btcgraphs

📊 Dashboard Updates daily

Charts and data generated automatically from live market data. Run ./update.sh (on pi@fridge) to refresh.

📄 Research Static

Completed research papers and analyses. These are standalone documents — not auto-regenerated.

🔬 Bitcoin Power Law Exponent (CNERVF Framework)

Why Bitcoin's exponent is ~5.7 (not 2.0 like most networks): three compounding network effects — network (2.0), security (1.7), market (2.0).

• bitcoin_power_law_exponent_theory.html — Full academic whitepaper (11 sections, MathJax)
• BITCOIN_EXPONENT_EXPLAINED.html — Plain-English FAQ version
• bitcoin_power_law_exponent_analysis.py — Automated validation script

📐 Scale Invariance

Tests whether Bitcoin's power law behavior is a universal property by comparing against 16+ assets including Internet users, broadband, McDonald's, and traditional stocks.

• scale_invariance_consolidated_report.html — Full report with live data (16 assets)
• SCALE_INVARIANCE_SYSTEM_SPEC.md — Technical spec
• scale_invariance_complete_system.py — Analysis script (live data)

📅 Genesis Date Hypothesis

Validates that January 3, 2009 (Genesis block) is the near-optimal starting date for Bitcoin power law modeling. Tested 147 start dates.

• genesis_date_sensitivity_analysis.html — Interactive 4-panel dashboard
• genesis_date_comparison.html — Genesis vs optimal date comparison
• genesis_day_hypothesis_analysis.md — Full report

🔮 LPPLS Bubble Detection

Log-Periodic Power Law Singularity model for identifying bubble tops and crash risks. Caution: extremely sensitive to window size.

• LPPLS_WINDOW_SENSITIVITY_REPORT.html — Window sensitivity report
• LPPLS_SENSITIVITY_SUMMARY.html — Executive summary
• LPPLS-model.html — Mathematical foundation
• lppls_ensemble_predictions.csv — Ensemble predictions (multi-window avg)

🌐 Power Law Social Networks

Shows that infection dynamics on scale-free social networks produce power law growth (R²~0.91-0.95), validating the clustered adoption hypothesis.

• POWER_LAW_SOCIAL_NETWORKS_FINAL_REPORT.html — Final report
• HYPOTHESIS_VALIDATED_SOCIAL_NETWORKS.md — Markdown version
• social_network_infection.py — Simulation script

📊 Clauset Power Law Testing

Rigorous Clauset-Shalizi-Newman (2009) methodology for proper power law validation. Addresses distribution-vs-trend distinction.

• CLAUSET_POWER_LAW_ANALYSIS_REPORT.md — Technical report
• DISTRIBUTION_VS_TREND_EXPLAINED.md — Plain-English explanation
• clauset_power_law_analysis.py — Analysis script

💰 Retirement Strategy

Long-term investment strategy based on power law projections. Accumulation, conversion, withdrawal, and tax optimization.

• RETIREMENT_STRATEGY_GUIDE.md — Complete guide (33KB)
• retirement/index.html — Interactive retirement calculator

🧰 Tools & Utilities

• btc_interactive_dashboard_js_full.html — Pure JS power law calculator (no install)
• btc_monthly_output/btc_price_monthly_overview.html — Monthly price breakdown by month
• investment_opportunities.html — Multi-asset scanner results (1,985+ assets)
• bracket_calculator.html — Bracket calculator tool
• multi_asset_powerlaw_scanner.py — Scanner script (run ./run_scanner.sh)

📁 Data Files

• btcpricehistory.csv — Daily BTC price history (updated by btc_price_graph.py) auto
• pl_coefficients.json — Power law coefficients (slope, intercept, floor, ceiling) auto
• difficultychartdata.csv — Mining difficulty history auto
• coinbase_ranking.csv — Coinbase app store ranking auto
• btc_intermediate_values.csv — Model attributes, predicted peaks & winter lows auto
• btc_peaks.csv — Identified peak events static
• dips.csv — Historical dip events static
• cleaned_btc_price_predictions.csv — Analyst price prediction sources static
• r-bitcoin-subscribers-history.csv — Reddit subscriber history static

🗄 Archived Not regenerable

One-off analysis outputs, experiments, and historical artifacts. Kept for reference but not regenerable from current scripts.