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
ProductGroup: Book
Binding: Hardcover
 Econometrics
| Economics
| Business & Investing
| Subjects
| Books
General
| Popular Economics
| Business & Investing
| Subjects
| Books
Finance
| Business & Investing
| Subjects
| Books
| Banks & Banking
| Corporate Finance
| Foreign Exchange
| Inflation
| Interest
General
| Business & Investing
| Subjects
| Books
General
| Accounting
| Industries & Professions
| Business & Investing
| Subjects
| Books
General
| Investing
| Business & Investing
| Subjects
| Books
Probability & Statistics
| Applied
| Mathematics
| Science
| Subjects
| Books
Statistics
| Applied
| Mathematics
| Professional Science
| Professional & Technical
| Subjects
| Books
General
| Accounting
| Accounting & Finance
| Professional & Technical
| Subjects
| Books
General
| Finance
| Accounting & Finance
| Professional & Technical
| Subjects
| Books
Statistics
| Mathematics
| Sciences
| New & Used Textbooks
| Stores
| Books
General
| Mathematics
| Sciences
| New & Used Textbooks
| Stores
| Books
General
| Accounting
| Business & Finance
| New & Used Textbooks
| Stores
| Books
General
| Business & Finance
| New & Used Textbooks
| Stores
| Books
General
| Economics
| Business & Finance
| New & Used Textbooks
| Stores
| Books
Quantitative Business
| Business & Finance
| New & Used Textbooks
| Stores
| Books
All Amazon Upgrade
| Amazon Upgrade
| Stores
| Books
Business & Investing
| Amazon Upgrade
| Stores
| Books
Professional & Technical
| Amazon Upgrade
| Stores
| Books
Science
| Amazon Upgrade
| Stores
| Books
All Titles
| Qualifying Textbooks - Fall 2007
| Stores
| Books
Business & Investing
| Qualifying Textbooks - Fall 2007
| Stores
| Books
Professional
| Qualifying Textbooks - Fall 2007
| Stores
| Books
Science
| Qualifying Textbooks - Fall 2007
| Stores
| Books
Similar Items:
-
Analysis of Financial Time Series, 2nd Edition (Wiley Series in Probability and Statistics)
-
Market Models: A Guide to Financial Data Analysis
-
Trading and Exchanges: Market Microstructure for Practitioners
-
Optimal Trading Strategies: Quantitative Approaches for Managing Market Impact and Trading Risk
-
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
Finance is one of the fastest growing areas in the modern banking and corporate world. This, together with the sophistication of modern financial products, provides a rapidly growing impetus for new mathematical models and modern mathematical methods. Indeed, the area is an expanding source for novel and relevant "real-world" mathematics. In this book, the authors describe the modeling of financial derivative products from an applied mathematician's viewpoint, from modeling to analysis to elementary computation. The authors present a unified approach to modeling derivative products as partial differential equations, using numerical solutions where appropriate. The authors assume some mathematical background, but provide clear explanations for material beyond elementary calculus, probability, and algebra. This volume will become the standard introduction for advanced undergraduate students to this exciting new field.
Customer Reviews:
Not bad... but there is better out there.......2007-10-23
A per its title, this is an applied mathematics book, and therefore a minimal level of math is expected from the reader. Taking a PDE approach, the book aims at presenting various methods for pricing financial options. While the first few chapters are pretty good at skimming the surface of the theory and laying down the key principles of options pricing, I find that in general, the book lacks depth. Many results (prices of barrier, lookback, asian, etc...) are simply given without real development (or simply with a little of "hand-waving") while the section on the linearity complementarity problem for the American Option is quite muddled... The book does not provide any new insight into the more difficult areas of option pricing and in that sense, simply goes through the typical presentation without adding much value.
It is nonetheless an acceptable and quick overview if you are looking for a refresher of key concepts. If you are looking for a thorough mathematical introduction to options pricing, You-Lan Zhu's book (for example) does a much better job at covering the PDE approach much more rigorously (proving for example some of the convergence criterias for the finite difference method, covering the linear complementarity approach in much more details as well as presenting other numerical techniques) without being overly formal.
Good Buy.......2007-08-29
maps one to one with many chapters in Hull. more elaborate derivations than Hull. Fixed income area treatment is very slim though. Good Buy for the Price.
