A Dynamic Factor Model of Cryptographic Asset Returns

Abstract

Since the launch of Bitcoin in 2009, there has been a dramatic proliferation of alternative cryptographically secured digital assets, also known as cryptocurrencies or "crypto assets", targeted at an increasingly wide variety of use cases that go far beyond Bitcoin's original vision. Data on this new and rapidly growing asset class is likewise becoming more available, making it an interesting area for the application of traditional financial econometric research methods. My thesis describes the implementation of a dynamic factor model for crypto asset returns, inspired by prior work by Stock and Watson (1991) and Ng et al. (1992), with the goal of explaining the structure of past returns in the space and forecasting future responses to systematic shocks. I find significant evidence to support a single-dynamic-factor model, but data availability is not sufficient to definitively forecast response to systematic factor shocks. Possible interpretations of the estimated dynamic factor are discussed, and suggestive evidence is presented to support the hypothesis that the value-weighted market portfolio is a dynamic factor for the crypto asset market.