Standard & Poor's Fundamentals of Corporate Credit Analysis Review

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(More customer reviews)I had the pleasure of working with one of the authors 15 years ago. But don't let that sway you. I truly appreciate the scope and effort put into this book. We will use it as an outline for how our analysts should approach analyzing a credit. Chapter 3 alone is worth the price of admission as the authors list the elusive "qualitative" factors that go into a credit rating, beyond what the ratios tell you it should be. While the book barely scratches the surface of certain analytical methods (the Merton Model got 1/2 a page), and it is written more for the layman or student, I still learned many things. And I've been in the business 20+ years. The prior reviewer, and many others will say they wished they wrote this book. I will too. I even briefly started my own version recently. But I first turned to S&P's ratings criteria as an outline. As such, the right people wrote this book. The authors fully used the vast resources and data mining of S&P. This certainly feels like a team effort. The telecom analyst wrote a piece on the rapid decline of telecom credits in 2000-2002, and other professionals added real life examples. The book organizes itself in the top down approach to analysis. It starts with sovereign risk, then moves to industry, then company business/competitive risk. It then highlights the ratios to look for, and also gives data on seniority and recovery values for specific levels of debt. It then uses these tools to analyze a fictional company. It ends with case studies that cover M&A, sovereign risk and other topical reviews that act as a real life summary to what you just learned. Highly recommended. Well done.

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An authoritative, in-depth guide to all aspects of credit analysis from the experts at Standard & Poor's

Credit analysis--gauging an issuer's ability to repay interest and principal on a bond issue--plays an essential role in determining how bond issues are rated and priced. Fundamentals of Corporate Credit Analysis provides both analysts and investors with the practical, up-to-date information they need, backed by Standard & Poor's research, data, and experience, to properly assess the credit risk of virtually any entity.

Whether used as a handy all-in-one guide or as a comprehensive training tool, it will give anyone the knowledge and tools needed to dig beneath standard ratings and determine an organization's true creditworthiness.

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Advanced modelling in finance using Excel and VBA Review

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(More customer reviews)I like the style of this book. Don't let the small number of pages fool you. The authors didn't get overly wordy explaining the basics of the models (they assume the reader is already a proficient Excel user), and focus instead on explaining the key Excel functions and VBA codes in order to allow the readers to get their own model up and running in a short time. Like the other reviewer said, the authors should be congratulated for such a superb effort.
Many subjects are materials not normally covered in a typical MBA curriculum (although they would in a MS program) Examples: in Chapter 13, Non-normal Distributions and Implied Volatility, the authors showed the way to model a Black & Scholes Equity Option using the more realistic non-normal distribution assumptions acounting for skewness and kurtosis (non-symetry and fat tails). In the Appendix, author introduced the ARIMA models in Excel (modeled typically with statistical or time-series software packages, such as SAS or SPSS), splines curve fitting and lastly estimation of eigenvalues and eigenvectors (for estimation of principal components analysis). You will find the Excel/VBA codes bundled in the CD handy for those who wish to develop more advanced models.
This book is a godsend for busy practitioners who want to master quickly the art and science of building numerical techniques and coding models with Excel. Feel free to email me if you need to know any details from the book.
P.S. book divided into four components
Part ONE: Advanded Modelling in Excel (teaches the advanced Excel functions and procedures, VBA macros and user-defined functions)
Part TWO: Equities
Part THREE: Options on Equities
Part FOUR: Options on Bonds
Appendix: Other VBA functions

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This new and unique book demonstrates that Excel and VBA can play an important role in the explanation and implementation of numerical methods across finance. Advanced Modelling in Finance provides a comprehensive look at equities, options on equities and options on bonds from the early 1950s to the late 1990s.
The book adopts a step-by-step approach to understanding the more sophisticated aspects of Excel macros and VBA programming, showing how these programming techniques can be used to model and manipulate financial data, as applied to equities, bonds and options. The book is essential for financial practitioners who need to develop their financial modelling skill sets as there is an increase in the need to analyse and develop ever more complex 'what if' scenarios.
Specifically applies Excel and VBA to the financial markets
Packaged with a CD containing the software from the examples throughout the book

Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file.

