Typical timeline for a basic system
The time to build a simple trading algorithm varies with experience, complexity, and available tools. For someone with basic programming skills and access to data, a minimal viable strategy can be prototyped in days to a few weeks.
Stages and estimated durations:
- Idea and design (1–3 days): Define entry/exit rules, position sizing, and risk limits.
- Data collection and cleaning (2–7 days): Obtain historical data and prepare it for testing.
- Backtesting prototype (3–14 days): Implement rules in a backtest framework and run simulations, adjusting for costs and slippage.
- Paper trading and validation (2–8 weeks): Test in a simulated or small live environment to observe behavior in real markets.
- Deployment and monitoring (ongoing): Set up execution, monitoring, and alerts before scaling capital.
Factors that extend timelines:
- Lack of programming experience: Learning Python or another language adds time.
- Data complexity: Obtaining and cleaning tick-level or alternative data can be time-consuming.
- Robustness needs: Adding risk systems, logging, and redundancy increases development time.
Practical tips to accelerate progress:
- Use existing frameworks and libraries for backtesting and order execution.
- Start with daily or hourly strategies to avoid handling low-latency complexities.
- Reuse templates and incrementally add features as the strategy proves itself.
For beginners, patience is key: a simple, well-tested system built slowly is preferable to a rushed, fragile deployment.