Investor sentiment and the risk–return relation: A two-in-one approach

Traditional finance theory posits a positive risk–return relation, but empirical evidence is inconclusive. Retail investor sentiment has long been viewed as a distorting factor, while more recently institutional investor sentiment is thought to play a role. We examine the separate and joint impacts of retail and institutional investor sentiments on the risk-return relation. We find, at both market and firm levels, the risk-return relation is more likely to be distorted by the two investor-type sentiments jointly, rather than separately. We further find a cross-sectional pattern, with the risk-return relation being more sensitive to investor sentiment for stocks with specific characteristics.     

Dynamic mean–variance problem with frictions

Finance and Stochastics - We study a dynamic mean–variance portfolio selection problem with return predictability and trading frictions from price impact. Applying mean-field type control...     

“Investor sentiment” and the closed-end fund puzzle: A 7 percent solution

Lee, Shleifer, and Thaler (1991) argue that the irrational noise trader model of DeLong, Shleifer, Summers, and Waldmann (1990) ... is consistent with the published evidence on closed-end fund prices. ... However, Lee, Shleifer, and Thaler provide no indication of how much of the variability of a closed-end fund's discounts and premiums is due to such investor sentiment. Using the signal extraction technique of French and Roll (1986) to measure noise, this article estimates that on average only 7 percent of the variance of a standardized measure of weekly changes in discounts and premiums can be attributed to noise-trading activity. Investor sentiment, therefore, seems to account for very little of a closed-end fund's discount and premium variability over time.     

Mean–variance and mean–semivariance portfolio selection: a multivariate nonparametric approach

While univariate nonparametric estimation methods have been developed for estimating returns in mean-downside risk portfolio optimization, the problem of handling possible cross-correlations in a vector of asset returns has not been addressed in portfolio selection. We present a novel multivariate nonparametric portfolio optimization procedure using kernel-based estimators of the conditional mean and the conditional median. The method accounts for the covariance structure information from the full set of returns. We also provide two computational algorithms to implement the estimators. Via the analysis of 24 French stock market returns, we evaluate the in-sample and out-of-sample performance of both portfolio selection algorithms against optimal portfolios selected by classical and univariate nonparametric methods for three highly different time periods and different levels of expected return. By allowing for cross-correlations among returns, our results suggest that the proposed multivariate nonparametric method is a useful extension of standard univariate nonparametric portfolio selection approaches.     

Predictability and the earnings–returns relation

This paper studies the effects of predictability on the earnings–returns relation for individual firms and for the aggregate. We demonstrate that prices better anticipate earnings growth at the aggregate level than at the firm level, which implies that random-walk models are inappropriate for gauging aggregate earnings expectations. Moreover, we show that the contemporaneous correlation of earnings growth and stock returns decreases with the ability to predict future earnings. Our results may therefore help explain the apparently conflicting recent evidence that the earnings–returns relation is negative at the aggregate level but positive at the firm level.     

Do IPO index portfolios improve the investment opportunities for mean–variance investors?

We set out in this study to examine whether investors can improve their investment opportunity sets through the addition of an IPO index portfolio into various sets of benchmark portfolios. Using the IPOX indices from the years 1980–2006, we find that adding an IPO index portfolio does lead to a statistically significant enlargement of the investment opportunity set for investors. Our empirical findings are robust, demonstrating that there is scope for the further development of financial products relating to IPO stocks, since investors can gain diversification benefits through investing in such IPO-related products.     

Time-consistent mean–variance asset-liability management in a regime-switching jump-diffusion market

Financial Markets and Portfolio Management - This paper investigates the time-consistent optimal control of a mean–variance asset-liability management problem in a regime-switching...     

Robust state-dependent mean–variance portfolio selection: a closed-loop approach

Finance and Stochastics - This paper studies a class of robust mean–variance portfolio selection problems with state-dependent risk aversion. Model uncertainty, in the sense of considering...     

