Application of noise level estimation for portfolio optimization
Abstract
Time changes of noise level at Warsaw Stock Market are analyzed using a recently developed method basing on properties of the coarse grained entropy. The condition of the minimal noise level is used to build an efficient portfolio. Our noise level approach seems to be a much better tool for risk estimations than standard volatility parameters. Implementation of a corresponding threshold investment strategy gives positive returns for historical data.
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