Document Type

Theses, Masters

Rights

This item is available under a Creative Commons License for non-commercial use only

Disciplines

Computer Sciences

Publication Details

Successfully submitted in partial fulfilment of the requirements of Dublin Institute of Technology for the degree of M.Sc. in Computing (Data Analytics), March, 2015.

Abstract

Recent studies have shown that, through the quantification of Wikipedia Usage Patterns as a result of information gathering, stock market moves can be predicted (Moat et al 2013). There was also research performed to determine the predictive nature of Wikipedia Data to predict movie box office success (Mestyan et al. 2013). The goal of any investor, in order to maximize the return of their investments, is to have an edge over other participants in the markets. Several tools and techniques have been used over the years to fulfil this, some proving to generate a consistent stream of income (Gillen 2012). With the improvement of technology and communication links, what was once considered a closed door, gentleman’s club operation, can now be tapped into by anybody who has access to a PC and communications link. It is said that approximately only 20% of investors are consistently successful in their investments (Terzo 2013). In order be successful, there needs to be a strategy in place that is strictly adhered to. The objective of these trading systems is to minimize, or ideally cut out, the human emotion factor and naturally, as a consequence, allow the strategy operate at its optimum. An example of this is through the use of technical analysis indicator which, when used correctly, can net the investor considerable, consistent returns. (Gillen 2012). Technical indicators, such as Coppock, are widely used in the field of stock market investment to provide traders and investors with an insight into which direction a stock or index is moving so as to facilitate the optimum time to enter or exit the market. This project investigates whether Wiki Article Traffic Statistics can be used to verify trading signals given by the Coppock technical indicator through the use of a suitable correlation technique.

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