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As before, the look-back parameter was stepped from 5 to 100, in increments of 5, and the solution with the best risk-to-reward ratio (and t-test probability) was selected. Commissions, slippage, exit parameters, and the ability to reenter a continuing trend (albeit on a pullback), remain unchanged. With a best look-back of 80 (same as in Test l), this model returned about 33% annually during the in-sample period. The probability that these returns were. due to chance is less than 5% when not corrected, or 61% when corrected for 20 optimization runs. Although profitable in-sample, the statistics suggest the
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model may fail in the future: indeed, out-of-sample returns were negative. As in Tests 1 and 2, trades lasted about seven bars and long trades were more profitable than short ones. The percentage of winners was 42%. Although the limit entry did not eliminate the damaging impact of transaction costs, performance improved. The limit order did not seriously reduce the~number of trades or cause many profitable trends to be missed, the market pulled back after most breakouts, allowing entry at more favorable prices. That a somewhat arbitrary, almost certainly suboptimal, limit entry strategy could so improve performance is highly encouraging. The equity curve again shows that this kind of system once worked but no longer does. Table 5-2 shows that, with few exceptions, there were positive returns for the currencies and oils, both in-sample and out-of-sample, consistent with findings in earlier tests. Coffee continued to trade well on both samples, and the S&P 500 remained profitable in the verification sample. Conclusion A limit-based entry can significantly improve the overall performance of a breakout model. Substantial benefit is obtained even with a fairly crude choice for the limit price. It is interesting that the markets to benefit most from the use of a limit order for entry were not necessarily those with the lowest dollar volatilities and implied transaction costs, as had been expected. Certain markets, like the S&P 500 and Eurodollars, just seem to respond well to limit entries, while others, such as Cocoa and Live Cattle, do not. HIGHEST HIGH / LOWEST LOW BREAKOUTS Would placing the thresholds further from current prices reduce whipsaws, increase winning trades, and improve breakout performance More stringent breakout levels are readily obtained by replacing the highest and lowest close from the previous model with the highest high and lowest low (HHLL) in the current model. Defined this way, breakout thresholds now represent traditional levels of support and resistance: Breakouts occur when previous highs or lows are taken out by the market. One possible way to further reduce spurious breakouts is by requiring the market to close beyond the bands, not merely to penetrate them at some point inside the bar. Speeding up system response by using a stop order for entry, or reducing transaction costs by entering on a pullback with a limit order, might also improve performance. Test 4: Close-Only HHLL Breakout with Entry at Open of Next Bar. This breakout buys at tomorrow s open when today s close breaks above the highest high of the last n days, and sells at tomorrow s open when today s close drops below the lowest low. The look-back (n) is the only model parameter. The beau-
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ty of this model, besides its simplicity, is that no important trend will be missed, and tomorrow s trades are fully known after today s close. ,, file = x09mod04.c ,, HHLL channel breakout system with entry next bar on open
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