At each maturity a discrete return distribution is inferred from option prices. Option pricing models imply a comparable theoretical distribution. As both the transformed data and the option pricing model deliver points on a simplex, the data is statistically modeled by a Dirichlet distribution...

We explore a multi-asset jump-diffusion pricing model, combining a systemic risk asset with several conditionally independent ordinary assets. Our approach allows for analyzing and modeling a portfolio that integrates high-activity security, such as an exchange trading fund (ETF) tracking a...

In this paper, we develop lower bounds on the variance of the permanent component and the transitory component, and on the variance of the ratio of the permanent to the transitory components of SDFs. Exactly solved eigenfunction problems are then used to study the empirical attributes of asset...

In this paper we develop the first estimator of the covariance matrix that relies solely on forward-looking information. This estimator only uses price information from a cross-section of plain-vanilla options. In an out-of-sample study for US blue-chip stocks we show that a minimum-variance...

In this paper we develop a new family of estimators of the covariance matrix that relies solely on forward-looking information. These estimators only use current price information from a cross-section of plain-vanilla options and employ different higher moments of the implied return...

We develop a new family of estimators of the covariance matrix that relies solely on forwardlooking information. It uses only current prices of plain-vanilla options. In an out-of-sample study we show that a minimum-variance strategy based on these fully-implied estimators outperforms several...

This paper proposes a simple and crude way of approximating the XVA sensitivities. In short, the idea is simply to recycle the existing base simulated portfolio values for the bumped ones. This is done by re-simulating the risk factors for the bumped market and finding out which other base state...

In dynamic asset pricing models, when the model structure becomes complex and derivatives data are introduced in estimation, traditional Bayesian MCMC methods converge slowly, are difficult to design efficient proposals for parameters, and have large computational cost. We propose a two-stage...

The hypothesis that asset returns are log-normally distributed has been widely rejected. The extant literature has shown that empirical asset returns are highly skewed and leptokurtic (fat tails). The Affine Jump-Diffusion (AJD) model improves upon the log-normal specification by adding a jump...