The time between order submission and order confirmation is crucial for high frequency traders as they risk slippage when latency is too high. We hypothesize that high latency in cryptocurrency markets implies correlations well below one across exchanges at high frequencies. To evaluate this...

This article analyzes asymmetric volatility effects for the 20 largest cryptocurrencies and reports a very different asymmetry compared to equity markets: positive shocks increase the volatility by more than negative shocks. We explain this atypical effect for financial assets with trading...

We examine the price discovery contributions of cryptocurrency exchanges in the presence of market microstructure noise. Cryptocurrency markets exhibit a decisively higher level of microstructure noise compared to the New York Stock Exchange or NASDAQ. Therefore, traditional measures of price...

Trading of Bitcoin is spread about multiple venues where buying and selling is offered in various currencies. However, all exchanges trade one common good and by the law of one price, the different prices should not deviate in the long run. In this context we are interested in which platform is...

We evaluate the usefulness of Google search volume to predict returns and volatility of multiple cryptocurrencies. The analysis is based on a new algorithm which allows to construct mulit-annual, consistent time series of Google search volume indices (SVIs) on various frequencies. As...

Bitcoin is traded on exchanges which use an open limit order book. This paper investigates the microstructure of various bitcoin markets with respect to liquidity and private information processing. The markets are found to be fairly liquid, providing liquidity at a stable rate throughout the 24...

Cryptocurrency markets are notoriously noisy, but not all markets might behave in the exact same way. Therefore, we investigate which market contributes the most to the evolution of the common volatility component of cryptocurrency markets. We extract each of the markets’ latent volatility...