Average customer rating:
- Detailed but Comprehensible
- Good Companion Book
- Good book
- Very thoughtful and clear explanation of financial math
- sophisticated maths
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Introduction to the Mathematics of Financial Derivatives
Salih N. Neftci
Manufacturer: Academic Press
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Similar Items:
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Options, Futures and Other Derivatives (6th Edition)
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Principles of Financial Engineering (Academic Press Advanced Finance)
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Financial Calculus : An Introduction to Derivative Pricing
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Heard on the Street: Quantitative Questions from Wall Street Job Interviews
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Stochastic Calculus for Finance II: Continuous-Time Models (Springer Finance)
ASIN: 0125153929 |
Book Description
This popular text, publishing Spring 1999 in its Second Edition, introduces the mathematics underlying the pricing of derivatives. The increase of interest in dynamic pricing models stems from their applicability to practical situations: with the freeing of exchange, interest rates, and capital controls, the market for derivative products has matured and pricing models have become more accurate. Professor Neftci's book answers the need for a resource targeting professionals, Ph.D. students, and advanced MBA students who are specifically interested in these financial products. The Second Edition is designed to make the book the main text in first year masters and Ph.D. programs for certain courses, and will continue to be an important manual for market professionals.
Customer Reviews:
Detailed but Comprehensible.......2007-10-14
This booke really helped me understand topics for a class I was taking. After reading it i almost felt like i understood change of measure and numeraire. one of the few books i'd recommend buying.
Good Companion Book.......2007-08-29
good companion book for the other book "Principles of Financial Engineering" by the same author
Clear and easy to understand treatment. The author does not assume a high level of math knowledge of the reader.
Good book.......2007-05-09
As title states this is a good Introduction to the mathematics of derivatives.
If you're looking for some book with C/C++/C#/Java code samples this isn't the book. Indeed a good mathematical introduction; its pre-requirements are a good mathematical and statistical ones.
Very thoughtful and clear explanation of financial math.......2007-02-05
I turn to this book after I get frustrated with Tomas Bojork's book "Arbitrage Theory in Continuous Time." As I am not from a strict math background, this Neftci's book makes much more sense to me. What I particularly like about this book is explanation in plain English of why the mathematical formulae are so, and how they are connected to the bigger picture. Also Neftci has a good grasp of how many real-life examples included in this book so that it doesn't lose its focus on the real math in finance.
sophisticated maths.......2006-06-16
Neftci takes us on a mathematically sophisticated tour of financial derivatives. The treatment is on a level akin to a senior-level undergrad text on physics or engineering. Indeed, to a reader who might come from that background, there will be a lot of similarities and familiar ideas.
For example, partial differential equations arise naturally in the pricing of derivative assets. But unlike many places in physics, here it is not sufficient to assume smoothly varying variables. The inherently discrete nature of most financial variables means that derivatives have to be approximated numerically.
Neftci also describes the various types of options, like basket, knock-out, multi-asset and so on. Each has a slightly different modelling. Another key idea involves the time aspect of pricing. So Wiener processes naturally arise, and the text shows how to handle these.
Much more is covered in the book. Perhaps just as importantly, it gives you enough maths preparation that you should be able to analyse other new types of financial instruments. Maybe even ones that you create yourself.
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.
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
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:
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.
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
Covering the essential elements of the subject of econometrics, the author also introduces and explains techniques that are now widely used in applied work, although rarely introduced in detail in non-specialist texts, such as integrated time series, cointegration, simulation analysis, Johansen's Approach to multivariate co-integration and ARCH. The author explains the central distinction between stationary and nonstationary time series, which is of crucial importance in many areas of analysis, especially in macroeconomics and financial economics.
Customer Reviews:
Very useful book.......2006-12-08
This book is useful for several reasons. First, it is readabale without being a collection of "how to" recipes (like, for instance, the book by Enders). It tries hard to provide a theoretical context to the results it presents, and almost always succeeds in so doing. Second, it focuses on selected (4 or 5) but "meaningful" applications (i.e. with all the steps necessary for actual publication, at least back in 1998), dedicating whole chapters to each of them. Third, it contains possibly the best textbook chapter ever written on cointegration (chapter 8, a pearl in my opinion). The VAR-VECM chapters are good too.
