Book Description
Gain the statistical tools and techniques you need to understand today's financial markets with the Second Edition of this critically acclaimed book.
Youll find a comprehensive and systematic introduction to financial econometric models and their applications in modeling and predicting financial time series data. This edition continues to emphasize empirical financial data and focuses on real-world examples. Youll master key aspects of financial time series, including volatility modeling, neural network applications, market microstructure and high-frequency financial data, continuous-time models and Ito's Lemma, Value at Risk, multiple returns analysis, financial factor models, and econometric modeling via computation-intensive methods.
This is an ideal textbook for MBA students and a key reference for researchers and professionals in business and finance. Order your copy today.
Download Description
Analysis of Financial Time Series, Second Edition provides a comprehensive and systematic introduction to current financial econometric models and their applications to modeling and prediction of financial time series data. It utilizes real-world examples and real financial data throughout the book to apply the models and methods described. The author begins with basic characteristics of financial time series data before covering three main topics: analysis and application of univariate financial time series; the return series of multiple assets; and Bayesian inference in finance methods.
Customer Reviews:
Excellent and detailed reference.......2007-05-03
The coverage of the topic is broad and deep. It is one of the few introductory books that devotes some space to transfer function modeling and does so intelligibly.
A must have for the novice as well as those more familiar with the topic that need a solid reference.
The best for Masters level, great all-around.......2007-02-12
This text is absolutely perfect for Masters students learning financial econometrics. There is a little theory, clear explanations, and quite a few real world examples. (I don't think any text would tell the reader what model to use when, because that's application-specific.) It assumes some knowledge of finance and basic econometrics/statistics, which is fair enough. To get more theory, Hamilton (1994) remains the authority, and Campbell, Lo, MacKinlay (1997) is a great introduction for PhD students, and generally an ideal companion volume to this one.
Excellent reference!.......2006-11-05
This book is an excellent toolbox for anyove dealing in the field of financial engineering, however, as a real toolbox, the author doesn't explain the exact use of all tools and how to interpret the results. This is why this book is for advanced users who need a well documented reference but it is not very suitable for beginners in the field. The Splus code is welcome.
Broad coverage, but not for the faint-hearted.......2006-07-05
Written by a University of Chicago professor, this book comprehensively covers times series topics relative to investment and trading-oriented finance (i.e., Wall Street money-making machines). Treatment is generally clear and thorough, but an advanced math and stat background is an absolute prerequisite for understanding the materials.
S-Plus/R code is given, but strangely, there is very little on *why* and
*when* one uses each of the techniques. Under what cirmcustances should I use or not use GARCH? What exactly is PCA good for in real-world applications? These important questions are not answered, in other words, you don't get a sense of the real-world context for these topics.
Best textbook I have ever read .......2005-09-19
First of all, it is well written in a very practical point of view. The whole book is aimed fullly to real financial data(appended in the author's web). People can gain not only the well-explained theories but the hand-on experience with data analysis using SPLUS or any other package.
Secondly, the author is a real expert in this field and has been publishing lots of nice work. All models in the book are clearly illustrated and commented.
Thirdly, it covers a lot of topics in analysis of FT. Reader can learn almost all the valuable things in this field from this book.
If anyone wanna truly learn this book, she/he has to sit down and plays some real data on computer. I think this is the best way and the only way to use this book.
Average customer rating:
- Well researched , but a bit dry
- Against The Gods, a highly recommended book for MBA
- So Close to Wonderful
- Unpretentious and pleasant
- Are you risk-seeker or risk-averse?
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Against the Gods: The Remarkable Story of Risk
Peter L. Bernstein
Manufacturer: Wiley
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ASIN: 0471121045 |
Amazon.com
With the stock market breaking records almost daily, leaving longtime market analysts shaking their heads and revising their forecasts, a study of the concept of risk seems quite timely. Peter Bernstein has written a comprehensive history of man's efforts to understand risk and probability, beginning with early gamblers in ancient Greece, continuing through the 17th-century French mathematicians Pascal and Fermat and up to modern chaos theory. Along the way he demonstrates that understanding risk underlies everything from game theory to bridge-building to winemaking.
