The Strategy: Worlds Like Fire

In this video, I demonstrate a live paper trade on Bank Nifty using my custom-built algorithmic trading system. The trade captured nearly a 100-point move, with an entry at 55,146 and a target hit at 55,048.

How the Algo Works

The Strategy Brain: TrendAnalyzer
The system processes 1-minute OHLC candles using the Impulse System. It requires alignment between EMA inertia and MACD histogram momentum before generating a trading signal.

Multi-Timeframe Filter
Before executing a 1-minute entry, the bot verifies a bearish bias on the 5-minute timeframe. Condition: price is below the 5-minute EMA-21.

Pattern Recognition
The system uses patterns.py to detect high-probability setups such as Shooting Stars and Bearish Engulfing patterns at key levels like VWAP and EMA-9.

Risk Control
Every trade is protected by an ATR-based trailing stop loss using 1.5 times ATR, along with a fixed profit target of 2.0 times ATR. The RiskEngine acts as a global circuit breaker to ensure capital preservation.

The Tech Stack
Language: Python 3.10+ (AsyncIO for low latency)
Broker: Upstox V3 WebSocket API
Database: MongoDB for audit trails and Redis for real-time dashboard syncing
Indicators: pandas_ta and NumPy

Follow along on this journey as I build, test, and document an automated trading system completely from scratch. No hype, just code and live logs.

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