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Continuous Time Processes for Finance

Switching, Self-exciting, Fractional and other Recent Dynamics

  • Book
  • © 2022

Overview

Authors:
  1. Donatien Hainaut

    1. ISBA, Université Catholique de Louvain, Louvain-La_Neuve, Belgium

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  • Focuses on the econometric estimation of continuous time processes
  • Contains original content on switching, self-excited processes
  • Gives an exhaustive presentation of sub-diffusions

Part of the book series: Bocconi & Springer Series (BS, volume 12)

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Table of contents (11 chapters)

  1. Front Matter

    Pages i-xviii
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  2. Switching Models: Properties and Estimation

    • Donatien Hainaut
    Pages 1-42

  3. Estimation of Continuous Time Processes by Markov Chain Monte Carlo

    • Donatien Hainaut
    Pages 43-62

  4. Particle Filtering and Estimation

    • Donatien Hainaut
    Pages 63-80

  5. Modeling of Spillover Effects in Stock Markets

    • Donatien Hainaut
    Pages 81-112

  6. Non-Markov Models for Contagion and Spillover

    • Donatien Hainaut
    Pages 113-141

  7. Fractional Brownian Motion

    • Donatien Hainaut
    Pages 143-178

  8. Gaussian Fields for Asset Prices

    • Donatien Hainaut
    Pages 179-219

  9. Lévy Interest Rate Models with a Long Memory

    • Donatien Hainaut
    Pages 221-258

  10. Affine Volterra Processes and Rough Models

    • Donatien Hainaut
    Pages 259-282

  11. Sub-diffusion for Illiquid Markets

    • Donatien Hainaut
    Pages 283-314

  12. A Fractional Dupire Equation for Jump-Diffusions

    • Donatien Hainaut
    Pages 315-345
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Keywords

About this book

This book explores recent topics in quantitative finance with an emphasis on applications and calibration to time-series. This last aspect is often neglected in the existing mathematical finance literature while it is crucial for risk management. The first part of this book focuses on switching regime processes that allow to model economic cycles in financial markets. After a presentation of their mathematical features and applications to stocks and interest rates, the estimation with the Hamilton filter and Markov Chain Monte-Carlo algorithm (MCMC) is detailed. A second part focuses on self-excited processes for modeling the clustering of shocks in financial markets. These processes recently receive a lot of attention from researchers and we focus here on its econometric estimation and its simulation. A chapter is dedicated to estimation of stochastic volatility models. Two chapters are dedicated to the fractional Brownian motion and Gaussian fields. After a summary of their features, we present applications for stock and interest rate modeling. Two chapters focuses on sub-diffusions that allows to replicate illiquidity in financial markets. This book targets undergraduate students who have followed a first course of stochastic finance and practitioners as quantitative analyst or actuaries working in risk management.

Reviews

“Hainaut has written a book which in such panorama has a position of its own and which should be considered with great interest. … the book should definitely be considered an excellent and warmly recommended read. It is likely that it will be soon become a reference for those interested in modern topics and for young researchers in particular.” (Gianluca Cassese, zbMATH 1512.91001, 2023)

Authors and Affiliations

  • ISBA, Université Catholique de Louvain, Louvain-La_Neuve, Belgium

    Donatien Hainaut

About the author

Donatien Hainaut is professor of quantitative finance and actuarial sciences at UCLouvain where he manages the new Master program in Data Science, statistical orientation. Prior to this he held several positions as associate professor at Rennes School of Business and the ENSAE in Paris. He also has several field experiences having worked as Risk Officer, Quantitative Analyst and ALM Officer. He is a Qualified Actuary and holds a PhD in the area of Assets and Liability Management. His current research focuses on contagion mechanism in stochastic processes, fractional processes and their application in insurance and finance.

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