Discussing the article: "Introduction to MQL5 (Part 38): Mastering API and WebRequest Function in MQL5 (XII)"
You are missing trading opportunities:
- Free trading apps
- Over 8,000 signals for copying
- Economic news for exploring financial markets
Registration
Log in
You agree to website policy and terms of use
If you do not have an account, please register
Check out the new article: Introduction to MQL5 (Part 38): Mastering API and WebRequest Function in MQL5 (XII).
Create a practical bridge between MetaTrader 5 and Binance: fetch 30‑minute klines with WebRequest, extract OHLC/time values from JSON, and confirm a bullish engulfing pattern using only completed candles. Then assemble the query string, compute the HMAC‑SHA256 signature, add X‑MBX‑APIKEY, and submit authenticated orders. You get a clear, end‑to‑end EA workflow from data acquisition to order execution.
In this article, we will create an MQL5 Expert Advisor that retrieves and analyzes market data by interacting with an external site like Binance. The project starts by choosing a certain coin on the site and using the API to retrieve candlestick data. To find a bullish engulfing pattern in the most recent finished candle, we will retrieve the last three closed 30-minute candles. We will go over the mechanism for programmatically identifying this pattern so you can use MQL5 to accurately detect it. We’ll also discuss how orders are really sent based on these conditions through API.
We will concentrate on how market data is retrieved and analyzed, how MetaTrader 5 securely creates requests, and how trading patterns are programmatically assessed throughout this process. This project shows how MQL5 may function as a bridge between MetaTrader 5 and platforms outside the MetaTrader ecosystem, going beyond conventional chart-based logic. By the end of this article, you will have a clear and reusable workflow for fetching candlestick data, understanding candle patterns such as bullish engulfing, and preparing your Expert Advisor to act on market conditions. You will also gain a strong understanding of how to adapt this approach for other patterns, timeframes, and advanced automation scenarios.
Author: Israel Pelumi Abioye