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Solving the problem of sustainable regional development by using a neural-network stock trading algorithm is of importance. Analysis has shown many businesses successfully use the stock market mechanisms not only to invest their temporarily disposable assets in securities portfolio, but also for speculation. Research has shown that in the modern world, the ever-larger bulk of stock exchange transactions are done by using mechanical trading systems (trading robots). AI-based systems stand out of mechanical trading systems. Our effort has produced a neural-network trading algorithm for speculative stock transactions with the SiH8 futures contract in USD. The developed neural network is a perception that has an sixparameter input layer, a hidden layer, and a single-parameter output layer that tells the user to either buy (+1) or sell a financial instrument. In the light of transition to digital economy, it is important to use artificial intelligence systems that enable big data processing for pattern-based problem solving. Keywords— sustainable development, speculative stock transactions, perceptron, neural-network algorithm, digital

Developing a AI Algorithm for Trading the SiH8 Futures Contract at MoEx on the Basis of Big Data Quantization