The University of Buckingham Press Journals
Not a member yet
1038 research outputs found
Sort by
EVALUATION OF THE RULE OF LAW AS A PRE-REQISITE TO THE RIGHT TO DEVELOPMENT IN AFRICA
Get PDFAfrica faces myriads of challenges one of which is the need for development; as a result, development is a critical issue in Africa. The apparent disparity and inequity of the global economic system in the aspect of international economic development, conspicuous particularly on the Africa continent has dominated academic discourses since the era of the decolonization of the undeveloped countries. One of the direct consequences of this was the evolution of right-based approach to development agenda which have implications for democracy and the rule of law; two elements that have suffered serious setbacks in almost all African countries. This paper examines the extent to which the effective enforcement of the rule of law in African countries can aid the human rights based approach to development in order to deliver meaningful improvements to the African development crisis. It starts by highlighting the evolution of the rights based approach to development agenda with a view to clarifying the meanings of the “right to development”. It further examines the import of the doctrine of rule of law, its relationship to the rights-based approach to development agenda and the theoretical underpinnings of both concepts. The paper continues to assess the position of the rule of law in African countries now, and its implications for the realization of the Right to Development (RTD), domestically (in each African country), regionally (and possibly sub-regionally).It is the argument of this paper that although, the African human rights-system, particularly the African Charter of Human and People’s Rights was the first enforceable document to contain the right to development, thereby making the African continent to be the first in conceiving it, yet one of the major reasons why development has eluded African over a considerable period of time until now is abysmal failure of the Rule of Law
Ethno-Linguistic Vitality of Koch
Get PDFThe Koch language is spoken in the states of Assam (Goalpara, Nagaon, Dhubri, Kokrajhar, Chirang, Bongaigao, Barpeta, Baksa, Udalguri, Karbi Anglong, Golaghat districts), Meghalaya (West Garo Hills, South-West Garo Hills, South Garo Hills and East Khasi Hills Districts). Koches are found in West Bengal (Northern part) and also in Bangladesh. The speaker strength of Koch in India according to 2011 census is 36,434. Koch community is the bilingual speakers of Assamese, Bengali, Garo, Hindi, and English. Contact situations of Koch with Assamese and Bengali languages have made the language vulnerable to language shift. The UNESCO report mentions Koch as ‘Definitely Endangered’1. Koch has gained the status of a scheduled tribe in Meghalaya in 1987. Kondakov (2013) traces six distinct dialects of Koch, viz., Wanang, Koch-Rabha (Kocha), Harigaya, Margan, Chapra and Tintekiya. He (2013:24) states, “The relationship between the six Koch speech varieties are rather complex. They represent a dialect chain that stretches out from Koch-Rabha in the north to Tintekiya Koch in the south.” This is diagrammatically represented as - Koch-Rabha(Kocha)→Wanang→Harigaya→Margan, Chapra→Tintekiya where the adjacent dialects exhibit more lexical similarity than those at the ends. Nine ethno-linguistic varieties of Koch (also mentioned in Kondakov, 2013:5) have been reported during field investigation. These are Harigaya, Wanang, Tintekiya, Margan, Chapra, Satpariya, Sankar, Banai and Koch Mandai
Comparing trading behaviour and profit composition in prediction markets
No full textPrediction markets have established itself as forecasting technique, especially within the IT industry. While the majority of existing studies focuses either on the output of such markets or its design settings, the traders who actually produce the forecasts got only little attention yet. Within this work, we develop a classification scheme for traders of a prediction market that is grounded on both, financial and prediction market literature. Over a period of three years, 127 prediction markets have been observed and its 4.329 traders are separated into seven subgroups (beginners, noise traders, average traders, experts, donkey traders, market makers and superior traders), based on their knowledge, experience and selectivity. We find empirical evidence for the existence of these subgroups and thus for the heterogeneity among the traders. For each of these subgroups, we analyze the trading behaviour and the profit composition
The Fédération Equestre Internationale Speaks for the Horse Who Has No Voice and the Court of Arbitration for Sport Listened: Equine Welfare and Anti-Doping in Equestrianism
Get PDFThe strict liability standard employed by the Fédération Equestre Internationale (FEI) in equine doping cases has been a source of contention among academics, riders and trainers. The FEI Disciplinary Tribunal and the Court of Arbitration for Sport (CAS) have consistently upheld the standard and no alternative has been considered. At the core of the application of the strict liability standard has been the protection of the equine athlete. With the dual aims of the protection of equine athletes and equality between competitors, the FEI imposes a provisional equine suspension when a horse’s sample records an adverse analytical finding. The standard of strict liability and the imposition of provisional suspensions together put the welfare of the horse to the fore. While the intentions of the FEI have been based on this noble premise, ambiguities and inconsistencies have undermined the effectiveness of the Equine Anti-Doping and Controlled Medication Regulations (EADCMRs)
