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.     

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.     

Bounded rationality,anchoring-and-adjustment sentiment,and asset pricing

This paper presents a framework that incorporates an investor’s limited attention and anchoring and adjustment sentiment and their joint effects on asset pricing, with endogenous cost of neglecting part of the dividends and the asymmetric rationality levels of investors. We find that the combined effect of the two bounded rationality factors is often embodied in the “loss”, and the retail investors are insensitive to market sentiment and forced to pay more cognitive loss. A higher level of investor rationality and bullish market sentiment will jointly increase demand and then prices, while the effects of different bounded rationality factors are asymmetric.     

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.     

The saving,human wealth and asset pricing nexus: Evidence from around the world

The present study examines the dynamics of the saving, human wealth and asset pricing nexus across developed and emerging economies. We introduce two equilibrium asset pricing models in an intertemporal capital asset pricing framework, including the priced factors human wealth and market portfolio in the first framework and the saving and market portfolio in the second framework. Both asset pricing frameworks consist of two-factor, four-factor and five-factor asset pricing models. We control for size and value factors in the four-factor model and size, value and momentum factors in the five-factor model. The IV-GMM estimation and GRS test results indicate that human wealth and market portfolio for the first framework and saving and market portfolio in the second framework are primary priced factors in explaining the average returns for developed economies and the aggregate level. On the contrary, both frameworks fail to yield significant results explaining the average returns for emerging economies.     

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.     

Asset pricing for inefficient markets: Evidence from China and India

Over last four decades, evidence of market inefficiencies has been widely documented by several scholars for all major stock markets in the globe. Chinese and Indian markets are not exempt. Inefficiencies in these markets are described by many authors as roots of all mispricing. Mispricing might be the outcome of application of familiar asset pricing models which may mislead an investor into adopting inappropriate policies for his new investments or for reallocating his old investments. In an alternative approach, we propose a transformation on original market returns in the objective of relaxing the strong assumption of market efficiency behind application of an asset pricing model. This modification will widen the scope of rational models on asset pricing ranging from an efficient to an inefficient market.     

Cross-industry asset allocation with the spatial interaction on multiple risk transmission channels

Taking into consideration the real link and information risk transmission channels, we used a spatial econometric approach to construct an economic distance-based spatial weight matrix, which can capture the spatial interaction across industries, and built a return estimation model with spatial interaction using the matrix. On this basis, we derived the covariance matrix and constructed the cross-industry asset allocation model. The empirical results showed that 1) the spatial interaction has a strong explanatory power to return and integrating the spatial interaction on multiple risk transmission channels can improve the effectiveness of the return estimation model; 2) the covariance matrix includes unsystematic risk (idiosyncratic risk) and systematic risk (market risk and cross-industry spillover risk); 3) the asset allocation model with spatial interaction can improve the performance of the portfolio and provide a valuable reference for investors' risk management and investment decision.     

The pricing accuracy of alternative equity valuation models: Scandinavian evidence

In many decision contexts, there is a need for benchmark equity valuations, based on simplified modeling and publicly available information. Prior research on U.S. data however shows that the accuracy of such valuation models can be low and sensitive to the choice of model specifications and value driver predictions. In this paper, we test the applicability and pricing accuracy of three fundamental valuation (dividend discount, residual income, and abnormal earnings growth) models, all based on forecasts of company dividends, earnings, and/or equity book values. Extending prior research, we apply these models to Scandinavian firms with accounting data from the period 2005–2014, explicitly testing two approaches for the prediction of the value drivers—exogenously forecasted numbers versus projected historical numbers. Given access to the forecasted value drivers, the dividend discount model comes out as the most accurate valuation model. In particular, this holds in a comparison between the most parsimonious model specifications. The residual income valuation model generates the best pricing accuracy given the prediction of value drivers based on historical financial numbers. Notably, we observe pricing errors that in general are lower than what has been reported in prior U.S.‐based research for the dividend discount and the residual income valuation models. The pricing accuracy of the abnormal earnings growth models is surprisingly weak in the Scandinavian setting. However, these models improve somewhat after a couple of complexity adjustments, in particular with value driver predictions based on the projected history setting.     