Book Description
A Business Week, New York Times Business, and USA Today Bestseller
"Ambitious and readable . . . an engaging introduction to the oddsmakers, whom Bernstein regards as true humanists helping to release mankind from the choke holds of superstition and fatalism." -The New York Times
"An extraordinarily entertaining and informative book." -The Wall Street Journal
"A lively panoramic book . . . Against the Gods sets up an ambitious premise and then delivers on it." -Business Week
"Deserves to be, and surely will be, widely read." -The Economist
"[A] challenging book, one that may change forever the way people think about the world." -Worth
"No one else could have written a book of such central importance with so much charm and excitement." -Robert Heilbroner author, The Worldly Philosophers
"With his wonderful knowledge of the history and current manifestations of risk, Peter Bernstein brings us Against the Gods. Nothing like it will come out of the financial world this year or ever. I speak carefully: no one should miss it." -John Kenneth Galbraith Professor of Economics Emeritus, Harvard University
In this unique exploration of the role of risk in our society, Peter Bernstein argues that the notion of bringing risk under control is one of the central ideas that distinguishes modern times from the distant past. Against the Gods chronicles the remarkable intellectual adventure that liberated humanity from oracles and soothsayers by means of the powerful tools of risk management that are available to us today.
"An extremely readable history of risk." -Barron's
"Fascinating . . . this challenging volume will help you understand the uncertainties that every investor must face." -Money
"A singular achievement." -Times Literary Supplement
"There's a growing market for savants who can render the recondite intelligibly-witness Stephen Jay Gould (natural history), Oliver Sacks (disease), Richard Dawkins (heredity), James Gleick (physics), Paul Krugman (economics)-and Bernstein would mingle well in their company." -The Australian
Customer Reviews:
Well researched , but a bit dry.......2007-10-16
As a statistics and economics teacher, I naturally jumped at this book. But while I found some parts to be interesting, I didn't love it. All too often, I found it a bit boring -- not nearly a page turner, like When Genius Failed, Fortune's Formula, Fermat's Enigma, or many other books that Amazon puts on the boat. It read to me more like a history textbook on a niche subject -- not really what I was hoping for.
I did learn a lot from reading it, but I found that I could only read one short chapter at a time before nodding off.
Against The Gods, a highly recommended book for MBA.......2007-09-18
The reason that I bought this book was because it was highly recommended by the teachers at my MBA class.
They were not kidding, from head to toe its very good and kept my attention till the end. It has been of great help to me. Aside the history content it helps you to think on how to mitigate risk and how improve the opportunities.
So Close to Wonderful.......2007-08-14
Bernstein does an adequate job bringing the concepts together, but this is not a page-turner. I found myself reading on for the promise of insight, and he offers some, but the writing is a bit dull.
Unpretentious and pleasant.......2007-07-10
Bernstein is an interesting writer since he is the consummate finance insider- a practioner, regulator and academic. This range helps and harms the book - in his efforts to render the history of risk, he delves into anecdotal caricatures while amusing definitely smack of basis risk with the underlying ideas that are provocative enough! I found the behavioural finance and derivatives section to be rather basic but then realised the book was written in 1996. It's a pleasant read but a more pragmatic introduction to probability is the infinitely witty Cartoon Guide to Statistics.
Are you risk-seeker or risk-averse?.......2007-07-01
According to this book you are both, it only depends on the point of view that is presented. I enjoy the book from the beginning to end, especially the last three chapters. The history and analysis of rational behavior is enlightening, to anyone who has ever thought about the process of decision.
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
Both in insurance and in finance applications, questions involving extremal events (such as large insurance claims, large fluctuations in financial data, stock market shocks, risk management, ...) play an increasingly important role. This book sets out to bridge the gap between the existing theory and practical applications both from a probabilistic as well as from a statistical point of view. Whatever new theory is presented is always motivated by relevant real-life examples. The numerous illustrations and examples, and the extensive bibliography make this book an ideal reference text for students, teachers and users in the industry of extremal event methodology.
Customer Reviews:
largest book written on extremes.......2002-01-30
This book presents extreme value theory and its applications with the finance industry as its primary target. There have been many excellent texts written on extreme value theory but none this extensive. As the authors admit even as extensive as it is the theory of multivariate extremes is neglected. They chose to only cover in detail the theory that is mature enough for application.
