249 citations · 1.2k across the 77 of their papers we have counts for
6 papers · 1 filter
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…
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…
Machine Learning for Forecasting Mid Price Movement using Limit Order Book Data
Paraskevi Nousi, Avraam Tsantekidis, Nikolaos Passalis +5
Forecasting the movements of stock prices is one the most challenging problems in financial markets analysis. In this paper, we use Machine Learning (ML) algorithms for the predict…
Temporal Attention augmented Bilinear Network for Financial Time-Series Data Analysis
Dat Thanh Tran, Alexandros Iosifidis, Juho Kanniainen +1
Financial time-series forecasting has long been a challenging problem because of the inherently noisy and stochastic nature of the market. In the High-Frequency Trading (HFT), fore…
Tensor Representation in High-Frequency Financial Data for Price Change Prediction
Dat Thanh Tran, Martin Magris, Juho Kanniainen +2
Nowadays, with the availability of massive amount of trade data collected, the dynamics of the financial markets pose both a challenge and an opportunity for high frequency traders…
Benchmark Dataset for Mid-Price Forecasting of Limit Order Book Data with Machine Learning Methods
Adamantios Ntakaris, Martin Magris, Juho Kanniainen +2
Managing the prediction of metrics in high-frequency financial markets is a challenging task. An efficient way is by monitoring the dynamics of a limit order book to identify the i…