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 ,
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Richard Olsen
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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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Market Models: A Guide to Financial Data Analysis
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Trading and Exchanges: Market Microstructure for Practitioners
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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
This book is aimed at the reader who wishes to gain a working knowledge of time series and forecasting methods as applied in economics, engineering, and the natural and social sciences. The book assumes knowledge only of basic calculus, matrix algebra and elementary statistics. This second edition contains detailed instructions on the use of the new totally windows-based computer package ITSM2000, the student version of which is included with the text. Expanded treatments are also given of several topics treated only briefly in the first edition. These include regression with time series errors, which plays an important role in forecasting and inference, and ARCH and GARCH models, which are widely used for the modeling of financial time series. These models can be fitted using the new version of ITSM. The core of the book covers stationary processes, ARMA and ARIMA processes, multivariate time series and state-space models, with an optional chapter on spectral analysis. Additional topics include the Burg and Hannan-Rissanen algorithms, unit roots, the EM algorithm, structural models, generalized state-space models with applications to time series of count data, exponential smoothing, the Holt-Winters and ARAR forecasting algorithms, transfer function models and intervention analysis. Brief introductions are also given to cointegration and to non-linear, continuous-time and long-memory models.
Customer Reviews:
good basic intro.......2006-11-10
A decent basic introduction covering a lot of topics. It's much more accessible for learning the subject for the first time then many other books which pile on the mathematical notation and obscure the actual meaning of things. The accompanying CD is very nice, although it gets annoying very fast that you're restricted to very small dataset sizes---but it does help in learning. The only two things that are somewhat of a problem with this book are 1) many times, rather than clearly stating "here's the algorithm you need to implement", you are referred to 3 or 4 other sections of the book for pieces of the algorithm, often without a clear explanation of exactly how that earlier section is supposed to be worked into the current desired algorithm and 2) there aren't a lot of practical insights as to how to actually initialize many of the algorithms (everything is great if you already know all the parameters in advance but starting from scratch with just raw data isn't dealt with I think as fully as would be useful). All in all, though, the book is helpful and, as I said, very good for learning the essential concepts for the first time.
When is an Introduction not an Introduction?.......2006-11-05
In the process of building a website targeted to those good folks that are striving valiantly to make a living through Internet marketing, you might think that an early objective would be to assemble a library of good reference material. After all, if you are planning on providing sensible information to your readers, then you should have a few good text books on hand to refer to when you need to be sure that some little tidbit of information might actually work. Well, at least I did. So, I have been scouring the Internet for textbook on the subject of Forecasting, which we share a common interest in. I have purchased a few and, for the most part, they are really quite informative and will be useful when the time comes. There is, however, an exception to this.
One book I purchased bears the title "Introduction to Time Series and Forecasting, Brockwell, Peter J and Richard A Davis". Being an intelligent sort of chap, I naturally took the word "Introduction" to mean just that. You know, you've been introduced to people before and becoming introduced usually means that 1. You look at the face. 2. You grasp their hand and shake firmly and 3. You exchange pleasantries, such as "Hello, it's nice to meet you".
Now, I never blame the person making the introduction if the relationship doesn't work out. After all, it's not their fault that two people hopefully sharing a common interest (after all, why bother making an introduction?) aren't all that compatible. There are likely to be many reasons for the incompatibility, the first of which could be that people travel in different circles and your circle isn't ever going to be part of their circle. Sort of an exclusionary relationship, you might say. And, not to be overly judgmental of others, of course, there may be plenty of good reasons for that. If everyone existed in one social circle, after all, the world would be beyond boring.
Anyways, the text book is a wonderful creation, that is, if you're a post-graduate or doctoral candidate. Upon opening the cover, expecting to be warmly introduced, I was rather amazed at the depth of equations and formulas gracing practically every page. I felt intimidated immediately. Remember the movie "The Ring"? This had to be rocket science, or more correctly, forecasting science at its most extreme! Wow! I should have really paid more attention during my statistics classes. So, I quickly closed the cover and tried to get a refund from the seller. Note the word Tried here. They didn't want it back either.
The good Post-Grand and PhD. candidates of the science of forecasting probably don't need an "Introduction" to Time Series and Forecasting. Next time I buy a book, I think I'll look for something with "Sandbox" in the title.
