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RANDOM EFFECT MODEL FOR THE CAUSES OF RECOMMENDATION - A BAYESIAN APPROACH
Keywords:
Bayesian, heterogeneity, investment consulting, stratification variables, trading.DOI:
https://doi.org/10.17654/0972361722036Abstract
Investment consulting plays a major role in any individual or corporate financial planning. Competent consultants research on technical analysis of different companies and stocks. This study uses the Bayesian statistical principle to apply the random effect model to binary outcomes. Furthermore, there seems to be little or no approach to develop quality metrics for financial advisers’ historic data and their plans offer. The relevance of monitoring stock broker recommendations and finding the predictive factors connected with it is addressed in this study. The main goal is to investigate the impact of variation in profit and loss call types within each cluster for the 2020 dataset acquired from an investment advisory. This study incorporates the essential module of Bayesian approach, construction of priors, suitable inferences using posterior distribution of the parameters. It is observed that the recommendation made for Sell call has higher odds for profit in the outcomes and a source of heterogeneity has been observed across the stratification variables.
Received: February 17, 2022
Revised: March 13, 2022
Accepted: April 1, 2022
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