An empirical study on the various stock market prediction methods

Investment in the stock market is one of the much-admired investment actions. However, prediction of the stock market has remained a hard task because of the non-linearity exhibited. The non-linearity is due to multiple affecting factors such as global economy, political situations, sector performance, economic numbers, foreign institution investment, domestic institution investment, and so on. A proper set of such representative factors must be analyzed to make an efficient prediction model. Marginal improvement of prediction accuracy can be gainful for investors. This review provides a detailed analysis of research papers presenting stock market prediction techniques. These techniques are assessed in the time series analysis and sentiment analysis section. A detailed discussion on research gaps and issues is presented. The reviewed articles are analyzed based on the use of prediction techniques, optimization algorithms, feature selection methods, datasets, toolset, evaluation matrices, and input parameters. The techniques are further investigated to analyze relations of prediction methods with feature selection algorithm, datasets, feature selection methods, and input parameters. In addition, major problems raised in the present techniques are also discussed. This survey will provide researchers with deeper insight into various aspects of current stock market prediction methods

Tax evasion, information reporting, and the regressive bias hypothesis

A robust prediction from the tax evasion literature is that optimal auditing induces a regressive bias in e¤ective tax rates compared to statutory rates. If correct, this will have important distributional consequences. Nevertheless, the regressive bias hypothesis has never been tested empirically. Using a unique data set, we provide evidence in favor of the regressive bias prediction but only when controlling for the tax agency�s use of third-party information in predicting true incomes. In aggregate data, the regressive bias vanishes because of the systematic use of third-party information. These results are obtained both in simple reduced-form regressions and in a data-calibrated state-of-the-art model

Concept design of a fast sail assisted feeder container ship

An environmentally sustainable fast sail-assisted feeder-container ship concept, with a maximum speed of 25 knots, has been developed for the 2020 South East Asian and Caribbean container markets. The use of low-carbon and zero-sulphur fuel (liquefied natural gas) and improvements in operational efficiency (cargo handling and scheduling) mean predicted Green house gas emissions should fall by 42% and 40% in the two selected operational regions. The adoption of a Multi-wing sail system reduces power requirement by up to 6% at the lower ship speed of 15 knots. The predicted daily cost savings are respectively 27% and 33% in South East Asian and the Caribbean regions.Two hull forms with a cargo capacity of 1270TEU utilising different propulsion combinations were initially developed to meet operational requirements. Analysis & tank testing of different hydrodynamic phenomena has enabled identification of efficiency gains for each design. The final propulsion chosen is a contra-rotating podded drive arrangement. Wind tunnel testing improved Multi-wing sail performance by investigating wing spacing, wing stagger and sail-container interactions. The associated lift coefficient was increased by 32%. Whilst savings in sail-assisted power requirement are lower than initially predicted an unexpected identified benefit was motion damping.The fast feeder-container ship is a proposed as a viable future method of container transhipment

Rating Shopping and Rating Inflation: Empirical Evidence from Israel

The collapse of structured bond ratings during the 2007-2008 financial crisis called attention to the possibility of rating inflation due to lowered rating standards and rating shopping. Nevertheless, little empirical evidence has been offered for this prospect. The Israeli corporate credit rating market serves as solid ground for investigating this matter. In this study, we use data on corporate bond ratings assigned by two local rating agencies affiliated with S&P and Moody’s during the period 2004-2009. We show that while one agency (Midroog) systematically assigned higher ratings, the ratings of the other agency (S&P-Maalot) were inflated due to rating shopping. These conclusions are based on several findings: the presence of selection bias in dual ratings, the superior accounting features of firms rated by S&P-Maalot relative to those similarly rated by Midroog, and the greater tendency of single ratings by S&P-Maalot to be downgraded. We confirm the predictions of recent theoretical studies that rating inflation may occur even when the value of the rating agencies derives from their reputation.

Which heuristics can aid financial-decision-making?

© 2015 Elsevier Inc. We evaluate the contribution of Nobel Prize-winner Daniel Kahneman, often in association with his late co-author Amos Tversky, to the development of our understanding of financial decision-making and the evolution of behavioural finance as a school of thought within Finance. Whilst a general evaluation of the work of Kahneman would be a massive task, we constrain ourselves to a more narrow discussion of his vision of financial-decision making compared to a possible alternative advanced by Gerd Gigerenzer along with numerous co-authors. Both Kahneman and Gigerenzer agree on the centrality of heuristics in decision making. However, for Kahneman heuristics often appear as a fall back when the standard von-Neumann-Morgenstern axioms of rational decision-making do not describe investors' choices. In contrast, for Gigerenzer heuristics are simply a more effective way of evaluating choices in the rich and changing decision making environment investors must face. Gigerenzer challenges Kahneman to move beyond substantiating the presence of heuristics towards a more tangible, testable, description of their use and disposal within the ever changing decision-making environment financial agents inhabit. Here we see the emphasis placed by Gigerenzer on how context and cognition interact to form new schemata for fast and frugal reasoning as offering a productive vein of new research. We illustrate how the interaction between cognition and context already characterises much empirical research and it appears the fast and frugal reasoning perspective of Gigerenzer can provide a framework to enhance our understanding of how financial decisions are made