Forecasting Bitcoin risk measures: A robust approach

B-Tier
Journal: International Journal of Forecasting
Year: 2019
Volume: 35
Issue: 3
Pages: 836-847

Score contribution per author:

2.011 = (α=2.01 / 1 authors) × 1.0x B-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

Over the last few years, Bitcoin and other cryptocurrencies have attracted the interest of many investors, practitioners and researchers. However, little attention has been paid to the predictability of their risk measures. This paper compares the predictability of the one-step-ahead volatility and Value-at-Risk of Bitcoin using several volatility models. We also include procedures that take into account the presence of outliers and estimate the volatility and Value-at-Risk in a robust fashion. Our results show that robust procedures outperform non-robust ones when forecasting the volatility and estimating the Value-at-Risk. These results suggest that the presence of outliers plays an important role in the modelling and forecasting of Bitcoin risk measures.

Technical Details

RePEc Handle
repec:eee:intfor:v:35:y:2019:i:3:p:836-847
Journal Field
Econometrics
Author Count
1
Added to Database
2026-01-29