We decompose aggregate market variance into an average correlation component and an average variance component. Only the latter commands a negative price of risk in the cross section of portfolios sorted by idiosyncratic volatility. Portfolios with high (low) idiosyncratic volatility relative to the Fama-French (1993) model have positive (negative) exposures to innovations in average stock variance and therefore lower (higher) expected returns. These two findings explain the idiosyncratic volatility puzzle of Ang et al. (2006, 2009). The factor related to innovations in average variance also reduces the pricing errors of book-to-market and momentum portfolios relative to the Fama-French (1993) model.
Time-to-build, time-to-produce, and inventory have important implications for asset prices and quantity dynamics in a general equilibrium model with recursive preferences. Time-to-build captures the delay in transforming new investments into productive capital, and time-to-produce captures the delay in transforming productive capital into output. Both delays increase risks in that time-to-build generates procyclical payouts, whereas the time-to-produce amplifies this procyclicality. Inventory smooths consumption and helps capture interest rate volatility even when the elasticity of intertemporal substitution is small. The model is consistent with a high equity premium, a high stock return volatility, and lead-lag relations between asset prices and macroeconomic quantities.
Time-preference shocks affect agents' preferences for assets with different durations. We consider longevity risk as a source of time-preference shocks and model it in the recursive preferences setting. This implies a consumption-based three-factor model, including longevity risk, consumption growth rate, and the market portfolio, where longevity has a negative price of risk. Empirically, this model explains many well-known cross-sectional portfolios. Notably, we find that longevity risk and the momentum factor share a common business cycle component, i.e., short-run consumption risks. Prior winners (losers) provide hedging against mortality (longevity) risk and thus have higher (lower) expected returns, because winners have higher dividend growth and shorter equity durations than losers. Time-varying longevity risk captures most momentum profits over time, including the large momentum crashes observed in the data.
Technology choice allows for substitution of production across states of nature and depends on state-dependent risk aversion. In equilibrium, endogenous technology choice can counter a persistent negative productivity shock with an increase in investment. An increase in risk aversion intensifies transformation across states, which directly leads to higher investment volatility. In our model and the data, the conditional volatility of investment correlates negatively with the price-dividend ratio and predicts excess stock market returns. In addition, the same mechanism generates predictability of consumption growth and produces fluctuations in the risk-free rate.
Discount rates affect stock prices directly via the discount-rate channel or indirectly via the cash-flow channel because expected future cash-flow growth varies with the discount rates. The traditional Macaulay duration captures the effect from the discount-rate channel. I propose a novel duration measure, the effective equity duration, to capture the effects from both channels. I use an event-based approach to estimate it, e.g., using unexpected policies in the federal funds rates (FOMC surprises). I find that the equity yield curve is hump-shaped because expected future cash flow growth increases with the discount rates. The effective equity duration captures information other than monetary policy risk.
We study the effects of local gender imbalance on corporate risk-taking. We find that firms in areas with a higher local male–female ratio have higher stock return volatilities, leverage ratios and capital expenditure, and less corporate hedging. Consequently, such firms face higher loan spreads, more collateral requirements and capital expenditure restrictions, and have more covenant violations. We address endogeneity concerns by using two instrumental variables for the local male-female ratio: the local prostate cancer and breast cancer mortality rates. We further show that local gender imbalance captures local residents’ risk preferences, which influence corporate policies via both local investor and employee channels.
Weather risk affects economy, agricultural production in particular. Index insurance is a promising tool to hedge against weather risk, but current piecewise-linear index insurance contracts face large basis risk and low demand. We propose embedding a neural network-based optimization scheme into an expected utility maximization problem to design the index insurance contract. Neural networks capture highly nonlinear relationship between the high-dimensional weather variables and production losses. We endogenously solve for the optimal insurance premium and demand. This approach reduces basis risk, lowers insurance premium, and improves farmers' utility.