High Frequency Lead-lag Relationships in The Bitcoin Market: An Empirical Analysis of the Price Movements of Bitcoin on Different Cryptocurrency Exchanges During the Year of 2018

Bendik Norheim Schei

Student thesis: Master thesis

Abstract

In a rational and efficiently functioning market, returns on financial products that represent the same underlying asset should be perfectly simultaneously correlated. However, due to market imperfections, lead-lag relationships are a commonly observed phenomenon in traditional financial markets. This thesis examines price movements in a new and emerging market. Bitcoin is the oldest and most liquid cryptocurrency and is traded on numerous exchanges. By the use of a traditional cointegration and causality approach, bidirectional relationships are confirmed between all bitcoin prices tested. A modern high frequency approach with the use of tick-by-tick data reveals strongly asymmetric crosscorrelation functions. Some bitcoin prices follow the path of others with a time lag up to 15 seconds. The analysis furthermore confirms that the lead-lag relationships are affected by the rate of information arrival, whose proxy is the unexpected trading volume on the exchanges. Moreover, sophisticated investors have a more significant effect on the lead-lag relationship than non-sophisticated ones. A simple trading strategy is used to forecast mid-quote changes in lagging exchanges with directional accuracy of up to 70%. Profitable arbitrage opportunities are found by the use of an algorithm-based trading strategy, under the assumptions of trading at the lowest fee levels and mid-quote execution. Nevertheless, trading fees, price slippage and lack of liquidity are found as the most important limits to arbitrage. Several aspects could explain why lead-lag relationships are found. Exchange characteristics like infrastructure, fee structure, location and investors types are important. However, the analysis in this thesis points towards liquidity of exchanges as the most likely explanation.

EducationsMSc in Finance and Investments, (Graduate Programme) Final Thesis
LanguageEnglish
Publication date2019
Number of pages127