Kaiko Market Data supports MIT & LSE Research on Arbitrage

August 22, 2018

Arbitrage, the strategy in which traders take advantage of price discrepancies across different markets, is not unique to the cryptocurrency industry. It has been used by traditional traders, banks and brokerage firms for a long time with financial instruments such as bonds, commodities, derivatives etc. The turbulent and disorganized nature of the crypto sphere, however, seems to amplify this phenomenon. Igor Makarov, from the London School of Economics and Antoinette Schoar, from MIT Sloan, teamed up to research Trading and Arbitrage in Cryptocurrecny Markets, based on Kaiko historical trade data.

Some key findings of the paper:

  • The total size of arbitrage profits just from December 2017 to February 2018 is above $1 billion.
  • Arbitrage opportunities are much larger across than within the same region.
  • Capital controls and other operational constraints across countries seem to limit those opportunities.

Read the full paper here: 

Trading and Arbitrage in Cryptocurrency Markets - Igor Makarov (London School of Economics) and Antoinette Schoar (MIT Sloan)

MIT LSE Kaiko Data Research

This paper studies the efficiency and price formation of bitcoin and other cryptocurrency markets. First, there are large recurrent arbitrage opportunities in cryptocurrency prices relative to fiat currencies across exchanges that often persist for several days or weeks. These price dispersions exist even in the face of significant trading volumes on many of the exchanges. The total size of arbitrage profits just from December 2017 to February 2018 is above of $1 billion. Second, arbitrage opportunities are much largeracrossthan within the same region; they are particularly large between the US, Japan and Korea, but smaller between the US and Europe. But spreads are much smaller when trading one cryptocurrency against another, suggesting that cross-border controls on fiat currencies play an important role. Finally, we decompose signed volume on each exchange into a common component and an idiosyncratic, exchange-specific one. We show that the common component explains up to 85% of the variation in bitcoin returns and that the idiosyncratic components of order flow play an important role in explaining the size of the arbitrage spreads between exchanges.