Features of Financial Returns Modelling Price Volatility Forecasting Standard Deviations The Accuracy of Autocorrelation Estimates Testing the Random Walk Hypothesis Forecasting Trends in Prices Evidence Against the Efficiency of Futures Markets Valuing Options Appendix: A Computer Program for Modelling Financial Time Series.

Modelling Financial Time Series

The purpose of this paper is to review the evidence on the profitability of technical analysis. The empirical literature is categorized into two groups, ‘early’ and ‘modern’ studies, according to the characteristics of testing procedures. Early studies indicate that technical trading strategies are profitable in foreign exchange markets and futures markets, but not in stock markets. Modern studies indicate that technical trading strategies consistently generate economic profits in a variety of speculative markets at least until the early 1990s. Among a total of 95 modern studies, 56 studies find positive results regarding technical trading strategies, 20 studies obtain negative results, and 19 studies indicate mixed results. Despite the positive evidence on the profitability of technical trading strategies, most empirical studies are subject to various problems in their testing procedures, e.g. data snooping, ex post selection of trading rules or search technologies, and difficulties in estimation of risk and transaction costs. Future research must address these deficiencies in testing in order to provide conclusive evidence on the profitability of technical trading strategies.

https://papers.ssrn.com/sol3/Delivery.cfm/joes_519.pdf?abstractid=1006275&mirid=2

What do we know about the profitability of technical analysis

Common Errors in Statistics (and How to Avoid Them): Good/Common Errors in Statistics (and How to Avoid Them), Second Edition

The purpose of this report is to review the evidence on the profitability of technical analysis. The empirical literature is categorized into two groups, "early" and "modern" studies, according to the characteristics of testing procedures. Early studies indicated that technical trading strategies were profitable in foreign exchange markets and futures markets, but not in stock markets before the 1980s. Modern studies indicated that technical trading strategies consistently generated economic profits in a variety of speculative markets at least until the early 1990s. Among a total of 92 modern studies, 58 studies found positive results regarding technical trading strategies, while 24 studies obtained negative results. Ten studies indicated mixed results. Despite the positive evidence on the profitability of technical trading strategies, it appears that most empirical studies are subject to various problems in their testing procedures, e.g., data snooping, ex post selection of trading rules or search technologies, and difficulties in estimation of risk and transaction costs. Future research must address these deficiencies in testing in order to provide conclusive evidence on the profitability of technical trading strategies.

https://papers.ssrn.com/sol3/Delivery.cfm/SSRN_ID603481_code17745.pdf?abstractid=603481&rulid=163369&mirid=4

The Profitability of Technical Analysis: A Review

A large universe of technical trading rules applied to a set of technology industry and small cap sector portfolios over the 1995–2010 period yields superior predictability after adjusting for data snooping bias in the first half of the sample period and delivers statistically significant profits for a number of portfolios when the transaction cost is assumed to be of small to moderate size. Technical analysis is not able to outperform the buy-and-hold approach for any portfolio in the set in the second half of the sample period. The finding that the short-term return predictability becomes much weaker in the more recent period suggests that the underlying segments of the equity market have become more efficient over time. The fact that mechanical trading strategies have been futile after adjusting for data snooping bias for two samples of portfolios where technical analysis is most anticipated to succeed suggests that it is unlikely to have delivered abnormal returns in any other segment of the domestic equity market in the last decade.

Performance of technical analysis in growth and small cap segments of the US equity market

The predictability of long time series of stock index levels and stock prices is investigated using both statistical and trading rule methodologies. The trading rule analysis uses a double moving-average rule and the methods of Brock, Lakonishok and LeBaron. Results are obtained for the FTA, FTSE-100, DJIA and S&P-500 indices, prices for twelve UK stocks and indices derived from these stock prices. Statistical analysis shows that the index and price series are not random walks. The trading rule analysis generally confirms this conclusion. However, small transaction costs would eliminate the profitability of the moving-average rule. Standard ARMA-ARCH models are estimated for time series of returns and bootstrap methods are used to decide if the models can explain the observed trading statistics. The models provide a reasonable description but there is evidence from the trading rule methodology that standard models sometimes fail to describe the dynamics of the indices and prices. Several comparisons are m...

Stephen J. Taylor

Papers

Stock index and price dynamics in the UK and the US: new evidence from a trading rule and statistical analysis