Modelo de precificação condicional com heteroscedasticidade: Avaliação de fundos brasileiros

IF 0.5 4区 管理学 Q4 BUSINESS Rae-Revista De Administracao De Empresas Pub Date : 2019-08-14 DOI:10.1590/S0034-759020190402
Leandro Machado da Costa, Frances Fischberg Blank, Fernando Luiz de Oliveira, Cristian Villalobos
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引用次数: 3

Abstract

Empirical studies have revealed that the conditional Capital Asset Pricing Model (CAPM) has a higher explanatory power than its unconditional version, particularly for the model in state-space form where the beta is estimated using Kalman filter. Most empirical analyses are based on stock portfolios to explain financial anomalies, but only a few studies proposed improving investment fund performance. The main contribution of this study is the assessment of Brazilian investment funds through traditional measures estimated from the CAPM model in state-space form with heteroscedastic and homoscedastic errors com­pared to alternative models, such as the unconditional CAPM and a four-factor model. Using a sample of stock funds from May 2005–April 2015, the results indicate that the conditional CAPM model produces better results than the alternative models, providing better performance evaluation practices for funds in both stock-picking and market-timing ability.
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异方差条件定价模型:巴西基金评估
实证研究表明,条件资本资产定价模型(CAPM)比无条件资本资产定价模型具有更高的解释力,特别是对于状态空间形式的模型,其中使用卡尔曼滤波器估计beta。大多数实证分析是基于股票投资组合来解释金融异常,但只有少数研究提出改善投资基金的业绩。本研究的主要贡献在于,与其他模型(如无条件CAPM和四因素模型)相比,通过状态空间形式CAPM模型估计的具有异方差和均方差误差的传统测度,对巴西投资基金进行了评估。以2005年5月至2015年4月的股票型基金为样本,结果表明,条件CAPM模型比备选模型效果更好,在选股能力和择时能力方面为基金提供了更好的绩效评价实践。
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来源期刊
CiteScore
1.30
自引率
12.50%
发文量
78
审稿时长
32 weeks
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