Real-time probability determination based on technical indicators in a financial instrument environment

A computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions readable/executable by a processor to cause the processor to:

• generate a model based on time-series historical data for a financial instrument, the model built from one or more technical indicators of the financial instrument based on one or more extracted components of the time-series historical data and goal values associated with the financial instrument;
• apply a transform to the model, the transform generating a quantile vector associated with the financial instrument based on one or more quantile values derived from the model for the financial instrument;
• compile a composite index of quantile vectors, each of the quantile vectors corresponding to a plurality of samples having time-series historical data within a similarity threshold relative to the time-series historical data of the financial instrument, wherein the composite index comprises a single sequential range of vector values;
• and
• generate a probability for the financial instrument to reach the goal values by determining an average number of quantile vectors of the composite index matching the quantile vector of the financial instrument.

A computer system comprising:

• a processor;
• a memory accessible by the processor;
• and
• a computer readable medium having instructions encoded thereon to:
• generate a model based on time-series historical data for a financial instrument, the model built from one or more technical indicators of the financial instrument based on one or more extracted components of the time-series historical data and goal values associated with the financial instrument;
• apply a transform to the model, the transform generating a quantile vector associated with the financial instrument based on one or more quantile values derived from the model for the financial instrument;
• compile a composite index of quantile vectors, each of the quantile vectors corresponding to a plurality of samples having time-series historical data within a similarity threshold relative to the time-series historical data of the financial instrument, wherein the composite index comprises a single sequential range of vector values;
• and
• generate a probability for the financial instrument to reach the goal values by determining an average number of quantile vectors of the composite index matching the quantile vector of the financial instrument.