Asset pricing with loss aversion

The use of standard preferences for asset pricing has not been very successful in matching asset price characteristics, such as the risk-free interest rate, equity premium and the Sharpe ratio, to time series data. Behavioral finance has recently proposed more realistic preferences such as those with loss aversion. Research is starting to explore the implications of behaviorally founded preferences for asset price characteristics. Encouraged by some studies of Benartzi and Thaler [1995. Myopic loss aversion and the equity premium puzzle. The Quarterly Journal of Economics 110 (1), 73–92] and Barberis et al. [2001. Prospect theory and asset prices. Quarterly Journal of Economics CXVI (1), 1–53] we study asset pricing with loss aversion in a production economy. Here, we employ a stochastic growth model and use a stochastic version of a dynamic programming method with an adaptive grid scheme to compute the above mentioned asset price characteristics of a model with loss aversion in preferences. As our results show using loss aversion we get considerably better results than one usually obtains from pure consumption-based asset pricing models including the habit formation variant.     

Disagreements with noisy signals and asset pricing

We consider a Lucas-type exchange economy with two trees and two investors to analyze the effects of heterogeneous beliefs and signal quality on stock market equilibrium. Our model has the following implications. There are spillover effects, in that the investors’ heterogeneous beliefs and signal quality related to one stock not only affect its own price and pricing moments, but also affect those of the other. Contrary to the conventional wisdom, we show that the volatility of one stock decreases with both its own and the other stock’s disagreements. Additionally, we reveal a negative correlation between the stocks, which decreases as the investors’ dispersions raise but increases as the discrepancy in signal quality reduces. We also show that heterogeneous beliefs and signal quality impact stock market beta mainly through scale and volatility effects, respectively. Furthermore, our findings suggest that both heterogeneous beliefs and signal quality have significant influences on the investors’ optimal portfolio plans.     

Heterogeneous beliefs with herding behaviors and asset pricing in two goods world

We construct a incomplete information equilibrium model with heterogeneous beliefs and herding behaviors to identify their joint effects on the dynamics of asset prices. Herding behaviors make investors revise some of their estimations about expected growth rates of goods streams toward to the other one’s by a manner of weighted average of their own forecast and the other’s. As we expected, herding behaviors generate influences on the Radon Nikodym derivative, that is so-called “sentiment” as in Dumas et al. (2009), and in turn not only impact the dynamics of asset prices but also generate influences on investors’ survivals. We also show that introducing heterogeneous beliefs with herding behaviors permits to explain both the Backus–Smith puzzle and the mixed results about the influences of herding behaviors on asset prices. Moreover, we uncover that herding behaviors have positive influences on stocks’ risk premiums.     

Identification and inference in two-pass asset pricing models

We introduce a framework that robustifies two-pass Fama–MacBeth regressions, in the sense that confidence regions for the ex post price of risk can be derived reliably even with weak identification. This region can be unbounded, if risk price is hard to identify, empty, if the model lacks fit, and bounded otherwise. Our framework thus provides automatic weak-identification and lack-of-fit warnings, and informative model rejections. Empirically relevant simulations document attractive size and power properties. Empirical applications with well known models and data sets illustrate practical usefulness and the potential value of additional cross-sectional information.     

Cross-sectional implications of dynamic asset pricing with stochastic volatility and ambiguity aversion

Building on recent research that highlights the importance of macroeconomic volatility and ambiguity aversion in explaining the dynamics of stock returns, in this paper we propose a dynamic asset pricing model that simultaneously accounts for stochastic macroeconomic volatility and ambiguity, assuming that investors deal with uncertainty about the mechanics of macroeconomic fluctuations using first-release consumption and revisions to aggregate consumption on vintage data. Our results show that the proposed model captures a large fraction of the cross-sectional variation of excess returns for a wide range of market anomaly portfolios. Furthermore, while the price of risk for ambiguity is positive and significant for the vast majority of assets under study, macroeconomic volatility yields ambiguous outcomes, although it significantly increases the explanatory power of the model for specific assets. Our results suggest that macroeconomic volatility and ambiguity complement each other in explaining the cross-sectional behavior of stock returns.     

Heterogenous beliefs with sentiments and asset pricing

We present a dynamic equilibrium model with two irrational investors: an extrapolator and a contrarian, whose beliefs regarding the growth rate of dividend stream are biased by their sentiments. The key contribution is to connect two disagreements with the degree of irrationality of investors and to provide novel insights into the predictability of stock return. We show that the higher level of sentiment disagreement is, the more stock price is overvalued. However, the future stock price will decline because the extrapolator’s sentiment will cool down over time. Therefore, the sentiment disagreement negatively predicts future return. At the meanwhile, our model not only shows that the survey expectations about cashflows increase the variations in asset price and dampen the corresponding volatility, but also helps to explain the mixed results about the relationship between the investors’ belief dispersions and stock return predictability.     

