--- language: [] license: other license_name: aion-edge-engine-license pipeline_tag: tabular-classification tags: - finance - trading - market-intelligence - indian-stock-market - risk-management - nifty - banknifty - sensex - indian-index-options - market-microstructure - trade-filter - evidence-based-trading - market-regime - pre-trade-gate - noise-filter - institutional-trading - nse - fno - commodity-trading - crude-oil - calibrated-confidence datasets: [] widget: [] --- # AION Edge Engine — Market Intelligence Layer A pre-trade evidence filter for Indian index options, commodities, and crude oil. Edge Engine does **not** tell you what to trade. It answers a narrower question: **does the current market state carry meaningful evidence, or should you stand down?** ## 1. Why This Exists Indian index options move fast. A short-horizon market state can look like a breakout, a reversal, or a trap, and mistaking noise for signal is one of the most expensive mistakes a trader can make. Edge Engine exists to reduce that mistake. It is designed for calibrated trust: it can stay silent when evidence is insufficient, and when it does produce a tradability judgment, it exposes audit fields instead of hiding everything behind one opaque score. ## 2. What Edge Engine Does Edge Engine converts intraday market state for NIFTY, BANKNIFTY, SENSEX, commodities, and crude oil into a structured pre-trade judgment: - **Tradable or not**, based on the current evidence profile - **Expected value context** and **confidence-bound telemetry**, exposed separately - **Underlying-specific routing**, because NIFTY, BANKNIFTY, SENSEX, and crude oil are different markets - **Audit-ready output**, preserving raw and enforced tradability fields It does not output a brokerage instruction. It outputs context. The difference matters. ## 3. Output Contract Every public field is intended to be auditable. No model weights, training data, or proprietary model internals are distributed through this repository. ```json { "edge_underlying": "nifty", "edge_ev": 0.1421, "edge_conf_low": 0.0314, "edge_conf_high": 0.0471, "edge_tradable": true, "edge_tradable_raw": true, "edge_motive": "model", "edge_model_key": "model:edge:nifty", "edge_shadow_mode": false, "edge_expiry_days": 7.0 } ``` | Field | Meaning | |---|---| | `edge_underlying` | Instrument family evaluated by the engine | | `edge_ev` | Expected-value context surfaced by the model | | `edge_conf_low` | Lower confidence-bound telemetry | | `edge_conf_high` | Upper confidence-bound telemetry | | `edge_tradable` | Enforced tradability after runtime policy gates | | `edge_tradable_raw` | Raw model tradability preserved for audit | | `edge_motive` | Why the judgment was produced, such as model or policy context | | `edge_model_key` | Underlying-specific model key used for inference | | `edge_shadow_mode` | Whether the output is live-enforced or shadow/paper-validation | | `edge_expiry_days` | Days-to-expiry context at inference time, when applicable | Raw tradability and enforced tradability are both preserved so integrators can audit when runtime policy differs from the raw model judgment. ## 4. Why Market-State Filtering Matters In Indian index options and commodity derivatives, very short-horizon market states can be distorted by spread changes, expiry behavior, auction spillover, and reaction loops. Edge Engine is designed around market-state evidence rather than urgency. When evidence is weak, the correct output may be to stand down. That restraint is the product: it helps suppress low-quality entries before they reach execution logic. ## 5. Intended Uses - **Pre-trade filtering:** run Edge Engine before existing entry logic to suppress signals during low-evidence market states - **Regime awareness:** monitor expected-value and confidence-bound telemetry to understand when conditions are improving or degrading - **Audit and post-trade analysis:** compare raw and enforced tradability decisions against later outcomes - **Paper validation:** use shadow-mode outputs to evaluate behavior before live enforcement ## 6. Out-of-Scope Uses - Blind execution as a standalone trade signal - Exact price prediction or directional forecasting - Compliance, suitability, or investment-advice decisions - Markets outside the supported Indian-market scope - Sub-market-state scalping or ultra-low-latency execution ## 7. Limitations - Edge Engine scores contextual tradability; it does not predict exact direction or magnitude. - Sudden structural breaks may not be fully reflected until the current market state is observed by the system. - Historical relationships can weaken during regime shifts, regulatory changes, or liquidity shocks. - Non-index coverage can carry wider confidence bounds than the most liquid index markets. - Shadow-mode outputs are for paper validation and audit, not live decision authority. ## 8. Deployment, Access, and Citation AION Edge Engine is an API-first system. Model weights are not publicly distributed. Production access is through the managed AION API. - API endpoint: https://api.aiondashboard.site/v1/edge - Dashboard: https://dashboard.aiondashboard.site/models/edge-engine - Registration: https://dashboard.aiondashboard.site/access/register - API gateway: https://dashboard.aiondashboard.site/systems/api-gateway - Organization: https://huggingface.co/AION-Analytics Freemium access includes selected AION market-intelligence surfaces. Edge Engine and broader multi-index access are available through API subscription. Requests are metered; over-quota requests are rejected by the managed API. If you integrate Edge Engine, monitor: - Whether stand-down decisions avoided chop, reversals, or false breakouts - Whether tradable decisions align with your own entry criteria - Differences between `edge_tradable_raw` and `edge_tradable` - Confidence-bound behavior over time ```bibtex @software{aion_edge_engine_2026, author = {AION Analytics}, title = {AION Edge Engine — Market Intelligence Layer for Indian Index Options}, year = {2026}, url = {https://huggingface.co/AION-Analytics/aion-edge-engine} } ```