Stock market volatility, excess returns, and the role of investor sentiment

Using the Investors' Intelligence sentiment index, we employ a generalized autoregressive conditional heteroscedasticity-in-mean specification to test the impact of noise trader risk on both the formation of conditional volatility and expected return as suggested by De Long et al. [Journal of Political Economy 98 (1990) 703]. Our empirical results show that sentiment is a systematic risk that is priced. Excess returns are contemporaneously positively correlated with shifts in sentiment. Moreover, the magnitude of bullish (bearish) changes in sentiment leads to downward (upward) revisions in volatility and higher (lower) future excess returns.     

The information content of option-implied information for volatility forecasting with investor sentiment

This study explores the effect of investor sentiment on the volatility forecasting power of option-implied information. We find that the risk-neutral skewness has the explanatory power regarding future volatility only during high sentiment periods. Furthermore, the implied volatility has varying volatility forecasting ability depending on the level of investor sentiment. Our findings suggest that the effectiveness of volatility forecasting models based on option-implied information varies over time with the level of investor sentiment. We confirm the important role of investor sentiment in volatility forecasting models exploiting option-implied information with strong evidence from in-sample and out-of-sample analyses. We also present improvements in the accuracy of volatility forecasts from volatility forecasting models derived by incorporating investor sentiment in these models.     

Exploring the relationship between investor sentiment and price volatility

By performing Grey relation analysis, this study elucidates the relationship between investor sentiment and price volatility in the Taiwanese stock market. A sequential relationship is identified between investor sentiment and price volatility, and ranked according to order of importance. Analytical results show that short sales volumes may be an individual leading indicator useful in observing the effects of sentiment on price volatility, followed by open interest put/call ratios and trading volumes, and buy/sell orders. Institutional investors are related, to a lesser extent, to price volatility and sentiment. Qualified foreign institutional investors, or more rational investors, are the least influenced by price volatility, followed by securities investment trust companies and dealers. TAIEX options exert the strongest influence on sentiment during the study period, making them a valuable reference for gauging price volatility.     

Biased information weight processing in stock markets

The concepts of over- and underreaction are frequently used in behavioral financial research to explain investor behavior and resulting market phenomena. This research often makes arbitrary assumptions about which of the two biases is prevalent in a specific situation although psychological research offers more explicit insights. Investors overreact towards information of low weight and underreact if the information has high weight (high reliability). We propose a model that transfers these experimental findings to a financial market setting. Our time-series and cross-sectional empirical analyses support the hypothesis that investors misperceive information weight, which leads to short-term predictability in returns.     

Forecasting aggregate stock market volatility with industry volatilities: The role of spillover index

In this paper, we aim to improve the predictability of aggregate stock market volatility with industry volatilities. The empirical results show that individual industry volatilities can provide useful predictive information, while the predictive contribution is limited. We further consider the spillover index between industry volatilities and find it displays strong predictive power for stock market volatility. Based on the portfolio exercise, we find that a mean-variance investor can achieve sizeable economic gains by using volatility forecasts of the spillover index. In addition, we conduct three extended analyses and further demonstrate the superior performance of the spillover index. Also, our results show robustness to a series of alternative settings. Finally, we investigate why the spillover index performs better and answer what information it contains. The results show that the spillover index can reflect and explain investor sentiments that are related to stock market volatility.     

Institutional investor sentiment and aggregate stock returns

This paper examines the equity market return predictability of institutional investor sentiment, in comparison to individual investor sentiment. Our findings suggest that institutional traders are informed and that their sentiment helps to tilt stock prices towards the intrinsic value. This is because the sentiment of institutions encompasses news regarding expectations on future cash flows of underlying firms that impounds itself into future price expectations. In this study, we add to the large number of studies that investigate the role and implications of investor sentiment, which has long been viewed as a pure behavioural phenomenon, on market efficiency and price discovery.     

Investor sentiment and stock volatility: New evidence

This study investigates the predictability of sentiment measure on stock realized volatility. We propose a new investor sentiment index (NISI) based on the partial least squares method. This sentiment index outperforms many existing sentiment indicators in three aspects. First, in-sample result shows that the NISI has greater predictive power relative to the others. Most sentiment indicators show predictability in the non-crisis period only while the NISI is also effective in the crisis period. Furthermore, the NISI exhibits more prominent superiority in longer horizons forecasting. Second, further analysis indicates that the NISI has robust predictability before and after the Chinese stock market turbulence periods while the others not. Importantly, the NISI is still effective significantly after considering leverage effect while most of the others not. Finally, out-of-sample analysis demonstrates that the NISI is more powerful than other sentiment measures. This result is reproducible in different robustness checks.     

