Abstract: Embodiments provide mobile computing devices, related systems, and methods for controlling predictive modeling processes on a mobile device. An embodiment may provide a method for controlling predictive modeling processes on a mobile device, which may include receiving modeling data associated with a predictive model, receiving computation resources data of the mobile device, determining one or more predictive model processing parameters of the predictive model based on the modeling data and the computation resources data, formulating processing instructions based on the one or more predictive model processing parameters, and sending the modeling data and the processing instructions to the mobile device for execution of the predictive model. The parameters may include aspects of a sufficient number of tests, a type of predictive modeling simulation technique, client/server processing, and/or device responsive rendering.

Abstract: Embodiments provide mobile computing devices, related systems, and methods for controlling predictive modeling processes on a mobile device. An embodiment may provide a method for controlling predictive modeling processes on a mobile device, which may include receiving modeling data associated with a predictive model, receiving computation resources data of the mobile device, determining one or more predictive model processing parameters of the predictive model based on the modeling data and the computation resources data, formulating processing instructions based on the one or more predictive model processing parameters, and sending the modeling data and the processing instructions to the mobile device for execution of the predictive model. The parameters may include aspects of a sufficient number of tests, a type of predictive modeling simulation technique, client/server processing, and/or device responsive rendering.

Abstract: Systems and methods for reducing computer processing resources required to maximize decrementation of an asset without reducing it to zero value over a period. A system may include a target deduction rate database storing time horizons and target deduction rates; a first processor calculating a total real return value and an estimated internal value associated with the asset; and a second processor testing deduction rates against historical data of previous changes in value of the asset and determining for each tested deduction rate and time horizon, historically successful and unsuccessful outcomes for the asset; limiting a percentage of unsuccessful outcomes by selecting, among the tested rates, a target deduction rate that achieves a desired percentage of successful outcomes and excluding remaining tested rates from further processing; and further limiting the percentage of unsuccessful outcomes by adjusting the target deduction rate by a value gap difference to determine the deduction rate.

Abstract: Embodiments provide mobile computing devices, related systems, and methods for controlling predictive modeling processes on a mobile device. An embodiment may provide a method for controlling predictive modeling processes on a mobile device, which may include receiving modeling data associated with a predictive model, receiving computation resources data of the mobile device, determining one or more predictive model processing parameters of the predictive model based on the modeling data and the computation resources data, formulating processing instructions based on the one or more predictive model processing parameters, and sending the modeling data and the processing instructions to the mobile device for execution of the predictive model. The parameters may include aspects of a sufficient number of tests, a type of predictive modeling simulation technique, client/server processing, and/or device responsive rendering.

Abstract: Systems and methods for reducing computer processing resources required to maximize decrementation of an asset without reducing it to zero value over a period. A system may include a target deduction rate database storing time horizons and target deduction rates; a first processor calculating a total real return value and an estimated internal value associated with the asset; and a second processor testing deduction rates against historical data of previous changes in value of the asset and determining for each tested deduction rate and time horizon, historically successful and unsuccessful outcomes for the asset; limiting a percentage of unsuccessful outcomes by selecting, among the tested rates, a target deduction rate that achieves a desired percentage of successful outcomes and excluding remaining tested rates from further processing; and further limiting the percentage of unsuccessful outcomes by adjusting the target deduction rate by a value gap difference to determine the deduction rate.

Abstract: A method and system for determining a deduction rate from a starting value, which maximizes the deduction rate without reducing the starting value to zero over a given time period. In an embodiment, a method may include using a computer processor to test deduction rates against historical data of previous changes in value of the starting value and determine a target deduction rate that achieves a desired percentage of historically successful outcomes for the starting value, determining a value gap difference between the starting value and an estimated internal value based on historical data, and adjusting the target deduction rate by the value gap difference to determine the deduction rate. The deduction rate may comprise a largest periodic amount that can be deducted from the starting value without reducing the starting value to zero over the given time period.

Abstract: A method and system for determining an investment portfolio withdrawal rate is disclosed, including determining a target draw rate and adjusting the target draw rate by a value gap to determine a safe maximum withdrawal rate. The value gap may be determined by comparing the investment portfolio to an estimated internal value of the portfolio or to a market trend value. Alternative embodiments may include subsequently adjusting the safe maximum withdrawal rate by a value gap when the value gap allows and if desired. Further embodiments may provide methods and systems for managing distributions associated with an investment account, which may incorporate the determination of a safe maximum withdrawal rate.