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Portfolio and Investment Analysis with SAS: Financial Modeling Techniques for

Description: Choose statistically significant stock selection models using SAS® Portfolio and Investment Analysis with SAS®: Financial Modeling Techniques for Optimization is an introduction to using SAS to choose statistically significant stock selection models, create mean-variance efficient portfolios, and aggressively invest to maximize the geometric mean. Based on the pioneering portfolio selection techniques of Harry Markowitz and others, this book shows that maximizing the geometric mean maximizes the utility of final wealth. The authors draw on decades of experience as teachers and practitioners of financial modeling to bridge the gap between theory and application. Using real-world data, the book illustrates the concept of risk-return analysis and explains why intelligent investors prefer stocks over bonds. The authors first explain how to build expected return models based on expected earnings data, valuation ratios, and past stock price performance using PROC ROBUSTREG. They then show how to construct and manage portfolios by combining the expected return and risk models. Finally, readers learn how to perform hypothesis testing using Bayesian methods to add confidence when data mining from large financial databases.

Price: 75.83 GBP

Location: Gloucester

End Time: 2025-01-14T20:21:29.000Z

Shipping Cost: 39.83 GBP

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Portfolio and Investment Analysis with SAS: Financial Modeling Techniques forPortfolio and Investment Analysis with SAS: Financial Modeling Techniques for

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Return postage will be paid by: Buyer

Returns Accepted: Returns Accepted

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EAN: 9781635266924

UPC: 9781635266924

ISBN: 9781635266924

MPN: N/A

Book Title: Portfolio and Investment Analysis with SAS: Financ

Item Length: 27.9 cm

Publisher: SAS Institute

Item Height: 279 mm

Subject: Computer Science

Publication Year: 2019

Number of Pages: 230 Pages

Publication Name: Portfolio and Investment Analysis with Sas: Financial Modeling Techniques for Optimization

Language: English

Type: Textbook

Item Weight: 526 g

Author: John B Guerard, Ziwei Wang, Ganlin Xu

Item Width: 210 mm

Format: Paperback

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