THE CHANGING SECONDARY CURRICULUM IN ENGLAND
Get PDFThe writer engages with the debate around the balancing act in the development of curricula between knowledge and skills. There is an advocacy of the idea that content should be given greater prominence.The recent developments in the English curriculum are used to illustrate the dichotomy between skills and knowledge. The author argues that this is in fact a false dichotomy and that higher order skills become undermined if they are not developed alongside a significant knowledge base. Writers such as Bloom and Hirsch are deployed to substantiate the presented arguments.A cogent critique is offered to support subject based, knowledge dominant curricula. Evidence is marshalled to imply that many recent moves to develop vocational curricula by emphasising skills has diluted their value and function as a progressional root to further education and employment
The contested significance of financial expertise in predicting short- and long-term risk and return on the stock market
No full textThis study investigates whether the influence of financial expertise on stock investors’ ability to predict risk and return is contingent on the length of the forecast horizon. In a quasi-experimental design, stock market professionals (N1=63, N2=36), private shareholders (N1=155, N2=172) and students (N1=124, N2=90) twice provided their short- (3-month) and long-term (2-year) risk and return predictions on stock indices. The results show that in general, experts did not outperform students or private shareholders in their return predictions. However, the level of financial expertise positively influenced the accuracy of risk predictions. An interaction effect between financial expertise and the length of the forecast horizon suggests that more knowledgeable and experienced investors performed better in the long term compared to the short term than inexperienced investors di
Modelling and forecasting unbiased extreme value volatility estimator: A study based on exchange rates with economic significance analysis
No full textThis study proposes the use of an alternate approach to generate more accurate forecasts of an unbiased AddRS estimator. The study also devises and implements trading strategies based on the volatility forecasts to highlight its economic significance. The findings indicate that the proposed framework provides more accurate forecasts of daily volatility in comparison to returns based and range based alternative volatility models. The findings based on economic significance analysis indicate that the risk averse investor can earn substantial gain by using the volatility forecasts of the proposed framework than by using the volatility forecasts of the alternative models
Forecasting Cryptocurrency Prices Using ARIMA and Neural Network: A Comparative Study
No full textThe prices of cryptocurrencies are very volatile and forecasting them is a challenging task for the researchers across the world. The present study examines the accuracy of forecasted returns of the two most popular cryptocurrencies (Bitcoin and Ethereum) for the sample period spanning from October 1, 2013, to November 30, 2018. Auto-regressive integrated moving average (ARIMA) and Neural Network models have been used to forecast the returns of the cryptocurrencies. The forecasting results for different time-horizons indicate that for a shorter time-horizon, ARIMA model is better for forecasting the returns of cryptocurrencies, whereas, for a longer time-horizon, Neural Network model is better for forecasting the returns of cryptocurrencies. These results have implications for traders, investors, regulators, policymakers and academia
The SEC vs. the Dow Jones: A Profitable Betting Strategy in NCAA Football
No full textThis article tests the efficient market hypothesis (EMH) and the profitability of a simple betting strategy in National Collegiate Athletic Association (NCAA) college football. We examine all games that have a point spread, from September 2003 through January 2015, for inter-conference matches involving a Power Five/Automatic Qualifying (P5/AQ) team against a Football Championship Subdivision (FCS) opponent. We further investigate one conference using these matches from 2016 through 2018 seasons. The betting strategy evidence suggests it is nonrandom and profitable to bet against the Southeastern Conference (SEC), despite its perceived status as the nation’s top conference
The Comparison of GARCH and ANN Model for Forecasting Volatility: Evidence based on Indian Stock Markets: Predicting Volatility using GARCH and ANN Models.
No full textIn this paper, we study the performance of the Artificial Neural Networks (ANNs) and GARCH modelsto predict the volatility of the Indian stock market indices namely, NIFTY 50, NIFTY Bank and NIFTYFMCG. We have used the GARCH (1,1) and Recurrent Neural Network, a type of neural network whichis widely used for predicting time series data. The purpose of the study is to investigate if the ArtificialNeural Networks perform better than the traditional GARCH (1,1) model. An out of sample testingmethodology is applied to the most recent 20 percent of the observations for all the three indices. Wehave used Root Means Squared Error (RMSE) and Mean Absolute Error (MAE) as metrics to evaluatethe volatility predicting performances of the models. The results show no clear evidence of ANN modelperforming better than GARCH model for any of the three indices. ANNs may prove to be betterindicators in periods with low volatility while its performance deteriorated in periods with highvolatility