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.     

Applications of a multivariate Hawkes process to joint modeling of sentiment and market return events

To investigate the complex interactions between market events and investor sentiment, we employ a multivariate Hawkes process to evaluate dynamic effects among four types of distinct events: positive returns, negative returns, positive sentiment, and negative sentiment. Using both intraday S&P 500 return data and Thomson Reuters News sentiment data from 2008 to 2014, we find: (a) self-excitation is strong for all four types of events at 15 min time scale; (b) there is a significant mutual-excitation between positive returns and positive sentiment and negative returns and negative sentiment; (c) decay of return events is almost twice as fast as sentiment events, which means market prices move faster than investor sentiment changes; (d) positive sentiment shocks tend to generate negative price jumps; and (e) the cross-excitation between positive and negative sentiments is stronger than their self-excitation. These findings provide further understanding of investor sentiment and its intricate interactions with market returns.     

Treasury return predictability and investor sentiment

We document that the Treasury market investor sentiment (TSENT) of institutional investors is a powerful predictor of bond risk premia. Specifically, TSENT positively predicts Treasury bond excess returns in and out of sample. The forecasting gains of TSENT are incremental to those in conventional bond return predictors: Fama–Bliss forward spreads, Cochrane–Piazzesi forward rate factor, and Ludvigson–Ng macro factor, as well as equity market sentiment proxies such as the investor sentiment index and the partial least squares sentiment index. Asset allocation analysis indicates the forecasting power of TSENT is economically valuable to investors. Finally, we show that the time-series bond risk premia predictability associated with TSENT relates to its predictive power for macroeconomic performance, such as payroll employment, unemployment rate, and industrial production.     

Dispersion in news sentiment and corporate bond returns

We construct a news sentiment index at the firm level by using textual analysis of news articles and find that dispersion in news sentiment is a significant predictor of corporate bond returns. Bonds of firms with high dispersion in news sentiment have a highly significant average return of 7.38 percent. A portfolio that longs bonds with high dispersion in news sentiments and shorts bonds with low dispersion earns an average biweekly return of 8.53 percent. This finding is in line with an argument that dispersion in news sentiment is a proxy for future cash flow uncertainty.     

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.     

The systematic pricing of market sentiment shock

ABSTRACT

We show that market sentiment shocks create demand shocks for risky assets and a systematic risk for assets. We measure a market sentiment shock as the unexpected portion of the University of Michigan Consumer Sentiment Index’s growth. This shock prices stock returns in arbitrage pricing theory framework at 1% after controlling for market, size, value, momentum, and liquidity risk factors. Its premium lowered the implied risk aversion by 97.9% to 11.46 between 1978 and 2009 in our sentiment consumption-based capital-asset-pricing model. Merton’s [1973. “An Intertemporal Capital Asset Pricing Model.” Econometrica 41: 867–887]. intertemporal capital-asset-pricing model reconfirms our finding that this market sentiment shock is a systematic risk factor that provides investment opportunities.     

International stock return predictability

We propose a new methodology for predicting international stock returns. Our Bayesian framework performs probabilistic selection of predictors that can shift at multiple unknown structural break dates. The approach generates significantly more accurate forecasts of international stock returns than a range of popular models that are economically meaningful for a risk-averse mean–variance investor. Allowing for regime-specific variable selection reduces considerably the international diversification of an unhedged U.S. investor’s portfolio.     

The short of it: Investor sentiment and anomalies

This study explores the role of investor sentiment in a broad set of anomalies in cross-sectional stock returns. We consider a setting in which the presence of market-wide sentiment is combined with the argument that overpricing should be more prevalent than underpricing, due to short-sale impediments. Long-short strategies that exploit the anomalies exhibit profits consistent with this setting. First, each anomaly is stronger (its long-short strategy is more profitable) following high levels of sentiment. Second, the short leg of each strategy is more profitable following high sentiment. Finally, sentiment exhibits no relation to returns on the long legs of the strategies.     

