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Using SAS in financial research / Ekkehart Boehmer, John Paul Broussard, Juha-Pekka Kallunki.

By: Contributor(s): Material type: TextTextPublisher: Cary, N.C. : SAS Publishing, [2002]Copyright date: ©2012Description: viii, 166 pages: illustrations ; 28 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 1590470397
  • 9781590470398
Subject(s): DDC classification:
  • 332.028553042 21
LOC classification:
  • HG104 .B64 2002
Contents:
Random walking or walking randomly : Using SAS to conduct variance ratio testing of asset prices -- Analyzing winners and losers : Using SAS to test the overreaction hypothesis -- Cross-sectional approach to the empirical test of the capital asset pricing model -- Event studies -- Effective use of SAS macros : An application to even studies -- Association types of studies : Investigating the price-earnings relationship -- Predicting bankruptcy from financial distress characterization models -- Using accounting information to forecast market performance.
Summary: 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, even studies, value versus growth, earnings response coefficients, and microstructure analysis. Readers will find the merging of theoretical and practical concepts unique and highly informative. The format of this book enables users to go directly to the research told and techniques required by the task at hand. In addition, a line-by-line discussion of all SAS code is provided, enabling users to interpret all variables and syntax easily. The procedures supplied that automate several frequently required analytical tasks are also a welcome feature of this book.
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Holdings
Item type Current library Call number Copy number Status Date due Barcode
Book City Campus City Campus Main Collection 332.028553042 BOE (Browse shelf(Opens below)) 1 Available A547670B

Includes bibliographical references and index.

Random walking or walking randomly : Using SAS to conduct variance ratio testing of asset prices -- Analyzing winners and losers : Using SAS to test the overreaction hypothesis -- Cross-sectional approach to the empirical test of the capital asset pricing model -- Event studies -- Effective use of SAS macros : An application to even studies -- Association types of studies : Investigating the price-earnings relationship -- Predicting bankruptcy from financial distress characterization models -- Using accounting information to forecast market performance.

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, even studies, value versus growth, earnings response coefficients, and microstructure analysis. Readers will find the merging of theoretical and practical concepts unique and highly informative. The format of this book enables users to go directly to the research told and techniques required by the task at hand. In addition, a line-by-line discussion of all SAS code is provided, enabling users to interpret all variables and syntax easily. The procedures supplied that automate several frequently required analytical tasks are also a welcome feature of this book.

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