Professional Investment Portfolio Management
Boosting Performance with Machine-Made Portfolios and Stock Market Evidence
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35 498 Ft
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Product details:
- Edition number 1st ed. 2023
- Publisher Springer Nature Switzerland
- Date of Publication 4 February 2024
- Number of Volumes 1 pieces, Book
- ISBN 9783031481680
- Binding Hardback
- No. of pages255 pages
- Size 235x155 mm
- Weight 600 g
- Language English
- Illustrations XXX, 255 p. 74 illus., 51 illus. in color. Illustrations, black & white 534
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Long description:
Professional investment portfolio management is increasingly utilizing sophisticated statistical and computer techniques to better control risks and improve performance. This book provides new quantitative tools and technology for securities professionals to help boost the performance of their investment portfolios offered to clients. Unlike other books in this area, the authors utilize revolutionary asset pricing methods and models to analyze data for U.S. stocks and show how to apply them to the problem of creating highly diversified portfolios that are efficient in terms of returns per unit risk.
Table of Contents:
Part I: Introduction.- Chapter 1: Portfolio Theory and Practice.- Part II: Previous Asset Pricing Models.- Chapter 2: General Equilibrium Asset Pricing Models.- Chapter 3: Multifactor Asset Pricing Models.- Part III: The ZCAPM.- Chapter 4: A New Asset Pricing Model: The ZCAPM.- Chapter 5: The Empirical ZCAPM.- Part IV: Portfolio Performance.- Chapter 6: Portfolio Performance Measures.- Part V: Building Stock Portfolios with the ZCAPM.- Chapter 7: Building the Global Minimum Variance Portfolio G.- Chapter 8: Net Long Portfolio Performance Analyses.- Chapter 9: Net Long Portfolio Risk Analyses.- Chapter 10: Long Only Efficient Portfolios.- Chapter 11: The Beta-Zeta Risk Architecture of the Mean-Variance Parabola.- Chapter 12: Mutual fund portfolios.- Part VI: Conclusion.- Chapter 13: The Future of Investment Practice, Artificial Intelligence, and Machine Learning.
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