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Semiparametric estimation of Value at Risk

Jianqing Fan Juan Gu

Statistics Theory and Methods mathscidoc:1912.43297

The Econometrics Journal, 6, (2), 261-290, 2003.11
Value at Risk (VaR) is a fundamental tool for managing market risks. It measures the worst loss to be expected of a portfolio over a given time horizon under normal market conditions at a given confidence level. Calculation of VaR frequently involves estimating the volatility of return processes and quantiles of standardized returns. In this paper, several semiparametric techniques are introduced to estimate the volatilities of the market prices of a portfolio. In addition, both parametric and nonparametric techniques are proposed to estimate the quantiles of standardized return processes. The newly proposed techniques also have the flexibility to adapt automatically to the changes in the dynamics of market prices over time. Their statistical efficiencies are studied both theoretically and empirically. The combination of newly proposed techniques for estimating volatility and standardized quantiles yields several new
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@inproceedings{jianqing2003semiparametric,
  title={Semiparametric estimation of Value at Risk},
  author={Jianqing Fan, and Juan Gu},
  url={http://archive.ymsc.tsinghua.edu.cn/pacm_paperurl/20191221113545009838857},
  booktitle={The Econometrics Journal},
  volume={6},
  number={2},
  pages={261-290},
  year={2003},
}
Jianqing Fan, and Juan Gu. Semiparametric estimation of Value at Risk. 2003. Vol. 6. In The Econometrics Journal. pp.261-290. http://archive.ymsc.tsinghua.edu.cn/pacm_paperurl/20191221113545009838857.
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