Mergers and Target Transparency

We empirically investigate the hypothesis that the less transparent (more difficult to value) the target’s assets are the more likely it is that the acquiring firm can obtain higher short- and long-term returns. We analyze a sample of 1,538 friendly acquisitions partitioned in two separate dimensions: acquisitions of public versus private firms, and acquisitions of a firm’s assets versus acquisitions of a firm’s assets and its management. Using a sample of (nondiversifying) real estate transactions with a public REIT as the acquirer, we find that acquisitions of public firms have insignificant short-term abnormal returns. Acquisitions of private targets have positive and significant short-term abnormal returns. The acquirer’s abnormal returns are higher in both cases when the transactions involve acquisition of the target firm’s management. We find parallel results when analyzing the acquirer’s Q over the merger year and the three following years. Our conclusions are robust to the type of financing (cash, stock, or a combination) used in the acquisition

Risk measures for direct real estate investments with non-normal or unknown return distributions

The volatility of returns is probably the most widely used risk measure for real estate. This is rather surprising since a number of studies have cast doubts on the view that volatility can capture the manifold risks attached to properties and corresponds to the risk attitude of investors. A central issue in this discussion is the statistical properties of real estate returns—in contrast to neoclassical capital market theory they are mostly non-normal and often unknown, which render many statistical measures useless. Based on a literature review and an analysis of data from Germany we provide evidence that volatility alone is inappropriate for measuring the risk of direct real estate. We use a unique data sample by IPD, which includes the total returns of 939 properties across different usage types (56% office, 20% retail, 8% others and 16% residential properties) from 1996 to 2009, the German IPD Index, and the German Property Index. The analysis of the distributional characteristics shows that German real estate returns in this period were not normally distributed and that a logistic distribution would have been a better fit. This is in line with most of the current literature on this subject and leads to the question which indicators are more appropriate to measure real estate risks. We suggest that a combination of quantitative and qualitative risk measures more adequately captures real estate risks and conforms better with investor attitudes to risk. Furthermore, we present criteria for the purpose of risk classification

The Effects of Assumption Financing Across Housing Price Categories

This study employs a standard housing valuation model to analyze the capitalization of below-market financing across housing price categories. The study also investigates the effect of secondary financing on housing prices and the effect of the expected holding period on discount capitalization. Using a randomly selected sample of 1981-82 housing transactions the study finds: the discount associated with below-market financing is inversely related to the absolute level of housing prices; secondary financing bears no systematic relationship to housing values; and discount capitalization is inversely related to the expected holding period. Copyright American Real Estate and Urban Economics Association.

Risk Analysis in Land Development

Land development poses a different set of risks from income-producing property. This paper explores the nature of land development risk with particular reference to large-scale subdivision development. Because several major variables in land development analysis are correlated, meaningful risk analysis requires that intercorrelation be explicitly recognized and incorporated into simulations. A case study is presented which demonstrates the application of risk analysis to land development and the handling of intercorrelation among random variables. Copyright American Real Estate and Urban Economics Association.

Does the introduction of stock index futures effectively reduce stock market volatility? Is the 'futures effect' immediate? Evidence from the Italian stock exchange using GARCH

The impact of futures trading on the underlying asset volatility, and its characteristics, is still debated both in the economic literature and among practitioners. The aim of this study is to analyse the effect of the introduction of stock index futures on the volatility of the Italian Stock Exchange. This study mainly addresses two issues: first, the study analyses whether the reduction of stock market volatility showed in the post-futures period, already pointed out in previous research, is effectively due to the introduction of futures contract. Second, whether the 'futures effect', if confirmed, is immediate or delayed with respect to the moment of the futures trading onset is tested. The results show that the introduction of stock index futures per se has led to diminished stock market volatility and no other contingent cause seems to have systematically reduced it. Further, they also suggest that the impact of futures onset on the underlying market volatility is likely to be immediate. These findings are consistent with those theories stating that active and developed futures markets enhance the efficiency of the corresponding spot markets.