Asset pricing with heterogeneous beliefs and relative performance

We propose an equilibrium asset pricing model in which agents with heterogeneous beliefs care about relative performance. We find that the concern with relative performance leads agents to trade more similarly, a development that has two effects. First, similar trading directly decreases volatility. Second, similar trading decreases the impact of dominant agents. The second effect dominates the first when agents expect large differences between their final performances, and vice versa when agents expect small differences between their final performances. Compared with the case in which agents are unconcerned about relative performance, the stock return volatility is higher when the second effect dominates, and lower when the first effect dominates. This paper also demonstrates that the concern about relative performance influences investors’ holdings, stock prices and risk premia.     

From boom ‘til bust: How loss aversion affects asset prices

This article studies the impact of heterogeneous loss averse investors on asset prices. In very good states loss averse investors become gradually less risk averse as wealth rises above their reference point, pushing up equity prices. When wealth drops below the reference point the investors become risk seeking and demand for stocks increases drastically, eventually leading to a forced sell-off and stock market bust in bad states. Heterogeneity in reference points and initial wealth of the loss averse investors does not change the salient features of the equilibrium price process, such as a relatively high equity premium, high volatility and counter-cyclical changes in the equity premium.     

Preference heterogeneity and asset prices: An exact solution

We introduce a general equilibrium model of a multi-agent, pure-exchange economy and find a set of conditions that enable us to obtain explicit closed-form solutions to the equilibrium interest rate, stock price, risk premium and stock market volatility when investors have heterogenous risk aversions. Because the market is dynamically complete, full risk sharing obtains and a representative agent can be constructed, though the risk aversion of this agent fluctuates over time with the state of the economy, as the relative wealth distribution of the individual investors changes. We show that preference heterogeneity can cause asset prices to be significantly more volatile than the underlying dividends and that it can lead to leverage-like effects in volatility, in the sense that volatility increases after stock-market declines.     

The only game in town: Stock-price consequences of local bias

Theory suggests that, in the presence of local bias, the price of a stock should be decreasing in the ratio of the aggregate book value of firms in its region to the aggregate risk tolerance of investors in its region. Using data on U.S. states and Census regions, we find clear-cut support for this proposition. Most of the variation in the ratio of interest comes from differences across regions in aggregate book value per capita. Regions with low population density—e.g., the Deep South—are home to relatively few firms per capita, which leads to higher stock prices via an “only-game-in-town” effect.     

MEASURING EFFECTS ON STOCK RETURNS OF SENTIMENT INDEXES CREATED FROM STOCK MESSAGE BOARDS

Various techniques and sources of information exist to aid investors in predicting future stock returns. However, no effective proxy for retail investors, such as stock message board users, has been established. This study provides guidelines for creating an effective proxy. The heart of such proxies is sentiment indexes, and in the past the indexes have had low predictive power. Introducing four methodological improvements for applying text classifiers and two probability measurements, we contrast eight widely applied text classifiers to stock message board data. Based on the classifier results and incorporating our new methods, the new sentiment index proves to be a significant “same‐day positive but next‐day negative” directional indicator.     

The coskewness puzzle

We propose a novel approach to testing non-linear stochastic discount factor (SDF) specifications that arise in rational representative investor models. Our approach does not require overly-restrictive assumptions about the shape of investors’ preferences, typically imposed by the extant literature, and is based instead on restrictions that rule out “good deals”, i.e., arbitrage opportunities as well as unduly large Sharpe ratios. We apply this framework to test the empirical admissibility of 3 and 4-moment versions of the CAPM. We find that, while coskewness and cokurtosis risk help price a number of stock strategies and portfolios, including static strategies based on a fine industry-level diversification, momentum strategies and portfolios managed on the basis of available information, the CAPM and its 3 and 4-moment versions cannot provide an exhaustive account of observed asset returns.     

Risk aversion and skewness preference

Empirically, co-skewness of asset returns seems to explain a substantial part of the cross-sectional variation of mean return not explained by beta. This finding is typically interpreted in terms of a risk averse representative investor with a cubic utility function. This paper questions this interpretation. We show that the empirical tests fail to impose risk aversion and the implied utility function takes an inverse S-shape. Unfortunately, the first-order conditions are not sufficient to guarantee that the market portfolio is the global maximum for this utility function, and our results suggest that the market portfolio is more likely to represent the global minimum. In addition, if we do impose risk aversion, then co-skewness has minimal explanatory power.     

An empirical analysis of marginal conditional stochastic dominance

Stochastic dominance is a more general approach to expected utility maximization than the widely accepted mean–variance analysis. However, when applied to portfolios of assets, stochastic dominance rules become too complicated for meaningful empirical analysis, and, thus, its practical relevance has been difficult to establish. This paper develops a framework based on the concept of Marginal Conditional Stochastic Dominance (MCSD), introduced by Shalit and Yitzhaki (1994), to test for the first time the relationship between second order stochastic dominance (SSD) and stock returns. We find evidence that MCSD is a significant determinant of stock returns. Our results are robust with respect to the most popular pricing models.     

