A volatilidade idiossincrática melhora a explicação dos retornos precificáveis?

IF 0.8 4区 农林科学 Q3 AGRONOMY Biotechnologie Agronomie Societe et Environnement Pub Date : 2021-04-20 DOI:10.4013/BASE.2021.181.01
Bruno Pereira Conte, P. S. Ceretta
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Abstract

The objective of this paper was to investigate if idiosyncratic volatility could be able to improve the explanation of the returnable prices. For this, the CAPM model of Fama & French was used, and based on works such as Ang et al. (2006) and Leite et al. (2016), the volatility fator was included. The difference of this work is the inclusion of portfolio volatility as well as in the calculation of this one that was obtained using the GJR-GARCH model. The study scope was the Brazilian capital market, between 2007 and 2017. The empirical results showed that the inclusion of volatility improves the explanation of the CAPM model Fama & French, fact evidenced by the sensible increase of adjusted R² of the regressions. In addition, it was noted that volatility, when significant, had an opposite relationship with return. When comparated, idiosyncratic volatility was further explained as explaining returns compared to market volatility, which indicates that the information on the montage of portfolios and their oscillations of individual returns seem to be more relevant than market movement, a result that becomes relevant both for hedging and for the search for maximization of returns by investors.
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特殊波动性是否改善了可定价回报的解释?
本文的目的是研究特殊波动率是否能够改善对可返还价格的解释。为此,使用Fama & French的CAPM模型,并根据Ang等人(2006)和Leite等人(2016)等人的工作,纳入波动因子。这项工作的不同之处在于纳入了投资组合波动率,以及使用GJR-GARCH模型计算的投资组合波动率。研究范围为2007年至2017年的巴西资本市场。实证结果表明,波动性的加入改善了Fama & French CAPM模型的解释性,回归调整后的R²显着增加证明了这一点。此外,有人指出,波动性显著时,与回报呈相反关系。当进行比较时,特质波动率被进一步解释为解释与市场波动率相比的回报,这表明关于投资组合蒙太奇及其个人回报波动的信息似乎比市场运动更相关,这一结果与对冲和投资者寻求回报最大化都相关。
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来源期刊
Biotechnologie Agronomie Societe et Environnement
Biotechnologie Agronomie Societe et Environnement AGRONOMY-ENVIRONMENTAL SCIENCES
CiteScore
1.60
自引率
0.00%
发文量
12
审稿时长
6-12 weeks
期刊介绍: BASE publishes original papers in the fields of life sciences: environmental science and technology, forest and natural space management, agronomical science, and chemistry and bio-industries.
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