Credit conditions and stock return predictability

U.S. stock return predictability is analyzed using a measure of credit standards (Standards) derived from the Federal Reserve Board׳s Senior Loan Officer Opinion Survey on Bank Lending Practices. Standards is a strong predictor of stock returns at a business cycle frequency, especially in the post-1990 data period. Empirically, a tightening of Standards predicts lower future stock returns. Standards performs well both in-sample and out-of-sample and is robust to a host of consistency checks. Standards captures stock return predictability at a business cycle frequency and is driven primarily by the ability of Standards to predict cash flow news.     

Consumer expectations and short-horizon return predictability

Lettau and Ludvigson [Lettau, M., Ludvigson, S, 2001. Consumption, aggregate wealth and expected stock returns. Journal of Finance 56, 815–849] argue that fluctuations from the equilibrium ratio of consumption to wealth (cây) reflect changing expectations of asset returns and document significant short-horizon predictability based on cây. This paper further explores the role of consumer expectations in modeling time variation of expected equity returns by considering two measures of consumer expectations: (i) consumer behavior as reflected in cây, and (ii) a more-direct measure of expectations captured by the Index of Consumer Sentiment (ICS). We report strong regression-based evidence of return predictability based on cây, which remains evident even after accounting for various sources of estimation risk. However, the regression-based evidence of predictability does not necessarily imply that shifts in aggregate consumption and the components of aggregate wealth give rise to economically significant investment signals. The survey-based measure of expectations (ICS) is shown to complement the behavioral measure (cây) but has no apparent stand-alone predictive value in forecasting equity returns.     

Stock return predictability and model uncertainty

We use Bayesian model averaging to analyze the sample evidence on return predictability in the presence of model uncertainty. The analysis reveals in-sample and out-of-sample predictability, and shows that the out-of-sample performance of the Bayesian approach is superior to that of model selection criteria. We find that term and market premia are robust predictors. Moreover, small-cap value stocks appear more predictable than large-cap growth stocks. We also investigate the implications of model uncertainty from investment management perspectives. We show that model uncertainty is more important than estimation risk, and investors who discard model uncertainty face large utility losses.     

Four centuries of return predictability

We combine annual stock market data for the most important equity markets of the last four centuries: the Netherlands and UK (1629–1812), UK (1813–1870), and US (1871–2015). We show that dividend yields are stationary and consistently forecast returns. The documented predictability holds for annual and multi-annual horizons and works both in- and out-of-sample, providing strong evidence that expected returns in stock markets are time-varying. In part, this variation is related to the business cycle, with expected returns increasing in recessions. We also find that, except for the period after 1945, dividend yields predict dividend growth rates.     

Tournament-based incentives and media sentiment

We find that promotion-based tournament incentives of executives are positively associated with firms’ media sentiment. This effect is more pronounced among firms with greater need for media favourability, captured by higher information opacity, lower analyst coverage, lower industry homogeneity, lower investment sentiment and lower managerial ability. Furthermore, we identify better financial performance and higher corporate branding as two channels through which tournament incentives can enhance a firm’s positive media sentiment. Our results are also robust to two quasi-natural experiments affecting promotion-based tournaments – (a) an exogenous CEO turnover due to health issues or sudden CEO death, and (b) the implementation of Say-on-Pay (SOP) law. Overall, our findings indicate that tournament-based incentives encourage a firm’s executives to showcase their skills to broader stakeholders, which consequently increases a firm’s media image.     

Investor sentiment and economic forces

Economic theory suggests that pervasive factors should be priced in the cross-section of stock returns. However, our evidence shows that portfolios with higher risk exposure do not earn higher returns. More importantly, our evidence shows a striking two-regime pattern for all 10 macro-related factors: high-risk portfolios earn significantly higher returns than low-risk portfolios following low-sentiment periods, whereas the exact opposite occurs following high-sentiment periods. These findings are consistent with a setting in which market-wide sentiment is combined with short-sale impediments and sentiment-driven investors undermine the traditional risk-return tradeoff, especially during high-sentiment periods.     

