Essentials Of Time Series For Financial Applications

Author : Massimo Guidolin,Manuela Pedio
Publisher : Academic Press
Page : 435 pages
File Size : 55,6 Mb
Release : 2018-05-29
Category : Business & Economics
ISBN : 9780128134108

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Essentials of Time Series for Financial Applications by Massimo Guidolin,Manuela Pedio Pdf

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)

Author : Ruey S. Tsay
Publisher : John Wiley & Sons
Page : 414 pages
File Size : 46,7 Mb
Release : 2013-11-11
Category : Mathematics
ISBN : 9781118617755

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Multivariate Time Series Analysis by Ruey S. Tsay Pdf

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.

Author : Ruey S. Tsay
Publisher : John Wiley & Sons
Page : 724 pages
File Size : 52,7 Mb
Release : 2010-10-26
Category : Mathematics
ISBN : 9781118017098

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Analysis of Financial Time Series by Ruey S. Tsay Pdf

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.

Author : Frank J. Fabozzi,Sergio M. Focardi,Svetlozar T. Rachev,Bala G. Arshanapalli
Publisher : John Wiley & Sons
Page : 448 pages
File Size : 43,6 Mb
Release : 2014-03-04
Category : Business & Economics
ISBN : 9781118727232

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The Basics of Financial Econometrics by Frank J. Fabozzi,Sergio M. Focardi,Svetlozar T. Rachev,Bala G. Arshanapalli Pdf

An accessible guide to the growing field of financial econometrics As finance and financial products have become more complex, financial econometrics has emerged as a fast-growing field and necessary foundation for anyone involved in quantitative finance. The techniques of financial econometrics facilitate the development and management of new financial instruments by providing models for pricing and risk assessment. In short, financial econometrics is an indispensable component to modern finance. The Basics of Financial Econometrics covers the commonly used techniques in the field without using unnecessary mathematical/statistical analysis. It focuses on foundational ideas and how they are applied. Topics covered include: regression models, factor analysis, volatility estimations, and time series techniques. Covers the basics of financial econometrics—an important topic in quantitative finance Contains several chapters on topics typically not covered even in basic books on econometrics such as model selection, model risk, and mitigating model risk Geared towards both practitioners and finance students who need to understand this dynamic discipline, but may not have advanced mathematical training, this book is a valuable resource on a topic of growing importance.

Author : Julie Rodriguez,Piotr Kaczmarek
Publisher : John Wiley & Sons
Page : 480 pages
File Size : 47,8 Mb
Release : 2016-05-02
Category : Computers
ISBN : 9781118907856

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Visualizing Financial Data by Julie Rodriguez,Piotr Kaczmarek Pdf

A fresh take on financial data visualization for greater accuracy and understanding Your data provides a snapshot of the state of your business and is key to the success of your conversations, decisions, and communications. But all of that communication is lost — or incorrectly interpreted — without proper data visualizations that provide context and accurate representation of the numbers. In Visualizing Financial Data, authors Julie Rodriguez and Piotr Kaczmarek draw upon their understanding of information design and visual communication to show you how to turn your raw data into meaningful information. Coverage includes current conventions paired with innovative visualizations that cater to the unique requirements across financial domains, including investment management, financial accounting, regulatory reporting, sales, and marketing communications. Presented as a series of case studies, this highly visual guide presents problems and solutions in the context of real-world scenarios. With over 250 visualizations, you’ll have access to relevant examples that serve as a starting point to your implementations. • Expand the boundaries of data visualization conventions and learn new approaches to traditional charts and graphs • Optimize data communications that cater to you and your audience • Provide clarity to maximize understanding • Solve data presentation problems using efficient visualization techniques • Use the provided companion website to follow along with examples The companion website gives you the illustration files and the source data sets, and points you to the types of resources you need to get started.

