Emergency department (ED) crowding is a significant threat to patient sa...
High-frequency trading requires fast data processing without information...
Cross-correlation analysis is a powerful tool for understanding the mutu...
Deep Learning models have become dominant in tackling financial time-ser...
Research on limit order book markets has been rapidly growing and nowada...
Financial time-series forecasting is one of the most challenging domains...
Data normalization is one of the most important preprocessing steps when...
Financial time-series analysis and forecasting have been extensively stu...
Stock price prediction is a challenging task, but machine learning metho...
Mid-price movement prediction based on limit order book (LOB) data is a
...
Mid-price movement prediction based on limit order book (LOB) data is a
...
Forecasting based on financial time-series is a challenging task since m...
Deep Learning (DL) models can be used to tackle time series analysis tas...
Time series forecasting is a crucial component of many important
applica...
The recent surge in Deep Learning (DL) research of the past decade has
s...
Forecasting the movements of stock prices is one the most challenging
pr...
Financial time-series forecasting has long been a challenging problem be...
Nowadays, with the availability of massive amount of trade data collecte...
Presently, managing prediction of metrics in high frequency financial ma...