Continuous Time Processes for Finance : Switching, Self-exciting, Fractional and other Recent Dynamics / / by Donatien Hainaut

• Record Nr.: UNINA9910590077503321
• Autore: Hainaut Donatien
• Pubbl/distr/stampa: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022
• ISBN: 9783031063619; 9783031063602
• Edizione: [1st ed. 2022.]
• Descrizione fisica: 1 online resource (359 pages)
• Collana: Bocconi & Springer Series, Mathematics, Statistics, Finance and Economics, , 2039-148X ; ; 12
• Disciplina: 332.015195
• Soggetti: Probabilities; Social sciences - Mathematics; Econometrics; Actuarial science; Probability Theory; Mathematics in Business, Economics and Finance; Actuarial Mathematics; Quantitative Economics
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di contenuto: Preface -- Acknowledgements -- Notations -- 1. Switching Models: Properties and Estimation -- 2. Estimation of Continuous Time Processes by Markov Chain Monte Carlo -- 3. Particle Filtering and Estimation -- 4. Modeling of Spillover Effects in Stock Markets -- 5. Non-Markov Models for Contagion and Spillover -- 6. Fractional Brownian Motion -- 7. Gaussian Fields for Asset Prices -- 8. Lévy Interest Rate Models With a Long Memory -- 9. Affine Volterra Processes and Rough Models -- 10. Sub-Diffusion for Illiquid Markets -- 11. A Fractional Dupire Equation for Jump-Diffusions -- References.
• Sommario/riassunto: 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.