Forecasting risk and return of listed real estate: A simulation approach with geometric Brownian motion for the German stock market

In this paper a forecasting model for real estate stock returns and risks is developed and tested with the data of German real estate companies from 1991 to 2021. In contrast to several other studies, alternative risk measures are used to adequately reflect investors’ preferences. At first, the paper constructs a traditional five-factor Arbitrage Pricing Theory model to measure the sensitivity of real estate stock returns to the stock, bond and real estate markets as well as to inflation and the overall economy. The analysis shows that German real estate stocks have a high idiosyncratic risk and that they are more impacted by changes in the economy and the stock market than by changes in the real estate market. Then a geometric Brownian motion concept combined with a Monte Carlo simulation is applied to model future asset prices. The downside risk measures value at risk and conditional value at risk are used to quantify the risk for an investor in listed real estate instead of the usual volatility. The paper finds that listed real estate has less downside risk than general stocks.