The financial market is a complex system with chaotic behavior that can lead to wild swings within the system. This drive into variety of interesting phenomenon such as phase transitions, bubbles, and crashes, so on. Of interest in modelling identifying distribution stylized facts particular time series, determine if volatility present, resulting risk contagion. Regression has been used this st...

Researchers are employing deep learning (DL) in many fields, and the scope of its application is expanding. However, because understanding rationale validity DL decisions difficult, a model occasionally called black-box model. Here, we focus on DL-based explainable time-series prediction We propose based long short-term memory (LSTM) followed by convolutional neural network (CNN) with residual ...

Symbolic encoding of information is the foundation Shannon’s mathematical theory communication. The concept informational efficiency capital markets closely related to issue processing by equity market participants. Therefore, aim this comprehensive research examine and compare a battery methods based on symbolic coding with thresholds modified Shannon entropy in context stock efficiency. As th...

The article considers financial and economic time series in production, banking, investment branches. Empirical research the field of economics increasingly uses data at individual or household level obtained from surveys. Some variables are difficult enough to measure that such problems arise even when estimating simple bivariate regressions; panel used ways effectively distinguish much true c...