Citation:
Anatolyev, Stanislav (2021) "Directional news impact curve", Journal of Forecasting, vol. 40, no. 1, pp. 94-107
Abstract:
The directional news impact curve (DNIC) is a relationship between returns and a probability of next period's return to exceed a certain threshold, zero in particular. Using long series of S&P500 index returns and a number of parametric models suggested in the literature as well and flexible semiparametric models, we investigate the shape of DNIC, as well as forecasting abilities of these models. The semiparametric approach reveals that the DNIC has complicated shapes characterized by non-symmetry with respect to past returns and their signs, heterogeneity across the thresholds, and changes over time. Simple parametric models often miss some important features of the DNIC, but some nevertheless exhibit superior out-of-sample performance.
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Presented at:
XLV New Economic School research conference, Moscow, November 7-8, 2019