Basics of Stock Trading Bots

🌐 한국어

Stock trading bots succeed on solid pipelines, not flashy algorithms. Most bots fit four stages:

1. Data Collection

Fetch quotes, order book, executions in real-time or periodically:

import requests

def fetch_price(symbol: str) -> float:

    resp = requests.get(f"https://api.example.com/price/{symbol}", timeout=3)

    resp.raise_for_status()

    return resp.json()["last"]

2. Signal Generation

Turn collected data into buy/sell signals. Simple moving average crossover example:

def ma_cross_signal(prices: list[float], short: int, long: int) -> str:

    ma_short = sum(prices[-short:]) / short

    ma_long = sum(prices[-long:]) / long

    if ma_short > ma_long:

        return "BUY"

    if ma_short < ma_long:

        return "SELL"

    return "HOLD"

3. Order Execution

Send real orders per signal. Idempotency and retry logic are critical.

4. Risk Management

The most important stage. Enforce stops, position size limits, daily max-loss caps.

Backtests look good until you forget risk management. Then your account disappears fastest.

Next: backtesting framework design.

This is educational material, not investment advice. Investment losses are your responsibility.