#AIImpactOnForex Predicting currency movements with genetic algorithms (GAs) involves using an evolutionary computation technique to identify patterns or optimal strategies for forecasting currency exchange rates. GAs mimic the process of natural selection, where potential solutions (in this case, trading strategies) evolve over generations through processes like selection, crossover, and mutation. The process typically starts by encoding different trading strategies as "chromosomes," which are evaluated based on their performance in predicting currency movements. The most successful strategies are then selected and recombined, with occasional mutations to introduce new variations. This process continues over multiple generations to evolve a more effective predictive model. GAs are useful in this context because they can handle complex, nonlinear, and noisy data often seen in financial markets. They can optimize parameters for technical analysis tools, trading rules, or machine learning models, helping traders develop more accurate forecasting systems for currency trading.