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Who Gets to Invest? Exploring the Barriers Limiting Female's Participation in Financial Market Investments

Donjeta Zabeli

Student thesis: Master thesis

Abstract

While Denmark is recognised for its progress on gender equality, a clear gap remains in financial market participation, as women continue to invest significantly less than men. This difference persists despite advances in education, labour market participation, and financial independence. The topic has received growing attention, yet much of the existing research has focused narrowly on psychological traits such as confidence, risk aversion and financial literacy, often without considering the broader social and structural conditions that shape investment behaviour. As a result, important questions remain about how gendered norms, accessibility, and institutional design influence who participates and why. This study investigates what factors contribute to female’s lower participation in financial market investments and how these can be addressed. Based on 21 semi-structured interviews with Danish women aged 23 to 45, the study applies a qualitative design grounded in social constructivism, guided by grounded theory principles, and analysed through the Gioia methodology, while also drawing on additional sources and behavioural theories to support interpretation. The findings identify five interrelated barriers: Cultural Barriers, Psychological Barriers, Knowledge Barriers, Entry Barriers, and Situational Barriers, alongside five motivational drivers that support engagement. The findings suggest that these barriers do not exist in isolation but reinforce one another, and that investment behaviour is shaped through the interaction of individual experiences, social contexts, and institutional structures. In doing so, the study offers a more comprehensive understanding of women’s investment behaviour and provides practical insights for creating more inclusive investment environments.

EducationsMSc in Economics and Business Administration - General Management and Analytics, (Graduate Programme) Final Thesis
LanguageEnglish
Publication date15 May 2025
Number of pages89