Professional Investment Portfolio Management

James W. Kolari is the JP Morgan Chase Professor of Finance and Academic Director of the Global Corporate Banking Program in the Department of Finance at Texas A&M University. With more than 100 articles published in refereed journals, numerous other papers and monographs, 20 co-authored books, and more than 200 competitive papers presented at academic conferences, he ranks in the top 1-2 percent of finance scholars in the United States.Wei Liu holds PhDs in both physics and finance from Texas A&M University. He has worked as a bank analyst for USAA Bank, a former owner and investment manager of a securities firm,  and now teaches finance at Texas A&M University. His research has been published in academic journals and textbooks.Seppo Pynnönen is a Professor of Statistics at the University of Vaasa, Finland and previously the Chairperson of the Department of Mathematics and Statistics. He has studied financial markets and taught various courses on statistical methodology. With numerous published papers in international finance and statistics journals, he is also the co-author of a recent investment valuation and asset pricing textbook.

• 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.