Execution, monitoring and risk of an algorithm

Recommended phases

• A solid backtest with realistic costs
• Paper trading (demo or real-time data without money) for at least a few weeks
• Live with minimum size, to verify execution, slippage and real behaviour
• Gradual size increase only if results stay consistent with the test

How to execute

• An Expert Advisor in MQL5 on MetaTrader 5, running directly in the platform
• A Python script connected to MetaTrader 5 through the official library, or to broker APIs where available
• A virtual private server (VPS) to keep the program running without interruption

What can go wrong

• Differences between backtest and real execution: variable spreads, slippage, rejected orders
• Bugs that open repeated or oversized positions
• Connection loss with open positions
• Broker rule changes (leverage, hours, symbols)

Essential safety systems

• A stop loss on every position, sent to the broker together with the order
• A daily and weekly loss limit that shuts the algorithm down
• A maximum number of open positions and a maximum size
• A manual switch (kill switch) that is easy to use
• A log of every decision and order, to understand what happened

Monitoring

Regularly compare the live statistics with the backtest ones: win rate, average R, drawdown. If they drift significantly for a long period, stop the algorithm and investigate: the market may have changed or the test was optimistic.

Course conclusion

You have seen a whole path: structure, liquidity, zones, timing, trading model, statistical validation and automation. The real skill is not knowing the terms, but being able to measure whether an idea has an edge and manage risk when it doesn't. Go slowly, with capital you can afford to lose, and always keep a journal of your results.