FMZ Beginner Guide to Building and Operating Trading Strategies
Summary
This beginner manual explains how to build automated trading strategies on the FMZ platform, using JavaScript examples while noting support for other languages. It walks through the strategy lifecycle, polling market data, configurable parameters, interactive controls, common market and account APIs, and a sample grid-strategy structure. It also describes debugging through code tools, historical backtests, and simulated trading, with practical guidance on logging, handling empty API responses, and avoiding excessive request rates.
The material is an implementation tutorial rather than evidence for a profitable strategy. Its examples illustrate platform mechanics, including manual order controls and configurable grid levels, but do not establish that these approaches work across markets. The guide warns that backtest results may not match live execution and that over-optimizing parameters can produce poor real-world behavior. It recommends testing in simulation before live use, starting with limited capital, and adding risk controls. Platform APIs and interface details may also change, so users should verify current documentation before relying on specific examples.
Key ideas
- FMZ strategies commonly use a repeating loop to fetch data, evaluate conditions, and act.
- Parameters let users adjust strategy behavior without editing the code.
- Interactive controls can pass manual commands or values to a running strategy.
- Backtests and simulated trading help check logic, but do not guarantee live results.
- The guide emphasizes checking API responses, pacing requests, and managing live trading risk.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.