We analyze a model in which traders have different trading opportunities and learn information from prices. The difference in trading opportunities implies that different traders may have different trading motives when trading in the same market—some trade for speculation and others for hedging—and thus they may respond to the same information in opposite directions. This implies that adding more informed traders may reduce price informativeness and therefore provides a source for learning complementarities leading to multiple equilibria and price jumps. Our model is relevant to various realistic settings and helps to understand a variety of modern financial markets.

We propose a new class of risk measures which satisfy convexity and monotonicity, two well-accepted axioms a reasonable and realistic risk measure should satisfy. Through a nonlinear weight function, the new measure can flexibly reflect the investor’s degree of risk aversion, and can control the fat-tail phenomenon of the loss distribution. A realistic portfolio selection model with typical market frictions taken into account is established based on the new measure. Real data from the Chinese stock markets and American stock markets are used for empirical comparison of the new risk measure with the expected shortfall risk measure. The in-sample and out-of-sample empirical results show that the new risk measure and the corresponding portfolio selection model can not only reflect the investor’s risk-averse attitude and the impact of different trading constraints, but can find robust optimal portfolios, which are superior to the corresponding optimal portfolios obtained under the expected shortfall risk measure.

ABSTRACT We examine the evolution of accounting regulation by linking disclosure policies and investments in a dynamic voting model. The disclosure policies are the outcome of voting by entrepreneurs, whose preferences are influenced by their investments. The investments are in turn endogenously determined by current and future disclosure policies. Absent external influences, accounting regimes are stable. A disclosure regime of high (low) quality and a strong (weak) economy coexist and reinforce each other. However, regulatory interventions can result in regime changes by changing the entrepreneurs’ expectations, even without direct enforcement. Unexpected shocks could also result in regime changes by impacting economic conditions and hence voter composition. Our analysis provides a framework to study the interaction between accounting regulation and firms’ economic decisions.

ABSTRACT This paper studies the asset pricing implications of industrial pollution. A long‐short portfolio constructed from firms with high versus low toxic emission intensity within an industry generates an average annual return of 4.42%, which remains significant after controlling for risk factors. This pollution premium cannot be explained by existing systematic risks, investor preferences, market sentiment, political connections, or corporate governance. We propose and model a new systematic risk related to environmental policy uncertainty. We use the growth in environmental litigation penalties to measure regime change risk and find that it helps price the cross section of emission portfolios' returns.

We build a general equilibrium model to examine the implications of prospect theory for the disposition effect, asset prices, and trading volume. Diminishing sensitivity predicts a disposition effect, price momentum, a reduced return volatility, and a positive return-volume correlation. Loss aversion generally predicts the opposite. In calibrated economies, there is a nontrivial range of preference parameters for prospect theory to simultaneously explain the disposition effect, the momentum effect, and the equity premium puzzle. Our model is helpful for understanding a wide range of financial phenomena and it also suggests new testable predictions.

In empirical corporate finance, firm size is commonly used as an important, fundamental firm characteristic. However, no research comprehensively assesses the sensitivity of empirical results in corporate finance to different measures of firm size. This paper fills this hole by providing empirical evidence for a “measurement effect” in the “size effect”. In particular, we examine the influences of employing different proxies (total assets, total sales, and market capitalization) of firm size in 20 prominent areas in empirical corporate finance research. We highlight several empirical implications. First, in most areas of corporate finance the coefficients of firm size measures are robust in sign and statistical significance. Second, the coefficients on regressors other than firm size often change sign and significance when different size measures are used. Unfortunately, this suggests that some previous studies are not robust to different firm size proxies. Third, the goodness of fit measured by R-squared also varies with different size measures, suggesting that some measures are more relevant than others in different situations. Fourth, different proxies capture different aspects of “firm size”, and thus have different implications. Therefore, the choice of size measures needs both theoretical and empirical justification. Finally, our empirical assessment provides guidance to empirical corporate finance researchers who must use firm size measures in their work.

The dynamic minimum variance hedge ratios (MVHRs) have been commonly estimated using the Bivariate GARCH model that overlooks the basis effect on the time-varying variance–covariance of spot and futures returns. This paper proposes an alternative specification of the BGARCH model in which the effect is incorporated for estimating MVHRs. Empirical investigation in commodity markets suggests that the basis effect is asymmetric, i.e., the positive basis has greater impact than the negative basis on the variance and covariance structure. Both in-sample and out-of-sample comparisons of the MVHR performance reveal that the model with the asymmetric effect provides greater risk reduction than the conventional models, illustrating importance of the asymmetric effect when modeling the joint dynamics of spot and futures returns and hence estimating hedging strategies.

To understand the link between financial intermediation activities and the real economy, we build a general equilibrium model in which agency frictions in the financial sector affect the efficiency of capital reallocation across firms and generate aggregate economic fluctuations. We develop a recursive policy iteration approach to fully characterize the nonlinear equilibrium dynamics and the off-steady-state crisis behavior. In our model, adverse shocks to agency frictions exacerbate capital misallocation and manifest themselves as variations in total factor productivity at the aggregate level. Our model endogenously generates countercyclical volatility in the aggregate time series and countercyclical dispersion in the marginal product of capital and asset returns in the cross-section.

This study investigates the relationship between internet penetration and venture capital (VC) investment in China. Exploiting staggered inclusion in demonstration cities under the Broadband China strategy as a positive shock to internet penetration, our difference-in-differences analysis shows that this policy shock results in an increase in VC investments in demonstration cities relative to others. Moreover, the increase in VC investments is concentrated in early stage financing and young start-ups. In terms of VC fund sources, we find a stronger effect on foreign and independent VCs. Our mechanism analysis suggests that the effect of the broadband rollout is mainly driven by cities with higher ex-ante costs of information acquisition and that such costs are reduced by the improvement of internet-based network infrastructure. Finally, we provide additional evidence on the benefits to established companies by showing that broadband rollout improves the information environment of listed firms. Our study sheds new light on the economic consequences of infrastructure development that reduces information acquisition costs in China.