Accessibility navigation

Risk driven investment in public real estate

Katyoka, M. M. (2019) Risk driven investment in public real estate. PhD thesis, University of Reading

Text - Thesis
· Please see our End User Agreement before downloading.

[img] Text - Thesis Deposit Form
· Restricted to Repository staff only


It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

To link to this item DOI: 10.48683/1926.00085946


The global financial crisis towards the end of the last decade saw an increasing need in the role of risk measurement and management in the mainstream financial investment market. Among other things, the measurement and management of market risk, credit risk, and operational risk have become pronounced than ever before. Different strategies have been employed in dealing with the unpredictable nature of the market. This research focuses on the risk-driven investment in public real estate. The aims of this research are threefold 1. To examine whether the real estate allocation based on risk parity leads to better performance compared to other allocation methods 2. To assess the performance of market risk models, namely value at risk (VaR) and expected shortfall on the real estate market. 3. To investigate the volatility transmission of the UK implied volatility index and UK REITs with traded options The results for the risk allocation generally show that risk parity does in some instances perform better than other allocation methods. Concerning market risk modelling, VaR offers much simple modelling in comparison to expected shortfall. The challenge in the expected shortfall is in its time-consuming nature but it does address the shortcoming of VaR. With regards to the volatility transmission, the results are significant there showing that there is a volatility spillover (transmission) between the changes in implied volatility of the FTSE 100 volatility index, the REIT companies with traded options and the UK REIT index prices.

Item Type:Thesis (PhD)
Thesis Supervisor:Stevenson, S.
Thesis/Report Department:Henley Business School
Identification Number/DOI:
Divisions:Henley Business School > Real Estate and Planning
ID Code:85946


Downloads per month over past year

University Staff: Request a correction | Centaur Editors: Update this record

Page navigation