Qu'est-ce que « QLIKE loss, Mincer–Zarnowitz regression, Diebold–Mariano test » ?

The QLIKE loss is $\hat\sigma^2/h + \ln h$ (up to terms that do not involve $h$), the negative Gaussian log-likelihood of the proxy’s return: minimised in expectation by $h = \E[\hat\sigma^2]$ and heavier on under-prediction than on over-prediction. The Mincer–Zarnowitz regression (1969) of the proxy on the forecast, $\hat\sigma^2_t = a + bh_t + e_t$, tests unbiasedness ($a = 0$, $b = 1$). The Diebold–Mariano test (1995) of equal accuracy divides the mean loss difference of two forecasts by its HAC standard error.