Overnight stock returns,intraday returns,and firm-specific investor sentiment

In this study, we propose a new index for measuring firm-specific investor sentiment using overnight and intraday stock returns. We use actual equity data to construct the firm-level investor sentiment index and find that the new index has characteristics expected of a sentiment measure. In addition, we propose a novel sentiment-weighted trading strategy and apply it to momentum and short-term reversal strategies. We find that the sentiment-weighted trading strategy generates better performance in momentum and short-term reversal strategies. The sentiment-weighted trading strategy’s superior performance is evidence that our firm-level investor sentiment index possesses predictive powers with regard to future returns.     

Individual stock sentiment beta and stock returns

Using the data in Chinese stock market, we measure the individual stock sentiment beta, which is defined as the sensitivity of individual stock returns to the individual stock sentiment changes. We demonstrate that stocks in the highest individual stock sentiment beta portfolio have significantly higher excess returns, CAPM alpha, Fama-French three-factor alpha and Fama-French five-factor alpha. Besides, we find that the high individual stock sentiment beta stocks are smaller, younger, more volatile stocks with higher price and higher market beta. After controlling for firm characteristic, the returns of High-Low individual stock sentiment beta portfolios are still significantly positive. Moreover, we show the effect of the individual stock sentiment beta on stock returns is positive and significant in different stock markets, in different sample periods, and in bull and bear market. Besides, the results of the Bayes-Stein individual stock sentiment beta are still stable.     

Liquidity,earnings management,and stock expected returns

This paper examines the relationships among liquidity, earnings management, and stock expected returns by using a sample of Chinese listed firms to investigate 22,022 firm–year observations from 1998 to 2018. Our study reveals that an increase in stock liquidity is associated with a decrease in the degree of earnings management. This result is robust to the use of alternative measures when endogeneity concerns are controlled for. Moreover, the findings indicate that the stock liquidity component of earnings management is positively associated with future stock returns in Chinese firms. Our results reveal that the stock liquidity component of short-termism in managerial decisions plays a critical role in determining future stock returns.     

Tornado activity,house prices,and stock returns

In this paper we investigate the effects of tornado activity on house prices and stock returns in the US. First, using geo-referenced and metropolitan statistical area (MSA)-level data, we find tornado activity to be responsible for a significant drop in house prices. Spillover tornado effects between adjacent MSAs are also detected. Furthermore, our granular analysis provides evidence of tornadoes having a negative impact on stock returns. However, only two sectors seem to contribute to such a negative effect (i.e., consumer discretionary and telecommunications). In a macro-analysis, which relies on aggregate data for the South, West, Midwest and Northeast US regions, we then show that tornado activity generates a significant drop in house prices only in the South and Midwest. In these regions, tornadoes are also responsible for a drop in income. Tornado activity is finally found to positively (negatively) affect stock returns in the Midwest (South). If different sectors are examined, a more heterogeneous picture emerges.     

Firm efficiency and stock returns

In this paper, we investigate the role of firm efficiency in asset pricing using a sample of US publicly listed companies for the period 1988–2007. We employ non-parametric data envelopment analysis (DEA) on various input/output combinations, focusing on sales and market value as output measures in the construction of the frontier technologies. Using these performance measures, we examine whether efficient firms perform differently from inefficient firms following standard financial analysis procedures. First, we employ performance attribution regressions, by forming portfolios based on efficiency scores and tracking the performance of the various portfolios over time. Second, we perform cross-sectional/panel regressions to determine whether firm efficiency indeed has explanatory power for the cross-section of stock returns. Our results suggest that firm efficiency plays an important role in asset pricing and that efficient firms significantly outperform inefficient firms even after controlling for known risk factors.     

Individual stock crowded trades,individual stock investor sentiment and excess returns

Recent behavioral asset pricing models and the popular press suggest that investors may follow similar strategies resulting in crowded equity positions to push prices further away from fundamentals. This paper develops a new approach to measure individual stock crowded trades, and further investigates the joint effects of individual stock crowded trades and individual stock investor sentiment on excess returns. Specifically, our results show that the combined effect of individual stock crowded trades and individual stock investor sentiment on excess returns is positive and significant, which reveals the importance of “anomaly factors” in asset pricing. Furthermore, our results suggest that increasing individual stock buyer-initiated crowded trades will increase excess returns simultaneously; however, increasing individual stock seller-initiated crowded trades will decrease excess returns simultaneously. Collectively, our results highlight the importance of individual stock crowded trades and individual stock investor sentiment on the formation of stock prices.     

