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Look-backs from 5 to 100 were tested in steps of 5. On the in-sample data, the model was profitable for only four of the look-backs. The best results were obtained with a look-back of 85, where in-sample returns were a mere 1.2% annually. Given these returns and the associated statistics, it is no surprise that this model lost 15.9% annually out-of-sample. Winners occurred about 39% of the time, and long trades were more profitable than short ones in-sample. As in all previous breakout simulations, the HHLL breakout performed best on the currencies, the oils, and Coffee; it performed worst on metals, livestock, and grains. Equity shows a model that never performed well, but that now performs disastrously. The results were slightly better than those for the close-only breakout with a similar entry at the open; they were not better enough to overcome transaction costs. In the close-only model, a limit order reduced the cost of failed breakouts and, thereby, improved performance. Because costs are higher with the HHLL breakout, due to the more stringent breakout thresholds, a limit entry may provide a greater boost to performance. A limit entry for a breakout model also sidesteps the flurry of orders that often hit the market when entry stops, placed at breakout thresholds, are triggered. Entries at such times are likely to occur at unfavorable prices. However, more sophisticated traders will undoubtedly fade the movements induced by the entry stops placed by more ndive traders, driving prices back. An appropriate limit order may be able to enter on the resultant pullback at a good price. If the breakout represents the start of a trend, the market is likely to resume its movement, yielding a profitable trade; if not, the market will have less distance to retrace from the price at entry, meaning a smaller loss. Even though the HHLL breakout appears only marginally better than the close-only breakout thus far, the verdict is not yet in; a limit entry may produce great improvement. The annualized return-on-account is used as an index of performance in these discussions and the risk-to-reward ratio is rarely mentioned, even though the probability statistic (a t-statistic) is computed using that measure. The risk-toreward ratio and return-on-account are very highly correlated with one another: They are almost interchangeable as indicators of model efficacy. Since it is easier to understand. the annualized return-on-account is referred to more often.
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Test 5: Close-Only HHLL Breakout with Enhy on Limit on Next Bar. For the close-only channel breakout, use of a limit order for entry greatly improved performance. Perhaps a limit entry could similarly benefit the HHLL breakout model.
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For the sake of consistency with the model examined in Test 3, the limit price is set to the mid-point of the breakout bar.
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The look-back parameter was stepped through the same range as in previous tests. All look-backs produced positive returns. The best in-sample results were with a look-back of 85, which yielded a return of 36.2% annually; the probability is less than 2% (33% when corrected for multiple tests) that this was due to chance. In-sample, long positions again yielded greater profits than short positions. Surprisingly, out-of-sample, the short side produced a small profit, while the long side resulted in a loss! With a return of -2.3%, out-of-sample performance was poor, but not as bad as for many other systems tested. In-sample, there were 43% wins and the average trade produced an $1,558 profit; out-of-sample, 41% were winners and the average trade lost $912. The equity curve in Figure 5-l may seem to contradict the negative out-ofsample returns, but the trend in the out-of-sample data was up and on par with the trend in the latter half of the in-sample period. The apparent contradiction results from a bump in the equity curve at the start of the out-of-sample period. Nevertheless, the HHLL breakout with entry on a limit (together with the standard exit) is not a system that one would want to trade after June 1988: The return was too low relative to the risk represented by the fluctuation of equity above and below the least-squares polynomial trendline (also shown in Figure 5-l). All currencies and oils had positive in-sample results. Strong out-of-sample returns were seen for the Swiss Franc, Canadian Dollar, and Deutschemark, as well as for Heating Oil and Light Crude; small losses were observed for the British Pound, Eurodollar, and Unleaded Gasoline. Coffee was profitable in both samples.
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