# Midgley LLM Energy Price Forecasting Engine — Technical Breakdown & Math Audit **Log Timestamp:** `2026-10-31 02:17:07` **Run Mode:** `LIVE_PROSPECTIVE` **Primary Event Trigger:** Daily Forecast Batch Execution (2026-10-31 02:17:07) --- ## 1. Execution Audit & Trigger Headline Context - **Headline Trigger:** Daily Forecast Batch Execution (2026-10-31 02:17:07) - **Active Ingested News Links:** - [NYMEX RBOB Futures & WTI Crude Spot Energy Commodity Benchmark Refresh](https://www.cmegroup.com/markets/energy/refined-products/rbob-gasoline.html) (CME Group / NYMEX) - [NOAA National Weather Service Multi-Basin Severe Weather & Freeze Warning Ingestion](https://www.weather.gov) (NOAA NWS Storm Alert) - [Executive Policy Feed & OPEC Weekend Open Price Gap Intelligence](https://www.bloomberg.com/energy) (Bloomberg Market Wire) --- ## 2. Ingested Factor Score Vector (Exact Run Values) - **Supply Disruption Score ($S$):** `0.10` - **Price Pressure Shock ($\Delta P$):** `+0.02` - **Geopolitical Risk Score ($G$):** `0.15` - **Demand Sentiment Score ($D$):** `0.00` - **OPEC Action Score ($O$):** `0.00` - **Decay Half-Life ($t_{1/2}$):** `5.0 days` --- ## 3. Step-by-Step Exponential Memory Decay Math for This Run Exponential Memory Decay Model Equation: $$M_t = M_{t-1} \cdot e^{-\frac{\ln(2)}{t_{1/2}}} + S_t$$ ![Exponential Decay Formula](https://latex.codecogs.com/svg.latex?M_t%20%3D%20M_%7Bt-1%7D%20%5Ccdot%20e%5E%7B-%5Cfrac%7B%5Cln%282%29%7D%7Bt_%7B1/2%7D%7D%7D%20%2B%20S_t) Decay Parameter Substitutions: - Decay constant: $\lambda = \frac{\ln(2)}{5.0} = 0.13863 \text{ day}^{-1}$ - Daily retention multiplier: $\gamma = e^{-0.13863} \approx 0.87055$ Numeric Retention Schedule for This Run ($M_0 = 0.1000$): - **Day 0 (Initial Shock Target)**: $M_0 = 0.1000$ - **Day 1 Decayed Shock**: $M_1 = 0.1000 \times 0.87055 = 0.0871$ - **Day 2 Decayed Shock**: $M_2 = 0.1000 \times (0.87055)^2 = 0.0758$ - **Day 3 Decayed Shock**: $M_3 = 0.1000 \times (0.87055)^3 = 0.0660$ - **Day 4 Decayed Shock**: $M_4 = 0.1000 \times (0.87055)^4 = 0.0574$ - **Day 5 (Target Horizon)**: $M_5 = 0.1000 \times 0.50000 = 0.0500$ (50.0% residual event memory) --- ## 4. Regional Metro Calibration Equations (Substituted Run Values) - **National Wholesale**: $P = \$3.114 + (-\$0.009) = \$3.050\text{/gal}$ (Delta: -\$0.009/gal, -0.28\%) - **Tulsa, OK Retail**: $P = \$3.803 + (+\$0.000) = \$3.803\text{/gal}$ (Delta: +\$0.000/gal, 0.00\%) - **Newark, DE Retail**: $P = \$3.992 + (-\$0.013) = \$3.910\text{/gal}$ (Delta: -\$0.013/gal, -0.32\%) - **Cincinnati, OH/KY**: $P = \$4.275 + (+\$0.000) = \$4.275\text{/gal}$ (Delta: +\$0.000/gal, 0.00\%) - **Greenville, NC Retail**: $P = \$3.705 + (+\$0.023) = \$3.642\text{/gal}$ (Delta: +\$0.023/gal, +0.63\%) - **Charlotte, NC Retail**: $P = \$3.447 + (-\$0.016) = \$3.362\text{/gal}$ (Delta: -\$0.016/gal, -0.46\%) - **Port St. Lucie, FL Retail**: $P = \$3.969 + (-\$0.013) = \$3.880\text{/gal}$ (Delta: -\$0.013/gal, -0.34\%) - **Chicago, IL/IN Retail**: $P = \$4.949 + (+\$0.000) = \$4.949\text{/gal}$ (Delta: +\$0.000/gal, 0.00\%) - **Houston, TX Retail**: $P = \$3.671 + (+\$0.000) = \$3.671\text{/gal}$ (Delta: +\$0.000/gal, 0.00\%) - **Los Angeles, CA Retail**: $P = \$6.021 + (+\$0.000) = \$6.021\text{/gal}$ (Delta: +\$0.000/gal, 0.00\%) - **Denver, CO Retail**: $P = \$4.292 + (+\$0.000) = \$4.292\text{/gal}$ (Delta: +\$0.000/gal, 0.00\%) - **New York, NY Retail**: $P = \$4.405 + (+\$0.000) = \$4.405\text{/gal}$ (Delta: +\$0.000/gal, 0.00\%) - **Oakland, CA Retail**: $P = \$5.965 + (+\$0.000) = \$5.965\text{/gal}$ (Delta: +\$0.000/gal, 0.00\%) *(includes CA statutory CARB excise, Cap-and-Trade & LCFS fee overhead of $0.953/gal)* - **SF Bay Area Region**: $P = \$6.003 + (-\$0.021) = \$5.875\text{/gal}$ (Delta: -\$0.021/gal, -0.35\%) *(includes CA statutory CARB excise, Cap-and-Trade & LCFS fee overhead of $0.953/gal)* - **ULSD Distillate Crack Engine (WIP)**: $P_{\text{ULSD}} = \$2.850\text{/gal}$, Distillate Crack Spread = $\$0.742\text{/gal}$, 3-2-1 Crack Margin = $\$0.685\text{/gal}$ *(Experimental Work-In-Progress undergoing multi-week feedback loop empirical evaluation)* --- ## 5. NOAA SPC-Style Technical Discussion & Narrative Synopsis ### Executive Forecast Summary SUMMARY FOR RUN [2026-10-31 02:17:07]: Baseline daily batch market conditions prevail with minimal exogenous shocks. Ingested supply disruption S=0.10 and geopolitical risk G=0.15 yield a price pressure vector of ΔP=+0.02/gal. Primary trigger: 'Daily Forecast Batch Execution (2026-10-31 02:17:07)'. The standardized Ridge model calculates stable wholesale futures re-anchoring, with Day-5 residual event memory decaying from M₀=0.1000 down to M₅=0.0500. ### Technical Discussion & Market Dynamics TECHNICAL DISCUSSION & MARKET DYNAMICS FOR THIS RUN: 1. Qualitative Shock Integration & Decay Dynamics: During execution 2026-10-31 02:17:07 (Mode: LIVE_PROSPECTIVE), primary event trigger 'Daily Forecast Batch Execution (2026-10-31 02:17:07)' was processed by the extraction engine. Inspiration stream ingested 3 headline bulletins from sources (NOAA NWS Storm Alert, CME Group / NYMEX, Bloomberg Market Wire). Ingested factor vector: Supply Disruption S=0.10, Price Pressure ΔP=+0.02, Geopolitical Risk G=0.15. Exponential decay constant λ = ln(2)/5.0 = 0.13863 day⁻¹ dictates daily retention factor γ ≈ 0.87055. Initial shock retention schedule for this specific execution: - Day 0: M₀ = 0.1000 - Day 1: M₁ = 0.0871 - Day 5: M₅ = 0.0500 (50.0% residual memory acting on Day-5 target horizon). 2. Substituted Regional Metro Price Calibrations: The base commodity forecast was calibrated across all 8 modeled metro locales for this run: • National Wholesale: $3.050/gal ($-0.009/gal, -0.28%) • Tulsa, OK Retail: $3.803/gal ($0.000/gal, 0.00%) • Newark, DE Retail: $3.910/gal ($-0.013/gal, -0.32%) • Cincinnati, OH/KY: $4.275/gal ($0.000/gal, 0.00%) • Greenville, NC Retail: $3.642/gal (+$0.023/gal, +0.63%) • Charlotte, NC Retail: $3.362/gal ($-0.016/gal, -0.46%) • Port St. Lucie, FL Retail: $3.880/gal ($-0.013/gal, -0.34%) • Chicago, IL/IN Retail: $4.949/gal ($0.000/gal, 0.00%) • Houston, TX Retail: $3.671/gal ($0.000/gal, 0.00%) • Los Angeles, CA Retail: $6.021/gal ($0.000/gal, 0.00%) • Denver, CO Retail: $4.292/gal ($0.000/gal, 0.00%) • New York, NY Retail: $4.405/gal ($0.000/gal, 0.00%) • Oakland, CA Retail: $5.965/gal ($0.000/gal, 0.00%) • SF Bay Area Region: $5.875/gal ($-0.021/gal, -0.35%) Largest upward shift for this run: Greenville, NC Retail at $3.642/gal (+0.023/gal). Largest downward shift for this run: SF Bay Area Region at $5.875/gal (-0.021/gal). California locations (Oakland & SF Bay Area) incorporate statutory $0.953/gal CARB excise, Cap-and-Trade, and LCFS fee overhead on top of the base commodity calibration. ### Forecast Uncertainty & Counterfactual Catalysts FORECAST UNCERTAINTY & CATALYST SCENARIOS FOR THIS RUN: Evaluated tail-risk catalysts specific to execution [2026-10-31 02:17:07]: • Execution Context: Run type 'LIVE_PROSPECTIVE' triggered by 'Daily Forecast Batch Execution (2026-10-31 02:17:07)'. Overall price pressure vector sits at ΔP=+0.02/gal. • Weather & Convective Risk: SPC convective outlook and NOAA zip-code alerts for Tulsa (74101), Newark (19711), Cincinnati (45202), Carolinas (27834/28202), and Oakland (94612) map zero active severe tornado trips for this forecast run. • Maritime & Geopolitical Exposure: Geopolitical risk score G=0.15. Counterfactual Strait of Hormuz blockade would inject +$0.109/gal (+2.88%) to current baseline. • Executive Social Media Gap Analysis: If weekend executive social media posts emerge while commodity exchanges are closed, Monday morning open price gap volatility is projected at 1.42x normal intraday range. • Climatological Plausibility Horizon: [SEASONALLY_PLAUSIBLE] Category 3 Atlantic Hurricane Landfall & Tar River Flooding; [SEASONALLY_PLAUSIBLE] Category 3 Atlantic Hurricane & Port Everglades Marine Shutdown; [SEASONALLY_PLAUSIBLE] PG&E PSPS Red Flag Wildfire Power Shutoff & Refinery Blackout; [SEASONALLY_PLAUSIBLE] Santa Ana Red Flag Wildfire & SCE/LADWP Grid PSPS Curtailment --- ## 6. Advanced Quantitative Feature & Physical Data Formulas ### 3-2-1 Refining Crack Spread Formula (Issue #169) $$\text{Crack}_{321} (\$/\text{bbl}) = \frac{2 \times (P_{\text{RBOB}} \times 42) + 1 \times (P_{\text{HO}} \times 42) - 3 \times P_{\text{WTI}}}{3}$$ ### Stacking Ensemble Quantile Prediction Bounds (Issue #170) $$P_{10} = P_{50} - 1.2815\sigma, \quad P_{90} = P_{50} + 1.2815\sigma$$ ### Dynamic Volatility-Gated Persistence Blending (DV-GPB) (Issue #214) $$\lambda_{\text{vol}} = \frac{1}{1 + e^{-200.0 \cdot (\sigma_{14\text{d}} - 0.015)}}, \quad \hat{y}_{t+5} = \lambda_{\text{vol}} \hat{y}_{\text{model}} + (1 - \lambda_{\text{vol}}) y_t$$ ### Empirical Residual 95% Confidence Intervals (Issue #214) $$\text{CI}_{95\%} = \hat{y}_{t+5} \pm 1.96 \cdot \sigma_{\text{residual, 30d}}(r)$$ ### USGS 3D Hypocentral Attenuation & Ground Shaking Intensity (Issue #55) $$R = \sqrt{d^2 + h^2}, \quad w(R) = \frac{1}{1 + (R/35)^2}, \quad I = 10^{M - M_{\text{base}}} \times w(R)$$ ### USGS Hydrological Streamflow & Barge Bottleneck Index (Issue #56) $$\text{Index}_{\text{barge}} = \max\left(0, \min\left(1, \frac{\text{Gage}_{\text{threshold}} - \text{Gage}_t}{\text{Gage}_{\text{threshold}} - \text{Gage}_{\text{min}}}\right)\right)$$ ### Multi-Feed AQI Standardized Flaring Outage Detection Z-Score (Issue #54) $$Z_{\text{PM2.5}} = \frac{\text{PM2.5}_t - \mu_{30\text{d}}}{\sigma_{30\text{d}}}, \quad Z_{\text{SO2}} = \frac{\text{SO2}_t - \mu_{30\text{d}}}{\sigma_{30\text{d}}}$$ ### EPA Ozone & Statutory Seasonal RVP Compliance Surcharge (Issue #73) $$\text{Surcharge}_{\text{RVP}} = \Delta \text{Spread}_{\text{Summer Blend}} + 0.040 \cdot \mathbf{1}_{\text{AQI}_{\text{O3}} \ge 101}$$ ### U.S. Census Commuter Inelastic Demand Score (Issue #75) $$\text{Score}_{\text{inelastic}} = \frac{\text{DriveAlone} + \text{Carpool}}{\text{TotalCommuters}} \times (1 - \text{TransitIndex})$$ ### Treasury 10Y-2Y Term Spread & Momentum Delta (Issue #66) $$\text{Spread}_{10\text{Y}-2\text{Y}} = Y_{10\text{Y}} - Y_{2\text{Y}}, \quad \Delta \text{Spread}_{5\text{d}} = \text{Spread}_t - \text{Spread}_{t-5}$$ ### Qlib Symbolic Alpha Factor Information Coefficient (Issue #127) $$IC_t = \text{Corr}(f_t, r_{t+h}), \quad IC_{IR} = \frac{\mu(IC)}{\sigma(IC)}$$ ### Multi-Horizon Forecast Scoreboard Accuracy (Issue #209) $$\text{MAE}_H = \frac{1}{N_H} \sum_{i=1}^{N_H} |\hat{y}_{i, H} - y_{i, H}|, \quad H \in [1\text{d}, 2\text{d}, 3\text{d}, 4\text{d}, 5\text{d}]$$ --- *Report generated automatically by Midgley Dashboard Generator Engine at 2026-10-31 02:17:07.*