Covariance Averaging for Improved Estimation and Portfolio Allocation
AbstractWe propose a new method for estimating the covariance matrix of a multivariate time series of nancial returns. The method is based on estimating sample covariances from overlapping windows of observations which are then appropriately weighted to obtain the nal covariance estimate. We extend the idea of (model) covariance averaging o ered in the covariance shrinkage approach by means of greater ease of use, exibility and robustness in averaging information over different data segments. The suggested approach does not su er from the curse of dimensionality and can be used without problems of either approximation or any demand for numerical optimization.
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Bibliographic InfoPaper provided by The Rimini Centre for Economic Analysis in its series Working Paper Series with number 66_13.
Date of creation: Dec 2013
Date of revision:
averaging; covariance estimation; nancial returns; multivariate time series; portfolio allocation; risk management; rolling window;
Find related papers by JEL classification:
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
- G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
This paper has been announced in the following NEP Reports:
- NEP-ALL-2014-01-17 (All new papers)
- NEP-ECM-2014-01-17 (Econometrics)
- NEP-ORE-2014-01-17 (Operations Research)
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