Industry Concentration and the Cross-section of Stock Returns: Evidence from the UK

In this paper, I examine the relationship between industry concentration and the cross-section of stock returns in the London Stock Exchange between 1985 and 2010. Using Multifactor asset pricing theory, I test whether industry concentration is a new asset pricing factor in addition to conventional risk factors such as beta, firm size, book-to-market ratio, momentum, and leverage. I find that industry concentration is negatively related to the expected stock returns in all Fama and MacBeth cross-sectional regressions. In addition, the negative relationship between industry concentration and expected stock returns remain significantly negative after beta, size, book-to-market, momentum, and leverage are included, while beta is never significant. The results are robust to firm- and industry-level regressions and the formation of firms into 100 size-beta portfolios. The findings indicate that competitive industries earn, on average, higher risk-adjusted returns compared to concentrated industries which is consistent with Schumpeter’s concept of creative destruction.Industry concentration, Stock returns, Multifactor asset pricing theory, Competitive industries, Concentrated industries, Creative destruction, London Stock Exchange

Comparison between random forests, artificial neural networks and gradient boosted machines methods of on-line vis-NIR spectroscopy measurements of soil total nitrogen and total carbon

Accurate and detailed spatial soil information about within-field variability is essential for variable-rate applications of farm resources. Soil total nitrogen (TN) and total carbon (TC) are important fertility parameters that can be measured with on-line (mobile) visible and near infrared (vis-NIR) spectroscopy. This study compares the performance of local farm scale calibrations with those based on the spiking of selected local samples from both fields into an European dataset for TN and TC estimation using three modelling techniques, namely gradient boosted machines (GBM), artificial neural networks (ANNs) and random forests (RF). The on-line measurements were carried out using a mobile, fiber type, vis-NIR spectrophotometer (305-2200 nm) (AgroSpec from tec5, Germany), during which soil spectra were recorded in diffuse reflectance mode from two fields in the UK. After spectra pre-processing, the entire datasets were then divided into calibration (75%) and prediction (25%) sets, and calibration models for TN and TC were developed using GBM, ANN and RF with leave-one-out cross-validation. Results of cross-validation showed that the effect of spiking of local samples collected from a field into an European dataset when combined with RF has resulted in the highest coefficients of determination (R-2) values of 0.97 and 0.98, the lowest root mean square error (RMSE) of 0.01% and 0.10%, and the highest residual prediction deviations (RPD) of 5.58 and 7.54, for TN and TC, respectively. Results for laboratory and on-line predictions generally followed the same trend as for cross-validation in one field, where the spiked European dataset-based RF calibration models outperformed the corresponding GBM and ANN models. In the second field ANN has replaced RF in being the best performing. However, the local field calibrations provided lower R-2 and RPD in most cases. Therefore, from a cost-effective point of view, it is recommended to adopt the spiked European dataset-based RF/ANN calibration models for successful prediction of TN and TC under on-line measurement conditions

Thrasymachus’ Unerring Skill and the Arguments of Republic 1

In defending the view that justice is the advantage of the stronger, Thrasymachus puzzlingly claims that rulers never err and that any practitioner of a skill or expertise (τέχνη) is infallible. In what follows, Socrates offers a number of arguments directed against Thrasymachus’ views concerning the nature of skill, ruling, and justice. Commentators typically take a dim view of both Thrasymachus’ claims about skill (which are dismissed as an ungrounded and purely ad hoc response to Socrates’ initial criticisms) and Socrates’ latter arguments (which are deemed extremely weak). In this paper, I clarify Thrasymachus’ views (and those of several other ancients) concerning qua locutions and the nature of skill and ability and I reconstruct Socrates’ arguments against Thrasymachus’ views concerning skill and justice. I argue that Thrasymachus’ views are not ungrounded or ad hoc and that Socrates’ arguments are rather different (and significantly stronger) than often supposed

Poverty and inequality in the non-income multidimensional space: A critical review in the Arab States

This paper examines the substantive pros and cons of the multidimensional poverty index (MPI) recently developed by Oxford University's Poverty and Human Development Initiative (OPHI). It provides comparative cross-country and country-specific discussion on multidimensional poverty and inequality in the non-income space, with a special reference to the countries in the Arab region. Despite the large degree of subjectivity in selecting the dimensions and the cut-off threshold (k=3) determining the minimum number of dimensions required to identify whether or not a household is multidimensionally poor, the MPI has an important advantage of capturing more dimensions of human deprivations and includes both the level of human deprivation and a measure of the intensity of poverty using micro survey data. Using survey data from 13 Arab countries with a combined population of 221.2 million in 2007, the OPHI estimated that 41.2 million people, representing 18.64 per cent of the combined population were living in multidimensional poverty in 2007, with an average intensity of 50.9. It is shown that the average intensity (A) has a strong positive correlation to headcount (H) in the Arab region. Somalia has the highest MPI value, 81 per cent of the population, with deprivation concentrated in indicators of living standard. The United Arab Emirates, the only Gulf Cooperation Council (GCC) state considered here, has the lowest MPI value, 0.57, with deprivation concentrated in education. Arab Mashreq countries have highest deprivation in both education and health, while Arab Maghreb countries have low deprivation in health and education but also in standard of living compared to both Arab Least Developed Countries (LDCs) and Arab Mashreq countries

