Book Description
Gain the statistical tools and techniques you need to understand today's financial markets with the Second Edition of this critically acclaimed book.
Youll find a comprehensive and systematic introduction to financial econometric models and their applications in modeling and predicting financial time series data. This edition continues to emphasize empirical financial data and focuses on real-world examples. Youll master key aspects of financial time series, including volatility modeling, neural network applications, market microstructure and high-frequency financial data, continuous-time models and Ito's Lemma, Value at Risk, multiple returns analysis, financial factor models, and econometric modeling via computation-intensive methods.
This is an ideal textbook for MBA students and a key reference for researchers and professionals in business and finance. Order your copy today.
Download Description
Analysis of Financial Time Series, Second Edition provides a comprehensive 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; and Bayesian inference in finance methods.
Customer Reviews:
Excellent and detailed reference.......2007-05-03
The coverage of the topic is broad and deep. It is one of the few introductory books that devotes some space to transfer function modeling and does so intelligibly.
A must have for the novice as well as those more familiar with the topic that need a solid reference.
The best for Masters level, great all-around.......2007-02-12
This text is absolutely perfect for Masters students learning financial econometrics. There is a little theory, clear explanations, and quite a few real world examples. (I don't think any text would tell the reader what model to use when, because that's application-specific.) It assumes some knowledge of finance and basic econometrics/statistics, which is fair enough. To get more theory, Hamilton (1994) remains the authority, and Campbell, Lo, MacKinlay (1997) is a great introduction for PhD students, and generally an ideal companion volume to this one.
Excellent reference!.......2006-11-05
This book is an excellent toolbox for anyove dealing in the field of financial engineering, however, as a real toolbox, the author doesn't explain the exact use of all tools and how to interpret the results. This is why this book is for advanced users who need a well documented reference but it is not very suitable for beginners in the field. The Splus code is welcome.
Broad coverage, but not for the faint-hearted.......2006-07-05
Written by a University of Chicago professor, this book comprehensively covers times series topics relative to investment and trading-oriented finance (i.e., Wall Street money-making machines). Treatment is generally clear and thorough, but an advanced math and stat background is an absolute prerequisite for understanding the materials.
S-Plus/R code is given, but strangely, there is very little on *why* and
*when* one uses each of the techniques. Under what cirmcustances should I use or not use GARCH? What exactly is PCA good for in real-world applications? These important questions are not answered, in other words, you don't get a sense of the real-world context for these topics.
Best textbook I have ever read .......2005-09-19
First of all, it is well written in a very practical point of view. The whole book is aimed fullly to real financial data(appended in the author's web). People can gain not only the well-explained theories but the hand-on experience with data analysis using SPLUS or any other package.
Secondly, the author is a real expert in this field and has been publishing lots of nice work. All models in the book are clearly illustrated and commented.
Thirdly, it covers a lot of topics in analysis of FT. Reader can learn almost all the valuable things in this field from this book.
If anyone wanna truly learn this book, she/he has to sit down and plays some real data on computer. I think this is the best way and the only way to use this book.
Average customer rating:
- modelling financial instruments
- good analysis on data error.
- From the experts in the field
- For the new millenium...that's what we need.
- More Than An Introduction
|
An Introduction to High-Frequency Finance
Ramazan Gençay ,
Michel Dacorogna ,
Ulrich A. Muller ,
Olivier Pictet , and
Richard Olsen
Manufacturer: Academic Press
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Similar Items:
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Analysis of Financial Time Series, 2nd Edition (Wiley Series in Probability and Statistics)
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Trading and Exchanges: Market Microstructure for Practitioners
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An Introduction to Wavelets and Other Filtering Methods in Finance and Economics
ASIN: 0122796713 |
Book Description
Liquid markets generate hundreds or thousands of ticks (the minimum change in price a security can have, either up or down) every business day. Data vendors such as Reuters transmit more than 275,000 prices per day for foreign exchange spot rates alone. Thus, high-frequency data can be a fundamental object of study, as traders make decisions by observing high-frequency or tick-by-tick data. Yet most studies published in financial literature deal with low frequency, regularly spaced data. For a variety of reasons, high-frequency data are becoming a way for understanding market microstructure. This book discusses the best mathematical models and tools for dealing with such vast amounts of data.
This book provides a framework for the analysis, modeling, and inference of high frequency financial time series. With particular emphasis on foreign exchange markets, as well as currency, interest rate, and bond futures markets, this unified view of high frequency time series methods investigates the price formation process and concludes by reviewing techniques for constructing systematic trading models for financial assets.
Customer Reviews:
modelling financial instruments.......2007-03-08
The book gives an indepth statistical modelling of important financial events, that have time dependency. It is suitable for the financial analyst who wants a semi-empirical approach.
For some quantities, like foreign exchange data, there is a comparison between fully empirical results and various theoretical models. What is investigated are such behaviours like scaling laws, for the absolute returns as a function of frequency. Here, it has been empirically observed that scalings do exist for FX rates.
