Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Bayesian Inference and MCMC Methods for Finance: Hierarchical Models, Portfolio Optimization, and Uncertainty Quantification

Bayesian Inference and MCMC Methods for Finance: Hierarchical Models, Portfolio Optimization, and Uncertainty Quantification

Schwartz, Alice
Bisette, Vincent

Paperback

Investing & FinanceProbability & Statistics

ISBN13: 9798180568571
Publisher: Independently Published
Published: Jun 7 2026
Pages: 402
Weight: 1.07
Height: 1.00 Width: 6.00 Depth: 9.00
Language: English
Reactive Publishing

Bayesian Inference and MCMC Methods for Finance provides a rigorous, practical introduction to modern Bayesian techniques and Markov Chain Monte Carlo (MCMC) methods tailored specifically for financial applications.

This book bridges the gap between theoretical statistics and real-world quantitative finance by demonstrating how hierarchical Bayesian models, advanced MCMC sampling, and uncertainty quantification can be applied to portfolio optimization, risk management, and decision-making under uncertainty. Readers will explore the construction and implementation of hierarchical models for capturing complex dependencies in financial data, along with robust methods for posterior inference and predictive simulation.

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