May all your Forecasts be Good Forecasts at [...]
Awesome.......2006-08-04
this book is excellent because it provides us with many examples and detailed explanations.
Not sure if it is introductory.......2005-12-24
I think the book is not written in a very organized way. It's not a book for picking up time series quickly. It's saturated with information, which I'm not sure if it's necessary for implementation. I have no problem following the math, however, if I want to pick up something and implement it within a day or two, the book is a bit harder to digest. Wouldn't think this is an undergraduate course book as it covers convergence in probability or mean-squared, which I learnt in PhD courses, not even master level.
Great book for a great price.......2004-02-12
This is one of those books that you can't find much cons to it. The book is inexpensive, and it's unbelievably lightweight. The material is rich, and yet easy to understand. The author actually brings you step by step from elementary to theorectical proofs.
Book Description
Integrating a contemporary approach to econometrics with the powerful computational tools offered by Stata, An Introduction to Modern Econometrics Using Stata focuses on the role of method-of-moments estimators, hypothesis testing, and specification analysis and provides practical examples that show how the theories are applied to real data sets using Stata. As an expert in Stata, the author successfully guides readers from the basic elements of Stata to the core econometric topics. He first describes the fundamental components needed to effectively use Stata. The book then covers the multiple linear regression model, linear and nonlinear Wald tests, constrained least-squares estimation, Lagrange multiplier tests, and hypothesis testing of nonnested models. Subsequent chapters center on the consequences of failures of the linear regression model's assumptions. The book also examines indicator variables, interaction effects, weak instruments, underidentification, and generalized method-of-moments estimation. The final chapters introduce panel-data analysis and discrete- and limited-dependent variables and the two appendices discuss how to import data into Stata and Stata programming. Presenting many of the econometric theories used in modern empirical research, this introduction illustrates how to apply these concepts using Stata. The book serves both as a supplementary text for undergraduate and graduate students and as a clear guide for economists and financial analysts.
Customer Reviews:
good crash intro to necessary STATA commands.......2007-05-14
This book gives a good overview of some of the commands one would need to do regression analysis with STATA. I needed something to give me a quick intro to STATA and this book has helped me a lot. Howver, just like MS Excel, STATA has tons of commands that I probably will never touch!
much cheaper from stata-press website.......2007-01-27
Not a review, sorry, but a tip for potential purchasers:
This book is much cheaper from stata-press dot com.
Book Description
This reference work and graduate level textbook considers a wide range of models and methods for analyzing and forecasting multiple time series. The models covered include vector autoregressive, cointegrated, vector autoregressive moving average, multivariate ARCH and periodic processes as well as dynamic simultaneous equations and state space models. Least squares, maximum likelihood, and Bayesian methods are considered for estimating these models. Different procedures for model selection and model specification are treated and a wide range of tests and criteria for model checking are introduced. Causality analysis, impulse response analysis and innovation accounting are presented as tools for structural analysis.
The book is accessible to graduate students in business and economics. In addition, multiple time series courses in other fields such as statistics and engineering may be based on it. Applied researchers involved in analyzing multiple time series may benefit from the book as it provides the background and tools for their tasks. It bridges the gap to the difficult technical literature on the topic.
Book Description
You'll find the "econ" back in econometrics with INTRODUCTION TO APPLIED ECONOMETRICS and its accompanying CD.. You'll have the opportunity to replicate classic empirical findings using original data sets and will develop an understanding of the relevance of economic theory to empirical analysis. The author integrates classic empirical examples and applications and builds toward a self-contained four-chapter introduction to time series analysis. The CD includes data sets formatted for STATA, Eviews, Excel, Minitab, SAS and ASCII, as well as an appendix presenting multiple regression in matrix form and another on treating portfolio theory and the capital asset pricing model.
Book Description
About two hundred and forty years ago, an English clergyman named Thomas Bayes developed a method to calculate the chances of uncertain events in the light of accumulating evidence. Though his method has extensive applications to the work of economists, it is only recent advances in computing that have made it possible to exploit its full power.In this new and expanding area, Tony Lancaster 's text provides a comprehensive introduction to the Bayesian way of doing applied economics. Using clear explanations and practical illustrations and problems, the text presents innovative, computer-intensive ways for applied economists to use the Bayesian method. In addition, each chapter includes numerical and graphical examples and demonstrates their solutions using the S programming language and Bugs software.
