Strategies

How to Set Up a Trading Bot, Step by Step

Astron Team · 09/24/2026 · 6 min read

A trading bot is, at its core, a set of rules written in code that automatically buys and sells assets when certain conditions are met. The promise is tempting: trading without needing to sit in front of the screen and without letting emotion interfere with the decision. But building a bot that actually works takes more planning than most people imagine.

This guide shows the steps to set up a trading bot, from defining the strategy to final testing, and the precautions that keep it from becoming a money-losing machine on autopilot.

Step 1: define the strategy in clear rules

Before thinking about code, write your strategy in simple, objective sentences. For example: buy when the 9-period moving average crosses above the 21-period average, and sell when the price drops 2% below the entry price. If you can't describe the strategy without ambiguity in words, the bot won't be able to execute it consistently either.

At this stage, also define the three pillars of any automated system: the entry condition, the profit-exit condition, and the loss-exit condition (the stop). A bot with no defined stop isn't an automated strategy, it's an automated risk.

Step 2: choose the platform and language

There are basically two paths: use a visual builder, where you assemble the logic with blocks and menus, without writing code, or program the bot in a language like Python, which gives more freedom but requires technical knowledge. For beginners, visual platforms are faster for validating a simple idea before investing time in programming.

Testing the logic before automating

A common mistake is jumping straight into programming the bot without first manually checking, on a historical chart, whether the strategy would have worked over the past few weeks. This quick manual test, done with your own eyes, avoids wasting time automating a rule that already failed on paper.

Step 3: run the backtest with historical data

A backtest is the process of running your strategy over past price data to see how it would have behaved. A well-done backtest accounts for trading costs, the bid-ask spread, and a period long enough to include both calm market moments and high-volatility ones.

Imagine a bot tested with R$ 10,000 in starting capital, risking 2% per trade (R$ 200). Over 100 simulated trades, with a 55% win rate and a 1-to-1.5 risk-reward ratio, the expected result would be roughly 21 more winning trades than losing ones, multiplied by the average gain — a math exercise that only makes sense when the backtest numbers are realistic, not inflated by luck in the chosen period.

• Use at least one or two years of historical data, if available.
• Include trading costs and spread in the calculation.
• Be suspicious of results that seem too perfect: they can indicate an error in the test.
• Set aside part of the data to validate outside the period used for tuning.

Step 4: test on a demo account before real capital

Even after a satisfactory backtest, the bot should run on a demo account, with live market data but no real money, for a reasonable period. This is the stage where problems the backtest can't capture show up, such as execution delays, connection failures, or the bot's behavior during breaking news.

Continuous monitoring

A trading bot isn't a project you set up once and forget. Changes in market behavior can turn a profitable strategy into an inconsistent one. Set aside weekly time to review the results, comparing the actual performance with what the backtest predicted.

How to put the bot into operation safely

When moving to a real account, start with a small amount of capital, enough to validate that live execution matches what was tested, but small enough that a configuration error doesn't cause serious damage. Increase the allocated capital gradually, as the real track record confirms what was seen in testing.

Regardless of the platform used to execute the orders, the bot is a discipline tool, not a profit guarantee. It removes emotional hesitation when it's time to press the button, but it remains exposed to market risk like any other form of trading, and losses are part of the process even with a well-built system.