and Western European countries the estimate of α is neither significantly negative nor positive at the 10% significance level. As transaction costs increase to 0.50%, the number of significant estimates of α decreases to 16. Significant estimates for α are then mainly found for the Asian stock market indices. As transaction costs increase even further to 1%, then the number of significant estimates of α decreases to 7. Significant estimates for α are then found only for the Peru Lima General, Indonesia Jakarta Composite, Pakistan Karachi 100, Sri Lanka CSE All Share, Thailand SET, and the Egypt CMA. If the Sharpe ratio selection criterion is used to select the best strategy in the training period of the recursive optimizing and testing procedure, then the results are similar as for the mean return selection criterion. If transaction costs increase to 1%, then significant estimates of α are found only for the Chile IPSA, Peru Lima General, Sri Lanka CSE All Share, Norway OSE All Share, Russia Moscow Times, and the Egypt CMA.
However, if the MSCI World Index is taken to be market portfolio in the CAPM regression, then the results become worse, as can be seen in table 5.17B. In the case of the mean return selection criterion the number of significant estimates of α decreases from 31 to 1 if transaction costs increase from 0 to 1%. Only for the Egypt CMA the estimate of α is significantly positive at the 10% significance level if transaction costs are equal to 1% per trade. If the Sharpe ratio selection criterion is used to select the best strategy in the training period, then also for the Russia Moscow Times the estimate of α is significantly positive at the 10% significance level.
Hence, after correction for sufficiently high transaction costs and risk, it can be concluded, independently of the selection criterion used, that the best recursive optimizing and testing procedure shows no statistically significant out-of-sample forecasting power for local main stock market indices world wide. Only for low transaction costs (≤ 0.25% per trade) technical trading shows statistically significant out-of-sample forecasting power for the Asian, Chilean, Czech, Greece, Mexican, Russian and Turkish stock market indices. In contrast, for the US, Japanese and most Western European stock market indices no significant out-of-sample forecasting power is found, even for low transaction costs.