Prerequisites
Before diving into algorithmic trading, you'll need to develop skills in several key areas. Don't be intimidated—you don't need to be an expert in everything, but a solid foundation will accelerate your learning.
Programming Skills
You'll need proficiency in at least one programming language. Python is the most popular choice due to its simplicity and extensive libraries for data analysis and trading. Other options include R for statistical analysis, C++ for high-frequency trading, and C# for platforms like QuantConnect.
# Calculate moving averages
short_ma = prices.rolling(window=10).mean()
long_ma = prices.rolling(window=50).mean()
# Generate signals
signals = pd.DataFrame(index=prices.index)
signals['signal'] = 0
signals.loc[short_ma > long_ma, 'signal'] = 1 # Buy signal
signals.loc[short_ma < long_ma, 'signal'] = -1 # Sell signalMarket Knowledge
Understanding how markets work is fundamental. You should be familiar with:
- Asset classes — Stocks, ETFs, futures, forex, and cryptocurrencies
- Order types — Market orders, limit orders, stop orders, and their execution
- Market microstructure — How orders are matched, bid-ask spreads, and liquidity
- Trading costs — Commissions, slippage, and their impact on strategy performance
Mathematics & Statistics
A basic understanding of statistics is essential for developing and evaluating trading strategies:
- Descriptive statistics (mean, standard deviation, correlation)
- Probability distributions and hypothesis testing
- Time series analysis fundamentals
- Basic calculus for understanding indicators
Choosing a Trading Platform
Your choice of platform depends on your goals, technical skills, and capital. Here are the main options:
| Platform Type | Best For | Examples |
|---|---|---|
| Cloud-Based | Beginners, no infrastructure management | Wick, QuantConnect, Alpaca |
| Local Frameworks | Custom development, full control | Backtrader, Zipline, LEAN |
| Broker APIs | Direct market access, experienced traders | Interactive Brokers, TD Ameritrade |
Your First Strategy: Keep It Simple
Begin with a straightforward strategy that you fully understand. The classic moving average crossover is an excellent starting point:
Moving Average Crossover Rules
- Buy Signal: When the short-term moving average crosses above the long-term moving average
- Sell Signal: When the short-term moving average crosses below the long-term moving average
- Parameters: Short MA = 10 periods, Long MA = 50 periods (adjust based on your timeframe)
This strategy won't make you rich, but it teaches you the complete workflow: data handling, signal generation, backtesting, and performance evaluation.
Risk Management From Day One
Even as a beginner, establish good risk management habits:
- Never risk more than 1-2% of your capital on any single trade
- Start with paper trading to validate your strategy without risking real money
- Keep detailed records of all trades and decisions for later analysis
- Set realistic expectations — consistent 15-20% annual returns is excellent
Don't jump straight to live trading. Spend at least 3-6 months paper trading and backtesting before risking real capital.