Renewed interest in the 1990s
Little work on technical analysis appeared during the 1970s and 1980s, because the efficient markets hypothesis was the dominating paradigm in finance. Brock, Lakonishok and LeBaron (1992) test the forecastability of a set of 26 simple technical trading rules by applying them to the closing prices of the DJIA in the period January 1897 through December 1986, nearly 90 years of data. The set of trading rules consists of moving average strategies and support-and-resistance rules, very popular trading rules among technical trading practitioners. Brock et al. (1992) recognize the danger of data snooping. That is, the performance of the best forecasting model found in a given data set by a certain specification search could be just the result of chance instead of truly superior forecasting power. They admit that their choice of trading rules could be the result of survivorship bias, because they consulted a technical analyst. However they claim that they mitigate the problem of data snooping by (1) reporting the results of all tested trading strategies, (2) utilizing a very long data set, and (3) emphasizing the robustness of the results across various non-overlapping subperiods for statistical inference. Brock et al. (1992) find that all trading rules yield significant profits above the buy-and-hold benchmark in all periods by using simple t-ratios as test statistics. Moreover they find that buy signals consistently generate higher returns than sell signals and that the returns following buy signals are less volatile than the returns following sell signals. However t-ratios are only valid under the assumption of stationary and time independent return distributions. Stock returns exhibit several well-known deviations from these assumptions like leptokurtosis, autocorrelation, dependence in the squared returns (volatility clustering or conditional heteroskedasticity), and changing conditional means (risk premia). The results found could therefore be the consequence of using invalid significance tests. To overcome this problem Brock et al. (1992) were the first who extended standard statistical analysis with parametric bootstrap techniques, inspired by Efron (1979), Freedman and Peters (1984a, 1984b) and Efron and Tibshirani (1986). Brock et al. (1992) find that the patterns uncovered by their technical trading rules cannot be explained by first order autocorrelation and by changing expected returns caused by changes in volatility. Stated differently, the predictive ability of the technical trading rules found is not consistent with a random walk, an AR(1), a GARCH-in-mean model, or an exponential GARCH model. Therefore Brock et al. (1992) conclude that the conclusion reached in earlier studies that technical analysis is useless may have been premature. However they acknowledge that the good results of the technical trading rules can be offset by transaction costs.The strong results of Brock, Lakonishok and LeBaron (1992) led to a renewed interest in academia for testing the forecastability of technical trading rules. It was the impetus
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