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Author: Peter Christoffersen
Publisher:
ISBN:
Category :
Languages : en
Pages : 51
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Book Description
We build a new class of discrete time models where the distribution of daily returns is driven by two factors: dynamic volatility and dynamic jump intensity. Each factor has its own risk premium. The likelihood function for the models is available using analytical filtering, which makes them much easier to implement than most existing models. Estimating the models on Samp;P500 returns, we find that they significantly outperform standard models without jumps. We find very strong empirical support for time-varying jump intensities, and thus for flexible skewness and kurtosis dynamics. Compared to the risk premium on dynamic volatility, the risk premium on the dynamic jump intensity has a much larger impact on option prices. We confirm these findings using joint estimation on returns and large option samples, which is feasible in our class of models.
Author: Peter Christoffersen
Publisher:
ISBN:
Category :
Languages : en
Pages : 51
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Book Description
We build a new class of discrete time models where the distribution of daily returns is driven by two factors: dynamic volatility and dynamic jump intensity. Each factor has its own risk premium. The likelihood function for the models is available using analytical filtering, which makes them much easier to implement than most existing models. Estimating the models on Samp;P500 returns, we find that they significantly outperform standard models without jumps. We find very strong empirical support for time-varying jump intensities, and thus for flexible skewness and kurtosis dynamics. Compared to the risk premium on dynamic volatility, the risk premium on the dynamic jump intensity has a much larger impact on option prices. We confirm these findings using joint estimation on returns and large option samples, which is feasible in our class of models.
Author: Dario Alitab
Publisher:
ISBN:
Category :
Languages : en
Pages : 46
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Book Description
We introduce a discrete-time model for log-return dynamics with observable volatility and jumps. Our proposal extends the class of Realized Volatility heterogeneous auto-regressive gamma (HARG) processes adding a jump component with time-varying intensity. The model is able to reproduce the temporary increase in the probability of occurrence of a jump immediately after an abrupt large movement of the asset price. Belonging to the class of exponentially affine models, the moment generating function under the physical measure is available in closed-form. Thanks to a flexible specification of the pricing kernel compensating for equity, volatility, and jump risks, the generating function under the risk-neutral measure inherits analytical tractability too. An application of the leveraged HARG model with dynamic jump intensity to the pricing of a large sample of S&P500 index options assesses its superior performances with respect to state-of-the-art benchmark models.
Author: Wing H. Chan
Publisher:
ISBN:
Category :
Languages : en
Pages : 25
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Book Description
This paper proposes a new class of GARCH-jump in mean models to test the presence of time varying risk premia associated with normal and extreme news events. The model allows for a dynamic jump component with autoregressive jump intensity, long-range dependence in volatility dynamics, and volatility in mean structure separately for normal and extreme news events. The results show significant jump risk premia in five stock market index returns. We also find that ignoring the long-memory feature in volatility dynamics leads to false rejection of time varying risk premia.
Author: Jonathan H. Wright
Publisher:
ISBN:
Category : Bonds
Languages : en
Pages : 64
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Book Description
Author: Kenneth J. Singleton
Publisher: Princeton University Press
ISBN: 1400829232
Category : Business & Economics
Languages : en
Pages : 497
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Book Description
Written by one of the leading experts in the field, this book focuses on the interplay between model specification, data collection, and econometric testing of dynamic asset pricing models. The first several chapters provide an in-depth treatment of the econometric methods used in analyzing financial time-series models. The remainder explores the goodness-of-fit of preference-based and no-arbitrage models of equity returns and the term structure of interest rates; equity and fixed-income derivatives prices; and the prices of defaultable securities. Singleton addresses the restrictions on the joint distributions of asset returns and other economic variables implied by dynamic asset pricing models, as well as the interplay between model formulation and the choice of econometric estimation strategy. For each pricing problem, he provides a comprehensive overview of the empirical evidence on goodness-of-fit, with tables and graphs that facilitate critical assessment of the current state of the relevant literatures. As an added feature, Singleton includes throughout the book interesting tidbits of new research. These range from empirical results (not reported elsewhere, or updated from Singleton's previous papers) to new observations about model specification and new econometric methods for testing models. Clear and comprehensive, the book will appeal to researchers at financial institutions as well as advanced students of economics and finance, mathematics, and science.
