Continuous time processes for finance switching, self-exciting, fractional and other recent dynamics / [electronic resource] :
- 作者： Hainaut, Donatien.
- 其他作者：
- 其他題名：
- Bocconi & Springer series, mathematics, statistics, finance and economics ;
- 出版： Cham : Springer International Publishing :Imprint: Springer
- 叢書名： Bocconi & Springer series, mathematics, statistics, finance and economics,v. 12
- 主題： Finance--Statistical methods. , Finance--Mathematical models. , Time-series analysis. , Stochastic processes. , Probability Theory. , Mathematics in Business, Economics and Finance. , Econometrics. , Actuarial Mathematics. , Quantitative Economics.
- ISBN： 9783031063619 (electronic bk.) 、 9783031063602 (paper)
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FIND@SFXID:
CGU
- 資料類型: 電子書
- 內容註: 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. Le?vy 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.
- 摘要註: 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.
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讀者標籤：
- 系統號： 005517137 | 機讀編目格式
館藏資訊
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.