When does investor sentiment predict stock returns?

We examine the asymmetry in the predictive power of investor sentiment in the cross-section of stock returns across economic expansion and recession states. We test the implication of behavioral theories and evidence that the return predictability of sentiment should be most pronounced in an expansion state when investors' optimism increases. We segregate economic states according to the NBER business cycles and further implement a multivariate Markov-switching model to capture the unobservable dynamics of the changes in the economic regime. The evidence suggests that only in the expansion state does sentiment perform both in-sample and out-of-sample predictive power for the returns of portfolio formed on size, book-to-market equity ratio, dividend yield, earnings-to-price ratio, age, return volatility, asset tangibility, growth opportunities, and 11 widely documented anomalies. In a recession state, however, the predictive power of sentiment is generally insignificant.     

When does the tone of earnings press releases matter?

The tone of a firm's financial disclosure is increasingly used as a variable in panel data regressions to predict future performance and explain investors' reaction at earnings announcement. We investigate when tone is informative, and argue that the informativeness of tone increases with the information asymmetry between firms and investors. Using a sample of over 50,000 earnings press releases of about 1800 U.S. public firms between 2004 and 2015, we find that firm growth, size, age, complexity and forecast inaccuracy are key drivers of tone informativeness. The effect is economically significant, since, compared to the reference case of a transparent firm, we find that the slope coefficient of tone doubles or even quadruples in panel data regressions when the firm operates in an environment with high information asymmetry.     

Insider trading around auto recalls: Does investor attention matter?

Review of Quantitative Finance and Accounting - Using a comprehensive sample of customer complaints filed with the National Highway Traffic Safety Administration, we examine the...     

How does news sentiment affect the states of Japanese stock return volatility?

This paper examines the impact of public news sentiment on the volatility states of firm-level returns on the Japanese Stock market. We firstly adopt a novel Markov Regime Switching Long Memory GARCH (MRS-LMGARCH), which is employed to estimate the latent volatility states of intraday stock return. By using the RavenPack Dow Jones News Analytics database, we fit discrete choice models to investigate the impact of news sentiment on changes of volatility states of the constituent stocks in the TOPIX Core 30 Index. Our findings suggest that news occurrence and sentiment, especially those of macro-economic news, are a key factor that significantly drives the volatility state of Japanese stock returns. This provides essential information for traders of the Japanese stock market to optimize their trading strategies and risk management plans to combat volatility.     

Does liquidity drive stock market returns? The role of investor risk aversion

In this paper, we explore the relations between liquidity, stock returns, and investor risk aversion as captured by the variance risk premium (VRP). This is motivated by theoretical and empirical evidence in the literature which suggests that investor risk aversion negatively correlates with asset liquidity, and ample empirical evidence documenting liquidity risk premium. We use monthly US data from January 1999 to December 2018 and show that innovations in the VRP Granger-cause stock returns, which in turn drive liquidity. Our findings are consistent with predictions of prior theories and highlight the predictability of the VRP. They also contribute to the on-going debate on the causal relation between stock returns and liquidity. Finally, we explore the channels through which the VRP impacts liquidity and find that the VRP influences market and momentum factors, and that movements in these factors lead to changes in liquidity.

     

Does the stock market influence investor everyday decisions? The case of parking violations

We explore in this study whether stock market returns influence investor decisions in their everyday life. We find that past and contemporaneous US stock market returns are related negatively to the registered number of parking violations in New York City between 2014 and 2020. We support as the channel of this relationship the level of investor anxiety. These results support extensions of the utility theory demonstrating the significance of emotions on individuals' decisions. Overall, this study shows evidence of the societal impact of finance.     

Does the weather affect stock market volatility?

This paper investigates the empirical association between stock market volatility and investor mood-proxies related to the weather (cloudiness, temperature and precipitation) and the environment (nighttime length). Overall, our results suggest that cloudiness and length of nighttime are inversely related to historical, implied and realized measures of volatility. The strength of association seems to vary with the location of an exchange on Earth with respect to the equator. Weather deviations from seasonal norms and dummies representing extreme weather conditions do not offer additional explanatory power in our datasets.     

