With the introduction of many derivatives into the capital market,including stock index futures,the trading strategies in financial markets have been gradually enriched.However,there is still no theoretical model that can determine whether these strategies are effective,what the risks are,and how costly the strategies are.We built an agent-based cross-market platform that includes five stocks and one stock index future,and constructed an evaluation system for stock index futures trading strategies.The evaluation system includes four dimensions:effectiveness,risk,occupation of capital,and impact cost.The results show that the informed strategy performs well in all aspects.The risk of the technical strategy is relatively higher than that of the other strategies.Moreover,occupation of capital and impact cost are both higher for the arbitrage strategy.Finally,the wealth of noise traders is almost lost.
A number of studies have investigated the predictability of Chinese stock returns with economic variables.Given the newly emerged dataset from the Internet,this paper investigates whether the Baidu Index can be employed to predict Chinese stock returns.The empirical results show that 1)the Search Frequency of Baidu Index(SFBI)can predict next day’s price changes;2)the stock prices go up when individual investors pay less attention to the stocks and go down when individual investors pay more attention to the stocks;3)the trading strategy constructed by shorting on the most SFBI and longing on the least SFBI outperforms the corresponding market index returns without consideration of the transaction costs.These results complement the existing literature on the predictability of Chinese stock returns and have potential implications for asset pricing and risk management.
Using stock market data over 16 years for Chinese stock markets and over 3 years for U.S.stock markets,this study explores the explanatory power of early intraday market-wide up and down movements to the subsequent intraday returns within the same trading day.As compared to the closing of the previous trading day,we 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 at each minute.A time series analysis shows an economically and statistically significant positive 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 in markets with high activity of individual investors(i.e.,high trading value,low trading volume per transaction,small-cap,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 in market movements in the same direction within the trading day.
