Dataset for Measuring Cryptocurrency Maturity: A Network-Centric Framework Using Bitcoin and the Decker Comparative Maturity Equation (DCME)

This dataset supports the research Measuring Cryptocurrency Maturity: A Network-Centric Framework Using Bitcoin and the Decker Comparative Maturity Equation (DCME)" by Nicolin Decker (2025). It provides real-time and historical data for analyzing cryptocurrency maturity, institutional liquidity, and systemic risk using the DCME framework. The dataset supports financial stability research, regulatory oversight, and institutional risk modeling, validated through Monte Carlo simulations, EGARCH/TGARCH volatility modeling, and institutional ownership analytics.

Backtesting confirms DCME’s predictive accuracy in identifying liquidity risks preceding major market disruptions, including ETF-driven volatility spikes.

Contents:
- Supplementary Documentation.
- DCME Collection & API Integration: API-based access to Glassnode, CoinGecko, Chainalysis, SEC Filings, and Bloomberg.
- DCME Backtesting System: Python-based software for historical validation and institutional risk modeling using Monte Carlo simulations.
- DCME Calculation Software: Python-based implementation for EGARCH/TGARCH volatility modeling and liquidity risk assessments.
- Web-Based DCME Calculator: A tool for computing DCME maturity scores with API-driven data.

Applications:
- Market Maturity Analysis: Bitcoin, Ethereum, and traditional assets.
- ETF Risk Assessment: Institutional ETF impact on volatility and liquidity.
- Stress Testing: Simulating institutional exits and liquidity crises.
- Regulatory Policy Development: Supporting Basel III, SEC, and IMF risk analysis.

Primary Data Sources (API-Based Access):
- Cryptocurrency Data: Glassnode, CoinGecko, Chainalysis, Binance
- Institutional & ETF Data: SEC Filings (13F Reports), BlackRock, Grayscale, Fidelity
- Macroeconomic Indicators: Federal Reserve (FRED), IMF, World Bank
- Traditional Asset Benchmarks: S&P 500, Gold, Bonds, Treasury Yields (Bloomberg API)

Citation & License:
Users must cite the original thesis and developer:

Decker, Nicolin (2025). Measuring Cryptocurrency Maturity: A Network-Centric Framework Using Bitcoin and the Decker Comparative Maturity Equation (DCME). Mendeley Data.

Derivative works must embed:

Decker Comparative Maturity Equation (DCME) Deployment System. Developed by Nicolin Decker. Based on the thesis: "Measuring Cryptocurrency Maturity," 2025. Licensed under MIT.

Software Versioning & Terms:
This dataset is linked to DCME Deployment System v1.0. Future updates will expand cryptocurrency adoption metrics and volatility-adjusted maturity models. The dataset relies on API-based data retrieval, requiring users to configure API keys and data requests.

The DCME Backtesting System (Python-based) enables historical validation and stress testing, allowing researchers to test financial stability using Monte Carlo simulations and maturity scoring.