Probabilistic closed-form formulas for pricing nonlinear payoff variance and volatility derivatives under Schwartz model with time-varying log-return volatility
Nontawat Bunchak, Udomsak Rakwongwan, Phiraphat Sutthimat

TL;DR
This paper derives closed-form formulas for pricing nonlinear variance and volatility derivatives under the Schwartz model with time-varying log-return volatility, enabling efficient and accurate valuation.
Contribution
It introduces novel analytical formulas for nonlinear payoff derivatives under a complex stochastic volatility model with time-varying features.
Findings
Formulas for volatility and variance swaps and options are derived.
Monte Carlo simulations demonstrate the accuracy and efficiency of the proposed methods.
Sensitivity analysis shows impact of volatility and trading days on fair strike prices.
Abstract
This paper presents closed-form analytical formulas for pricing volatility and variance derivatives with nonlinear payoffs under discrete-time observations. The analysis is based on a probabilistic approach assuming that the underlying asset price follows the Schwartz one-factor model, where the volatility of log-returns is time-varying. A difficult challenge in this pricing problem is to solve an analytical formula under the assumption of time-varying log-return volatility, resulting in the realized variance being distributed according to a linear combination of independent noncentral chi-square random variables with weighted parameters. By utilizing the probability density function, we analytically compute the expectation of the square root of the realized variance and derive pricing formulas for volatility swaps. Additionally, we derive analytical pricing formulas for volatility call…
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Taxonomy
TopicsStochastic processes and financial applications · Insurance, Mortality, Demography, Risk Management · Financial Risk and Volatility Modeling