The market for salmon futures: an empirical analysis of fish pool using the Schwartz multifactor model

Using the popular Schwartz 97 two-factor approach, we study future contracts written on fresh farmed salmon, which have been actively traded at the Fish Pool Market in Norway since 2006. This approach features a stochastic convenience yield for the salmon spot price. We connect this approach with the classical literature on fish-farming and aquaculture using first principles, starting by modeling the aggregate salmon farming production process and modeling the demand using a Cobb-Douglas utility function for a representative consumer. The model is estimated by means of Kalman filtering, using a rich data set of contracts with different maturities traded at Fish Pool between 12/06/2006 and 22/03/2012. The results are then discussed in the context of other commodity markets, specifically live cattle which acts as a substitute

Estimation of secondary soil properties by fusion of laboratory and on-line measured vis-NIR spectra

Visible and near infrared (vis-NIR) diffuse reflectance spectroscopy has made invaluable contributions to the accurate estimation of soil properties having direct and indirect spectral responses in NIR spectroscopy with measurements made in laboratory, in situ or using on-line (while the sensor is moving) platforms. Measurement accuracies vary with measurement type, for example, accuracy is higher for laboratory than on-line modes. On-line measurement accuracy deteriorates further for secondary (having indirect spectral response) soil properties. Therefore, the aim of this study is to improve on-line measurement accuracy of secondary properties by fusion of laboratory and on-line scanned spectra. Six arable fields were scanned using an on-line sensing platform coupled with a vis-NIR spectrophotometer (CompactSpec by Tec5 Technology for spectroscopy, Germany), with a spectral range of 305-1700 nm. A total of 138 soil samples were collected and used to develop five calibration models: (i) standard, using 100 laboratory scanned samples; (ii) hybrid-1, using 75 laboratory and 25 on-line samples; (iii) hybrid-2, using 50 laboratory and 50 on-line samples; (iv) hybrid-3, using 25 laboratory and 75 on-line samples, and (v) real-time using 100 on-line samples. Partial least squares regression (PLSR) models were developed for soil pH, available potassium (K), magnesium (Mg), calcium (Ca), and sodium (Na) and quality of models were validated using an independent prediction dataset (38 samples). Validation results showed that the standard models with laboratory scanned spectra provided poor to moderate accuracy for on-line prediction, and the hybrid-3 and real-time models provided the best prediction results, although hybrid-2 model with 50% on-line spectra provided equally good results for all properties except for pH and Na. These results suggest that either the real-time model with exclusively on-line spectra or the hybrid model with fusion up to 50% (except for pH and Na) and 75% on-line scanned spectra allows significant improvement of on-line prediction accuracy for secondary soil properties using vis-NIR spectroscopy

Phonetic inventory for an Arabic speech corpus

Corpus design for speech synthesis is a well-researched topic in languages such as English compared to Modern Standard Arabic, and there is a tendency to focus on methods to automatically generate the orthographic transcript to be recorded (usually greedy methods). In this work, a study of Modern Standard Arabic (MSA) phonetics and phonology is conducted in order to create criteria for a greedy meth-od to create a speech corpus transcript for recording. The size of the dataset is reduced a number of times using these optimisation methods with different parameters to yield a much smaller dataset with identical phonetic coverage than before the reduction, and this output transcript is chosen for recording. This is part of a larger work to create a completely annotated and segmented speech corpus for MSA

Blended E85-diesel fuel droplet heating and evaporation

The multidimensional quasi-discrete (MDQD) model is applied to the analysis of heating and evaporation of mixtures of E85 (85 vol % ethanol and 15 vol % gasoline) with diesel fuel, commonly known as “E85–diesel” blends, using the universal quasi-chemical functional group activity coefficients model for the calculation of vapor pressure. The contribution of 119 components of E85–diesel fuel blends is taken into account, but replaced with smaller number of components/quasi-components, under conditions representative of diesel engines. Our results show that high fractions of E85–diesel fuel blends have a significant impact on the evolutions of droplet radii and surface temperatures. For instance, droplet lifetime and surface temperature for a blend of 50 vol % E85 and 50 vol % diesel are 23.2% and up to 3.4% less than those of pure diesel fuel, respectively. The application of the MDQD model has improved the computational efficiency significantly with minimal sacrifice to accuracy. This approach leads to a saving of up to 86.4% of CPU time when reducing the 119 components to 16 components/quasi-components without a sacrifice to the main features of the model