8 citations · 9 across the 8 of their papers we have counts for
16 papers
How informative is the Order Book Beyond the Best Levels? Machine Learning Perspective
Dat Thanh Tran, Juho Kanniainen, Alexandros Iosifidis
Research on limit order book markets has been rapidly growing and nowadays high-frequency full order book data is widely available for researchers and practitioners. However, it is…
Multi-head Temporal Attention-Augmented Bilinear Network for Financial time series prediction
Mostafa Shabani, Dat Thanh Tran, Martin Magris +2
Financial time-series forecasting is one of the most challenging domains in the field of time-series analysis. This is mostly due to the highly non-stationary and noisy nature of f…
Bilinear Input Normalization for Neural Networks in Financial Forecasting
Dat Thanh Tran, Juho Kanniainen, Moncef Gabbouj +1
Data normalization is one of the most important preprocessing steps when building a machine learning model, especially when the model of interest is a deep neural network. This is…
Data Normalization for Bilinear Structures in High-Frequency Financial Time-series
Dat Thanh Tran, Juho Kanniainen, Moncef Gabbouj +1
Financial time-series analysis and forecasting have been extensively studied over the past decades, yet still remain as a very challenging research topic. Since the financial marke…
Mid-price Prediction Based on Machine Learning Methods with Technical and Quantitative Indicators
Adamantios Ntakaris, Juho Kanniainen, Moncef Gabbouj +1
Stock price prediction is a challenging task, but machine learning methods have recently been used successfully for this purpose. In this paper, we extract over 270 hand-crafted fe…
Clusters of investors around Initial Public Offering
Margarita Baltakienė, Kęstutis Baltakys, Juho Kanniainen +2
The complex networks approach has been gaining popularity in analysing investor behaviour and stock markets, but within this approach, initial public offerings (IPO) have barely be…