Hot and cold merger markets

We study mergers and acquisition during the period from 1988 to 2005 and examine the impact of merger market intensity, i.e., merger waves, on the means of payment and the returns to target and acquirer shareholders. We use two proxies to measure the intensity of the merger market—the number of mergers in the trailing 12-month period prior to a merger and the total dollar volume of mergers in the trailing 12-month period prior to a merger—and use these measures to define hot and cold merger markets. We find that stock financing is more common after a stock price run-up for the acquiring firm and in hot merger markets. We also find that the acquisition premium is larger in hot merger markets. Returns to acquiring company shareholders are lower for stock financed mergers and are lower when merger markets are intense. Our results are consistent with the predictions of the behavioral theory for merger waves.     

Asymmetric Adjustment in the City of London Office Market

Earlier estimates of the behavior of the City of London office market are extended by considering a longer time series of data, covering two full cycles, and by explicitly modeling asymmetric space market responses to employment and supply shocks. A long run structural model linking real rental levels, office-based employment and the supply of office space is estimated and then rental adjustment processes are modeled using an error correction model framework. Rental adjustment is seen to be asymmetric, depending both on the direction of the supply and demand shocks and on the state of the space market at the time of the shock. Vacancy adjustment does not display statistically significant asymmetries. There is also a supply adjustment equation. Two three-equation systems, one with symmetric rental adjustment and the other with asymmetric adjustment, are subjected to positive and negative shocks to employment. These illustrate differences in the properties of the two systems.     

Flood Hazards and Urban Housing Markets: The Effects of Katrina on New Orleans

This study examines the impacts on consumers’ willingness to pay for certain characteristics of housing in greater New Orleans before and after the flooding of Hurricane Katrina. Single-family home sales from January 2004 to August 2006 are collected and used in a hedonic price function to estimate the changes in the value of amenities, and structural, neighborhood and geographic characteristics, including the mean elevation of each property. Elevation, which buyers did not know for certain prior to the storm, but may now be inferred from water level marks in most neighborhoods, is found to have a positive relationship with selling prices. Results indicate that pre-Katrina, there was a premium of only 1.4% per foot in flood-prone areas, and was insignificant in areas not subject to flooding. This increased to 4.6% for flooded areas after Katrina. These findings are attributed to not only the perceived risk of flooding, but also to the potential of higher compliance costs associated with rebuilding under more stringent National Flood Insurance Program (NFIP) guidelines.     

A Theory on REIT’s Advisor Choice and the Optimal Compensation Mechanism

This paper proposes a model which examines the power of monitoring and forcing contract on improving managerial efficiency. We put particular focus on its implication regarding the choice of advisor type used by REITs. This question has long been a puzzling one in real estate literature. Our model provides a theoretical justification regarding the potential appeal of external managerial structure, which is usually regarded as being inferior to internal managerial structure. A crucial driving force regarding advisor choice is the heterogeneity on monitoring power between internal and external advisors and across REIT firms. Provided that the gap of monitoring power is large enough between internal and external advisors, shareholders could make use of the heterogeneity, and induce higher effort levels from external advisors. We motivate the rationale for expecting a “monitoring advantage” over external management from two aspects: the dual-role of external advisory firm and a bigger reputational cost associated with external advisor. Furthermore, we are able to specify the range within which an improved monitoring power is Pareto-optimal for both REIT shareholders and advisors. One implication is that, as agents, it may also be to the benefit of advisors to be better monitored. Finally, we compare the difference between fixed and stochastic forcing contracts. Our findings show that with their imperfect performance measures, the stochastic forcing contracts always dominate the fixed one.     

Rising UI benefits over time

We re-examine a key result in the optimal UI literature that benefits should decline over time. We show that when the population is heterogeneous, Pareto-efficiency may call for multiple payment schedules, some with benefits that fall over time and some with benefits that rise over time.     

A fast Fourier transform technique for pricing American options under stochastic volatility

This paper develops a non-finite-difference-based method of American option pricing under stochastic volatility by extending the Geske-Johnson compound option scheme. The characteristic function of the underlying state vector is inverted to obtain the vector’s density using a kernel-smoothed fast Fourier transform technique. The method produces option values that are closely in line with the values obtained by finite-difference schemes. It also performs well in an empirical application with traded S&P 100 index options. The method is especially well suited to price a set of options with different strikes on the same underlying asset, which is a task often encountered by practitioners.     

Links and interdependence of developed stock markets under global economic crisis conditions

The scope of this article is to determine whether global stock markets behave differently under conditions of economic crisis by studying the interdependence among the price indices of 10 markets, including Dow Jones (DJ), DAX and NIKKEI. The stock markets under examination are those of the USA, Belgium, France, Germany, Greece, Italy, The Netherlands, Spain, the United Kingdom and Japan. The sample includes the logarithmic daily closing prices from 1 January 2000 to 20 February 2009, with a total of approximately 2.385 observations analyzed. The empirical findings suggest that the recent deep crisis has increased dramatically their correlation, thus tightening the existing links. Causality also seems to be affected by the crisis, as DJ and DAX cease to exert a dominant influence on the other stock indices. However, in all the other periods, the findings of previous studies (suggesting that DJ and DAX seriously affect the other indices) were verified, independent of the prevailing bear or bull market conditions.     

Comparing Firm Failure Predictions Between Logit,KMV, and ZPP Models: Evidence from Taiwan’s Electronics Industry

This paper applies the Taiwan electronics industry data to detect the discriminatory powers of Logit, KMV, and zero-price probability (ZPP) models that represent respectively the regressive fitting model, the option-based pricing model, and the GARCH time series simulation model. In our circumstances, according to cumulative accuracy profile, receiver operating characteristic, and even Brier score, the KMV performs the worst. The disadvantages for KMV are that the equity market exists some nonlinear characteristics, the unknown market value of asset affected by the change of capital structure is not exogenous, and the failure point is difficult to be estimated correctly. Besides, KMV is however too simple to model the fluctuation of the equity value as the GARCH does. On the other hand, the Logit performs above average. To preclude over-fitting and keep model parsimonious, two significant factors are extracted from as many as forty financial variables for the logistic regression on binary failure data. The result of Logit training has perfect discrimination. However, for the post-sample data, the fitting to categorical but not ordinal data makes Logit have the divergent failure predicted probabilities and highest Briser Score. In practical, ZPP GARCHNorm uses just equity value to predict firm failure but it performs remarkably well supposing that downward price trend or volatility persistence in stock price changes is appropriately caught. It implies that the distorted signals such as overreaction of traders and insider trading would definitely impair the ZPP GARCHNorm. Nevertheless, the larger type I error than type II error in all models indicates that the prediction of non-failed firms should be more examined further than that of failed firms.     

Efficiency of Microfinance Institutions: A Data Envelopment Analysis

This study examines the cost efficiency of 39 microfinance institutions across Africa, Asia and the Latin America using non-parametric data envelopment analysis. Our findings show non-governmental microfinance institutions particularly; under production approach, are the most efficient and this result is consistent with their fulfillment of dual objectives: alleviating poverty and simultaneously achieving financial sustainability. However, bank-microfinance institutions also outperform in the measure of efficiency under intermediation approach. This result reflects that banks are the financial intermediaries and have access to local capital market. It may be possible that bank-microfinance institutions may outperform the non-governmental microfinance institutions in the long run.