Last hour momentum in the Chinese stock market

PurposeTo capture the last hour momentum over the intraday session, the authors develop a trading strategy for the exchange-traded fund (ETF) that is effective because of the T+0 trading rule. This strategy generates annualized excess return of 9.673%.Design/methodology/approachIn this study, the authors identify a last hour momentum pattern in which the sixth (seventh) half-hour return predicts the next half-hour return by employing high frequency 2012–2017 data from the China Securities Index (CSI) 300 and its ETF.FindingsOverall, both the predictability and the trading strategy are statistically and economically significant. In addition, the strategy performs more strongly on high volatility days, high trading volume days, high order-imbalance days and days without economic news releases than on other days.Originality/valueNoise trading, late-information trading, infrequent rebalancing and disposition effects from retail investors may account for this phenomenon.

Tick Size and Price Reversal after Order Imbalance

It is well known that intraday returns tend to reverse the following intraday period, conditional on excess buying pressure on the bid or ask side. This suggests that liquidity providers “overreact” to order imbalance (OIB) by initially altering quotes so much that a negative autocorrelation is seen in mid-price returns. We investigate under which circumstances this behavior is most common. Specifically, it seems the tick size augments “OIB-reversal”. However, if the tick size is binding for much of the trading day, it has the opposite effect of censoring such reversals. In addition, if market liquidity is high, the reversal becomes more frequent.

The Effect of Online Investor Sentiment on Stock Movements: An LSTM Approach

With more and more investors exerting their voices through network forums or social media platforms, the relationships between online investor sentiment and stock movements have drawn more and more attention. In this paper, we crawl stock comments from China’s most popular online stock forum, East Money (www.eastmoney.com), and then develop a sentiment classifier using the LSTM method. Using the online investor sentiment of the stock forum, we explore the effect of online investor sentiment on the stock movements of CSI300. The results show that online investor sentiment has a significant positive impact on both stock return and trading volume and remains significant after controlling book-to-market ratio, BETA, and market value. Moreover, investor sentiment has a significant positive impact on order imbalance of big trade, which represents the main flow of money in the market. As a result, investor sentiment has a positive impact on the major fund flows in the market. In other words, an increase in investor sentiment can boost the major money flows in the market to some extent. From a practical point of view, investor sentiment can assist investors to make investment decisions and help the government to regulate the stock market.