23 16.76
Note: results include a deduction of $100 per round-turn trade for slippage on daily
time frame and $75 per round-turn for shorter time frames. Data source: CQG, Inc.
Short-Term Systems 95
TABLE 5.6 Slow stochastics extremes with CCI filter and 30-hour time exit.
Asset # Profit Trades # Days Max Draw MDD MCL P:MD P:L Ratio %W Time %
ND 70093 110 1.5 -69336 954 9 1.01 1.33 41.82 4.27
Note: results include a deduction of $100 per round-turn trade for slippage on daily time frame and $75 per round-turn for shorter time frames. Data source: CQG, Inc.
significant improvement in percentage of winning trades. To reiterate, slow stochastics extremes enjoyed a higher winning percentage because it exits trades as soon as the market reverts to its mean. By contrast, RSI extremes held trades on average for almost twice as long to capitalize on the reassertion of the “longer-term” trend.
MEAN REVERSION SYSTEMS USING 60-MINUTE BARS

As a general rule, the longer the time frame chosen, the greater diversity of profitable trading systems available to system traders. Here we will showcase three trading systems using 60-minute bar charts on the Nasdaq 100 index. The data displayed includes history from November 30, 1998, to January 30, 2004.
RSI Extremes with 200-Hour Moving Average Filter
Table 5.7 presents the results of this same trend-following mean reversion system for the 60-minute time frame.
Despite increases in maximum drawdown and maximum consecutive losses, a comparison of Tables 5.5 and 5.7 shows considerable overall improvements for this system’s performance over the shorter time frame. Especially noteworthy were improvements in percentages of winning trades as well as the profit to maximum drawdown ratios. Although such superior performance is indisputable, I would not throw away the 2-hour time frame
TABLE 5.7 RSI extremes with 200-hour moving average filter.
Asset # Profit Trades # Days Max Draw MDD MCL P:MD P:L Ratio %W Time %
ND 115647 214 1.75 -77166 234 7 1.50 1.17 44.39 20.04
Note: results include a deduction of $100 per round-turn trade for slippage on daily
time frame and $75 per round-turn for shorter time frames. Data source: CQG, Inc.
96
MECHANICAL TRADING SYSTEMS
in favor of 60-minute bars. In general, as shown in Table 5.1, performance of mechanical trading systems tends to deteriorate as time frames are shortened.
NONDIRECTIONALLY BIASED MEAN REVERSION SYSTEMS

Seven-Period Reversal
The seven-period reversal works because it generates trades only when markets are extremely overbought or oversold. For example, sell signals are initiated only when markets can move consistently higher for seven consecutive bars and then reverse direction on the most recent bar. This strategy differs from the mean reversion systems discussed so far in that it generates buy or sell signals only when the market has reversed its shortterm trend (at least during the most recent bar).
Although there are many successful ways to exit this system, I will employ a seven-period reversal criteria along with profit targets and fail-safe stop loss exits set to 1 percent of entry price.
Long Entry:
Close(@)[-8] > Close(@)[-7] AND Close(@)[-7] > Close(@)[-6] AND Close(@)[-6] > Close(@)[-5] AND Close(@)[-5] > Close(@)[-4] AND Close(@)[-4] > Close(@)[-3] AND Close(@)[-3] > Close(@)[-2]
AND Close(@)[-2] < Close(@)[-1]
Long Exit—Condition #1:
Cl ose(@ [-7] < Cl ose(@ [-6] AND
Cl ose(@ [-6] < Cl ose(@ [-5] AND
Cl ose(@ [-5] < Cl ose(@ [-4] AND
Cl ose(@ [-4] < Cl ose(@ [-3] AND
Cl ose(@ [-3] < Cl ose(@ [-2]
AND Close(@)[-2] < Close(@)[-1]
Long Exit—Condition #2 set “Price” field to:
EntryPrice(@,0,All,ThisTradeOnly)+(.01*
EntryPrice(@,0,All,ThisTradeOnly))
Short-Term Systems
97
Long Exit—Condition #3 set “Price” field to:
EntryPrice(@,0,All,ThisTradeOnly)-(.01*
EntryPrice(@,0,All,ThisTradeOnly);
For short entry, along with short exit codes for condition #1, simply reverse all greater than and less than signs. For short exit conditions #2 and #3, just reverse the plus and minus signs.
Once again, a comparison of Tables 5.7 and 5.8 shows that the elimination of our trend-following filter resulted in a deterioration of profit to maximum drawdown (P:MD) ratios. Of course, as in Chapter 4, this also improved our win/loss ratio and reduced the number of consecutive losses endured.
Previous << 1 .. 33 34 35 36 37 38 < 39 > 40 41 42 43 44 45 .. 82 >> Next