Construction of a prediction model for individual investors' psychology and behaviour based on cognitive neuroscience

Shiyong Liu and Sang Fu

International Journal of Industrial and Systems Engineering, 2022, vol. 40, issue 3, 292-308

Abstract: Traditional forecasting models cannot extract the trend information of retail investors' multi-scale psychological and behavioural data, and the predictions are not accurate. To solve this problem, a Markov-based individual investor psychology and behaviour prediction model is proposed. Using the wavelet multi-scale analysis method, the multi-scale data of individual investor's psychology and behaviour are extracted. A long-term-memory analysis is performed on multi-scale data of individual investors' psychology and behaviour using the correlation analysis method, and the trend information is extracted. On this basis, a Markov prediction model is established, and a modified investment preference model is introduced to improve the accuracy of the prediction. Using the individual similarity degree, the nearest neighbour set of the target individual is established, and a multi-order predictive Markov fusion model for multiple individuals is formed to achieve accurate prediction. The experimental results show that the proposed model achieves better nonlinear fitting and higher prediction accuracy.

Keywords: individual investors; psychology and behaviour; prediction model; Markov. (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:ids:ijisen:v:40:y:2022:i:3:p:292-308

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