This study aims to examine Bitcoin’s demand and price dynamics as it transitions from a growth state to a mature state, focusing on user base expansion and inventory levels. It refines valuation models and financial strategies by analyzing Bitcoin’s shift from network-driven asset characteristics to commodity-like price behavior, offering insights for regulatory oversight.
Using the Pruned Exact Linear Time algorithm to identify regime shifts, instrumental variable (IV) regression models to address endogeneity and derivatives data to estimate convenience yield and implied volatilities, the study analyzes blockchain and market-level data from 2013 to 2020. Five hypotheses on Bitcoin’s demand, returns, inventory effects, convenience yield and implied volatility are tested.
In the growth state, Bitcoin demand rises with user base expansion, with 100 unique users increasing demand by 0.23%. In the mature state, inventory levels negatively impact returns, with a 133-bitcoin increase lowering returns by 1 basis point. Convenience yields decline with inventory, while implied volatility slopes increase, confirming Bitcoin’s commodity-like behavior.
Findings rely on historical data and future research can explore similar patterns in other cryptocurrencies. Blockchain data limitations, such as address clustering and transaction anonymity, may impact results.
Results provide insights for traders, risk managers and policymakers. Portfolio managers can align investments with Bitcoin’s lifecycle, while derivative traders can leverage insights into convenience yields and implied volatility.
This study empirically tests Bitcoin’s transition from a growth-driven financial asset to a commodity-like asset. It integrates network effect and commodity pricing models, offering a unified framework for understanding Bitcoin’s lifecycle.