Okay but not an introduction.......2006-07-31
If you want an introduction, read another book like Hull. If you want to learn how to apply Partial Differential Equations (PDEs) approach to finance then it is a useful book. However, it is better to read an elementary PDEs book before reading this book. At least, learn how to solve parabolic PDEs analytically because the technical notes in the book would not help much.
Introduction to partial differential equations in finance.......2005-10-13
This book treats only the partial differential equations
in Finance and how to treat them using Finite Differences
and Tree. For this purpose it is very well written and
understandable. A very good beginning for student. Even
undergraduate.
Now after reading it you should understand the martingales reading the baxter and how to implement Monte Carlo using, for example Glasserman (see my reviews)
A good introduction to the PDE approach.......2005-10-10
Contrary to what many readers believe, this book explains the pricing of derivatives much better than Hull. Hull gives an overview of the mechanics and properties of the derivative pricing industry, along with its pricing methodologies, and this book provides an in depth method to one of the pricing methods.
Financial derivatives can be priced by a wide range of methodologies, among some the elegant equivalent martingale measure approach (or risk-neutral pricing), replication, multinomial tree approximation, Monte Carlo simulation, partial differential equations etc etc.
This book gives an excellent introduction, and an insight to the PDE approach. Although being a big fan of the Girsanov-change-of-measure method myself, these analytical methods often fail in the valuation of highly complex derivatives like the exotics. Pricing americans prove to be hard and inefficient too, even with simulation and the risk-neutral approach.
This is where PDE methods come in. Since most derivatives (or term structures) have a PDE describing its evolution, solving the PDE seems to be a good (or sometimes the best) way, no matter how complex the derivative can get. PDEs on the other hand, have very robust and easy methods for solving. Therefore, this book brings the reader through basic PDE solving methods, analytical solutions, techniques for fast and efficient numerical approximations as well as rigorous technical explanations for some of the mathematics of partial differential equations (which arise in the financial industry).
The authors are famous for their research in the field of Industrial and Applied Mathematics, and this book continues to be a classic for undergraduates in mathematics in Oxford. If you want to have an overview of the pde approach to option valuation, without the hassle of learning up Radon-Nikodým and martingales, I highly recommend this book!
Book Description
In today's increasingly competitive financial world, successful risk management, portfolio management, and financial structuring demand more than up-to-date financial know-how. They also call for quantitative expertise, including the ability to effectively apply mathematical modeling tools and techniques. An Introduction to Credit Risk Modeling supplies both the bricks and the mortar of risk management. In a gentle and concise lecture-note style, it introduces the fundamentals of credit risk management, provides a broad treatment of the related modeling theory and methods, and explores their application to credit portfolio securitization, credit risk in a trading portfolio, and credit derivatives risk. The presentation is thorough but refreshingly accessible, foregoing unnecessary technical details yet remaining mathematically precise. Whether you are a risk manager looking for a more quantitative approach to credit risk or you are planning a move from the academic arena to a career in professional credit risk management, An Introduction to Credit Risk Modeling is the book you've been looking for. It will bring you quickly up to speed with information needed to resolve the questions and quandaries encountered in practice.
Customer Reviews:
read this before going for it.......2007-04-23
Well first off I would like to tell anyone who doesn't have a solid working knowledge of calculus (including multivariate) to avoid this book as it requires multiple integrals and infinite series and sequences. Now onto the good and the bad:
THE GOOD:
This text explains concepts very well and is FULL of examples. I mean literally 3/4 of the book, maybe more, is examples. Every chapter also has a section of problems that have partial solutions, which can come in very handy. This is pretty much all that is good about this text, but keep in mind that explaination is the most important part of any textbook.
THE BAD:
The proofs skip plenty of steps. And I mean plenty, so much that a proof in the book would take 5 lines but when my professor proved it in class it would take him nearly 15. Also while there are tonnes of examples, too many are theoretical and very hard. The book costs a hefty amount of change and is suprisingly small, Author couldl have given few more examples to make it interesting. However the worst thing about this book is how the author leaves important things in with the text often. However most these things are small, and overall the text is a good intro to probability theory.
a very good book.......2006-10-31
The authors wanted to write the book that they themselves would have liked to read before starting a profession in risk management. I am working for a treasury consultancy firm. This book was the best of the five I bought. The text is very clear yet does not assume too much prior knowledge. It covers theory as well as industry practice. The book contains much advanced statistics and readers must have some background in order to handle this. The authors keep it simple but not too simple. Their approach is pragmatic throughout. I am really happy to have read this book when I started doing work in credit risk management.
good combination of math and finance.......2006-02-22
As indicated on the back of the book, the authors are aiming at audience who have some knowledge in both math and finance but may be weak in one and strong in another. Either way, this is a good book to read on credit risk.
