A low frequency factor model regression uses returns computed at a lower frequency than data available. An example is using monthly rather than daily returns to estimate the Capital Asset Pricing Model (CAPM). I show that when using overlapping observations to estimate low frequency factor model...

In this paper we expand the literature of risk neutral density estimation across maturities from implied volatility curves, usually estimated and interpolated through cubic smoothing splines. The risk neutral densities are computed through the second derivative as in Panigirtzoglou and...

We consider the problems of derivative pricing and inference when the stochastic discount factor has an exponential-affine form and the geometric return of the underlying asset has a dynamics characterized by a mixture of conditionally Normal processes. We consider both the static case in which...

The purpose of this paper is to propose discrete-time term structure models where the historical dynamics of the factor (xt) is given, in the univariate case, by a Gaussian AR(p) process, and, in the multivariate case, by a Gaussian n-dimensional VAR(p) process. The factor (xt) is considered as...

The purpose of this paper is to propose discrete-time term structure models where the historical dynamics of the factor (xt) is given, in the univariate case, by a Gaussian AR(p) process, and, in the multivariate case, by a Gaussian n-dimensional VAR(p) process. The factor (xt) is considered as...

We adopt a family of nonparametric Cressie-Read estimators to price options based on relative pricing using the underlying asset returns. We use option models with stochastic volatility and jumps to investigate the ability of each member in this family to price options with different moneynesses...

Using high-frequency intraday data, we construct, test and model seven new realized volatility estimators for six international equity indices. We detect jumps in these estimators, construct the jump components of volatility and perform various tests on their properties. Then we use the class of...

In this paper we approximate the risk factors of a polynomial arbitrage-free dynamic term structure model by running a sequential set of linear regressions independent across time. This approximation avoids the cost of a full optimization procedure allowing for a simple method to extract the...

This paper introduces the concept of stochastic volatility of volatility in continuous time and, hence, extends standard stochastic volatility (SV) models to allow for an additional source of randomness associated with greater variability in the data. We discuss how stochastic volatility of...

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...