Does futures trading increase stock market volatility? The case of the Nikkei stock index futures markets

We propose new tests to examine whether stock index futures affect stock market volatility. These tests decompose spot portfolio volatility into the cross-sectional dispersion and the average volatility of returns on the portfolio's constituent securities. Our tests show that for Nikkei stocks spot portfolio volatility increased and cross-sectional dispersion decreased compared with average volatility when Nikkei futures began trading on the Osaka Securities Exchange, but not on the Singapore International Monetary Exchange. For non-Nikkei stocks, no shift occurred when futures trading began on either exchange. These findings are consistent with the hypotheses that futures trading increases spot portfolio volatility but that there is no volatility “spillover” to stocks against which futures are not traded. However, the increase in volatility attributable to futures trading is small compared with volatility shifts induced by changes in broad economic factors.     

Where are the sources of stock market mispricing and excess volatility?

Using a simple dividend model, we illustrate and synthesize the sources of stock market mispricing and excess volatility based upon two hypotheses—inflation illusion and heterogeneous beliefs. Our theoretical framework posits that equity mispricing arises when investors have subjective expectations about discount rates or dividend growth rates. We then analyze the sources of equity mispricing and market excess volatility under a VAR framework. Empirically, we find that both inflation illusion and heterogeneous beliefs explain equity mispricing. However, heterogeneous beliefs play a more important role in explaining stock mispricing in the long run. We also find that heterogeneous beliefs cause excess volatility, but inflation illusion does not. Therefore, dispersion in investors’ beliefs is a better explanation of stock market mispricing than the investors’ inability to properly discount future cash flows.     

How does electronic trading affect efficiency of stock market and conditional volatility? Evidence from Toronto Stock Exchange

The present paper investigates informational efficiency and changes in conditional volatility of the TSX before and after the implementation of an automated trading system on April 23, 1997. Using a battery of unit root, stationarity, as well as linear tests, we find that the introduction of electronic trading led to an increase in linearity dependence in TSX daily returns. In addition, when we examined the nonlinearity dependences using powerful econometric tests, we find that electronic trading has increased nonlinear dependencies in return series, which is the main cause of rejecting the Random Walk Hypothesis (RWH). Our results suggest that the automated trading system has negatively affected informational efficiency of the TSX. We also find evidence of long memory following automation which suggests that the introduction of electronic trading has increased the level of persistence of information and trading shocks.     

The stock market’s reaction to macroeconomic news under ambiguity

Financial Markets and Portfolio Management - We investigate the quality of the information that macroeconomic news conveys to the stock market about future business conditions. Our econometric...     

Institutional investor horizon and stock price synchronicity: Do product market competition and analyst coverage matter?

This paper provides new insights into the relation between institutional investment horizon and stock price synchronicity and investigates whether this relationship depends on the intensity of product market competition and analyst coverage. Based on a sample of French listed companies, we find that long-term (short-term) institutional investors are associated with lower (higher) stock price synchronicity. The results also show that the negative effect of long-term institutional investors is more accentuated for firms in less competitive markets and with high analyst coverage. An additional analysis shows that the synchronicity reduction effect does not vary during the financial crisis. Overall, these findings suggest that unlike their short-term counterparts, long term investors reduce asymmetric information and help disseminate firm-specific information into stock prices.     

When do investors gamble in the stock market?

Recent studies have uncovered gambling-motivated trading activities in financial markets in which investors seek lottery-type payoffs by using financial assets. Building on prospect theory, this study provides an important complement to prior research and investigates what period that investors make gambling-motivated trading in the stock market. Examining data from the Chinese stock market, investors are revealed to have asymmetric gambling preferences in gain and loss domains. Investors' gambling motivations are more easily triggered when the market is experiencing a loss. In such periods of time, investors may preferentially opt for lottery-type stocks that offer them a small chance to earn an extreme return at the risk of a likely small loss, simply due to their ‘aversion to a sure loss’.     

