The Endogenous Constraint: Hysteresis, Stagflation, and the Structural Inhibition of Monetary Velocity in the Bitcoin Network (2016–2025)

By Hamoon Soleimani

Rating

1494
Battle Count: 50

Relevance

5/10
The paper is moderately relevant to quantitative trading. While not directly proposing trading strategies, it provides important structural insights into Bitcoin's monetary dynamics that inform market microstructure understanding. The identification of regime-switching behavior (normal vs. shock) in velocity could inform volatility regime detection. The hysteresis findings suggest predictable recovery patterns after congestion events. The 'Stagflation Matrix' classification (price momentum vs. utility momentum) could serve as a market state indicator. The Crypto Multiplier inversion (hoarding vs. velocity) provides insight into demand-side dynamics. However, the paper is primarily macroeconomic/structural rather than focused on alpha generation or execution strategies.

Implementation Complexity

7/10
The econometric methodology is moderately complex, requiring expertise in threshold regression (Hansen 2000), IV estimation with GMM (Caner & Hansen 2004), bootstrap inference, and time series diagnostics. The data pipeline involves multiple sources (Blockchain.com, Bitcoin Visuals) with specific harmonization requirements. The composite TCI construction, Realized Capitalization derivation, and hysteresis topology analysis add implementation layers. However, the core regression is standard econometrics rather than ML/DL, and the open-source code repository reduces implementation burden. The main complexity lies in data acquisition, cleaning, and ensuring correct specification of the threshold search domain.

Reproducibility

4/5
The paper provides an open-source GitHub repository with Python source code for the Forensic Engine, Threshold Regression analysis, and Hysteresis topology generation. Data sources are clearly identified (Blockchain.com, Bitcoin Visuals). However, the data spans 2016-2025 and relies on specific provider endpoints that may change over time. The synthetic data generator is included. Econometric specifications are fully detailed with equations. The threshold search domain and bootstrap parameters are explicitly stated.

About this paper

Methodology: Threshold Regression with Instrumental Variable Estimation. Problem types: Regression, Causal Inference, Structural Break Detection, Time Series Analysis, Regime Classification, Economic Exclusion Quantification.

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