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Stock Market Volatility

Stock Market Volatility PDF Author: Greg N. Gregoriou
Publisher: CRC Press
ISBN: 1420099558
Category : Business & Economics
Languages : en
Pages : 654

Book Description
Up-to-Date Research Sheds New Light on This Area Taking into account the ongoing worldwide financial crisis, Stock Market Volatility provides insight to better understand volatility in various stock markets. This timely volume is one of the first to draw on a range of international authorities who offer their expertise on market volatility in devel

Stock Market Volatility

Stock Market Volatility PDF Author: Greg N. Gregoriou
Publisher: CRC Press
ISBN: 1420099558
Category : Business & Economics
Languages : en
Pages : 654

Book Description
Up-to-Date Research Sheds New Light on This Area Taking into account the ongoing worldwide financial crisis, Stock Market Volatility provides insight to better understand volatility in various stock markets. This timely volume is one of the first to draw on a range of international authorities who offer their expertise on market volatility in devel

Application of GARCH Models for Modeling Stock Market Volatility

Application of GARCH Models for Modeling Stock Market Volatility PDF Author: Shabarisha N.
Publisher:
ISBN:
Category :
Languages : en
Pages :

Book Description
Return is the major attribute of an investment asset which can be construed as a random variable, and the 'variability in return' can be interpreted as volatility. Forecasting volatility and modeling it are the most prolific areas for research. This paper empirically investigates the conditional variance (volatility) pattern in Indian stock market based on financial time series data that consists of daily closing prices of CNX Nifty 50 market index for 10 years from April 2006 to March 2016. For the purpose of estimating conditional variance (volatility) in the daily returns of the index, Autoregressive Conditional Heteroskedasticity (ARCH) models are employed. Both symmetric and asymmetric models are used to capture stylized facts about CNX Nifty 50 market index returns such as volatility clustering and leverage effect. The findings of the study show that the asymmetric models are a better fit than symmetric models, confirming the presence of volatility clustering and leverage effect.

Applications of GARCH Models to Stock Market Volatility

Applications of GARCH Models to Stock Market Volatility PDF Author: Wei Liu
Publisher:
ISBN:
Category :
Languages : en
Pages : 76

Book Description


An Introduction to Wavelets and Other Filtering Methods in Finance and Economics

An Introduction to Wavelets and Other Filtering Methods in Finance and Economics PDF Author: Ramazan Gençay
Publisher: Elsevier
ISBN: 0080509223
Category : Business & Economics
Languages : en
Pages : 383

Book Description
An Introduction to Wavelets and Other Filtering Methods in Finance and Economics presents a unified view of filtering techniques with a special focus on wavelet analysis in finance and economics. It emphasizes the methods and explanations of the theory that underlies them. It also concentrates on exactly what wavelet analysis (and filtering methods in general) can reveal about a time series. It offers testing issues which can be performed with wavelets in conjunction with the multi-resolution analysis. The descriptive focus of the book avoids proofs and provides easy access to a wide spectrum of parametric and nonparametric filtering methods. Examples and empirical applications will show readers the capabilities, advantages, and disadvantages of each method. The first book to present a unified view of filtering techniques Concentrates on exactly what wavelets analysis and filtering methods in general can reveal about a time series Provides easy access to a wide spectrum of parametric and non-parametric filtering methods

Handbook of Volatility Models and Their Applications

Handbook of Volatility Models and Their Applications PDF Author: Luc Bauwens
Publisher: John Wiley & Sons
ISBN: 1118272056
Category : Business & Economics
Languages : en
Pages : 566

