Decoding Women’s Mutual Fund Investment Decisions: A Decision Tree Classification Approach

Abstract

This study investigates women’s mutual-fund investment behaviour by mapping the interplay between intrinsic and extrinsic drivers. Survey data from 474 women were analyzed with decision-tree modelling and feature importance metrics, enabling an objective ranking of determinants and a robust classification of investors versus non-investors. Findings confirm that financial knowledge and awareness dominate all other predictors of participation. Nevertheless, investment decisions also reflect a non-linear pattern, linking intrinsic attributes of psychological traits, financial independence and financial stability with extrinsic influences such as financial advisory support and, to a lesser extent, market conditions and cultural norms. The model also reveals that advisory guidance markedly increases uptake among women with modest financial knowledge, while risk-averse women remain disengaged despite favourable market signals. By integrating these factors within a single analytical framework, the study offers practitioners actionable insights for designing targeted advisory strategies, literacy and training programmes, and policy interventions that can expand women’s engagement with mutual funds.