Individual Investors

Growing attention is paid on the individual investors due to their significant impact to the asset price and market stabilization,especially in the short term.In this paper,the behavior of individual investors is investigated by empirical and agent-based modeling approach.In the empirical studies,I find a significant explanatory power of early intraday market-wide up and down movements to the subsequent intraday returns within the same trading days.Compared to the closing of the previous trading day,I introduce two intraday market-wide up/down indicators in terms of the index return and the proportional difference in the numbers of stocks moving upwards to downwards for each minute.Time series analysis shows significantly positive,both economically and statistically,relation between the intraday indicators and the subsequent intraday returns of the market indices.Intraday trading strategies that exploit this intraday relationship lead to monthly returns of 4.1% in the Chinese market and 2.8% in the U.S.market.In addition,the strategies are more profitable for the markets with high activeness of individual investors(i.e.,high trading value,low trading volume per transaction,smallcap,high B/M ratio,low institutional ownership,low price,and high number of shareholders).The results indicate that simple intraday market-wide up/down movements in the earlier trading affect the sentiment of retail investors,resulting the market to move in the same direction within the trading days.Moreover,a sentiment contagion among the individual investors,who engage in an online message board in China,is discovered.Using the number of clicks of online messages as a proxy of sentiment contagion,and two filters to remove messages containing hard news or information,I find that the number of clicks has predictability on stock returns,order imbalance of individual investors,and the total trading volume.More importantly,the prediction suffers a reversal in the long term which implies that the filtered messages contain no information about the fundament of stocks.In addition,it is found that sentiment-based portfolios in China can generate excess returns.Combining the empirical finding and the ideal of learning,by introducing conditional reinforcement learning into an order-driven limit order market with informed and uninformed traders,I find that the learning becomes very effective with respect to pricediscovery and individuals' trading behavior.It helps traders to trade rationally,leading to trading behaviors that are consistent with fully rational equilibrium model.Order book information plays important role for individual investors' order choice and trading behavior.In particular,orderbook information related to the information signal about the fundamental value is crucial for informed traders to choose between market and limit orders,while the information on the last market order provides uninformed trader signals for their momentum trading behavior.Furthermore,the learning improves market liquidity,increases liquidity supply from uninformed traders and liquidity consumption from informed traders.It also improves traders' profitability,market information efficiency and price discovery.