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Large Scale Covariance Estimates for Portfolio Selection

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Abstract

We propose an estimator of the Covariance Matrix (SWSE) of a large number of assets. This estimator improves the Similarity Weighted Estimator (SWE) introduced in Munnix et al. (2014), by combining it with the shrinkage estimator of the sample covariance matrix towards the market factor developed by Ledoit and Wolf (2003). We compare the performance of our estimator to some alternatives already available form the literature and the industry. For this purpose we analyse both statistical and economic measures associated to the Global Minimum Variance (GMV) Portfolio, composed by the stocks included in the S&P 500 index and computed using the different estimators considered in our comparison.

Suggested Citation

  • Francesco Lautizi, 2015. "Large Scale Covariance Estimates for Portfolio Selection," CEIS Research Paper 353, Tor Vergata University, CEIS, revised 07 Aug 2015.
    • Handle: RePEc:rtv:ceisrp:353
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    References listed on IDEAS

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    More about this item

    Keywords

    Portfolio selection; large scale covariance matrix; precision matrix; shrinkage; minimum variance; market dynamics;
    All these keywords.

    JEL classification:

    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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