Trend-following systems identify and ride sustained directional moves using rules-based approaches — moving average crossovers, breakout channels (Donchian, Keltner), and momentum filters. The strategy accepts many small losses for occasional outsized winners, relying on fat-tailed distribution of returns in financial markets.
Moving average crossover systems (dual, triple). Channel breakouts (Donchian 20/55-day). Volatility-adjusted position sizing (ATR-based). Turtle Trading rules. Time-series momentum (absolute momentum). Cross-sectional momentum (relative strength). Trend filter (200-day MA, ADX) for trade qualification.
Price closes above Donchian channel high (breakout entry). Fast MA crosses above slow MA with ADX > 20. Price above 200 EMA and RSI above 50 (momentum confirmation). New 52-week high with expanding volume.
Price breaks below trailing stop (chandelier exit or ATR-based). Opposite channel breakout. Moving averages cross back. Time-based exit if trade hasn't moved in defined period. Trailing stop: 2-3 ATR from highest close.
Daily, Weekly — trend-following historically performs best on daily and above. 4H can work for more active management.
Trend-following has long drawdown periods (30-50% of the time). Diversify across many uncorrelated markets to smooth the equity curve. Never second-guess the system — the edge comes from consistency over hundreds of trades, not from any single trade.
Backtesting applies a trading strategy to historical data to evaluate how it would have performed, while Monte Carlo simulation randomises the order of those historical trades across thousands of iterations to understand the range of possible outcomes. Together, these techniques provide both an estimate of expected performance and a probabilistic view of risk, drawdown, and return distributions.
Algorithmic trading uses computer programs to execute trades based on predefined rules — from simple moving average crossovers to complex machine learning models. The key advantage is removing emotion, achieving consistent execution speed, and backtesting strategies across decades of data before risking real capital.
Execution algorithms such as VWAP (Volume-Weighted Average Price) and TWAP (Time-Weighted Average Price) are automated strategies designed to execute large orders with minimal market impact. VWAP algorithms slice orders to match historical volume patterns throughout the day, while TWAP algorithms distribute orders evenly over time. These tools help institutional and advanced traders achieve better average execution prices on large positions.
Statistical arbitrage (stat arb) exploits temporary mispricings between correlated assets using quantitative models. Pairs trading — the simplest form — goes long the underperformer and short the outperformer when their price ratio deviates beyond historical norms, profiting as the spread reverts to the mean.