Building a Simple Yet Profitable Automated Trading Algorithm

In today’s fast-paced financial markets, algorithmic trading has become increasingly accessible to individual investors. While complex trading systems power major hedge funds, you can create a surprisingly effective automated trading strategy with just basic Python knowledge. This guide will walk you through building a profitable trading bot that can operate 24/7 without emotional bias.

Python offers powerful tools to create automated trading systems. Let’s explore how to build one that’s both effective and maintainable.

import yfinance as yf
import pandas as pd
import numpy as np
from datetime import datetime, timedelta

class SMACrossoverTrader:
    def __init__(self, symbol, cash=10000, short_window=20, long_window=50):
        self.symbol = symbol
        self.cash = cash
        self.position = 0
        self.short_window = short_window
        self.long_window = long_window
        self.trades = []
        
    def fetch_data(self, start_date, end_date):
        """Fetch historical data from Yahoo Finance"""
        stock = yf.Ticker(self.symbol)
        df = stock.history(start=start_date, end=end_date)
        return df
        
    def calculate_signals(self, df):
        """Calculate trading signals based on SMA crossover"""
        # Calculate short and long-term moving averages
        df['SMA_short'] =…