Investment Q Theory,Mispricing And Expected Stock Returns

Stock market is one of the most important components of the capital market,therefore,it is crucial to see what drives the expected stock returns going up and down and this is also the prerequisites for capital market to serve the real economy.Since 1970s,many studies in asset pricing have suggested that the differences in stock returns are due to those in firm fundamentals,which is known as anomalies.Along with more and more financial ratios exploited,it is minor contribution to explore new anomalies and the theories behind are becoming a hot topic in asset pricing accordingly.To classify the large quantities of anomalies,it takes around 20 years to develop the asset pricing models of three factors(Fama and French,1993)into five(Fama and French,2015)or four(Hou,Xue and Zhang,2016).Despite of different theoretical basis,both the two competing models consider profitability and investment as additional pricing factors,suggesting the great importance of these two groups of anomalies.Hence,this study tries to investigate the predicting power of firm investment in stock market,and then goes further into how to integrate single profitability signals or large quantities of fundamental indicators into one proxy and tests their relation with expected stock returns,respectively.Moreover,dissect the fundamental anomalies based on the rational investment Q theory and the behavioral mispricing.The research questions and results are addressed as follows.First,examine the relations between firm investment and expected stock return as well as the corresponding driving mechanisms.Based on the two-period model of the investment Q theory,the research hypotheses are proposed as follows:the firm investment is negatively correlated with expected stock returns;and this negative relation is steepened among firms with greater investment frictions.The empirical results show that company investment is indeed a negative predictor of stock returns in the U.S.stock market;and that the greater the investment friction,the greater the premium generated by firm investment,which is especially significant in the investment-to-asset and asset-growth anomalies.It is also found that the equity constraint is likely to drive these two anomalies,and that the overall financing constraint also helps to explain the predicting power of investment to asset.So the empirical results are consistent with the investment Q theory.For example,the corporates,which have more difficulties in issuing equities,usually face higher investment costs.Given the same increase in investment to asset,the corresponding expected stock return decreases more than those having less difficulties in equity issuing,showing a stronger negative correlation between the asset growth and the expected return.Therefore,this study can support the investment Q theory empirically with the text-based investment friction measurements to dissect the firm investment anomalies.Meanwhile,this paper also examines the mispricing channels due to limits-to-arbitrage,and finds that limited arbitrage helps understand the investment anomalies of asset growth,investment growth and net operating assets in the U.S.stock market.Specifically,the higher level of limits-to-arbitrage is likely to be a signal of suffering from mispricing,and leads to a stronger negative relation between firm investment and expected stock returns.Actually,the economic mechanisms based on limits-to-arbitrage and the investment Q theory are not mutually exclusive but explain for anomalies from the view of investors and firms,respectively.This paper finds that both of the aforementioned mechanisms contribute to dissecting the cross-sectional predicting power of firm investment in stock returns.Second,this paper studies the Chinese stock return predictability resulted from firm financial strength as a representative of profitability indicators and its economic mechanism.I construct the quarterly F-score to proxy firm financial strength as the sum of 9 signals based on the single financial ratios measuring profitability,balance sheet structure and operation efficiency from quarterly financial reports(including the first quarterly,semi-annual,third quarterly and annual reports).Specifically,the signals equal to 1 if the firm's ability is improved compared to that in the same quarter last year in terms of financial strength,and 0 otherwise.The result of univariate portfolio analysis shows that the expected stock returns are higher for the firms with higher F-score and that the predicting power of F-score cannot be explained away by Fama and French(2015)five factors,indicating that the information of F-score might not be contained in the single signal,for example,ROA,ROE(return on equity),etc.The conjecture is verified by correlation analysis and independent bivariate portfolio sorting.After controlling for profitability and(or)size,book-to-market ratio and momentum,F-score is still significantly and positively associated with the expected returns,suggesting a robust predicting power of firm financial strength.To dissect the premium generated by F-score,results show that the premium is higher among SOEs(low investment friction),firms with high turnover(high limits-to-arbitrage)and following high sentiment.Therefore,both the rational investment Q theory and behavioral mispricing help to dissect the effectiveness of firm financial strength in Chinese stock market.Third,construct the comprehensive quality measure of the fundamentals based on a large number of fundamental indicators,test its predictive power in the cross-sectional expected stock return,and explore the driving mechanisms.First of all,based on the Gordon's Dividend Growth Model,a universe of firm characteristics consisting of 115 indicators is obtained by selecting the company's fundamental indicators from the five aspects,including profitability,growth ability,corporate governance,potential value,and security.Employ principal component analysis(PCA),Fama and Mac Beth regression(FM),forecast combination(FC),composite principal component analysis(CPCA)and partial least squares(PLS)to construct the indicators to measure the comprehensive quality of firm fundamentals,respectively.The