Abstract: A method and system are disclosed for more efficiently constructing a volatility surface. The methodology results in measurable reduction in the quantity of storage memory space needed on a computer executing the novel methodology, reduces the measurable, on-demand computational load on the processor(s) of a computer executing the novel methodology, and permits as-of-day calculations of the volatility surface that were previously impossible to obtain in near real-time.

Abstract: A method and system are disclosed for more efficiently constructing a volatility surface. The methodology results in measurable reduction in the quantity of storage memory space needed on a computer executing the novel methodology, reduces the measurable, on-demand computational load on the processor(s) of a computer executing the novel methodology, and also permits as-of-day calculations of the volatility surface that were previously impossible to obtain in near real-time.

Abstract: Datasets may be characterized by patterns. The patterns may be caused or otherwise influenced by external factors, such as temporal, meteorological, and/or system factors. The external factors, as well as the patterns which result in the data values of the dataset because of the external factors, may provide for techniques used to account for missing data elements, outlier data elements and/or otherwise cleanse the dataset. New elements may be generated to provide for the missing data elements, and derivative datasets may be generated based on one or more cleansed datasets.

Abstract: Systems and methods are provided for efficiently determining prices of futures, spreads and swaps by considering product interdependencies. The disclosed systems and methods use interpolation, extrapolation and backward propagation to produce accurate results.

Abstract: A method and system are disclosed for more efficiently constructing a volatility surface. The methodology results in measurable reduction in the quantity of storage memory space needed on a computer executing the novel methodology, reduces the measurable, on-demand computational load on the processor(s) of a computer executing the novel methodology, and also permits as-of-day calculations of the volatility surface that were previously impossible to obtain in near real-time.

Abstract: Datasets may be characterized by patterns. The patterns may be caused or otherwise influenced by external factors, such as temporal, meteorological, and/or system factors. The external factors, as well as the patterns which result in the data values of the dataset because of the external factors, may provide for techniques used to account for missing data elements, outlier data elements and/or otherwise cleanse the dataset. New elements may be generated to provide for the missing data elements, and derivative datasets may be generated based on one or more cleansed datasets.