Abstract: An asset portfolio prediction method performed by a computing system comprise determining a target prediction task which is data specifying an objective task; collecting raw data to perform the determined target prediction task; aligning the collected raw data in a time-series on a specific time axis; training a predetermined time-series prediction model based on the aligned raw data and the determined target prediction task; predicting daily portfolio asset weight data over a predetermined prediction unit period based on the trained time-series prediction model; generating a single set of portfolio asset weight data by processing the predicted daily portfolio asset weight data at each predetermined rebalancing time; and providing the generated single set of portfolio asset weight data.

Abstract: A target prediction method for predicting a future outlook of a target performed by a computing device or a processor may collect related structured and unstructured data when a user requests target prediction, analyze the relationship between the target and a variable affecting the target at a semantic level, and compute a target outlook of a future.

Abstract: A target prediction method for predicting a future outlook of a target performed by a computing device or a processor may collect related structured and unstructured data when a user requests predictive generation, analyze the relationship between the target and a variable affecting the target at a semantic level, and compute a target outlook of a future.

Abstract: A predictive generation method for predicting a future outlook of a target performed by a computing device or a processor may collect related structured and unstructured data when a user requests predictive generation, analyze the relationship between the target and a variable affecting the target at a semantic level, and compute a target outlook of a future.