The book is not perfect, though. First, it got old soon. There is little or nothing on cointegration and unit root testing with structural breaks, nothing on panel data cointegration, etc. Second, chapter 9 (on endogeneity and the FM-OLS estimator) is somewhat difficult and a little outdated (I mean, who uses FM-OLS estimators in this day and age? What about DOLS?). All in all, is still a nice introduction to time series analysis to people who need to understand why and how things are done in a particular way, as opposed to just how they are done.
An Awkward Treatment of Time Series Econometrics.......2002-01-24
Patterson's text is perhaps one of the worst econometrics textbooks that I have come across in recent years. The writing is cumbersome and unwiedy, the exposition is awkward, and the overall treatment of the subject is rather tiresome, uninspiring.
The only reason that I did not give this book a "one-star" is that it could serve a useful purpose: it can show budding econometric textbook authors how not to write a textbook.
The panacea for studying a stimulated-simulated approach TSA.......2001-08-27
Looking for miracles before examination? This is the book that I have depended on for 2 months to understand time series analysis in a logical manner. The book is an impetus for a much more simpler approach in studying econometrics. The matrix method was not left out which is a stride in understanding the greater complexities of mathematics involved in many econometrics textbook. Written in a lively fashioned aligned with some of the famous empirical studies which are pillars of modern economic thinking. The approach is based on the authors' thinking to act as a support function for many students who are indeed interested to learn the values of empirical analysis in economics. Without this book I would have never apotheosised the study of econometrics in this way. I congratulate the author for his successful scholarly work!!! Your book paved way to my success!
The Long waiting gift for beginners in time series.......2001-02-01
There are many good books on time series analysis, i.e. Enders (1995), Hamilton (1994), and Maddala and Kim (1998). Unfortunately, the books is intended for advance learner. While Enders (1995) is accessible for begginners, it seems getting old and become a nostalgia.
Fortunately, Patterson (2001) has provided a readability book for student and practitioner that all this time has been forgotten by most writers in this subject. Without going into much frighteners (and more likely will confuse the beginners) advance mathematical, matrix, and econometric theory; the book give theoretical insight into what is supposed to be known in the subject. While this book is only a complete refresher (and could be boring) for advance learner, I cannot find a better introduction book.
As detailed reference textbook, it covers basic subject on time series (i.e. ADF test, Engle-Granger procedure, cointegration, VAR, and VECM) up to several higher-level issues such as multiple unit roots, structural and seasonal problems in unit roots/cointegration, ARCH, and GARCH. This book is intended to provide students, researchers, and forecasters with a definitive, self-contained survey of time series analysis.
With intensive application, the book will attract applied academician and practitioner in business sector. 5 chapters exclusively dedicate for application, this equal to 30% of the book contain (around 230 page from 750 page contain). The subject cover in application section are popular subject: money demand, term and structure interest rate, Phillips curve, and exchnage rate. More examples also available in every chapter. From this point of view, the book delivery what its promise in the title: "Applied Econometric; A Time Series Approach".
With such a simplifying way in explaining the subject, the book will be a richly enjoy reading for undergraduate and first year graduate students of all sciences, not only in economics. This much-needed book synthesizes major developments in Time Series into a single, coherent presentation of the current state of the art of this increasingly important field.
Average customer rating:
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Introduction to Multiple Time Series Analysis
Helmut Lütkepohl
Manufacturer: Springer
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Similar Items:
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Time Series Analysis
ASIN: 3540569405 |
Book Description
This graduate level textbook deals with analyzing and forecasting multiple time series. It considers a wide range of multiple time series models and methods. The models include vector autoregressive, vector autoregressive moving average, cointegrated, and periodic processes as well as state space and dynamic simultaneous equations models. Least squares, maximum likelihood, and Bayesian methods are considered for estimating these models. Different procedures for model selection or specification are treated and a range of tests and criteria for evaluating the adequacy of a chosen model are introduced. The choice of point and interval forecasts is considered and impulse response analysis, dynamic multipliers as well as innovation accounting are presented as tools for structural analysis within the multiple time series context. This 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 this book. Applied researchers involved in analyzing multiple time series may benefit from the book as it provides the background and tools for their task. It enables the reader to perform his or her analyses in a gap to the difficult technical literature on the topic.