What you will find here that is not in many texts on this subject is a treatment of risk theory and fluctuations of sums and various time series models including cases with heavy-tailed marginal distributions.
Chapter 8 on special topics is particularly interesting with a lot of coverage for the extremal index, large claim index, ARCH processes, large deviations, reinsurance, stable processes and self-similarity. The book contains over 600 references to the literature and is a welcome resource for practitioners in finance and insurance as well as extreme value theorists.
Highly recommended.......2000-08-15
This book covers the theory and applications of extremal value theory (an area of applied probability). The mathematics is kept at an acceptable level, i.e. advanced undergraduates in math/physics/engineering, but the breadth and the sophistication of the statements are such that the results are never trivial. Chapters 2-3-4 introduce the reader to the property of sums, maxima and order statistics of random variables. Many results are only stated but not proved. Yet, this does not detract to the readability of the book. Chpater 5 treats point processes and requires a deeper mathematical background. Among the chapters, this was the most disappointing to me. The monographs of Resnick and of Kallenberg, as well as many good introductions to point processes in queueing theory, are in my opinion both a more intuitive and rigorous introduction to random measures. This is not a major flaw of the book, given its view toward applications; and besides this, the bibliographical notes will point the reader to the relevant literature. Chapter 6, on statistical analysis of extremal events, is enjoyable and extremely useful for practitioners in finance and insurance. Chapter 7 touches upon time series and its relation to heavy tails. Finally, chapter 8 is a put-pourri of topics: ARCH processes, stable processes, self-similarity. Overall, I found this book useful as a reference, but sometimes lacking in focus: some topics seem juxtaposed with no clear logical continuity. Another potential shortcoming of the book is that it is neither completely rigorous nor completely readable (i.e., an undergraduate-level book). At the same time, these can be considered as qualities: with regards to the former, there is plenty of material to consult and draw inspiration from; and at the same time each reader will find the "right" level of mathematics in the book. In my opinion the final balance is largely positive, and I would recommend this book without hesitation.
Book Description
The estimation and validation of the Basel II risk parameters PD (default probability), LGD (loss given default), and EAD (exposure at default) is an important problem in banking practice. These parameters are used on the one hand as inputs to credit portfolio models, on the other to compute regulatory capital according to the new Basel rules. The book covers the state-of-the-art in designing and validating rating systems and default probability estimations. Furthermore, it presents techniques to estimate LGD and EAD. A chapter on stress testing of the Basel II risk parameters concludes the monograph.
Customer Reviews:
A good introduction.......2007-08-07
For anyone who needs to learn the financial philosophy and mathematical formalism behind the Basel II accords, this book will be an excellent introduction. Consisting of a collection of articles written competently and concisely, the book should be on the shelf of those who are not only responsible for implementing the Basel II accords but also work in the trenches on how to validate it with respect to the banking institutions in which they are employed. The technical details behind the Basel II accords are straightforward to understand mathematically, but the accords can be delicate to implement from a data collection standpoint. However the latter is not addressed in this book, with emphasis primarily given to the formalism and how to validate it in real situations.
Due to its mathematical rigor the chapter on PD validation by R. Rauhmeier is one of the more valuable ones in the book. It deals with mathematical methods for assessing the quality of estimates for PD, but gives examples from practical banking experience. Most interesting is that the author discusses how to compare rating systems developed by human experts with those that result from machines (algorithmic ratings with no human input). Along these lines, the author views a rating system as essentially a collection of modules, the first one of which is called a `machine rating' since it estimates the PD by an algorithm based on statistical models and not therefore dependent on human judgment (excluding the judgment of the developer of the algorithm of course). The machine rating is then subjected to expert opinion in the second module, wherein it is expected that the rating will be adjusted according to the judgments (and biases) of the (human) expert. The third module is also very standardized, and deals with the degree to which the borrower is supported by others when in financial distress. Any support structure that exists will of course influence the PD of the borrower. Manual overrides that arise because of exceptional situations are part of the fourth and final module. The author views the rating model as `default generating process' which is function of certain selected risk drivers, and is typically measured in terms of rating scales. He gives an example of a `master scale' in this chapter, with this one deploying a "point-in-time" rating approach.
