In this paper we develop efficient Monte Carlo methods for estimating American option sensitivities. The problem can be re-formulated as how to perform sensitivity analysis for a stochastic optimization problem when it has model uncertainty. We introduce a generalized infinitesimal perturbation...

A foundational problem in marketing and economics involves accurately predicting purchase decisions at both individual and aggregate levels. Building on recent advances in neuroeconomic models of decision making, we investigate the possibility of improving upon the prediction accuracy of popular...

In this paper we develop a new delta expansion approach to deriving analytical approximation to the transition densities of multivariate diffusions using the Ito-Taylor expansion of the conditional expectation of the Dirac delta function. Our approach yields an explicit recursive formulas for...

The stochastic-alpha-beta-rho (SABR) model introduced by Hagan et al. (2002) provides a popular vehicle to model the implied volatilities in the interest rate and foreign exchange markets. To exclude arbitrage opportunities, we need to specify an absorbing boundary at zero for this model, which...

We examine the impact of data access within a vertically integrated e-commerce platform. Using a unique daily panel, we find that both the platform owner and third-party sellers base pricing on past sales, but only the owner exploits competitors' sales data. We estimate a price competition model...