Random walk versus multiple trend breaks in stock prices : evidence from 15 European markets

This letter extends research reported in Narayan and Smyth (2005) by employing multiple trend break unit root tests to examine the random walk hypothesis for 15 European stock market indices. The results provide strong support for the view that stock prices are characterized by a random walk.

Mean reversion versus random walk in G7 stock prices evidence from multiple trend break unit root tests

This paper provides evidence on the random walk hypothesis in G7 stock price indices using unit root tests which allow for one and two structural breaks in the trend. Of the seven countries we find, at best, evidence of mean reversion in the stock price index of Japan. Thus, overall, our results support the random walk hypothesis. We also consider the implications of the identified structural breaks for movement in stock prices over time. Our main conclusion from this exercise is that the second break in stock prices has had a detrimental effect on movements in stock prices in the G7 countries.

Functional and metabolic remodelling in GLUT4-deficient hearts confers hyper-responsiveness to substrate intervention

Impaired glucose uptake is associated with both cardiac hypertrophy and contractile dysfunction, but whether there are common underlying  mechanisms linking these conditions is yet to be determined. Using a ‘gene dose’ Cre-Lox GLUT4-deficient murine model, we examined the effect of suppressed glucose availability on global myocardial gene expression and glycolysis substrate bypass on the function of isolated perfused hearts. Performance of hearts from 22- to 60-week-old male GLUT4 knockout (KO, > 95% reduction in GLUT4), GLUT4 knockdown (KD, 85% reduction in cardiac GLUT4) and C57Bl/6 wild-type (WT) controls was measured ex vivo in Langendorff mode perfusion. DNA microarray was used to profile mRNA expression differences between GLUT4-KO and GLUT4-KD hearts. At 22 weeks, GLUT4-KO hearts exhibited cardiac hypertrophy and impaired contractile function ex vivo, characterized by a 40% decrease in developed pressure. At 60 weeks, dysfunction was accentuated in GLUT4-KO hearts and evident in GLUT4-KD hearts. Exogenous pyruvate (5 mM) restored systolic pressure to a level equivalent to WT (GLUT4-KO, 176.8 ± 13.2 mmHg vs. WT, 146.4 ± 9.56 mmHg) in 22-week-old GLUT4-KO hearts but not in 60-week-old GLUT4-KO hearts. In GLUT4-KO, DNA microarray analysis detected downregulation of a number of genes centrally involved in mitochondrial oxidation and upregulation of other genes indicative of a shift to cytosolic β-oxidation of long chain fatty acids. A direct link between cardiomyocyte GLUT4 deficiency, hypertrophy and contractile dysfunction is demonstrated. These data provide mechanistic insight into the myocardial metabolic adaptations associated with short and long-term insulin resistance and indicate a window of opportunity for substrate intervention and functional ‘rescue’.

Nutrient contribution to hyper-eutrophic wetlands in Perth, Western Australia

This thesis investigates nutrient contribution to six hyper-eutrophic lakes located within close proximity of each other on the Swan Coastal Plain and 20 kilometres south of the Perth Central Business District, Western Australia. The lakes are located within a mixed land use setting and are under the management of a number of state and local government departments and organisations. These are a number of other lakes on the Swan Coastal Plain for which the majority are less than 3 metres in depth and considered as an expression of the groundwater as their base is below the regional groundwater table throughout most of the year. The limited amount of water quality data available for these six lakes and the surface water and groundwater flowing into them has restricted a thorough understanding of the processes influencing the water quality of the lakes. Various private and public companies and organisations have undertaken studies on some of the individual wetlands and there is a wide difference in scientific opinion as to the major source of the nutrients to those wetlands. These previous studies failed to consider regional surface water and groundwater effects on the nutrient fluxes and they predominantly only investigated single wetland systems. This study attempts for the first time to investigate the regional contribution of nutrients to this system of wetlands existing on the Swan Coastal plain. As such, it also includes new research on the nutrient contribution to some of the remaining wetlands. The research findings indicate that the lake sediments represent a considerable store of nutrients (nitrogen and phosphorus). These sediments in turn control the nutrient status of the lake's water column. Surface water is found to contribute on an event-basis load of nutrients to the lakes whilst the groundwater surprisingly appears to contribute a comparatively low input of nutrients but governs the water depth. Analysis of the regional groundwater shows efficient denitrifying abilities as a result of denitrifying bacteria and the transport is localised. Management recommendations for the remediation of the social and environmental value of the lakes include treatment of the lake’s sediments via chemical bonding or atmospheric oxidation; utilising the regional groundwater’s denitrifying abilities to ‘treat’ the surface water via infiltration basins; and investigating the merits of managed or artificial aquifer recharge (MAR).

A comparison of the ICI Pillbox and the Random Tumble Methods is assessing pilling and appearance change of worsted spun cashmere and cashmere-wool blend knitwear

This study evaluated the differences between two international test methods on the assessment of pilling and appearance change of worsted spun cashmere and superfine wool knitwear and their blends. Differences between the standard ICI Pill Box Method and the Random Tumble Method were found in both the significance and magnitude of resistance to pilling and appearance change and the amount of fabric mass loss of worsted spun cashmere and cashmere superfine wool blend knit fabrics. The ICI Pill Box Method differentiated to a greater extent the effects of wool type and blend ratio of cashmere and wool compared with the Random Tumble Method. Generally the addition of cashmere or low crimp superfine wool resulted in fabrics being more resistance to pilling and appearance change compared with fabrics made from high crimp superfine wool. This was associated with increased fabric mass loss when assessed by the ICI Pill Box Method but not with the Random Tumble Method. KEYWORDS: Cashmere, crimp, wool, pilling, appearance change, knitwear

Testing for a random walk in Italy's inflation in the post-war period, 1947-1996

This paper investigates the unit root properties of Italy’s inflation rate in the post-war period (1947-1996). To achieve the aim of this study, the Zivot and Andrews (1992) one break test and the Lumsdaine and Papell (1997) two breaks test for unit roots are applied. It is found that inflation for Italy was a non-stationary breakpoint for the period 1947-1996. This result has important implications for econometric modeling and in understanding the behavior of shocks to Italy’s inflation.