Book Description
This treatment of extreme value theory is unique in book literature in that it focuses on some beautiful theoretical results along with applications. All the main topics covering the heart of the subject are introduced to the reader in a systematic fashion so that in the final chapter even the most recent developments in the theory can be understood.
Key to the presentation is the concentration on the probabilistic and statistical aspects of extreme values without major emphasis on such related topics as regular variation, point processes, empirical distribution functions, and Brownian motion.
The work is an excellent introduction to extreme value theory at the graduate level, requiring only some mathematical maturity.
Customer Reviews:
for very speculative applications.......2007-06-02
Initially, the problem seems intractable. How to understand a probability distribution with a long tail of possible values? Where this is little or no observed data at these large values. This probably stymied any serious research into this field until recent decades. The book discusses what can be deduced about such distributions, based on known observations at small values.
It is an advanced statistical monograph. Perhaps best suited for at least the graduate level. It differs qualitatively from most texts, but uses standard ideas like the maximum likelihood estimation, and moment estimators.
As to the applications of this book, that is also speculative. It is hoped that in fields like finance, the ideas can be used to posit more realistic models of rare but potentially catatrophic events.
Average customer rating:
|
Introduction To Dynamic Economic Models
Brian S. Ferguson , and
G.C. Lim
Manufacturer: Manchester University Press
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Binding: Paperback
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ASIN: 0719049970 |
Book Description
This book is about economic dynamics--about how the economy adjusts over time. Its focus is on economic analysis rather than mathematics, so unlike many other books in the field which treat mathematics as the core and choose economic examples to suit the requirements of the math, it keeps the focus on the economics, treating mathematics as a tool of economic analysis. The book is example-driven, built around models drawn from a wide range of fields in economics. The focus of the illustrations is qualitative analysis of the sort found in economic journals, and the structure of the models is dictated by the requirements of the economic analysis. Unnecessary complexity has been avoided, yet the models have been presented in the same general form as they appear in the professional literature.
Customer Reviews:
A reader from KL.......2003-07-14
An excellent book for a beginner in dynamic economic models. It is presented in a simpler way that readers could them without much difficulty.
Book Description
Statistical physics concepts such as stochastic dynamics, short- and long-range correlations, self-similarity and scaling, permit an understanding of the global behavior of economic systems without first having to work out a detailed microscopic description of the system. This pioneering text explores the use of these concepts in the description of financial systems, the dynamic new specialty of econophysics. The authors illustrate the scaling concepts used in probability theory, critical phenomena, and fully-developed turbulent fluids and apply them to financial time series. They also present a new stochastic model that displays several of the statistical properties observed in empirical data. Physicists will find the application of statistical physics concepts to economic systems fascinating. Economists and other financial professionals will benefit from the book's empirical analysis methods and well-formulated theoretical tools that will allow them to describe systems composed of a huge number of interacting subsystems.
Customer Reviews:
Excellent Introduction.......2004-12-01
This book is an excellent introduction to financial analitics for Physicists and also for others. Though a little out dated, but what can you expect from such a fast changing subject?
This is not the first book I have read in this subject, but it is my favorite right now. I could have saved myself a lot of trouble if this would have been the first.
Nevertheless, it should be considered as an intial reference point and not as to expect it to contain all the details. After all it only has 148 pages.
target audience not defined.......2003-09-22
I find the book rather poorly written in the aspect of providing links between statistical physics and its application in economics. As a physicist with a background in stochastic processes, I was looking for an introduction to their applications to economic analysis, complete with examples and discussion of the methods' limitations. The book was somewhat disappointing in this respect. Quite often, in many chapters, the necessary math is explained, then some aspects of how it is manefest in economical data are presented and then the chapter ends, leaving the reader wonder what the specific cases may be and if it is practical to use those methods at all. Above all, there is very little discussion as to what the results actually mean, in economical terms.
