New publications in CodeBase
- Balance Of Power The Balance of Power (BOP) is an indicator originally developed by Igor Livshin in 2001 to measure the balance of power between buyers and sellers during each candle.
- A script for a tester that extends the standard MetaTrader 5 optimisation features This is a tester script that extends the standard MetaTrader 5 optimisation capabilities, allowing you to evaluate strategies according to complex user-defined criteria (with separation into in-sample and out-of-sample periods, advanced metrics and statistical tests).
- 3 way Aroon value calculation Showing different ways of the Aroon values calculation
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- Questions from Beginners MQL5 MT5 MetaTrader 5 23 new comments
- Did Structs Change with the last MT5 Update? 21 new comments
- Machine learning in trading: theory, models, practice and algo-trading 20 new comments
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Published article "Automating Trading Strategies in MQL5 (Part 34): Trendline Breakout System with R-Squared Goodness of Fit".

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.
New publications in CodeBase
- Stochastic Eclipse - MT4 EA By identifying overbought and oversold conditions, it helps traders catch early reversals, ride strong momentum shifts, and filter false signals.
- Trend Vision MT4 Indicator Trend Vision is a custom MT4 indicator that combines MACD momentum with Bollinger Bands volatility to give clear, reliable trading signals. MACD shows momentum shifts, divergence, and trend strength. Bollinger Bands measure volatility, expansion, and squeezes. By fusing these two, Trend Vision filters out false moves and highlights only the high-probability moments when both momentum and volatility agree.
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Published article "Statistical Arbitrage Through Cointegrated Stocks (Part 5): Screening".

This article proposes an asset screening process for a statistical arbitrage trading strategy through cointegrated stocks. The system starts with the regular filtering by economic factors, like asset sector and industry, and finishes with a list of criteria for a scoring system. For each statistical test used in the screening, a respective Python class was developed: Pearson correlation, Engle-Granger cointegration, Johansen cointegration, and ADF/KPSS stationarity. These Python classes are provided along with a personal note from the author about the use of AI assistants for software development.
Published article "MQL5 Wizard Techniques you should know (Part 80): Using Patterns of Ichimoku and the ADX-Wilder with TD3 Reinforcement Learning".

This article follows up ‘Part-74’, where we examined the pairing of Ichimoku and the ADX under a Supervised Learning framework, by moving our focus to Reinforcement Learning. Ichimoku and ADX form a complementary combination of support/resistance mapping and trend strength spotting. In this installment, we indulge in how the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm can be used with this indicator set. As with earlier parts of the series, the implementation is carried out in a custom signal class designed for integration with the MQL5 Wizard, which facilitates seamless Expert Advisor assembly.
Published article "How to build and optimize a cycle-based trading system (Detrended Price Oscillator - DPO)".

This article explains how to design and optimise a trading system using the Detrended Price Oscillator (DPO) in MQL5. It outlines the indicator's core logic, demonstrating how it identifies short-term cycles by filtering out long-term trends. Through a series of step-by-step examples and simple strategies, readers will learn how to code it, define entry and exit signals, and conduct backtesting. Finally, the article presents practical optimization methods to enhance performance and adapt the system to changing market conditions.
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10 new signals now available for subscription:
| Growth: | 277.52 | % |
| Equity: | 23,111.60 | USD |
| Balance: | 31,028.63 | USD |
Published article "Automating Trading Strategies in MQL5 (Part 33): Creating a Price Action Shark Harmonic Pattern System".

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
Published article "The MQL5 Standard Library Explorer (Part 1): Introduction with CTrade, CiMA, and CiATR".

The MQL5 Standard Library plays a vital role in developing trading algorithms for MetaTrader 5. In this discussion series, our goal is to master its application to simplify the creation of efficient trading tools for MetaTrader 5. These tools include custom Expert Advisors, indicators, and other utilities. We begin today by developing a trend-following Expert Advisor using the CTrade, CiMA, and CiATR classes. This is an especially important topic for everyone—whether you are a beginner or an experienced developer. Join this discussion to discover more.
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Most downloaded source codes this month
- Tarantella Tarantella EA: Advanced grid trading system with hedging capabilities and Market Profile integration. Uses ADX trend filtering, Fibonacci-based grid spacing, and multi-layered entry conditions (RSI/ATR/volume) to execute trades only within Market Profile value areas. Features intelligent risk management including trailing stops, breakeven triggers, and partial hedge closing.
- TardioBot TardioBot V1.05, named after of a historical figure Giuseppe Tardio, is an Expert Advisor designed for MetaTrader 5 that employs a triangular arbitrage strategy.
- Multi_Divergence_EA The EA identifies trade setups by waiting for a user-defined number of indicators (e.g., 2 out of 3) to show divergence simultaneously. This multi-layer confirmation approach filters out market noise. Key Features: Triple Confirmation Engine: Analyzes RSI, MACD, & Stochastic divergence. Advanced Filters: Optional Trend Filter (MA) and Volume Filter for superior signal quality. Full Customization: Control all indicator settings, divergence sensitivity, and trade logic. Professional Risk Management: Use fixed lots or percentage-based money management with SL/TP.
Most read articles this month

In this article, we demonstrate an easy way to install MetaTrader 5 on popular Linux versions — Ubuntu and Debian. These systems are widely used on server hardware as well as on traders’ personal computers.

