We estimate a continuous-time model with stochastic volatility and dynamic crash probability for the S&P 500 index and find that market illiquidity dominates other factors in explaining the stock market crash risk. While the crash probability is time-varying, its dynamic depends only weakly on...

We decompose total variance into its bad and good components and measure the premia associated with their fluctuations using stock and option data from a large cross-section of firms. The total variance risk premium (VRP) represents the premium paid to insure against fluctuations in bad variance...

This paper provides a novel methodology for estimating option pricing models based on risk-neutral moments. We synthesize the distribution extracted from a panel of option prices and exploit linear relationships between risk-neutral cumulants and latent factors within the continuous time affine...

Advances in variance analysis permit the splitting of the total quadratic variation of a jump diffusion process into upside and downside components. Recent studies establish that this decomposition enhances volatility predictions, and highlight the upside/downside variance spread as a driver of...

We introduce generalized autoregressive gamma (GARG) processes, a class of autoregressive and moving-average processes that extends the class of existing autoregressive gamma (ARG) processes in one important dimension: each conditional moment dynamic is driven by a different and identifiable...

We decompose the quadratic payoff on a stock into its loss and gain components and measure the premia associated with their fluctuations, called the loss and gain quadratic risk premium (QRP) respectively. The loss QRP interprets as the premium paid for downside risk hedging, while the gain QRP...

We propose a new methodology for modeling and estimating time-varying downside risk and upside uncertainty in equity returns and for assessment of risk-return trade-off in financial markets. Using the salient features of the binormal distribution, we explicitly relate downside risk and upside...

We build a small-scale representation of an economy in which the short rate, inflation and output exhibit unobserved secular and cyclical components that both drive bond yields. We impose the economic restriction that expected bond returns are purely cyclical so that their variance does not...

We document that the term structures of risk-neutral expected loss and gain uncertainty on the S&P500 returns are upward sloping on average. These shapes mainly reflect the higher premium required by investors to hedge downside risk, and the belief that potential gains will increase in the...

Macro news have large impact on bond yields in high-frequency data. We aggregate the impact of macro news within each month, which we use in a no-arbitrage term structure models. We find that macro news explain 50 percent in the term premium of the 10-year bond at the monthly frequency and 40...