| 摘要 |
A method and system allowing the analysis of risk through the use of Monte Carlo simulation, statistical and data analysis, stochastic forecasting, and optimization. The present invention includes novel methods such as the detailed reporting capabilities coupled with advanced analytical techniques, an integrated risk management process and procedures, adaptive licensing technology, and model profiling and storage procedures. |
| 主权项 |
1. A system for analyzing business risk comprising:
a computing device comprising a processor communicatively connected to a storage medium, a motherboard, and an Ethernet card; an operating system stored in a memory of said device configured to provide instructions to said processor; computer readable instructions residing in a memory of said device, wherein said computer readable instructions comprise a risk simulation module comprising:a plurality of forecasting and risk simulation models and methods, and a plurality of basic econometric models;a basic econometrics module configured to run one or more basic econometric models by (1) identifying input variables from said user provided data and designating at least one independent variable and at least one dependent variable from among said input variables, (2) calculating at least one of the following metrics: R-Squared, Adjusted R-Squared, Multiple R, Standard Error of the Estimates, ANOVA F Statistic, and ANOVA p-Value; (3) testing for regression errors including at least one of: heteroskedasticity, multicollinearity, micronumerosity, lags, leads, and autocorrelation, and (4) adjusting the data to fix any identified regression errors;an autoregressive integrated moving average (ARIMA) module configured to analyze and rank said forecasting and risk simulation models and methods from best to worst based on said adjusted user provided data, by testing various combinations of p, d, and q integers to determine the best-fitting model for the user provided data, wherein one or more of said ranked forecasting and risk simulation models may be selected for use in a simulation;a simulation selection module configured to allow a user to select an active simulation defined by one or more forecasting and/or risk simulation models being applied to a set of input variables derived from the user provided data;a stochastic process forecasting module configured to forecast future values for at least one of equities, assets, interest rates, inflation rates, and commodities using at least one of Brownian motion random walk, mean-reversion, and jump-diffusion;a distribution analysis module configured to generate the probability density function (PDF), cumulative distribution function (CDF), and the inverse cumulative distribution function (ICDF) of distributions calculated in the Risk Simulator; anda Statistical Analyses module comprising a Descriptive Statistics sub-module which includes descriptive statistics functions, a Distributional Fitting sub-module which includes distributional fitting functions, a Histogram and Charts sub-module which includes histogram and chart generating functions, a Hypothesis Testing sub-module which includes hypothesis testing functions to determine the probability that a given hypothesis is true, a Nonlinear Extrapolation sub-module which includes extrapolation functions that extrapolates or extends non-linear data into the future, a Normality Test sub-module which includes functions for determining whether the user provided data set is well-modeled by a normal distribution and how likely it is for a variable underlying the data set to be normally distributed, a Stochastic Process Parameter Estimation sub-module which includes functions for estimating parameters to achieve a best fit regarding characteristics of the user provided data set, a Time-series Autocorrelation sub-module which includes functions for identifying auto correlation as a function of time, and a Trend Line Projection sub-module which includes trend line projection functions. |