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.     

Liquidity and asset pricing: Evidence from the Chinese stock markets

We introduce a novel two-factor model, incorporating market and liquidity factors, which outperforms the CAPM and Fama–French factor models when applied to stock market returns in Shanghai and Shenzhen over 2000–2019. We compute the liquidity factor as the return on a liquidity-mimicking portfolio, which we construct simultaneously using two measures of liquidity (one of them capturing liquidity’s trading-quantity dimension, and the other associated with its price-impact dimension). Unlike the CAPM and Fama–French factor models, the advocated two-factor model is able to account for numerous return anomalies, such as size, book-to-market ratio, earnings-to-price ratio, cash-flow-to-price ratio, return-on-equity, and volatility. The model’s performance is similar when applied separately to the Shanghai and Shenzhen stock markets. Furthermore, it fares similarly over the 1994–2004 and 2005–2019 sub-periods. This result is somewhat surprising, because liquidity seems likely to have been substantially lower over 1994–2004, as the Chinese markets were noticeably smaller, and the critical market reform aimed at eliminating non-tradable shares by the end of 2006 did not occur until 2005.     

Systemic risk of Chinese financial institutions and asset price bubbles

Although there has not been a large-scale systemic crisis in China, high-risk financial events have occurred continuously in recent years. This research thus creatively analyzes the determinants of systemic risk for Chinese financial institutions from the view of asset price bubbles. First, we identify bubbles in the China stock and real estate markets on the basis of the generalized sup Augmented Dickey-Fuller (GSADF) model and explain the reasons for bubble formations according to the stage of China's economic development and policies implementation. At this stage, considering the differences in economic development levels of different cities, the real estate bubbles in the first, second and third tier cities and the whole country were innovatively identified. Second, on the basis of the DCG-GARCH-CoVaR model to measure the systemic risk of listed financial institutions in China and to classify institutions, the results show that the main source of such risk is the banking sector. Furthermore, by constructing regression models, stock market bubbles and real estate bubbles both positively correlate with systemic risk throughout the sample period. Meanwhile, the impact of bubbles on the systemic risk of different types of financial institutions was taken into account so that regulators prioritized different types of institutions with different characteristics when faced with decisions. Finally, we provide macro-prudential policy advice to regulators in order to weaken the impact of bubbles on financial stability to avoid systemic crises.     

Measure preserving derivatives and the pricing kernel puzzle

Recent empirical studies have found evidence of nonmonotonicity in the pricing kernels for a variety of market indices. This phenomenon is known as the pricing kernel puzzle. The payoff distribution pricing model of Dybvig predicts that the payoff distribution of a direct investment of $1 in a market index may be replicated by investing less than $1 in some derivative written on that market index whenever the associated pricing kernel is nondecreasing. Using the Hardy–Littlewood rearrangement inequality, we obtain an explicit solution for the cheapest replicating derivative, which we refer to as the optimal measure preserving derivative. The optimal measure preserving derivative is the permutation appearing in Ryff’s decomposition of the pricing kernel with respect to the market payoff measure. We compute optimal measure preserving derivatives corresponding to the estimated physical and risk neutral distributions in the paper by Jackwerth (2000) that first brought attention to the pricing kernel puzzle.     

Impact of investor’s varying risk aversion on the dynamics of asset price fluctuations

While investors’ responses to price changes and their price forecast have been identified as one of the major factors contributing to large price fluctuations in financial markets, our study shows that investors’ heterogeneous and dynamic risk aversion (DRA) preferences may play a more critical role in understanding the dynamics of asset price fluctuations. We allow an agent specific and time-dependent risk aversion index in a popular power utility function with constant relative risk aversion to construct our DRA model in which we made two key contributions. We developed an approximated closed-form price setting equation, providing a necessary framework for exploring the impact of various agents’ behaviors on the price dynamics. The dynamics of each agent’s risk aversion index is modeled by a bounded random walk with a constant variance, and such dynamics is incorporated in the price formula to form our DRA model. We show numerically that our model reproduces most of the “stylized” facts observed in the real data, suggesting that dynamic risk aversion is an important mechanism for understanding the dynamics of the financial market and the resultant financial time series.     