The sentiment pricing dynamics with short-term and long-term learning

Combining the behavioral characteristics of rational uninformed investors with learning information behavior of sentiment investors, this paper establishes a mathematical model about the impact of learning information behavior on the investor's transaction and asset equilibrium price under asymmetric information. Research shows that when rational uninformed investors learn information in the short term, on the one hand, they choose to bet against sentiment investors, thus reducing the influence of sentiment; on the other hand, they occasionally mistake sentiment for information to chase sentiment investors, then amplifying sentiment shocks. Furthermore, sentiment investors can also gain valuable information indirectly by observing the price in the long term. When sentiment investors learn information in the long term, the price fluctuations caused by sentiment and information, informativeness of the price system and market efficiency are no longer dependent on the quality of information.     

Disagreement with procyclical beliefs and asset pricing

We consider a pure exchange economy with incomplete information in which the expected growth rate of endowment is unobservable. The economy is populated by two investors, one is rational, but the other irrationally believes that the dynamics of endowment exhibit procyclical feature. Such different opinions about the dynamics of endowment process produce persistent disagreement between the investors. We show that model-implied riskfree rate is procyclical. Further, the procyclical beliefs not only explain the excess volatility puzzle, but also help to explain the mixed results about the relationship between the investors’ belief dispersions and stock return. Moreover, we uncover that the rational investor prefers to short stock positions in good times as the degree of the other investor’s irrationality increasing.     

Explicit characterizations of financial prices with history-dependent utility

The present paper demonstrates how explicit representations of financial prices and returns can be derived in economies with history-dependent utility. While the techniques are applicable to a wide range of economies, they are applied to a representative consumer economy where (i) the consumer’s preferences exhibit habit formation, and (ii) purchases of the consumption good also gives rise to a flow of services. Solutions are computed for the case of multiplicative or nonlinear habit formation, and additive service flows. Other applications are also indicated.     

Coupled projects,core imputations,and the CAPM

Projects, private or public, that share input factors or output requirements had better be construed as members of a portfolio. Present risk, the capital asset pricing model may facilitate valuation of each member. Chief results of that model are derived and generalized here as core solutions to a transferable-utility production game. Shadow prices define stochastic discount factors that determine values of individual projects. Variance aversion largely affects such prices whence optimal allocations.     

Stochastic equilibria of an asset pricing model with heterogeneous beliefs and random dividends

We investigate dynamical properties of a heterogeneous agent model with random dividends and further study the relationship between dynamical properties of the random model and those of the corresponding deterministic skeleton, which is obtained by setting the random dividends as their constant mean value. Based on our recent mathematical results, we prove the existence and stability of random fixed points as the perturbation intensity of random dividends is sufficiently small. Furthermore, we prove that the random fixed points converge almost surely to the corresponding fixed points of the deterministic skeleton as the perturbation intensity tends to zero. Moreover, simulations suggest similar behaviors in the case of more complicated attractors. Therefore, the corresponding deterministic skeleton is a good approximation of the random model with sufficiently small random perturbations of dividends. Given that dividends in real markets are generally very low, it is reasonable and significant to some extent to study the effects of heterogeneous agents’ behaviors on price fluctuations by the corresponding deterministic skeleton of the random model.     

Adverse effects of leverage and short-selling constraints in a financial market model with heterogeneous agents

This paper investigates the impact of leverage and short-selling constraints on financial market stability. Investors׳ demand is modelled in a well-known asset pricing model with heterogeneous beliefs. In particular, I generalise the heterogeneous agents model of Brock and Hommes (1998) and Anufriev and Tuinstra (2013) to allow for leverage constraints as well as a short-selling tax. I consider two examples of adaptive belief systems describing the coevolution of prices and investors׳ beliefs. First, if the market is inhabited by fundamentalist and chartist traders, demand constraints have potential adverse effects and may restrict the stabilising fundamentalist strategy such that mispricing and price volatility increase. Second, if the market is inhabited by fundamentalists, optimists and pessimists with fixed beliefs, demand constraints drive down price volatility, but mispricing remains. The results suggest the stabilising effects of demand constraints in financial markets are limited. Only if asset prices are too high compared to fundamentals, policy makers should consider constraining leverage ratios in order to deflate financial bubbles.