# High-Frequency Jump Analysis of the Bitcoin Market

## TL;DR

This paper analyzes high-frequency bitcoin price jumps using data from the Mt. Gox exchange leak, revealing their clustering, predictors, and impact on market activity and liquidity.

## Contribution

It provides the first detailed high-frequency analysis of bitcoin jumps, identifying key predictors and their effects on market dynamics.

## Key findings

- Jumps are frequent and tend to cluster in time.
- Order flow imbalance and aggressive trading predict jumps.
- Jumps temporarily increase market activity and illiquidity.

## Abstract

We use the database leak of Mt. Gox exchange to analyze the dynamics of the price of bitcoin from June 2011 to November 2013. This gives us a rare opportunity to study an emerging retail-focused, highly speculative and unregulated market with trader identifiers at a tick transaction level. Jumps are frequent events and they cluster in time. The order flow imbalance and the preponderance of aggressive traders, as well as a widening of the bid-ask spread predict them. Jumps have short-term positive impact on market activity and illiquidity and see a persistent change in the price.