Abstract: A method and system for probability distribution forecast evaluation are disclosed. The present disclosure is directed to embodiments of a system that evaluates probability distribution forecasts by acquiring one or more of a probability distribution forecast, a probability distribution realization, and a prior knowledge of the probability distribution forecast. The system disclosed herein may then compute an accuracy score and an information score based on the acquired forecast, realization, and prior knowledge. In evaluating the forecast, a performance score may also be computed based on the accuracy score and the information score.

Abstract: A method and system for probability distribution forecast evaluation are disclosed. The present disclosure is directed to embodiments of a system that evaluates probability distribution forecasts by acquiring one or more of a probability distribution forecast, a probability distribution realization, and a prior knowledge of the probability distribution forecast. The system disclosed herein may then compute an accuracy score and an information score based on the acquired forecast, realization, and prior knowledge. In evaluating the forecast, a performance score may also be computed based on the accuracy score and the information score.

Abstract: A system and method for enabling information extraction from large data sets (so-called “big data”) according to a new paradigm is disclosed. This system does not generate functions describing why certain inputs result in certain outputs. Instead, it creates incident mappings of inputs to outputs without regard to why inputs result in outputs. These mappings can be distributions or other data sets representative of different outcomes occurring. This enables several useful operations. For example, by providing a data set indicative of outputs that have historically occurred following a particular input, the disclosed system can be used to predict future outcomes with probabilities. For example, if a particular stock price pattern is provided as an input, the system generates an output data set indicating the probabilities of certain price behaviors following that input pattern. This data set can thus be used to predict future behavior. Other useful operations are disclosed herein.

Abstract: A system and method for enabling information extraction from large data sets (so-called “big data”) according to a new paradigm is disclosed. This system does not generate functions describing why certain inputs result in certain outputs. Instead, it creates incident mappings of inputs to outputs without regard to why inputs result in outputs. These mappings can be distributions or other data sets representative of different outcomes occurring. This enables several useful operations. For example, by providing a data set indicative of outputs that have historically occurred following a particular input, the disclosed system can be used to predict future outcomes with probabilities. For example, if a particular stock price pattern is provided as an input, the system generates an output data set indicating the probabilities of certain price behaviors following that input pattern. This data set can thus be used to predict future behavior. Other useful operations are disclosed herein.

Abstract: A method and system for probability distribution forecast evaluation are disclosed. The present disclosure is directed to embodiments of a system that evaluates probability distribution forecasts by acquiring one or more of a probability distribution forecast, a probability distribution realization, and a prior knowledge of the probability distribution forecast. The system disclosed herein may then compute an accuracy score and an information score based on the acquired forecast, realization, and prior knowledge. In evaluating the forecast, a performance score may also be computed based on the accuracy score and the information score.

Abstract: A system and method for enabling information extraction from large data sets (so-called “big data”) according to a new paradigm is disclosed. This system does not generate functions describing why certain inputs result in certain outputs. Instead, it creates incident mappings of inputs to outputs without regard to why inputs result in outputs. These mappings can be distributions or other data sets representative of different outcomes occurring. This enables several useful operations. For example, by providing a data set indicative of outputs that have historically occurred following a particular input, the disclosed system can be used to predict future outcomes with probabilities. For example, if a particular stock price pattern is provided as an input, the system generates an output data set indicating the probabilities of certain price behaviors following that input pattern. This data set can thus be used to predict future behavior. Other useful operations are disclosed herein.

Abstract: Robust content-based decision-making support is enabled by software with a customizable knowledge base. Utilizing proprietary information contained within a knowledge base, the software enables users to search the indexed database by feature, example firm, or pattern and update the knowledge base based on the results. The information contained in the knowledge base enables results to be ranked by relevance and enables other feedback to be provided. The system and methods provide process support by helping financial professionals identify, analyze, and construct data analysis patterns based on individual domain knowledge and preferences. The system and methods automatically detect abnormal patterns and automatically analyze their correlations to market events to provide further process support to financial professionals. Using the results of any searching, analysis, and processing, the system and methods provide a neural network or other learning algorithm to provide content-based decision-making support.

Abstract: Robust content-based financial data processing is enabled by software with a customizable knowledge base. The software indexes a publicly or privately available financial database based on the content of the database records. Utilizing proprietary information contained within a knowledge base, the software enables users to search the indexed database by feature, example firm, or pattern. The information contained in the knowledge base enables results to be ranked by relevance. Moreover, users provide feedback about search results to enhance the knowledge base. Software analyzes data by using adaptive signal processing to remove market trends or noise and enable complicated market research.