Macroeconomic Risk in U.S. Equity and Fixed-Income Securities [link] 

I develop an asset pricing model in which investors form behavioral expectations on asset price movements that exhibit stochastic volatility. Investor's preferences consist of macroeconomic-driven non-Gaussian shocks that account for tail events. The one-step ahead predictive distributions of US equity and investment-grade corporate bond returns correctly capture downward spikes during the 2008 financial crisis and the COVID-19 recession. The state update distributions of risky assets provide additional information to the portfolio choice problem, generating higher risk-adjusted returns in the long run.

A Non-Parametric Jump-Diffusion Analysis of Global Equities (with Ajay Kirpekar)

Tail risk or 'Black Swan' events seldom occur and yet play a pivotal role in driving global equity returns. However, investors still remain unable to mitigate such events. After estimating two Behavioral Stochastic Volatility models using macro-financial data, we find accounting for Jump-Diffusion in the macroeconomy improves portfolio returns and reduces losses from macro-financial crises. Incorporating rare disasters produces a 1.034 Sortino ratio and downside deviation of 8.87%, while the next best strategy yields a 0.747 Sortino ratio and downside deviation of 8.97%. Generating predictive distributions via mixture modeling better characterizes risk than traditional approaches.

Equity Premium Under Non-optimal Consumption: A Second-Order Approximation

I take a partial equilibrium model (Anderson, 2021) that allows for non-optimal consumption choice and use a second-order approximation of the discount factor to analyze equity risk premia. The second-order approximation incorporates second-order moments of innovations to the consumption stream as additional risk factors. Although the macro-finance literature considers aggregate consumption to be not volatile enough, when agents worry about fluctuations to consumption in the next 6 quarters or less, second-order and first-order moments of innovations to the consumption stream contribute almost equally to equity premium. When agents account for a long horizon of future shocks to consumption growth and expected returns, the new components become relatively more significant as the level of risk aversion increases. I also empirically show that accounting for the new components helps reduce the pricing errors of the model.

Rare Disasters and Asset Pricing in A Macroeconomic Model

I introduce a rare disaster term to technology in a simple New Keynesian model and show that the model can explain a variety of asset pricing facts with a much lower coefficient of relative risk version, including the equity premium puzzle, real and nominal risk-free term premium puzzle, and credit spread puzzle. When a rare disaster shock indirectly hits total output through capital, labor increases temporarily, causing a smaller increase in equity premium compared to when an equally destructive shock hits total output directly.