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Contribution Details
| Type | Master's Thesis |
| Scope | Discipline-based scholarship |
| Title | Analysis of Multi-Factor Asset Pricing Model for Cryptocurrency Assets Taking Market Cycles into Account |
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| Institution | University of Zurich |
| Faculty | Faculty of Business, Economics and Informatics |
| Date | 2023 |
| Abstract Text | In this thesis, we examine 25 zero-investment long-short strategies derived from factors constructed using price, market capitalization, and trading volume of cryptocurrency assets to identify significant alpha generation. We employ various parsimonious factor models, incorporating market return, size, momentum, and market cycle to explain the observed alphas. Our findings reveal that a model encompassing all four factors can account for six out of the seven significant strategies. Additionally, we utilize a Fama-MacBeth Regression to demonstrate that the risk premia associated with market, size, and momentum exposures are not only significant over time but also exhibit greater strength and volatility during bullish market cycles. |
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