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Best Practices for Equity Research Analysts: Essentials for Buy-Side and Sell-Side Analysts Review

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(More customer reviews)My friend Tom Brakke, liked this book and said I would too. He was right, and soon afterward, I heard the author speak at the Baltimore CFA Society. Hearing James Valentine speak is an advantage here. He summarized what is most important, which if you are reading the book, it would be chapter 20 (out of 27). It is his FaVeS framework: Forecast, Valuation, and Sentiment, in that order of importance. Remember that as a key to the book if you read it; it tells you what to focus on as an analyst.
Another key, since the book is long, is to look at the shaded summaries which are usually at the back of each chapter. If stretched for time, read those first, and then read the chapter if you didn't get it.
This book aims to focus analysts on information that matters. Aim for information that makes a difference, and that few others have. Create an information web that maximizes the value of your time, and creates value for your research.
This book covers both the buy-side and the sell-side, telling each how to best use the other side. As a former buy-side analyst, to me it means fewer analyses, and better analyses. Aside from that, it is a game: buy-side: identify the better sell-side analysts and listen to them. Sell-side: identify clients that will generate commissions and market their best insights to them.
Regardless, analysts must identify the few factors that account for 80% of the performance in a given industry, and focus on those intensely. It helps to get into the industry organizations, which can help drive insight into the industry as a whole, and provide a backdrop for questions to ask when talking with executives in the industry.
Learning this will give an analyst a leg up on other analysts. Analysts should also understand the basic accounting structures of their industry so that they can identify companies that are not playing fair -- over-reporting income. I would add don't get negative too quickly. Frauds can develop a momentum of their own. Wait until the fraud gets large relative to the size of the industry before issuing a sell call -- wait for price momentum to go to zero. (Note: for investigative journalists, this does not apply. Jump on early, so that you can say that you warned everyone.)
Basic forensic accounting skills help, as do modeling skills, and basic statistical skills. I was surprised to learn a bunch of Excel shortcuts that I haven't seen elsewhere, and I have used Excel for nineteen years at a high level. The summary of accounting deviations is cogent, as well as pointing readers to Mulford and Schilit.
One idea that I heartily agree with: set up your spreadsheets to differentiate data and formulas. Cells with data series should only contain data. Formulas should have no numbers in them, unless they are trivial. This makes analysis a lot easier and cleaner in the long run.
The book also brings out the need to consider multiple scenarios, which help an analyst to flesh out his analysis. Being willing to consider what can go wrong, or right, richens an analysis. Also, the book warns against common pathologies that overcome analysts, notably -- Confirmation bias, overconfidence, Self-Attribution-bias, Optimism, Recency, Momentum, Heuristics, Familiarity, Snakebite (won't go back to one that hurt you), Falling in love, anxiety, over-reaction, loss-aversion, etc. I have experienced a few of those myself, and would have benefited from thinking these through before becoming an analyst.
Quibbles
I would warn any analyst trying to use simple or multiple regression that they are playing with fire, unless they understand the weaknesses of the data, and the limitations of the general linear model. In twelve-plus years working on Wall Street, I never saw regression used right once.
The author seems to favor DCF over multiples. Truth, neither works well, and one must live with the weaknesses of any approach. DCF embeds a lot of assumptions that are known, though some may be wrong -- multiples embed unknown assumptions.
The author does not like price-to-sales. For industrials and utilities I would say look at a chart of price versus price-to-sales. In most cases, they track, because sales don't vary that much in the short run. If you know the high and low P/S ratios for companies in an industry (P/B for financials) you have valuable information. It gives you boundaries to look at in buy and sell decisions.
I would also warn analysts against using Damodaran and those like him. I don't think his models are wrong so much as impractical. I would rather use a simple model that catches 80-90% of the action, versus one that catches 100% of the action, bet cannot practically be calculated.
Who would benefit from this book:
All equity analysts would benefit from this book. It is detailed, and yet practical. Some of our competitors will benefit from it, and if you don't read it, you will wonder why.

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Handbook of Financial Analysis, Forecasting, and Modeling Review

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(More customer reviews)This book is useful for looking up not just formulas but valuation methodologies in a hurry. However most of the techniques, though illustrated well, do not go very deep. This book is probably good for beginners in finance. Experienced readers may be served better by other publications. All in all, I found this text useful as a quick and easy "boiled down" reference guide for models, formulas and valuation techniques.

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Ready-to-use forecasting and modeling tools to read the future under any given set of assumptions. Manipulate variables such as revenues, expenses, cash flow and earnings while improving the quality of decision-making and reduces risk of error.

