Modelling Volatility In Financial Markets
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Forecasting Volatility In The Financial Markets
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Author : Stephen Satchell
language : en
Publisher: Elsevier
Release Date : 2011-02-24
Forecasting Volatility In The Financial Markets written by Stephen Satchell and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-02-24 with Business & Economics categories.
This new edition of Forecasting Volatility in the Financial Markets assumes that the reader has a firm grounding in the key principles and methods of understanding volatility measurement and builds on that knowledge to detail cutting-edge modelling and forecasting techniques. It provides a survey of ways to measure risk and define the different models of volatility and return. Editors John Knight and Stephen Satchell have brought together an impressive array of contributors who present research from their area of specialization related to volatility forecasting. Readers with an understanding of volatility measures and risk management strategies will benefit from this collection of up-to-date chapters on the latest techniques in forecasting volatility. Chapters new to this third edition: * What good is a volatility model? Engle and Patton * Applications for portfolio variety Dan diBartolomeo * A comparison of the properties of realized variance for the FTSE 100 and FTSE 250 equity indices Rob Cornish * Volatility modeling and forecasting in finance Xiao and Aydemir * An investigation of the relative performance of GARCH models versus simple rules in forecasting volatility Thomas A. Silvey * Leading thinkers present newest research on volatility forecasting *International authors cover a broad array of subjects related to volatility forecasting *Assumes basic knowledge of volatility, financial mathematics, and modelling
Modelling Volatility In Financial Markets
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Author : Chun Liu
language : en
Publisher:
Release Date : 2007
Modelling Volatility In Financial Markets written by Chun Liu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with categories.
In this thesis, I study the dynamics of the volatility process and focus on estimation and forecasting. Recent research uses high frequency intraday data to construct ex post measures of daily volatility including realized volatility (RV). Chapter 1 is the introduction. In Chapter 2, I use a Bayesian approach to investigate the evidence for structural breaks in reduced form time-series models of RV. I focus on the popular heterogeneous autoregressive (HAR) models of the logarithm of realized volatility. Using Monte Carlo simulations I demonstrate that the estimation approach is effective in identifying and dating structural breaks. Applied to daily S & P 500 data, I find strong evidence of a single structural break in log(RV). The main effect of the break is on the long-run mean and variance of log-volatility. Chapter 3 uses a Bayesian model averaging approach to forecast realized volatility. Candidate models include HAR specifications based on the logarithm of realized volatility, realized power variation, realized bipower variation, a jump and leverage term. The Bayesian model averaging provides very competitive density forecasts and consistent but modest improvements in point forecasts over the benchmarks. Applied to equity and exchange rate volatility over several forecast horizons, the Bayesian model averaging provides the best performance compared to the benchmarks including HAR, AR and simple model averaging models. I discuss the reasons for this, including the importance of using realized power variation as a predictor. In the last chapter, I propose a new joint model of volatility and duration in high frequency framework using tick-by-tick data. This model decomposes the conditional variance into different volatility components associated with different transaction horizons. Using stock market data, I demonstrate its superiority over the traditional GARCH counterpart. In addition, I show that a fat-tailed t-distribution for return innovations and a Burr distribution for duration innovations improve density forecasts, compared with normal and exponential distribution, respectively.
Modelling Financial Time Series
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Author : Stephen J. Taylor
language : en
Publisher: World Scientific
Release Date : 2008
Modelling Financial Time Series written by Stephen J. Taylor and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Business & Economics categories.
This book contains several innovative models for the prices of financial assets. First published in 1986, it is a classic text in the area of financial econometrics. It presents ARCH and stochastic volatility models that are often used and cited in academic research and are applied by quantitative analysts in many banks. Another often-cited contribution of the first edition is the documentation of statistical characteristics of financial returns, which are referred to as stylized facts.This second edition takes into account the remarkable progress made by empirical researchers during the past two decades from 1986 to 2006. In the new Preface, the author summarizes this progress in two key areas: firstly, measuring, modelling and forecasting volatility; and secondly, detecting and exploiting price trends.
Forecasting Volatility In The Financial Markets
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Author : John Knight
language : en
Publisher: Butterworth-Heinemann
Release Date : 1998
Forecasting Volatility In The Financial Markets written by John Knight and has been published by Butterworth-Heinemann this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with Business forecasting categories.
An aid to understanding the significance of volatility in the financial market, this text details modelling/forecasting techniques and uses a technical survey to define the models of volatility and return and explain the ways to measure risk. Applications in the financial markets are then detailed.
