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Stochastic framework for carbon price risk estimation of real estate: a Markov switching GARCH simulation approach

Cay Oertel (IntReal, Hamburg, Germany)
Ekaterina Kovaleva (IntReal, Hamburg, Germany)
Werner Gleißner (FutureValue Group AG, Leinfelden-Echterdingen, Germany)
Sven Bienert (International Real Estate Business School, University Regensburg, Regensburg, Germany)

Journal of Property Investment & Finance

ISSN: 1463-578X

Article publication date: 14 February 2022

Issue publication date: 24 June 2022

220

Abstract

Purpose

The risk management of transitory risk for real assets has gained large interest especially in the past 10 years among researchers as well as market participants. In addition, the recent regulatory tightening in the EU urges financial market participants to disclose sustainability-related financial risk, without providing any methodological guidance. The purpose of the study is the identification and explanation of the methodological limitations in the field of transitory risk modeling and the logic step to advance toward a stochastic approach.

Design/methodology/approach

The study reviews the literature on deterministic risk modeling of transitory risk exposure for real estate highlighting the heavy methodological limitations. Based on this, the necessity to model transitory risk stochastically is described. In order to illustrate the stochastic risk modeling of transitory risk, the empirical study uses a Markov Switching Generalized Autoregressive Conditional Heteroskedasticity model to quantify the carbon price risk exposure of real assets.

Findings

The authors find academic as well as regulatory urgency to model sustainability risk stochastically from a conceptual point of view. The own empirical results show the superior goodness of fit of the multiregime Markov Switching Generalized Autoregressive Conditional Heteroskedasticity in comparison to their single regime peer. Lastly, carbon price risk simulations show the increasing exposure across time.

Practical implications

The practical implication is the motivation of the stochastic modeling of sustainability-related risk factors for real assets to improve the quality of applied risk management for institutional investment managers.

Originality/value

The present study extends the existing literature on sustainability risk for real estate essentially by connecting the transitory risk management of real estate and stochastic risk modeling.

Keywords

Citation

Oertel, C., Kovaleva, E., Gleißner, W. and Bienert, S. (2022), "Stochastic framework for carbon price risk estimation of real estate: a Markov switching GARCH simulation approach", Journal of Property Investment & Finance, Vol. 40 No. 4, pp. 381-397. https://doi.org/10.1108/JPIF-12-2021-0104

Publisher

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Emerald Publishing Limited

Copyright © 2022, Emerald Publishing Limited

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