Author: Matthias Fengler (Wirtschaftswissenschaftler Univ. St. Gallen.)Publisher:
ISBN:
Category :
Languages : en
Pages : 50
Book Description
Additive Modeling of Realized Variance
Author: Matthias Fengler (Wirtschaftswissenschaftler Univ. St. Gallen.)Publisher:
ISBN:
Category :
Languages : en
Pages : 50
Book Description
Specification and Structural Break Tests for Additive Models with Applications to Realized Variance Data
Author: Matthias R. FenglerPublisher:
ISBN:
Category :
Languages : en
Pages :
Book Description
We study two types of testing problems in a nonparametric additive model setting: We develop methods to test (i) whether an additive component function has a given parametric form and (ii) whether an additive component has a structural break. We apply the theory to a nonparametric extension of the linear heterogeneous autoregressive model which is widely employed to describe realized variance data. We find that the linearity assumption is often rejected, but actual deviations from linearity are mild.
Handbook of Volatility Models and Their Applications
Author: Luc BauwensPublisher: John Wiley & Sons
ISBN: 0470872519
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.
A Simple Approximate Long-Memory Model of Realized Volatility
Author: Fulvio CorsiPublisher:
ISBN:
Category :
Languages : en
Pages :
Book Description
The paper proposes an additive cascade model of volatility components defined over different time periods. This volatility cascade leads to a simple AR-type model in the realized volatility with the feature of considering different volatility components realized over different time horizons and thus termed Heterogeneous Autoregressive model of Realized Volatility (HAR-RV). In spite of the simplicity of its structure and the absence of true long-memory properties, simulation results show that the HAR-RV model successfully achieves the purpose of reproducing the main empirical features of financial returns (long memory, fat tails, and self-similarity) in a very tractable and parsimonious way. Moreover, empirical results show remarkably good forecasting performance.
Handbook of Volatility Models and Their Applications
Author: Luc BauwensPublisher: 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.
A Simple Long Memory Model of Realized Volatility
Author: Fulvio CorsiPublisher:
ISBN:
Category :
Languages : en
Pages : 27
Book Description
In the present work we propose a new realized volatility model to directly model and forecast the time series behavior of volatility. The purpose is to obtain a conditional volatility model based on realized volatility which is able to reproduce the memory persistence observed in the data but, at the same time, remains parsimonious and easy to estimate. Inspired by the Heterogeneous Market Hypothesis and the asymmetric propagation of volatility between long and short time horizons, we propose an additive cascade of different volatility components generated by the actions of different types of market participants. This additive volatility cascade leads to a simple AR-type model in the realized volatility with the feature of considering volatilities realized over different time horizons. We term this model, Heterogeneous Autoregressive model of the Realized Volatility (HAR-RV). In spite of the simplicity of its structure, simulation results seem to confirm that the HAR-RV model successfully achieves the purpose of reproducing the main empirical features of financial data (long memory, fat tail, self-similarity) in a very simple and parsimonious way. Preliminary results on the estimation and forecast of the HAR-RV model on USD/CHF data, show remarkably good out of sample forecasting performance which steadily and substantially outperforms those of standard models.
Multivariate Modeling of Realized Variance
Author: Katja GislerPublisher:
ISBN:
Category :
Languages : en
Pages :
Book Description
Mit der Verfügbarkeit von Hochfrequenz-Daten sind neue Modellansätze für Varianzen und Kovarianzen entstanden, die so genannten realisierten Kovarianzmodelle. Während sich die meisten dieser realisierten Kovarianzmodelle auf einen univariaten Ansatz konzentrieren, verfolgt diese Masterarbeit das Ziel die gesamte Kovarianzmatrix zu modellieren. Infolgedessen präsentieren wir eine Erweiterung des univariaten heterogenen autoregressiven Modells für realisierte Volatilität (HAR-RV) von Corsi (2009), indem wir ein Vektor-HAR analog zum vektor-autoregressiven (VAR) Standard- Modell entwickeln und dabei die realisierte Bipower Kovariation bzw. Variation als konsistenten Schätzer für die integrierte Kovarianz bzw. Varianz verwenden. Wie andere multivariate Kovarianzmodelle leidet das multivariate HAR Modell für realisierte Bipower Variation (MHAR-BV) allerdings am sogenannten "Fluch der Dimensionalität". Wir reduzieren daher die Anzahl der Parameter anhand ökonometrischer Überlegungen. Das resultierende restringierte multivariate HAR-BV Modell zeigt, dass Kovarianzen bei der multivariaten Modelierung von realisierter Varianz eine signifikante Rolle spielen. Basierend auf dem restringierten Modell, führen wir anschliessend noch eine Spillover Analyse analog zu Diebold and Yilmaz (2009) durch. Diese Analyse zeigt nochmals auf, dass Spillovers entlang von realisierter Varianz und Kovarianz wichtig sind und insbesondere auf ökonomische Events reagieren, welche wir während der letzten Finanzkrise beobachten konnten.
Studies on Realized Variance - GARCH - Beta Models
Author: Wei WuGeneralized Additive Models
Author: Simon WoodPublisher: CRC Press
ISBN: 1584884746
Category : Mathematics
Languages : en
Pages : 412
Book Description
Now in widespread use, generalized additive models (GAMs) have evolved into a standard statistical methodology of considerable flexibility. While Hastie and Tibshirani's outstanding 1990 research monograph on GAMs is largely responsible for this, there has been a long-standing need for an accessible introductory treatment of the subject that also emphasizes recent penalized regression spline approaches to GAMs and the mixed model extensions of these models. Generalized Additive Models: An Introduction with R imparts a thorough understanding of the theory and practical applications of GAMs and related advanced models, enabling informed use of these very flexible tools. The author bases his approach on a framework of penalized regression splines, and builds a well-grounded foundation through motivating chapters on linear and generalized linear models. While firmly focused on the practical aspects of GAMs, discussions include fairly full explanations of the theory underlying the methods. Use of the freely available R software helps explain the theory and illustrates the practicalities of linear, generalized linear, and generalized additive models, as well as their mixed effect extensions. The treatment is rich with practical examples, and it includes an entire chapter on the analysis of real data sets using R and the author's add-on package mgcv. Each chapter includes exercises, for which complete solutions are provided in an appendix. Concise, comprehensive, and essentially self-contained, Generalized Additive Models: An Introduction with R prepares readers with the practical skills and the theoretical background needed to use and understand GAMs and to move on to other GAM-related methods and models, such as SS-ANOVA, P-splines, backfitting and Bayesian approaches to smoothing and additive modelling.
Author: Roel C. A. Oomen