Movie Popularity Classification based on Inherent Movie Attributes using C4.5,PART and Correlation Coefficient

Abundance of movie data across the internet makes it an obvious candidate for machine learning and knowledge discovery. But most researches are directed towards bi-polar classification of movie or generation of a movie recommendation system based on reviews given by viewers on various internet sites. Classification of movie popularity based solely on attributes of a movie i.e. actor, actress, director rating, language, country and budget etc. has been less highlighted due to large number of attributes that are associated with each movie and their differences in dimensions. In this paper, we propose classification scheme of pre-release movie popularity based on inherent attributes using C4.5 and PART classifier algorithm and define the relation between attributes of post release movies using correlation coefficient.Comment: 6 page

Ensemble Committees for Stock Return Classification and Prediction

This paper considers a portfolio trading strategy formulated by algorithms in the field of machine learning. The profitability of the strategy is measured by the algorithm's capability to consistently and accurately identify stock indices with positive or negative returns, and to generate a preferred portfolio allocation on the basis of a learned model. Stocks are characterized by time series data sets consisting of technical variables that reflect market conditions in a previous time interval, which are utilized produce binary classification decisions in subsequent intervals. The learned model is constructed as a committee of random forest classifiers, a non-linear support vector machine classifier, a relevance vector machine classifier, and a constituent ensemble of k-nearest neighbors classifiers. The Global Industry Classification Standard (GICS) is used to explore the ensemble model's efficacy within the context of various fields of investment including Energy, Materials, Financials, and Information Technology. Data from 2006 to 2012, inclusive, are considered, which are chosen for providing a range of market circumstances for evaluating the model. The model is observed to achieve an accuracy of approximately 70% when predicting stock price returns three months in advance.Comment: 15 pages, 4 figures, Neukom Institute Computational Undergraduate Research prize - second plac

Corn or Current? The Agro-Industrial Water Conflict

A new report shows where conflicts between industry and agriculture for limited water supplies could be most severe. MSCI ESG Research used data from WRI's Aqueduct Water Risk Atlas to evaluate agro-industrial water conflict for 110 publicly traded, water-intensive companies operating in highly irrigated and water-stressed U.S. counties.The report found that competition for water in stressed areas between power generators and other industrial users and agricultural operations could create stranded assets, reduce overall productivity, create community conflicts, and threaten food and water security

Should the advanced measurement approach be replaced with the standardized measurement approach for operational risk?

Recently, Basel Committee for Banking Supervision proposed to replace all approaches, including Advanced Measurement Approach (AMA), for operational risk capital with a simple formula referred to as the Standardised Measurement Approach (SMA). This paper discusses and studies the weaknesses and pitfalls of SMA such as instability, risk insensitivity, super-additivity and the implicit relationship between SMA capital model and systemic risk in the banking sector. We also discuss the issues with closely related operational risk Capital-at-Risk (OpCar) Basel Committee proposed model which is the precursor to the SMA. In conclusion, we advocate to maintain the AMA internal model framework and suggest as an alternative a number of standardization recommendations that could be considered to unify internal modelling of operational risk. The findings and views presented in this paper have been discussed with and supported by many OpRisk practitioners and academics in Australia, Europe, UK and USA, and recently at OpRisk Europe 2016 conference in London

Model of Enterpreneurship and Social-cultural and Market Orientation of Small Business Owners in Poland

In the development of SMEs in Poland crucial meaning is legislation, steadily adapted to EU regulations, especially to the European Charter for Small Enterprises. Research conducted in Poland by many authors provide data for doing so, to confirm the hypothesis that among small businesses a vital role in shaping their work situation did not continue to play the market mechanisms and orientations, but mainly socio-cultural factors.W rozwoju MŚP w Polsce podstawowe znaczenie mają również uregulowania prawne, systematycznie dostosowywane do regulacji unijnych, zwłaszcza zaś do Europejskiej Karty Małych Przedsiębiorstw. Badania prowadzone w Polsce przez wielu autorów dostarczają danych ku temu, by potwierdzić tezę, że wśród drobnych przedsiębiorców decydującą rolę w kształtowaniu ich sytuacji pracy odgrywają nadal nie mechanizmy i orientacje rynkowe, ale przede wszystkim czynniki społeczno-kulturowe

Analyst Underreaction to Past Information About Earnings: reporting, processing or plain old misspecification bias?

We revisit the debate concerning the interpretation given to prior year’s earnings changes in predicting future earnings as discussed by Abarbanell & Bernard (1992), Francis & Philbrick (1993) and Easterwood and Nutt (1999). We advance a new specification of this relationship which distinguishes between earnings reversion and momentum. On a large UK dataset, we find there is substantial underreaction, particularly in situations of earnings momentum, approximately six times as large as that identified by Abarbanell & Bernard. This suggests that analysts behaviour is still a candidate to explain post earnings announcement drift. We also show that our model performs well relative to a specification recently proposed by Easterwood and Nutt (1999)