HARQ is a simple and powerful extension of the heterogeneous autoregressive volatility model (HAR) proposed by Bollerslev et al. (2016). HARQ takes into account the impact of realised variance measurement error that might compomise the validity of HAR coefficients by introducing a realised quarticity term that explicitly estimates the variance of realised variance. Today we are discussing the mathematical and econometric concepts behind the HARQ model, its implementation in Excel with high-frequency data, interpret its results, and discuss its applications for forecasting.
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