Clear and comprehensive.......2005-10-27
This book clearly articulates basic concepts of credit risk modeling. At the same time it is mathematically rigorous. This book enables non mathematician with some (basic) knowledge in probability statistic to better understand and develop his risk management skills.
A good read!.......2004-08-19
Easy to understand with not a tremendous amount of complicated math to dicipher. Just what the doctor ordered.
Book Description
A state-of-the-art introduction to the powerful mathematical and statistical tools used in the field of finance
The use of mathematical models and numerical techniques is a practice employed by a growing number of applied mathematicians working on applications in finance. Reflecting this development, Numerical Methods in Finance and Economics: A MATLAB®-Based Introduction, Second Edition bridges the gap between financial theory and computational practice while showing readers how to utilize MATLAB®—the powerful numerical computing environment—for financial applications.
The author provides an essential foundation in finance and numerical analysis in addition to background material for students from both engineering and economics perspectives. A wide range of topics is covered, including standard numerical analysis methods, Monte Carlo methods to simulate systems affected by significant uncertainty, and optimization methods to find an optimal set of decisions.
Among this book's most outstanding features is the integration of MATLAB®, which helps students and practitioners solve relevant problems in finance, such as portfolio management and derivatives pricing. This tutorial is useful in connecting theory with practice in the application of classical numerical methods and advanced methods, while illustrating underlying algorithmic concepts in concrete terms.
Newly featured in the Second Edition:
- In-depth treatment of Monte Carlo methods with due attention paid to variance reduction strategies
- New appendix on AMPL© in order to better illustrate the optimization models in Chapters 11 and 12
- New chapter on binomial and trinomial lattices
- Additional treatment of partial differential equations with two space dimensions
- Expanded treatment within the chapter on financial theory to provide a more thorough background for engineers not familiar with finance
- New coverage of advanced optimization methods and applications later in the text
Numerical Methods in Finance and Economics: A MATLAB®-Based Introduction, Second Edition presents basic treatments and more specialized literature, and it also uses algebraic languages, such as AMPL©, to connect the pencil-and-paper statement of an optimization model with its solution by a software library. Offering computational practice in both financial engineering and economics fields, this book equips practitioners with the necessary techniques to measure and manage risk.
Customer Reviews:
Great book for quants.......2007-09-30
This is a great book if you want to be a quant or are interested in using mathematical methods for finance purposes. There are not many good books in this field and this one is definitely one of the few good ones out there.
However, this book is not for people with little background in math.
Like it, just what I need.......2007-05-23
It has up to date information about finance and math background needed. I pretty much like it.
Misssing the new stuff, still good on the old methods.......2007-04-19
The book earns 4 stars for how it combines what has been out there for some time with Matlab functionality. What one would have appreciated though is something about all the new stuff that has evolved in the last few years (e.g. credit risk, etc.)
Book Description
Highly praised for its clarity and great examples, Weiers' text takes an informal, student-oriented approach to presenting fundamental statistical concepts. Non-technical terminology and outstanding illustrations explain statistical concepts presented in the context of contemporary applications and student experience. Aware that many business students are intimidated by this course, Weiers provides numerous learning aids and interesting applications drawn from real-world experience common to many students.
Customer Reviews:
Probably more than you will need.......2006-12-22
The college I teach in replaced this book with another, widely accepted book with a simiar name. This was two years ago, and yet the instructors still keep this book to use for examples, and we would like it back as the book of choice. It stands head and shoulders above most of the competition.
My students are mainly business majors, not mathematicians, and this book is 100% suited to this type of application. The examples are 'real world' that actually explain where a particular concept or distribution may be used. In essence-this book covers everything you'll need and then some...
If I DO have a couple of 'moans' about the book, it gets a bit too 'in depth' in some areas, way more than the average business student would ever need, and also the CD, which is a bit of a waste of time, dealing with data files for Excel and Minitab. There are no 'REAL' learning tools.
