Abstract: This is an invention implying a risk management method based on synthetic data. Synthetic data are random variables that take their mean and standard deviation from experimental data. It reproduces the experimental data underlying statistic information with a statistical confidence of 99%. Experimental data could represent financial variables i.e., prices and quantities. This method implements alternative recursive bias approach that achieve convergence with related estimations already published. Also, this method is decomposable allowing synthetic data and econometric models parameter values and different risk scenarios alternatives in order to measure the system responses under different controls.

Abstract: This is an invention implying a system and method to construct synthetic data of said financial variables i.e., prices and quantities and to construct sophisticated econometric models that achieve convergence with related estimations already published. These system and method is abled to run under different risk scenarios and input settings; they also allow lower costs by simulating time frequencies, variables and factors of economic activity, through the use of random number machines and Monte Carlo simulations. This invention furnishes risk sensitivities based on sophisticated econometric models and mathematical not lineal models and a set of behavioral and statistic assumptions by using the synthetic data herein constructed. Great results in providing criteria for risk management and decision making with 99% of statistical significance. Modifications of this invention can generate a multiplicity of applications by those skilled in the art.