Applied Probability and Stochastic Processes Review

Average Reviews:

(More customer reviews)I randomly ran across this book in my math library trying to find an extra book to help with the difficult Stochastics Process class I was taking. Little did I know I would find a book I value as much as Douglas Kelly's Introduction to Probability. This book has applied problems and examples! It is not the dry, endless pages of confusing equations we have come to expect from Stochastics Processes books. There is something better out there! This book saved me as an undergraduate, and am now looking forward to it living up to my God like expecations as a post grad. If you are a professor, please use this book for you students. It ties together and lets you appreciate many fields such as linear analysis and even graph theory from computer science. This book will not disappoint.

Click Here to see more reviews about: Applied Probability and Stochastic Processes

This book presents applied probability and stochastic processes in an elementary but mathematically precise manner, with numerous examples and exercises to illustrate the range of engineering and science applications of the concepts. The book is designed to give the reader an intuitive understanding of probabilistic reasoning, in addition to an understanding of mathematical concepts and principles. The initial chapters present a summary of probability and statistics and then Poisson processes, Markov chains, Markov processes and queuing processes are introduced. Advanced topics include simulation, inventory theory, replacement theory, Markov decision theory, and the use of matrix geometric procedures in the analysis of queues.Included in the second edition are appendices at the end of several chapters giving suggestions for the use of Excel in solving the problems of the chapter. Also new in this edition are an introductory chapter on statistics and a chapter on Poisson processes that includes some techniques used in risk assessment. The old chapter on queues has been expanded and broken into two new chapters: one for simple queuing processes and one for queuing networks. Support is provided through the web site http://apsp.tamu.edu where students will have the answers to odd numbered problems and instructors will have access to full solutions and Excel files for homework.

Get 21% OFF

Click here for more information about Applied Probability and Stochastic Processes

Read More...

Probability, Stochastic Processes, and Queueing Theory: The Mathematics of Computer Performance Modeling Review

Average Reviews:

(More customer reviews)This book is suitable for my graduate studies on computer performance. The author directs us from combinatorics, distribution theory, queue theory to queueing networks in a systematic way. I have read the book at ease for its stepwise elaboration of concepts. However, I have also read with hardship as it requires the readers to possess a good command of mathematics, both pure and applied, in order to go through the book.
For a mathematics graduate studying computer networks, I recommend this book. A novice or a mediocrity should pay more patience to read if not yet at a loss.
This book has aroused my interest and eagerness to know more about computer performance from the viewpoint of queueing and networking. In a word, I enjoy reading this book.

Click Here to see more reviews about: Probability, Stochastic Processes, and Queueing Theory: The Mathematics of Computer Performance Modeling

This textbook provides a comprehensive introduction to probability and stochastic processes, and shows how these subjects may be applied in computer performance modelling. The author's aim is to derive the theory in a way that combines its formal, intuitive, and applied aspects so that students may apply this indispensable tool in a variety of different settings. Readers are assumed to be familiar with elementary linear algebra and calculus, including the concept of limit, but otherwise this book provides a self-contained approach suitable for graduate or advanced undergraduate students. The first half of the book covers the basic concepts of probability including expectation, random variables, and fundamental theorems. In the second half of the book the reader is introduced to stochastic processes. Subjects covered include renewal processes, queueing theory, Markov processes, and reversibility as it applies to networks of queues. Examples and applications are drawn from problems in computer performance modelling.

Get 21% OFF

Click here for more information about Probability, Stochastic Processes, and Queueing Theory: The Mathematics of Computer Performance Modeling

Read More...

Financial Modeling Under Non-Gaussian Distributions (Springer Finance) Review

Average Reviews:

