After the recent financial crisis, the market for volatility derivatives has expanded rapidly to meet the demand from investors, risk managers and speculators seeking diversification of the volatility risk. In this paper, we develop a novel and efficient transform-based method to price swaps and...

A new valuation and calibration method for VIX futures and VIX options is proposed. The method is based on a closed-form Hermite series expansion for a stochastic volatility model with the stochastic variance process driven by an affine drift term. We implement the methodology for the Heston and...

We study a Bayesian learning model with heterogeneity in which the agents control both short-term manipulations and long-term efforts aimed at solving the optimal contract in dynamic environments. At the same time, considering the dynamic characteristics of contracts, the paper considers the...

We theoretically compare variances between the Infinitesimal Perturbation Analysis (IPA) estimator and the Likelihood Ratio (LR) estimator to Monte Carlo gradient for stochastic systems. The conditions proposed in [Cui et al., 2020] when the IPA estimator has a smaller variance can yield sharper...

We present a new method to sample random variables through the use of orthogonal polynomial expansions of the associated quantile function that utilize the inverse transform technique. In particular, we obtain an explicit representation of the quantile function through an orthogonal expansion...

In this paper, we consider the optimal investment problem with both probability distor- tion/weighting and general non-concave utility functions with possibly finite number of inflection points. Our model contains the model under cumulative prospect theory (CPT) as a special case, which has...