USE OF MACHINE LEARNING TO FORECAST, RECOMMEND, AND TRADE SECURITIES IN CURRENCY MARKETS

摘要

Machine learning-based approaches are used to predict market data, determine financial recommendations, and execute those recommendations. For example, for a plurality of time periods, a prediction model can be trained. The prediction models can be trained on market data and market activity that correspond to each prediction models' period of time. The prediction models can process market data and market activity to determine a predicted currency score and time-limited exchange rate for the time period a prediction model is associated with. For a selected time period, a trained model can evaluate market data to predict a currency value that satisfies a threshold level of change. The value (e.g., a next value currency) can then be used to, for example, complete a financial transaction, a document agreement, and the like.