aion-edge-engine / README.md
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---
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}
}
```