results of univariate portfolio sorting show that the indicator by PLS()outperforms the others and that thehedge portfolios are the only to earn significant value weighted returns.Besides,after controlling for value effect,the investors still can earn money by longing the stocks of highest quality and shorting the counterparts.However,the same investment strategy is only valid among small and micro stocks.The less the market capitalization,the more profitable the strategy.It is double confirmed by the low and insignificant returns of the strategy among the large cap universe.To dissect the predicting power of firm comprehensive quality in stock returns,investment Q theory believe that the quality anomaly should be stronger among less frictional firms,which is inconsistent with the empirical results.Then examine the mispricing mechanisms based on market-level and firm individual investor sentiment and limits-to-arbitrage.Behavioral theory based on investor sentiment argues that the premium generated by firm quality should be higher among optimistic investors than the pessimistic counterparts.Empirical results show that the spread portfolio returns based on long and short strategy is slightly higher following high market sentiment than low.In terms of firm-level investor sentiment,the investment strategy based on the fundamental quality among optimistic investors generates the significantly highest returns.After controlling for the market,size and value factors,the results are still robust,consistent with the theoretical expectations.Based on the mispricing channel of limited arbitrage,it is rational to conjecture that the predicting power of firm quality should be stronger among firms difficult to arbitrage.The results of bivariate portfolio analysis show that the higher level of limits-to-arbitrage(higher illiquidity,lower stock price and smaller the trading volume),the larger premium generated by fundamental quality.In conclusion,the positive relation between the comprehensive quality of firm fundamentals and the cross-sectional expected stock returns is driven by the mispricing due to firm-level investor sentiment and limits-to-arbitrage.To sum up,following are the contributions.Firstly,this study contributes to the literature in exploiting the effectiveness of fundamental analysis in Chinese stock market.Different from the US market,the Chinese market is a highly speculative emerging market,which is long seen as more individual investors than institutional investors,more speculation than long-term investment,more information manipulation than information disclosure,and more sudden rise and fall than steady slow bull,etc.Empirical studies also document that the role of fundamentals is weakening in the Chinese stock market(Zhang,Yang and Dai,2007,in Chinese)and this is quite different from the U.S.market with over 400 anomalies driven by fundamentals.To my best knowledge,this study is the first to show that the firm financial strength proxied by F-score is positively associated with the expected stock returns in China.More importantly,the empirical results confirm the important role of comprehensive fundamental information in predicting the Chinese stock returns in cross sections,indicating the effectiveness of fundamental analysis in China.Secondly,dissect stock fundamental anomalies from both rational and behavioral mechanisms.In contrast,existing studies often seek the drivers of anomalies from only one view above.For example,a battery of studies by Fama and French(1993,2008,2015)argue that stock anomalies are due to one of the risk factors such as size,value,profitability,investment,etc.;and Piotroski(2002)and Cheema,nartea and man(2018)believe that behavioral misprice leads to anomalies.In this study,I try to explain for the predicting power of fundamentals from both the rational risk-based investment Q theory with investment frictions and the behavioral mispricing due to investor sentiment and limits-to-arbitrage.Specifically,this paper studies the mispricing mechanisms caused by investor sentiment from both market level and firm level.Thirdly,from the view of big data,this paper studies the cross-sectional expected stock returns with the innovative measurements based on PLS and textual information.In terms of big data in financial ratios,existing literature studies the profitability premium with uni-dimentional proxies,whereas I employ F-score with the sum of 9 dummy signals to proxy firm financial strength which is effective in predicting the Chinese stock returns.Furthermore,a tiny cohort of basic indicators and simple methodologies are used to construct the measurements of firm quality.In this paper,I employ PLS,an econometrics method of newly introduced and more adaptable in asset pricing,extract the most relevant information to expected stock returns from 115 fundamental indicators,and propose a measurement of firm comprehensive quality with outstanding performance in predicting cross-sectional stock returns.Therefore,this study contributes to the literature in dimensionality reduction of quantitative big data in stock market.Considering textual big data,to examine the economic mechanisms more accurately,this paper employs the textual measures of investment friction and investor sentiment with which the results show empirical evidence for the investment Q theory and the mispricing mechanism respectively.The textual proxies of financial constraints in this paper can measure where exactly the firms are constrained in financing with direct information(for example,debt-,equity-constraint).Additionally,the textual measurements are more accurate compared to widely-used proxies,which can screen out the less constrained firms from the small or the young,for instance.As for textual sentiment measurement,based on the news sentiment dataset provided by Data Go Technology Co.,Ltd.,this study constructs a firm-level sentiment indicator,outperforming the previous proxies which mostly measure the market sentiment based on indirect information.Accordingly,the news-based sentiment indicator can be used to examine the mispricing mechanism driven by individual sentiment.Hence,this thesis contributes to the empirical asset pricing studies on the numerous text-based information.