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Bitcoin price determinants and valuation framework

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posted on 2022-11-08, 03:37 authored by Bi Zhou

This paper investigates the value of Bitcoin both empirically and theoretically. Based on the market data from January 2012 to July 2021, this paper empirically examines the significance of thirty-eight potential price determinants of Bitcoin. Specifically, the study applies the “Least Absolute Shrinkage and Selection Operator” (LASSO) framework to investigate a range of drivers, including Bitcoin-unique factors, public attention, macro indicators and financial assets returns. The paper also splits the sample period into four sub-periods and by calendar year to analyse the evolvement of Bitcoin price formation over time. Consistent with prior studies, findings confirm the significant impact of demand factors, network growth, investor sentiment and negative public attention on Bitcoin returns, whereas equities, bonds, interest rates and the US monetary stimulus are found to be largely irrelevant. Meanwhile, in contrast to prior studies that suggest Bitcoin return is positively associated with public attention, this study finds a robust negative relationship between the two. In addition, significant time variance is observed and confirms that the Bitcoin return determination is dynamic. Furthermore, the paper is the first to investigate and evidence the crucial and positive impact of inflation expectations and non-energy commodity returns in Bitcoin price determination, especially since January 2018. Theoretically, the paper extends a Bitcoin fundamental valuation framework based on a demand and supply equilibrium model and use case approaches to predict the fundamental value of Bitcoin once it reaches a steady status and is accepted as money. The valuation results show that the probability-weighted Bitcoin fair value is $23,359, suggesting the current Bitcoin market has fully priced in the most optimistic scenario and underestimates the regulation risks.


Table of Contents

1. Introduction -- 2. Literature review -- 3. Methodology and data of the price determinants -- 4. Results of LASSO regression -- 5. Valuation framework -- 6. Conclusion -- References -- Appendix

Awarding Institution

Macquarie University

Degree Type

Thesis MRes


Thesis (MRes), Macquarie University, Macquarie Business School, 2022

Department, Centre or School

Department of Applied Finance

Year of Award


Principal Supervisor

Cynthia Cai

Additional Supervisor 1

Rui Xue


Copyright: Bi Zhou Copyright disclaimer:




73 pages

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