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on Financial Literacy and Education |
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Issue of 2018‒03‒26
four papers chosen by |
| By: | Francesco D'Acunto; Nagpurnanand Prabhala; Alberto G. Rossi |
| Abstract: | We study a robo-advising portfolio optimizer that constructs tailored strategies based on in- vestors’ holdings and preferences. Adopters are similar to non-adopters in terms of demographics, but have more assets under management, trade more, and have higher risk-adjusted performance. The robo-advising tool has opposite effects across investors with different levels of diversification before adoption. It increases portfolio diversification and decreases volatility for those that held less than 5 stocks before adoption. These investors’ portfolios perform better after using the tool. At the same time, robo-advising barely affects diversification for investors that held more than 10 stocks before adoption. These investors trade more after adoption with no effect on average performance. For all investors, robo-advising reduces - but does not fully eliminate - pervasive behavioral biases such as the disposition effect, trend chasing, and the rank effect, and increases attention based on online account logins. Our results emphasize the promises and pitfalls of robo-advising tools, which are becoming ubiquitous all over the world. |
| Keywords: | FinTech, portfolio choice, behavioral finance, individual investors, financial literacy, technology adoption |
| JEL: | D14 G11 O33 |
| Date: | 2018 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_6907&r=fle |
| By: | Andrej Cupak (National Bank of Slovakia and LIS: Cross-National Data Center in Luxembourg); Pirmin Fessler (Oesterreichische Nationalbank); Maria Silgoner (Oesterreichische Nationalbank); Elisabeth Ulbrich (Oesterreichische Nationalbank) |
| Abstract: | We examine recently compiled microdata from the OECD/INFE survey covering information on the financial literacy of adult individuals from twelve countries around the globe. We find large differences in financial literacy across countries and decompose them into those explainable by differences in individual characteristics and those that cannot be explained by such differences. We show that individual characteristics matter with regard to differences in average financial literacy, but do not fully explain the observed differences. We further relate the unexplained differences in our microeconometric analysis to institutional differences across countries. We find strong relationships between the differences in financial literacy not explained by individual characteristics and life expectancy, social contribution rate, PISA math scores, internet usage, and to a lesser degree by GDP per capita, the gross enrolment ratio and stock market capitalization. Our results suggest that there is room for harmonization of economic environments across countries regarding decreasing inequality in the population’s financial literacy. |
| Keywords: | financial literacy gaps; inequality; decomposition analysis; counterfactual methods; personal finance; survey data |
| JEL: | D14 D91 I20 |
| URL: | http://d.repec.org/n?u=RePEc:svk:wpaper:1055&r=fle |
| By: | Zhengqing Gui (Department of Economics , The Hong Kong University of Science and Technology); Yangguang Huang (Department of Economics , The Hong Kong University of Science and Technology; Institute of Emerging Market Studies, The Hong Kong University of Science and Technology); Xiaojian Zhao (Chinese University of Hong Kong (Shenzhen) and Hong Kong University of Science and Technology) |
| Abstract: | We study how investors are exploited by fraudulent financial products. These investors purchase financial products that are inconsistent with their risk attitudes, and in turn, their behaviors provide an incentive for firms to commit financial fraud. We then conduct experiments and surveys in Shenzhen, China to measure investors' risk preferences and the effect of an eye-opening financial education program. Participating in our education program significantly reduces investors' tendency to invest in fraudulent products, especially among those who are risk-averse. Therefore, compared to randomly assigning the education program to investors, targeting risk-averse investors will be more effective in fighting financial fraud. |
| Date: | 2018–01 |
| URL: | http://d.repec.org/n?u=RePEc:hku:wpaper:201852&r=fle |
| By: | Corinne C Delechat; Monique Newiak; Rui Xu; Fan Yang; Goksu Aslan |
| Abstract: | Using a broad set of macroeconomic country characteristics to supplement a new and comprehensive micro-level dataset for 140 countries, we identify structural factors, policies, and individual characteristics that are associated with financial inclusion—in general, and for women in particular. We find that structural country characteristics, such as resource-richness and level of development, and policies, such as stronger institutions, and financial development are significantly related to financial inclusion. We find a robust negative relationship between being female and financial inclusion as in previous studies, and our analysis points to legal discrimination, lack of protection from harassment, including at the work place, and more diffuse gender norms as possible explanatory factors. |
| Date: | 2018–03–05 |
| URL: | http://d.repec.org/n?u=RePEc:imf:imfwpa:18/38&r=fle |