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Mean | 118. | |
Variance | 1736.72 | 818.455 |
Observations | ||
Pearson correlation | 0.410 | |
Hypothesized mean difference | ||
df | ||
tStat | 8.055 | |
P(T<=t) one-tail | 1.05 | |
t Critical one-tail | 1.833 | |
P(T<=t) two-tail | 2.10 | |
t Critical two-tail | 2.262 |
trades by 76 percent. Now you have to decide if these changes suit your trading style.
Next we examine the effects of adding the volatility exit to the reference system (see Table 5.3). There is a statistically significant (t-statis-tic: 2.54 > t-critical: 2.26) reduction in average profits from $51,638 to $34,820. Thus, the 33-percent reduction in profits occurs with a significant 61-percent increase in the total number of trades (t-statistic: 8.82 > t-critical: 2.26). Thus, the volatility exit reduces profits and increases trading frequency. Of course, it introduces a neutral zone, and should reduce your overall market exposure. You may like this exit because it responds to a particular exit pattern, such as a large countertrend move. Some traders may prefer the equity curve produced by this exit to the equity curve of the reference system. Others may like the higher trading frequency because it means they will get many opportunities to trade.
The effect of using the 20-tick barrier did not produce a statistically significant reduction in net profits when tested without any exits (see Table 5.5). The average profit per market was $51,638 with the reference system, and $49,989 with the 20-tick barrier. Thus, adding the barrier did not reduce profits significantly. However, it did reduce the number of trades by about 25 percent, which was statistically significant (t-statistic 4.71, t-critical = 2.62), suggesting that the barrier acted as a filter.
The effect of adding a volatility exit to the 20-tick barrier (Table 5.4) also produced no statistically significant difference in net profits.
Two ADX Variations 165
However, the number of trades was significantly higher. You will have to examine the equity curves to decide if you like the effects of adding the exit.
There was no significant difference in performance between the reference system and the breakout with the inside volatility barrier (Table 5.7). For example, the average profits with the 20-tick barrier are $51,638 versus $44,732 with the inside volatility barrier. However, the number of trades was 60 percent smaller without the inside volatility barrier. The inside volatility barrier produces a statistically significant increase in the trading frequency. Thus, the inside barrier will whet your appetite for frequent trading without a large performance penalty.
The analysis of this section shows that you should use a statistical test to verify that the differences in performance are statistically significant. You can use a spreadsheet for your statistical analysis, or you may use specialized software. You should carefully note how changing exit strategies changed the profits, trading frequency, and drawdowns. Thus, you can easily match an entry signal to your trading needs.
Дата публикования: 2014-11-28; Прочитано: 346 | Нарушение авторского права страницы | Мы поможем в написании вашей работы!