Investor Sentiment,Limits Of Arbitrage And Anomaly Returns

The traditional asset pricing theory suggests that stock returns are only related to risk,and mispricing will be eliminated immediately in an efficient market.However,there are many phenomena in the market that do not conform to traditional asset pricing theory,which are called anomalies.Since the 1970s,hundreds of anomalies have been discovered in academic literature,and the cross-sectional anomaly factor is also an important basis for constructing investment strategies in the actual investment process.As the anomaly factor continues to be mined,the marginal contribution of researching new cross-sectional anomalies has become lower and lower.The focus of research on anomalies in the field of asset pricing has gradually shifted to a comprehensive analysis of existing anomalies and their influencing factors(Hou,Xue and Zhang,2018;McLean and Pontiff,2016).China is the world’s second largest economy,and has the world’s second largest stock market.It is meaning to study the Chinese market anomalies’ overall performance,sources and influencing factors.This paper studies how investor sentiment affects the performance of cross-sectional anomalies within the framework of behavioral finance.Fluctuations in investor sentiment can make security prices subjective.In the presence of arbitrage limits,mispricing becomes difficult to eliminate(Baker and Wurgler,2006).The individual investor ownership and it’s trading activity in the Chinese market have reached more than 80%,which exposes the market to prominent noise trader risk.Investor sentiment plays an important role in the asset pricing in the Chinese market.The influence of sentiment in China is so prominent that it even weakens many classical asset pricing theories’ effects.The performance of the anomalies in the Chinese market also has characteristics different from other capital markets.The research in this paper includes how investor sentiment leads to the unique performance of anomalies in the Chinese market,how sentiment drive the waves of anomaly returns,and the predictive power of sentiment on anomaly returns.Further,the research includes role of the limits of arbitrage on the relationship between sentiment and anomalies.Details as follows:First,we find that the performance of anomalies in the Chinese market is different from that in the US market,due to the rampant investor sentiment.We find that the anomalies related to transaction frictions are the most pronounced in the Chinese market.The average return for anomalies in the trading frictions category far exceeds that of anomalies in other categories.The anomalies related to value and investment perform worse,and many of them are unstable.The anomalies related to momentum and profitability perform the worst,and most are nonsignificant.We find an increase in anomaly returns over time,which is different from the results from the American market(Chordia,Subrahmanyam and Tong,2014).We also find that the anomaly returns increase post publication,which is different from the results of McLean and Pontiff(2016).Even the returns of anomalies that have received extensive coverage in Chinese journals increase over time.We also find that the publication effect is a subset of the positive time effect.Second,we find that investor sentiment is a factor that drives anomaly returns.During periods of high sentiment,anomaly returns are high.We add the sentiment factor into the anomaly time effects regression and find that it explains the time effects of anomalies.The anomaly returns change with the trend of sentiment.Rapid economic growth and increasingly more noise traders give sentiment an increasing time trend.This also drives the positive time effects of anomaly returns.We also use lagged and detrended sentiment to explain the anomaly returns in order to present the predictive power.With the FF3 factors as control variables,the detrended sentiment factor has significant effects on anomaly returns.This indicates that sentiment is an important factor behind anomalies,in addition to the market return,size effect,and value effect represented by FF3.Investor sentiment can predict the wave of anomaly returns.Periods of high sentiment are when opportunities to profit from mispricing emerge.Third,we study the role of arbitrage limits in the relationship between sentiment and anomaly.The mispricing caused by sentiment need to be maintained by limits of arbitrage.Assuming that sentiment is constant,the anomaly pays off higher with higher arbitrage limits.This paper first uses three indicators of market capitalization,institutional ownership,and idiosyncratic volatility to represent arbitrage limits.It is found that stocks with high arbitrage limits have higher returns and are more obviously affected by investor sentiment.We then investigated whether arbitrage asymmetry exists in anomaly portfolios due to short-sale restrictions.The conclusions are different from other literature.We find that the arbitrage asymmetry is not obvious in China’s market anomalies,the long-leg of the anomalies also have excess returns,and sentiment also has effects on the long-legs,even after removing the impact of transaction costs.We consider that in addition to the impact of transaction costs,noise trader risk is also one of the sources of anomalies’ long-leg returns.The long-leg returns also provide a theoretical basis for "bargain-hunting".The main innovations of this paper are as follows:(1)Some empirical results are different from foreign literature,and we also provide reasons behind them.For example,this paper finds that the trading frictions anomalies are the most pronounced in the Chinese market,while the trading friction anomalies are the worst in the US market;Another example is that the anomaly returns have an increased time effect,which is also opposite to the US market.The reasons behind them are due to the high proportion of retail investors in the Chinese market and the prominent effects of investor sentiment.(2)This article provides a perspective that is more suitable for the Chinese market—behavioral finance to explain the Chinese market.This paper permeates the influence of investor sentiment into every aspect of asset pricing research.For example,it is proposed that sentiment,as an important factor other than the three Fama-French factors,drives the wave of anomaly returns in the Chinese market.Moreover,this paper also believes that salient sentiment has destroyed the explanatory power of traditional asset pricing theory in China.Many classical theories are not based on investor sentiment,and because the outstanding investor sentiment in the Chinese market makes stock prices subjective,these theories are difficult to work in the Chinese market.(3)Different from the literature on individual anomalies,this paper focuses on exploring the overall laws of China’s market anomalies to reflect the characteristics of China’s market.The 62 anomalies studied cover all categories,but also highlight the focus of trading frictions category anomalies.(4)The innovation of this paper also lies in improving the profits of the existing anomaly strategies,which has guiding significance for the actual investment.For many years,academic research has been committed to discovering new anomalies,but the marginal contribution of new anomalies has become lower and lower.This paper does not study new anomalies(or trading strategies),but focuses on exerting the effects of existing strategies.The research in this paper indicates to "timely" construct an anomaly based on market sentiment.At the stage of higher investor sentiment,when the mispricing and noise trader risk is higher,investors can obtain greater returns by using the anomalies related to sentiment.On the contrary,when the sentiment is low,the mispricing is also low,and there is no noise trader risk to maintain the mispricing."Timely" investment can not only improve the efficiency of capital utilization,but also reduce the losses caused by transaction costs.