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Luca Liebi
Former Member
Title
M.A.
Last Name
Liebi
First name
Luca
Phone
+41 71 224 70 15
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Item type:Publication, Survivorship and Delisting Bias in Cryptocurrency
Markets(2022-11-28); ; Stöckl, SebastianThis study quantifies performance measure distortions in a cryptocurrency sample truncated by survivorship and delisting bias. Previous research shows that the attrition rate in cryptocurrency markets is high. However, the survivorship and delisting bias in cryptocurrencies lacks empirical research. Using data for 3’904 cryptocurrencies during the 2014-2021 period, we estimate an annualized bias of 0.93% (62.19%) for value-weighted (equal-weighted) portfolios. After controlling for survivorship and delisting bias, we revisit the relationship between average returns, size, past performance, market β, liquidity, and downside risk. Our results confirm the size effect, but the premium is overestimated by 50% in a survival-conditioned sample. In contrast, we find no evidence of a positive relationship between average returns, one-week momentum, market β, and downside risk. Our results suggest that the survivorship and delisting bias are important biases that ought to be omitted.Type:journal article - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Antony Lewis: The basics of bitcoins and blockchainsType:journal articleJournal:Financial Markets and Portfolio Management - Some of the metrics are blocked by yourconsent settings
Item type:Publication, The effect of ETFs on financial markets: a literature reviewType:journal articleJournal:Financial Markets and Portfolio ManagementVolume:34Issue:2Scopus© Citations 39 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Is there a value premium in cryptoasset markets?(2020-11-23)This paper identifies active addresses-to-network value as an additional common risk factor in the returns on cryptoassets. Active addresses refer to the number of unique wallet addresses that conduct an on-chain transaction, whereas the network value of a cryptoasset corresponds to its market capitalization. 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.Type:forthcoming