smq/directoryAn evolving quant resource archive
Back to directoryResource
Paper / 2026SMQ / 52066825882872
Optimal Investment and Entropy-Regularized Learning Under Stochastic Volatility Models with Portfolio Constraints
Pertiny Nkuize / Thai Nguyen
optimization / partial differential equationsResource overview

Optimal Investment and Entropy-Regularized Learning Under Stochastic Volatility Models with Portfolio Constraints

Paper2026

by Pertiny Nkuize, Thai Nguyen

Tags
optimizationpartial differential equationsportfolio optimizationreinforcement learningstochastic processes

Access resource

Open original source Understand this paper

Continue on SelfMadeQuant

Understand this paper

Suggested foundations for volatility models and surfaces and optimisation and numerical methods. 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. Vectors, Matrices and Linear Systems

    Read the linear algebra used to define a numerical problem.

  4. Constrained and Convex Optimisation

    Identify the objective, constraints and conditions for an optimum.

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. Calibration as an Inverse Problem

    Understand identifiability and fitted model parameters.

Explore a related reading path

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

Explore Advanced Derivatives and Exotic Options Explore Linear Algebra, Optimisation and Numerical Methods

Keep exploring

Related resources

More ideas from similar topics.

6

From the same author

Pertiny Nkuize, Thai Nguyen

4