<b>Measuring Cryptocurrency Maturity: A Network-Centric Framework Using Bitcoin and the Decker Comparative Maturity Equation (DCME)</b>
Creators: name: Decker, Nicolin
Publisher: name: figshare
Year: 2025
Subjects: classificationCode: 380107
subject: Financial economics
classificationCode: 380203
subject: Economic models and forecasting
classificationCode: 460401
subject: Cryptography
classificationCode: 461199
subject: Machine learning not elsewhere classified
classificationCode: 490508
subject: Statistical data science
classificationCode: 350202
subject: Finance
classificationCode: 350208
subject: Investment and risk management
classificationCode: 350203
subject: Financial econometrics
classificationCode: 380299
subject: Econometrics not elsewhere classified
classificationCode: 440404
subject: Political economy and social change
classificationCode: 440709
subject: Public policy

description: The development of cryptocurrency markets has introduced new financial models that challenge traditional valuation and maturity assessment methodologies. This dissertation presents the Decker Comparative Maturity Equation (DCME) as a framework for quantifying cryptocurrency maturity by integrating network effects, volatility dynamics, institutional influence, and macroeconomic scaling factors. Unlike conventional valuation models, DCME incorporates the Institutional Adjustment Factor (I_adj) to measure the dual role of institutional participation—balancing liquidity provision with risks of market centralization, price manipulation, and ETF-driven volatility suppression.The study applies quantitative modeling, econometric analysis, and machine learning techniques to assess cryptocurrency maturity across various financial conditions. By benchmarking Bitcoin and Ethereum against fiat currencies, traditional assets, and emerging blockchain networks, the research evaluates how institutional investment influences financial stability, market efficiency, and decentralization. The Comparative Maturity Ratio (CMR) is introduced as a metric to compare cryptocurrency resilience against traditional assets such as gold, government bonds, and the S&amp;P 500.Empirical results, derived from Monte Carlo simulations, vector autoregression (VAR), and historical case studies, demonstrate that institutional ownership beyond 40% increases market manipulation risks, suppresses organic network growth, and delays maturity acceleration. Meanwhile, decentralized adoption models, self-custody initiatives, and regulatory transparency enhance cryptocurrency resilience by mitigating systemic risks associated with ETF liquidity dominance and coordinated short-selling.The study also examines geopolitical and macroeconomic implications, including the role of cryptocurrencies in financial warfare, regulatory arbitrage, and capital flight from inflationary economies. As central banks develop CBDCs (Central Bank Digital Currencies), the research evaluates their potential to challenge Bitcoin’s monetary properties and affect global cryptocurrency adoption patterns.From a policy perspective, this dissertation provides recommendations for regulatory frameworks that preserve the benefits of institutional liquidity while preventing excessive centralization. Short-selling restrictions, institutional ownership caps, and enhanced ETF transparency are proposed as mechanisms to balance financial stability with the core principles of decentralized networks.Ultimately, this research positions DCME as an essential tool for investors, policymakers, and financial institutions to assess the maturity of digital assets in comparison to traditional markets. By establishing a quantitative, data-driven approach, this dissertation contributes to the academic discourse on cryptocurrency valuation, institutional risk assessment, and financial stability in the digital asset market.