For the purpose of managing financial risk and making investment decisions, interval stock
price forecasting is essential. Currently, decomposition integration frameworks are widely …

Statistical analysis of high-frequency stock market order transaction data is conducted to
understand order transition dynamics. We employ a first-order time-homogeneous discrete …

This work analyses the time evolution of the amplitude of chaos for the Historical Prices of
the Title Transfer Facility (TTF) and the United States Natural Gas Fund (UNG) commodities …

Extreme events (EEs) are rare and unpredictable, as have been observed in nature. Up to
now, manipulating EEs has remained a challenge. Here, we experimentally observe the …

This paper identifies the cryptocurrency market crashes and analyses its dynamics using the
complex network. We identify three distinct crashes during 2017-20, and the analysis is …

This paper employs Topological Data Analysis (TDA) to detect extreme events (EEs) in the
stock market at a continental level. Previous approaches, which analyzed stock indices …

Purpose: Share price movements after the COVID-19 pandemic experienced a decline in
several sectors, especially in the share prices of the Aneka Tambang Company, which …

Maximizing investment returns is a key focus for investors and stakeholders, the challenge
pertaining to stock market forecasting has assumed significant importance within this …

The first International Conference on Applied Intelligence (ICAI 2023) was held during
December 8–12, 2023, in Nanning, Guangxi, China. The conference was started to provide …