Sensitivity to investor sentiment and stock performance of open market share repurchases

This paper finds that stocks of repurchasers with high sensitivity to investor sentiment are more likely to be mispriced. Thus, such repurchases are followed by superior post-buyback stock performance. This abnormal return associated with sensitivity to sentiment cannot be explained by other undervaluation factors: book-to-market or prior return effects. My results are robust with factor model analysis and controls for contamination effects. I conclude that this sentiment-driven undervaluation may result from the difficulty to value and/or limits to arbitrage rather than investor overreaction.     

Framing and the disposition effect: evidence from mutual fund investor redemption behaviour

Research on decision-making under uncertainty has highlighted that individuals often use simple heuristics and/or exhibit behavioural biases. Specifically, with respect to portfolio decisions, research has indicated that investors are subject to the disposition effect, i.e. they are reluctant to sell assets that have performed poorly (losers) and prone to sell assets that have performed well (winners). We find that the mutual fund investors in our sample are subject to the disposition effect when they withdraw the redemption proceeds from their account, but not when they reallocate the proceeds within the account. The evidence is consistent with Shefrin and Statman’s hypothesis that framing a transaction as a transfer as opposed to a sale mitigates the disposition effect.     

Investor sentiment and return predictability of disagreement

This study examines the influence of investor sentiment on the relationship between disagreement among investors and future stock market returns. We find that the relationship between disagreement and future stock market returns time-varies with the degree of investor sentiment. Higher disagreement among investors’ opinions predicts significantly lower future stock market returns during high-sentiment periods, but it has no significant effect on future stock market returns during low-sentiment periods. Our findings imply that investor sentiment is related to several causes of short-sale impediments suggested in the previous literature on investor sentiment, and that the stock return predictability of disagreement is driven by investor sentiment. We demonstrate that investor sentiment has a significant impact on the stock market return predictability of disagreement through in-sample and out-of-sample analyses. In addition, the profitability of our suggested trading strategy exploiting disagreement and investor sentiment level confirms the economic significance of incorporating investor sentiment into the relationship between disagreement among investors and future stock market returns.     

Asset pricing with investor sentiment: On the use of investor group behavior to forecast ASEAN markets

A study of investor behavior, using four investor groups (local, foreign, institutional, and dealer's accounts) on the Stock Exchange of Thailand (SET). The daily net purchases of each group are used as leading indicators for sentiment. The sentiments are examined with relation to each other and market returns. Eight proven macroeconomic factors with known cross-sectional relationships and known to forecast with returns are examined as a benchmark for the newly proposed sentiment factor model. Retesting the factors allows for an apples to apples comparison with the proposed sentiment factors. Using a VAR framework this research finds that dealers predominantly sell to institutional accounts, creating a negative correlation between the two groups, in addition to strong institutional herding which is all indicative of potential agency problems on the exchange. Also find that local individual accounts practice negative feedback trading and the other groups practice positive feedback trading. Of the four groups, the only group that influences the SET is the local individual group of investors. The foreign investor is found to be the least significant group on market returns, provide market liquidity to locals, and be the least responsive to daily market changes-following the prudent man rule. Lastly, propose a simple model, using investor behavior to accurately predict the market's direction for the following day 76 percent of the time with market timing ability (66 percent in Malaysia). This can be useful for buying and shorting the market.     

Institutional trading,investor sentiment,and lottery-like stock preferences

This paper explores the time-varying institutional investor preference for lottery-like stocks. On average, institutional investor holdings reflect an aversion to lottery-like stocks. However, I find that an institutions’ aversion to lottery-like stocks is reduced when investor sentiment is low. Moreover, I find that during low sentiment periods, institutional investors have abnormally high trading profits in more positively skewed stocks. These results suggest that institutions reduce their aversion toward lottery-like stocks during low sentiment periods to profitably trade in lottery-like stocks.     

News sentiment and the investor fear gauge

This note examines the relationship between aggregate news sentiment and changes in the implied volatility index (VIX). A significant negative contemporaneous relationship between changes in VIX and news sentiment is discovered. The relationship is asymmetric whereby changes in VIX are larger following the release of negative news items.     

Islamic and conventional portfolios optimization under investor sentiment states: Bayesian vs Markowitz portfolio analysis

This paper investigates the portfolio optimization under investor’s sentiment states of Hidden Markov model and over a different time horizon during the period 2004–2016. To compare the efficient portfolios of the Islamic and the conventional stock indexes, we have employed two approaches: the Bayesian and Markowitz mean-variance. Our findings reveal that the Bayesian efficient frontier of Islamic and conventional stock portfolios is affected by the investor’s sentiment state and the time horizon. Our findings also indicate that the investor’s sentiment regimes change the Islamic and the conventional optimal diversified portfolios.Moreover, the results show that the potential diversification benefits seem to be more important when using the Bayesian approach than when applying the Markowitz approach. This finding is valid for the bearish, depressed, bullish and calm states in Islamic stock markets. However, the diversification of potential portfolios is significant only for the bullish and the bubble states in the conventional financial markets.The findings of the study provided additional evidence for investors to exploit googling investor sentiment states to evaluate the portfolio performance and make an optimal portfolio allocation.     