Whenever possible, the book gives rigorous results, often encapsulated in theorems relating to distributions of independently distributed random variables. The reader should have a background in statistics, with the equivalent of several years of undergraduate courses.
good analysis on data error........2007-01-16
Many type of error the book list are frequently occur in FX data.
This book give good guide on how to filter them.
From the experts in the field.......2002-06-06
Michel Dacorogna and the team at the former Olsen & Associates are well-known experts in the field of foreign exchange rate data analysis, and their book provides us with a vast, useful source of information. Unfortunately for students and other beginners, the book is written like a compilation of papers and review articles, the opposite of pedagogical, and with an awful choice of 'computerese' notation (MA(t,n)=sum(EMA(t',k)... etc) that makes Boudhaud-Potters look easy in comparison. More to the point, even their noncomputerese notation is difficult to follow. I hope for a very different second edition written pedagogically for students of this growing and important field. On the positive side, data analyses are performed using logarithmic returns, not price increments. Workers in the field who consult this text will find it helpful.
For the new millenium...that's what we need........2001-07-23
The book covers a wide range of topics related to high-frequency data in Finance. There is a very detailed approach to tackle a huge amount of data and to deal with its based stylized facts. The book triggers the reader's desire to update his knowledge in the field of finance.
More Than An Introduction.......2001-05-28
This one of the few books on high frequency finance is a most welcome to the literature. The book is useful not only for people who are new to the subject but also for researchers in the field since it is a most uniform treatment of many topics. From adaptive data cleaning (chapter 4) to intraday and weekly seasonality (chapter 6) and real time trading models (chapter 11), it covers a broad range of topics specific to high frequency financial time series analysis. Chapters on volatility modeling (Chapter 8), forecasting (chapter 9) and correlation and multivariate risk (chapter 10) are enlightening especially for risk exposure analysis and risk management purposes. Finally, the the extensive bibliography is a precious source for those who would like to explore certain topics in detail. I highly recommend it for practitioners as well as researchers in the field.
Book Description
Fully revised and updated, the second edition of the best-selling The Econometric Modelling of Financial Time Series provides comprehensive coverage of the variety of models currently used in the empirical analysis of financial markets. Covering bond, equity and financial markets, it is essential for scholars and practitioners wishing to acquire an understanding of the latest research techniques and findings in the field, and also graduate students wishing to research in financial markets. It provides many examples to illustrate techniques that are only just emerging in the technical literature.
Download Description
Fully revised and updated, the second edition of the best-selling The Econometric Modelling of Financial Time Series provides comprehensive coverage of the variety of models currently used in the empirical analysis of financial markets. Covering bond, equity and financial markets, it is essential for scholars and practitioners wishing to acquire an understanding of the latest research techniques and findings in the field, and also graduate students wishing to research in financial markets. It provides many examples to illustrate techniques that are only just emerging in the technical literature.
Customer Reviews:
Poorly Written and Unclear.......2001-01-10
Obviously patched together from topics written over a period of time, this book is not cohesive nor understandable. Mills doesn't spend any words developing his topics nor explaning the development. Spend your resources on Hamilton's classic and great definative bible, Time Series Analysis instead.
it's a terrific book for non-linear time series analysis.......2000-04-06
This is a very compact, practical book. It edits in a very readable way. What I like it most is that it contributes to non-linear time series analysis a lot, whereas not too many other time series related books do. The real data in the appendix can be downloaded and played around by the readers. You will really have a great time to read it.
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.
Customer Reviews:
Good summary of models and live examples.......2007-08-14
I side with Yin Luo: this book is a good mixture of basic theory and fairly complicated, real-life examples. Actually, it can even be used as a tool to refresh one's theoretical "model specification database" because it covers a wide range of many families of models in a single book. However, being mainly a S+FinMetrics manual, it doesn't go so far as to show how to make a choice among a few competing models. Apparently, one has to have a certain theoretical background before he/she can benefit from the undoubtedly great power of S+FinMetrics.
Great applied econometrics book, even without FinMetrics!.......2006-10-09
Zivot and Wang have done a phenomenal job of covering intermediate to advanced topics in econometrics along with the S programming language. Extensive literature reviews are coupled with robust examples and mathematics, and topped off with S code. I am a quantitative hedge fund manager, and I use the Open Source R package [..] and RMetrics [..]. I can adapt every single excercise in "Modeling Financial Time Series with S-PLUS" to use in R, and make use of them in my work. If I have one complaint it is that the book does not cover non-linear models like quantile regression or least squares, or optimization for much more than trivial two or three asset portfolios.
Deceptive Title.......2005-01-30
As other reviewers have mentioned, this book is useless without FinMetrics. It is merely a user manual for that package, and has hardly any intrinsic value on its own.
Useless without FinMetrics module.......2003-10-27
This book is useless without the S+FinMetrics module.I wish I knew that in advance. Moreover, you can download it for free on www.insightful.com
WITHOUT S+FinMetrics module.......2003-10-07
This book does NOT come with the S+FinMetrics module. This book contains reviews of advanced time series theory, however, without S+FinMetrics module some part of the book is not insightful. This book is also not of financilal econometrics because there is no financial theory. This is a very good time series book if it comes with S+FinMetrics module.
