Algo Trading with AI: How to Build Your First Bot

Algorithmic trading used to be for Wall Street hedge funds. Now, with Python and AI, anyone can do it.

Disclaimer

This is for educational purposes only. Trading involves risk.

The Stack

1. Language: Python 3.10+
2. Data Source: Yahoo Finance (`yfinance`) or Alpha Vantage.
3. Broker API: Zerodha Kite or Upstox API.
4. AI Layer: GPT-5 for sentiment analysis.

Step 1: Fetching Data

```python import yfinance as yf

Get data for Tata Motors

data = yf.download("TATAMOTORS.NS", start="2024-01-01", end="2025-01-01") print(data.head()) ```

Step 2: Defining a Strategy (Moving Average Crossover)

```python data['SMA_50'] = data['Close'].rolling(window=50).mean() data['SMA_200'] = data['Close'].rolling(window=200).mean()

def signal(row): if row['SMA_50'] > row['SMA_200']: return "BUY" elif row['SMA_50'] < row['SMA_200']: return "SELL" return "HOLD"

data['Signal'] = data.apply(signal, axis=1) ```

Step 3: AI Sentiment Analysis

Price isn't everything. News matters.

```python def analyze_news(headline): prompt = f"Analyze the sentiment of this news for stock price: {headline}. Output: POSITIVE, NEGATIVE, or NEUTRAL." # Call GPT-5 API here... return sentiment ```

Conclusion

Combining technical analysis (Moving Averages) with fundamental analysis (AI Sentiment) gives you a powerful edge.