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Modelling Time Series Counts Data in Financial Microstructure

Modelling Time Series Counts Data in Financial Microstructure PDF Author: Andreas Heinen
Publisher:
ISBN:
Category : Analysis of variance
Languages : en
Pages : 268

Book Description


Modelling Time Series Counts Data in Financial Microstructure

Modelling Time Series Counts Data in Financial Microstructure PDF Author: Andreas Heinen
Publisher:
ISBN:
Category : Analysis of variance
Languages : en
Pages : 268

Book Description


Analysis of Financial Time Series

Analysis of Financial Time Series PDF Author: Ruey S. Tsay
Publisher: John Wiley & Sons
ISBN: 0471746185
Category : Business & Economics
Languages : en
Pages : 576

Book Description
Provides statistical tools and techniques needed to understandtoday's financial markets The Second Edition of this critically acclaimed text provides acomprehensive and systematic introduction to financial econometricmodels and their applications in modeling and predicting financialtime series data. This latest edition continues to emphasizeempirical financial data and focuses on real-world examples.Following this approach, readers will master key aspects offinancial time series, including volatility modeling, neuralnetwork applications, market microstructure and high-frequencyfinancial data, continuous-time models and Ito's Lemma, Value atRisk, multiple returns analysis, financial factor models, andeconometric modeling via computation-intensive methods. The author begins with the basic characteristics of financialtime series data, setting the foundation for the three maintopics: Analysis and application of univariate financial timeseries Return series of multiple assets Bayesian inference in finance methods This new edition is a thoroughly revised and updated text,including the addition of S-Plus® commands and illustrations.Exercises have been thoroughly updated and expanded and include themost current data, providing readers with more opportunities to putthe models and methods into practice. Among the new material addedto the text, readers will find: Consistent covariance estimation under heteroscedasticity andserial correlation Alternative approaches to volatility modeling Financial factor models State-space models Kalman filtering Estimation of stochastic diffusion models The tools provided in this text aid readers in developing adeeper understanding of financial markets through firsthandexperience in working with financial data. This is an idealtextbook for MBA students as well as a reference for researchersand professionals in business and finance.

Modeling Financial Time Series with S-PLUS

Modeling Financial Time Series with S-PLUS PDF Author: Eric Zivot
Publisher: Springer Science & Business Media
ISBN: 0387217630
Category : Business & Economics
Languages : en
Pages : 632

Book Description
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 and Forecasting High Frequency Financial Data

Modelling and Forecasting High Frequency Financial Data PDF Author: Stavros Degiannakis
Publisher: Springer
ISBN: 1137396490
Category : Business & Economics
Languages : en
Pages : 411

Book Description
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.

Modeling Market Microstructure Time Series

Modeling Market Microstructure Time Series PDF Author: Joel Hasbrouck
Publisher:
ISBN:
Category :
Languages : en
Pages : 76

Book Description
Microstructure data typically consist of trades and bid and offer quotes for financial securities that are collected at fine sampling intervals (often within the day). This paper reviews approaches taken to modeling these data. The emphasis is on the techniques of stationary multivariate time series analysis: autoregressive and moving average representations o f standard microstructure models, vector autoregressive estimation, random-walk decompositions and cointegration. The paper also discusses the challenges posed by irregular observation frequencies, discreteness and nonlinearity.

Modelling Financial Time Series

Modelling Financial Time Series PDF Author: Stephen J. Taylor
Publisher: World Scientific
ISBN: 9812770844
Category : Business & Economics
Languages : en
Pages : 297

Book Description
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.

