文章基本信息

标题：Combinação da projeção da volatilidade percebida por redes neurais e HAR
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作者：Alcides Araújo ; Alessandra Montini ; Joelson Sampaio 等
期刊名称：Brazilian Review of Finance
印刷版ISSN：1984-5146
出版年度：2019
卷号：17
期号：1
页码：51-79
DOI：10.12660/rbfin.v17n1.2019.71580
出版社：Link to the Brazilian Society of Finance
摘要：This paper examines a combination of HAR and neural networks methods to better predict perceived volatility and, consequently, to more efficiently manage risk. To carry out the projections, combinations and tests, the series of perceived volatility of Ibovespa was collected between 2000 and 2018, producing a sample of 4,530 observations. The main results show that the combination of both models better predict perceived volatility, which can be interpreted as an efficiency gain for risk management. In addition, this article also evaluates the performance of the models, considering the profitability of trading with options. For the case of profitability, combinations of linear and nonlinear models present better performance.
关键词：Dados em Alta Frequência; Volatilidade Percebida; Combinação de Projeções.