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Researchers, graduate students, and practitioners in the financial market now have the first reference-style handbook detailing the mechanics of statistical testing on financial and accounting data. This one-of-a-kind book illustrates how to use SAS software to conduct basic empirical analyses of stock market and financial statement data. It covers various research topics, including investigating the predictability of stock returns, estimating the risk of common stock, and analyzing the impact of earnings and other financial statement information. The use of the SAS language to investigate these issues is demonstrated with numerous real-world examples employing traditional to state-of-the-art analytical estimation techniques. Main topics covered are variance ratio testing, capital asset pricing model, event studies, value versus growth, earnings response coefficients, and microstructure analysis. Readers will find the merging of theoretical and practical concepts unique and informative.
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"This book is for knowledgeable researchers, graduate students and financial practitioners. It was refreshing to find that the authors provide a summary of each topic that explains in simple to understand language both the output from the various SAS PROCs used and the statistical interpretation with respect to the hypothesis being tested. In addition, the actual SAS code is listed, highlighted and illustrated in a way that makes it easy for people to start using SAS quickly and easily to do their financial and statistical analysis. As a working mathematician and statistician who has no formal education and limited experience in economics or the stock market, I found the book enlightening about some of the inner philosophies of economics and stock market trading practices. And for those people who are involved in such areas and who have to perform financial research, I highly recommend this book as a valuable asset to their financial tools. I especially recommend it to those people who are in the early stages of their careers, during which statistical analysis using computer software is often required." -- Charles Patridge "The Hartford"

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