I heartily recommend this book to anyone who wants to learn the subject at their own pace. It's expensive, and the prior versions contain about the same stuff, just in a cheaper package. There have been no real 'breakthroughs' in Stats in the last few decades, so the subject matter is pretty much unchanged. As the adage goes "You pays yer money and takes yer choice"- a few 'dog-eared' pages won't kill you!
lacking, poorly structured.......2005-12-15
This text is geared toward the 'business student' and assumes minimal amounts of prior math (the general prerequisite is a semester of college algebra). That said, this text is very poorly structured which can lead to a general frustration when reading it. The main 'flaw' are the 'applications boxes' that appear quite often. The 'boxes' tend to be in the middle of a discussion on math - and take up half the page. As the authors run out of real world examples, they make people up (and tell you the photo is real, the guy is fake in his quotes).
My issue with this book has to do with the approach to statistics. This book could easily be condensed to 200-300 pages and nothing would be lost - you'd gain from a cheaper text. The CD is not worth anything - it just contains data files from problems that are completely worked out in the book. There is very little mathematical rigor - the emphasis is on an applied, formula memorization approach. Another problem is that some important (tested) topics are mentioned in two sentences.
The solution manual is not worth getting - I had an instructor who posted the word version of it. Instead of actually going through the steos to reach the answer, the approach is essentially to give you the answer and nothing else. It's not at all helpful.
I realize this is a required text for most of you, but you would do well to purchase a used copy and avoid the solutions manual.
Great Service!.......2005-09-28
The condition of the book was great(like new). Seemed like I turned around after ordering and the book arrived it was so quick. My only issue was that it was the wrong edition and that might have been me not paying attention to the sellers description. So make sure you do that. Otherwise, great service!
The best statistics book ever.......2000-05-18
Finally a statistics book that isn't just a math book with no practical implication.
This book really helped me at my job to make decision calculations.
Book Description
This textbook emphasizes the applications of statistics and probability to finance. Students are assumed to have had a prior course in statistics, but no background in finance or economics. The basics of probability and statistics are reviewed and more advanced topics in statistics, such as regression, ARMA and GARCH models, the bootstrap, and nonparametric regression using splines, are introduced as needed. The book covers the classical methods of finance such as portfolio theory, CAPM, and the Black-Scholes formula, and it introduces the somewhat newer area of behavioral finance. Applications and use of MATLAB and SAS software are stressed.
The book will serve as a text in courses aimed at advanced undergraduates and masters students in statistics, engineering, and applied mathematics as well as quantitatively oriented MBA students. Those in the finance industry wishing to know more statistics could also use it for self-study.
From the reviews:
"The inherent interaction of statistical and financial modeling makes this book a very useful and motivating instrument with which to introduce students from engineering, mathematics, statistics and economics to study statistics and/or finance."
Short Book Reviews of the International Statistical Institute, December 2004
"This book will be on my list of study book sfor 2005. If you have any interest or involvement with statistics in financial applications, I recommend this book to you."
Technometrics, May 2005
"...The book is well-written and clear....the clear writing with illustrative examples and pictures strongly recommend the book as a basis for finance-motivated statistics classes at the undergraduate level."
SIAM Review, Vol. 47, No. 2
"David Ruppert’s … discusses computation in SAS and MATLAB. … the book is very well written and clear. … the clear writing and illustrative examples and pictures strongly recommend the book as a basis for finance-motivated statistics classes at the undergraduate level." (Ronnie Sircar, SIAM Review, Vol. 47 (2), 2005)
"That statistical methods are becoming more important in finance is further evidenced by this book from a statistician who has written some excellent … . For the statistician, this is a very good book to peruse, because it presumes no background in finance. Here the financial concepts are fully explained … . book with a considerable statistical content. … will be on my list of study books for 2005. If you have any interest in or involvement with statistics in financial applications, I recommend this book to you." (Technometrics, Vol. 47 (2), May, 2005)
"This book emphasizes the application of probability and statistics to finance by studying statistical models of financial markets … . The emphasis is on concepts rather than mathematics, and several examples are given as illustration. … . This book should be a valuable resource for those who are interested in the applications of probability and statistics to finance, and I believe that it will be a very useful addition to any scholarly library." (Theofanis Sapatinas, Journal of the Royal Statistical Society Series A, Vol. 168 (2), 2005)
"The inherent interaction of statistical and financial modeling makes this book a very useful and motivating instrument with which to introduce students from engineering, mathematics, statistics and economics to study statistics and/or finance. … the manuscript succeeds in covering relatively recent topics from statistics and finance, like the bootstrap, penalized splines, some VaR estimation models and behavioural finance. … Students having gained confidence with the material of this book can also be expected to be ready for advanced topics … ." (F. Trojani, Short Book Reviews International Statistical Institute, Vol. 24 (3), 2004)
"...Ruppert's book succeeds at presenting this classic material in a concises, readable way that is suitable for a wide audience including undergraduate business, economics, and statistics majors, MBA students, and master's level engineering students."
