The real estate market is affected by great uncertainty due to the nexus of various factors: a) the specificity of the assets traded, which are illiquid, unique and very hetherogeneous from each other; b) the ‘structural disequilibrium’ of the market caused by the differences emerging in elasticity of supply with respect to demand; c) the noncompetitiveness of the market, which often turns into a bilateral monopoly; d) the great variability of market prices. Since the subprime mortgage crisis that broke out at the end of 2006 in the United States, it has clearly emerged that, in a sector that represents about a third of world wealth, it is necessary, on the one hand, to implement proper and increasingly sophisticated valuation tools, to support the design of effective risk management strategies and, on the other hand, to improve the reliability of real estate data, in order to allow for a more robust verification of the hypotheses on the trend of the cash flows generated by the investment and a more accurate valuation of the investment risk and, consequently, of the project expected rate of return. The main objective of this work is to investigate the accuracy and robustness of the estimates of real estate investors of the expected returns on an urban development project in a mediumsized city representative of the North East of Italy. Using a simulationbased approach, the gap between the observed internal rate of return, estimated ex post on the basis of the actual trend of the parameters that influence investment returns, and the expected internal rate of return, calculated ex ante on the basis of the information available at the time of the investment decision. Firstly, we constructed the time series from 1995 to 2015 of the expected and observed internal rates of return of investments in the residential sector. We obtained the time series of the cash flows generated by the investment under investigation by implementing a simulationbased approach. Starting from the comparison between observed internal rate of return and expected internal rates of return, we identified ex post the risk implicitly assumed by the investor at the time of the decision to undertake the investment. Secondly, the effectiveness of the Capital Asset Pricing Model as a method for estimating the return on a property investment was verified, by comparing the project’s observed (ex post) internal rate of return with its ex ante rate of return, estimated through the Capital Asset Pricing Model. To carry out the above analyses, we constructed the time series of observed and expected internal rate of returns from 1995 to 2015 of investments in the residential sector. The time series of the internal rate of returns of real estate investments were obtained by implementing a simulationbased approach to determine the cash flows of real estate investments representative of the context under investigation and by adopting as model inputs the parameters usually adopted in exante and expost real estate valuations. Starting from the comparison between observed and expected internal rate of returns, we identified expost the risk implicitly assumed by the developer at the time of the decision to undertake the investment. Finally, by investigating the determinants of the divergence between the investment’s observed and expected internal rate of return and cyclical variables, we identified the factors (i.e., the macroeconomic fundaments) which, in the period under investigation, affected investment risk and, consequently, investment return. Finally, by investigating the relationships that account for the difference between the observed and expected internal rate of return and the economic factors that can determine the current stage in economic cycles, we identified the determinants of invetment risk and returns.
Risk and returns in real estate development projects at the black swan test
Paolo Rosato^{ Conceptualization};Chiara D’Alpaos^{Methodology}
20220101
Abstract
The real estate market is affected by great uncertainty due to the nexus of various factors: a) the specificity of the assets traded, which are illiquid, unique and very hetherogeneous from each other; b) the ‘structural disequilibrium’ of the market caused by the differences emerging in elasticity of supply with respect to demand; c) the noncompetitiveness of the market, which often turns into a bilateral monopoly; d) the great variability of market prices. Since the subprime mortgage crisis that broke out at the end of 2006 in the United States, it has clearly emerged that, in a sector that represents about a third of world wealth, it is necessary, on the one hand, to implement proper and increasingly sophisticated valuation tools, to support the design of effective risk management strategies and, on the other hand, to improve the reliability of real estate data, in order to allow for a more robust verification of the hypotheses on the trend of the cash flows generated by the investment and a more accurate valuation of the investment risk and, consequently, of the project expected rate of return. The main objective of this work is to investigate the accuracy and robustness of the estimates of real estate investors of the expected returns on an urban development project in a mediumsized city representative of the North East of Italy. Using a simulationbased approach, the gap between the observed internal rate of return, estimated ex post on the basis of the actual trend of the parameters that influence investment returns, and the expected internal rate of return, calculated ex ante on the basis of the information available at the time of the investment decision. Firstly, we constructed the time series from 1995 to 2015 of the expected and observed internal rates of return of investments in the residential sector. We obtained the time series of the cash flows generated by the investment under investigation by implementing a simulationbased approach. Starting from the comparison between observed internal rate of return and expected internal rates of return, we identified ex post the risk implicitly assumed by the investor at the time of the decision to undertake the investment. Secondly, the effectiveness of the Capital Asset Pricing Model as a method for estimating the return on a property investment was verified, by comparing the project’s observed (ex post) internal rate of return with its ex ante rate of return, estimated through the Capital Asset Pricing Model. To carry out the above analyses, we constructed the time series of observed and expected internal rate of returns from 1995 to 2015 of investments in the residential sector. The time series of the internal rate of returns of real estate investments were obtained by implementing a simulationbased approach to determine the cash flows of real estate investments representative of the context under investigation and by adopting as model inputs the parameters usually adopted in exante and expost real estate valuations. Starting from the comparison between observed and expected internal rate of returns, we identified expost the risk implicitly assumed by the developer at the time of the decision to undertake the investment. Finally, by investigating the determinants of the divergence between the investment’s observed and expected internal rate of return and cyclical variables, we identified the factors (i.e., the macroeconomic fundaments) which, in the period under investigation, affected investment risk and, consequently, investment return. Finally, by investigating the relationships that account for the difference between the observed and expected internal rate of return and the economic factors that can determine the current stage in economic cycles, we identified the determinants of invetment risk and returns.File  Dimensione  Formato  

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