Volatility forecasting in the Bitcoin market: A new proposed measure based on the VS-ACARR approach

Document Type

Article

Source of Publication

The North American Journal of Economics and Finance

Publication Date

7-1-2023

Abstract

This paper proposes a new volatility-spillover-asymmetric conditional autoregressive range (VS-ACARR) approach that takes into account the intraday information, the volatility spillover from crude oil as well as the volatility asymmetry (leverage effect) to model/forecast Bitcoin volatility (price range). An empirical application to Bitcoin and crude oil (WTI) price ranges shows the existence of strong volatility spillover from crude oil to the Bitcoin market and a weak leverage effect in the Bitcoin market. The VS-ACARR model yields higher forecasting accuracy than the GARCH, CARR, and VS-CARR models regarding out-of-sample forecast performance, suggesting that accounting for the volatility spillover and asymmetry can significantly improve the forecasting accuracy of Bitcoin volatility. The superior forecast performance of the VS-ACARR model is robust to alternative out-of-sample forecast windows. Our findings highlight the importance of accommodating intraday information, spillover from crude oil, and volatility asymmetry in forecasting Bitcoin volatility.

ISSN

1062-0860

Publisher

Elsevier BV

Volume

67

First Page

101948

Last Page

101948

Disciplines

Business

Keywords

C53, E47, G11, G15, Bitcoin, Price range, Volatility spillover, Crude oil, Leverage effect, Conditional Auto Regressive Range (CARR)

Indexed in Scopus

no

Open Access

no

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