EconPapers    
Economics at your fingertips  
 

Modern Portfolio Theory

W. Brent Lindquist, Svetlozar T. Rachev, Yuan Hu and Abootaleb Shirvani
Additional contact information
W. Brent Lindquist: Texas Tech University
Svetlozar T. Rachev: Texas Tech University
Yuan Hu: University of California San Diego
Abootaleb Shirvani: Kean University

Chapter Chapter 3 in Advanced REIT Portfolio Optimization, 2022, pp 29-48 from Springer

Abstract: Abstract The basic elements of modern portfolio theory are covered in this Chapter. Starting from the basics of price return time series, the authors introduce Markowitz’s mean variance optimization and the central concept of the efficient frontier. Extensions to other risk measure optimization methods within the portfolio theory framework are covered, including: tangent portfolio optimization which exploits the relationship between the efficient frontier and the capital market line; minimization of the conditional value-at-risk, a tail-risk measure replacing the variance; and the Black–Litterman model, designed to address issues appearing in mean variance optimization. The classical implementation of these optimization techniques using moving windows of historical asset return data is developed.

Date: 2022
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:dymchp:978-3-031-15286-3_3

Ordering information: This item can be ordered from
http://www.springer.com/9783031152863

DOI: 10.1007/978-3-031-15286-3_3

Access Statistics for this chapter

More chapters in Dynamic Modeling and Econometrics in Economics and Finance from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-04-01
Handle: RePEc:spr:dymchp:978-3-031-15286-3_3