Stocks with high net gamma exposure robustly underperform stocks with low net gamma exposure by 10% per year. This effect is distinct from multiple previously documented return predictors, and survives many robustness checks. We show that stocks with low net gamma exposure negatively predicts...

Option prices embed predictive content for the outcomes of pending mergers and acquisitions. This is particularly important in merger arbitrage, where deal failure is a key risk. In this paper, I propose a dynamic asset pricing model that exploits the joint information in target stock and option...

We investigate the effect of including variance derivatives as calibration and hedging instruments for pricing and hedging exotic structures. This is studied empirically using market data for SPX and VIX derivatives applied in a stochastic volatility jump diffusion model

An enhanced option pricing framework that makes use of both continuous and discontinuous time paths based on a geometric Brownian motion and Poisson-driven jump processes respectively is performed in order to better fit with real-observed stock price paths while maintaining the analytical...

SABR stochastic volatility model is appealing for modeling smile and skew of option prices. Hagan, who first proposed this model, derived a closed form approximation for european options and showed that it provides consistent and stable hedges. Here I prove a new exact closed formula for the...

We propose a modelling treatment for the option-implied risk neutral distribution (RND) which disaggregates its long-term and short-term dynamics. Long memory parameters calibrated on the RND moments serve as tractable mathematical constructs to filter out effects of smooth structural change...

In this paper we provide several applications of Gram-Charlier expansions in financial derivative pricing. We first give an exposition on how to calculate swaption prices under a two-factor Cox-Ingersoll-Ross (CIR2) model. Then we apply this method to an extended version of the model (CIR2 ). We...

We employ a refined tree method to value employee stock options (ESOs) in the stochastic volatility model of Heston. Our setting covers risk-averse employees maximizing expected utility where we in particular focus on subjective option valuation, personal market beliefs and stochastic...

Finance researchers keep producing increasingly complex and computationally-intensive models of stock returns. Separately, professional analysts forecast stock returns daily for their clients. Are the sophisticated methods of researchers achieving better forecasts or are we better off relying on...

Option prices embed predictive content for the outcomes of pending mergers and acquisitions. This is particularly important in merger arbitrage, where deal failure is a key risk. In this paper, I propose a dynamic asset pricing model that exploits the joint information in target stock and option...