Most of the chapter is devoted to finding PD validation methods that can test all the rating grades simultaneously. One of these is the Spiegelhalter test, which uses as a test statistic the ratio of the difference between the observed mean square error and the expected mean square and the square root of the variance of the mean square error. If the null hypothesis, namely that the forecasted and observed default probabilities are equal for every obligor, then this ratio is normally distributed and then standard techniques can be used. The Spiegelhalter test helps to remove the bias that exists in merely averaging the PDs of obligors in the same rating grade, but it does assume that the default events are independent. The assumption that the default events are independent can be dropped by using Monte Carlo simulations, and the author gives the reader a taste of how to do this in this chapter. As is typical in Monte Carlo simulations, random paths are generated in order to approximate the distribution of the test statistic. The author discusses an explicit simulation study using various choices of the asset correlation parameter, and it is clear that its value has a dramatic effect on the distribution of the test statistic. It would have been helpful if the author had expounded on how to calculate the value of the asset correlation parameter and discussed its connection with various credit risk models, such as the Merton model.
The last chapter of the book discusses stress testing, which the authors define as the study of risk characteristics to fictional perturbations or shocks. Stress testing is practiced widely in the financial industry, especially when sudden and dramatic losses occur in credit portfolios. These losses can surprise risk managers and create extreme skepticism towards the mathematical models used for forecasting. It follows of course that the Basel II accords would be interested in stress testing, but the authors of this chapter assert that they do not yet have the level of sophistication that one can find in the financial industry nor are they precise. The methods that the Basel II accords recommend are reviewed in this chapter. In this regard the authors point out that it is the probability of default (PD) that is the parameter of interest for stress testing, since the EAD and the LGD are relatively insensitive to radical events by their very definition. The PD is varied either by modifying rating grades or by modifying the PDs of the rating grades used for the stress test. The authors give an example of a stress test involving a very well-diversified "virtual" portfolio which shows the effects on regulatory and economic capital of various shocks, such as dramatic rises (and drops) in the oil price, recessions, and appreciative drops in the stock market index. Real portfolios they argue will exhibit even more dramatic effects, since they are not as diversified as this example. It would have been more helpful if the authors had included a more rigorous analysis, possibly one that uses Monte Carlo simulations or extreme value theory, but as applied to a practical situation that risk managers might encounter. One example might be the extreme losses that occurred in mortgage portfolios beginning in the third quarter of 2006. These losses took the risk community completely by surprise, and the forecasting models in place at the time, even though they underwent considerable stress testing before these losses began accelerating, were unable to predict them. The lesson to be learned from this example is that one must perform stress testing not with scenarios that may not have occurred in the past. The imagining of hypothetical scenarios that may shock a portfolio but that have never been realized in the past will be an important part of the future game of stress testing.
Good practice cooke book.......2007-05-21
Good by all segments of Basel II risk components. Especially on EAD, LGD and partly on retail the domains not so frequently worked out in other similar book. Perhaps some more effort on retail, concentrationa and economic capital. But that could be a new book allready. Stress test domain is good example.
Book Description
Discover how to optimize business strategies from both qualitative and quantitative points of view
Operational Risk: Modeling Analytics is organized around the principle that the analysis of operational risk consists, in part, of the collection of data and the building of mathematical models to describe risk. This book is designed to provide risk analysts with a framework of the mathematical models and methods used in the measurement and modeling of operational risk in both the banking and insurance sectors.
Beginning with a foundation for operational risk modeling and a focus on the modeling process, the book flows logically to discussion of probabilistic tools for operational risk modeling and statistical methods for calibrating models of operational risk. Exercises are included in chapters involving numerical computations for students' practice and reinforcement of concepts.
Written by Harry Panjer, one of the foremost authorities in the world on risk modeling and its effects in business management, this is the first comprehensive book dedicated to the quantitative assessment of operational risk using the tools of probability, statistics, and actuarial science.
In addition to providing great detail of the many probabilistic and statistical methods used in operational risk, this book features:
* Ample exercises to further elucidate the concepts in the text
* Definitive coverage of distribution functions and related concepts
* Models for the size of losses
* Models for frequency of loss
* Aggregate loss modeling
* Extreme value modeling
* Dependency modeling using copulas
* Statistical methods in model selection and calibration
Assuming no previous expertise in either operational risk terminology or in mathematical statistics, the text is designed for beginning graduate-level courses on risk and operational management or enterprise risk management. This book is also useful as a reference for practitioners in both enterprise risk management and risk and operational management.
