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Non-linear time series models in empirical finance, Philip Hans Franses

Non-linear time series models in empirical finance

Автор: Philip Hans Franses
Название:  Non-linear time series models in empirical finance   (Нелинейный ряд времени в эмпирических финансах)
Издательство: Cambridge Academ
Классификация:
Эконометрика

ISBN: 0521779650
ISBN-13(EAN): 9780521779654
ISBN: 0-521-77965-0
ISBN-13(EAN): 978-0-521-77965-4
Обложка/Формат: Paperback
Страницы: 296
Вес: 0.59 кг.
Дата издания: 27.07.2000
Язык: ENG
Иллюстрации: 51 tables 44 figures
Размер: 24.49 x 17.37 x 1.91 cm
Читательская аудитория: Tertiary education (us: college)
Рейтинг:
Поставляется из: Англии
Описание: Although many of the models commonly used in empirical finance are linear, the nature of financial data suggests that non-linear models are more appropriate for forecasting and accurately describing returns and volatility. The enormous number of non-linear time series models appropriate for modeling and forecasting economic time series models makes choosing the best model for a particular application daunting. This classroom-tested advanced undergraduate and graduate textbook - the most up to-date and accessible guide available - provides a rigorous treatment of recently developed non-linear models, including regime-switching and artificial neural networks. The focus is on the potential applicability for describing and forecasting financial asset returns and their associated volatility. The models are analysed in detail and are not treated as ‘black boxes’. Illustrated using a wide range of financial data, drawn from sources including the financial markets of Tokyo, London and Frankfurt.
Описание: Reviews recently developed non-linear time series models, and their applications to financial markets.
Дополнительное описание: Subject: Economics, business studies / Econometrics, statistics
Readership: finance, econometrics, time series modelling, forecasting
Level: academic researchers, graduate students, professionals, undergraduate students
Format: 247 x 174 mm 296pp 51 tables 44 figures
Chapter Titles: 1. Introduction; 2. Some concepts in Time Series analysis; 3. Regime-switching models for returns; 4. Regime-Switching models for Volatility; 5. Artificial neural networks for returns; 6. Conclusion.



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Time Series Models for Business and Economic Forecasting

Автор: Franses Philip Hans
Название: Time Series Models for Business and Economic Forecasting
ISBN: 0521520916 ISBN-13(EAN): 9780521520911
Издательство: Cambridge Academ
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Название: Analysis of Financial Time Series
ISBN: 0470414359 ISBN-13(EAN): 9780470414354
Издательство: Wiley
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Наличие на складе: Поставка под заказ.
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Автор: Hamilton, James
Название: Time Series Analysis
ISBN: 0691042896 ISBN-13(EAN): 9780691042893
Издательство: Wiley
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Автор: Harvey, Andrew C.
Название: Forecasting, structural time series models and the kalman filter
ISBN: 0521405734 ISBN-13(EAN): 9780521405737
Издательство: Cambridge Academ
Цена: 4032 р.
Наличие на складе: Поставка под заказ.
Описание: This book is concerned with modelling economic and social time series and with addressing the special problems which the treatment of such series pose.
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Автор: Franses Philip Hans
Название: Time Series Models for Business and Economic Forecasting
ISBN: 0521817706 ISBN-13(EAN): 9780521817707
Издательство: Cambridge Academ
Цена: 7449 р.
Наличие на складе: Поставка под заказ.
Описание: With a new author team contributing decades of practical experience, this fully updated and thoroughly classroom-tested second edition textbook prepares students and practitioners to create effective forecasting models and master the techniques of time series analysis. Taking a practical and example-driven approach, this textbook summarises the most critical decisions, techniques and steps involved in creating forecasting models for business and economics. Students are led through the process with an entirely new set of carefully developed theoretical and practical exercises. Chapters examine the key features of economic time series, univariate time series analysis, trends, seasonality, aberrant observations, conditional heteroskedasticity and ARCH models, non-linearity and multivariate time series, making this a complete practical guide. Downloadable datasets are available online.
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ISBN: 0387946268 ISBN-13(EAN): 9780387946269
Издательство: Springer
Цена: 6157 р.
Наличие на складе: Нет в наличии.
Описание: Offers a survey of techniques in econometrics, which may be used to analyse semiparametric models. This book covers topics such as instrumental variable estimation, nonparametric density and regression function estimation, and semiparametric limited dependent variable models. It also explains how these methods may be implemented using software.
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ISBN: 047005316X ISBN-13(EAN): 9780470053164
Издательство: Wiley
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Описание: This groundbreaking book extends traditional approaches of risk measurement and portfolio optimization by combining distributional models with risk or performance measures into one framework. Throughout these pages, the expert authors explain the fundamentals of probability metrics, outline new approaches to portfolio optimization, and discuss a variety of essential risk measures. Using numerous examples, they illustrate a range of applications to optimal portfolio choice and risk theory, as well as appl cations to the area of computational finance that may be useful to financial engineers.
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Название: The Econometric Modelling of Financial Time Series
ISBN: 0521883814 ISBN-13(EAN): 9780521883818
Издательство: Cambridge Academ
Цена: 5697 р.
Наличие на складе: Поставка под заказ.
Описание: Terence Mills' best-selling graduate textbook provides detailed coverage of the latest research techniques and findings relating to the empirical analysis of financial markets. In its previous editions it has become required reading for many graduate courses on the econometrics of financial modelling. The third edition, co-authored with Raphael Markellos, contains a wealth of new material reflecting the developments of the last decade.

