the inferences about serial correlation in the returns. For the full sample period 1973-2001 and the two subperiods 1973-1986 and 1987-2001 for respectively 18, 9 and 19 data series the null hypothesis of no autocorrelation is not rejected by the adjusted Q-statistic, while it is rejected by the Ljung-Box (1978) Q-statistic. The autocorrelation functions of the squared returns show that for all data series and for all periods the autocorrelations are high and significant up to order 20. The Ljung-Box (1978) Q-statistics reject the null of no autocorrelation in the squared returns firmly. Hence, all data series exhibit significant volatility clustering, that is large (small) shocks are likely to be followed by large (small) shocks.

3.3  Technical trading strategies

We refer to section 2.3 for an overview of the technical trading rules applied in this chapter. In this thesis we mainly confine ourselves to objective trend-following technical trading techniques which can be implemented on a computer. In total we test in this chapter a set of 787 technical trading strategies2. This set is divided in three different groups: moving-average rules (in total 425), trading range break-out (also called support-and- resistance) rules (in total 170) and filter rules (in total 192). These strategies are also described by Brock, Lakonishok and LeBaron (1992), Levich and Thomas (1993) and Sullivan, Timmermann and White (1999). We use the parameterizations of Sullivan et al. (1999) as a starting point to construct our sets of trading rules. The parameterizations are presented in Appendix B. If a signal is generated at the end of day t, we assume that the corresponding trading position at day t+1 is executed against the price at the end of day t. Each trading strategy divides the data set of prices in three subsets. A buy (sell) period is defined as the period after a buy (sell) signal up to the next trading signal. A neutral period is defined as the period after a neutral signal up to the next buy or sell signal. The subsets consisting of buy, sell or neutral periods will be called the set of buy sell or neutral days.

3.4  Trading profits

We superimpose the signals of a technical trading rule on the buy-and-hold benchmark. If a buy signal is generated, then money is borrowed against the risk-free interest rate and a double position in the risky asset is held. On a neutral signal only a long position
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