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 volatility,operating performance and stock returns: International evidence on drivers of the ‘low volatility’ anomaly

This study highlights the link between stock return volatility, operating performance, and stock returns. Prior studies suggest that there is a ‘low volatility’ anomaly, where firms with a low stock return volatility out-perform firms with a high stock return volatility. This paper confirms that low volatility stocks earn higher returns than high volatility stocks in emerging markets and developed markets outside of North America. We also show that low volatility stocks have higher operating returns and this might explain why low volatility stocks earn higher stock returns. These results provide a partial explanation for the ‘low volatility effect’ that is independent from the existence of market anomalies or per se inefficiencies that might otherwise drive a low volatility effect. We emphasize the importance of controlling for stock return volatility when analyzing operating performance and stock performance.     

The world price of jump and volatility risk

We study international integration of markets for jump and volatility risk, using index option data for the main global markets. To explain the cross-section of expected option returns we focus on return-based multi-factor models. For each market separately, we provide evidence that volatility and jump risk are priced risk factors. There is little evidence, however, of global unconditional pricing of these risks. We show that UK and US option markets have become increasingly interrelated, and using conditional pricing models generates some evidence of international pricing. Finally, the benefits of diversifying jump and volatility risk internationally are substantial, but declining.     

Return decomposition and the Intertemporal CAPM

The Intertemporal CAPM (ICAPM) from Merton (1973) has had a strong impact in empirical asset pricing leading to numerous multifactor models. This paper shows that the explanatory power of the ICAPM application by Campbell and Vuolteenaho (2004) relies critically on the computation of Dimson (1979) covariances (betas). If one employs the standard factor covariances (excluding lagged factors), the two-factor ICAPM has virtually no explanatory power for the average returns of the 25 size/book-to-market portfolios. More specifically, it is the covariance with the lagged innovation in one of the state variables (the value spread) that drives the explanatory power of the model. These results are inconsistent with the central economic intuition from the ICAPM. By specifying a more general version of the ICAPM, the fit of the model improves relative to the Campbell and Vuolteenaho (2004) model.     

Hedge fund portfolio construction: A comparison of static and dynamic approaches

This article studies the impact of modeling time-varying covariances/correlations of hedge fund returns in terms of hedge fund portfolio construction and risk measurement. We use a variety of static and dynamic covariance/correlation prediction models and compare the optimized portfolios’ out-of-sample performance. We find that dynamic covariance/correlation models construct portfolios with lower risk and higher out-of-sample risk-adjusted realized return. The tail-risk of the constructed portfolios is also lower. Using a mean-conditional-value-at-risk framework we show that dynamic covariance/correlation models are also successful in constructing portfolios with minimum tail-risk.     

Does investor recognition predict returns?

Merton [1987. A simple model of capital market equilibrium with incomplete information. Journal of Finance 42, 483–510] shows that stocks about which not all investors are informed should yield a return premium. This premium depends on the shadow cost of incomplete information which in turn depends on the shareholder base, relative market size, and idiosyncratic risk. Utilizing a comprehensive database of Swedish shareholdings, we demonstrate that stock returns are positively related to the shadow cost. We also find that the shareholder base is negatively related to returns when controlling for size and idiosyncratic risk. Zero-cost portfolios based on the shadow cost/shareholder base yield substantial trading profits that are never positively correlated with the market and are only modestly explained by the four-factor model.     

Using industry momentum to improve portfolio performance

Minimum-variance portfolios, which ignore the mean and focus on the (co)variances of asset returns, outperform mean–variance approaches in out-of-sample tests. Despite these promising results, minimum-variance policies fail to deliver a superior performance compared with the simple 1/N rule. In this paper, we propose a parametric portfolio policy that uses industry return momentum to improve portfolio performance. Our portfolio policies outperform a broad selection of established portfolio strategies in terms of Sharpe ratio and certainty equivalent returns. The proposed policies are particularly suitable for investors because portfolio turnover is only moderately increased compared to standard minimum-variance portfolios.     

Dividend distributions and closed-end fund discounts

Empirical support for the hypothesis that closed-end fund discounts are related to overhanging tax liabilities has been mixed. We introduce a new approach to testing this hypothesis by examining changes in discount levels following distributions of dividends and capital gains. Since distributions reduce future shareholder tax liabilities, the tax liability hypothesis implies that closed-end fund discounts should decline following distributions. Focusing on changes in discounts isolates this tax effect by eliminating the impact of other fund-specific factors on discount levels. Our results support the tax liability hypothesis, showing that short-run fluctuations in discounts are directly affected by taxable distributions.     

Performance Evaluation Of U.K. Unit Trusts Within The Stochastic Discount Factor Framework

We examine the performance of U.K. unit trusts between January 1982 and December 1996 within the stochastic discount factor approach across a wide class of models. No one model dominates the others in correctly pricing passive portfolios or detecting superior performance for hypothetical trading strategies. We find no evidence of significant superior performance by the unit trusts for any model of the stochastic discount factor. Also, the charges of the trust have a mixed effect on trust performance.