Dynamic relationships between industry returns and stock market returns

Different from prior studies which concentrate on the unidirectional impact of industry leading, this study examines the bi-directional dynamical causal relation between industry returns and stock market returns by considering multiple structural breaks for ten major eastern and southern Asia countries. Our results show that finance and consumer service industry returns have significant power in explaining the movements of market returns. Further, we apply logit regressions to explore the determinants of the leading hypotheses and find exchange rate and interest rate are important in explaining the industry–market nexus. In a developed market the industry and the market have feedback relations, but in a highly controlled economy the influence from the stock market dominates.     

Overnight stock returns and realized volatility

The information flow in modern financial markets is continuous, but major stock exchanges are open for trading for only a limited number of hours. No consensus has yet emerged on how to deal with overnight returns when calculating and forecasting realized volatility in markets where trading does not take place 24 hours a day. Based on a recently introduced formal testing procedure, we find that for the S&P 500 index, a realized volatility estimator that optimally incorporates overnight information is more accurate in-sample. In contrast, estimators that do not incorporate overnight information are more accurate for individual stocks. We also show that accounting for overnight returns may affect the conclusions drawn in an out-of-sample horserace of forecasting models. Finally, there is considerably less variation in the selection of the best out-of-sample forecasting model when only the most accurate in-sample RV estimators are considered.     

Over-investment in corporate R&D,risk, and stock returns

Large-size firms which significantly increase their R&D expenditures experience subsequently three-year-long negative abnormal stock returns on the magnitude of 56 basis-points per month. We find no robust evidence of significant event-induced abnormal returns for small-size sample firms or any systematic risk changes for the small- and large- size firms. We also find that the large-size sample firms generate relatively much larger cash flows (i.e., have significantly greater over-investment discretion) and have significantly larger (over-) valuation multiples than the small-size firms. Moreover, some of their operating performance measures show signs of deterioration instead of improvement following these R&D programs. These findings are consistent with the view that investors initially underestimate the over-investment in R&D by some large-size firms that appear to be overvalued and have high cash flows at the time of the investment, only to be disappointed later.     

Indicator selection and stock return predictability

We propose a momentum-determined indicator-switching (MDIS) strategy, simple and effective, to improve the predictability of stock returns, which can effectively select predictors. Empirical results indicate that the stock return forecasts generated by the MDIS strategy are statistically and economically significant. And we find that super long-term momentum of predictability (SMoP) exists in predictive factors. That is, in a long period of time in the past, the best predictor among a series of factors has best prediction ability in the future. We also design restricted momentum-determined indicator-switching (RMDIS) strategy when considering economic constrain. It is robust for the prediction performance of this strategy using a series of extension and robustness test. Success of the RMDIS strategy is also seen in using technical indicators to forecast stock returns.     

Large changes in stock prices: Market,liquidity, and momentum effect

This article investigates the determinants of large changes in stock prices. Empirical evidences suggest that the asymmetry phenomenon in determinants of large changes in stock prices is found in three stock exchanges. In the New York Stock Exchange (NYSE), momentum effect accounts for most of the likelihood of big gains in stock prices, while liquidity characteristics account for sharp declines of stock prices. An interesting finding is that the opposite is true for stocks traded in Amex and NASDAQ. The possible explanations of the different results in different stock exchanges may attribute to the characteristics of firms listed in these stock exchanges are different.     

US elections and monthly stock market returns

Using monthly market returns over a period of 104 years, we investigate possible relationships between stock market performance and various occurrences in American elections. Unlike most prior studies, we find little relationship between the two. In the relatively few cases where we do find statistically significant relationships, the degree of explanatory power is quite small. Specifically, market returns do not appear to vary based on partisan control of the government, a result that is robust to the inclusion or exclusion of macroeconomic control variables. Further, the often-discussed “second-half” effect, which predicts higher returns during the second half of a given presidential term, turns out to be both weaker and less straightforward than is commonly believed. Overall, neither election results nor the election cycle appears to offer much help in predicting stock market returns.      