(More customer reviews)This book is an outstanding a clear presentation of non-Gaussian financial modeling. In financial markets, the Gaussian curve or bell curve, is not accurate in that most markets are skewed (a predisposition to grow on average, not zero) and fat-tailed (rare events such as market crashes happen more often than a Gaussian curve would suggest). Therefore, non-Gaussian modeling is essential to make money in the market or assess risk. This book goes through all the new techniques of non-Gaussian modeling. It does an exceptional job discussing the GARCH generalized autoregressive conditional heteroskedasticity. This is but a fancy word for fluctuations in volatility over time pretty much dependent on recent fluctuations. It works very well I must say empirically, and has tripled the rationality and profitability of my portfolio - especially one of the versions of the GARCH over the others reviewed - but which one I'd rather not say, for obvious reasons ;) The book is weakest at page 183 or so, with the models and I was rather disappointed with the exclusion of the market crash of the 80s in the empirical analysis - wouldn't rare events be the main reason for improving non-Gaussian modeling? Anyway it's rather poor, but thorough, with additive and multivariate GARCHes but the fault lies with the faultiness of the theories not the authors, at least they're encyclopedic. The book picks up at the end with copulas, and a complete discussion of non-Gaussian option pricing. The review of BSM is appreciated and actually well-done, and a nice reminder of what we are trying to improve on exactly. I think this is a most incredible book, very clearly written, and at times, quite an enjoyable read for such a topic. All it takes is multivariate calculus and basic statistics, but more math ability will make the implications and comments breathtaking at times. I often find myself inspired by a passage or footnote to create a whole subroutine in R or python. I think avoiding Bayesian topics and Monte Carlo was disappointing, but wise in terms of focus. A great book for graduate mathematics in applications of statistics or stochastic calculus, or a good book for modeling fundamentals in economics or business management at the post-graduate level.


Click Here to see more reviews about: Financial Modeling Under Non-Gaussian Distributions (Springer Finance)

This book examines non-Gaussian distributions. It addresses the causes and consequences of non-normality and time dependency in both asset returns and option prices. The book is written for non-mathematicians who want to model financial market prices so the emphasis throughout is on practice. There are abundant empirical illustrations of the models and techniques described, many of which could be equally applied to other financial time series.

Get 20% OFF

Click here for more information about Financial Modeling Under Non-Gaussian Distributions (Springer Finance)

Read More...

Interest Rate Modeling. Volume 1: Foundations and Vanilla Models Review

Average Reviews:

(More customer reviews)About me: I am a trader in rates volatility and have a MS degree in MFE. I have only read the vol 1 of the 3 books so I am only reviewing the vol 1.
The book is more or less seperated into 2 parts: chap 1 to 5 are introductory materials for required math and numerical methods, and chap 6 to 9 are where things gets bit more technical and interesting. To me, if you want to get something out of this book you got to be comfortable with quants stuff, some basics like "Continuous time finance 2" from Shreve is required before you start this book. I found the material in chap6 to 9 interesting and instructive. There are many books about local and stochastic vols but I have yet to find any book that covered the material from head to toe like this book. The style of the writing is theory/proof/remark/example, and the derivations of the proof and formula is not too hard to follow, as long as you have the background as I mentioned before. The author also covered some important results from recent papers in the field, and talked about implementation challenges in numerical methods, which is very detail and I think it provides some coverage of the gap from theory to implementation. I'd love to read more about the details of what the banks used in their desks but I guess the authors would not expose what they really used at their work.
Overall this is a good book for quants. For traders I think vol 1 could be too technical and not much use because it does not cover the pricing and hedging of specific vol products, which is supposed to be in vol 3.

Click Here to see more reviews about: Interest Rate Modeling. Volume 1: Foundations and Vanilla Models

Table of contents for all three volumes (full details at andersen-piterbarg-book.com)Volume I. Foundations and Vanilla Models Part I. Foundations
Introduction toArbitrage Pricing Theory
Finite Difference Methods
Monte Carlo Methods
Fundamentals of Interest Rate Modelling
Fixed Income Instruments
Part II. Vanilla Models
Yield Curve Construction and Risk Management
Vanilla Models with Local Volatility
Vanilla Models with Stochastic Volatility I
Vanilla Models with Stochastic Volatility II
Volume II. Term Structure Models Part III. Term Structure Models
One-Factor Short Rate Models I
One-Factor Short Rate Models II
Multi-Factor Short Rate Models
The Quasi-Gaussian Model with Local and Stochastic Volatility
The Libor Market Model I
The Libor Market Model II
Volume III. Products and Risk Management Part IV. Products
Single-Rate Vanilla Derivatives
Multi-Rate Vanilla Derivatives
Callable Libor Exotics
Bermudan Swaptions
TARNs, Volatility Swaps, and Other Derivatives
Out-of-Model Adjustments
Part V. Risk management
Fundamentals of Risk Management
Payoff Smoothing and Related Methods
Pathwise Differentiation
Importance Sampling and Control Variates
Vegas in Libor Market Models
Appendix
Markovian Projection

Get 10% OFF

Click here for more information about Interest Rate Modeling. Volume 1: Foundations and Vanilla Models

Read More...

