Allan Munene Mutiiria / Профиль

In this article, we develop a Candle Range Theory (CRT) trading system in MQL5 that identifies accumulation ranges on a specified timeframe, detects breaches with manipulation depth filtering, and confirms reversals for entry trades in the distribution phase. The system supports dynamic or static stop-loss and take-profit calculations based on risk-reward ratios, optional trailing stops, and limits on positions per direction for controlled risk management.

In Part 6 of our MQL5 AI trading system series, we advance the ChatGPT-integrated Expert Advisor by introducing chat deletion functionality through interactive delete buttons in the sidebar, small/large history popups, and a new search popup, allowing traders to manage and organize persistent conversations efficiently while maintaining encrypted storage and AI-driven signals from chart data.

In this article, we build an MQL5 Expert Advisor for Fibonacci retracement trading, using either daily candle ranges or lookback arrays to calculate custom levels like 50% and 61.8% for entries, determining bullish or bearish setups based on close vs. open. The system triggers buys or sells on price crossings of levels with max trades per level, optional closure on new Fib calcs, points-based trailing stops after a min profit threshold, and SL/TP buffers as percentages of the range.

In Part 5 of our MQL5 AI trading system series, we enhance the ChatGPT-integrated Expert Advisor by introducing a collapsible sidebar, improving navigation with small and large history popups for seamless chat selection, while maintaining multiline input handling, persistent encrypted chat storage, and AI-driven trade signal generation from chart data.

In this article, we develop an MQL5 strategy tracker system that detects moving average crossover signals filtered by a long-term MA, simulates or executes trades with configurable TP levels and SL in points, and monitors outcomes like TP/SL hits for performance analysis.

In this article, we develop an MQL5 Expert Advisor for statistical mean reversion trading, calculating moments like mean, variance, skewness, kurtosis, and Jarque-Bera statistics over a specified period to identify non-normal distributions and generate buy/sell signals based on confidence intervals with adaptive thresholds

In this article, we build an MQL5 EA that detects hidden RSI divergences via swing points with strength, bar ranges, tolerance, and slope angle filters for price and RSI lines. It executes buy/sell trades on validated signals with fixed lots, SL/TP in pips, and optional trailing stops for risk control.

In this article, we build an MQL5 EA that detects regular RSI divergences using swing points with strength, bar limits, and tolerance checks. It executes trades on bullish or bearish signals with fixed lots, SL/TP in pips, and optional trailing stops. Visuals include colored lines on charts and labeled swings for better strategy insights.

In this article, we enhance the ChatGPT-integrated program in MQL5 overcoming multiline input limitations with improved text rendering, introducing a sidebar for navigating persistent chat storage using AES256 encryption and ZIP compression, and generating initial trade signals through chart data integration.

In this article, we create a supply and demand trading system in MQL5 that identifies supply and demand zones through consolidation ranges, validates them with impulsive moves, and trades retests with trend confirmation and customizable risk parameters. The system visualizes zones with dynamic labels and colors, supporting trailing stops for risk management.

In this article, we upgrade the ChatGPT-integrated program in MQL5 to a scrollable single chat-oriented UI, enhancing conversation history display with timestamps and dynamic scrolling. The system builds on JSON parsing to manage multi-turn messages, supporting customizable scrollbar modes and hover effects for improved user interaction.

In this article, we create a Breaker Block Trading System in MQL5 that identifies consolidation ranges, detects breakouts, and validates breaker blocks with swing points to trade retests with defined risk parameters. The system visualizes order and breaker blocks with dynamic labels and arrows, supporting automated trading and trailing stops.

In this article, we develop an MQL5 First Run User Setup Wizard for Expert Advisors, featuring a scrollable guide with an interactive dashboard, dynamic text formatting, and visual controls like buttons and a checkbox allowing users to navigate instructions and configure trading parameters efficiently. Users of the program get to have insight of what the program is all about and what to do on the first run, more like an orientation model.

In this article, we develop a Trendline Breakout System in MQL5 that identifies support and resistance trendlines using swing points, validated by R-squared goodness of fit and angle constraints, to automate breakout trades. Our plan is to detect swing highs and lows within a specified lookback period, construct trendlines with a minimum number of touch points, and validate them using R-squared metrics and angle constraints to ensure reliability.

In this article, we develop a Shark pattern system in MQL5 that identifies bullish and bearish Shark harmonic patterns using pivot points and Fibonacci ratios, executing trades with customizable entry, stop-loss, and take-profit levels based on user-selected options. We enhance trader insight with visual feedback through chart objects like triangles, trendlines, and labels to clearly display the X-A-B-C-D pattern structure

In this article, we develop a ChatGPT-integrated program in MQL5 with a user interface, leveraging the JSON parsing framework from Part 1 to send prompts to OpenAI’s API and display responses on a MetaTrader 5 chart. We implement a dashboard with an input field, submit button, and response display, handling API communication and text wrapping for user interaction.

In this article, we develop a JSON parsing framework in MQL5 to handle data exchange for AI API integration, focusing on a JSON class for processing JSON structures. We implement methods to serialize and deserialize JSON data, supporting various data types like strings, numbers, and objects, essential for communicating with AI services like ChatGPT, enabling future AI-driven trading systems by ensuring accurate data handling and manipulation.

In this article, we develop a 5 Drives pattern system in MQL5 that identifies bullish and bearish 5 Drives harmonic patterns using pivot points and Fibonacci ratios, executing trades with customizable entry, stop loss, and take-profit levels based on user-selected options. We enhance trader insight with visual feedback through chart objects like triangles, trendlines, and labels to clearly display the A-B-C-D-E-F pattern structure.