We investigate the impacts of policy and information shocks on the correlation of China’s T-bond and stock returns, using originally the asymmetric dynamic conditional correlation (DCC) model that allows for the coexistence of opposite-signed asymmetries. The co-movements of China’s capital markets react to large macroeconomic policy shocks as evidenced by structural breaks in the correlation following the drastic 2004 macroeconomic austerity. We show that the T-bond market and the bond–stock correlations bear more of the brunt of the macroeconomic contractions. We also find that the bond–stock correlations respond more strongly to joint negative than joint positive shocks, implying that investors tend to move both the T-bond and stock prices in the same direction when the two asset classes have been hit concurrently by bad news, but tend to shift funds from one asset class to the other when hit concurrently by good news. However, the stock–stock correlation is found to increase for joint positive shocks, indicating that investors tend to herd more for joint bullish than joint bearish stock markets in Shanghai and Shenzhen.

This paper presents evidence that information asymmetry increases equity misvaluation by showing the impact of analyst coverage on misvaluation. To establish the causality, I use two exogenous events (broker closures and mergers), as well as an instrumental variable approach. The identification strategies indicate that there is a negative causal effect of analyst coverage on equity misvalutaion. The evidence is consistent with the hypothesis that information environment can cause investors to use their perceived value in cash flow and discount rate to estimate their perceived equity prices, which deviate from intrinsic value.

This paper proposes a novel channel through which innovation externalities can affect firm performance. I find cross-sectional evidence that the positive innovation outputs of customer firms increase their supplier profitability as measured by firm ROE. This result is robust to the inclusion of industry fixed effect, a control for both supplier and customer characteristics, such as ROE, advertisement expenditure, capital expenditure, firm age, industry concentration, institutional ownership, dividend yield, and a control for industry spillover or geographical spillover. To identify the causal effect of customer innovation outputs on supplier performance, I study an exogenous shock—State Street Bank and Trust Company v. Signature Financial Group, Inc.—and find that an increase in granted customer patents causes an improvement in future supplier performance. This effect is mainly driven by the demand channel and the knowledge diffusion channel from customers to suppliers.

Speculative activity in commodity markets has increased dramatically since 2002. This paper investigates how aggregate risk aversion and risk premiums in the crude oil market covary with the level of speculation. Using crude oil futures and option data, we estimate aggregate risk aversion in the crude oil market and find that it is significantly lower between 2005 and 2008 when speculative activity increases dramatically. Risk premiums implied by the state-dependent risk aversion are also negatively correlated with speculative activity and are on average lower and more volatile during this period. These findings, together with the increased index fund and managed-money infusion in the commodity market, suggest that speculators who demand commodity futures for the purpose of portfolio diversification are willing to accept lower compensation for their positions. Decreasing speculation after 2009 amid increased producers’ hedging demand has a reverse impact on the market risk aversion and risk premiums.

This paper examines risk-taking incentives in banks under different accounting regimes in presence of capital regulation. In the model the bank jointly determines the capital issuance and investment policy. Given an exogenous minimum capital requirement, lower-of-cost-or-market accounting is the most effective regime that induces the bank to issue more excess equity capital above the minimum required level and implement less risky investment policy. However, the disciplining role of lower-of-cost-or-market accounting may discourage the bank from exerting project discovery effort ex-ante. From the regulator’s perspective, the accounting regime that maximizes the social welfare is determined by a tradeoff between the social cost of capital regulation and the efficiency of the bank’s project discovery efforts. When the former effect dominates, the regulator prefers lower-of-cost-or-market accounting; when the latter effect dominates, the regulator may prefer other regimes.

This paper investigates the determinants of the Troubled Asset Relief Program (TARP) funds distribution to banks and the stimulus effect of TARP investments on credit supply in the economy. Using banks’ political and regulatory connections as instruments, this paper finds that TARP investments increased bank loan supply by an annualized rate of 6.36% for banks with below median Tier 1 capital ratios. This increase is found in all major types of loans and can be translated into $404 billion of additional loans for all TARP banks. On average, TARP banks employed about one-third of their TARP capital to support new loans and kept the rest to strengthen their balance sheets. Furthermore, there is little evidence that loans made by TARP banks had lower quality than those by non-TARP banks. In sum, this paper shows a positive stimulus effect of TARP on credit supply during the 2008–2009 financial crisis.

The main goal of this paper is to study the cross-sectional pricing of market volatility. The paper proposes that the market return, diffusion volatility, and jump volatility are fundamental factors that change the investors’ investment opportunity set. Based on estimates of diffusion and jump volatility factors using an enriched dataset including S&P 500 index returns, index options, and VIX, the paper finds negative market prices for volatility factors in the cross-section of stock returns. The findings are consistent with risk-based interpretations of value and size premia and indicate that the value effect is mainly related to the persistent diffusion volatility factor, whereas the size effect is associated with both the diffusion volatility factor and the jump volatility factor. The paper also finds that the use of market index data alone may yield counter-intuitive results.

This paper investigates the risk-return trade-off by taking into account the model specification problem. Market volatility is modeled to have two components, one due to the diffusion risk and the other due to the jump risk. The model implies Merton’s ICAPM in the absence of leverage effects, whereas the return–volatility relations are determined by interactions between risk premia and leverage effects in the presence of leverage effects. Empirically, I find a robust negative relationship between the expected excess return and the jump volatility and a robust negative relationship between the expected excess return and the unexpected diffusion volatility. The latter provides an indirect evidence of the positive relationship between the expected excess return and the diffusion volatility.

This paper uses a variant of the consumption-based representative agent model in Campbell and Cochrane [Campbell, J.Y., Cochrane, J.H., 1999. By force of habit: Consumption-based explanation of aggregate stock market behavior. Journal of Political Economy 107, 205–251] to study how investors’ time-varying risk aversion affects asset prices. First, we show that a countercyclical variation of risk aversion drives a procyclical conditional risk premium. Second, we show that with a small value for the volatility of the log surplus consumption ratio, a large value of risk aversion may not determine whether the equity premium and the risk-free rate puzzles can be resolved or not. Third, we show that countercyclical risk aversion may not help explain the predictability of long-horizon stock returns, the univariate mean-reversion of stock prices and the “leverage effect” in return volatility.