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.     

Risk aversion and the elasticity of substitution in general dynamic portfolio theory: Consistent planning by forward looking, expected utility maximizing investors

Using the measure of risk aversion suggested by Kihlstrom and Mirman [Kihlstrom, R., Mirman, L., 1974. Risk aversion with many commodities. Journal of Economic Theory 8, 361–388; Kihlstrom, R., Mirman, L., 1981. Constant, increasing and decreasing risk aversion with many commodities. Review of Economic Studies 48, 271–280], we propose a dynamic consumption-savings–portfolio choice model in which the consumer-investor maximizes the expected value of a non-additively separable utility function of current and future consumption. Preferences for consumption streams are CES and the elasticity of substitution can be chosen independently of the risk aversion measure. The additively separable case is a special case. Because choices are not dynamically consistent, we follow the “consistent planning” approach of Strotz [Strotz, R., 1956. Myopia and inconsistency in dynamic utility maximization. Review of Economic Studies 23, 165–180] and also interpret our analysis from the game theoretic perspective taken by Peleg and Yaari [Peleg, B., Yaari, M., 1973. On the existence of a consistent course of action when tastes are changing. Review of Economic Studies 40, 391–401]. The equilibrium of the Lucas asset pricing model with i.i.d. consumption growth is obtained and the equity premium is shown to depend on the elasticity of substitution as well as the risk aversion measure. The nature of the dependence is examined. Our results are contrasted with those of the non-expected utility recursive approach of Epstein–Zin and Weil.     

Forecasting volatility: A reality check based on option pricing, utility function, value-at-risk, and predictive likelihood

We analyze the predictive performance of various volatility models for stock returns. To compare their performance, we choose loss functions for which volatility estimation is of paramount importance. We deal with two economic loss functions (an option pricing function and an utility function) and two statistical loss functions (a goodness-of-fit measure for a value-at-risk (VaR) calculation and a predictive likelihood function). We implement the tests for superior predictive ability of White [Econometrica 68 (5) (2000) 1097] and Hansen [Hansen, P. R. (2001). An unbiased and powerful test for superior predictive ability. Brown University]. We find that, for option pricing, simple models like the Riskmetrics exponentially weighted moving average (EWMA) or a simple moving average, which do not require estimation, perform as well as other more sophisticated specifications. For a utility-based loss function, an asymmetric quadratic GARCH seems to dominate, and this result is robust to different degrees of risk aversion. For a VaR-based loss function, a stochastic volatility model is preferred. Interestingly, the Riskmetrics EWMA model, proposed to calculate VaR, seems to be the worst performer. For the predictive likelihood-based loss function, modeling the conditional standard deviation instead of the variance seems to be a dominant modeling strategy.     

On revenue recycling and the welfare effects of second-best congestion pricing in a monocentric city

This paper examines congestion taxes in a monocentric city with pre-existing labor taxation. When road toll revenue is used to finance labor tax cuts, 35% of the optimal road tax in our numerical model does not reflect marginal external congestion costs, but rather functions as a Ramsey–Mirrlees tax, i.e. an efficiency enhancing mechanism allowing for an indirect spatial differentiation of the labor tax. This adds a quite different motivation to road pricing, since welfare gains can be produced even in absence of congestion. We find that the optimal road tax is non-monotonic across space, reflecting the different impacts of labor supply elasticity and marginal utility of income, which both vary over space. The relative efficiencies of some archetype second-best pricing schemes (cordon toll, flat kilometer tax) are high (84% and 70% respectively). When road toll revenue is recycled lump-sum, the optimal toll lies below its Pigouvian level. Extensions in a bimodal framework show that the optimality of using road toll revenue to subsidize public transport depends on the initial inefficiency in public transport pricing.