Particular attention is paid to the wide range of nonlinear models that are used to analyse financial data observed at high frequencies and to the long memory characteristics found in financial time series. The central material on unit root processes and the modelling of trends and structural breaks has been substantially expanded into a chapter of its own. There is also an extended discussion of the treatment of volatility, accompanied by a new chapter on nonlinearity and its testing.

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Название: The Econometric Analysis of Seasonal Time Series
ISBN: 0521562600 ISBN-13(EAN): 9780521562607
Издательство: Cambridge Academ
Цена: 4645 р.
Наличие на складе: Поставка под заказ.
Описание: Eric Ghysels and Denise R. Osborn provide a thorough and timely review of the recent developments in the econometric analysis of seasonal economic time series, summarizing a decade of theoretical advances in the area. The authors discuss the asymptotic distribution theory for linear nonstationary seasonal stochastic processes. They also cover the latest contributions to the theory and practice of seasonal adjustment, together with its implications for estimation and hypothesis testing. Moreover, a comprehensive analysis of periodic models is provided, including stationary and nonstationary cases. The book concludes with a discussion of some nonlinear seasonal and periodic models. The treatment is designed for an audience of researchers and advanced graduate students.
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Название: Applied Time Series Econometrics
ISBN: 052183919X ISBN-13(EAN): 9780521839198
Издательство: Cambridge Academ
Цена: 4383 р.
Наличие на складе: Поставка под заказ.
Описание: Time series econometrics is a rapidly evolving field. Particularly, the cointegration revolution has had a substantial impact on applied analysis. Hence, no textbook has managed to cover the full range of methods in current use and explain how to proceed in applied domains. This gap in the literature motivates the present volume. The methods are sketched out, reminding the reader of the ideas underlying them and giving sufficient background for empirical work. The treatment can also be used as a textbook for a course on applied time series econometrics. Topics include: unit root and cointegration analysis, structural vector autoregressions, conditional heteroskedasticity and nonlinear and nonparametric time series models. Crucial to empirical work is the software that is available for analysis. New methodology is typically only gradually incorporated into existing software packages. Therefore a flexible Java interface has been created, allowing readers to replicate the applications and conduct their own analyses.
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Автор: Plasmans
Название: Modern Linear and Nonlinear Econometrics
ISBN: 0387257608 ISBN-13(EAN): 9780387257600
Издательство: Springer
Цена: 13089 р.
Наличие на складе: Нет в наличии.
Описание: The basic characteristic of "Modern Linear and Nonlinear Econometrics" is that it presents a unified approach of modern linear and nonlinear econometrics in a concise and intuitive way. It covers four major parts of modern econometrics: linear and nonlinear estimation and testing, time series analysis, models with categorical and limited dependent variables, and, finally, a thorough analysis of linear and nonlinear panel data modeling. Distinctive features of this handbook are: a unified approach of both linear and nonlinear econometrics, with an integration of the theory and the practice in modern econometrics; emphasis on sound theoretical and empirical relevance and intuition; focus on econometric and statistical methods for the analysis of linear and nonlinear processes in economics and finance, including computational methods and numerical tools; completely worked out empirical illustrations are provided throughout, the macroeconomic and microeconomic (household and firm level) data sets of which are available from the internet; these empirical illustrations are taken from finance (e.g.

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patenting), business cycle analysis, monetary economics, housing economics, labor and educational economics (e.g. demand for teachers according to gender) and many others; exercises are added to the chapters, with a focus on the interpretation of results; several of these exercises involve the use of actual data that are ty ical for current empirical work and that are made available on the internet. What is also distinguishable in "Modern Linear and Nonlinear Econometrics" is that every major topic has a number of examples, exercises or case studies.

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ISBN: 0071224440 ISBN-13(EAN): 9780071224444
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