The market for cryptocurrencies has developed steadily since its inception in 2009. Thousands of currencies currently exist and are traded on crypto exchanges. In contrast to traditional markets, however, these currencies cannot be assigned any clear characteristics. For example, these include currencies, vouchers, software licenses or securities that are traded as blockchain-based assets. This broad range of underlying values and possible uses make as uniform regulation difficult. While cryptocurrency markets and exchanges show clear similarities to traditional financial markets, they are by no means regulated to the same extent. This leads to crypto exchanges, for example, reporting their trading volume incorrectly in order to suggest liquidity or informed trading in Bitcoin markets.
In the article „Market Reaction to Exchange Listings of Cryptocurrencies“ I examine effects of 327 exchange listings of 180 different cryptocurrencies on 22 exchanges. On the one hand, a general overview of the phenomenon should be provided and on the other hand, potential signs of informed trading should be identified. The investigation is carried out using event study methodology, which allows to calculate so-called abnormal returns. Basically, one takes an observation period before the period to be examined around an event and calculates how an asset normally behaves. If one now calculates the return in the period to be observed around an exchange listing and sets it in relation to the normal behavior of the asset, one can calculate the abnormal return. Additionally, I extend the model to control that negative or positive effects were not caused by price developments of Bitcoin. Since the methodology requires an existing price history, I could only examine cross-listings of assets that had already been tradable on other exchanges for at least 30 days.
The results for the overall market show that on the day of listing a highly significant average positive abnormal return of 7.4% is achieved. If the time window is extended to three days before to three days after the event (-3, +3), the abnormal return is 9.2%. In the period (‑3, ‑2) in which the market should have no knowledge of the upcoming event, highly significant positive abnormal returns of 3.2% are identified. This is a clear indication that informed trading is taking place.
I break down this evaluation on each of the 22 crypto exchanges to find out how effects differ for individual exchanges. Extreme differences are identified. Over the entire 7-day event window (-3, +3), only five exchanges recorded significant positive returns. For six exchanges, effects are even negative. The significant positive effects on the day of listing are largely distributed among some exchanges, such as Binance (14.7%), Bitfinex (25.5%), Bittrex (23.5%) or Bithump (5.1%), while listings on other exchanges even lead to significantly negative returns (e.g. Gate.io – 4.5%; Bibox – 3.6%). Signs of informed trading are also only apparent for certain exchanges. Further analyses show that country characteristics, comparatively lower trading volume and lower asset market capitalization are relevant determinants of listing success.
The study has several implications. It identifies that the low level of regulation of the market is exploited in the form of informed trading. Regulators should see this as a starting point. In addition, the results can be used by cryptocurrency traders or projects to evaluate where listings have positive (or negative) price effects. For cryptocurrency exchanges, the results provide indications that information may leak or which form of assets leads to comparatively higher listing returns. In the article I list several potential avenues for future research.