Avraam Tsantekidis

According to our database, Avraam Tsantekidis authored at least 20 papers between 2017 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Modeling limit order trading with a continuous action policy for deep reinforcement learning.

Avraam Tsantekidis, Nikolaos Passalis, Anastasios Tefas

Neural Networks, August, 2023

Leveraging Deep Learning and Online Source Sentiment for Financial Portfolio Management.

Paraskevi Nousi, Loukia Avramelou, Georgios Rodinos, Maria Tzelepi, Theodoros Manousis, Konstantinos Tsampazis, Kyriakos Stefanidis, Dimitris Spanos, Emmanouil Kirtas, Pavlos Tosidis, Avraam Tsantekidis, Nikolaos Passalis, Anastasios Tefas

CoRR, 2023

2022

Multisource financial sentiment analysis for detecting Bitcoin price change indications using deep learning.

Nikolaos Passalis, Loukia Avramelou, Solon Seficha, Avraam Tsantekidis, Stavros Doropoulos, Giorgos Makris, Anastasios Tefas

Neural Comput. Appl., 2022

Online Knowledge Distillation for Financial Timeseries Forecasting.

Pavlos Floratos, Avraam Tsantekidis, Nikolaos Passalis, Anastasios Tefas

Proceedings of the International Conference on INnovations in Intelligent SysTems and Applications, 2022

Sentiment-Aware Distillation for Bitcoin Trend Forecasting Under Partial Observability.

Georgios Panagiotatos, Nikolaos Passalis, Avraam Tsantekidis, Anastasios Tefas

Proceedings of the IEEE International Conference on Acoustics, 2022

2021

Deep learning techniques for financial data

Avraam Tsantekidis

PhD thesis, 2021

Price Trailing for Financial Trading Using Deep Reinforcement Learning.

Avraam Tsantekidis, Nikolaos Passalis, Anastasia-Sotiria Toufa, Konstantinos Saitas Zarkias, Stergios Chairistanidis, Anastasios Tefas

IEEE Trans. Neural Networks Learn. Syst., 2021

Deep adaptive group-based input normalization for financial trading.

Angelos Nalmpantis, Nikolaos Passalis, Avraam Tsantekidis, Anastasios Tefas

Pattern Recognit. Lett., 2021

Diversity-driven knowledge distillation for financial trading using Deep Reinforcement Learning.

Avraam Tsantekidis, Nikolaos Passalis, Anastasios Tefas

Neural Networks, 2021

Transferring trading strategy knowledge to deep learning models.

Avraam Tsantekidis, Anastasios Tefas

Knowl. Inf. Syst., 2021

Improving Deep Reinforcement Learning for Financial Trading Using Deep Adaptive Group-Based Normalization.

Angelos Nalmpantis, Nikolaos Passalis, Avraam Tsantekidis, Anastasios Tefas

Proceedings of the 2021 IEEE 31st International Workshop on Machine Learning for Signal Processing (MLSP), 2021

Learning Sentiment-Aware Trading Strategies for Bitcoin Leveraging Deep Learning-Based Financial News Analysis.

Nikolaos Passalis, Solon Seficha, Avraam Tsantekidis, Anastasios Tefas

Proceedings of the Artificial Intelligence Applications and Innovations, 2021

2020

Using Deep Learning for price prediction by exploiting stationary limit order book features.

Avraam Tsantekidis, Nikolaos Passalis, Anastasios Tefas, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis

Appl. Soft Comput., 2020

Improving Deep Reinforcement Learning for Financial Trading Using Neural Network Distillation.

Avraam Tsantekidis, Nikolaos Passalis, Anastasios Tefas

Proceedings of the 30th IEEE International Workshop on Machine Learning for Signal Processing, 2020

2019

Machine Learning for Forecasting Mid-Price Movements Using Limit Order Book Data.

Paraskevi Nousi, Avraam Tsantekidis, Nikolaos Passalis, Adamantios Ntakaris, Juho Kanniainen, Anastasios Tefas, Moncef Gabbouj, Alexandros Iosifidis

IEEE Access, 2019

Deep Reinforcement Learning for Financial Trading Using Price Trailing.

Konstantinos Saitas Zarkias, Nikolaos Passalis, Avraam Tsantekidis, Anastasios Tefas

Proceedings of the IEEE International Conference on Acoustics, 2019

2018

Machine Learning for Forecasting Mid Price Movement using Limit Order Book Data.

Paraskevi Nousi, Avraam Tsantekidis, Nikolaos Passalis, Adamantios Ntakaris, Juho Kanniainen, Anastasios Tefas, Moncef Gabbouj, Alexandros Iosifidis

CoRR, 2018

2017

Forecasting Stock Prices from the Limit Order Book Using Convolutional Neural Networks.

Avraam Tsantekidis, Nikolaos Passalis, Anastasios Tefas, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis

Proceedings of the 19th IEEE Conference on Business Informatics, 2017

Using deep learning to detect price change indications in financial markets.

Avraam Tsantekidis, Nikolaos Passalis, Anastasios Tefas, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis

Proceedings of the 25th European Signal Processing Conference, 2017

Time-series classification using neural Bag-of-Features.

Nikolaos Passalis, Avraam Tsantekidis, Anastasios Tefas, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis

Proceedings of the 25th European Signal Processing Conference, 2017