Simultaneous dependence between firm-level stock returns

We show that use of ordinary least-squares to explore relationships involving firm-level stock returns as the dependent variable in the face of structured dependence between individual firms leads to an endogeneity problem. This in turn leads to biased and inconsistent least-squares estimates. A maximum likelihood estimation procedure that will produce consistent estimates in these situations is illustrated. This is done using methods that have been developed to deal with spatial dependence between regional data observations, which can be applied to situations involving firm-level observations that exhibit a structure of dependence. In addition, we show how to correctly interpret maximum likelihood parameter estimates from these models in the context of firm-level dependence, and provide a Monte Carlo as well as applied illustration of the magnitude of bias that can arise.     

Jump tails,extreme dependencies,and the distribution of stock returns

We provide a new framework for estimating the systematic and idiosyncratic jump tail risks in financial asset prices. Our estimates are based on in-fill asymptotics for directly identifying the jumps, together with Extreme Value Theory (EVT) approximations and methods-of-moments for assessing the tail decay parameters and tail dependencies. On implementing the procedures with a panel of intraday prices for a large cross-section of individual stocks and the S&P 500 market portfolio, we find that the distributions of the systematic and idiosyncratic jumps are both generally heavy-tailed and close to symmetric, and show how the jump tail dependencies deduced from the high-frequency data together with the day-to-day variation in the diffusive volatility account for the “extreme” joint dependencies observed at the daily level.     

Risk and return in the Tehran stock exchange

This paper analyzes market index returns in the Tehran stock exchange (TSE) within the context of three variants of the Capital Asset Pricing Model: the static international; the constant-parameter intertemporal; and a Markov-switching intertemporal CAPM, which allows for time-varying degree of integration with regional and international equity markets. We find that TSE returns are CAPM-efficient at monthly frequency with respect to several international market indices. Moreover, we find evidence in support of international integration of the TSE with respect to international markets. In addition, we conduct an extensive investigation for the direction of causality between TSE returns, international market index returns, and those in neighboring countries.     

Abnormal research and development investments and stock returns

We investigate the relation between abnormal research and development (R&D) investments change and expected stock returns. We provide evidence that firms that abnormally increase their R&D investments (RDI) earn higher returns in comparison to the market portfolio. Specifically, our findings document an economically significant annual positive abnormal RDI returns that ranges from 3.2% to 11.5%. These findings are robust to well-established risk factors in the literature and suggest that the abnormal increases in RDI impacts stock returns.     

Earnings announcements and the variability of stock returns

This article is concerned with the dissemination process of firm-specific annual earnings information in the Norwegian capital market. We find a significant reduction in stock price volatility in the post-announcement period relative to the pre-announcement period for companies traded on the Oslo Stock Exchange in the period 1990–1995. Potential explanations for this phenomenon are tested by relating the observed return volatility to changes in the volatility of the underlying business, the speed at which information is incorporated into stock prices, and the amount of noise in the price process. The empirical analyses reveal no significant changes in either the underlying business variance or the price adjustment coefficients. However, we find a significant decline in the noise term for the largest companies after the earnings release date, supporting the hypothesis that earnings announcements reduce informational asymmetries among investors.     

Earnings and stock returns: evidence from Germany

Past research in the US indicates that stock prices and earnings per share are related. Evidence pertaining to this relationship in other countries is not as extensive. This paper extends two recent studies focusing on Germany, and provides additional information concerning the important informative role played by DVFA earnings. DVFA earnings are a metric jointly constructed by the Deutscher Vereinigung für Finanzanalyse und Anlageberatung and the Schmalenbach-Gesellschaftwith the purpose of providing investors and others interested in share value with a more meaningful measure of economic income than the traditional published earnings figure     

Cross listing,disclosure regimes,and trading volume sensitivity to stock returns

In this paper, we propose that investors of cross-listed firms use trading volume to revise their perception of firms’ value. We further propose that firms that cross list from low-disclosure regimes (usually from emerging economies) have higher trading volume sensitivity to returns than those that cross list from high-disclosure regimes (usually from developed economies), as those from low-disclosure regimes have relatively lax and less stringent disclosure requirements. We use a sample of foreign firms that are cross listed in the U.S. as exchange-listed American Depositary Receipts, adopted the international financial reporting standards (formerly international accounting standards), and filed Form 20-F reconciliation with the U.S. Securities and Exchanges Commission during the period of 1994–2005. Using these firms and a matched-sample of U.S. firms based on exchange, industry and firm size, we document results supporting our hypotheses. Our results have implications for policy makers, regulators and academics.