STOCHASTIC VOLATILITY MODELS AND THE TAYLOR EFFECT

It has been often empirically observed that the sample autocorrelations of absolute financial returns are larger than those of squared returns. This property, know as Taylor effect, is analysed in this paper in the Stochastic Volatility (SV) model framework. We show that the stationary autoregressive SV model is able to generate this property for realistic parameter specifications. On the other hand, the Taylor effect is shown not to be a sampling phenomena due to estimation biases of the sample autocorrelations. Therefore, financial models that aims to explain the behaviour of financial returns should take account of this property.