Articlegreen2006

A new technique for calibrating stochastic volatility models: the Malliavin gradient method

26 citations0/0 files storedQuantitative Finance

No readable copy stored yet — this record is metadata only.

No open-access location is known for this record yet.

Literature note Cite in a project Citation map

Stochastic processes and financial applications Financial Risk and Volatility Modeling Markov Chains and Monte Carlo Methods

Abstract

We discuss the application of gradient methods to calibrate mean reverting stochastic volatility models. For this we use formulas based on Girsanov transformations as well as a modification of the Bismut–Elworthy formula to compute the derivatives of certain option prices with respect to the parameters of the model by applying Monte Carlo methods. The article presents an extension of the ideas to apply Malliavin calculus methods in the computation of Greek's.

Paper brief

Loading…

Cite this work

Citation unavailable for this work.

BibTeX RIS CSL-JSON

No public copy is stored for this record, so only the metadata is cited.

Citations in this library

Citation map →

Stored only when both papers are in the corpus — 26 citations exist upstream.

References

1993A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options 2016Numerical solution of stochastic differential equations 2005Stochastic Integration and Differential Equations 1987The Pricing of Options on Assets with Stochastic Volatilities 1983Stochastic Differential Equations and Diffusion Processes 2003Monte Carlo Methods in Financial Engineering 1995The Malliavin Calculus and Related Topics 1987The Pricing of Options on Assets with Stochastic Volatilities

Explore the map →

Papers that cite the same references — the relational fallback while embeddings are still backfilling.

Imported from OpenAlex (CC0) — nothing here is generated.