Journal of the American Statistical Association, June 2006
Customer Reviews:
Avoid Like Michael Jackson at a Chuck E. Cheese.......2007-04-23
Ruppert tries to cover too many topics in too few pages. As a result, the treatment of topics is perfunctory at best, and the exercises are almost nonexistent. If you really want to learn the material, look at the table of contents, and for each chapter, buy a separate textbook.
Book reached me in good condition.......2007-03-08
The book reached me in good condition in time. What else can one ask for!
great book, especially for statisticians.......2006-07-28
This book is an ambitious and unique combination of stat and finance - and because of the very close relationship of the two areas, this book is excellent and useful for 1) statisticians who want to learn financial modeling; and 2) financial analysts who need to understand the underlying stat concepts at a relatively advanced level. It is generally well-written and the author provides clear explanation on many finance theories.
a good new book.......2006-06-23
an interesting and authoritative perspective on many things of practical interest in asset management
a very boring and confusing book.......2006-02-26
I am from mit, and I'm really smart. I cannot understand this book. There are also quite a few mistakes in this book.
Book Description
In recent years portfolio optimization and construction methodologies have become an increasingly critical ingredient of asset and fund management, while at the same time portfolio risk assessment has become an essential ingredient in risk management, and this trend will only accelerate in the coming years. Unfortunately there is a large gap between the limited treatment of portfolio construction methods that are presented in most university courses with relatively little hands-on experience and limited computing tools, and the rich and varied aspects of portfolio construction that are used in practice in the finance industry. Current practice demands the use of modern methods of portfolio construction that go well beyond the classical Markowitz mean-variance optimality theory and require the use of powerful scalable numerical optimization methods. This book fills the gap between current university instruction and current industry practice by providing a comprehensive computationally-oriented treatment of modern portfolio optimization and construction methods. The computational aspect of the book is based on extensive use of S-Plus®, the S+NuOPT™ optimization module, the S-Plus Robust Library and the S+Bayes™ Library, along with about 100 S-Plus scripts and some CRSP® sample data sets of stock returns. A special time-limited version of the S-Plus software is available to purchasers of this book.
“For money managers and investment professionals in the field, optimization is truly a can of worms rather left un-opened, until now! Here lies a thorough explanation of almost all possibilities one can think of for portfolio optimization, complete with error estimation techniques and explanation of when non-normality plays a part. A highly recommended and practical handbook for the consummate professional and student alike!”
Steven P. Greiner, Ph.D., Chief Large Cap Quant & Fundamental Research Manager, Harris Investment Management
“The authors take a huge step in the long struggle to establish applied post-modern portfolio theory. The optimization and statistical techniques generalize the normal linear model to include robustness, non-normality, and semi-conjugate Bayesian analysis via MCMC. The techniques are very clearly demonstrated by the extensive use and tight integration of S-Plus software. Their book should be an enormous help to students and practitioners trying to move beyond traditional modern portfolio theory.”
Peter Knez, CIO, Global Head of Fixed Income, Barclays Global Investors
“With regard to static portfolio optimization, the book gives a good survey on the development from the basic Markowitz approach to state of the art models and is in particular valuable for direct use in practice or for lectures combined with practical exercises.”
Short Book Reviews of the International Statistical Institute, December 2005
Customer Reviews:
If your copy did not include the web registration code..........2007-05-12
Some copies (especially used copies) of this book don't include the web registration key sticker. If you need it, you can contact Insightful Technical Support (keys at insightful dot com) to get a registration key and password.
Customer Service.......2007-03-28
I have got a very good and prompt service and response from Amazon for the book ordered.
