Managerial-finance

Given the glowing rating this book has received from most reviewers, I have been somewhat disappointed with this book. My main thought is this: This is a good book for non-accountants to keep as a *reference text* since the authors' do a good job of explaining technical financial accounting matters in a straightforward way. However, I do not think this is a good book to actually *learn financial statement analysis* from.

The book tends to focus on technical accounting details while ignoring other important aspects of analysis (e.g., econometric methods, the relationship between the decision model and the nature of the analysis, etc.). It is difficult to tell what the authors see as the most important, central concepts and methods in financial statement analysis. One gets the idea that if you were to ask the authors "What are the really important concepts and methods in this book?", they would answer "Oh, it's *all* good!"

In my experience as an analyst, technical accounting details were rarely important--even when using historical financial statement data to develop financial simulation models for firms. There's a simple explanation for why this is so: An individual firm's financial statements might be "garbage," but the only reasonable way of telling this is by making inferences from the relationship between exogenous economic factors, competitors' financial results (on average), and the individual firm's results. It's about the only reasonable way to extract signals (likely economic "truth") from noisy financial statement data.

I definitely agree with previous reviewers who stated the book is poorly written: it is often both wordy and vague. Consider the (lack of) discussion on p. 332 of the important topic, R&D expenditures:

"Companies invest in ... (R&D) because they expect ... profitable future products. However, absent a resultant commercial product, these expenditures may have not value to the firm. Further, the value of any product may be unrelated to the amount spent on R&D. Due to valuation uncertainties, R&D is generally unacceptable to creditors as security for loans."

I think they mean this: Firms make investments since they expect economic returns on them, but return on R&D expenditures is usually very unpredictable. (Whew. I'm glad they told me! Now I won't feel stupid when talking to other analysts.) The authors then proceed immediately to a summary of accounting standards on R&D expenditures. (This is financial statement analysis?)

It's not clear either that the purpose of presenting a cohesive view of financial statement analysis is served by the sometimes excessive references to empirical research by accounting academics. A cynical reader might suspect this is done to ingratiate the book with accounting professors who will make it the required text for their course!

In the end, I think the book fails to explain fundamental concepts and methods of analysis by which specific information is derived from financial statements for input to specific decision models. What's the antidote? Get Fridson (Wiley) and Bergevin (Prentice-Hall): Nice straightforward books that really explain how to do financial statement analysis.

After reading the reviews on this book, I feel that I must comment on the book's high quality.

In order to fully appreciate this book, an understanding must exist as to where the material fits in the financial analysis process. Clearly this book is not meant to explicitly teach readers how to build financial models; other books are available for that purpose. This book is designed to teach readers how to thoroughly read, understand, and more importantly, become an astute critic of the language of financial statements, GAAP.

I disagree that technical accounting details are not very important in analysis engagements. Rather the opposite holds true in a majority of cases: One must thoroughly understand technical accounting and the implications that it has on economic reality in order to build quality financial models. Otherwise, "junk in/junk out" models will result.

Given the highly publicized debacles that have recently occurred in the financial world, including Enron, the importance of distinguishing technical accounting from economic reality has become obvious. This book does effectively explain and build off the foundations of GAAP; however, this book is primarily focused on helping an analyst analyze and question the quality of financial statements versus how to simply prepare them. This is the big difference between this book and technical accounting textbooks.

Of course, building financial models for decisions is the end objective of any analyst. However, this book is a must read in building quality financial models and projections. Again this book is not a financial modeling textbook, nor a technical accounting manual. Rather, it is a critical bridge between technical accounting material and decision modeling material. I recommend taking the time to read this excellent book and walk across the bridge before moving on to modeling.

This book is great!!! I have finished reading the assigned chapters for the CFA test and I already feel way more confident than I did last year after using Stalla study notes. Buy the book because it helps you way more in terms of examples and explanations. Trust me I know.
Note: Example are clear and concise!!!

What do you know about DEA? Are you an expert in Operational Research, Linear Programming, Algebra and Statistics and interested in DEA's mathematics? Or are you just willing to learn enough to apply DEA model in a simple and interesting case you found? Well, I'm an industrial engineering student without much time to get deep in DEA studies. Although I have some knowledge in statistics and OR, I just wanted to apply DEA model in a fast food chain. In this case, I do not recommend this book. I quit reading it as it was hard to understand and full of non-sense equations. On the other hand, it might be useful if you are doing a deep research about DEA, its theory etc.