Let's discuss how to build an algo trading system from idea to implementation. We'll break it down into stages:
1. The Idea. Use an example of reversal after the news. Get intuition by looking at charts. Consider news sources (e.g. Twitter vs Reuters), scheduled (FOMC) vs surprise news, and indicator changes (e.g. volume spikes).
2. Formalize the idea. Use historical data (e.g. past year of 1-min SPY data) or simulations (e.g. random walk with parameters that match your idea). Decide how to capture the signal (e.g. classify as news if volume > 3 std dev in 1 min). Then bet on reversal after 2% price move (entry limit order 1% from current).
3. Test and refine. Calculate stats (e.g. 60% win rate, 1.5:1 profit ratio). Backtest the idea (e.g. last 5 years, 1-min SPY, $10K starting capital). Tweak parameters to maximize return/risk metrics. Build a basic live system (e.g. paper trade to check fills, real-time data handling). Iterate until stat edges hold.
4. Final system. Choose robust architecture (e.g. low-latency C feedhandler execution algo). Add monitoring (e.g. strategy KPI dashboard). Minimize data/execution latency. Refine for months (e.g. add machine learning to boost edge).
So the key is iteration - keep building, testing and refining your idea until it becomes a robust, monitored trading system with a demonstrable edge!