A Call for Second-Generation Cryptocurrency Valuation Metrics

Abstract

This chapter builds on the body of work that has depicted cryptocurrency as a model for science and higher education funding. To that end, this work examines the degree to which one or more cryptocurrencies would need to be adopted and achieve a network effect prior to implementation of such a funding model. Empirical data from three different cryptocurrencies were examined. The current work deploys generalized autoregressive conditional heteroskedasticity (GARCH) to analyze stochastic volatility. This work contends that the examined coins are likely overdistributed and too volatile, thereby limiting the wealth generation possibilities for funding science or higher education. Additionally, based on the GARCH analysis, this work highlights that cryptocurrency pricing metrics and valuation models, to this point, may be insufficiently complex to persuade institutional investors to seriously allocate capital to this ecosphere.

Does the Hashrate Affect the Bitcoin Price?

“…In this regard, we want to remark that Shanaev et al (2019) recently showed that some of the previously reported positive relationships between crypto-coins prices and their hashrate, or between crypto-coins prices and their transaction counts, were either spurious due to serial correlation or inconsistent due to endogeneity. Therefore, the development of "second-generation valuation metrics" for cryptocurrencies (Lehner et al 2019;Shanaev et al 2019) able to accommodate both modern empirical finance asset-pricing models and theory-driven valuation models is definitively a compelling avenue for further research. be equal to 21 million bitcoin.…”

Does the Hashrate Affect the Bitcoin Price?

“…In this regard, we want to remark that Shanaev et al (2019) recently showed that some of the previously reported positive relationships between crypto-coins prices and their hashrate, or between crypto-coins prices and their transaction counts were either spurious due to serial correlation or inconsistent due to endogeneity. Therefore, the development of "second-generation valuation metrics" for cryptocurrencies (Lehner et al (2019) and Shanaev et al (2019)) able to accommodate both modern empirical finance asset-pricing models and theory-driven valuation models is definitively a compelling avenue for further research.…”