Forecasting market turbulence using regime-switching models

We propose an early warning system to timely forecast turbulence in the US stock market. In a first step, a Markov-switching model with two regimes (a calm market and a turbulent market) is developed. Based on the time series of the monthly returns of the S&P 500 price index, the corresponding filtered probabilities are successively estimated. In a second step, the turbulent phase of the model is further specified to distinguish between bullish and bearish trends. For comparison only, a Markov-switching model with three states (a calm market, a turbulent bullish market, and a turbulent bearish market) is examined as well. In a third step, logistic regression models are employed to forecast the filtered probabilities provided by the Markov-switching models. A major advantage of the presented modeling framework is the timely identification of the factors driving the different phases of the capital market. In a fourth step, the early warning system is applied to an asset management case study. The results show that explicit consideration of the models’ signals yields better portfolio performance and lower portfolio risk compared to standard buy-and-hold and constant proportion portfolio insurance strategies.     

Accuracy of self-reports on donations to charitable organizations

In this paper we assess overall accuracy in survey self-reports on giving to charitable organizations, direction of bias in self-reports, and the influence of this bias on relationships. We compare donations to one specific health charity reported in the Giving in the Netherlands Panel Study 2003 with donations recorded in the database (n =  191). We find that (a) reported donations are significantly higher than recorded donations; (b) reported amounts contributed are correlated very strongly with recorded contributions; (c) differences between amounts reported and amounts recorded are positively related to education, religious affiliation, and the tendency to social desirability, and negatively to household income. This suggests that effects of education are overestimated and effects of income and religious affiliation are underestimated using self-reports on donations rather than archival records.     

Linking participatory and GIS-based land use planning methods: A case study from Burkina Faso

Sustainable land use planning is crucial for realizing the aim of food security and for combating land degradation in the Sahel. A participatory land use planning workshop was organised in a village in the eastern region of Burkina Faso to investigate land use problems, their causes, effects and possible solutions. Participatory research tools and GIS were combined to get insight into possible conflicts or synergies between different land use options as mapped by different ethnic groups. Pictograms were used to locate alternative land use options on the map, after which they were digitised for analysis with GIS. The workshop confirms the importance of integrating scientific and local knowledge to develop concrete options for sustainable land use that fit to local realities and aspirations. Local people are knowledgeable about the driving forces behind land degradation, they take actions to combat the effects of degradation, and they have concrete ideas about alternative land use options. The use of GIS proved its added value in the participatory process of integrated land use planning. The maps that were produced also facilitate discussions between community members, researchers and government representatives at the regional level, both regarding current land use problems and regarding alternative options as perceived by the local population.     

The law of proportionate effect and OECD bank sectors

The paper investigates the growth dynamics of the bank sectors in the OECD area over the period 1985–1994 and examines whether the structural financial reforms of the late 1980s have affected their growth path. Based on a test of Gibrat's law of proportionate effect, it is found that the 1985–89 period was characterized by size convergence, implying that smaller bank sectors were expanding more rapidly. However, in the 1990–1994 period the pattern reversed to proportionate growth. The analysis of the determinants of bank market growth reveals that macroeconomic growth, operational bank efficiency, credit quality, and capitalization are the main drivers of bank industry growth.     

The limits to IPR standardization policies as evidenced by strategic patenting in UMTS

The impact of patents and patent royalties are a major concern of standards setting organizations. This study examines the patents filed in the standardization of UMTS, the third-generation mobile phone technology developed under sponsorship of the European Telecommunications Standards Institute (ETSI) and others, using a patent policy developed in response to issues faced in the earlier GSM (née Group Special Mobile) standardization. After contrasting firm strategies and policy effectiveness between the GSM and UMTS efforts, the paper reviews the potential impact of potential changes to the ETSI IPR (intellectual property rights) policy.     

How CEOs protect themselves against dismissal: A social status perspective

In this study, we address the question of why some CEOs stay in office during a performance downturn while others don't. Taking a social status perspective, we argue that an individual's board network embeddedness—as reflected in the number of outside directorships—plays an important role in dismissal decisions. We predict that a high status of the CEO relative to the chairman of the board protects an underperforming CEO against dismissal, while the relative salience of board network outsiders can counter this effect. Using longitudinal data of large German corporations, we find support for our predictions. Ltd. Copyright © 2015 John Wiley & Sons, Ltd.     

Stochastic covariance and dimension reduction in the pricing of basket options

This paper presents a tailor-made method for dimension reduction aimed at approximating the price of basket options in the context of stochastic volatility and stochastic correlation. The methodology is built on a modification to the Principal Component Stochastic Volatility (PCSV) model, a stochastic covariance model that accounts for most stylized facts in prices. The method to reduce dimension is first derived theoretically. Afterwards the results are applied to a multivariate lognormal context as a special case of the PCSV model. Finally empirical results for the application of the method to the general PCSV model are illustrated.