Introduction
Algorithmic trading has transformed financial markets. Python is the language of choice for building automated strategies. Whether stocks on SGX, crypto on Binance, or forex — Python gives you everything needed.
What Is Algo Trading?
Programs execute trades based on predefined rules — faster and without emotional bias. Common strategies:
- Trend Following — Buy above moving average, sell below
- Mean Reversion — Buy below average, expect bounce
- Arbitrage — Exploit price differences between exchanges
- Market Making — Profit from bid-ask spread
Python Libraries
- pandas — Price data manipulation
- numpy — Fast numerical computing
- ccxt — Unified API for 100+ crypto exchanges
- backtrader — Backtesting framework
- ta-lib — 200+ technical indicators
Moving Average Crossover Strategy
Classic beginner strategy: 20-day MA crosses above 50-day MA = buy. Crosses below = sell. Captures trends while filtering noise.
Backtesting
Never trade without testing. Key metrics: Total Return, Sharpe Ratio (above 1.0 good), Maximum Drawdown, Win Rate.
Live Trading with CCXT
CCXT provides unified access to Binance, Kraken, Bybit. For Singapore traders, check MAS regulatory compliance.
Risk Management
80% of success is risk management:
- Never risk more than 2% per trade
- Always use stop-losses
- Position size based on volatility (ATR)
- Paper trade 30+ days before going live
Crypto Tax in Singapore
Capital gains from crypto are generally not taxable for individuals in Singapore (2026). If trading is primary income, IRAS may classify as taxable. Keep records.
Common Mistakes
- Overfitting to historical data
- Ignoring transaction fees
- No risk management
- Emotional override of the system
Conclusion
Start with moving average crossover, backtest thoroughly, paper trade for a month, then small live trades. Build a systematic approach that compounds over time.
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