Quantitative methods for risk management in the real estate development industry: Risk measures, risk aggregation and performance measures

Introduction

Investment in real estate is based on dynamic, uncertain and complex assumptions. This is especially true for real estate development given its speculative and entrepreneurial activity. Factors such as unknown future demand, risks and uncertainty are key elements of real estate development (Byrne, 1996; Isaac et al., 2010; Schulte and Bone-Winkel, 2002). Effective risk management is thus a decisive strategic success factor. Though not always evident during periods of strong economic growth, it is undoubtedly of paramount importance during economic downturns. The global financial crisis and the deterioration in real estate markets across large parts of Europe in 2008/2009 clearly demonstrated the significance of the real estate industry for the world economy. Despite the structural significance of real estate to the economy and even though risk management has been widely analyzed in academic research, there remains limited substantive research on risk management that pertains directly to real estate development. Further, even less empirical data exists that can provide an overview of industry practice with respect to risk management by major development organisations (RICS, 2003; Shun, 2000). This paper provides a comprehensive overview of risk quantification, which may be expressed by probability distributions, and the calculation of risk measures, such as “capital requirements” (value-at-risk). A key technique is the aggregation of risks by means of simulation that creates transparency about planning certainty.