Advanced REIT Portfolio Optimization - Lindquist, W. Brent

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Résumé :
This book provides an investor-friendly presentation of the premises and applications of the quantitative finance models governing investment in one asset class of publicly traded stocks, specifically real estate investment trusts (REITs). The models provide highly advanced analytics for REIT investment, including: portfolio optimization using both historic and predictive return estimation; model backtesting; a complete spectrum of risk assessment and management tools with an emphasis on early warning systems, risk budgeting, estimating tail risk, and factor analysis; derivative valuation; and incorporating ESG ratings into REIT investment. These quantitative finance models are presented in a unified framework consistent with dynamic asset pricing (rational finance). Given its scope and practical orientation, this book will appeal to investors interested in portfolio optimization and innovative tools for investment risk assessment.

Biographie:
Prof. W. Brent Lindquist is a computational mathematician at Texas Tech University (USA). He has developed numerical methods for portfolio optimization, flow in porous media, 3D image analysis, Riemann problems, hierarchy formation in social groups, and quantum electrodynamics. He was a co-founder of a petroleum software company and has commercially licensed his image analysis code. Yuan Hu received her Ph.D. from Texas Tech University (USA) in 2022. Her current research considers approaches to discrete option pricing...

Sommaire:
Chapter 1. The Real Estate Investment Market: The Current State and Why Advances Are Needed.- Chapter 2. The Data.- Chapter 3. Modern Portfolio Theory.- Chapter 4. Historical Portfolio Optimization - Domestic REITs.- Chapter 5. Diversification with International REITs.- Chapter 6. Black-Litterman Optimization Results.- Chapter 7. Dynamic Portfolio Optimization: Beyond MPT.- Chapter 8. Backtesting.- Chapter 9. Diversification with Real Estate Stocks.- Chapter 10. Risk Information and Management.- Chapter 11. Optimization with Performance-Attribution Constraints.- Chapter 12. Option Pricing.- Chapter 13. Inclusion of ESG Ratings in Optimization.- Chapter 14. Inclusion of ESG Ratings in Option Pricing.