Risk management is facilitated by tracking and forecasting multivariate data using nonparametric statistical procedures. Enhanced matrix factorization is used for developing a nonparametric tracking and forecasting algorithm, based on Kalman smoothing, that applies a state space model to both (i) factor loading, and (ii) factor time series of multivariate data in the matrix factorization. One example of use is tracking and forecasting financial risk according to a yield curve based on multivariate financial data. The forecasted yield curve change forms the bases, for example, of risk exposure adjustments associated with US Treasury bond investment.
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