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Paper / 2025SMQ / 159670407785904
Data-driven Feynman-Kac Discovery with Applications to Prediction and Data Generation
Denny Serdarevic / Guang Lin / Purav Matlia / Qi Feng
stochastic calculus / stochastic differential equationsResource overview

Data-driven Feynman-Kac Discovery with Applications to Prediction and Data Generation

Paper2025

by Denny Serdarevic, Guang Lin, Purav Matlia, Qi Feng

Tags
stochastic calculusstochastic differential equationsstochastic processes

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Suggested foundations for stochastic processes and pricing. Specialist prerequisites vary by paper.

Before you read

  1. Conditional Expectation

    Understand what it means to condition on current information.

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

    Follow Brownian dynamics and the second-order term in Itô calculus.

Go further

  1. Market Model and Risk-Neutral Valuation

    Connect stochastic dynamics to no-arbitrage prices.

  2. Simulating SDEs

    Translate continuous dynamics into a numerical experiment.

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