9780470052204-0470052201-Quantitative Investment Analysis

Quantitative Investment Analysis

ISBN-13: 9780470052204
ISBN-10: 0470052201
Edition: 2
Author: Jerald E. Pinto, Dennis W. McLeavey, Richard A. DeFusco, David E. Runkle
Publication date: 2007
Publisher: Wiley
Format: Hardcover 600 pages
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Book details

ISBN-13: 9780470052204
ISBN-10: 0470052201
Edition: 2
Author: Jerald E. Pinto, Dennis W. McLeavey, Richard A. DeFusco, David E. Runkle
Publication date: 2007
Publisher: Wiley
Format: Hardcover 600 pages

Summary

Quantitative Investment Analysis (ISBN-13: 9780470052204 and ISBN-10: 0470052201), written by authors Jerald E. Pinto, Dennis W. McLeavey, Richard A. DeFusco, David E. Runkle, was published by Wiley in 2007. With an overall rating of 4.5 stars, it's a notable title among other Economics (Finance, Investing) books. You can easily purchase or rent Quantitative Investment Analysis (Hardcover) from BooksRun, along with many other new and used Economics books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.51.

Description

In the Second Edition of Quantitative Investment Analysis, financial experts Richard DeFusco, Dennis McLeavey, Jerald Pinto, and David Runkle outline the tools and techniques needed to understand and apply quantitative methods to today's investment process.

Now, in Quantitative Investment Analysis Workbook, Second Edition, they offer you a wealth of practical information and exercises that will further enhance your understanding of this discipline. This essential study guide--which parallels the main book chapter by chapter--contains challenging problems and a complete set of solutions as well as concise learning outcome statements and summary overviews.

If you're looking to successfully navigate today's dynamic investment environment, the lessons found within these pages can show you how. Topics reviewed include:

  • The time value of money
  • Discounted cash flow
  • Probability distributions
  • Sampling and estimation
  • Hypothesis testing
  • Multiple regression
  • Time-series analysis
  • And much more
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