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Purpose: The purpose of this paper is to examine what the optimal time is in a typical trading day for investors to buy/sell stocks in the Australian stock market. Design/methodology/approach: The study mainly focuses on the S&P/ASX200. Each trading day, between 10:00 a.m. and 4:00 p.m., is divided into 30-min blocks. The effectiveness of easily implementable trading strategy to purchase the index in the morning and sell at the close is tested. The study controls for the excess overnight price volatility to improve the effectiveness of the investment strategy. This trading strategy is compared against other 66 possible day-trading combinations. Findings: The results show that the trading strategy of buying in the first 30 min of the trading session and close off the position during the last 30 min obtains higher returns than other 66 strategies. Practical implications: The day-trading strategy proposed in this study is very simple and therefore can be easily implemented by investors including individual investors. Originality/value: To the best of our knowledge, this is the first study which constructs a trading strategy using the J- or U-shaped intraday return pattern. [ABSTRACT FROM AUTHOR]

We demonstrate that arbitrage risk, constructed using three measures — noise trader risk, trading cost and information uncertainty — can predict the return of stocks cross-sectionally in China. The findings are broadly consistent even when out-of-sample tests are conducted using the Fama-MacBeth cross-sectional regression approach. We also construct hypothetical portfolios using the information arising from arbitrage risk and find the existence of abnormal returns which is robust to the use of various portfolios constructed by re-sampling the observations through multiple approaches (e.g., by market capitalization and by book-to-market ratio). Lastly, we reconstruct our portfolios by considering the unique nature of the Chinese stock market (e.g., the dominance of individual investors). Our trading strategies again successfully obtain abnormal returns, suggesting that arbitrage risk can be useful to construct effective investment portfolios in China. • In- and out-of-sample tests are conducted on the cross-sectional stock return in China. • Arbitrage risk is decomposed into noise trader risk, trading cost and information uncertainty. • These risk components effectively forecast stock returns. • These risk components can be used to construct portfolios with abnormal returns. [ABSTRACT FROM AUTHOR]