Excellent academic treatise a little less useful for practitioners........2007-01-28
I will admit to being torn between four and five stars for this book. I ultimately deduct a star because of: the lack of any sign of the promised web registration key for downloading the 150 day trial software and data, the heavy use of NuOPT where vanilla S/R code would have been sufficient and possibly even easier to understand, and the frequent use by the authors of providing symbolic solutions from Scherer's 2000 book on optimization where implementation is "left as an excercise".
The book dispenses with traditional Markowitz mean-variance optimization in the first chapter, and then moves on to many other methods of optimization for different types of portfolios, asset classes, and investor utility functions. All of this is excellent, comprising the broadest treatment in a single title that I am aware of.
The book makes heavy use of NuOPT, an add-on package for S-Plus from Insightful, and the SIMPLE linear programming included with NuOPT. I was disappointed that the authors make no effort to work problems without NuOPT, even when simplex or other methods would solve the problems presented in more elegant manner.
I was most disappointed that the authors often leave implementation to the reader. Every chapter has "Exercises" at the end. This is fine. I don't think it is fine to discuss the symbolic solution of a problem (like several of the scenario optimization methods discussed in Chapter 5), and then leave as an excercise the implementation of those portfolio solutions in S-PLUS, SIMPLE, or NuOPT. Nearly every chapter has a significant section, usually lifted largely from Scherer's 2000 book, that suffers from this deficiency. It is almost as if the publishers were pushing for a draft, and the authors went through and "left as exercises" whatever they didn't have tested code for.
All my negatives left to the side, this is still the best treatment you'll find in a single title on many issues of portfolio optimization under varying conditions today. Buy this book if you work in portfolio optimization with S-Plus or R.
great reference.......2005-09-09
The best book on this subject. It provides both an excellent up-to-date overview of the relevant literature and an application-oriented perspective. The chapter on robust estimation is outstanding.
Book Description
Using high-quality, real-world case studies and examples, this introduction to mathematical statistics shows how to use statistical methods and when to use them. This book can be used as a brief introduction to design of experiments. This successful, calculus-based book of probability and statistics, was one of the first to make real-world applications an integral part of motivating discussion. The number of problem sets has increased in all sections. Some sections include almost 50% new problems, while the most popular case studies remain.
For anyone needing to develop proficiency with Mathematical Statistics.
Customer Reviews:
dry and difficult.......2007-07-07
In case you're unclear on the matter, "mathematical statistics" is code talk for "statistics with calculus." So don't think this is book is a high-school or even undergraduate-level "introduction" for statistics. For that I would recommend the friendlier but still meaty Stats: Modeling the World (2nd Edition) (DeVeaux/Velleman/Bock).
At my university, this book is usually used in the first math class required of those in graduate school majoriing in the statistical social sciences.
So make sure you're ready. The authors assume you are quite solid at the calculus.
Confused and confusing.......2007-04-12
I used this as the text in a sequence on probability and statistics I taught recently, and I soon came to regret this choice. The authors are obviously quite confused about basic concepts. Here are some examples: the "definition" of the median ignores obvious problems with existence and uniqueness; the "proof" of the central limit theorem is thoroughly incomplete; the "theorems" on the tests in Sect. 9.2, 9.3 summarize previous discussions, but the "proofs" of these theorems (we are even referred to an appendix - no small surprise when the statements seem obvious) establish something entirely different; finally, to conclude this (very incomplete) selection, there is the delightful claim that the golden ratio is a transcendental number (which just proves that the authors don't have the slightest idea what a transcendental number really is, but then it might have been wise to avoid the use of the term).
In addition to these blatant problems, the authors' treatment frequently misses the point and/or is confusing.
Infuriating.......2006-11-08
The text presents all relevant information, but does so in such a confusing and poorly explained fashion as to prompt the reader to wonder if the authors have ever met anyone who hasn't known all subtleties of probability since the womb. There is no avenue for the student who does not understand, no pedagogy whatsoever. Everything is presented at lightning pace with blisteringly difficult proofs and, often, no meaningful explanation of the physical meaning of the concepts explained. A very solid background in calculus is an absolute necessity, to the point where many problems in the text are more challenging in evaluating integrals than they are in actually applying concepts. This is a serious problem that recurs over and over.