I believe the book may be helpful for reseachers active in this field but I would not recommend it as a first introduction to econophysics. For economists, the math may be rather difficult to go through as some of the fundamental concepts are not defined consistently. For physicists with no previous exposure to econophysics, I would prefer to see more economics.
Not bad, considering..........2002-08-13
The book is not bad considering the total lack of existence of intelligible literature in this supposedly vast field.
The content is really a collection of quickie crib-sheets on a sundry of topics with nominally common theme: Finance.
A lot of the actually useful stuff is the author's previously published papers on price-return distributions.
Aside from his own previously published work, he has a good tutorial on the GARCH scheme though with precious little follow up reading resources for delving in deeper (or even sideways).
This book is priced far too high given its content and depth.
Look for a used copy, and do not count on the author to answer questions by email.
First in the new field.......2002-06-05
I found several parts of this book useful while preparing lectures for an introductory econophysics course in Fall, 2001. The discussions of convolutions of distributions, Levy distributions and scaling are well-written and easy to follow. In the brief discussion of the St. Petersburg Paradox I missed a critical discussion of expected utility, which was invented by Bernoullli to 'resolve' that paradox. Spurred by von Neumann and Morgenstern, neo-classical economics relies on the idea of expected utility, which seems empirically to be wrong. The chapter on time correlations is also very readable (although Wiener processes are not 1/f^2 noise!). ARCH and GARCH methods are discussed, saving the student from the pain of reading badly-written papers by mathematically-minded economists, but the chapters on options are too brief with nothing new. The best introduction to options is still the original Black-Scholes paper (excepting their erroneous claim that CAPM and the delta-hedge strategy produce option pricing pdes that agree with each other). Also, it would have been nice to have seen a discussion of CAPM. The discussion of algorithmic complexity left me cold (see my earlier books and papers on nonlinear dynamics), and I would like to have seen a critical discussion of the EMH. These criticisms are ok, though, the gaps leave something for the rest of us to work on.
Physicists Land On Planet Economics.......2001-06-11
SINCE the last decade, physicists have been trying to cope with the issues traditionally approached by economics using their own tools and methodologies. This research has been dubbed 'econophysics'. One reason why this incursion should be welcomed is the failure of mainstream economics to recognise financial systems as complex systems. Take mainstream international finance, for instance. In the most respectable workhorse model--so-called 'new open economy macroeconomics model'--foreign exchange rates always reach some sort of stable equilibrium. To put it bluntly, this means that currencies do not exhibit complex behaviour.
However, financial markets do demonstrate several of the properties that characterise complex systems. What is more, they are highly complex, open systems in which many subunits interact nonlinearly in the presence of feedback and stable governing rules. Earlier attempts to find chaos in financial data, for instance, have been disappointing exactly because the phenomenon is likely to emerge in systems which are only moderately complex. Although it cannot be ruled out that financial markets follow chaotic dynamics, econophysics assumes that asset price dynamics are stochastic processes.
A fundamental commitment of the mainline model of international finance is to theory itself, and not to data. Modelling is devoted to equipping the discipline with an underlying rational behaviour at the individual level. Yet this is at odds with the fact that financial markets are prone to collective 'irrational exuberance'. Instead, econophysics attemps to build up stochastic models that encompass essential features observed in the financial data. Now that the time evolution of many financial markets is continually monitored, it is possible to test the accuracy and predictive power of the developed models using available data. One common objection to such a practice is that it is impossible to perform large-scale experiments in economics that could falsify any given theory. The authors note that this limitation is not specific to economics, but also affects such well developed areas of physics as astrophysics, atmospheric physics, and geophysics. By analogy with the activity in these more established areas, we are able to test and falsify any theories associated with the current available sets of financial data.
Complex systems can sometimes behave in remarkable simple ways. These are reflected in power law distributions and scaling. The authors illustrate these concepts and others, and apply them to the financial time series. The book is thus useful not only for physicists but also for economists and people in the financial world. Some familiarity with probability theory or statistical physics is required, though. Economists dissatisfied with the mainline approach of their discipline will find the book opportune. The others might end up welcoming econophysics as well. After all, economists implicitly see physics as nature's economics. What is then wrong with physicists thinking of economics as social physics?
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