Integrating psychology and big data for emotionally smarter investment

Research output: Other contribution

Abstract / Description of output

The use of psychological theories to understand and predict financial markets isn't new, but sophisticated techniques are evolving that integrate computational and social intelligence to help engineer-out emotionality from human trades and engineer it in to automated ones. This BBC article describes a current breed of IT companies plying their trade in behavioural finance and the ways in which intelligent systems are helping to augment human decision making, through highlighting cognitive and affective biases, whilst enabling algorithm-driven systems to cope with volatile and atypical market conditions, where speculation based on fuzzy predictors akin to hunches and hope might be more useful. Through co-learning between software and humans, underpinned by big data, a 'social machine for finance' is arguably emerging.* Whether it helps to improve market ethics, as the article speculates, is an open question.
Original languageEnglish
Media of outputOnline
PublisherLinkedIn Publishing
Number of pages1
Publication statusPublished - 18 Mar 2015

Keywords / Materials (for Non-textual outputs)

  • Social Machines
  • Big Data
  • Machine Learning
  • Ethics
  • behavioural finance


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