Customer Reviews:
Good book!.......2007-04-12
I'm taking an intro to Bayesian stats class and we are using the Carlin & Louis book -- it is a POS.
I found this book in the library and it is much better. It gives very clear explanations of the ideas, and lots of concrete worked examples. Props to the author.
Clear as crystal and plenty of workouts.......2006-07-25
This is as clear as crystal. It also has plenty of workouts. It is a very useful volume.
Great Book.......2006-03-19
If you are looking for a book for Bayesian estimation, this is the one. The first several chapters say it all about Bayesian methods. The rest of the book is applications. Very helpful reading for learning the method.
Book Description
Developing the statistical concepts unique to survival data, An Introduction to Survival Analysis Using Stata, Revised Edition includes statistical theory, step-by-step procedures for analyzing survival data, a detailed usage guide for Stata's most widely used st commands, and pointers for using Stata to analyze survival data and present the results. The first several chapters cover basic theoretical concepts as well as censoring and truncation. The next few chapters describe the formatting, manipulation, stsetting, and error-checking involved in preparing survival data for analysis using Stata's st analysis commands. The book also discusses Cox regression and includes various examples of fitting a Cox model, obtaining predictions, interpreting results, building models, and modeling diagnostics. The final chapters cover parametric models, which are fitted using Stata's streg command.
Average customer rating:
- "Introductory" for a math major
- financial engineering
- It is a wonderful book.
- Which is worse...the book or the class Dr. Sheldon taught?
- Its easy to read!
|
An Elementary Introduction to Mathematical Finance: Options and other Topics
Sheldon M. Ross
Manufacturer: Cambridge University Press
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Binding: Hardcover
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Similar Items:
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A Course in Financial Calculus
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Introduction to the Mathematics of Financial Derivatives
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Financial Calculus : An Introduction to Derivative Pricing
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Introduction to Probability Models, Ninth Edition
ASIN: 0521814294 |
Book Description
This original text on the basics of option pricing is accessible to readers with limited mathematical training. It is for both professional traders and undergraduates studying the basics of finance. Assuming no prior knowledge of probability, Sheldon Ross offers clear, simple explanations of arbitrage, the Black-Scholes option pricing formula, and other topics such as utility functions, optimal portfolio selections, and the capital assets pricing model. Among the many new features of this second edition are: a new chapter on optimization methods in finance, a new section on Value at Risk and Conditional Value at Risk; a new and simplified derivation of the Black-Scholes equation, together with derivations of the partial derivatives of the Black-Scholes option cost function and of the computational Black-Scholes formula; three different models of European call options with dividends; a new, easily implemented method for estimating the volatility parameter. Sheldon M. Ross is a professor in the Department of Industrial Engineering and Operations Research at the University of California at Berkeley. He received his Ph.D. in statistics at Stanford University in 1968 and has been at Berkeley ever since. He has published nearly 100 articles and a variety of textbooks in the areas of statistics and applied probability including Topics in Finite and Discrete Mathematics (Cambridge University Press, 2000), An Introduction to Probability Methods, Seventh Edition (Harcourt Science snd Technology Company, 2000), Introduction to Probability and Statistics for Engineers and Scientists (Academic Press, 1999), A First Course in Probability, Sixth Edition (Prentice-Hall, 2001), Simulation, Third Edition (Academic Press, 2002), and Stochastic Processes (John Wiley & Sons, 1982). He is the founding and continuing editor of the journal Probability in the Engineering and Informational Sciences, a fellow of the Institute of Mathematical Statistics, and a recipient of the Humboldt U.S. Senior Scientist Award.
