Gender and Investment Decision-Making
The first female student government president in Ghana’s history was Ashesi alumna Yawa Hansen-Quao ‘07 (pictured sitting). After graduation Yawa founded Leading Ladies’ Network, whose for-profit women’s career coaching arm funds mentorship programs for thousands of women and girls. “I want to provide [the women of Africa] the stepping stones to success, to prepare them to participate at every leadership table,” says Yawa. Research by an Ashesi lecturer on issues of gender bias revealed that the impact of anchoring bias on investment decision-making was evidenced in Ghana, such bias affects the dynamics of investor decision-making concerning mutual funds, and the bias differs amongst genders and levels of financial knowledge.
47%
of Ashesi students are women; 52% of women students receive scholarships. We are committed to gender equality.
She also found that investors were prone to be significantly influenced by the anchoring bias. There was a strong, albeit not significant, association between participants’ susceptibility to anchor in both genders and the level of financial knowledge of participants. Females were observed to be more likely to anchor than their male counterparts.
Also, a higher level of financial knowledge did not help reduce the possibility of anchoring; instead, it increased it. The study adds to the body of knowledge on the influences of behavioural biases in the sub-region to make investors aware of their biases and minimise the impact of these biases on their investment decisions, particularly female entrepreneurs.
Many Ashesi alumni are working to achieve gender equality and empower all women and girls. Regina Honu ‘05 founded Soronko Solutions, a software company focused on producing software solutions to support local SMEs. Through Soronko, Regina supports Tech Needs Girls, a social enterprise she founded to teach girls in underserved communities how to code. Since its inception, Regina has enrolled over 5,000 girls in her program, and created a mentor network spanning 200 women in computer science and engineering.




