Testing the profitability of technical trading rules on stock markets

摘要

This empirical study continues previous research [2] that investigated the profitability of simple technical trading rules. We have added Athena Stock Exchange Composite Index to our universe of three previously researched indices: FTSE in Great Britain, S&P in USA and DAX in Germany. We have applied a new test based on Hansen's SPA Test [6] with the primary goal of rejecting the hypothesis of data mining resulted from a possible survivorship bias of trading rules; we have also provided a detailed explanation of our bootstrap implementation of the test. We did manage to find lower p-values for the new test that compared favorably to White's Reality Check [9], but we were still not able to reject the null hypothesis that data mining could partially be responsible for the apparent superior performance of some of the trading rules that we have tested on the DAX and S&P indices. On the other hand, we are more confident that data mining cannot be ruled out as a cause for perceived superior performance for any of the 100 rules tested on the FTSE index. Finally, we have discovered not only that all the 100 tested strategies manage to beat the buy & hold benchmark on the Greek composite index, but also that they explain that market dynamics better than a random walk with drift, and that is highly unlikely that data mining could have distorted these findings, which are important both for academics and investment professionals. We suspect that the superior performance of these simple rules is influenced by: 1. the inclusion of dividends in the researched index and 2. By the degree of maturity of that market.