Download Description
This original text on the basics of option pricing is accessible to readers with limited mathematical training. It is for both professional traders and undergraduates studying the basics of finance. Assuming no prior knowledge of probability, Sheldon Ross offers clear, simple explanations of arbitrage, the Black-Scholes option pricing formula, and other topics such as utility functions, optimal portfolio selections, and the capital assets pricing model. Among the many new features of this second edition are: a new chapter on optimization methods in finance, a new section on Value at Risk and Conditional Value at Risk; a new and simplified derivation of the Black-Scholes equation, together with derivations of the partial derivatives of the Black-Scholes option cost function and of the computational Black-Scholes formula; three different models of European call options with dividends; a new, easily implemented method for estimating the volatility parameter. Sheldon M. Ross is a professor in the Department of Industrial Engineering and Operations Research at the University of California at Berkeley. He received his Ph.D. in statistics at Stanford University in 1968 and has been at Berkeley ever since. He has published nearly 100 articles and a variety of textbooks in the areas of statistics and applied probability including Topics in Finite and Discrete Mathematics (Cambridge University Press, 2000), An Introduction to Probability Methods, Seventh Edition (Harcourt Science snd Technology Company, 2000), Introduction to Probability and Statistics for Engineers and Scientists (Academic Press, 1999), A First Course in Probability, Sixth Edition (Prentice-Hall, 2001), Simulation, Third Edition (Academic Press, 2002), and Stochastic Processes (John Wiley & Sons, 1982). He is the founding and continuing editor of the journal Probability in the Engineering and Informational Sciences, a fellow of the Institute of Mathematical Statistics, and a recipient of the Humboldt U.S. Senior Scientist Award.
Customer Reviews:
"Introductory" for a math major.......2007-09-15
This is an introductory book on modern options pricing mathematics, for math major types. If you don't have good knowledge of calculus you won't understand the formulas in the book. The early chapter on probability theory is basic, but there is a big jump from this chapter to the material in the rest of the book. I don't believe someone without a strong math or physics background would understand the chapter on Brownian motion. There are also no solutions given to the end-of-chapter exercises. If you are a math or engineering grad student, you would probably find this book light reading. If you are not, this is not the book for you.
financial engineering.......2006-11-14
Another good book from Dr. Sheldon Ross. Beginning with basic probability, discusses the concepts of options, Arbitrage, Black-Scholes equation, Geometric Brownian Motion, Utility values, Dynamic Programming etc in a very easy-to-understand manner. This is a very good book for an intro to financial engineering.
It is a wonderful book........2005-12-01
Does anybody know whether the book has a students' manual or solutions to the exercises of each chapter.
Which is worse...the book or the class Dr. Sheldon taught?.......2005-08-05
I was unfortunate to have taken Dr. Ross's graduate level class. He taught directly from his book which was not an elementary introduction to mathmatical finance. If you do not have a strong background in finance or math....buy another book.
Its easy to read!.......2003-07-17
This is a pretty good book for whom doesn't have strong background in financial engeering. It begins from probability and I think this is a very good point to start. On the other hand, you also can know the where the formula comes from because the author use a small space to explain it. It is pretty funny!
One problem, this book doesnot cover all of the importnat topics such as Ito calculus but it is still a good book.
Book Description
This book is an ideal introduction for beginning students of econometrics that assumes only basic familiarity with matrix algebra and calculus. It features practical questions which can be answered using econometric methods and models. Focusing on a limited number of the most basic and widely used methods, the book reviews the basics of econometrics before concluding with a number of recent empirical case studies. The volume is an intuitive illustration of what econometricians do when faced with practical questions.
Customer Reviews:
Of little value.......2004-06-22
I used to know a bit of econometrics and hoped this would jog my memory and give some practical pointers. I found it almost useless for my purposes. It reads almost like a really detailed glossary of terms.
An unique gem of a book.......2004-03-13
I'm really surprised that there haven't been more knowledgable reviews of this book before now. I'm also surprised that there isn't a lot of buzz out there about *A Concise Introduction to Econometrics.* This is an unique gem of a book for anyone who is interested in econometrics but does not have a PhD in economics.
What is this book about? This is one of the few books that lives up to its title.
It is concise (the heart of the book is about 100 pages) and is reminiscent of Oxford UP's 'A Very Short Introduction' series.
It deals with econometrics - the statistical analysis of economic data. The book provides a brief but informative remedial section on basic statistics necessary to understand the heart of the book, regression analysis (both cross-sectional and time-series). The book dissects some case studies -- examples from actual, real-life econometric studies (as opposed to made up 'toy' examples used in much more dense books) -- with a special emphasis on topics relevant to finance (financial econometrics) and marketing.
