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Scaling portfolio volatility and calculating risk contributions in the presence of serial cross-correlations

机译:扩大投资组合的波动性并计算风险贡献  存在串行互相关

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摘要

In practice daily volatility of portfolio returns is transformed to longerholding periods by multiplying by the square-root of time which assumes thatreturns are not serially correlated. Under this assumption this procedure ofscaling can also be applied to contributions to volatility of the assets in theportfolio. Close prices are often used to calculate the profit and loss of aportfolio. Trading at exchanges located in distant time zones this can lead tosignificant serial cross-correlations of the closing-time returns of the assetsin the portfolio. These serial correlations cause the square-root-of-time ruleto fail. Moreover volatility contributions in this setting turn out to bemisleading due to non-synchronous correlations. We address this issue andprovide alternative procedures for scaling volatility and calculating riskcontributions for arbitrary holding periods.
机译:实际上,通过乘以时间的平方根(假设收益与收益没有序列相关),将投资组合收益的每日波动率转换为较长的持有期。在此假设下,这种缩放过程也可以应用于资产组合中资产波动的贡献。收盘价通常用于计算投资组合的损益。在位于遥远时区的交易所进行交易,可能导致投资组合中资产的收市时收益出现明显的系列互相关。这些串行相关性导致时间平方根规则失败。此外,在这种情况下,由于非同步相关性,波动性影响令人误解。我们解决了这个问题,并提供了在任意持有期间扩大波动率和计算风险贡献的替代程序。

著录项

  • 作者

    Nikolaus Rab; Richard Warnung;

  • 作者单位
  • 年度 2012
  • 总页数
  • 原文格式 PDF
  • 正文语种 {"code":"en","name":"english","id":9}
  • 中图分类

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