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Mini-articles with technical and fundamental analysis on the way as forecasts and levels - https://www.mql5.com/en/channels/forecast
With all the trading data and information such as indicators (there are more than 36 built-in indicators in MetaTrader 5), symbol pairs (there are more than 100 symbols) that can also be used as data for correlation strategies, there are also news which are valuable data for traders, etc. The point I'm trying to raise is that there is abundant information for traders to use in manual trading or when trying to build Artificial Intelligence models to help us make smart trading decisions in our ...
In this article, we focus on developing an Expert Advisor (EA) using MQL5, designed to identify potential market reversals. The EA employs the Parabolic SAR for signal detection, generating trading signals by monitoring technical indicators, evaluating their validity in real time, and identifying optimal exit points when predefined levels are reached. more...
In this article, we explore a feature selection algorithm introduced in the paper 'Local Feature Selection for Data Classification' by Narges Armanfard, James P. Reilly, and Majid Komeili. This method aims to identify predictive features that are often overlooked by traditional selection techniques due to their limited global utility. We will begin with a general overview of the algorithm, followed by its implementation in Python to create classifier models suitable for export to MetaTrader ...
In the previous article we built the main modules of the MSFformer model, including CSCM and Skip-PAM. The CSCM module constructs a feature tree of the analyzed time series, while Skip-PAM extracts information from time series at multiple scales using attention mechanism based on a temporal feature tree. In this article, we will continue that work by training the model and evaluating its performance on real-world data using the MetaTrader 5 Strategy Tester. more...
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