Assesing Performance of Moving Average Investment Timing Strategy Over the UK Stock Market

Predicting stock returns, despite being complicated, has always been of interest to investors, financial analysts, academicians and policy makers. The finance theory, broadly, follows two approaches, namely fundamental and technical analyzes, in order to forecast future prices. Fundamental analysis uses variables related to intrinsic properties of the stock to estimate price, or value. In contrast, technical analysis utilizes historical data on prices (or other information) to drive signals about future prices. Despite its practical usage, profitability of technical analysis remains questionable. While prior studies apply technical analysis, especially moving average, on US stocks, this study follows the methodology adopted by Han, Yang and Zhou (2013) to assess the performance of moving average technical analysis on UK stock market. The study uses daily data on UK-DS Market-PRICE INDEX, 1-Month T-Bill rate, and all stocks listed on London Stock Exchange, United Kingdom (UK). Data has been downloaded from Thomson Reuters's DataStream over a period of more than sixteen years from December 31, 1999 to February 29, 2016. Data on risk free rate and market index do not have any missing values. However, stock prices do include missing values; we replace all of them by not available (NA). We apply moving average investment timing strategy to five quantile portfolios sorted by volatility and compare their performance with respective buy-and-hold portfolios. We also asses risk adjusted returns of quantile portfolios using CAPM. For robustness check, we test the strategy for alternative lag lengths, random switching, and breakeven transactions costs. The results suggest that MA strategy substantially outperforms buy-and-hold strategy in UK stock market by producing significantly higher average returns and risk adjusted returns, lower standard deviations, higher Sharpe ratios, and reasonable success ratios. Results are quite robust to most of the lag lengths and quantiles. However, random switching strategy does not produce significant results in this case. We test MA strategy for various lag lengths; the strategy based on 10-day lag length performs the best. This indicates that signals generated from closer history provide better proxy for future trading. Finally, although breakeven transaction costs are considerably larger than actual transaction costs in UK, other variables measuring trading behaviour under MA strategy provide mixed results when seen in relation to volatility. The Uk stock market is weak from the efficiency empirically proved through this study, then the investors should be able to exploit predictable patterns of share returns in order to earn excess returns on a regular basis. There is reasonable degree of predictability in their security returns.