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Modeling Financial Time Series with S-PLUS

Author: Eric Zivot

Publisher: Springer Science & Business Media

Published: 2013-11-11

Total Pages: 632

ISBN-13: 0387217630

The field of financial econometrics has exploded over the last decade This book represents an integration of theory, methods, and examples using the S-PLUS statistical modeling language and the S+FinMetrics module to facilitate the practice of financial econometrics. This is the first book to show the power of S-PLUS for the analysis of time series data. It is written for researchers and practitioners in the finance industry, academic researchers in economics and finance, and advanced MBA and graduate students in economics and finance. Readers are assumed to have a basic knowledge of S-PLUS and a solid grounding in basic statistics and time series concepts. This Second Edition is updated to cover S+FinMetrics 2.0 and includes new chapters on copulas, nonlinear regime switching models, continuous-time financial models, generalized method of moments, semi-nonparametric conditional density models, and the efficient method of moments. Eric Zivot is an associate professor and Gary Waterman Distinguished Scholar in the Economics Department, and adjunct associate professor of finance in the Business School at the University of Washington. He regularly teaches courses on econometric theory, financial econometrics and time series econometrics, and is the recipient of the Henry T. Buechel Award for Outstanding Teaching. He is an associate editor of Studies in Nonlinear Dynamics and Econometrics. He has published papers in the leading econometrics journals, including Econometrica, Econometric Theory, the Journal of Business and Economic Statistics, Journal of Econometrics, and the Review of Economics and Statistics. Jiahui Wang is an employee of Ronin Capital LLC. He received a Ph.D. in Economics from the University of Washington in 1997. He has published in leading econometrics journals such as Econometrica and Journal of Business and Economic Statistics, and is the Principal Investigator of National Science Foundation SBIR grants. In 2002 Dr. Wang was selected as one of the "2000 Outstanding Scholars of the 21st Century" by International Biographical Centre.

Modelling Financial Time Series

Author: Stephen J. Taylor

Publisher: World Scientific

Published: 2008

Total Pages: 297

ISBN-13: 9812770852

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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. Sample Chapter(s). Chapter 1: Introduction (1,134 KB). Contents: Features of Financial Returns; Modelling Price Volatility; Forecasting Standard Deviations; The Accuracy of Autocorrelation Estimates; Testing the Random Walk Hypothesis; Forecasting Trends in Prices; Evidence Against the Efficiency of Futures Markets; Valuing Options; Appendix: A Computer Program for Modelling Financial Time Series. Readership: Academic researchers in finance & economics; quantitative analysts.

Modelling Financial Time Series

Author: Stephen J. Taylor

Publisher: World Scientific

Published: 2008

Total Pages: 297

ISBN-13: 9812770844

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Analysis of Financial Time Series

Author: Ruey S. Tsay

Publisher: John Wiley & Sons

Published: 2010-10-26

Total Pages: 724

ISBN-13: 1118017099

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This book provides a broad, mature, and systematic introduction to current financial econometric models and their applications to modeling and prediction of financial time series data. It utilizes real-world examples and real financial data throughout the book to apply the models and methods described. The author begins with basic characteristics of financial time series data before covering three main topics: Analysis and application of univariate financial time series The return series of multiple assets Bayesian inference in finance methods Key features of the new edition include additional coverage of modern day topics such as arbitrage, pair trading, realized volatility, and credit risk modeling; a smooth transition from S-Plus to R; and expanded empirical financial data sets. The overall objective of the book is to provide some knowledge of financial time series, introduce some statistical tools useful for analyzing these series and gain experience in financial applications of various econometric methods.

Asset Price Dynamics, Volatility, and Prediction

Author: Stephen J. Taylor

Publisher: Princeton University Press

Published: 2011-02-11

Total Pages: 544

ISBN-13: 1400839254

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This book shows how current and recent market prices convey information about the probability distributions that govern future prices. Moving beyond purely theoretical models, Stephen Taylor applies methods supported by empirical research of equity and foreign exchange markets to show how daily and more frequent asset prices, and the prices of option contracts, can be used to construct and assess predictions about future prices, their volatility, and their probability distributions. Stephen Taylor provides a comprehensive introduction to the dynamic behavior of asset prices, relying on finance theory and statistical evidence. He uses stochastic processes to define mathematical models for price dynamics, but with less mathematics than in alternative texts. The key topics covered include random walk tests, trading rules, ARCH models, stochastic volatility models, high-frequency datasets, and the information that option prices imply about volatility and distributions. Asset Price Dynamics, Volatility, and Prediction is ideal for students of economics, finance, and mathematics who are studying financial econometrics, and will enable researchers to identify and apply appropriate models and methods. It will likewise be a valuable resource for quantitative analysts, fund managers, risk managers, and investors who seek realistic expectations about future asset prices and the risks to which they are exposed.

The Econometric Modelling of Financial Time Series

Author: Terence C. Mills

Publisher: Cambridge University Press

Published: 1995-04-20

Total Pages: 255

ISBN-13: 9780521422574

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This book provides detailed coverage of the variety of models that are currently being used in the empirical analysis of financial markets. Covering bond equity and foreign exchange markets, it is aimed at scholars and practitioners wishing to acquire an understanding of the latest research techniques and findings in the field, and also at graduate students wishing to research in financial markets. The book is divided into two main sections, covering univariate models, and econometric and multivariate techniques respectively. In the former, the areas covered include linear and non-linear stochastic models, random walk, unit root tests, GARCH models, deterministic chaos, trend reversion, and bubbles. In the latter, regression models, time varying parameter models, the Kalman filter, vector autoregressions, present value models, and cointegration are discussed.

Handbook of Financial Time Series

Author: Torben Gustav Andersen

Publisher: Springer Science & Business Media

Published: 2009-04-21

Total Pages: 1045

ISBN-13: 3540712976

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The Handbook of Financial Time Series gives an up-to-date overview of the field and covers all relevant topics both from a statistical and an econometrical point of view. There are many fine contributions, and a preamble by Nobel Prize winner Robert F. Engle.

Modelling Trends and Cycles in Economic Time Series

Author: T. Mills

Publisher: Springer

Published: 2003-05-15

Total Pages: 178

ISBN-13: 0230595529

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Modelling trends and cycles in economic time series has a long history, with the use of linear trends and moving averages forming the basic tool kit of economists until the 1970s. Several developments in econometrics then led to an overhaul of the techniques used to extract trends and cycles from time series. Terence Mills introduces these various approaches to allow students and researchers to appreciate the variety of techniques and the considerations that underpin their choice for modelling trends and cycles.

Introduction to Modern Time Series Analysis

Author: Gebhard Kirchgässner

Publisher: Springer Science & Business Media

Published: 2008-08-27

Total Pages: 288

ISBN-13: 9783540687351

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This book presents modern developments in time series econometrics that are applied to macroeconomic and financial time series. It contains the most important approaches to analyze time series which may be stationary or nonstationary.

Economic Time Series

Author: William R. Bell

Publisher: CRC Press

Published: 2018-11-14

Total Pages: 544

ISBN-13: 1439846588

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Economic Time Series: Modeling and Seasonality is a focused resource on analysis of economic time series as pertains to modeling and seasonality, presenting cutting-edge research that would otherwise be scattered throughout diverse peer-reviewed journals. This compilation of 21 chapters showcases the cross-fertilization between the fields of time s