The role of functional activation in neural networks in the context of financial time series analysis
Nowadays, neural networks are among the most popular analysis tools. They are effective in solving classification, pattern recognition, and clustering problems. This paper provides a detailed description and analysis of the operational principles of two neural networks, namely a Siamese network and a multilayer perceptron. A model for using these neural networks in time series forecasting is proposed. As an example, a web application was created in which the described neural networks were used to analyze the correlation between pairs of financial assets and assess t