This paper studies the predictability of S&P500 returns using short term risk premia as a conditioning variable. We construct dividend prices using futures data and identify short term risk premia by projecting excess returns of dividend claims on their lagged prices. Regression results for...

We model the S&P500 index options dynamics using the CGMY distribution, with independent "up" and "down" return jumps, and diffusive jump intensities. Allowing the up and down parts to be separately parameterised accounts for the dynamic smirk effect, without correlation between returns and...

Term premiums, defined as the excess return of long-dated contracts over short-dated contracts, in commodity futures are strongly predictable, both in the time series and in the cross section, by roll yield spreads. Strategies that exploit this predictability show sizable Sharpe ratios and are...

We derive expected bond return equations for various structural credit valuation models with alternative stochastic processes and boundary conditions for default given in Merton [1974], Merton [1976], Black and Cox [1976], Heston [1993], Longstaff and Schwartz [1995], and Collin-Dufresne and...

We develop a continuous-time intertemporal CAPM model that allows for risky beta exposure, which we explicitly specify. In the model, the expected return on a stock depends on beta's co-movement with market variance and more generally with the stochastic discount factor and deviates from the...

Market index and individual stock returns exhibit jumps in addition to normal shocks. Equities have exposure to the market and sensitivity to the market is important for explaining equity returns and option prices. I develop a new factor model that explores (i) if a separate beta for market...

We document that properly scaled deviations from put-call parity estimate the contribution of market frictions to expected returns (CFER) accurately, by means of a non-parametric theoretically founded identification strategy. The required conditions are that our estimator predicts the underlying...

We use simultaneous data from equity, index and option markets in order to estimate a single-factor market model in which idiosyncratic volatility is allowed to be priced. We model the index dynamics' physical distribution as a mean-reverting stochastic volatility process as in Heston (1993),...

I study a novel data set of short-term dividend futures contracts for individual stocks. I combine this data with dividend forecasts from equity research analysts to construct a model-free measure of short-term equity risk premia. I provide the first description of the cross-section of risk...