Examples worked out in the chapter sections also almost never bear any resemblance to the problems students are expected to complete. Although the examples vary in terms of difficulty, a student stuck on an exercise almost definitely will not find any help in the teaching material of the section in completing it simply because the examples never entirely cover the concepts demanded in the exercises.
s
Excellent intro to the mathematics of traditional statistics.......2005-03-19
The first half of the book begins with basic discrete and continuous probability theory. It continues with thorough overviews of the basic distributions (normal, Poisson, binomial, multinomial, chi-squared and student-T). The focus is on basic probability and variance analysis, though it briefly covers higher-order moments.
The second half of this book is devoted to hypothesis testing and regression. There is an excellent explanation of the mathematical presuppositions of the various classical experimental methodologies ranging from chi-square to t-tests to generalized likelihood ratio testing. It contains a very nicely organized chapter on general regression analysis, concentrating on the common least squares case under the usual transforms (e.g. exponential, logistic, etc.).
Like many books in mathematics, this introduction starts from first principles in the topic it's introducing, but assumes some "mathematical sophistication". In this case, it assumes you're comfortable with basic definition-example-theorem style and that you understand the basics of multivariate differential equations. I was a math and computer science undergrad who did much better in abstract algebra and set theory than analysis and diff eqs, but I found this book extremely readable. I couldn't have derived the proofs, but I could follow them because they were written as clearly as anything I've ever read in mathematics. I found the explanation of the central limit theorem and the numerous normal approximation theorems for sampling to be exceptionally clear.
The examples were both illuminating and entertaining. One of the beauties of statistics is that the examples are almost always interesting real-world problems, in this case ranging from biological (e.g. significance testing for cancer clusters) to man-made (e.g. Poisson models of football scoring) to physical (e.g. loaded dice). The examples tied directly to the techniques being explored. The exercises were more exercise-like in this book than in some math books where they're a dumping ground for material that wouldn't fit into the body of the text. This book has clearly been tuned over many years of classroom use with real students.
I read this book because I found I couldn't understand the applied statistics I was reading in machine learning and Bayesian data analysis research papers in my field (computational linguistics). In paticular, I wanted the background to be able to tackle books such as Hastie et al.'s "Elements of Statistical Learning" or Gelman et al.'s "Bayesian Data Analysis", both of which pretty much assume a good grounding in the topics covered in this book by Larsen and make excellent follow-on reading.
Master your calculus.......2005-02-07
I took up this book for my course in economics and i found the book clear and examples quite relevant. However, our calculus background was rather weak and we were left to study integrals by oursleves. Because of this, most of us floundered in the text and could not fully appreciate some of the more essential steps of the proofs. The solutions to many examples requires a solid background in calculus to fully appreciate and, at times, even understand since certain steps are ommited. So much so that our eco teacher, with a degree in engineering mind you, admitted the book was a bit too terse and spent most of the time explaining the calculus that we learnt very little of actual statistics.
In short, master your calculus or this book will only give you a rough feel for elementary statistics but will definitely not arm you to take up higher stat courses.
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.
Customer Reviews:
Welcomed Surprise.......2007-10-13
This book provides a fairly elementary view of the vast subject of time series analysis. It easy to read and the author provides lots of basic calculations. Typically, such books stay away from the cutting edge topics but not this one. It is quite complete. I highly recommend it to anyone that knows a few basic things about time series and wants to take it much further.
