North-West University, Potchefstroom, South Africa; Centre for Business Mathematics and Informatics, North-West University, Potchefstroom, South Africa
van Vuuren, G., North-West University, Potchefstroom, South Africa; Yacumakis, R., Centre for Business Mathematics and Informatics, North-West University, Potchefstroom, South Africa
In the capital asset pricing model, portfolio market risk is recognised through β while α summarises asset selection skill. Traditional parameter estimation techniques assume time-invariance and use rolling-window, ordinary least squares regression methods. The Kalman filter estimates dynamic α s and βs 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. © 2015, Universiteit Stellenbosch. All rights reserved.