Analytic estimation of parameters of stochastic volatility diffusion models with exponential-affine characteristic function for currency option pricing
Miko{\l}aj {\L}ab\k{e}dzki

TL;DR
This paper introduces a new analytical method for estimating parameters in stochastic volatility models with exponential-affine characteristic functions, improving option pricing accuracy and calibration efficiency, especially for currency options.
Contribution
It develops novel formulas for parameter estimation in advanced stochastic volatility models, including the new OUOU two-factor model, enhancing derivative pricing tools.
Findings
The new formulas provide faster, more accurate parameter estimates.
The OUOU model extends existing models with semi-analytical valuation.
Performance tests show improved calibration accuracy on EURUSD options.
Abstract
This dissertation develops and justifies a novel method for deriving approximate formulas to estimate two parameters in stochastic volatility diffusion models with exponentially-affine characteristic functions and single- or two-factor variance. These formulas aim to improve the accuracy of option pricing and enhance the calibration process by providing reliable initial values for local minimization algorithms. The parameters relate to the volatility of the stochastic factor in instantaneous variance dynamics and the correlation between stochastic factors and asset price dynamics. The study comprises five chapters. Chapter one outlines the currency option market, pricing methods, and the general structure of stochastic volatility models. Chapter two derives the replication strategy dynamics and introduces a new two-factor volatility model: the OUOU model. Chapter three analyzes the…
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Taxonomy
TopicsStochastic processes and financial applications
