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The impact of covariance misspecification in risk-based portfolios

(2017) ANNALS OF OPERATIONS RESEARCH. 254(1-2). p.1-16
Author
Organization
Abstract
The equal-risk-contribution, inverse-volatility weighted, maximum-diversification and minimum-variance portfolio weights are all direct functions of the estimated covariance matrix. We perform a Monte Carlo study to assess the impact of covariance matrix misspecification to these risk-based portfolios at the daily, weekly and monthly forecasting horizon. Our results show that the equal-risk-contribution and inverse-volatility weighted portfolio weights are relatively robust to covariance misspecification. In contrast, the minimum-variance portfolio weights are highly sensitive to errors in both the estimated variances and correlations, while errors in the estimated correlations can have a large effect on the weights of the maximum-diversification portfolio.
Keywords
MODELS, Covariance misspecification, Monte Carlo study, Risk-based portfolios

Citation

Please use this url to cite or link to this publication:

MLA
Ardia, David et al. “The Impact of Covariance Misspecification in Risk-based Portfolios.” ANNALS OF OPERATIONS RESEARCH 254.1-2 (2017): 1–16. Print.
APA
Ardia, D., Bolliger, G., Boudt, K., & Gagnon-Fleury, J.-P. (2017). The impact of covariance misspecification in risk-based portfolios. ANNALS OF OPERATIONS RESEARCH, 254(1-2), 1–16.
Chicago author-date
Ardia, David, Guido Bolliger, Kris Boudt, and Jean-Philippe Gagnon-Fleury. 2017. “The Impact of Covariance Misspecification in Risk-based Portfolios.” Annals of Operations Research 254 (1-2): 1–16.
Chicago author-date (all authors)
Ardia, David, Guido Bolliger, Kris Boudt, and Jean-Philippe Gagnon-Fleury. 2017. “The Impact of Covariance Misspecification in Risk-based Portfolios.” Annals of Operations Research 254 (1-2): 1–16.
Vancouver
1.
Ardia D, Bolliger G, Boudt K, Gagnon-Fleury J-P. The impact of covariance misspecification in risk-based portfolios. ANNALS OF OPERATIONS RESEARCH. Dordrecht: Springer; 2017;254(1-2):1–16.
IEEE
[1]
D. Ardia, G. Bolliger, K. Boudt, and J.-P. Gagnon-Fleury, “The impact of covariance misspecification in risk-based portfolios,” ANNALS OF OPERATIONS RESEARCH, vol. 254, no. 1–2, pp. 1–16, 2017.
@article{8600213,
  abstract     = {The equal-risk-contribution, inverse-volatility weighted, maximum-diversification and minimum-variance portfolio weights are all direct functions of the estimated covariance matrix. We perform a Monte Carlo study to assess the impact of covariance matrix misspecification to these risk-based portfolios at the daily, weekly and monthly forecasting horizon. Our results show that the equal-risk-contribution and inverse-volatility weighted portfolio weights are relatively robust to covariance misspecification. In contrast, the minimum-variance portfolio weights are highly sensitive to errors in both the estimated variances and correlations, while errors in the estimated correlations can have a large effect on the weights of the maximum-diversification portfolio.},
  author       = {Ardia, David and Bolliger, Guido and Boudt, Kris and Gagnon-Fleury, Jean-Philippe},
  issn         = {0254-5330},
  journal      = {ANNALS OF OPERATIONS RESEARCH},
  keywords     = {MODELS,Covariance misspecification,Monte Carlo study,Risk-based portfolios},
  language     = {eng},
  number       = {1-2},
  pages        = {1--16},
  publisher    = {Springer},
  title        = {The impact of covariance misspecification in risk-based portfolios},
  url          = {http://dx.doi.org/10.1007/s10479-017-2474-7},
  volume       = {254},
  year         = {2017},
}

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