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Tests I through 3: Stochastic Overbought/Oversold Models. These tests evaluate the model with entry at the open (Test l), on a limit (Test 2), and on a stop (Test 3). Lane s original Fast %K was used. The length was stepped from 5 to 25 in increments of 1. The best values for this parameter in-sample were 25, 20, and 16 (Tests 1 through 3, respectively). For the Stochastic, the traditional thresholds are 20 (lower) and 80 (upper). As a whole, these models lost heavily in- and out-of-sample (see Table 7-3). As in previous tests, the limit
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order was the best in both samples, having the least loss per trade; the percent of winning trades (37% in-sample, 36% out-of-sample) was also highest with this order. The stop order was intermediate in performance, with the entry at open being the worst. No markets traded well in either sample. Out-of-sample, the British Pound and Orange Juice were profitable across all orders, and Lumber, Soybeans, and Live Hogs made profits with a stop; other small profits were occasionally noted, hut had no consistency. This model is among the worst tested.
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Tests 4 through 6: RSI Overbought/Oversold Models. The model was tested with entry at the open (Test 4) on a limit (Test 5), and on a stop (Test 6). The RSI was computed as suggested by its originator, Larry Williams. The length was stepped from 5 to 2.5 in increments of 1. Across all tests, 25 was the best value for this parameter in-sample. The traditional thresholds were used: 30 (lower) and 70 (upper). The model performed more poorly than the Stochastic overbought/oversold one. The percentage of winning trades was extremely low, ranging from 26% to 37%, depending on sample and test. The average loss per trade reached over $7,000. Net profits were better than for the Stochastic because there were fewer trades; even though the loss per trade was greater, the total loss was smaller. This model did not capture any market inefficiency. The limit order was best, while the stop and open were about equal. Significantly more markets showed positive returns, especially in Test 5 when the limit was used: Profits occurred in-sample for Bonds, COMEX Gold, Silver, Platinum, Feeder Cattle, Oats, and Coffee; out-of-sample, Gold, Silver, Platinum, Feeder Cattle, and Oats still traded profitably. Also profitable out-of-sample were the NYFE, British Pound, Heating Oil, Corn, Sugar, Orange Juice, and Lumber. Tests of Signal Line Models These are essentially moving average crossover models, except that an oscillator is substituted for prices when searching for crossovers. In this case, the moving average is called the signal line. A short entry is signalled when the oscillator crosses from above to below the signal line; when the oscillator does the reverse, a long entry is generated. Since oscillators show less lag than moving averages and less noise than raw prices, perhaps more timely and reliable signals can be generated. In Tests 7 through 12, the Stochastic and MACD are considered. The Slow %K usually exhibits strong cyclic behavior, appropriate for use with a signal line entry. The MACD is traditionally plotted with the signal line, even if crossovers are not a traditional entry criteria. Tests 7 through 9: Stochastic Signal Line Models. The model was tested with entry at the open, on a limit, and on a stop (Tests 7 through 9, respectively). Lane s original Slow %K Stochastic was used because, in preliminary testing, Fast %K produced an incredible excess of trades, resulting from very high noise levels and the indicator pegging near its extremes. The signal line consisted of a 3-bar simple moving average of Slow %K. The length of the Stochastic was stepped from 5 to 25, in increments of 1. The best values for this parameter insample were 15, 14, and 11 (Tests 7 through 9). Overall, these models lost heavily on a per trade basis. Due to the large number of trades, the losses were astronomical. The limit order was best, showing the least loss per trade and the highest percent of winning trades across samples. Entry at the open was worst.
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This model likes stops, perhaps because they act as trend filters: After countertrend activity is detected (triggering an entry signal), before entry can occur, the market must demonstrate reversal by moving in the direction of the trade. Stops also performed better in countertrend moving average models, Only two markets had positive returns in-sample, but not out-of-sample. Out-of-sample, the stop produced a few small profits; Coffee made more than $2,000 per trade. Tests 10 through 12: MACD Signal Line Models. Entry at the open (Test lo), on a limit (Test ll), and on a stop (Test 12) were examined. The classic MACD, employing exponential moving averages, was used. The shorter moving average was stepped from a length of 3 to a length of 15 in increments of 2; the longer moving average was stepped from lengths of 10 through 40 in increments of 5. The moving average serving as the signal line had a fixed traditional period of 9. This was the best performing oscillator model thus far. In-sample, the limit order was best and entry at open was worst. Out-of-sample, the stop was best and the limit order worst. Out-of-sample, the stop produced the highest percentage of wins (40%) seen so far, and the smallest loss per trade. In-sample, only Lumber was substantially profitable with a limit. Live Hogs, Pork Bellies, Coffee, and Sugar were profitable in-sample with a stop. Lumber, Live Hogs, Pork Bellies, and Coffee held up out-of-sample. Many markets unprofitable in-sample, were profitable out-of-sample. The highest number of markets traded profitably with a stop.
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