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Enhancing FX Option Pricing: Comparing Stochastic and Constant Volatility Models

This paper by Yaw-huei Wang investigates the shortcomings of lognormal density functions in fitting market prices and aims to compare the performance of constant vs. stochastic volatility models for FX option pricing, focusing on Garman & Kohlhagen versus Heston models. Findings reveal that Heston's model outperforms the constant volatility approach, with a quicker mean reversion of FX volatility and a tendency toward less negative skewness. The work not only highlights comparative pricing performance but also urges deeper exploration into the economic implications of model parameters. Various data processing methods enhance the reader's understanding.

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Enhancing FX Option Pricing: Comparing Stochastic and Constant Volatility Models

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  1. Discussion for Chen and Gau (2004) : Pricing Currency Options under Stochastic Volatilityby Yaw-huei Wang • A potentially interesting paper • Summary: • Motivation: A lognormal density fails to fit market prices. • Objective: Comparing the performance of a constant and a stochastic volatility model for FX option pricing. • Models: Garman & Kohlhagen v.s. Heston • Findings: • (1) Heston’s model outperforms • (2) Speed of volatility mean reverting for FX is faster • (3) FX exhibits less negatively skewed.

  2. Contribution: comparing pricing performance and economic meanings implied in estimated parameters. • Questions & Comments: • Reader-friendly presentation in the article. • Sophisticated data processing. • Synchronization, Transformation from American to European, Abandon short-time-to-maturity data … etc. • Comparison of models’ performance is interesting. But, comparison of economic meanings implied in a good model could be more interesting, particularly for different assets. • Does jumps matter? Jumps in returns or volatility, or both? • Empirical implementations of a jump stochastic volatility model for pricing FX options could be interesting?

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