average trading strategies with momentum indicators or oscillators, so called relative strength or stochastics. These oscillators should indicate when an asset is overbought or oversold and they are supposed to give appropriate signals when to step out of the market. Isakov and Hollistein (1999) find that the use of oscillators does not add to the performance of the moving averages. For the basic moving average strategies they find an average yearly excess return of 18% on the SBC index. Bootstrap simulations show that an AR(1) or GARCH(1,1) model for asset returns cannot explain the predictability of the trading rules. However it is concluded that in the presence of trading costs the rules are only profitable for a particular kind of investor, namely if the costs are not higher than 0.3-0.7% per transaction, and that therefore weak-form efficiency cannot be rejected for small investors.
LeBaron (2000b) tests a 30-week single crossover moving-average trading strategy on weekly data at the close of London markets on Wednesdays of the US Dollar against the BP, DEM and JPY in the period June 1973 through May 1998. It is found that the strategy performed very well on all three exchange rates in the subperiod 1973-1989, yielding significant positive excess returns of 8, 6.8 and 10.2% yearly for the BP, DM and JPY respectively. However for the subperiod 1990-1998 the results are not significant anymore. LeBaron (2000b) argues that this reduction in forecastability may be explained by changes in the foreign exchange markets, such as lower transaction costs allowing traders to better arbitrage, foreign exchange intervention, the internet or a better general knowledge of technical trading rules. Another possibility is that trading rules are profitable only over very long periods, but can go through long periods in which they lose money, during which most users of the rules are driven out of the market.
LeBaron (2000a) reviews the paper of Brock et al. (1992) and tests whether the results found for the DJIA in the period 1897-1986 also hold for the period after 1986. Two technical trading rules are applied to the data set, namely the 150-day single crossover moving-average rule, because the research of Brock et al. (1992) pointed out that this rule performed consistently well over a couple of subperiods, and a 150-day momentum strategy. LeBaron (2000a) finds that the results of Brock et al. (1992) change dramatically in the period 1988-1999. The trading rules seem to have lost their predictive ability. For the period 1897-1986 the results could not be explained by a random walk model for stock returns, but for the period 1988-1999, in contrast, it is concluded that the null of a random walk cannot be rejected.
Coutts and Cheung (2000) apply the technical trading rule set of Brock et al. (1992) to daily data of the Hang Seng Index quoted at the Hong Kong Stock Exchange (HKSE) for the period October 1985 through June 1997. It is found that the trading range break-