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Stock prices forecasting model based on Walsh functions and Markov chain theory

A mathematical model for market stock prices forecasting within time periods from one to six months was developed. The model is based on modern signal processing methods and Markov chain theory. High forecasting accuracy regardless of stock prices probability distributions parameters and the model’s parameters adaptability due to calculations information storing are the model advantages. Economists, traders and students engaged in mathematical methods of financial markets behavior forecasting will be the most likely users of the model.