How to purchase a trading robot from the MetaTrader Market and to install it?
A product from the MetaTrader Market can be purchased on the MQL5.com website or straight from the MetaTrader 4 and MetaTrader 5 trading platforms. Choose a desired product that suits your trading style, pay for it using your preferred payment method, and activate the product.
How to Test a Trading Robot Before Buying
Buying a trading robot on MQL5 Market has a distinct benefit over all other similar options - an automated system offered can be thoroughly tested directly in the MetaTrader 5 terminal. Before buying, an Expert Advisor can and should be carefully run in all unfavorable modes in the built-in Strategy Tester to get a complete grasp of the system.
Published article "Moving to MQL5 Algo Forge (Part 3): Using External Repositories in Your Own Projects".

Let's explore how you can start integrating external code from any repository in the MQL5 Algo Forge storage into your own project. In this article, we finally turn to this promising, yet more complex, task: how to practically connect and use libraries from third-party repositories within MQL5 Algo Forge.
New publications in CodeBase
- Pinbar Detector This MQL5 indicator identifies Upward (Bullish) and Downward (Bearish) Pinbars, displayed with customizable arrows (lime for upward, red for downward). It allows fine-tuning of detection parameters like tail body ratio and protrusion. Pop-up and push notification alerts signal new pinbars. Ideal for traders seeking precise reversal pattern detection.
- MA Cross Alert MT4 Indicator MA Cross Alert is a custom MT4 indicator that solves one key problem: MetaTrader’s built-in Moving Average shows the line but has no way to alert you when price crosses it.
Published article "Overcoming The Limitation of Machine Learning (Part 4): Overcoming Irreducible Error Using Multiple Forecast Horizons".

Machine learning is often viewed through statistical or linear algebraic lenses, but this article emphasizes a geometric perspective of model predictions. It demonstrates that models do not truly approximate the target but rather map it onto a new coordinate system, creating an inherent misalignment that results in irreducible error. The article proposes that multi-step predictions, comparing the model’s forecasts across different horizons, offer a more effective approach than direct comparisons with the target. By applying this method to a trading model, the article demonstrates significant improvements in profitability and accuracy without changing the underlying model.
Published article "Automating The Market Sentiment Indicator".

In this article, we automate a custom market sentiment indicator that classifies market conditions into bullish, bearish, risk-on, risk-off, and neutral. The Expert Advisor delivers real-time insights into prevailing sentiment while streamlining the analysis process for current market trends or direction.
Published article "Building AI-Powered Trading Systems in MQL5 (Part 2): Developing a ChatGPT-Integrated Program with User Interface".

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.
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Published article "Developing Trading Strategies with the Parafrac and Parafrac V2 Oscillators: Single Entry Performance Insights".

This article introduces the ParaFrac Oscillator and its V2 model as trading tools. It outlines three trading strategies developed using these indicators. Each strategy was tested and optimized to identify their strengths and weaknesses. Comparative analysis highlighted the performance differences between the original and V2 models.
Published article "Developing a Volatility Based Breakout System".

Volatility based breakout system identifies market ranges, then trades when price breaks above or below those levels, filtered by volatility measures such as ATR. This approach helps capture strong directional moves.
Published article "Simplifying Databases in MQL5 (Part 2): Using metaprogramming to create entities".

We explored the advanced use of #define for metaprogramming in MQL5, creating entities that represent tables and column metadata (type, primary key, auto-increment, nullability, etc.). We centralized these definitions in TickORM.mqh, automating the generation of metadata classes and paving the way for efficient data manipulation by the ORM, without having to write SQL manually.
Published article "Price Action Analysis Toolkit Development (Part 41): Building a Statistical Price-Level EA in MQL5".

Statistics has always been at the heart of financial analysis. By definition, statistics is the discipline that collects, analyzes, interprets, and presents data in meaningful ways. Now imagine applying that same framework to candlesticks—compressing raw price action into measurable insights. How helpful would it be to know, for a specific period of time, the central tendency, spread, and distribution of market behavior? In this article, we introduce exactly that approach, showing how statistical methods can transform candlestick data into clear, actionable signals.

























