Advanced REIT Portfolio Optimization : Innovative Tools for Risk Management
Language: English
Published by Springer, 2022
- Hardcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
£ 63.70
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Add to basketItem description from seller
Druck auf Anfrage Neuware - Printed after ordering - 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.
Seller Inventory # 9783031152856
- Title
- Advanced REIT Portfolio Optimization : Innovative Tools for Risk Management
- Author
- Abootaleb Shirvani
- Publisher
- Springer
- Publication year
- 2022
- Condition
- Neu
- Binding
- Buch
- Language
- English
- ISBN 10
- 3031152859
- ISBN 13
- 9783031152856
- Item weight
- 576 grams
- Dimensions
- 241x160x21 mm
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.
"Synopsis" may belong to another edition of this title.
About the Author
Yuan Hu received her Ph.D. from Texas Tech University (USA) in 2022. Her current research considers approaches to discrete option pricing; risk management and option valuation of crypto assets; and portfolio optimization constrained by performance attribution. She is currently the Stefan E. Warschawski Visiting Assistant Professor in the Department of Mathematics at the University of California San Diego (USA).
Dr. Abootaleb Shirvani received his Ph.D. from Texas Tech University (USA) in 2021. His general research interests include financial mathematics, statistics, and actuarial mathematics. He is currently an assistant professor in Statistics and Actuarial Science in the Department of Mathematics at Kean University (USA).
Prof. Svetlozar (Zari) Rachev is a Professor at the Department of Mathematics and Statistics at Texas Tech University (USA) and one of the world’s foremost authorities in the application of heavy-tailed distributions in finance. He was a co-founder and President of Bravo Risk Management Group, originator of the Cognity methodology. Bravo was acquired by FinAnalytica, where Zari served as Chief Scientist.
"About the title" may belong to another edition of this title.
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