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In this paper we apply a new approach of the string theory to the realfinancial market. It is direct extension and application of the work [1] intoprediction of prices. The models are constructed with an idea of predictionmodels based on the string invariants (PMBSI). The performance of PMBSI iscompared to support vector machines (SVM) and artificial neural networks (ANN)on an artificial and a financial time series. Brief overview of the results andanalysis is given. The first model is based on the correlation function asinvariant and the second one is an application based on the deviations from theclosed string/pattern form (PMBCS). We found the difference between these twoapproaches. The first model cannot predict the behavior of the forex marketwith good efficiency in comparison with the second one which is, in addition,able to make relevant profit per year.

The string prediction models as an invariants of time series in forex market