Exploring optimal time frames for EURUSD prediction, the study assesses model error across 11 frames, revealing minimal error on monthly and hourly frames. An intriguing find is Granger causality between hourly and monthly returns, harnessing a VAR model for prediction. Using MetaTrader 5, the data is fetched and analyzed, focusing on the correlation and error distribution. Advanced techniques like Time Series Warping align time series data, and parameter tuning enhances model accuracy. Implementation in MQL5 allows flexible trading strategies through ONNX-exported AI models, adapting to technical analysis indicators for trade execution on the MetaTrader 5 platform.
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