In recent years, the validity of the weak form efficient market hypothesis (EMH) has been called into question as several studies have uncovered evidence that technical trading rules have predictive ability with respect to both developed and emerging stock market indices. This study analyses the forecasting power of 2 of the most popular trading rules using index data for a selection of 11 European stock markets over the January 1991 to December 2000 period. The findings indicate that the emerging markets included in this paper are informationally inefficient; these markets displayed some degree of predictability in their share returns, although the developed markets did not. Furthermore, the results point to large differences in the performance of the rules examined; while small size filters consistently outperformed the buy-and-hold strategy in the emerging markets examined even after the consideration of transaction costs, the performance of the moving average rules was erratic and varied dramatically from market to market.

The question of whether active trading strategies outperform the more naïve approaches that are available to investors has returned to the research agenda. The topic had been hotly debated in the early and middle 1960s, but seemed to have been dispatched to the academic sidelines by proponents of the Efficient Market Hypothesis (EMH). However, the developments in behavioural finance which recognize that individuals may make mistakes when valuing securities have revived interest in this topic. In addition, recent evidence has re-ignited the debate and there is now a new strand of literature which re-examines whether trading strategies based on historic information can yield profits. The current article builds on this recent body of evidence by examining moving average rules for 15 emerging and three developed markets over the period 1989–2003. The results indicate that the return behaviour of the emerging markets studied differed markedly from that of their developed market counterparts; moving average rules were more profitable when tested using emerging stock market indices. In addition, this profitability persisted for longer moving averages, suggesting that trends in share returns were larger and more persistent in emerging markets.

This study examines the impact of the COVID 19 pandemic on the stock markets of China, India, Pakistan, the UK and the US using Generalised Autoregressive Conditional Heteroscedasticity (GARCH) and Threshold GARCH models with COVID 19 as an exogenous dummy variable in the variance equation. The sample period of 2016–2021 is divided into two sub-periods: the pre-COVID 19 period and the COVID 19 period. The results of the study indicate that there was persistent volatility in these markets and that this volatility increased as a result of the pandemic. In addition, the Threshold GARCH results indicate that the asymmetric term was significant in all markets indicating that bad news, such as the pandemic, had a stronger impact on the conditional variance of the returns as compared to good news. In addition, the results further confirm that the US market had no significant impact on the volatility of the Chinese market during the pandemic. The results have important implications for (1) international investors regarding portfolio management and investment risk minimisation in situations like the COVID 19 pandemic; and (2) policy-makers in terms of how they respond to any future pandemic.