Probabilistic Graphical Models: A New Way of Thinking in Financial Modelling - Softcover

Inhaltsangabe

Probabilistic Graphical Models gives an overview of PGMs (a framework encompassing techniques like bayesian networks, markov random fields and chain graphs), which incorporate forward-looking information for making financial decisions, and applies them to stress testing, asset allocation, hedging, and credit risk.

This approach describes a new way to contend with stress testing (a big component of regulations like CCAR, the AIFMD, and Solvency II), teaches the reader how to strengthen their portfolios, presents a forward-looking way of conducting tail hedging, and gives a clear picture of the credit risk of the institution in question (such as a bank or a hedge fund).

Probabilistic Graphical Models teaches this relatively new technique to the reader, explaining how it can be applied to a variety of everyday challenges. Previous to their use in finance, PGMs have been used in disciplines such as computer science, engineering and medicine. Author Alexander Denev expands on this pre-existing material to examine other types of PGMs, demonstrating a novel range of applications.

Chapters feature:
- Why is a new approach needed?
- Probabilistic Graphical Models: An Overview
- Stress Testing
- Asset Allocation
- Hedging
- Credit Risk

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