Metatrader 5 / Metatrader 4 for MQL5 / MQL4 articles preview

This article is not just a guide to analyzing central bank balance sheets. It is an in-depth exploration of how to build a system that, like an alchemical cauldron, transforms raw liquidity data into golden forecasts of currency pair movements. We will combine information from the US Federal Reserve (Fed), the European Central Bank (ECB), the Bank of Japan (BOJ) and the People's Bank of China (PBoC) to create a composite index of global liquidity. We will explore how machine learning and technical analysis can work in tandem to uncover hidden patterns traditional methods often fail to capture. Moreover, we will show how to integrate this system with real trading, turning abstract data into concrete trading decisions.

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Although MetaTrader 5 provides basic tools for manual chart analysis, it does not offer an automated solution for identifying and validating expanding formations like the megaphone pattern. As a result, traders are forced to analyze swing structures manually, create widening trend lines, and track breakout behavior continuously, which can reduce efficiency and introduce inconsistency into the analysis process. In this article, we will build a custom megaphone pattern indicator in MQL5 capable of automatically detecting bullish and bearish expanding structures directly on the chart. The implementation will cover swing detection, structure refinement, trend line validation, breakout confirmation, and stop loss and take profit projection.

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In the previous article, we became acquainted with the theoretical aspects of the Actor–Director–Critic framework, an extended version of the Actor–Critic architecture. The classical Actor–Critic architecture has become a cornerstone of many successful reinforcement learning (RL) algorithms. In this setup, the agent is divided into two components: the Actor proposes actions, while the Critic evaluates them based on rewards received from the environment. This combination enables the gradual development of a strategy in which actions become increasingly purposeful and evaluations progressively more accurate. However, despite its elegance and effectiveness, this architecture encounters several significant limitations in real-world applications, particularly in trading.

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