Interest Rate Modeling. Volume 3: Products and Risk Management Review

Average Reviews:

(More customer reviews)I have read the vol 1 and vol 3. This review is for vol 3 only. After reading vol 1 (pls refer to my review for Vol 1) I was very impressed with the theoretical coverage and numerical tips, given by the authors who are probably the best quants on the street. Having this in mind I was expecting the same excitement and detail coverage for a wide range of vol products in vol 3. Now I have briefly finished reading vol 3, I have to say my feeling of vol 3 is mixed. I love the theortical treatment very well, the mapping in chap 16, the spread options in chap 17, the different improvements of regression in chap 18, the bermudans in 19, etc. The good thing is the subject is talked in detail with proofs and some implementation tips, and it is hard to find such material in other quant books. However, I feel something is missing. Some real trade examples maybe would fill some blanks. Just how to vega hedge a perticular CLE in real life, for example? I know there is no simple answer but would love to see how the big banks are doing it. I was expecting the authors discuss the hedging strategy for various type of vol products, 1 by 1, in detail, but I was a bit disappointed. Another pity I feel is the lack of discussion of forward vol and certain 2nd-order derivative profiles for the callables. Such as negative volga for accretor callables, I think every vol trader on the street knows this is ugly, however the authors didn't talk about it. Maybe the focus of this book is mainly about pricing models but not hedging/managing a vol book. Well, there are really too many things to cover I guess so can't expect a perfect book. Overall I would still highly recommend this book for quants and vol traders.

Click Here to see more reviews about: Interest Rate Modeling. Volume 3: Products and Risk Management

Table of contents for all three volumes (full details at andersen-piterbarg-book.com)Volume I. Foundations and Vanilla Models Part I. Foundations
Introduction toArbitrage Pricing Theory
Finite Difference Methods
Monte Carlo Methods
Fundamentals of Interest Rate Modelling
Fixed Income Instruments
Part II. Vanilla Models
Yield Curve Construction and Risk Management
Vanilla Models with Local Volatility
Vanilla Models with Stochastic Volatility I
Vanilla Models with Stochastic Volatility II
Volume II. Term Structure Models Part III. Term Structure Models
One-Factor Short Rate Models I
One-Factor Short Rate Models II
Multi-Factor Short Rate Models
The Quasi-Gaussian Model with Local and Stochastic Volatility
The Libor Market Model I
The Libor Market Model II
Volume III. Products and Risk Management Part IV. Products
Single-Rate Vanilla Derivatives
Multi-Rate Vanilla Derivatives
Callable Libor Exotics
Bermudan Swaptions
TARNs, Volatility Swaps, and Other Derivatives
Out-of-Model Adjustments
Part V. Risk management
Fundamentals of Risk Management
Payoff Smoothing and Related Methods
Pathwise Differentiation
Importance Sampling and Control Variates
Vegas in Libor Market Models
Appendix
Markovian Projection

Click here for more information about Interest Rate Modeling. Volume 3: Products and Risk Management

Read More...

Dynamic Term Structure Modeling: The Fixed Income Valuation Course & CD-ROM (Wiley Finance) Review

Average Reviews:

(More customer reviews)I came across this book in my library and decided to buy it after browsing it. What I like about it is that it gives all the explicit formula for analytical affine DTSM, such as multifactor Vasicek model, multifactor CIR model, and mixed Vasicek-CIR model, as well as the risk neutral models (+, ++ and +++) models. A lot of detail in close to 700 pages. Very useful as a reference. The book also gives tree implementations of DTSM but personally I have not used them.

