Quantitatives Risikomanagement in der Immobilienwirtschaft

Oertel, Cay

doi:10.1007/978-3-658-23971-8

Cited by 1 publication

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“…Based on this definition, FMPs are thus facing the actual challenge to translate the Plan's fiduciary duties into applied methodology. For alternative investments such as real estate, risk modeling is generally challenging and, both, highly data-sensitive and -dependent (Oertel, 2018). The data scarcity and methodological uncertainty surrounding new risk factors in the field of sustainability increase the challenge to implement risk management systems even more.…”

Section: Introduction and Recent Regulatory Tightening In The Eumentioning

confidence: 99%

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

Oertel¹,

Ковалева²,

Gleißner

et al. 2022

JPIF

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PurposeThe 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/approachThe 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.FindingsThe 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 implicationsThe 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/valueThe 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.

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Section: Introduction and Recent Regulatory Tightening In The Eumentioning

confidence: 99%