Abstract
This paper analyses one of the main factors that cause financial crisis and that are real estate portfolio management in banks. VAR and SVAR models were introduced and impulse response functions were obtained. The aforementioned function demonstrated how residential prices reacted to shock. Afterwards, financial turbulence index based on Mahalanobis distance and correlation between real estate prices in Austria, Germany and Switzerland was calculated and its relation to stock prices in EURO area. Financial turbulence demonstrated the lagging effect of financial crisis originating from USA. Data were taken from St. Louis FED database. Having calculated correlations, portfolio was created consisting of REITs, ETFs and stocks. It was optimised and efficient frontiers were found for different portfolio weightings. It was proved that the best way to optimise real estate portfolio was to invest in Swiss real estate as prices were growing and to hedge with Austrian real estate or some variations of ETFs.
Highlights
Financial bubbles are a real threat to the system
Impulse response function demonstrates that Swiss real estate prices will continue to grow, but German growth is slowing down, the implication is the following: the correlation between German and Austrian real estate prices will decrease, the correlation is still too high to make investment as a measure of diversification in the aforementioned real estate in Germany and Switzerland
By using impulse response function, the possible movement of real estate prices was presented in the aforementioned countries
Summary
Financial bubbles are a real threat to the system. The arousal of financial bubbles must be closely monitored as. (2015) Analysing and Optimising Bank Real Estate Portfolio by Using Impulse Response Function, Mahalanobis Distance and Financial Turbulence. In order to analyse the financial bubbles, nonlinearities and illogical movement of correlated time series must be observed. Impulse response functions are related to SVAR and VAR models, their observation independently can be very useful as they serve as a perfect tool to observe illogical movement between time series. By observing impulse response functions, it could come to a conclusion that illogical movement could act as a predictor of real estate bubbles. The results will be analysed and will be tried to be applied to real estate portfolio management by analysing correlation between stock prices and real estate price movement in the aforementioned countries. Concerning the aforementioned analysis, sensitivity analysis will be conducted and different points of efficient frontier will be obtained
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