infonet-economy

The optimum scope of bank activities is central to many proposals for banking system reform. For example, a core component of the Dodd-Frank Act (2010) and regulatory proposals in the UK and the EU has been the concept of “ring-fencing” – i.e., restricting banks’ activities to their core retail and wholesale financial intermediation functions. It is argued that limiting the scope of bank activities reduces the likelihood of failure related to business lines that are highly risky. However, an alternative view holds that diversification of banks across traditional interest generating business and non-traditional businesses enhances bank profitability and reduces risk. Based on a sample of 368,006 quarterly observations on 10,341 US banks during the period 2002-2013, we find that a higher ratio of non-interest income (derived from fees and non-core activities such as investment banking, venture capital and trading) to interest income (associated with deposit-taking and lending to retail and commercial clients) is associated with higher profitability as well as lower failure probability. This finding is stronger during the crisis period than in either the pre- and post-crisis periods. We find similar results using trading (and investment banking) income instead of non-interest to interest income. Our results generally hold across bank size groups and are robust to the inclusion of bank fixed effects, bank size, and various measures of leverage and asset quality in the regressions. We find similar results in a sample of bank holding companies (BHCs), and in addition show that a higher fraction of non-traditional bank income is not associated with a higher contribution to systemic risk. Overall, our results question the benefits of “ring-fencing” bank activities.

We merge the literature on downside return risk with that on systematic liquidity risk and introduce the concept of extreme downside liquidity (EDL) risk. We show that the
cross-section of expected stock returns reflects a premium for EDL risk. Strong EDL risk stocks deliver a positive risk premium of more than 4% p.a. as compared to weak EDL risk stocks. The effect is more pronounced after the market crash of 1987. It is not driven by linear liquidity risk or by extreme downside return risk, and it cannot
be explained by other firm characteristics or other systematic risk factors.

The local robustness properties of generalized method of moments (GMM) estimators and of a broad class of GMM based tests are investigated in a unified framework. GMM statistics are shown to have bounded influence if and only if the function defining the orthogonality restrictions imposed on the underlying model is bounded. Since in many applications this function is unbounded, it is useful to have procedures that modify the starting orthogonality conditions in order to obtain a robust version of a GMM estimator or test. We show how this can be obtained when a reference model for the data distribution can be assumed. We develop a flexible algorithm for constructing a robust GMM (RGMM) estimator leading to stable GMM test statistics. The amount of robustness can be controlled by an appropriate tuning constant. We relate by an explicit formula the choice of this constant to the maximal admissible bias on the level or (and) the power of a GMM test and the amount of contamination that one can reasonably assume given some information on the data. Finally, we illustrate the RGMM methodology with some simulations of an application to RGMM testing for conditional heteroscedasticity in a simple linear autoregressive model. In this example we find a significant instability of the size and the power of a classical GMM testing procedure under a non-normal conditional error distribution. On the other side, the RGMM testing procedures can control the size and the power of the test under non-standard conditions while maintaining a satisfactory power under an approximatively normal conditional error distribution.

Background
Several studies indicate a significant association between birth season and personality and neuropsychiatric disorders. The aim of our present study was to investigate the association between affective temperaments and season of birth in a nonclinical sample.

Methods
366 university students completed the standardized Hungarian version of the Temperament Evaluation of Memphis, Pisa, Paris and San Diego-Auto-questionnaire (TEMPS-A). Ordinary Least Squares regression was applied to explain the relationship between TEMPS-A subscale and birth season of the respondents.

Results
We found a significant association between temperament scores and birth season in the case of the Hyperthymic, Cyclothymic, Irritable and Depressive temperaments, while no significant results emerged for the Anxious temperament.

Limitations
The relatively small sample size, especially in the case of seasonal and monthly subsamples limits generalization of our results.

Conclusions
Our results support the evidence that there is a strong association between season of birth and personality, extending the results to affective temperaments as well. Furthermore, our results are in line with clinical observations concerning the seasonal variation of onset and hospitalization due to affective episodes. This is especially important, since affective temperaments are conceived as the subaffective and subclinical manifestations of major and minor affective disorders indicating a risk for the development of these disorders and also exerting a possible pathoplastic effect, thus our results also have clinical significance.

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While there is little controversy on the profitability of momentum strategies, their implementation is afflicted with many difficulties. Most important, chasing momentum can generate high turnover. Though there are already several attempts to make momentum strategies less expensive with respect to transaction costs, we go a step further in the simplification of momentum strategies. By restricting our sample to Switzerland's largest blue-chip stocks and choosing only one winner and one loser stock, we find average returns to our momentum arbitrage portfolios of up to 44% p.a. depending on the formation and holding periods. While unconditional risk models are at odds with momentum profits, stock market predictability and time-varying expected returns explain a large part of the momentum payoffs, including the post-holding period behavior of the winner and loser stocks (overreaction and subsequent price correction). We also report interesting patterns of a number of stock characteristics over the (pre-)formation and (post-)holding periods.

In a recent paper, Collin-Dufresne and Goldstein (2002) show that the movements of the yield curve and of interest rate derivatives are mostly uncorrelated, advocating the presence of unspanned volatility. This letter shows that their results can be explained in the framework of a Gaussian HJM model with humped term-structure volatility. This implies that hedging interest rate derivatives with interest rate swaps is not ruled out.

Background: Multicentre clinical trials are challenged by high administrative burden, data management pitfalls and costs. This leads to a reduced enthusiasm and commitment of the physicians involved and thus to a reluctance in conducting multicentre clinical trials.Objective: The purpose of this study was to develop a web-based open source platform to support a multi-centre clinical trial.Methods: We developed on Drupal, an open source software distributed under the terms of the General Public License, a web-based, multi-centre clinical trial management system with the design science research approach.Results: This system was evaluated by user-testing and well supported several completed and on-going clinical trials and is available for free download.Conclusion: Open source clinical trial management systems are capable in supporting multi-centre clinical trials by enhancing efficiency, quality of data management and collaboration.