A methodology for discovering upstream and downstream causal relationships in stock market

Abstract

Causal relationships between events pertaining to stock market have potential to influence the stakeholders of the companies associated with those events. Understanding causal relationships in stock markets help in making intelligent decisions. Traditional prediction approaches cannot estimate the upstream and downstream causal relationships. Therefore, it is inevitable to consider portfolios that exhibit causal relationships. Simple correlation between variables may not reflect causal relationships unless there is an event that is the result of occurrence of another event. Finding upstream and downstream causal relationships is challenging. In the literature it is found that inter-transactional details can help in finding causal relationships. Based on this idea, in this paper, we planneda methodology to mine upstream and downstream causal relationships. An algorithm by name Upstream Downstream-Causal Relationship Mining (UD-CRM) is proposed to achieve this. The framework and underlying algorithm produce specific rules that are used to conclude causal relations. Experiments are made with stock dataset using a prototype application built. The experimental results revealed that the proposed framework is useful and performance better than existing approach.