Advanced REIT Portfolio Optimization (eBook)

Innovative Tools for Risk Management
eBook Download: PDF
2022 | 1st ed. 2022
XIV, 258 Seiten
Springer International Publishing (Verlag)
978-3-031-15286-3 (ISBN)

Lese- und Medienproben

Advanced REIT Portfolio Optimization - W. Brent Lindquist, Svetlozar T. Rachev, Yuan Hu, Abootaleb Shirvani
Systemvoraussetzungen
50,28 inkl. MwSt
  • Download sofort lieferbar
  • Zahlungsarten anzeigen

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.



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; 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.

Erscheint lt. Verlag 9.11.2022
Reihe/Serie Dynamic Modeling and Econometrics in Economics and Finance
Dynamic Modeling and Econometrics in Economics and Finance
Zusatzinfo XIV, 258 p. 1 illus.
Sprache englisch
Themenwelt Wirtschaft Betriebswirtschaft / Management
Wirtschaft Volkswirtschaftslehre
Schlagworte Derivative pricing for hedging investment risk • Innovative investment tools • Investment risk assessment • Modern Portfolio Theory • Option pricing • Portfolio Investment • portfolio optimization • Quantitative Finance • Real Estate Investment Market • Real Estate Investment Trusts • real estate stocks • REIT investment • Risk budgeting
ISBN-10 3-031-15286-7 / 3031152867
ISBN-13 978-3-031-15286-3 / 9783031152863
Haben Sie eine Frage zum Produkt?
PDFPDF (Wasserzeichen)
Größe: 15,2 MB

DRM: Digitales Wasserzeichen
Dieses eBook enthält ein digitales Wasser­zeichen und ist damit für Sie persona­lisiert. Bei einer missbräuch­lichen Weiter­gabe des eBooks an Dritte ist eine Rück­ver­folgung an die Quelle möglich.

Dateiformat: PDF (Portable Document Format)
Mit einem festen Seiten­layout eignet sich die PDF besonders für Fach­bücher mit Spalten, Tabellen und Abbild­ungen. Eine PDF kann auf fast allen Geräten ange­zeigt werden, ist aber für kleine Displays (Smart­phone, eReader) nur einge­schränkt geeignet.

Systemvoraussetzungen:
PC/Mac: Mit einem PC oder Mac können Sie dieses eBook lesen. Sie benötigen dafür einen PDF-Viewer - z.B. den Adobe Reader oder Adobe Digital Editions.
eReader: Dieses eBook kann mit (fast) allen eBook-Readern gelesen werden. Mit dem amazon-Kindle ist es aber nicht kompatibel.
Smartphone/Tablet: Egal ob Apple oder Android, dieses eBook können Sie lesen. Sie benötigen dafür einen PDF-Viewer - z.B. die kostenlose Adobe Digital Editions-App.

Buying eBooks from abroad
For tax law reasons we can sell eBooks just within Germany and Switzerland. Regrettably we cannot fulfill eBook-orders from other countries.

Mehr entdecken
aus dem Bereich