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Both in- and out-of-sample, and across all models, the limit order provided the greatest edge; the stop and market-at-open orders did poorly. The benefit of the limit order for entering the market undoubtedly stemmed from its ability to obtain entries at more favorable prices, The dramatic impact of transaction costs and unfavorable entry prices is evident in Tests 1 and 2. Surprisingly, the limit order even worked with a trend-following methodology like breakouts. It might be expected that too many good trends would be missed while waiting to enter on a limit; however, the market pulls back (even after valid breakouts) with
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Summary of Breakout Entry Results Arranged for Easy Comparison
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enough frequency to enter on a limit at a better price without missing too many good trends. The same three periods, evident when average equity was broken down by breakout type, appeared when entry orders were analyzed. For the limit and stop entries, equity surged strongly from August 1985 to June 1988. Equity increased, but to a lesser extent, with a stop order. For entry at the open and on a stop, equity was choppy and down-trending from June 1988 to July 1994, when the limit order modestly gained. From July 1994 to December 1998, equity for entry at the open mildly declined, the stop evidenced a serious decline, and the limit had no consistent movement. The stop did better than average during the first period and much worse than average during the third, more decay in performance over time occurred with a stop order than with the other orders. In all periods, the limit order performed best. When equity was analyzed for all models and order types combined, most of its gains were in the first period, which covered less than the first third of the insample period. By the end of this period, more than 70% of the peak equity had
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already accumulated. In the second period, equity drifted up a little. In the third period, equity declined, at first gradually and then, after July 1997, at a faster pace.
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Interactions seemed strongest between breakout types and time. The most notable was between volatility breakouts (versus the others) and time (in-sanple versus out-of-sample). Volatility breakouts performed best early on, but later became the worst. The volatility breakout with stop entry deteriorated more in recent years than it did with entry on a limit, perhaps due to the common use of stops for entry in trend-following models. Finally, the highesthigMowest-low breakout sometimes favored a stop, while the volatility model never did.
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Restricting trades to long positions greatly improved the performance of the volatility breakout in-sample, and improved it to some extent out-of-sample. Breakout models do better on the long side than on the short one. The ADX trend filter had a smaller benefit in-sample and provided no benefit out-ofsample. Restricting trading to currencies produced lessened in-sample performance, but dramatic improvements out-of-sample. The gain was so great that the model actually profited out-of-sample, which cannot be said for any of the other combinations tested! The currencies were not affected by the rising efficiency other markets had to simple breakout systems, perhaps because the currency markets are huge and driven by powerful fundamental forces. The poorer in-sample performance can be explained by the reduced number of markets traded.
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Net profit and annual return were averaged for each market over all tests. The calculated numbers contained no surprises. Positive returns were seen in both samples for the Deutschemark, Swiss Franc, Japanese Yen, and Canadian Dollar, and for Light Crude and Heating Oil. Trading a basket of all six currencies, all three oils, or both, would have been profitable in both samples. Although no other market group demonstrated consistent profitability, some individual markets did. In order of minimum net profit, Coffee, Live Hogs, and Random Lumber had positive retarns. The S&P 500, NYFE, Comex Gold, Corn, and the wheats had positive outof-sample returns with in-sample losses. The index markets profitability may have resulted from the strong trends that developed out-of-sample. Positive insample returns, associated with out-of-sample losses, were somewhat more
common; T-Bonds, IO-Year Notes, Palladium, Feeder Cattle, Pork Bellies, Soybeans, Soybean Meal, Bean Oil, Oats, Orange Juice, and Cotton had this pattern. T-Bills, Silver, Platinum, Live Cattle, Cocoa, and Sugar lost in both samples. A correlation of 0.15 between net in-sample and net out-of-sample profits implies markets that traded well in the optimization period tended to trade well in the verification period.
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