2020
DOI: 10.1016/j.irfa.2020.101590
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Who is unhappy for Brexit? A machine-learning, agent-based study on financial instability

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Cited by 15 publications
(7 citation statements)
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“…The current work could be extended by implementing our methodology into an agent-based simulation model (Gambacorta & Karmakar, 2016;Polyzos et al, 2020) to test whether increased efficiency in CAR estimation affects banks' stability.…”
Section: Discussionmentioning
confidence: 99%
“…The current work could be extended by implementing our methodology into an agent-based simulation model (Gambacorta & Karmakar, 2016;Polyzos et al, 2020) to test whether increased efficiency in CAR estimation affects banks' stability.…”
Section: Discussionmentioning
confidence: 99%
“…In the pessimistic scenario, the EU could face several attempts from its members to withdraw from the Eurozone area, with the rest of the PIIGS countries being the first in line. The pending (at the time) decision for Brexit deepened this risk (Polyzos et al, 2020). Despite claims and reassurances from EU policymakers that the financial condition in the Eurozone was tranquil, stock markets were strongly interconnected with rumors and negative information.…”
Section: Discussionmentioning
confidence: 99%
“…We use ML procedures to build a happiness function, similarly to Polyzos et al (2020). Firstly, we use an eager learning naïve Bayes probabilistic classifier to create three groups of households based on their preferences (financial stability, public goods and neutral).…”
Section: Methodsmentioning
confidence: 99%
“…Similarly, to Polyzos et al (2020), the output variables are the weights w k that have been assigned to financial stability and public goods in the happiness function of each individual household, as follows: where H is the resulting happiness level (as reported individually); wi are the weights assigned to each of the inputs (financial stability and public goods spending); and φ are the remaining components of the happiness functions, which we assume to be uniform for all households. The parameters are estimated using maximum likelihood.…”
Section: Methodsmentioning
confidence: 99%
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