Less is more? New evidence from stock market volatility predictability

The complex nature of stock market volatility has motivated researchers to apply a variety of predictors to obtain reliable predictive information for precise forecasting. This study seeks to examine the effectiveness of the novel Global Financial Uncertainty (GFU) indices, comprising of only five sub-indices, in predicting stock market volatility using the widely used mixed-data sampling (MIDAS) model. The results demonstrate the remarkable and stable predictive power of GFU, even during crises and global financial uncertainty shocks. Specifically, the financial uncertainty index from Europe plays a significant role in our analysis. Importantly, we find that the GFU index outperforms a large number of other indicators in stock volatility forecasting. The statistical and economic significance of the predictive power of GFU is remarkable. Our study provides significant insights for market participants and policymakers that highlight the need to prioritize global financial uncertainty.     

How asymmetric is U.S. stock market volatility?

This paper explores differences in the impact of equally large positive and negative surprise return shocks in the aggregate U.S. stock market on: (1) the volatility predictions of asymmetric time-series models, (2) implied volatility, and (3) realized volatility. Following large negative surprise return shocks, both asymmetric time-series models (such as the EGARCH and GJR models) and implied volatility predict an increase in volatility and, consistent with this, ex post realized volatility normally rises as predicted. Following large positive return shocks, asymmetric time-series models predict an increase in volatility (albeit a much smaller increase than following a negative shock of the same magnitude), but both implied and realized volatilities generally fall sharply. While asymmetric time-series models predict a decline in volatility following near-zero returns, both implied and realized volatility are normally little changed from levels observed prior to the stable market. The reasons for the differences are explored.     

Testing for efficiency in the Saudi stock market: does corporate governance change matter?

Review of Quantitative Finance and Accounting - We study the informational efficiency of the Saudi stock market (SSM), while accounting for corporate governance change, based on single, multiple,...     

The effect of bank capital on lending: Does liquidity matter?

This paper uses a sample of quarterly observations of insured US commercial banks to examine whether the effect of bank capital on lending differs depending upon the level of bank liquidity. We find that the effect of an increase in bank capital on credit growth, defined as growth rate of net loans and unused commitments, is positively associated with the level of bank liquidity only for large banks and that this positive relationship has been more substantial during the recent financial crisis period. This result suggests that bank capital exerts a significantly positive effect on lending only after large banks retain sufficient liquid assets.     

Does the major market influence transfer? Alternative effect on Asian stock markets

Based on the time-varying regression model of Chow et al. (J Comp Econ 39(4):577–583, 2011. doi: 10.1016/j.jce.2011.06.001), this paper simultaneously analyzes the ebb and flow of change by China and the U.S. as leading players in relation to their comovement on various Asian stock markets. We include several important controls for worldwide economy performance, the stock market return rates of major importing nations, and linear/non-linear time trend fixed effects to stress the influence of China and U.S. on eight Asian economies. The empirical results indicate the increasing influence of the China stock market during the subprime mortgage crisis. Moreover, the U.S. market remains influential on the Chinese region, but loses/decreases its influence, especially on the Four Asian Tigers, significantly during/after the subprime mortgage crisis.     

Are stock market crises contagious? The role of crisis definitions

Financial contagion studies generally examine whether co-movement between markets increases during a crisis. We use a flexible co-movement measure to examine how conclusions of such analyses depend on the sample chosen as the ‘crisis’. To this end, we analyse stock market co-movement during the 1997 Asian crisis and the 2007 global financial crisis for all possible source countries and for all possible time periods or extreme return quantiles. This way we account for the main crisis dating approaches adopted in the literature. Our results suggest there is no clear relationship between excess co-movement and commonly used crisis samples.     

Do FOMC minutes matter to markets? An intraday analysis of FOMC minutes releases on individual equity volatility and returns

This paper examines the 2006 to 2007 time period to determine the extent to which the release of the Federal Reserve minutes affects equity volatility and returns for 2832 individual firms. Using intraday data, we find that equity returns are essentially unaffected by FOMC minutes releases. We do find evidence of volatility effects, in that conditional volatility is lower prior to the minutes release and higher after the minutes release on release days, relative to a “control” day one week prior to the release date. These differences manifest at the 2:00–2:05 pm interval, and generally dissipate within 15 min. Consistent with previous literature, we also find evidence of both industry-specific and firm size effects in our data. Finally, we see that volatility is higher (lower) when the minutes are released after the Federal Reserve engages in restrictive (expansionary) monetary policy. Our results are robust to a variety of different definitions of the “control” dates, as well as differing industry definitions.