Update README for Space description

README.md

@@ -1,26 +1,39 @@
----
-tags:
-- ml-intern
----
+# AlphaForge x K2 Think V2 — Institutional Quant Platform
+
+A **10-module institutional-grade quantitative trading system** built for the **Build with K2 Think V2 Challenge** by MBZUAI.
 
-# Premchan369/alphaforge-k2think
+**Live Space:** https://huggingface.co/spaces/Premchan369/alphaforge-k2think
 
-<!-- ml-intern-provenance -->
-## Generated by ML Intern
+## 10 Modules
 
-This model repository was generated by [ML Intern](https://github.com/huggingface/ml-intern), an agent for machine learning research and development on the Hugging Face Hub.
+| Module | Feature | Institution Equivalent |
+|--------|---------|------------------------|
+| 📈 Technical | 18+ indicators, candlestick, Bollinger, Ichimoku, VWAP, ADX, MFI, OBV | Bloomberg Terminal |
+| ⚡ Backtest | 5 strategies, ATR sizing, equity curves, drawdown, trade logs | Jane Street backtest engine |
+| 💼 Portfolio | Markowitz MPT, 10K-portfolio MC, efficient frontier, Sharpe max | AQR, D.E. Shaw |
+| 📐 Options | Black-Scholes + full Greeks (ΔΓΘVΡ), scenario P/L, 6-panel charts | Goldman Sachs derivatives desk |
+| 🔗 Pairs | Cointegration, OLS hedge ratio, OU half-life, Z-score signals | Two Sigma stat arb |
+| 🪙 Crypto Arb | Cross-exchange spread heatmap, funding rate concepts | Jump Trading |
+| 🛡️ Risk Engine | VaR 95/99, stress testing, correlation breakdown | Bridgewater risk |
+| 📰 Sentiment | Composite gauge (-100 to +100), keyword extraction | Citadel NLP |
+| 🌍 Macro | Cross-asset regime dashboard (S&P, 10Y, Gold, Oil, DXY, BTC) | Bridgewater All Weather |
+| 🤖 K2 AI | Chain-of-thought: entry/stop/target, catalyst calendar, contrarian | MBZUAI K2 Think V2 |
 
-- Try ML Intern: https://smolagents-ml-intern.hf.space
-- Source code: https://github.com/huggingface/ml-intern
+## Setup
 
-## Usage
+1. Add `K2_API_KEY` in Space Settings → Repository Secrets
+2. No key required — all quant modules work standalone
 
-```python
-from transformers import AutoModelForCausalLM, AutoTokenizer
+## Stack
 
-model_id = 'Premchan369/alphaforge-k2think'
-tokenizer = AutoTokenizer.from_pretrained(model_id)
-model = AutoModelForCausalLM.from_pretrained(model_id)
-```
+- yfinance / synthetic fallback (market data)
+- Plotly (Bloomberg Terminal aesthetic)
+- NumPy/Pandas (vectorized quant math)
+- K2 Think V2 (MBZUAI reasoning)
 
-For non-causal architectures, replace `AutoModelForCausalLM` with the appropriate `AutoModel` class.
+## Data Notice
+
+When Yahoo Finance rate-limits shared IPs (common on HF Spaces), the app automatically falls back to **deterministic synthetic data** seeded by ticker + date. Same ticker = same realistic data on the same day. All indicators, backtests, and optimizations work normally.
+
+---
+*Built by Premchan | Build with K2 Think V2*