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The theoretical basis for the SAR-model applied for calculating the financial risk of time series of exchange instruments has been considered. The article describes the AI neural network for assessing financial risk in the course of exchange trading in a SiU8 US dollar futures contract on the Moscow Exchange by the MoExSAR method in order to minimize the risk.
There has been suggested and proven a hypothesis that the Kohonen map neural network enables forecasting the extent of loss in the course of exchange trading in a SiU8 US dollar futures contract on the Moscow Exchange by the MoExSAR method, as well as predicting the financial instrument price, which is of practical importance for successful trading.
The relevance is due to the fact that in the conditions of increasing volatility in the USD futures contract price, the risk of financial losses and its value increase, with the artificial intelligence systems applied being of great importance to forecast financial risk using the SAR model.
Assessing the extent of loss on financial risk using the neural network forecast of the financial instrument price has practical significance in the conditions of market uncertainty. The neural network that allows predicting both the SiU8 futures contract price and financial risk losses in the trading process has been successfully developed.
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- Financial Risk Assessment in the SiU8 Futures Trading Using Neural Network Based on the SAR-Method
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