Volatility forecasting accuracy for Bitcoin

DOI10.1016/j.econlet.2019.108836zbMath1442.91119OpenAlexW2983744991WikidataQ126832347 ScholiaQ126832347MaRDI QIDQ777644

Gerrit Köchling, Peter N. Posch, Philipp Schmidtke

Publication date: 7 July 2020

Published in: Economics Letters (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/2003/38165

zbMATH Keywords

GARCHvolatilitymodel confidence setcryptocurrencyBitcoinrobust loss function

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Applications of statistics to actuarial sciences and financial mathematics (62P05) Statistical methods; risk measures (91G70)

Related Items

Volatility prediction comparison via robust volatility proxies: an empirical deviation perspective ⋮ Assessing the accuracy of exponentially weighted moving average models for Value-at-Risk and Expected Shortfall of crypto portfolios ⋮ Transaction activity and bitcoin realized volatility

Uses Software

• Rugarch

Cites Work

• The Model Confidence Set
• Jump-robust volatility estimation using nearest neighbor truncation
• Volatility forecast comparison using imperfect volatility proxies
• Volatility estimation for Bitcoin: a comparison of GARCH models
• A Reality Check for Data Snooping
• Econometric Analysis of Realized Volatility and its Use in Estimating Stochastic Volatility Models
• Asymptotic Inference about Predictive Ability

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