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08/31/2023
Forecasting Emergency Department Crowding with Advanced Machine Learning Models and Multivariable Input
Emergency department (ED) crowding is a significant threat to patient sa...
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04/17/2023
Optimum Output Long Short-Term Memory Cell for High-Frequency Trading Forecasting
High-frequency trading requires fast data processing without information...
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10/26/2022
Predicting the State of Synchronization of Financial Time Series using Cross Recurrence Plots
Cross-correlation analysis is a powerful tool for understanding the mutu...
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07/23/2022
Augmented Bilinear Network for Incremental Multi-Stock Time-Series Classification
Deep Learning models have become dominant in tackling financial time-ser...
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03/15/2022
How informative is the Order Book Beyond the Best Levels? Machine Learning Perspective
Research on limit order book markets has been rapidly growing and nowada...
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01/14/2022
Multi-head Temporal Attention-Augmented Bilinear Network for Financial time series prediction
Financial time-series forecasting is one of the most challenging domains...
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09/01/2021
Bilinear Input Normalization for Neural Networks in Financial Forecasting
Data normalization is one of the most important preprocessing steps when...
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03/01/2020
Data Normalization for Bilinear Structures in High-Frequency Financial Time-series
Financial time-series analysis and forecasting have been extensively stu...
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07/13/2019
Mid-price Prediction Based on Machine Learning Methods with Technical and Quantitative Indicators
Stock price prediction is a challenging task, but machine learning metho...
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04/10/2019
Feature Engineering for Mid-Price Prediction with Deep Learning
Mid-price movement prediction based on limit order book (LOB) data is a ...
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04/10/2019
Feature Engineering for Mid-Price Prediction Forecasting with Deep Learning
Mid-price movement prediction based on limit order book (LOB) data is a ...
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03/05/2019
Data-driven Neural Architecture Learning For Financial Time-series Forecasting
Forecasting based on financial time-series is a challenging task since m...
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02/21/2019
Deep Adaptive Input Normalization for Price Forecasting using Limit Order Book Data
Deep Learning (DL) models can be used to tackle time series analysis tas...
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01/24/2019
Temporal Logistic Neural Bag-of-Features for Financial Time series Forecasting leveraging Limit Order Book Data
Time series forecasting is a crucial component of many important applica...
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10/23/2018
Using Deep Learning for price prediction by exploiting stationary limit order book features
The recent surge in Deep Learning (DL) research of the past decade has s...
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09/19/2018
Machine Learning for Forecasting Mid Price Movement using Limit Order Book Data
Forecasting the movements of stock prices is one the most challenging pr...
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12/04/2017
Temporal Attention augmented Bilinear Network for Financial Time-Series Data Analysis
Financial time-series forecasting has long been a challenging problem be...
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09/05/2017
Tensor Representation in High-Frequency Financial Data for Price Change Prediction
Nowadays, with the availability of massive amount of trade data collecte...
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05/09/2017