A Practical Guide To Forecasting Financial Market Volatility
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Author : Ser-Huang Poon
language : en
Publisher: John Wiley & Sons
Release Date : 2005-08-19
A Practical Guide To Forecasting Financial Market Volatility written by Ser-Huang Poon and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-08-19 with Business & Economics categories.
Financial market volatility forecasting is one of today's most important areas of expertise for professionals and academics in investment, option pricing, and financial market regulation. While many books address financial market modelling, no single book is devoted primarily to the exploration of volatility forecasting and the practical use of forecasting models. A Practical Guide to Forecasting Financial Market Volatility provides practical guidance on this vital topic through an in-depth examination of a range of popular forecasting models. Details are provided on proven techniques for building volatility models, with guide-lines for actually using them in forecasting applications.
Modelling And Forecasting High Frequency Financial Data
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Author : Stavros Degiannakis
language : en
Publisher: Springer
Release Date : 2016-04-29
Modelling And Forecasting High Frequency Financial Data written by Stavros Degiannakis and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-29 with Business & Economics categories.
The global financial crisis has reopened discussion surrounding the use of appropriate theoretical financial frameworks to reflect the current economic climate. There is a need for more sophisticated analytical concepts which take into account current quantitative changes and unprecedented turbulence in the financial markets. This book provides a comprehensive guide to the quantitative analysis of high frequency financial data in the light of current events and contemporary issues, using the latest empirical research and theory. It highlights and explains the shortcomings of theoretical frameworks and provides an explanation of high-frequency theory, emphasising ways in which to critically apply this knowledge within a financial context. Modelling and Forecasting High Frequency Financial Data combines traditional and updated theories and applies them to real-world financial market situations. It will be a valuable and accessible resource for anyone wishing to understand quantitative analysis and modelling in current financial markets.
Derivatives In Financial Markets With Stochastic Volatility
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Author : Jean-Pierre Fouque
language : en
Publisher: Cambridge University Press
Release Date : 2000-07-03
Derivatives In Financial Markets With Stochastic Volatility written by Jean-Pierre Fouque and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-07-03 with Business & Economics categories.
This book, first published in 2000, addresses pricing and hedging derivative securities in uncertain and changing market volatility.
Empirical Studies On Volatility In International Stock Markets
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Author : Eugenie M.J.H. Hol
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-09
Empirical Studies On Volatility In International Stock Markets written by Eugenie M.J.H. Hol and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-09 with Business & Economics categories.
Empirical Studies on Volatility in International Stock Markets describes the existing techniques for the measurement and estimation of volatility in international stock markets with emphasis on the SV model and its empirical application. Eugenie Hol develops various extensions of the SV model, which allow for additional variables in both the mean and the variance equation. In addition, the forecasting performance of SV models is compared not only to that of the well-established GARCH model but also to implied volatility and so-called realised volatility models which are based on intraday volatility measures. The intended readers are financial professionals who seek to obtain more accurate volatility forecasts and wish to gain insight about state-of-the-art volatility modelling techniques and their empirical value, and academic researchers and students who are interested in financial market volatility and want to obtain an updated overview of the various methods available in this area.
Martingale Methods In Financial Modelling
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Author : Marek Musiela
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-01-20
Martingale Methods In Financial Modelling written by Marek Musiela and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-01-20 with Mathematics categories.
A new edition of a successful, well-established book that provides the reader with a text focused on practical rather than theoretical aspects of financial modelling Includes a new chapter devoted to volatility risk The theme of stochastic volatility reappears systematically and has been revised fundamentally, presenting a much more detailed analyses of interest-rate models
Financial Models In Production
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Author : Othmane Kettani
language : en
Publisher: Springer Nature
Release Date : 2020-09-16
Financial Models In Production written by Othmane Kettani and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-16 with Mathematics categories.
This book provides a hands-on guide to how financial models are actually implemented and used in practice, on a daily basis, for pricing and risk-management purposes. It shows how to put these models into use in production while minimizing the cost of implementation and maximizing robustness and control. Addressing some of the most important and cutting-edge issues, it describes how to build the necessary models in order to risk manage all the costs involved in options fabrication within the world of equity derivatives and hybrids. This is achieved by extending classical models and improving them in order to account for complex features. The book is primarily aimed at market practitioners (traders, risk managers, risk control, top managers), as well as Masters students in Quantitative/Mathematical Finance. It will also be useful for instructors hoping to enrich their courses with practical examples. The prerequisites are basic stochastic calculus and a general knowledge of financial markets and financial derivatives.