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Light Crude, Lumber, and Coffee were highly profitable in both samples. Again, there was no profitability for the wheats. There was enough consistency for this model to be tradable using a stop order and focusing on appropriate markets. Tests of the Crossover Model with Confirmatlon and Inversions This model is the same as the crossover model with confirmation. However, additional trades were taken where inversions may have occurred; i.e., if a seasonal buy was signaled by a crossover, but the market was going up or near a top (as indicated by the Fast %K being greater than 75%), a sell signal was posted. The assumption with this model is that the usual seasonal cycle may have inverted or flipped over, where a top is formed instead of a bottom. Likewise, if the crossover signaled a sell, but the Fast %K indicated that the market was down by being less than 25%, a buy was posted. These signals were issued in addition to those described in the crossover with confirmation model. Entries were executed at the open (Test IO), on a limit (Test 11). or on a stop (Test 12). Optimization for these tests involved stepping the length of the moving averages (avglen) from 5 to 20 in increments of 5 (PI) and the displacement (disp) from 0 to 20 in increments of 1 (PZ). For entry at the open, a movingaverage length of 15 and a displacement of 2 were best. Entry on a limit was best with a length of 20 and a displacement of 4. Entry on a stop again required a length of 20 and a displacement of 9. For entry at the open, the equity curve showed a smooth, severe decline from one end of the sampling period to the other. There was a steeply declining equity curve for the limit order, although the overall decline was roughly half that of the one for entry at open. For entry on stop, the curve declined until May 1987. It then became very choppy but essentially flat until August 1993. From August 1993 until June 1995, the curve steeply accelerated, but turned around and sharply declined throughout the rest of the out-of-sample period. Adding the inversion element was destructive to the crossover model. The seasonal patterns studied apparently do not evidence frequent inversions, at least not insofar as is detectable by the approach used. Adding the inversion signals to the model dramatically worsened performance on a per-trade basis across all entry orders, Losses were seen for every combination of sample and order type, except for a very small profit with a stop in the out-of-sample period. There were no markets that showed consistently good trading across multiple order types in both samples, although there were isolated instances of strong profits for a particular order type in certain markets. The NYFE again traded very profitably with a stop order, as did IO-Year Notes, in both samples. Platinum and Silver also traded well in- and out-of-sample with a stop order. Soybeans traded very profitably with a stop order in-sample, but only somewhat
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profitably out-of-sample. There were consistent losses, or no profits at all, across all orders and samples for the wheats.
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Results from the different tests were combined into one table and two charts for overall analysis. Table 8-3 provides performance numbers broken down by sample, entry order, and model. For each model, there are two rows of numbers: The first row contains the figures for annualized return-on-account, and the second row contains the average dollar profit or loss per trade. The two rightmost columns contain averages across all order types for the in-sample and out-of-sample performance. The last two rows contain the average across all models for each type of order. Of the three types of orders, it is evident that the stop performed best. The limit and entry at open performed about equally well, but much worse than the stop. In fact, for the stop, the average across all four models actually showed a positive return and small profits on a per-trade basis both in-sample and out-of-sample. When examining models averaged across all order types, the in-sample performance was best using the crossover-with-confirmation model and worst for the crossover-with-confirmation and inversion model. Out-of-sample, the basic crossover model showed the best performance, while the crossover with confirmation and inversion had the worst. As can be seen, in-sample the best performance was observed when the stop order was used with the crossover-with-confirmation model. This is also the combination of order and model that performed best out-of-sample.
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