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Financial Modeling Review

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(More customer reviews)Simon Benninga's 3rd Edition of Financial Modelling with Excel is the single most useful book for finance students and professionals ever published and continues to offer an outstanding reference and textbook for students and practitioners of applied finance.
For further information, please use the "Look Inside" feature and examine the Table of Contents carefully, because I will emphasize selected portions.
It is difficult to overstate how useful and practical and helpful this work is for a wide audience and Financial Modelling is the single finance book I recommend for everyone after they have taken (or read themselves) Introductory Finance.
For those looking for "one-stop-shopping" for models that resemble those of professional financial analysts then there is no better value than Benninga's FM3.
Benninga's FM3 is a coal-face work for those who must make financial decisions using models. There are further specialist texts in topics covered here (credit modelling, portfolio construction, option pricing), but the models in FM3 are the first advanced models applied to loans, bonds, options, and equity portfolios. Master these and then specialized texts are easier to digest.
"Cookbook" metaphors are too strong and do not do this work justice, for Financial Modelling 3rd (FM3) is not a mere collection of recipes but rather topical introduction, explanation, and then direct technique.
If we can make a comparison with a "cookbook" then FM3 falls somewhere between "The Joy of Cooking" and "Mastering the Art of French Cooking." "Joy" combines chapters on technique, ingredients, and tools with dense pages of endless recipes, whereas "Mastering" emphasises technique and a few well-selected recipes.
The welcome new chapters cover bank valuation, the Black-Litterman approach to portfolio optimization, and Monte Carlo methods and applications to option pricing, and the previous 2nd edition's small chapter on using array functions and formulas has been expanded. The chapter on data downloads from YAHOO is also welcome, especially for those on a budget.
There is a single significant flaw in the work, which is excusable and redeemable. Far too often the discounting in the chapters is done over a flat interest rate curve. While the term structure of interest rates is covered, and historical term structures and parallel shifts and steepening and flattening is covered in isolation in a thorough chapter and with wonderful data files, the necessity and explicit connection of discounting from an appropriate yield curve is left implied and only mentioned in a few exercises. I would have preferred a "round up" chapter where each of the subjects treated (bond discounting, portfolio expected returns, options, etc.) under a yield curve with advanced models. Sure BLOOMBERG and REUTERS have these sort of things (often incorrectly) programmed, but students need to learn explicitly about them and do the exercise themselves to comprehend the importance of curve discounting.
The CD attached in the back of the book is alone worth the price, with over two score of models that are practical and adaptable for students and professionals alike. The files are stored and separated according to chapters and subject matter. Each file has logical progression of the concepts advanced in the book, and each separate sheet either stands alone or appropriately links to data and models on other sheets, so editing for your own purposes is a breeze.
For those who want to train themselves in Finance (not "personal finance") then I suggest reading Copeland, Weston, & Shastri's Financial Theory and Corporate Policy (4th Edition) and Brealey, Myers, and Marcus's "Corporate Finance" and "Investments" followed by working through FM3. Such a course would give any self-disciplined person the equivalent of a Masters of Science in Finance.
Full disclosure: I am thanked in the "Acknowledgements" for providing a few helpful comments on the second edition.

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Too often, finance courses stop short of making a connection between textbook finance and the problems of real-world business. Financial Modeling bridges this gap between theory and practice by providing a nuts-and-bolts guide to solving common financial models with spreadsheets. Simon Benninga takes the reader step by step through each model, showing how it can be solved using Microsoft Excel. The long-awaited third edition of this standard text maintains the "cookbook" features and Excel dependence that have made the first and second editions so popular. It also offers significant new material, with new chapters covering such topics as bank valuation, the Black-Litterman approach to portfolio optimization, Monte Carlo methods and their applications to option pricing, and using array functions and formulas. Other chapters, including those on basic financial calculations, portfolio models, calculating the variance-covariance matrix, and generating random numbers, have been revised, with many offering substantially new and improved material.Other areas covered include financial statement modeling, leasing, standard portfolio problems, value at risk (VaR), real options, duration and immunization, and term structure modeling. Technical chapters treat such topics as data tables, matrices, the Gauss-Seidel method, and tips for using Excel. The last section of the text covers the Visual Basic for Applications (VBA) techniques needed for the book. The accompanying CD contains Excel worksheets and solutions to end-of-chapter exercises. Praise for the previous editions: "Benninga has a clear writing style and uses numerous illustrations, which make this book one of the best texts on using Excel for finance that I've seen." --Ed McCarthy, Ticker Magazine "The author describes this as a 'cookbook' and that is a good analogy...Its breadth is extensive, covering simple present valuing and cost of capital ...to the likes of real options and early exercise of American-style options...A worthwhile acquisition."--Paul Dentskevitch, Risk Magazine "Financial Modeling is highly-recommended to readers who are interested in an introduction to basic, traditional approaches to financial modeling and analysis, as well as to those who want to learn more about applying spreadsheet software to financial analysis." --Edward Weiss, Journal of Computational Intelligence in Finance "Financial Modeling belongs on the desk of every finance professional. Its no-nonsense, hands-on approach makes it an indispensable tool." --Hal R. Varian, Dean, School of Information Management and Systems, University of California, Berkeley "This is applied finance theory for the professional at its best. As a student, I and countless others learnt the intricacies of Lotus and financial theory from Professor Benninga's first book--Numerical Techniques in Finance. Now, as a professional, I do not have to 're-invent the wheel' in Excel. An invaluable guide. A must for all financial analysts." --Vikas Nath, Global Strategist, Emerging Equity Markets, Union Bank of Switzerland, London

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