#AITradingAffectsForex Assessing the impact of data quality on AI-driven Forex trading is crucial for ensuring the reliability and accuracy of trading decisions. Poor data quality can lead to biased or inaccurate models, resulting in significant losses. Several factors can affect data quality in Forex trading, including: - Noisy or incomplete data - Inconsistent or irregular data formats - Outdated or stale data - Biased or manipulated data To assess the impact of data quality on AI-driven Forex trading, traders can employ various techniques, such as: - Data cleaning and preprocessing - Data validation and verification - Data normalization and transformation - Data visualization and exploratory analysis By ensuring high-quality data, traders can develop more accurate and reliable AI-driven Forex trading models, leading to improved trading performance and reduced risk. Additionally, traders can use techniques such as data augmentation and data synthesis to enhance data quality and improve model robustness.