Analyzing Financial Time-Series Using Random Matrix Theory - MATLAB
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    Analyzing Financial Time-Series Using Random Matrix Theory

    Duan Wang, SLC Management

    Random matrix theory (RMT) is a useful tool for noise reduction in the sample covariance matrix in financial time-series analysis. Duan Wang, a quantitative analyst on the Derivatives and Quantitative Strategies team, demonstrates how SLC Management implemented RMT in MATLAB® to produce an improved estimator for the sample covariance variance. He also shows a couple of examples in portfolio optimization and asset allocation.

    Published: 14 Nov 2022

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