Economics at your fingertips  

Forecasting the good and bad uncertainties of crude oil prices using a HAR framework

Xu Gong and Boqiang Lin ()

Energy Economics, 2017, vol. 67, issue C, 315-327

Abstract: Good (or bad) uncertainty is the volatility that is associated with positive (or negative) innovations to asset prices. This paper proposes new heterogeneous autoregressive type (HAR-type) models to forecast the good and bad uncertainties of crude oil prices. In this paper we investigate the effects of lagged bad and good uncertainties, daily positive and negative signed jump variations, and leverages on predicting good and bad uncertainties by in-sample and out-of-sample analysis. The in-sample results show that bad and good uncertainties have long memory property, and the predictability of long-term good and bad uncertainties is stronger than that of short- and mid-term good and bad uncertainties. The out-of-sample results indicate that lagged bad (or good) uncertainties, daily positive signed jump variation, and daily negative signed jump variation contain incremental out-of-sample information for forecasting good (or bad) uncertainties, and in most cases lagged leverages also play indispensable roles in forecasting the good and bad uncertainties in the crude oil market. Moreover, the results of out-of-sample analysis remain robust across using the other estimation window, other HAR-type models, and the other sample.

Keywords: Forecasting uncertainty; Good uncertainty; Bad uncertainty; Realized semivariance; HAR; MCS (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (33) Track citations by RSS feed

Downloads: (external link)
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

DOI: 10.1016/j.eneco.2017.08.035

Access Statistics for this article

Energy Economics is currently edited by R. S. J. Tol, Beng Ang, Lance Bachmeier, Perry Sadorsky, Ugur Soytas and J. P. Weyant

More articles in Energy Economics from Elsevier
Bibliographic data for series maintained by Haili He ().

Page updated 2020-08-29
Handle: RePEc:eee:eneeco:v:67:y:2017:i:c:p:315-327