Customer Reviews:
Best quantitative OR book.......2007-02-13
This book covers all the quantitative topics around the loss distribution approach for OR. It follows an actuarial-driven approach to explain the models for frequency, severity and aggregation of loss distribution, and the relative statistical estimating and testing. But do not look for OR management topics in this book: it give its best in the actuarial measurement of operational risk.
Best overview of operational risk modeling techniques currently available.......2006-12-07
I train and consult bankers in credit and operational risk modeling for a living. I mention this because I think I have a decent feel for the pedagogy necessary for helping practitioners grasp the step-by-step application of these often highly theoretical concepts. Not all of us are rocket-scientists from birth and even though I have a quantitative PhD from Princeton, my often slow brain likes having things explained in simple terms. Panjer's book does this beautifully.
He has found the perfect balance between rigor and application--both in the exposition and scope of the book. He also includes examples of every concept that are easy to follow, replicate and extend. Moreover, Panjer takes you right to the edge of where advanced modeling of operational risk is at present. For example, he discusses EVT, copulas, infinite-mean models, kernel smoothing, robust methods, Bayesian methods, aggregation principles and compound processes as well as model selection--all of which characterize the current state of operational risk modeling and research. Indeed, beyond these points of technical modeling, most researchers (even mathematicians) are starting to agree that the returns are greatly diminishing and better qualitative/quantitative mixtures need to be developed (see Neslehova, et.al. Journal of Operational Risk, Spring, (2006)).
"Weak" spots in the book relate, for example, to how it fails to base itself firmly within the current operational risk literature. This is without loss of generality during this the infancy of operational risk modeling but I believe subsequent editions should address (at least to comment on) the growing number of papers popping up on websites and in trade journals. On the other hand, since I am not a statistician, I appreciated the author's references within that field as many of the topics are not part of the standard statistics canon. Finally, the book does not discuss operational risk management though, buying a book entitled "Operational Risk Modeling", I am not sure whether or why anyone would expect it to.
If this book were twice the price (such as for RiskBooks) I would still be happy with my purchase.
Book Description
This unique resource provides simulation techniques for financial risk managers ensuring you become well versed in many recent innovations, including Gibbs sampling, the use of heavy-tailed distributions in VaR calculations, construction of volatility smile, and state space modeling. The authors illustrate key concepts with examples and case studies you can reproduce using either S-PLUS® or Visual Basic® and provide exercises so you can apply new concepts and test your knowledge.
Simulation Techniques in Financial Risk Management is invaluable both as a resource for risk managers in the financial and actuarial industries and as a coursebook for upper-level undergraduate and graduate courses in simulation and risk management.
Customer Reviews:
Bypass this one.......2007-10-16
The book claims to be between Ross's "Simulation" and Glasserman's "Monte Carlo Methods in Financial Engineering" (both first-class books). Would that the same could be said of this sorry-looking text. I will be charitable and descibe it as watered-down Glasserman with some S-Plus code thrown in for good measure, and some material nicked from Ross. Wiley should be more careful about what it accepts for publication.
Book Description
The main objective of Credit Risk: Modeling, Valuation and Hedging is to present a comprehensive survey of the past developments in the area of credit risk research, as well as to put forth the most recent advancements in this field. An important aspect of this text is that it attempts to bridge the gap between the mathematical theory of credit risk and the financial practice, which serves as the motivation for the mathematical modeling studied in the book. Mathematical developments are presented in a thorough manner and cover the structural (value-of-the-firm) and the reduced (intensity-based) approaches to credit risk modeling, applied both to single and to multiple defaults. In particular, the book offers a detailed study of various arbitrage-free models of defaultable term structures with several rating grades.
Customer Reviews:
Could have been much better.......2002-09-03
In summary, this book is a disappointment. It presents a lot of material in an inaccessible way and doesn't provide solid explanations/proofs for a lot of material. It is also largley mathematical as opposed to the far superior 'Martingale methods in finance' by the same author, which takes the time to talk about applications to finance. As a credit derivatives quantitative analyst I was already familiar with the material in the text and that is the only reason why I understood it. It attempts to bridge the gap between theory and practice but in my opnion achieves neither.