Average customer rating:
|
Numerical Methods in Finance: A MATLAB-Based Introduction
Paolo Brandimarte
Manufacturer: Wiley-Interscience
ProductGroup: Book
Binding: Hardcover
General
| Popular Economics
| Business & Investing
| Subjects
| Books
Finance
| Business & Investing
| Subjects
| Books
| Banks & Banking
| Corporate Finance
| Foreign Exchange
| Inflation
| Interest
General
| Business & Investing
| Subjects
| Books
General
| Applied
| Mathematics
| Science
| Subjects
| Books
Probability & Statistics
| Applied
| Mathematics
| Science
| Subjects
| Books
General
| Applied
| Mathematics
| Professional Science
| Professional & Technical
| Subjects
| Books
Statistics
| Applied
| Mathematics
| Professional Science
| Professional & Technical
| Subjects
| Books
General
| Finance
| Accounting & Finance
| Professional & Technical
| Subjects
| Books
General
| Computers & Internet
| Subjects
| Books
Mathematical & Statistical
| Software
| Computers & Internet
| Subjects
| Books
General
| Computer Science & Information Systems
| New & Used Textbooks
| Stores
| Books
Software
| Information Systems
| Computer Science & Information Systems
| New & Used Textbooks
| Stores
| Books
Statistics
| Mathematics
| Sciences
| New & Used Textbooks
| Stores
| Books
General
| Mathematics
| Sciences
| New & Used Textbooks
| Stores
| Books
General
| Business & Finance
| New & Used Textbooks
| Stores
| Books
Quantitative Business
| Business & Finance
| New & Used Textbooks
| Stores
| Books
All Titles
| Qualifying Textbooks - Fall 2007
| Stores
| Books
Business & Investing
| Qualifying Textbooks - Fall 2007
| Stores
| Books
Computers & Internet
| Qualifying Textbooks - Fall 2007
| Stores
| Books
Professional
| Qualifying Textbooks - Fall 2007
| Stores
| Books
Science
| Qualifying Textbooks - Fall 2007
| Stores
| Books
Similar Items:
-
Monte Carlo Methods in Financial Engineering (Stochastic Modelling and Applied Probability)
-
Stochastic Calculus for Finance II: Continuous-Time Models (Springer Finance)
-
Business, Economics, and Finance with Matlab, GIS, and Simulation Models
-
Options, Futures and Other Derivatives (6th Edition)
-
Financial Instrument Pricing Using C++ (The Wiley Finance Series)
ASIN: 0471396869 |
Book Description
Balanced coverage of the methodology and theory of numerical methods in finance
Numerical Methods in Finance bridges the gap between financial theory and computational practice while helping students and practitioners exploit MATLAB for financial applications.
Paolo Brandimarte covers the basics of finance and numerical analysis and provides background material that suits the needs of students from both financial engineering and economics perspectives. Classical numerical analysis methods; optimization, including less familiar topics such as stochastic and integer programming; simulation, including low discrepancy sequences; and partial differential equations are covered in detail. Extensive illustrative examples of the application of all of these methodologies are also provided.
The text is primarily focused on MATLAB-based application, but also includes descriptions of other readily available toolboxes that are relevant to finance. Helpful appendices on the basics of MATLAB and probability theory round out this balanced coverage. Accessible for students-yet still a useful reference for practitioners-Numerical Methods in Finance offers an expert introduction to powerful tools in finance.
Download Description
This book integrates the topics of numerical methods, financial problem solving, and MATLAB programming into one balanced treatment. Its tutorial approach features MATLAB examples as a means of illustrating the concepts in practical, every day financial problems.
Customer Reviews:
Too much introductive.......2003-04-08
Since there is few books on financial application of Matlab, I would say that Mr. Brandimarte has done a good pretty good job. I liked especially the fact that the book covers many topics (bond pricing, derivatives, optimization), however, even if the title says "an introduction", it is still too much introductive and you don't get a grip on the amazing capabilities of Matlab. This book is suitable for people discovering Matlab and Finance at the same time.
Books:
- An Introduction to Mathematical Statistics and Its Applications (3rd Edition)
- Animal Disease Surveillance and Survey Systems: Methods and Applications
- Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences
- Basic Business Statistics: Concepts and Applications and CD package (10th Edition)
- Bringing Out the Best in Yourself at Work: How to Use the Enneagram System for Success
- : Business Process Management and the Balanced Scorecard : Focusing Processes on Strategic Drivers
- Business Statistics: First Course and Student CD (4th Edition)
- Business Statistics: First Course and Student CD (4th Edition)
- Contemporary Engineering Economics (3rd Edition)
- Continuous Improvement Tools: A Practical Guide to Achieve Quality Results (Volume 2)
Books Index
Books Home
Recommended Books
- Schaum's Outline of Statistics and Econometrics
- Concrete Countertops: Design, Form, and Finishes for the New Kitchen and Bath
- Sweet Smell of Success: And Other Stories
- The Rape of Nanking: The Forgotten Holocaust of World War II
- Ways of Seeing: Based on the BBC Television Series
- Dead Men's Secrets
- An Invitation to Health
- Net Profit: How to Invest and Compete in the Real World of Internet Business
- The Homevoter Hypothesis: How Home Values Influence Local Government Taxation, School Finance, and L
- When Will the Dead Lady Sing