Testing for the random walk hypothesis in the case of visitor arrivals : evidence from Indian tourism

Testing for the random walk hypothesis, which asserts that a series is a non-stationary process or a unit root process, in the case of visitor arrivals has important implications for policy. If, for instance, visitor arrivals are characterized by a unit root, then it implies that shocks to visitor arrivals are permanent. However, if visitor arrivals are without a unit root, this implies that shocks to visitor arrivals are temporary. This study provides evidence on the random walk hypothesis for visitor arrivals to India using the recently developed Im et al. (2003) and Maddala and Wu (1999) panel unit root tests. Both tests allow one to reject the random walk hypothesis, implying that shocks to visitor arrivals to India from the 10 major source markets have a temporary effect on visitor arrivals.

Are OECD stock prices characterized by a random walk? Evidence from sequential trend break and panel data models

This paper examines whether stock prices for a sample of 22 OECD countries can be best represented as mean reversion or random walk processes. A sequential trend break test proposed by Zivot and Andrews is implemented, which has the advantage that it can take account of a structural break in the series, as well as panel data unit root tests proposed by Im et al., which exploits the extra power in the panel properties of the data. Results provide strong support for the random walk hypothesis.

Is extrapair mating random? On the probability distribution of extrapair young in avian broods

A dichotomy in female extrapair copulation (EPC) behavior, with some females seeking EPC and others not, is inferred if the observed distribution of extrapair young (EPY) over broods differs from a random process on the level of individual offspring (binomial, hypergeometrical, or Poisson). A review of the literature shows such null models are virtually always rejected, with often large effect sizes. We formulate an alternative null model, which assumes that 1) the number of EPC has a random (Poisson) distribution across females (broods) and that 2) the probability for an offspring to be of extrapair origin is zero without any EPC and increases with the number of EPC. Our brood-level model can accommodate the bimodality of both zero and medium rates of EPY typically found in empirical data, and fitting our model to EPY production of 7 passerine bird species shows evidence of a nonrandom distribution of EPY in only 2 species. We therefore argue that 1) dichotomy in extrapair mate choice cannot be inferred only from a significant deviation in the observed distribution of EPY from a random process on the level of offspring and that 2) additional empirical work on testing the contrasting critical predictions from the classic and our alternative null models is required.

Multilabel classification by BCH code and random forests

This paper uses error correcting codes for multilabel classification. BCH code and random forests learner are used to form the proposed method. Thus, the advantage of the error-correcting properties of BCH is merged with the good performance of the random forests learner to enhance the multilabel classification results. Three experiments are conducted on three common benchmark datasets. The results are compared against those of several exiting approaches. The proposed method does well against its counterparts for the three datasets of varying characteristics.

Dual-random ensemble method for multi-label classification of biological data

This paper presents a dual-random ensemble multi-label classification method for classification of multi-label data. The method is formed by integrating and extending the concepts of feature subspace method and random k-label set ensemble multi-label classification method. Experiemental results show that the developed method outperforms the exisiting multi-lable classification methods on three different multi-lable datasets including the biological yeast and genbase datasets.

Random forest based lung nodule classification aided by clustering

An automated lung nodule detection system can help spot lung abnormalities in CT lung images. Lung nodule detection can be achieved using template-based, segmentation-based, and classification-based methods. The existing systems that include a classification component in their structures have demonstrated better performances than their counterparts. Ensemble learners combine decisions of multiple classifiers to form an integrated output. To improve the performance of automated lung nodule detection, an ensemble classification aided by clustering (CAC) method is proposed. The method takes advantage of the random forest algorithm and offers a structure for a hybrid random forest based lung nodule classification aided by clustering. Several experiments are carried out involving the proposed method as well as two other existing methods. The parameters of the classifiers are varied to identify the best performing classifiers. The experiments are conducted using lung scans of 32 patients including 5721 images within which nodule locations are marked by expert radiologists. Overall, the best sensitivity of 98.33% and specificity of 97.11% have been recorded for proposed system. Also, a high receiver operating characteristic (ROC) A_z of 0.9786 has been achieved.

A triple-random ensemble classification method for mining multi-label data

This paper presents a triple-random ensemble learning method for handling multi-label classification problems. The proposed method integrates and develops the concepts of random subspace, bagging and random k-label sets ensemble learning methods to form an approach to classify multi-label data. It applies the random subspace method to feature space, label space as well as instance space. The devised subsets selection procedure is executed iteratively. Each multi-label classifier is trained using the randomly selected subsets. At the end of the iteration, optimal parameters are selected and the ensemble MLC classifiers are constructed. The proposed method is implemented and its performance compared against that of popular multi-label classification methods. The experimental results reveal that the proposed method outperforms the examined counterparts in most occasions when tested on six small to larger multi-label datasets from different domains. This demonstrates that the developed method possesses general applicability for various multi-label classification problems.