Projects

Trend following

EMA cross

A simple algorithm built on QuantConnect, designed to capitalise on short- to medium-term price trends using exponential moving averages across different time frames. It identifies trend reversals and entry and exit points based on momentum shifts.

  • QuantConnect
  • Python
  • Volatility sizing
EMA cross

Universe

Applied to highly liquid US equities, focusing on large caps to ensure smooth execution and minimal slippage. Its modular design means it can be adapted to other asset classes and equity universes.

Trading logic

The strategy tracks two EMAs, one long-term (slow), one short-term (fast). A buy signal triggers when the fast EMA crosses above the slow EMA, indicating a potential upward trend. A sell signal triggers when it crosses below, signalling a downward trend.

Position sizing and risk

This implementation uses volatility-adjusted position sizes. A trailing stop locks in profits during favourable trends, and risk per trade is controlled to avoid overexposure.

A maximum drawdown limit ensures the algorithm exits all positions if performance dips beyond a pre-specified threshold.