Investor sentiment,SEO market timing,and stock price performance

This article details an investigation of the impact of investor sentiment on the probability of firms conducting seasoned equity offerings (SEOs) and on stock price performance around and subsequent to SEOs. The results show that investor sentiment has a positive impact on SEO probability and that this impact is stronger for small and young firms. Furthermore, firms conducting SEOs during high sentiment periods experience less severe short-run price drops around the issuance yet more severe post-issue long-run underperformance, compared with firms conducting SEOs during low sentiment periods. These effects of investor sentiment on stock price performance are stronger for small, young, and high market-to-book ratio firms.     

The pricing of sentiment risk in European stock markets

This paper studies whether sentiment is rewarded with a significant risk premium in the European stock markets. We examine several sentiment proxies and identify the Economic Sentiment Indicator from the EU Commission as the most relevant sentiment proxy for our sample. The analysis is performed for the contemporaneous excess returns of EA-11 stock markets in the period from February 1999 to September 2015. We apply a conditional multi-beta pricing model in order to track the variation of the sentiment risk premium over time. The results demonstrate a positive significant relationship between sentiment and contemporaneous excess returns which is consistent with previous studies. The calculated sentiment risk premium is significant as well but negative implying that an investment in EA-11 countries over the examined time period – that is bearing sentiment risk – would have been unattractive to the investors on average.     

The impact of conventional and unconventional monetary policy on investor sentiment

This paper examines the relationship between monetary policy and investor sentiment across conventional and unconventional monetary policy regimes. During conventional times, we find that a surprise decrease in the fed funds rate leads to a large increase in investor sentiment. Similarly, when the fed funds rate is at its zero lower bound, research results indicate that expansionary unconventional monetary policy shocks also have a large and positive impact on investor mood. Together, our findings highlight the importance of both conventional and unconventional monetary policy in the determination of investor sentiment.     

Effects of investor sentiment and country governance on unexpected conditional volatility during the COVID-19 pandemic: Evidence from global stock markets

This paper first investigates the relationship between investor sentiment, captured by internet search behaviour, and the unexpected component of stock market volatility during the COVID-19 pandemic. According to data on 12 major stock markets, our research indicates a positive correlation between the Google search volume index on COVID-19 and the unexpected volatility of stock markets. The result suggests that greater COVID-19-related investor sentiment during this pandemic is associated with higher stock market uncertainty.Our study further examines whether country-level governance plays a role in protecting stock markets during this pandemic and reveals that the unexpected conditional volatility is lower when a country's governance is more effective. The impact of investor sentiment and country governance on unexpected volatility after the initial shock of COVID-19 is also investigated. The findings demonstrate the importance of establishing good country-level governance that can effectively reduce stock market uncertainty in the context of this pandemic, and support continual policy development related to investor protection.     

The asymmetric relationship between returns and implied volatility: Evidence from global stock markets

We investigate the asymmetric relationship between returns and implied volatility for 20 developed and emerging international markets. In particular we examine how the sign and size of return innovations affect the expectations of daily changes in volatility. Our empirical findings indicate that the conditional contemporaneous return-volatility relationship varies not only based on the sign of the expected returns but also upon their magnitude, according to recent results from the behavioral finance literature. We find evidence of an asymmetric and reverse return-volatility relationship in many advanced, Asian, Latin-American, European and South African markets. We show that the US market displays the highest reaction to price falls, Asian markets present the lowest sensitivity to volatility expectations, while the Euro area is characterized by a homogeneous response both in terms of direction and impact. These results may be safely attributed to cultural and societal characteristics. An extensive quantile regression analysis demonstrates that the detected asymmetric pattern varies particularly across the extreme distribution tails i.e., in the highest/lowest quantile ranges. Indeed, the classical feedback and leverage hypotheses appear not plausible, whilst behavioral theories emerge as the new paradigm in real-world applications.     

Aggressive reporting,investor protection and stock price informativeness: Evidence from Chinese firms

This paper investigates the impact of aggressive reporting on the ability of stock prices to inform in Chinese firms. Using both stock price synchronicity and the probability of informed trading as proxies for stock price informativeness, we find that aggressive reporting damages the ability of stock prices to inform in Chinese firms. Our findings are robust to potential endogeneity and the use of alternative aggressive-reporting measures. Finally, we find that the impact of aggressive reporting in reducing stock price informativeness is stronger in firms located in regions of weaker institutional development and in private sectors firms.