Analysing the impact of online news sentiment on individualsʼ sequential trading decisions

He, He, Ma, Tiejun, Sung, Ming-Chien and Johnson, Johnnie E.V. (2021) Analysing the impact of online news sentiment on individualsʼ sequential trading decisions. 22nd Conference of the International Federation of Operational Research Societies, , Seoul, Korea, Democratic People's Republic of. 23 - 27 Aug 2021. (In Press)

Abstract

Several empirical studies have reported that the consequences of prior actions can affect subsequent risky decisions. However, little work has investigated how the news environment in which prior actions were taken alters the impact of prior consequences. In this study, we examine to what extent the effects of individual traders’ prior gains on their subsequent trade size are contingent on different news sentiment environments in which these gains were secured. The results are derived from an individual-level trading dataset containing details of 285,725 trades of 4,857 traders between 2004 and 2013, complemented by a news archive that contains over 20 million news items. We find that individuals increase trade size following prior gains, but the magnitude of the increase depends on the type of the news sentiment environment - amplified/reduced by the news sentiment that was consistent/inconsistent with the prior decisions that generated gains. We suggest the news environment affects individual sequential risky decisions through its effects on emotions – prior gains lead an individual to have positive emotions, and the emotions are amplified/reduced when the individual receives positive/negative feedback from the news sentiment that is consistent/inconsistent with the gain-generating trading decisions. This study contributes to the literature on the roles of contexts and emotions in decision-theory models.

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Contributors

Author: He He

Author: Ming-Chien Sung

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