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  • 标题:Quantitative Portfolio Optimization Techniques Applied to the Brazilian Stock Market
  • 本地全文:下载
  • 作者:André Alves Portela Santos ; Cristina Tessari
  • 期刊名称:Brazilian Review of Finance
  • 印刷版ISSN:1984-5146
  • 出版年度:2012
  • 卷号:10
  • 期号:3
  • 页码:369-393
  • 语种:Portuguese
  • 出版社:Link to the Brazilian Society of Finance
  • 摘要:In this paper we assess the out-of-sample performance of two alternative quantitative portfolio optimization techniques - mean-variance and minimum variance optimization – and compare their performance with respect to a naive 1/N (or equally-weighted) portfolio and also to the market portfolio given by the Ibovespa. We focus on short selling-constrained portfolios and consider alternative estimators for the covariance matrices: sample covariance matrix, RiskMetrics, and three covariance estimators proposed by Ledoit and Wolf (2003), Ledoit and Wolf (2004a) and Ledoit and Wolf (2004b). Taking into account alternative portfolio re-balancing frequencies, we compute out-of-sample performance statistics which indicate that the quantitative approaches delivered improved results in terms of lower portfolio volatility and better risk-adjusted returns. Moreover, the use of more sophisticated estimators for the covariance matrix generated optimal portfolios with lower turnover over time.
  • 其他摘要:In this paper we assess the out-of-sample performance of two alternative quantitative portfolio optimization techniques - mean-variance and minimum variance optimization – and compare their performance with respect to a naive 1/N (or equally-weighted) portfolio and also to the market portfolio given by the Ibovespa. We focus on short selling-constrained portfolios and consider alternative estimators for the covariance matrices: sample covariance matrix, RiskMetrics, and three covariance estimators proposed by Ledoit and Wolf (2003), Ledoit and Wolf (2004a) and Ledoit and Wolf (2004b). Taking into account alternative portfolio re-balancing frequencies, we compute out-of-sample performance statistics which indicate that the quantitative approaches delivered improved results in terms of lower portfolio volatility and better risk-adjusted returns. Moreover, the use of more sophisticated estimators for the covariance matrix generated optimal portfolios with lower turnover over time.
  • 关键词:Optimization;estimation error;volatility;Otimização;erro de estimação;volatilidade
  • 其他关键词:Economics; Business; Statistics; Mathematics; Econometrics;;Optimization; estimation error; volatility;G11; G32.
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