Book Description
This book--an overview of contemporary topics related to the modelling of financial time series--is set against a backdrop of rapid expansions of interest in both the models themselves and the financial problems to which they are applied.
The book forms part of a new series of upper level textbooks, Routledge Advanced Texts in Economics and Finance and includes the following features:
* an exposition of the use of three popular computer packages used for econometric estimation - including Microfit
* end of chapter points for discussion
* contexts that provide background.
Customer Reviews:
Financially Viable.......2003-03-14
This is the first book of its kind on the market and it was a real relief to see it when it came out. It covers everything an advanced student of financial econometrics needs to know and does so with impressive mathematical clarity.
I can see this book doing very well indeed, and the contents list alone should be enough to recommend it.
Book Description
Nonlinear Modelling of High Frequency Financial Time Series Edited by Christian Dunis and Bin Zhou In the competitive and risky environment of today's financial markets, daily prices and models based upon low frequency price series data do not provide the level of accuracy required by traders and a growing number of risk managers. To improve results, more and more researchers and practitioners are turning to high frequency data. Nonlinear Modelling of High Frequency Financial Time Series presents the latest developments and views of leading international researchers and market practitioners, in modelling high frequency data in finance. Combining both nonlinear modelling and intraday data for financial markets, the editors provide a fascinating foray into this extremely popular discipline. This book evolves around four major themes. The first introductory section focuses on high frequency financial data. The second part examines the exact nature of the time series considered: several linearity tests are presented and applied and their modelling implications assessed. The third and fourth parts are dedicated to modelling and forecasting these financial time series.
Average customer rating:
|
Neural Network Time Series: Forecasting of Financial Markets
E. Michael Azoff
Manufacturer: John Wiley & Sons
ProductGroup: Book
Binding: Hardcover
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ASIN: 0471943568 |
Customer Reviews:
Better than I expected.......1997-02-26
A good introduction to neural nets and their applicability tothe futures markets. Provides mathematical/theoretical basis fortechniques involved in neural net training, testing, chaos and touches on nonlinear systems in general. Also provides interesting benchmarks of several nets against several time series. Great bibliography. Includes Fortran source code for running trained nets but not for training a net.
Book Description
The editors are pleased to offer the following papers to the reader in recognition and appreciation of the contributions to our literature made by Robert Engle and Sir Clive Granger, winners of the 2003 Nobel Prize in Economics. The basic themes of this part of Volume 20 of Advances in Econometrics are time varying betas of the capital asset pricing model, analysis of predictive densities of nonlinear models of stock returns, modelling multivariate dynamic correlations, flexible seasonal time series models, estimation of long-memory time series models, the application of the technique of boosting in volatility forecasting, the use of different time scales in GARCH modelling, out-of-sample evaluation of the Fed Model in stock price valuation, structural change as an alternative to long memory, the use of smooth transition auto-regressions in stochastic volatility modelling, the analysis of the balanced-ness of regressions analyzing Taylor-Type rules of the Fed Funds rate, a mixture-of-experts approach for the estimation of stochastic volatility, a modern assessment of Clives first published paper on Sunspot activity, and a new class of models of tail-dependence in time series subject to jumps.
*This Series: Aids in the diffusion of new econometric techniques
* Emphasis is placed on expositional clarity and ease of assimilation for readers who are unfamiliar with a given topic of a volume
*Illustrates new concepts
Book Description
The editors are pleased to offer the following papers to the reader in recognition and appreciation of the contributions to our literature made by Robert Engle and Sir Clive Granger, winners of the 2003 Nobel Prize in Economics. The basic themes of this part of Volume 20 of Advances in Econometrics are time varying betas of the capital asset pricing model, analysis of predictive densities of nonlinear models of stock returns, modelling multivariate dynamic correlations, flexible seasonal time series models, estimation of long-memory time series models, the application of the technique of boosting in volatility forecasting, the use of different time scales in GARCH modelling, out-of-sample evaluation of the Fed Model in stock price valuation, structural change as an alternative to long memory, the use of smooth transition auto-regressions in stochastic volatility modelling, the analysis of the balanced-ness of regressions analyzing Taylor-Type rules of the Fed Funds rate, a mixture-of-experts approach for the estimation of stochastic volatility, a modern assessment of Clives first published paper on Sunspot activity, and a new class of models of tail-dependence in time series subject to jumps.
*This Series: Aids in the diffusion of new econometric techniques
*Emphasis is placed on expositional clarity and ease of assimilation for readers who are unfamiliar with a given topic of a volume
*Illustrates new concepts
Average customer rating:
|
Financial control by time absorption analysis: A tool for profit control (Small business management series ; no. 37)
Cole D Neff
Manufacturer: Small Business Administration : for sale by the Supt. of Docs., U.S. Govt. Print. Off
ProductGroup: Book
Binding: Unknown Binding
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ASIN: B0006CRYRO |
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