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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Market Models: A Guide to Financial Data Analysis
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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
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:
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!
waste of time.......2005-03-10
This book is very bad, lacks almost everything you can think of, but if you don't know any better you probably won't care. It certainly needs to be supplemented by a respectable book if you want to learn derivatives (c.f. Hull's textbook, for example), and on the other hand, the math isn't rigorous at all, so you'll need a book on stochastic calculus (e.g. Michael Steele's, actually there are tons of better books out there, it's not hard to find better).
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
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
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.
Average customer rating:
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Numerical Methods in Finance: A MATLAB-Based Introduction
Paolo Brandimarte
Manufacturer: Wiley-Interscience
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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.
Book Description
In recent years the growing importance of derivative products financial markets has increased the demand for mathematical skills in financial institutions. The purpose of this book is to introduce the mathematical methods of financial modelling to provide a clear explanation of the most useful models. Introduction to Stochastic Calculus begins with an elementary presentation of discrete models, including the Cox-Ross-Rubenstein model. This book will be valued by derivatives trading, marketing, and research divisions of investment banks and other institutions, and also by graduate students and research academics in applied probability and finance theory.
Customer Reviews:
Very good.......2007-07-03
I am quite familiar with this book since I enjoyed it when it was used (along with many other good books as it should) in Purdue Computational Finance program. I got to do a number of exercises from it. Some Matlab code is available on my website (click on my name above).
A very efficient book for the right audience.......2007-01-21
Introduction to Stochastic Calculus Applied to Finance, translated from French, is a widely used classic graduate textbook on mathematical finance and is a standard required text in France for DEA and PhD programs in the field.
Most folks familiar with Steve Shreve's Stochastic Calculus Models for Finance will be surprised at its brevity, for this work is aimed at different audiences.
Whereas Shreve's work is aimed at mathematicians and physicists who are coming to finance, and building on the commonalities of understandings of time series and data sets and signals, Lamberton & Lapeyre's work is aimed at an audience of mathematically trained engineers, who look at data sets as information for solving problems. Shreve's work, is, therefore, to help people come up with mathematical proofs, and L&L's is to help people solve problems.
Both probabilistic and partial differential equation approaches are covered, so both those from electrical and telecommunication engineering and mechanical engineering will be satisfied and on familiar ground. Numerical and algorithmic methods are also covered for those with systems analysis and operations management backgrounds.
This book, however, is decidedly for those who have had significant mathematical training. Whereas with Hull, Wilmott, Neftci, or Joshi you can play around with their approaches almost instantly in Excel or other programming tools (VBA, C, etc.), Lamberton and Lapeyre's work is for those who think out loud with a white board and others do the dirty work of coding. This work lacks specific examples, data sets, etc. Which makes it difficult to place. Its clarity and brevity are welcome, and it expands the knowledge beyond Hull of those who are not trained in math and came up the practical coding grunt side of quantfin. But it also is not a complete theoretical treatment for the first string math and theory set.
In short, the book is what it is: a short primer on a large area of mathematics in finance for those well-trained in a variety of engineering and applied mathematical subjects. In other words, this book is for the French, because all the best French students are always Engineers first and something else afterwards. If you also happen to be trained as an engineer and find Hull, Wilmott, Joshi & Neftci too easy, and Shreve too hard, then this is the book for you. Or if you are like me, and you've banged your head against this stuff for years just through the happenstance of your career and want to see how a mathematician writes about your gritty world, this is a great book for shedding light in areas filled with cobwebs.
Clear and concise introduction to mathematical finance........2001-07-25
This book, translated from French, is by now a classic graduate textbook on mathematical finance, and provides a clear and concise introduction to the basic and important aspects of the theory. Although one of the first textbooks on the subject, it still remains in my opinion one of the best.
The book has been written for engineering students not mathematicians and avoids the theorem/proof format, going straight to essentials.
Also, while most textbooks on mathematical finance exclusively adopt either a probabilistic (like Baxter & Rennie) or a PDE approach to the theory (Wilmott et al, Wilmott), this book maintains the balance between the two aspects. Moreover, it does not neglect numerical methods and gives details on several algorithms for option pricing ( trees, Finite Difference, Monte Carlo) Finally, and perhaps this point is very important, the book maintains a reasonable volume while treating all these topics AND maintaining a high level of scientific rigor: all statements and notations are precise and oversimplification is avoided. Advanced topics such as variational inequalities for American options and HJM theory of interest rates are also included.
Some drawbacks of the book are: - a complete absence of empirical data/ real life figures - no description of various kinds of derivative products, why they are used,... But then, what can you ask for in such a small volume?
If you are an engineering/maths student and you want to discover what mathematical finance is about, I recommend you this book instead of John Hull's book.
A good INTRODUCTION to ONE part of finance.......1999-03-14
As precisely mentioned in the title, this book is only an introduction; and it is not an introduction to finance, but to stochastic calculus applied to finance.
The buyer of this book should therefore be aware of three facts:
1. After having read this book you are not (yet) an expert on stochastic calculus applied to finance. You have to continue with other books mentioned in Lamberton/Lapeyre. But this book is an excellent framework that leads you to many important results, omiting proofs that are only technical.
2. Mathematics is used in many other areas of Finance too (Time Series Analysis for example). What is treated in this book is only a very small part of Finance Mathematics, but an important one.
3. One should read another book with more economic background at the same time.
The authors begin with discrete-time models to present many important ideas in a (mathematically) simple environment before treating the contiuous models. Introduction to stochastic integration and stochastic differential equations is brief. Stochastic integration is only with respect to the standard browning motion. After having reached the Black-Scholes model and american options, the approach via partial differential equations is treated, followed by interest rate models, models with jumps and, a good idea: a chapter on simulations.
The book has very few mistakes, no important ones, only a strange layout failure on pages 6 to 7.
So I highly recommend this book as an INTRODUCTION to ONE important part of finance mathematics if read in combination with another book with more economic background. It can especially be used for upper graduate student seminars or as a basis for lecture courses.
A stochastic approach of finance for engineers!.......1998-07-28
The french initial version of this book has been one of my first technical papers that deal with stochastic calculus towards finance. It is written by and for engineers I must admit, but students in actuarial sciences (like me) won't be lost by so many formulas and equations if they agree to read with a piece of paper and a pencil on the hand. I have worked on the Vasicek's model and the simulations described have helped me a lot. Too bad that the lattice model is not explored. Anyway it is a good preparation before the opening of "Brownian Motion and Stochastic Calculus" from Karatzas & Shreve.
Book Description
This text offers the ideal approach for economics and business students seeking to understand the mathematics relevant to them. Each chapter demonstrates basic mathematical techniques, while also explaining the economic analysis and business context where each is used. By following the worked examples and tackling the practice problems, students will discover how to use and apply each of these techniques.Now in its second edition, the text features expanded summaries of economic analysis, new sections on matrix algebra and linear programming, and additional demonstrations of economics applications. Along with these new features, the book continues to separate mathematical methods and economics applications into discrete sections, allowing the student to learn the mathematics needed, or to proceed immediately to the economics examples.Although the book is complete in itself, it also encourages students to develop their understanding of both mathematics and economics by using the interactive CD-ROM in the back of the book. This CD-ROM includes the award-winning MathEcon software, Excel files, Powerpoint slides, all definitions and 'remember ' boxes, and additional practice questions. In its flexibility, comprehensiveness, and readable format, this text will continue to serve as an essential resource for students in this area.
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