Figure 2.8 The August 1995 crude oil contract with curve-fitted system
profitable trades. As many as 87 percent of all trades (20 out of 23) were profitable. A second clue was in the 14 consecutive profitable trades. A third clue was in a suspiciously large profit factor (= gross profit/gross loss) of 13.49. These results are what you might see in curve-fitted systems tested over a relatively short time period. The computer-generated buy and sell signals are shown in Figure 2.8.
This curve-fitted system was tested by using a continuous contract of crude oil futures data from January 3, 1989, through June 30, 1995. Not surprisingly, this system would have lost $107,870 on paper, as shown in Table 2.4. Note how only 32 percent of the trades would have been profitable. There would have been as many as 48 consecutive losing trades, requiring quite an act of faith to continue trading this system. Also, the profit factor was a less impressive 0.61, a sharp drop from the 13.49 value in Table 2.3. These calculations show that curve-fitted systems may not work over long periods of time.
Interestingly, this system has its merits. When tested over 12 other markets to check if these rules were robust enough to use across many
Rule 3: Robust Trading Rules 27
Table 2.3 Results of testing August 1995 crude oil curve-fitted system N.Y. Light Crude Oil 08/95-Daily 12/01 /94 - 07/20/95
Total net profit ($) 12,990.00
Gross profit ($) 14,030.00
Total number of trades 23
Number of winning trades 20
Largest winning trade ($) 1,370.00
Average winning trade ($) 701.50
Maximum consecutive 14
winners
Average number of bars 20
in winners
Maximum intraday -1,670.00
drawdown ($)
Profit factor 13.49
Open position profit/loss ($) 520.00 Gross loss ($) -1,040.00
Percent profitable 87
Number of losing trades 3
Largest losing trade ($) -860.00
Average losing trade ($) -346.67
Average trade ($) 564.78 Maximum consecutive losers 2
Average number of bars in 1 losers
Maximum number of contracts held
markets (Table 2.5), the results were better than expected; on some markets the system tested very well. This result was surprising because (1) this particular combination of rules had never been tested on these markets and were derived by inspection of just one chart; and (2) the
Table 2.4 Results of testing crude oil curve-fitted system over a long time period
| Performance | Summary: All Trades 01/03/89 - 06/30/95 | ||
| Total net profit ($) | -107,870 | ||
| Total number of trades | Percent profitable | ||
| Number of winning trades | Number of losing trades | ||
| Largest winning trade ($) | 7,160 | Largest losing trade ($) | -3,670 |
| Average winning trade ($) | Average losing trade ($) | -761 | |
| Average trade ($) | -200 | ||
| Maximum consecutive winners | Maximum consecutive losers | ||
| Average number of bars in winners | Average number of bars in losers | ||
| Maximum intraday drawdown ($) | -120,950 | ||
| Profit factor | 0.61 | Maximum number of contracts held |
28 Principles of Trading System Design
Table 2.5 A check for robustness: crude oil curve-fitted system over 12 markets (test period: 1 /3/89-6/30/95, using continuous contracts, $100 slippage, and commission charge)
| Market | Paper Profit (S) | Average Trade ($) |
| Coffee | 132,908 | |
| S&P-500 | 145,545 | |
| Cotton | 84,925 | |
| U.S. bond | 84,319 | |
| Japanese yen | 67,975 | |
| Swiss franc | 1 7,975 | |
| 10-year T-note | 1 3,538 | |
| Gold, Comex | -1 3,270 | -33 |
| Copper, high-grade | -22,167 | -49 |
| Soybeans | ^1,656 | -117 |
| Heating oil | -45,868 | -80 |
| Sugar #11 | -56,394 | -136 |
long entries and short entries are asymmetric. A symmetrical trading system uses identical rules for entries and exits, except that the signs of the required changes are reversed. For example, a moving average system would require an upside crossover or a downside crossunder for signals.
A closer look at the rules shows that they do follow some sound principles. For example, during an uptrend, each successive 50-bar breakout adds a contract until nine contracts are acquired. Thus, market exposure is increased during strong uptrends. The sell rule tends to lock in profits close to intermediate highs. As we sell rallies in downtrends, we are increasing exposure in the direction of the intermediate term trend. Also, a relatively tight $1,000 initial money management stop was used. Thus, even though these rules were derived by inspection, they followed sound principles of following the trend, adding to with-the-trend positions, letting profits run, and cutting losses quickly.
In summary, it is easy to develop a curve-fitted system over a short test sample. If these rules are not robust, they will not be profitable over many different market conditions. Hence, they will not be profitable over long time periods and many markets. Such rules are unlikely to be consistently profitable in the future. Hence, you should try to develop robust trading systems.
Rule 4: Trading Multiple Contracts 29