Enhancing financial knowledge and risk literacy through edutainment:CONSOB’s experience

2021 ◽  
pp. 135-148
Author(s):  
Nadia Linciano
Keyword(s):  
Financial Knowledge ◽  
Risk Literacy

Financial Knowledge and 401(K) Investment Performance

2014 ◽  
Author(s):  
Robert L. Clark ◽  
Annamaria Lusardi ◽  
Olivia S. Mitchell
Keyword(s):  
Financial Knowledge ◽  
Investment Performance

scholarly journals On Present Value Evaluation under the Impact of Behavioural Factors Using Oriented Fuzzy Numbers

Symmetry ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 468
Author(s):  
Krzysztof Piasecki ◽  
Anna Łyczkowska-Hanćkowiak
Keyword(s):  
Fuzzy Numbers ◽  
Asset Price ◽  
Financial Knowledge ◽  
Present Value ◽  
Market Knowledge ◽  
Value Evaluation ◽  
Starting Point ◽  
Behavioural Factors ◽  
Objective Financial Knowledge ◽  
The Impact

In general, the present value (PV) concept is ambiguous. Therefore, behavioural factors may influence on the PV evaluation. The main aim of our paper is to propose some method of soft computing PV evaluated under the impact of behavioural factors. The starting point for our discussion is the notion of the Behavioural PV (BPV) defined as an imprecisely real-valued function of distinguished variables which can be evaluated using objective financial knowledge or subjective behavioural premises. In our paper, a BPV is supplemented with a forecast of the asset price closest to changes. Such BPV is called the oriented BPV (O-BPV). We propose to evaluate an O-BPV by oriented fuzzy numbers which are more useful for portfolio analysis than fuzzy numbers. This fact determines the significance of the research described in this article. O-BPV may be applied as input signal for systems supporting invest-making. We consider here six cases of O-BPV: overvalued asset with the prediction of a rise in its price, overvalued asset with the prediction of a fall in its price, undervalued asset with the prediction of a rise in its price, undervalued asset with the prediction of a fall in its price, fully valued asset with the prediction of a rise in its rice and fully valued asset with the prediction of a fall in its rice. All our considerations are illustrated by numerical examples. Presented examples show the way in which we transform superposition of objective market knowledge and subjective investment opinion into simple return rate.

scholarly journals Predicting Fraud Victimization Using Classical Machine Learning

Entropy ◽  
2021 ◽  
Vol 23 (3) ◽  
pp. 300
Author(s):  
Mark Lokanan ◽  
Susan Liu
Keyword(s):  
Machine Learning ◽  
Financial Literacy ◽  
Learning Algorithm ◽  
Demographic Characteristics ◽  
Financial Knowledge ◽  
The Past ◽  
Machine Learning Model ◽  
Long Time ◽  
Regulatory Organization ◽  
Investment Fraud

Protecting financial consumers from investment fraud has been a recurring problem in Canada. The purpose of this paper is to predict the demographic characteristics of investors who are likely to be victims of investment fraud. Data for this paper came from the Investment Industry Regulatory Organization of Canada’s (IIROC) database between January of 2009 and December of 2019. In total, 4575 investors were coded as victims of investment fraud. The study employed a machine-learning algorithm to predict the probability of fraud victimization. The machine learning model deployed in this paper predicted the typical demographic profile of fraud victims as investors who classify as female, have poor financial knowledge, know the advisor from the past, and are retired. Investors who are characterized as having limited financial literacy but a long-time relationship with their advisor have reduced probabilities of being victimized. However, male investors with low or moderate-level investment knowledge were more likely to be preyed upon by their investment advisors. While not statistically significant, older adults, in general, are at greater risk of being victimized. The findings from this paper can be used by Canadian self-regulatory organizations and securities commissions to inform their investors’ protection mandates.

Examining the financial knowledge of immigrants in Canada: a new dimension of economic inequality

2021 ◽  
pp. 1-18
Author(s):  
Mohammad Nuruzzaman Khan ◽  
Ilyan Ferrer ◽  
Yeonjung Lee ◽  
David W. Rothwell
Keyword(s):  
Economic Inequality ◽  
Financial Knowledge

scholarly journals Improving hand hygiene in hospitals: comparing the effect of a nudge and a boost on protocol compliance

2021 ◽  
pp. 1-23
Author(s):  
Henrico van Roekel ◽  
Joanne Reinhard ◽  
Stephan Grimmelikhuijsen
Keyword(s):  
Hand Hygiene ◽  
Behavioral Interventions ◽  
Hand Hygiene Compliance ◽  
Hospital Nurses ◽  
Improve Hand Hygiene ◽  
Policy Practice ◽  
Effective Interventions ◽  
Risk Literacy ◽  
Hygiene Compliance ◽  
Hospital Wards

Abstract Nudging has become a well-known policy practice. Recently, ‘boosting’ has been suggested as an alternative to nudging. In contrast to nudges, boosts aim to empower individuals to exert their own agency to make decisions. This article is one of the first to compare a nudging and a boosting intervention, and it does so in a critical field setting: hand hygiene compliance of hospital nurses. During a 4-week quasi-experiment, we tested the effect of a reframing nudge and a risk literacy boost on hand hygiene compliance in three hospital wards. The results show that nudging and boosting were both effective interventions to improve hand hygiene compliance. A tentative finding is that, while the nudge had a stronger immediate effect, the boost effect remained stable for a week, even after the removal of the intervention. We conclude that, besides nudging, researchers and policymakers may consider boosting when they seek to implement or test behavioral interventions in domains such as healthcare.

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