Abstract: A suite of predictions is defined to model the financial data commonly used to calculate technical indicators one or more periods in the future. Neural networks are trained to make these predictions. The predictions are then integrated with the standard technical indicator calculations to produce predictive technical indicators which are superior because they lead more and lag less.

Abstract: A method and a system for performing intermarket analysis. The method can include, from a pool of available markets in which at least one key intermarket has been selected and removed, selecting at least one market as a general intermarket, and removing the market selected as the general intermarket from the pool of available markets. From the pool of available markets from which the general intermarket has been removed, at least one market can be selected as a predictive intermarket and removed from the pool of available markets. Market data for each of the key intermarket, the general intermarket and the predictive intermarket can be processed to train a neural network. After training the neural network, market data for the primary market can be processed with the neural network to predict future market data for the primary market. The predicted future market data can be output.

Abstract: A method and a system for performing intermarket analysis. The method can include, from a pool of available markets in which at least one key intermarket has been selected and removed, selecting at least one market as a general intermarket, and removing the market selected as the general intermarket from the pool of available markets. From the pool of available markets from which the general intermarket has been removed, at least one market can be selected as a predictive intermarket and removed from the pool of available markets. Market data for each of the key intermarket, the general intermarket and the predictive intermarket can be processed to train a neural network. After training the neural network, market data for the primary market can be processed with the neural network to predict future market data for the primary market. The predicted future market data can be output.

Abstract: A suite of predictions is defined to model the financial data commonly used to calculate technical indicators one or more periods in the future. Neural networks are trained to make these predictions. The predictions are then integrated with the standard technical indicator calculations to produce predictive technical indicators which are superior because they lead more and lag less.