Political sentiment and corporate social responsibility

This paper examines the association between firm-level political sentiment and corporate social responsibility (CSR). Drawing inferences from signaling and resource-based theory, we posit a positive relationship between political sentiment and CSR. Using 23,160 firm-year observations of US public firms between 2002 and 2018 as our sample, we find empirical support for our prediction. In addition, the positive relationship between political sentiment and CSR is driven by the environment, community relations, employee relations, and diversity dimensions of CSR activities. We find consistent evidence when we measure CSR using some ‘real effect’ variables. Our cross-sectional analyses reveal that the positive association between political sentiment and CSR is more evident for firms that have a high level of information asymmetry and firms that are large, mature, and active in political lobbying. Our findings remain robust to a batch of sensitivity and endogeneity tests. Overall, our findings advance the literature by highlighting the interplay between politics and firms in an ever-changing political environment.     

Style investing,comovement and return predictability

Barberis and Shleifer (2003) argue that style investing generates momentum and reversals in style and individual asset returns, as well as comovement between individual assets and their styles. Consistent with these predictions, in some specifications, past style returns help explain future stock returns after controlling for size, book-to-market and past stock returns. We also use comovement to identify style investing and assess its impact on momentum. High comovement momentum portfolios have significantly higher future returns than low comovement momentum portfolios. Overall, our results suggest that style investing plays a role in the predictability of asset returns.     

Investor sentiment and the underperformance of technology firms initial public offerings

This research examines the effect of individual and institutional investor sentiment toward the overall market at the time of Initial Public Offering (IPO) on the aftermarket performance of technology IPO shares. The study which is based on 1346 U.S. technology IPOs completed between 1992 and 2009 shows that the irrational component of individual investor sentiment negatively affects shares’ aftermarket performance: the more optimistic individual investors are at the time of IPO, the lower the shares’ aftermarket return. On the other hand, the rational component of institutional investor sentiment does not affect the shares’ short-run performance, yet positively affects their long-run performance. In contrast with prior theoretical models this paper shows that investor overconfidence positively affects technology IPO shares’ aftermarket performance. The paper extends the behavioral finance literature by providing evidence on the negative role played by noise trading in affecting technology and biotechnology IPO shares performance.     

Disagreement and return predictability of stock portfolios

This paper provides evidence that portfolio disagreement measured bottom-up from individual-stock analyst forecast dispersions has a number of asset pricing implications. For the market portfolio, market disagreement mean-reverts and is negatively related to ex post expected market return. Contemporaneously, an increase in market disagreement manifests as a drop in discount rate. For book-to-market sorted portfolios, the value premium is stronger among high disagreement stocks. The underperformance by high disagreement stocks is stronger among growth stocks. Growth stocks are more sensitive to variations in disagreement relative to value stocks. These findings are consistent with asset pricing theory incorporating belief dispersion.     

European business cycles and stock return predictability

This paper finds that the European leading economic indicator, a prime business cycle indicator for the European economies published by the OECD, can strongly predict European stock returns and generate utility gains. Importantly, the predictive power of the European indicator is above and beyond that contained in the country-specific leading indicator. Furthermore, we find that the predictive power of the European indicator is stable.     

Industry return predictability,timing and profitability

This paper aims to investigate the predictability of Australian industrial stock returns. Several identified economic variables are found to contain significant predictive power over industry portfolio returns in a Bayesian dynamic forecasting model. The Bayesian updating process was also applied in an investigation of out-of-sample prediction, timing ability and the profitability of an investment strategy of industry-rotation. When the predictor variables are employed in out-of-sample analysis, the predictive power is superior to the naïve prediction. The timing ability and profitability associated with predictability are also economically significant. When the industry momentum is examined, the results show that a group-rotation strategy can enhance the portfolio performance.