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Finance · Automation · Python2025

ALGO TRADING BOT

Rules-based trading. No emotions. Just signals.

Role

Solo Developer

Stack
PythonPandasZerodha Kite Connect API
Status

Completed (Paper Trading)

Overview

I built an EMA (Exponential Moving Average) crossover strategy algorithmic trading bot integrated with Zerodha's Kite Connect API. It monitors live NSE market data, generates buy/sell signals from EMA crossover logic, places orders automatically, and logs all trades for performance analysis.

I validated it in paper trading mode using Zerodha's sandbox environment, and built a full backtesting suite on historical OHLC data using Pandas.

Screenshots

Key Features

EMA crossover signalsConfigurable fast/slow windows
Live data streamingZerodha Kite Connect WebSocket for live tick data
Automated ordersPlacement via Kite REST API
Trade loggingPer-session P&L tracking
BacktestingPandas backtesting on historical OHLC datasets

Tech Deep Dive

Kite Connect WebSocket streams live tick data for my selected instruments. Pandas computes rolling EMA on incoming price series in real-time. My signal logic: BUY when fast EMA crosses above slow EMA; SELL on reverse crossover. Paper trading mode intercepts order calls and routes them to a simulated execution log instead of live markets. All parameters are configurable: EMA windows, capital allocation, instrument selection.