Introduction to Modern Time Series Analysis

Introduction to Modern Time Series Analysis PDF Author: Gebhard Kirchgässner
Publisher: Springer Science & Business Media
ISBN: 3642334350
Category : Business & Economics
Languages : en
Pages : 326

Book Description
This book presents modern developments in time series econometrics that are applied to macroeconomic and financial time series, bridging the gap between methods and realistic applications. It presents the most important approaches to the analysis of time series, which may be stationary or nonstationary. Modelling and forecasting univariate time series is the starting point. For multiple stationary time series, Granger causality tests and vector autogressive models are presented. As the modelling of nonstationary uni- or multivariate time series is most important for real applied work, unit root and cointegration analysis as well as vector error correction models are a central topic. Tools for analysing nonstationary data are then transferred to the panel framework. Modelling the (multivariate) volatility of financial time series with autogressive conditional heteroskedastic models is also treated.

Nonlinear Time Series Analysis of Economic and Financial Data

Nonlinear Time Series Analysis of Economic and Financial Data PDF Author: Philip Rothman
Publisher: Springer Science & Business Media
ISBN: 0792383796
Category : Business & Economics
Languages : en
Pages : 394

Book Description
Nonlinear Time Series Analysis of Economic and Financial Data provides an examination of the flourishing interest that has developed in this area over the past decade. The constant theme throughout this work is that standard linear time series tools leave unexamined and unexploited economically significant features in frequently used data sets. The book comprises original contributions written by specialists in the field, and offers a combination of both applied and methodological papers. It will be useful to both seasoned veterans of nonlinear time series analysis and those searching for an informative panoramic look at front-line developments in the area.

Multivariate Time Series Analysis

Multivariate Time Series Analysis PDF Author: Ruey S. Tsay
Publisher: John Wiley & Sons
ISBN: 1118617754
Category : Mathematics
Languages : en
Pages : 414

Book Description
An accessible guide to the multivariate time series tools used in numerous real-world applications Multivariate Time Series Analysis: With R and Financial Applications is the much anticipated sequel coming from one of the most influential and prominent experts on the topic of time series. Through a fundamental balance of theory and methodology, the book supplies readers with a comprehensible approach to financial econometric models and their applications to real-world empirical research. Differing from the traditional approach to multivariate time series, the book focuses on reader comprehension by emphasizing structural specification, which results in simplified parsimonious VAR MA modeling. Multivariate Time Series Analysis: With R and Financial Applications utilizes the freely available R software package to explore complex data and illustrate related computation and analyses. Featuring the techniques and methodology of multivariate linear time series, stationary VAR models, VAR MA time series and models, unitroot process, factor models, and factor-augmented VAR models, the book includes: • Over 300 examples and exercises to reinforce the presented content • User-friendly R subroutines and research presented throughout to demonstrate modern applications • Numerous datasets and subroutines to provide readers with a deeper understanding of the material Multivariate Time Series Analysis is an ideal textbook for graduate-level courses on time series and quantitative finance and upper-undergraduate level statistics courses in time series. The book is also an indispensable reference for researchers and practitioners in business, finance, and econometrics.

Essentials of Time Series for Financial Applications

Essentials of Time Series for Financial Applications PDF Author: Massimo Guidolin
Publisher: Academic Press
ISBN: 0128134100
Category : Business & Economics
Languages : en
Pages : 435

Book Description
Essentials of Time Series for Financial Applications serves as an agile reference for upper level students and practitioners who desire a formal, easy-to-follow introduction to the most important time series methods applied in financial applications (pricing, asset management, quant strategies, and risk management). Real-life data and examples developed with EViews illustrate the links between the formal apparatus and the applications. The examples either directly exploit the tools that EViews makes available or use programs that by employing EViews implement specific topics or techniques. The book balances a formal framework with as few proofs as possible against many examples that support its central ideas. Boxes are used throughout to remind readers of technical aspects and definitions and to present examples in a compact fashion, with full details (workout files) available in an on-line appendix. The more advanced chapters provide discussion sections that refer to more advanced textbooks or detailed proofs. Provides practical, hands-on examples in time-series econometrics Presents a more application-oriented, less technical book on financial econometrics Offers rigorous coverage, including technical aspects and references for the proofs, despite being an introduction Features examples worked out in EViews (9 or higher)