Is There a Value Premium in Cryptoasset Markets?
This paper identifes active addresses-to-network value as an additional common risk factor in the returns on cryptoassets. Investigating 652 cryptoassets, I find that there are anomalous returns that increase with active addresses-to-network value ratio, a proxy for the value anomaly. Cryptoassets with a high active address to network value ratio yield on average 2.1 percentage points higher weekly returns compared to cryptoassets with low active addresses to network value ratio, and comparable size. A four-factor model directed at capturing the value pattern in average returns performs better than a three-factor model, including the market, size, and momentum factor. Importantly, the results suggest that cryptoasset prices are related to their fundamentals.
I study the effect of hard forks and airdrops on cryptocurrency prices. At the hard fork and airdrop date, holders of the parent coin receive additional coins of a different cryptocurrency. The announcement of a hard fork or airdrop does not affect parent coin prices. In contrast, the distribution of coins immediately decreases the prices of the parent coin by 4.65%. The cumulative average abnormal return over the 5-day post-distribution date equals -12.29%. Importantly, I show that the price drop of the parent coin is significantly lower than the value of the distributed cryptocurrency. This suggests that hard forks and airdrops are partly free money.
with Zeno Adams
We examine household location choice for eight cities in Switzerland. In line with other studies for Europe and the U.S., empirical evidence for the income gradient is weak in standard regression specifications that control for household characteristics and amenities. We provide a possible solution for this long standing empirical puzzle and obtain negatively sloped income gradients that are postulated by the monocentric city model. We show that municipality taxes, a variable that has particular spatial variation in Switzerland, plays a dominant role in explaining households‘ cross-sectional arrangements. This has significant implications for policymakers, their local tax rate decisions, and the maximization of the tax substrate.
Survivorship Bias and Cryptoasset Returns
Working Paper with Manuel Ammann, Sebastian Stöckl, and Tom Burdorf
In this paper we quantify the survivorship bias in cryptocurrency markets and provide an R package to obtain historical data from Coinmarketcap. Importantly, the methodology we use to scrape the historical data remarks an important contribution to the webscraping literature.