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Risk evaluation with enhaced covariance matrix

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  • Krzysztof Urbanowicz
  • Peter Richmond
  • Janusz A. Holyst

Abstract

We propose a route for the evaluation of risk based on a transformation of the covariance matrix. The approach uses a `potential' or `objective' function. This allows us to rescale data from different assets (or sources) such that each data set then has similar statistical properties in terms of their probability distributions. The method is tested using historical data from both the New York and Warsaw Stock Exchanges.

Suggested Citation

  • Krzysztof Urbanowicz & Peter Richmond & Janusz A. Holyst, 2006. "Risk evaluation with enhaced covariance matrix," Papers physics/0612059, arXiv.org, revised May 2007.
    • Handle: RePEc:arx:papers:physics/0612059
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    Cited by:

    1. Ajay Singh & Dinghai Xu, 2016. "Random matrix application to correlations amongst the volatility of assets," Quantitative Finance, Taylor & Francis Journals, vol. 16(1), pages 69-83, January.
    2. Bertram, William K., 2008. "Measuring time dependent volatility and cross-sectional correlation in Australian equity returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(13), pages 3183-3191.

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