Understanding jumps in high frequency digital asset markets

Danial Saef, Odett Nagy, Sergej Sizov, Wolfgang Karl Härdle

While attention is a predictor for digital asset prices, and jumps in Bitcoin prices are well-known, we know little about its alternatives. Studying high frequency crypto data gives us the unique possibility to confirm that cross market digital asset returns are driven by high frequency jumps clustered around black swan events, resembling volatility and trading volume seasonalities. Regressions show that intra-day jumps significantly influence end of day returns in size and direction. This provides fundamental research for crypto option pricing models. However, we need better econometric methods for capturing the specific market microstructure of cryptos. All calculations are reproducible via the quantlet.com technology.

MoreLess

Year of publication:	[2021]
Authors:	Saef, Danial ; Nagy, Odett ; Sizov, Sergej ; Härdle, Wolfgang
Publisher:	Berlin : International Research Training Group 1792
Subject:	jumps \| market microstructure noise \| high frequency data \| cryptocurrencies \| CRIX \| option pricing \| Finanzmarkt \| Financial market \| Volatilität \| Volatility \| Marktmikrostruktur \| Market microstructure \| Virtuelle Währung \| Virtual currency \| Optionspreistheorie \| Option pricing theory \| Stochastischer Prozess \| Stochastic process \| Börsenkurs \| Share price \| Noise Trading \| Noise trading