Another math book.......2002-05-09
This is another typical book written by mathematician, and for mathematician. What can one learn from this book? Basically not much. If you don't really know much about credit risk, you still won't know after much after you read the book. If you are a quant, this book definitely won't help you much.
Who might need this book? If you are a mathemtician with research interest in probablity, AND you like the book "Martingale Methods in Financial Markets" by Musiela and Rotkowski, you might want to buy this book.
Book Description
Building upon the technical and organizational groundwork presented in the first edition, Risk Assessment and Decision Making in Business and Industry: A Practical Guide, Second Edition addresses the many aspects of risk/uncertainty (R/U) process implementation. This comprehensive volume covers four broad aspects of R/U: general concepts, implementation processes, technical aspects, and examples of application. Each section provides practical guidance, combining technical information with advice on how to implement R/U techniques and processes in real-world corporate environments. Following an examination of general principles involved in quantitatively assessing risks and their impact on value, the book describes the two main probabilistic measures of project value - Expected Value of Success (EVS) and the Expected Value for the Portfolio (EVP). The text clearly demonstrates how these metrics are used in individual-project and portfolio management. By presenting concepts in layman's terms and fully integrating advice related to technical and human characteristics of R/U-related corporate life, this book serves as a complete primer for professionals in any business environment. What's New in the Second Edition: · Provides guidance for implementation of R/U processes in modern corporations · Offers a crucial breakthrough by defining the terms "risk" and "uncertainty" in ways that can be applied in all aspects of science and business · Explores real-world impediments to process change and implementation · Addresses R/U from a corporate decision-maker's perspective, detailing how to employ R/U to set budgets, manage portfolios, value investments, and execute other critical tasks
Customer Reviews:
Great for Beginners and Intermediates!!.......2001-03-15
This book does an excellent job of laying out the basic of risk assessment, including all of the non-mathematical aspects, such as office politics and educating others in the use of risk models. It's easy to understand, even if you don't have a strong math background. I'm an English major, so I should know!
Unique book - very practical - no fluff.......1999-08-10
This is a great book for someone who is starting to practice Risk Assessment, either as a consultant, or internally. It covers the practical aspects of risk assessment studies which are usually overlooked, such as working and communicating with stakeholders. The 'softer' side of risk assessment theory is covered i.e. what does all this mean in plain english - how do you communicate the results etc.
The author has a good style, and the text does not contain the usual fluff and buzzwords often found in business-oriented books. Check it out!
Average customer rating:
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ASIN: 0136750184 |
Books:
- Beyond E-Learning: Approaches and Technologies to Enhance Organizational Knowledge, Learning, and Performance
- Building Storage Networks
- Buy Low, Sell High, Collect Early and Pay Late: The Manager's Guide to Financial Survival
- C.A.R.E. Packages for the Workplace: Dozens of Little Things You Can Do To Regenerate Spirit At Work
- Case Studies in Information Technology Ethics (2nd Edition)
- CCNP Video Mentor
- "China and the New World Order: How Entrepreneurship,Globalization, and Borderless Business Are Reshaping China and the World"
- Cisco ASA and PIX Firewall Handbook
- CMMI(R): Guidelines for Process Integration and Product Improvement (2nd Edition) (The SEI Series in Software Engineering)
- Commercial Banking: The Management of Risk
Books Index
Books Home
Recommended Books
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- Solution States: A Course in Solving Problems in Business with the Power of NLP
- Principles of Program Analysis
- The Frugal Gourmet Celebrates Christmas
- When I Am/Cuando estoy
- Toxic Contamination in Large Lakes/World Conference on Large Lakes Mackinac'86
- Simple Abundance: A Daybook of Comfort and Joy
- Performance Measurement and Management: A Strategic Approach to Management Accounting
- The Lion's Skin
Market Models: A Guide to Financial Data Analysis
Options, Futures and Other Derivatives (6th Edition)
Monte Carlo Methods in Financial Engineering (Stochastic Modelling and Applied Probability)
Time Series Analysis
Active Portfolio Management: A Quantitative Approach for Producing Superior Returns and Controlling Risk
