Core strategy types
– Trend following: Enter positions that align with a clearly established trend using indicators like moving averages, ADX, or price action breakouts.
Trend strategies work best in markets with persistent directional moves and require patience to let winners run.
– Momentum trading: Focus on assets showing strong relative strength over multiple timeframes. Momentum setups often use volume confirmation and can be paired with trailing stops to capture extended moves.
– Mean reversion: Buy oversold and sell overbought conditions when price tends to revert to a mean. Tools include RSI, Bollinger Bands, and z-score on returns. Mean reversion generally performs better in range-bound markets.
– Pairs and statistical arbitrage: Use correlation and cointegration to identify relative value trades between two related instruments.
Risk comes from structural correlation breakdowns, so hedging and dynamic rebalancing are critical.
– Option strategies: Use covered calls to generate income, protective puts to manage downside, or spreads to express directional views with limited risk. Options require attention to implied volatility and time decay.
Risk management: the trade decides survival
– Position sizing: Define risk per trade as a fixed percent of capital (commonly 1–3%) or use volatility-adjusted sizing. Regardless of method, size must preserve capital through losing streaks.
– Stop-loss and exits: Predefine stop levels and profit targets. Consider using volatility-based stops (e.g., ATR) and trailing stops to protect gains.
– Diversification and correlation: Avoid over-concentration in correlated positions. Construct a portfolio of strategies and assets that reduce drawdown risk.
– Costs and slippage: Factor commission, spread, and market impact into expected returns—high turnover strategies can be eroded by fees.
Testing and robustness
– Backtesting: Test on quality data with realistic assumptions for costs and slippage. Beware of look-ahead bias and data snooping.
– Walk-forward and out-of-sample testing: Validate stability by testing strategy variations on unseen data and adjusting parameters minimally.
– Scenario testing and stress tests: Simulate drawdowns, volatility spikes, and liquidity stress to understand behavior under adverse conditions.
Execution and operational considerations
– Timeframes and multiple horizons: Combine longer-term bias with shorter-term timing. For example, use daily charts to set trend direction and intraday charts for entries.
– Automation and monitoring: Automate execution for speed and discipline where appropriate, while keeping manual oversight for unusual market events.
– Journaling and review: Record each trade’s rationale, outcome, and lessons. Periodic review helps prune underperforming setups and improve edge.
Psychology and discipline
Emotional control matters as much as edge. Use rules-based decision-making, predefined risk limits, and routine checklists to reduce impulsive behavior. Accept that losses are part of any strategy—focus on process, not individual outcomes.
Practical checklist before trading
– Have a documented rule set for entry, exit, sizing, and risk limits
– Backtest and validate on out-of-sample data
– Account for costs and liquidity
– Keep a trade journal and review monthly
– Limit position size relative to total portfolio risk
A thoughtful combination of a clear edge, disciplined risk controls, and rigorous testing is the foundation of sustainable trading. Start small, measure objectively, and iterate until you have a repeatable process that fits your capital, temperament, and target markets.