Behavioral theories predict that firm valuation dispersion in the cross-section (‘‘dispersion’’) measures aggregate overpricing caused by investor overconfidence and should be negatively related to expected aggregate returns. This paper develops and tests these hypotheses. Consistent with the model predic- tions, I find that measures of dispersion are positively related to aggregate valuations, trading volume, idiosyncratic volatility, past market returns, and current and future investor sentiment indexes. Disper- sion is a strong negative predictor of subsequent short- and long-term market excess returns. Market beta is positively related to stock returns when the beginning-of-period dispersion is low and this rela- tionship reverses when initial dispersion is high. A simple forecast model based on dispersion signifi- cantly outperforms a naive model based on historical equity premium in out-of-sample tests and the predictability is stronger in economic downturns.

We propose a novel measure, DOT, to capture belief divergence on extreme tail events in stock returns. Defined as the standard deviation of expected probability forecasts generated by distinct information processing functions and neural network models, DOT exhibits significant predictive power for future stock returns. A value-weighted (equal-weighted) long-short portfolio based on DOT yields an average return of -1.07% (-0.98%) per month. Furthermore, we document novel evidence supporting a risk-sharing channel underlying the negative relation between DOT and the equity premium following extreme negative shocks. Finally, our findings are also in line with a mispricing channel in normal periods.

Using a proprietary granular database of a major Chinese stock exchange, we examine heterogenous investors’ trading dynamics around one of the most important macro announcements of the Chinese central bank, the monthly release of monetary aggregates data. Exploiting the trading heterogeneity across assets and across investor types, we find that before announcements, institutional investors reduce their aggregate stock exposure while over-weighing riskier stocks of smaller caps, whereas retail investors provide liquidity by increasing their aggregate stock exposure and avoiding the riskier stocks. Large retail and institutional investors become more informed before announcements and trade in correct directions consistent with the news surprises after announcements, while smaller retail investors trade in opposite directions. While the institutional investors accumulate positive returns with risk compensated, the market realizes sizable pre-announcement equity premium.

Using a proprietary granular database of a major Chinese stock exchange, we examine heterogenous investors’ trading dynamics around one of the most important macro announcements of the Chinese central bank, the monthly release of monetary aggregates data. Exploiting the trading heterogeneity across assets and across investor types, we find that before announcements, institutional investors reduce their aggregate stock exposure while over-weighing riskier stocks of smaller caps, whereas retail investors provide liquidity by increasing their aggregate stock exposure and avoiding the riskier stocks. Large retail and institutional investors become more informed before announcements and trade in correct directions consistent with the news surprises after announcements, while smaller retail investors trade in opposite directions. While the institutional investors accumulate positive returns with risk compensated, the market realizes sizable pre-announcement equity premium.

Using a proprietary database of stock transactions in China, we document significant trading disparities between retail and institutional investors around important macro announcements. These disparities are driven by differences in information positions. We find that before the monthly releases of China’s key monetary aggregates data, institutional investors reduce their stock exposure and shift towards riskier, smaller-cap stocks. In contrast, retail investors increase their stock exposure and avoid riskier stocks. The risk positions of institutional investors are compensated by the pre-announcement premium in smaller stocks. Following the announcements, institutional investors trade in line with news surprises, contributing to price discovery and reinforcing monetary policy transmission into asset prices. Our findings have implications for understanding announcement-related equity premium and for evaluating the general efficiency of stock market in China.

There is mixed evidence of a positive relationship between the stock market risk and return. We reexamine this critical implication of asset pricing theory using fresh data from China's stock market, which is largely segmented from the rest of the global financial market. Using formal variable selection methods and a comprehensive set of predictor variables, we identify conditional market variance, scaled market prices, and inflation as crucial determinants of equity premiums. The estimated simple risk-return relationship exhibits downward omitted variable bias, which underlines the importance of considering multiple factors to explain the variation in equity premiums. We cannot wholly attribute the three-factor conditional equity premium model to data mining, as Guo, Sanni, and Yu (2022) select the same model for the U.S. stock market. These findings challenge existing asset pricing models and provide valuable guidance for future theoretical research.

The equity premium puzzle, properly termed the American Equity Premium Puzzle, is one of the most significant empirical anomalies in finance, as it pertains to the observation that the expected return on equities has been consistently higher than that of bonds for many years, and that this premium is excessive. This paper presents one answer to the Equity Premium Puzzle, viz., the Disruptive Dependency Theory. The Disruptive Dependency Theory states that the world can be viewed in terms of “core” and “periphery” nations. Thus, there is a "core" set of nations in the world that are strong and a "periphery" that is relatively weak. This has been the state of the world since the end of the Second World War. The nations in the "core" are the strong nations. This includes the United States, China, Russia, France and the United Kingdom. What constitutes the "periphery" is a bit nebulous, but certainly the weakest nations such as island nations (Vanuatu, Togo, Jamaica, Antigua & Barbuda) belong the periphery. The nations in the core use the following to exert their influence on the nations in the periphery: (a) political strategies; (b) economic strategies; (c) social and cultural strategies; (d) technological strategies. Disruptive innovation has emerged as one of the chief strategies. With the rise of disruptive innovation, they are able to "disrupt" existing business in a very large number of periphery nations, thereby a very small number of individuals are becoming super-rich billionaires while the rest of the world remains still quite poor. According to this theory, it is the power differential of nations that historically resulted in the equity premium for stocks being excessively high. This paper explores the implications of the Disruptive Dependency Theory and its potential contribution to understanding the Equity Premium Puzzle.

We extend the ex-ante mean-variance (SVIX) asset pricing models of Martin (2017) and Martin-Wagner (2019) to a mean-variance-asymmetry (AVIX) framework by incorporating higher-moment and co-moment risk in asset pricing. Our proposed AVIX model is risk-neutral with left-tail asymmetries in returns to correct the SVIX approach's downside bias. We derive an option implied market beta of a stock as the weighted average of the betas of SVIX and AVIX. Empirically, the implied beta has significant predictability of risk/return relationship We develop an investible portfolio (MKT*) that mimics realized outcomes on the implied market index adjusted for volatility asymmetry.

This paper investigates the intertemporal relation between expected aggregate stock market returns and conditional variance considering periodic trading breaks. We propose a modified version of Merton’s intertemporal asset pricing model that merges two different processes driving asset prices, (i) a continuous process modeling diffusive risk during the trading day and, (ii) a discontinuous process modeling overnight price changes of random magnitude. Relying on high-frequency data, we estimate distinct premia for diffusive trading volatility and volatility induced by overnight jumps. While diffusive trading volatility plays a minor role in explaining the expected market risk premium, overnight jumps carry a significant risk premium and establish a positive risk-return trade-off. Our study thereby contributes to the ongoing debate on the sign of the intertemporal risk-return relation.

This paper investigates the trading behavior of ambiguity-loving investors and the corresponding impacts on asset price. The ambiguity-loving attitude increases investors' willingness to participate in the risky asset market. Their rising participation gradually crowds out ambiguity-averse and sophisticated investors, extending their nonparticipation region. When the market supply is small, the discontinuous and non-unique properties of ambiguity-loving investors' demand mapping can cause flat ranges in the equilibrium price. When the market supply is moderate or large, an increase in the fraction of ambiguity-loving investors or ambiguity level reduces equity premium. We find the effect of ambiguity-loving attitudes remains with short-sales constraints except for ambiguity-loving investors' positions and the equity premium. Their positions shrink, and equity premium decreases when the market supply is small. Besides, the rising fraction of ambiguity-level investors and ambiguity level increases equity premium when ambiguity-loving investors with heterogenous opinions only sell the risky asset.