n Studies in Economics and Econometrics - Hedge fund performance evaluation using the Kalman filter

Volume 39, Issue 3
  • ISSN : 0379-6205


In the capital asset pricing model, portfolio market risk is recognised through while summarises asset selection skill. Traditional parameter estimation techniques assume time-invariance and use rolling-window, ordinary least squares regression methods. The Kalman filter estimates s and s where measurement noise covariance and state noise covariance are known - or may be calibrated - in a state-space framework. These time-varying parameters result in superior predictive accuracy of fund return forecasts against ordinary least square (and other) estimates, particularly during the financial crisis of 2008/9 and are used to demonstrate increasing correlation between hedge funds and the market.

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