Value-at-risk capital requirement regulation,risk taking and asset allocation: a mean–variance analysis

In this study, the mean–variance framework is employed to analyze the impact of the Basel value-at-risk (VaR) market risk regulation on the institution's optimal investment policy, the stockholders’ welfare, as well as the tendency of the institution to change the risk profile of the held portfolio. It is shown that with the VaR regulation, the institution faces a new regulated capital market line, which induces resource allocation distortion in the economy. Surprisingly, only when a riskless asset is available does VaR regulation induce the institution to reduce risk. Otherwise, the regulation may induce higher risk, accompanied by asset allocation distortion. On the positive side, the regulation implies an upper bound on the risk the institution takes and it never induces the firm to select an inefficient portfolio. Moreover, when the riskless asset is available, tightening the regulation always increases the amount of maintained eligible capital and decreases risk.     

Mean–variance convergence around the world

In this paper, we show (i) that the risk-return characteristics of our sample of 17 developed stock markets of the world have converged significantly toward each other during our study period 1974–2007, and (ii) that this international convergence in risk-return characteristics is driven mainly by the declining ‘country effect’, rather than the rising ‘industry effect’, suggesting that the convergence is associated with international market integration. Specifically, we first compute the risk-return distance among international stock markets based on the Euclidean distance and find that the distance thus computed has been decreasing significantly over time, implying a mean–variance convergence. In particular, the average risk-return distance has decreased by about 50% over our sample period. We also document that the risk-return characteristics of our sample of 14 emerging markets have been converging rapidly toward those of developed markets in recent years. This development notwithstanding, emerging markets still remain as a distinct asset class. Lastly, we show that the convergence in risk-return characteristics has exerted a negative impact on the efficiency of international investment during our sample period.     

Searching for a listed infrastructure asset class using mean–variance spanning

This study examines the portfolio-diversification benefits of listed infrastructure stocks. We employ three different definitions of listed infrastructure and tests of mean–variance spanning. The evidence shows that viewing infrastructure as an asset class is misguided. We employ different schemes of infrastructure asset selection (both traditional asset classes and factor exposures) and discover that they do not provide portfolio-diversification benefits to existing asset allocation choices. We also find that defining and selecting infrastructure investments by business model as opposed to industrial sectors can reveal a very different investment profile, albeit one that improves the mean–variance efficient frontier since the global financial crisis. This study provides new insights into defining and benchmarking infrastructure equity investments in general, as well as into the extent to which public markets can be used to proxy the risk-adjusted performance of privately held infrastructure investments.     

Time-varying betas and the cross-sectional return–risk relation: evidence from the UK

The seminal study by Fama and MacBeth in 1973 initiated a stream of papers testing for the cross-sectional relation between return and risk. The debate as to whether beta is a valid measure of risk was reanimated by Fama and French and subsequent studies. Rather than focusing on exogenous variables that have a larger explanatory power than an asset's beta in cross-sectional tests, the matrix of variances-covariances is assumed to follow a time varying ARCH process. Using monthly data from the UK market from February 1975 to December 1996, the cross-sectional return–risk relations obtained with an unconditional specification for assets’ betas are compared to those obtained when the estimated betas are based on an ARCH model. The approach taken by Pettengill, Sundaram and Mathur, which allows a negative cross sectional return–risk relation in periods in which the market portfolio yields a negative return relative to the risk free rate, was also investigated. These tests are also carried out on samples pertaining to a specific month and on samples from which a particular month is removed. Results suggest that the CAPM holds better in downward moving markets than in upward moving markets hence beta is a more appropriate measure of risk in bear markets.     

Foreign exchange,fractional cointegration and the implied–realized volatility relation

Almost all relevant literature has characterized implied volatility as a biased predictor of realized volatility. In this paper we provide new time series techniques to investigate the validity of this finding in several foreign exchange options markets, including the Euro market. First, we develop a new fractional cointegration test that is shown to be robust to both stationary and non-stationary regions. Second, we employ both intra-day and daily data to measure realized volatility in order to assess the relevance of data frequency in resolving the bias. Third, we use data on implied volatility traded on the market. In contrast to previous studies, we show that the frequency of data used for measuring realized volatility within a fractionally cointegrating framework is important for the results of unbiasedness tests. Significantly, for many popular exchange rates, the use of intra-day rather than daily data affects the emergence of a different bias, as the possibility of a fractionally integrated risk premium admits itself!     