Author : Jaydip Sen,Tamal Datta Chaudhuri
Publisher : Unknown
Page : 264 pages
File Size : 46,5 Mb
Release : 2017-08-23
Category : Electronic
ISBN : 3330653868

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Analysis and Forecasting of Financial Time Series Using R by Jaydip Sen,Tamal Datta Chaudhuri Pdf

Author : Gebhard Kirchgässner,Jürgen Wolters
Publisher : Springer Science & Business Media
Page : 288 pages
File Size : 47,8 Mb
Release : 2008-08-27
Category : Business & Economics
ISBN : 3540687351

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Introduction to Modern Time Series Analysis by Gebhard Kirchgässner,Jürgen Wolters Pdf

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.

Author : Peter J. Brockwell,Richard A. Davis
Publisher : Springer Science & Business Media
Page : 437 pages
File Size : 53,9 Mb
Release : 2006-04-10
Category : Computers
ISBN : 9780387216577

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Introduction to Time Series and Forecasting by Peter J. Brockwell,Richard A. Davis Pdf

This is an introduction to time series that emphasizes methods and analysis of data sets. The logic and tools of model-building for stationary and non-stationary time series are developed and numerous exercises, many of which make use of the included computer package, provide the reader with ample opportunity to develop skills. Statisticians and students will learn the latest methods in time series and forecasting, along with modern computational models and algorithms.

Author : Edward W. Frees
Publisher : Cambridge University Press
Page : 585 pages
File Size : 54,8 Mb
Release : 2010
Category : Business & Economics
ISBN : 9780521760119

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Regression Modeling with Actuarial and Financial Applications by Edward W. Frees Pdf

This book teaches multiple regression and time series and how to use these to analyze real data in risk management and finance.

Author : J. Michael Steele
Publisher : Springer Science & Business Media
Page : 303 pages
File Size : 52,7 Mb
Release : 2012-12-06
Category : Mathematics
ISBN : 9781468493054

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Stochastic Calculus and Financial Applications by J. Michael Steele Pdf

Stochastic calculus has important applications to mathematical finance. This book will appeal to practitioners and students who want an elementary introduction to these areas. From the reviews: "As the preface says, ‘This is a text with an attitude, and it is designed to reflect, wherever possible and appropriate, a prejudice for the concrete over the abstract’. This is also reflected in the style of writing which is unusually lively for a mathematics book." --ZENTRALBLATT MATH

Author : Aileen Nielsen
Publisher : O'Reilly Media
Page : 500 pages
File Size : 51,6 Mb
Release : 2019-09-20
Category : Computers
ISBN : 9781492041627

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Practical Time Series Analysis by Aileen Nielsen Pdf

Time series data analysis is increasingly important due to the massive production of such data through the internet of things, the digitalization of healthcare, and the rise of smart cities. As continuous monitoring and data collection become more common, the need for competent time series analysis with both statistical and machine learning techniques will increase. Covering innovations in time series data analysis and use cases from the real world, this practical guide will help you solve the most common data engineering and analysis challengesin time series, using both traditional statistical and modern machine learning techniques. Author Aileen Nielsen offers an accessible, well-rounded introduction to time series in both R and Python that will have data scientists, software engineers, and researchers up and running quickly. You’ll get the guidance you need to confidently: Find and wrangle time series data Undertake exploratory time series data analysis Store temporal data Simulate time series data Generate and select features for a time series Measure error Forecast and classify time series with machine or deep learning Evaluate accuracy and performance

Author : John Y. Campbell,Andrew W. Lo,A. Craig MacKinlay
Publisher : Princeton University Press
Page : 630 pages
File Size : 54,8 Mb
Release : 2012-06-28
Category : Business & Economics
ISBN : 9781400830213

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The Econometrics of Financial Markets by John Y. Campbell,Andrew W. Lo,A. Craig MacKinlay Pdf

