Identification of Critical Factors in Large Crisis Decision Making Processes using Computational Tools: The case of ATHENA

Crises are a constant element of modern day life. Earthquakes, floods, terrorist acts are major examples of crises that occur in different areas under different frequencies. Crisis situations are always dynamic and they are characterised by unpredictable consequences that societies cannot always handle. The dynamics of crisis situations are such that societies have to re-evaluate and re-design their policies. This paper aims to present a Social Media-based system that coordinates the responses of the authorities in a large crisis. The paper performs extensive review of literature in order to identify decision making approaches in crisis situations and the different factors that affect these approaches. It also presents the ATHENA Crisis Management system which is based on a platform that makes combined use of data mining algorithms for the purpose of analysing large amounts of data received through the Social Media during and after a large crisis. A number of conclusions are drawn on the identification of different types of factors that impact large crisis decision making

Investor Sentiment and Stock Returns

In this chapter, the authors investigate the relationship between investor sentiment and stock returns in an out of sample market, namely Borsa Istanbul. The authors use the Consumer Confidence Index as an investor sentiment proxy, while utilizing BIST Second National Index as a measure of small capitalized stock returns. The sample period spans from January 2004 to May 2014. By using monthly data, the authors employ cointegration test and Error-Correction based Granger causality models. The authors' findings suggest that there is a long-term relationship between investor sentiment and stock returns in Borsa Istanbul. Moreover, a unidirectional causal relationship from investor sentiment to stock returns is also found. © 2015, IGI Global. All rights reserved