Reactive or proactive? Investor sentiment as a driver of corporate social responsibility

Investors and financial markets have been a neglected stakeholder group in studies on a firm’s motivations to be socially and environmentally responsible. Despite being a strong driving force behind firm value, no study has investigated the influence of market and investor sentiments on CSR behaviour. Using a global sample, we investigate the effects of market and investor sentiments on firm CSR performance. We find negative market and investor sentiments in the prior year motivate firms to improve their CSR performance in the next year. We also find the magnitude of improvement in CSR performance differs not only by country, but by CSR sub-category as well. These findings imply that a firm’s motivation to improve its CSR performance is reactionary, rather than being driven by altruism. Regulators and proponents of CSR should thus seek to persuade investors and financial markets to put pressure on firms to further advance the CSR agenda.     

Financial investor sentiment and the boom/bust in oil prices during 2003–2008

From both theoretical and policy perspectives, it is important to understand if financial speculation contributes to the boom/bust in oil prices during 2003–2008. In this paper, we disentangle the effects of financial speculation from those of economic fundamentals by focusing on exogenous changes of financial speculation in oil markets identified by changes in financial investor sentiment. Furthermore, we focus on a quasi-experiment setting, and investigate both sentiment-driven overvaluation of oil prices and subsequent mispricing correction. Our findings suggest that financial speculation might have contributed to the 2003–2008 boom/bust in oil prices.     

Optimal tax policy and expected longevity: a mean and variance utility approach

This paper studies the normative problem of redistribution between agents who can influence their survival probability through private health spending, but who differ in their attitude towards the risks involved in the lotteries of life to be chosen. For that purpose, a two-period model is developed, where agents’ preferences on lotteries of life can be represented by a mean and variance utility function allowing, unlike the expected utility form, some sensitivity to what Allais (Econometrica 21(4), 503–546, 1953) calls the ‘dispersion of psychological values’. It is shown that if agents ignore the impact of health spending on the return of their savings, the decentralization of the first-best utilitarian optimum requires intergroup lump sum transfers and group-specific positive taxes on health spending. Under asymmetric information, a differentiated taxation across agents is still required, but subsidizing health spending may be optimal as a way to solve the incentive problem.     

Risk sentiment and firms’ liquidity in the French market

This paper investigates the impact of risk sentiment on market liquidity by using panel data. We use six risk word lists; uncertain, weak model, negative, legal, opportunity, and environmental & social responsibility word lists to measure the risk sentiment. Concerning the liquidity proxies, we use three measures, quoted spread, effective spread, and adverse selection component. The results indicate that an intensive risk tone and uncertain information in annual reports lead to decreased liquidity. In addition we find that risk sentiment variable impacts the liquidity but not vice versa.     

Managing the narrative: Investor relations officers and corporate disclosure✰

Investor relations officers (IROs) play a central role in corporate communications with Wall Street. We survey 610 IROs at U.S. public companies and conduct 14 follow-up interviews to deepen our understanding of the role of IROs in corporate disclosure events. Three important themes emerge from our results: (i) the value, nature, and timing of private communication between IROs, analysts, and investors; (ii) the significant influence IROs have on corporate disclosures; and (iii) the degree of “theater” involved in public earnings conference calls, even the Q&A portion. We provide insights into the investor relations, analyst, institutional investor, and disclosure literatures.     

Betting against sentiment? Seemingly unrelated anomalies and the low-risk effect

The negative CAPM alphas of high-beta and high-variance stocks are attributable to an unaccounted factor in the CAPM. We use eight seemingly unrelated anomalies to construct a composite factor in the spirit of the optimal orthogonal portfolio (FOP). Accounting for FOP re-establishes a positive relation between beta and average returns in time series regressions as well as cross-sectional and explains the negative alphas of high-beta and high-variance stocks. To analyze economic drivers behind FOP, we perform a horse race between leverage constraints, investor sentiment, and disagreement. Our results highlight investor sentiment as the most promising explanation for the low-risk effect.