The past twenty years have seen an extraordinary growth in the use of quantitative methods in financial markets. Finance professionals now routinely use sophisticated statistical techniques in portfolio management, proprietary trading, risk management, financial consulting, and securities regulation. This graduate-level textbook is intended for PhD students, advanced MBA students, and industry professionals interested in the econometrics of financial modeling. The book covers the entire spectrum of empirical finance, including: the predictability of asset returns, tests of the Random Walk Hypothesis, the microstructure of securities markets, event analysis, the Capital Asset Pricing Model and the Arbitrage Pricing Theory, the term structure of interest rates, dynamic models of economic equilibrium, and nonlinear financial models such as ARCH, neural networks, statistical fractals, and chaos theory. Each chapter develops statistical techniques within the context of a particular financial application. This exciting new text contains a unique and accessible combination of theory and practice, bringing state-of-the-art statistical techniques to the forefront of financial applications. Each chapter also includes a discussion of recent empirical evidence, for example, the rejection of the Random Walk Hypothesis, as well as problems designed to help readers incorporate what they have read into their own applications.

Author : Dr. Avishek Pal,Dr. PKS Prakash
Publisher : Packt Publishing Ltd
Page : 238 pages
File Size : 44,6 Mb
Release : 2017-09-28
Category : Computers
ISBN : 9781788294195

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Practical Time Series Analysis by Dr. Avishek Pal,Dr. PKS Prakash Pdf

Step by Step guide filled with real world practical examples. About This Book Get your first experience with data analysis with one of the most powerful types of analysis—time-series. Find patterns in your data and predict the future pattern based on historical data. Learn the statistics, theory, and implementation of Time-series methods using this example-rich guide Who This Book Is For This book is for anyone who wants to analyze data over time and/or frequency. A statistical background is necessary to quickly learn the analysis methods. What You Will Learn Understand the basic concepts of Time Series Analysis and appreciate its importance for the success of a data science project Develop an understanding of loading, exploring, and visualizing time-series data Explore auto-correlation and gain knowledge of statistical techniques to deal with non-stationarity time series Take advantage of exponential smoothing to tackle noise in time series data Learn how to use auto-regressive models to make predictions using time-series data Build predictive models on time series using techniques based on auto-regressive moving averages Discover recent advancements in deep learning to build accurate forecasting models for time series Gain familiarity with the basics of Python as a powerful yet simple to write programming language In Detail Time Series Analysis allows us to analyze data which is generated over a period of time and has sequential interdependencies between the observations. This book describes special mathematical tricks and techniques which are geared towards exploring the internal structures of time series data and generating powerful descriptive and predictive insights. Also, the book is full of real-life examples of time series and their analyses using cutting-edge solutions developed in Python. The book starts with descriptive analysis to create insightful visualizations of internal structures such as trend, seasonality and autocorrelation. Next, the statistical methods of dealing with autocorrelation and non-stationary time series are described. This is followed by exponential smoothing to produce meaningful insights from noisy time series data. At this point, we shift focus towards predictive analysis and introduce autoregressive models such as ARMA and ARIMA for time series forecasting. Later, powerful deep learning methods are presented, to develop accurate forecasting models for complex time series, and under the availability of little domain knowledge. All the topics are illustrated with real-life problem scenarios and their solutions by best-practice implementations in Python. The book concludes with the Appendix, with a brief discussion of programming and solving data science problems using Python. Style and approach This book takes the readers from the basic to advance level of Time series analysis in a very practical and real world use cases.

Author : Albert N. Shiryaev
Publisher : World Scientific
Page : 852 pages
File Size : 45,6 Mb
Release : 1999
Category : Business & Economics
ISBN : 9789810236052

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Essentials of Stochastic Finance by Albert N. Shiryaev Pdf

Readership: Undergraduates and researchers in probability and statistics; applied, pure and financial mathematics; economics; chaos.

Author : Eric Zivot,Jiahui Wang
Publisher : Springer Science & Business Media
Page : 632 pages
File Size : 55,7 Mb
Release : 2013-11-11
Category : Business & Economics
ISBN : 9780387217635

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Modeling Financial Time Series with S-PLUS by Eric Zivot,Jiahui Wang Pdf

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.