Click Here to see more reviews about: Dynamic Term Structure Modeling: The Fixed Income Valuation Course & CD-ROM (Wiley Finance)

Praise for Dynamic Term Structure Modeling"This book offers the most comprehensive coverage of term-structure models I have seen so far, encompassing equilibrium and no-arbitrage models in a new framework, along with the major solution techniques using trees, PDE methods, Fourier methods, and approximations. It is an essential reference for academics and practitioners alike." --Sanjiv Ranjan DasProfessor of Finance, Santa Clara University, California, coeditor, Journal of Derivatives"Bravo! This is an exhaustive analysis of the yield curve dynamics. It is clear, pedagogically impressive, well presented, and to the point." --Nassim Nicholas Talebauthor, Dynamic Hedging and The Black Swan"Nawalkha, Beliaeva, and Soto have put together a comprehensive, up-to-date textbook on modern dynamic term structure modeling. It is both accessible and rigorous and should be of tremendous interest to anyone who wants to learn about state-of-the-art fixed income modeling. It provides many numerical examples that will be valuable to readers interested in the practical implementations of these models."--Pierre Collin-DufresneAssociate Professor of Finance, UC Berkeley"The book provides a comprehensive description of the continuous time interest rate models. It serves an important part of the trilogy, useful for financial engineers to grasp the theoretical underpinnings and the practical implementation."--Thomas S. Y. Ho, PHDPresident, Thomas Ho Company, Ltd, coauthor, The Oxford Guide to Financial Modeling

Get 37% OFF

Click here for more information about Dynamic Term Structure Modeling: The Fixed Income Valuation Course & CD-ROM (Wiley Finance)

Read More...

Interest Rate Modeling. Volume 2: Term Structure Models Review

Average Reviews:

(More customer reviews)I really find "Interest Rate Modeling" by Leif Andersen and Vladimir Piterbarg not only the best practical guide on interest rates derivatives modeling but also one of the best books on quantitative finance, in general. It is no wonder that many quants supporting asset classes other than interest rates derivatives bought this book as well. It is not only rigorous to ensure good understanding and giving the big picture but also very practical showing what would work in practice and what not, and how (using what tools) it can be achieved. Other books sometimes go on describing in details models that no one would ever use in practice just for the sake of completeness, or never discuss implementation details, which are the most important if the model is to be applied in practice (not mentioning curves building, Greeks and Risk Management). I am sure that every trading desk has already got a few copies of this book for reference: before it was a sharp need for a comprehensive interest rate derivatives book in practice like that. It is comprehensive because it methodologically covers all the components for successful understanding, development, and application of interest rates modeling in practice: mathematical and financial background (with tractable proofs and very useful references), the detailed description of traded interest rate derivatives, various practically applicable models (from basic to the most sophisticated) and numerical methods in a very systematic and consistent approach. I really recommend this book to everyone interested in quantitative finance: equally to academics (including students in financial engineering, mathematical finance etc) and practitioners.

Click Here to see more reviews about: Interest Rate Modeling. Volume 2: Term Structure Models

Table of contents for all three volumes (full details at andersen-piterbarg-book.com)Volume I. Foundations and Vanilla Models Part I. Foundations
Introduction toArbitrage Pricing Theory
Finite Difference Methods
Monte Carlo Methods
Fundamentals of Interest Rate Modelling
Fixed Income Instruments
Part II. Vanilla Models
Yield Curve Construction and Risk Management
Vanilla Models with Local Volatility
Vanilla Models with Stochastic Volatility I
Vanilla Models with Stochastic Volatility II
Volume II. Term Structure Models Part III. Term Structure Models
One-Factor Short Rate Models I
One-Factor Short Rate Models II
Multi-Factor Short Rate Models
The Quasi-Gaussian Model with Local and Stochastic Volatility
The Libor Market Model I
The Libor Market Model II
Volume III. Products and Risk Management Part IV. Products
Single-Rate Vanilla Derivatives
Multi-Rate Vanilla Derivatives
Callable Libor Exotics
Bermudan Swaptions
TARNs, Volatility Swaps, and Other Derivatives
Out-of-Model Adjustments
Part V. Risk management
Fundamentals of Risk Management
Payoff Smoothing and Related Methods
Pathwise Differentiation
Importance Sampling and Control Variates
Vegas in Libor Market Models
Appendix
Markovian Projection

Get 11% OFF

Click here for more information about Interest Rate Modeling. Volume 2: Term Structure Models

Read More...