Book Description
A complete guide to the theory and practice of volatility models in financial engineering Volatility has become a hot topic in this era of instant communications, spawning a great deal of research in empirical finance and time series econometrics. Providing an overview of the most recent advances, Handbook of Volatility Models and Their Applications explores key concepts and topics essential for modeling the volatility of financial time series, both univariate and multivariate, parametric and non-parametric, high-frequency and low-frequency. Featuring contributions from international experts in the field, the book features numerous examples and applications from real-world projects and cutting-edge research, showing step by step how to use various methods accurately and efficiently when assessing volatility rates. Following a comprehensive introduction to the topic, readers are provided with three distinct sections that unify the statistical and practical aspects of volatility: Autoregressive Conditional Heteroskedasticity and Stochastic Volatility presents ARCH and stochastic volatility models, with a focus on recent research topics including mean, volatility, and skewness spillovers in equity markets Other Models and Methods presents alternative approaches, such as multiplicative error models, nonparametric and semi-parametric models, and copula-based models of (co)volatilities Realized Volatility explores issues of the measurement of volatility by realized variances and covariances, guiding readers on how to successfully model and forecast these measures Handbook of Volatility Models and Their Applications is an essential reference for academics and practitioners in finance, business, and econometrics who work with volatility models in their everyday work. The book also serves as a supplement for courses on risk management and volatility at the upper-undergraduate and graduate levels.

Forecasting Daily Stock Volatility Using GARCH Model

Forecasting Daily Stock Volatility Using GARCH Model PDF Author: Sasikanta Tripathy
Publisher:
ISBN:
Category :
Languages : en
Pages :

Book Description
Modeling and forecasting the volatility of stock markets has been one of the major topics in financial econometrics in recent years. Based on the daily closing value of 23 years data, an average of 5,605 observations, for both Sensex and Shanghai Stock Exchange Composite Index, this paper makes an attempt to fit appropriate GARCH model to estimate the conditional market volatility for both Bombay Stock Exchange (BSE) and Shanghai Stock Exchange (SSE), respectively. The empirical results demonstrate that there are significant ARCH effects in both the stock markets, and it is appropriate to use the GARCH model to estimate the process.

Forecasting Volatility in the Financial Markets

Forecasting Volatility in the Financial Markets PDF Author: Stephen Satchell
Publisher: Elsevier
ISBN: 0080471420
Category : Business & Economics
Languages : en
Pages : 428

Book Description
Forecasting Volatility in the Financial Markets, Third Edition 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

Non-Linear Time Series Models in Empirical Finance

Non-Linear Time Series Models in Empirical Finance PDF Author: Philip Hans Franses
Publisher: Cambridge University Press
ISBN: 0521770416
Category : Business & Economics
Languages : en
Pages : 299

Book Description
This 2000 volume reviews non-linear time series models, and their applications to financial markets.

Modeling Stochastic Volatility with Application to Stock Returns

Modeling Stochastic Volatility with Application to Stock Returns PDF Author: Mr.Noureddine Krichene
Publisher: International Monetary Fund
ISBN: 1451854846
Category : Business & Economics
Languages : en
Pages : 30

Book Description
A stochastic volatility model where volatility was driven solely by a latent variable called news was estimated for three stock indices. A Markov chain Monte Carlo algorithm was used for estimating Bayesian parameters and filtering volatilities. Volatility persistence being close to one was consistent with both volatility clustering and mean reversion. Filtering showed highly volatile markets, reflecting frequent pertinent news. Diagnostics showed no model failure, although specification improvements were always possible. The model corroborated stylized findings in volatility modeling and has potential value for market participants in asset pricing and risk management, as well as for policymakers in the design of macroeconomic policies conducive to less volatile financial markets.

Modelling Stock Market Volatility

Modelling Stock Market Volatility PDF Author: Peter H. Rossi
Publisher: Elsevier
ISBN: 0080511872
Category : Business & Economics
Languages : en
Pages : 505

Book Description
This essay collection focuses on the relationship between continuous time models and Autoregressive Conditionally Heteroskedastic (ARCH) models and applications. For the first time, Modelling Stock Market Volatility provides new insights about the links between these two models and new work on practical estimation methods for continuous time models. Featuring the pioneering scholarship of Daniel Nelson, the text presents research about the discrete time model, continuous time limits and optimal filtering of ARCH models, and the specification and estimation of continuous time processes. This work will lead to a rapid growth in their empirical application as they are increasingly subjected to routine specification testing. Provides for the first time new insights on the links between continuous time and ARCH models Collects seminal scholarship by some of the most renowned researchers in finance and econometrics Captures complex arguments underlying the approximation and proper statistical modelling of continuous time volatility dynamics