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Paper / 2022SMQ / 174577468121710
The characteristic function of Gaussian stochastic volatility models: an analytic expression
Eduardo Abi Jaber
derivatives / option pricingResource overview

The characteristic function of Gaussian stochastic volatility models: an analytic expression

Paper2022

by Eduardo Abi Jaber

Tags
derivativesoption pricingrough volatilitystochastic processes

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Understand this paper

Suggested foundations for volatility models and surfaces and options and derivatives pricing. Specialist prerequisites vary by paper.

Before you read

  1. Stochastic Processes, Brownian Motion and Itô's Lemma

    Follow diffusion-based models and their assumptions.

  2. ARCH and GARCH

    Separate conditional volatility from observed returns.

  3. The Binomial Model

    Build replication and risk-neutral probabilities in a tractable model.

  4. Market Model and Risk-Neutral Valuation

    Distinguish pricing probabilities from physical forecasts.

Go further

  1. Stochastic Volatility and the Heston Model

    Study a correlated stochastic-variance model.

  2. Reading the Implied Vol Surface — Moneyness, Term Structure, and Quoting Conventions

    Interpret prices across strikes and expiries.

  3. The Black-Scholes PDE, Formula and Implied Volatility

    Connect the pricing equation, closed-form value and implied volatility.

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Lesson links open public previews. Access to full lessons depends on the topic and your membership.

Explore Advanced Derivatives and Exotic Options Explore Derivatives Pricing and Computational Finance

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