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On Robo assessment of risk profiles
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Orientador(es)
Resumo(s)
Nos tempos que correm, o mundo tecnológico tem crescido a um ritmo muito acelerado, o que significa que tem de haver uma rápida adaptação, e as empresas sentem a necessidade de se reinventar. As inovações tecnológicas também alcançaram a indústria de serviços de gestão de ativos com os chamados Robo-Advisors. Estas são as plataformas que fornecem aconselhamento financeiro ou gestão automatizada de investimentos. Os Robo-Advisors coletam informações sobre a situação financeira e os objetivos futuros de seus clientes através de questionários, recomendando carteiras baseadas em ETFs, supostamente adequadas ao perfil de risco do investidor. No entanto, os questionários parecem vagos e os robôs não revelam os métodos usados na alocação de ativos. Este estudo visa contribuir para a compreensão da eficácia dessas plataformas. Baseia-se na teoria da utilidade esperada e, para vários níveis de aversão relativa ao risco, propomos carteiras de média-variância ótimas. Em seguida, comparamos as nossas carteiras com as carteiras propostas pela plataforma Riskalyze, para três tipos diferentes de investidores: conservador, moderado e agressivo. Avaliando o seu desempenho in-sample e out-of-sample. Concluímos que, a longo prazo, a metodologia utilizada pelos robo-portfolios, de acordo com o perfil de risco do investidor, pode ser eficaz para investidores que apresentam um maior nível de aversão ao risco, porém para investidores com aversão ao risco relativamente menor os portfólios de média-variância tendem a ter melhor desempenho.
Nowadays, the technological world has been growing at a very fast rate, which means there has to be a quick adaptation and companies feel the need to reinvent themselves. Technological innovations also reached the asset management service industry with the so-called the Robo-Advisors. These are platforms that provide financial advice or automated investment management. Robo-Advisors collect information about their clients' financial situation and future goals through questionnaires, then recommending ETF based portfolios supposed to fit investor's risk profile. However, questionnaires seem to be vague, and robos do not reveal the methods used in asset allocation. This study aims at contributing to the understanding the effectiveness of these platforms. It relies on expected utility theory, and, for various levels of relative risk aversion we propose optimal mean-variance portfolios. We then compare our portfolios with the portfolios proposed by the Riskalyze platform, for three different types of investors: conservative, moderate and aggressive. By evaluating their in-sample and out-of-sample performance. We conclude, that in the long run, the methodology used by robo-portfolios, according to the investor's risk profile, can be effective for investors who have a higher level of risk aversion, however for investors with relatively lower risk aversion the mean-variance portfolios tend to perform better.
Nowadays, the technological world has been growing at a very fast rate, which means there has to be a quick adaptation and companies feel the need to reinvent themselves. Technological innovations also reached the asset management service industry with the so-called the Robo-Advisors. These are platforms that provide financial advice or automated investment management. Robo-Advisors collect information about their clients' financial situation and future goals through questionnaires, then recommending ETF based portfolios supposed to fit investor's risk profile. However, questionnaires seem to be vague, and robos do not reveal the methods used in asset allocation. This study aims at contributing to the understanding the effectiveness of these platforms. It relies on expected utility theory, and, for various levels of relative risk aversion we propose optimal mean-variance portfolios. We then compare our portfolios with the portfolios proposed by the Riskalyze platform, for three different types of investors: conservative, moderate and aggressive. By evaluating their in-sample and out-of-sample performance. We conclude, that in the long run, the methodology used by robo-portfolios, according to the investor's risk profile, can be effective for investors who have a higher level of risk aversion, however for investors with relatively lower risk aversion the mean-variance portfolios tend to perform better.
Descrição
Mestrado em Finanças
Palavras-chave
Robo-Advisors serviços de assessoria financeira perfil de risco teoria da média variância teoria da utilidade esperada aversão relativa ao risco função de tolerância ao risco carteiras ativos sharpe ratio financial advisory services risk profile mean variance theory expected utility theory relative risk aversion risk tolerance function portfolios assets
Contexto Educativo
Citação
Oliveira, Madalena Mendes de Almeida Esteves de (2020). "On Robo assessment of risk profiles". Dissertação de Mestrado. Universidade de Lisboa. Instituto Superior de Economia e Gestão.
Editora
Instituto Superior de Economia e Gestão