Finally, it lives up to its byline "An Intuitive Guide." It really does deliver a (relatively) intuitive guide to a highly mathematical subject. Even though the book recommends familiarity with calculus and linear algebra, it can easily be read and understood by an intelligent person with a more limited mathematical background (high-school algebra is probably all you need, but you do need mathematical 'maturity' and patience). The emphasis is on understanding the underlying reasoning and not on calculation or formal proofs. It even deals with advanced topics like ARCH/GARCH in this relatively intuitive way.
Who is this book for? I think that the audience for this book are beginning students of econometrics or regression analysis outside of economics. This would obviously include undergrads in economics, finance, etc. and non-quant MBA students. But what many people don't realize is the extent to which econometrics has gained in importance in seemingly unrelated fields. Many law schools, lawyers, and legal scholars make use of econometrics and they could benefit from a book like this. Those people in public policy (academics or in practice), public health, and non-econ social sciences could also benefit from this book. The book is written on a level that intelligent law and policy students should be able to get a lot of knowledge about a topic they would normally be intimidated by.
Another audience for this book are people who have to deal with econometrics on a PRACTICAL level. One of the things that many people who studied econometrics in school find when they have to use it in the real world (on-the-job) is that the formal academic training both OVER-prepared them and UNDER-prepared them for the real world uses of econometrics in finance and marketing (the two areas of emphasis in this book). At least in non-academic settings (and in research assistant work in academe), you don't really need to formally derive a proof or have memorized the content of Greene's econometrics textbook. In fact, a lot of the gibberish one learns in a formal setting will confuse you and often times not clarify how you would model a situation you confront and what kind of data (and how to get it) you need to properly answer the problems you're tackling.
Philip Hans Franses, the author of this book, actually relays to the readers that he is very cogniscent of these types of issues. In fact that was his main motivation for writing this book. He comes from a marketing and financial econometrics background so he is very familiar with on-the-job issues relevant to making practical use of econometrics.
I contrast all of the above with a book like Peter Kennedy's famous guide to econometrics. I don't want to knock or disparage that book, because (for what it is intended to do) it does a great job. But Kennedy's book is designed as a way for economics students (especially graduate and advanced undergrad) and PhD economists to have a reference and general overview of a variety of topics in academic econometrics. That isn't to say that it is not useful -- it would be especially useful for financial engineers dealing with advanced issues in financial econometrics. But, in spite of its strengths for those taking formal econometrics courses or in need of a academically oriented refresher or intro, it does not do what Franses' book does: A practically oriented and brief light-on-the-math introduction to econometrics especially useful for legal and policy scholars and for econonomics, finance, MBA, etc. students that find even Kennedy's book to be over their heads.
I don't know of any other book of its kind out there in the marketplace. If you're even vaguely intrigued, I suggest you buy this relatively inexpensive book. Frankly, it's a lot better than books ten times its price and size.
Learn the basics of econometrics.......2003-04-28
This book is about the wierd subject of econometrics. Econometrics iis a subject that uses math, economics, and statistics. They take an economic question and use data that some what relates to that to try to predict what is going to happen. If this interests you you might like this book. I have never read anything about econometrics before and this book helped to explain it. Sometimes the book would get really complicated and get really hard to follow. The key points in the book are in italics and the practical questions are in bold. These are really helpful. If you read this book make sure you understand how to read functions and how to work with them. You will also have to be able to follow multi-variable equations. You also need a basic understanding of integrals and what they do. If you can understand all of this math and are interested in learning about math in economics you might like this book. The final chapter was helpful becuase it looks at actual questions that have been answered with econometrics. This should it in action. Overall I think this book was informative, but really confusing.
Book Description
This is a classical reprint edition of the original 1971 edition of An Introduction to Bayesian Inference in Economics. This historical volume is an early introduction to Bayesian inference and methodology which still has lasting value for today's statistician and student. The coverage ranges from the fundamental concepts and operations of Bayesian inference to analysis of applications in specific econometric problems and the testing of hypotheses and models.
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