Juho Kanniainen

According to our database, Juho Kanniainen authored at least 44 papers between 2007 and 2024.

Collaborative distances:

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

2024

Valuation of option price in commodity markets described by a Markov-switching model: A case study of WTI crude oil market.

Farshid Mehrdoust, Idin Noorani, Juho Kanniainen

Math. Comput. Simul., January, 2024

Detachment Problem - Application in Prevention of Information Leakage in Stock Markets.

Henri Hansen, Juho Kanniainen

CoRR, 2024

2023

Early Warning Software for Emergency Department Crowding.

Jalmari Tuominen, Teemu Koivistoinen, Juho Kanniainen, Niku Oksala, Ari Palomäki, Antti Roine

J. Medical Syst., December, 2023

Predicting the trading behavior of socially connected investors: Graph neural network approach with implications to market surveillance.

Kestutis Baltakys, Margarita Baltakiene, Negar Heidari, Alexandros Iosifidis, Juho Kanniainen

Expert Syst. Appl., October, 2023

Augmented bilinear network for incremental multi-stock time-series classification.

Mostafa Shabani, Dat Thanh Tran, Juho Kanniainen, Alexandros Iosifidis

Pattern Recognit., September, 2023

Predicting the state of synchronization of financial time series using cross recurrence plots.

Mostafa Shabani, Martin Magris, George Tzagkarakis, Juho Kanniainen, Alexandros Iosifidis

Neural Comput. Appl., September, 2023

Sparse Index Tracking via Topological Learning.

Anubha Goel, Puneet Pasricha, Juho Kanniainen

CoRR, 2023

Forecasting Emergency Department Crowding with Advanced Machine Learning Models and Multivariable Input.

Jalmari Tuominen, Eetu Pulkkinen, Jaakko Peltonen, Juho Kanniainen, Niku Oksala, Ari Palomäki, Antti Roine

CoRR, 2023

Optimum Output Long Short-Term Memory Cell for High-Frequency Trading Forecasting.

Adamantios Ntakaris, Moncef Gabbouj, Juho Kanniainen

CoRR, 2023

Credit Card Fraud Detection with Subspace Learning-based One-Class Classification.

Zaffar Zaffar, Fahad Sohrab, Juho Kanniainen, Moncef Gabbouj

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2023

Cryptocurrency Portfolio Optimization by Neural Networks.

Quoc Minh Nguyen, Dat Thanh Tran, Juho Kanniainen, Alexandros Iosifidis, Moncef Gabbouj

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2023

2022

Trade synchronization and social ties in stock markets.

Margarita Baltakiene, Kestutis Baltakys, Juho Kanniainen

EPJ Data Sci., 2022

How informative is the Order Book Beyond the Best Levels? Machine Learning Perspective.

Dat Thanh Tran, Juho Kanniainen, Alexandros Iosifidis

CoRR, 2022

Multi-head Temporal Attention-Augmented Bilinear Network for Financial time series prediction.

Mostafa Shabani, Dat Thanh Tran, Martin Magris, Juho Kanniainen, Alexandros Iosifidis

Proceedings of the 30th European Signal Processing Conference, 2022

2021

Forecasting Financial Time Series Using Robust Deep Adaptive Input Normalization.

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

J. Signal Process. Syst., 2021

Structure of Investor Networks and Financial Crises.

Kestutis Baltakys, Hung Le Viet, Juho Kanniainen

Entropy, 2021

Bilinear Input Normalization for Neural Networks in Financial Forecasting.

Dat Thanh Tran, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis

CoRR, 2021

2020

Deep Adaptive Input Normalization for Time Series Forecasting.

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

IEEE Trans. Neural Networks Learn. Syst., 2020

Temporal Bag-of-Features Learning for Predicting Mid Price Movements Using High Frequency Limit Order Book Data.

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

IEEE Trans. Emerg. Top. Comput. Intell., 2020

Temporal logistic neural Bag-of-Features for financial time series forecasting leveraging limit order book data.

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

Pattern Recognit. Lett., 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

Data Normalization for Bilinear Structures in High-Frequency Financial Time-series.

Dat Thanh Tran, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis

Proceedings of the 25th International Conference on Pattern Recognition, 2020

Adaptive Normalization for Forecasting Limit Order Book Data Using Convolutional Neural Networks.

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

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019

Temporal Attention-Augmented Bilinear Network for Financial Time-Series Data Analysis.

Dat Thanh Tran, Alexandros Iosifidis, Juho Kanniainen, Moncef Gabbouj

IEEE Trans. Neural Networks Learn. Syst., 2019

Mid-price Prediction Based on Machine Learning Methods with Technical and Quantitative Indicators.

Adamantios Ntakaris, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis

CoRR, 2019

Data-driven Neural Architecture Learning For Financial Time-series Forecasting.

Dat Thanh Tran, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis

CoRR, 2019

Deep Adaptive Input Normalization for Price Forecasting using Limit Order Book Data.

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

CoRR, 2019

Feature Engineering for Mid-Price Prediction With Deep Learning.

Adamantios Ntakaris, Giorgio Mirone, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis

IEEE Access, 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 Temporal Logistic Bag-of-features for Forecasting High Frequency Limit Order Book Time Series.

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

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

Benchmark Dataset for Mid-Price Prediction of Limit Order Book data.

Adamantios Ntakaris, Martin Magris, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis

CoRR, 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

Tensor representation in high-frequency financial data for price change prediction.

Dat Thanh Tran, Martin Magris, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis

Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, 2017

Long-range auto-correlations in limit order book markets: Inter-and cross-event analysis.

Martin Magris, Jiyeong Kim, Esa Räsänen, Juho Kanniainen

Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, 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

2015

A fast universal self-tuned sampler within Gibbs sampling.

Luca Martino, H. Yang, David Luengo, Juho Kanniainen, Jukka Corander

Digit. Signal Process., 2015

2013

Calibration of GARCH models using concurrent accelerated random search.

Juliane Müller, Juho Kanniainen, Robert Piché

Appl. Math. Comput., 2013

2011

Forecasting the Diffusion of Innovation: A Stochastic Bass Model With Log-Normal and Mean-Reverting Error Process.

Juho Kanniainen, Saku J. Mäkinen, Robert Piché, Alok Chakrabarti

IEEE Trans. Engineering Management, 2011

Option pricing under joint dynamics of interest rates, dividends, and stock prices.

Juho Kanniainen

Oper. Res. Lett., 2011

2009

Can properly discounted projects follow geometric Brownian motion?

Juho Kanniainen

Math. Methods Oper. Res., 2009

Matrix-based numerical modelling of financial differential equations.

Robert Piché, Juho Kanniainen

Int. J. Math. Model. Numer. Optimisation, 2009

2007

Solving financial differential equations using differentiation matrices.

Robert Piché, Juho Kanniainen

Proceedings of the World Congress on Engineering, 2007