Author: Wing-Keung Wong
Publisher: MDPI
ISBN: 3039435736
Category : Business & Economics
Languages : en
Pages : 232
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Book Description
Mathematical finance plays a vital role in many fields within finance and provides the theories and tools that have been widely used in all areas of finance. Knowledge of mathematics, probability, and statistics is essential to develop finance theories and test their validity through the analysis of empirical, real-world data. For example, mathematics, probability, and statistics could help to develop pricing models for financial assets such as equities, bonds, currencies, and derivative securities.
Author: Jianjian Jin
Publisher:
ISBN:
Category :
Languages : en
Pages : 66
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Book Description
This paper calibrates a class of jump-diffusion long-run risks models and quantifies how well they can account for both equity and variance risk premiums while generating realistic volatility dynamics. I find that jumps in the level and the volatility of long-run consumption growth rates perform equally well in explaining the variance risk premium. Moreover, compared to jump-in-growth models, jump-in-volatility models generate more realistic volatility dynamics and stronger predictability of returns by the variance risk premium. Finally, both jump-in-volatility and jump-in-growth models suggest that a non-trivial portion of the equity risk premium is due to compensation for jump risks.
Author: Robert Huitema
Publisher:
ISBN:
Category :
Languages : en
Pages : 67
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Book Description
This paper proposes a new approach to measure premiums for volatility and jump risks in option markets. These risks are captured by a multi-factor jump-diffusion model for the joint evolution of the underlying and the implied volatility surface. This market-based approach enables us to carefully test and select the most relevant risk factors in option markets. We extend the approach of Schonbucher (1998) to processes that include jumps and derive a condition that ensures absence of dynamic arbitrage. As this condition is derived under the physical measure, it incorporates a premium for each risk factor in the model. We then interpret the no-arbitrage constraint as a noisy measurement of these risk premiums and other latent variables such as the volatility and jump-intensity of the underlying. This allows us to dynamically calibrate these variables to data from several markets using a Bayesian filtering framework. The results shed new light on how option risk premiums vary over time and across markets. As our approach provides an accurate and arbitrage-free description of option price dynamics it can also be used for risk management of portfolios of options and for testing dynamic option strategies.
Author: Sanjay K. Nawalkha
Publisher: John Wiley & Sons
ISBN: 0470140062
Category : Business & Economics
Languages : en
Pages : 722
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Book Description
Praise for Dynamic Term Structure Modeling "This book offers the most comprehensive coverage of term-structure models I have seen so far, encompassing equilibrium and no-arbitrage models in a new framework, along with the major solution techniques using trees, PDE methods, Fourier methods, and approximations. It is an essential reference for academics and practitioners alike." --Sanjiv Ranjan Das Professor of Finance, Santa Clara University, California, coeditor, Journal of Derivatives "Bravo! This is an exhaustive analysis of the yield curve dynamics. It is clear, pedagogically impressive, well presented, and to the point." --Nassim Nicholas Taleb author, Dynamic Hedging and The Black Swan "Nawalkha, Beliaeva, and Soto have put together a comprehensive, up-to-date textbook on modern dynamic term structure modeling. It is both accessible and rigorous and should be of tremendous interest to anyone who wants to learn about state-of-the-art fixed income modeling. It provides many numerical examples that will be valuable to readers interested in the practical implementations of these models." --Pierre Collin-Dufresne Associate Professor of Finance, UC Berkeley "The book provides a comprehensive description of the continuous time interest rate models. It serves an important part of the trilogy, useful for financial engineers to grasp the theoretical underpinnings and the practical implementation." --Thomas S. Y. Ho, PHD President, Thomas Ho Company, Ltd, coauthor, The Oxford Guide to Financial Modeling
Author: Carsten Wehn
Publisher: Academic Press
ISBN: 0124158889
Category : Business & Economics
Languages : en
Pages : 657
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Book Description
It is widely acknowledged that many financial modelling techniques failed during the financial crisis, and in our post-crisis environment many techniques are being reconsidered. This single volume provides a guide to lessons learned for practitioners and a reference for academics. Including reviews of traditional approaches, real examples, and case studies, contributors consider portfolio theory; methods for valuing equities and equity derivatives, interest rate derivatives, and hybrid products; and techniques for calculating risks and implementing investment strategies. Describing new approaches without losing sight of their classical antecedents, this collection of original articles presents a timely perspective on our post-crisis paradigm. Highlights pre-crisis best classical practices, identifies post-crisis key issues, and examines emerging approaches to solving those issues Singles out key factors one must consider when valuing or calculating risks in the post-crisis environment Presents material in a homogenous, practical, clear, and not overly technical manner
