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Pricing timer options and variance derivatives with closed-form partial transform under the 3/2 model.

Wendong Zheng1, Pingping Zeng2

  • 1Department of Mathematics, Hong Kong University of Science and Technology, Hong Kong, China.

Applied Mathematical Finance
|July 15, 2017
PubMed
Summary
This summary is machine-generated.

The 3/2 stochastic volatility model (SVM) offers better volatility skew prediction than the Heston model. This study derives a closed-form formula for its partial transform, crucial for pricing complex options.

Keywords:
3/2 modeldiscrete monitoringtimer optionstriple joint transition densityvariance derivatives

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Area of Science:

  • Quantitative Finance
  • Mathematical Finance
  • Stochastic Processes

Background:

  • Empirical studies often favor the 3/2 stochastic volatility model (SVM) over the square-root (CIR) process in the Heston model.
  • The 3/2 SVM demonstrates superior ability in capturing volatility skew evolution for option pricing compared to the Heston model.

Purpose of the Study:

  • To investigate the analytic tractability of the 3/2 SVM.
  • To derive a closed-form formula for the partial transform of the triple joint transition density for log asset price, quadratic variation, and instantaneous variance.

Main Methods:

  • Derivation of a closed-form partial transform formula using two distinct formulations.
  • Analysis of the analytic properties of the 3/2 SVM.

Main Results:

  • A closed-form formula for the partial transform of the triple joint transition density is obtained.
  • The derived formula facilitates the deduction of marginal partial transforms and characteristic functions.
  • The partial transform is shown to be crucial for pricing discretely sampled variance derivatives and exotic options.

Conclusions:

  • The 3/2 SVM exhibits enhanced analytic tractability through the derived closed-form partial transform.
  • The methodology provides a versatile tool for pricing various financial derivatives, including moment swaps and timer options with discrete monitoring.