Tail Parameters of Stable Distributions Using One Million Observations of Real Estate Returns from Five Continents

Posted: 28 Nov 2015

See all articles by Michael Stein

Michael Stein

University of Duisburg-Essen

Daniel Piazolo

THM Technische Hochschule Mittelhessen

Stoyan V. Stoyanov

Charles Schwab

Multiple version iconThere are 3 versions of this paper

Date Written: November 27, 2015

Abstract

This study focuses on global real estate return distributions. For our analysis, we employ the class of stable distributions that has become prominent in the real estate literature. We add to the literature by undertaking a global-scale analysis for the first time.

By using data since the early 1990s, we show that there is considerable variation in the tail weights of return distributions, both between countries as well as among sectors within the countries. It is important to note that the tail parameters vary over time as well.

Our results strengthen the notion of non- constant tail parameters in stable distributions that followed earlier findings of constant tail parameters. In addition, our results provide evidence that it is merely the time horizon that causes variation in parameters, than purely methodological differences.

Keywords: Real Estate Return Distributions, Stable Distributions, Tail Dependence

JEL Classification: G01, G10, G12

Suggested Citation

Stein, Michael and Piazolo, Daniel and Stoyanov, Stoyan Veselinov, Tail Parameters of Stable Distributions Using One Million Observations of Real Estate Returns from Five Continents (November 27, 2015). Journal of Real Estate Research, Vol. 37, No. 2, 2015, 245 - 279 , Available at SSRN: https://ssrn.com/abstract=2696105

Michael Stein (Contact Author)

University of Duisburg-Essen ( email )

Universitätsst. 12
Duisburg, 45117
Germany

HOME PAGE: http://www.fmoek.wiwi.uni-due.de/

Daniel Piazolo

THM Technische Hochschule Mittelhessen ( email )

University of Applied Sciences
Wilhelm-Leuschner-Straße 13
Friedberg, 61169
Germany

HOME PAGE: http://www.thm.de/wi/daniel-piazolo

Stoyan Veselinov Stoyanov

Charles Schwab ( email )

101 Montgomery Street (120K-15)
San Francisco, CA 94104
United States

Do you have negative results from your research you’d like to share?

Paper statistics

Abstract Views
469
PlumX Metrics