No abstract

Obsessive–compulsive disorder (OCD) is a psychiatric illness that significantly impacts affected patients and available treatments yield suboptimal therapeutic response. Recently, the role of the gut–brain axis (GBA) in psychiatric illness has emerged as a potential target for therapeutic exploration. However, studies concerning the role of the GBA in OCD are limited. To investigate whether a naturally occurring obsessive–compulsive‐like phenotype in a rodent model, that is large nest building in deer mice, is associated with perturbations in the gut microbiome, we investigated and characterised the gut microbiota in specific‐pathogen‐free bred and housed large (LNB) and normal (NNB) nest‐building deer mice of both sexes (n = 11 per group, including three males and eight females). Following baseline characterisation of nest‐building behaviour, a single faecal sample was collected from each animal and the gut microbiota analysed. Our results reveal the overall microbial composition of LNB animals to be distinctly different compared to controls (PERMANOVA p < .05). While no genera were found to be significantly differentially abundant after correcting for multiple comparisons, the normal phenotype showed a higher loading of Prevotella and Anaeroplasma, while the OC phenotype demonstrated a higher loading of Desulfovermiculus, Aestuariispira, Peptococcus and Holdemanella (cut‐off threshold for loading at 0.2 in either the first or second component of the PCA). These findings not only provide proof‐of‐concept for continued investigation of the GBA in OCD, but also highlight a potential underlying aetiological association between alterations in the gut microbiota and the natural development of obsessive–compulsive‐like behaviours.

The exponential distribution is a popular model both in practice and in theoretical work. As a result, a multitude of tests based on varied characterisations have been developed for testing the hypothesis that observed data are realised from this distribution. Many of the recently developed tests contain a tuning parameter, usually appearing in a weight function. In this paper we compare the powers of 20 tests for exponentiality-some containing a tuning parameter and some that do not. To ensure a fair 'apples to apples' comparison between each of the tests, we employ a data-dependent choice of the tuning parameter for those tests that contain these parameters. The comparisons are conducted for various samples sizes and for a large number of alternative distributions. The results of the simulation study show that the test with the best overall power performance is the Baringhaus & Henze test, followed closely by the test by Henze & Meintanis; both tests contain a tuning parameter. The score test by Cox & Oakes performs the best among those tests that do not include a tuning parameter.

Standard Bank, South Africa, currently employs a methodology when developing application or behavioural scorecards that involves logistic regression. A key aspect of building logistic regression models entails variable selection which involves dealing with multicollinearity. The objective of this study was to investigate the impact of using different variance inflation factor 1 (VIF) thresholds on the performance of these models in a predictive and discriminatory context and to study the stability of the estimated coefficients in order to advise the bank. The impact of the choice of VIF thresholds was researched by means of an empirical and simulation study. The empirical study involved analysing two large data sets that represent the typical size encountered in a retail credit scoring context. The first analysis concentrated on fitting the various VIF models and comparing the fitted models in terms of the stability of coefficient estimates and goodness-of-fit statistics while the second analysis focused on evaluating the fitted models' predictive ability over time. The simulation study was used to study the effect of multicollinearity in a controlled setting. All the above-mentioned studies indicate that the presence of multicollinearity in large data sets is of much less concern than in small data sets and that the VIF criterion could be relaxed considerably when models are fitted to large data sets. The recommendations in this regard have been accepted and implemented by Standard Bank.

Background: There are various studies that confirm the efficiency of the Johannesburg Stock Exchange (JSE), implying that there are no opportunities for active portfolio managers to earn excess returns over the long run.Aim: The aim of the research is to prove that the sub-indices on the JSE go through cycles of efficiency and inefficiency even though the JSE as a whole might be considered informationally efficient.Setting: Although the JSE as a whole can be considered to be weak-form efficient, portfolio managers are not bound to investing in large liquid stocks alone. Many aggressive funds allow managers to also allocate a portion of their portfolio to smaller stocks. This has implications when considering the efficiency of the stocks being selected.Methods: Given the impact efficiency has on portfolio selection, we test for the adaptive market hypothesis using a representative sample of stock indices by means of the automatic variance ratio test, the Chow–Denning joint variance ratio and the joint sign test on the JSE.Results: Our results confirm that some of the smaller, and in some instances younger, indices are not always as efficient as the all share index, thus allowing portfolio managers with an active management approach some opportunities to profit from informational inefficiencies in the market.Conclusion: The practice of active management by portfolio managers in the South African market seems to defy logic if one considers the fact that the JSE as a whole is at the very least weak-form efficient. By proving that some of the sub-indices that make up the all share index are inefficient most of the time, this article shows that the phenomenon of active portfolio managers is less of a surprise.