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2020 – today
- 2024
[j21]Farshid Mehrdoust, Idin Noorani
, Juho Kanniainen:
Valuation of option price in commodity markets described by a Markov-switching model: A case study of WTI crude oil market. Math. Comput. Simul. 215: 228-269 (2024)- [i22]Henri Hansen, Juho Kanniainen:
Detachment Problem - Application in Prevention of Information Leakage in Stock Markets. CoRR abs/2401.07074 (2024) - 2023
- [j20]Kestutis Baltakys, Margarita Baltakiene, Negar Heidari, Alexandros Iosifidis, Juho Kanniainen:
Predicting the trading behavior of socially connected investors: Graph neural network approach with implications to market surveillance. Expert Syst. Appl. 228: 120285 (2023) - [j19]Jalmari Tuominen, Teemu Koivistoinen, Juho Kanniainen, Niku Oksala, Ari Palomäki, Antti Roine:
Early Warning Software for Emergency Department Crowding. J. Medical Syst. 47(1): 66 (2023) - [j18]Mostafa Shabani, Martin Magris, George Tzagkarakis, Juho Kanniainen, Alexandros Iosifidis:
Predicting the state of synchronization of financial time series using cross recurrence plots. Neural Comput. Appl. 35(25): 18519-18531 (2023) - [j17]Mostafa Shabani, Dat Thanh Tran, Juho Kanniainen, Alexandros Iosifidis:
Augmented bilinear network for incremental multi-stock time-series classification. Pattern Recognit. 141: 109604 (2023) - [c12]Quoc Minh Nguyen, Dat Thanh Tran, Juho Kanniainen, Alexandros Iosifidis, Moncef Gabbouj:
Cryptocurrency Portfolio Optimization by Neural Networks. SSCI 2023: 25-32 - [c11]Zaffar Zaffar, Fahad Sohrab, Juho Kanniainen, Moncef Gabbouj:
Credit Card Fraud Detection with Subspace Learning-based One-Class Classification. SSCI 2023: 407-412 - [i21]Jalmari Tuominen, Teemu Koivistoinen, Juho Kanniainen, Niku Oksala, Ari Palomäki, Antti Roine:
Early Warning Software for Emergency Department Crowding. CoRR abs/2301.09108 (2023) - [i20]Adamantios Ntakaris, Moncef Gabbouj, Juho Kanniainen:
Optimum Output Long Short-Term Memory Cell for High-Frequency Trading Forecasting. CoRR abs/2304.09840 (2023) - [i19]Jalmari Tuominen, Eetu Pulkkinen, Jaakko Peltonen, Juho Kanniainen, Niku Oksala, Ari Palomäki, Antti Roine:
Forecasting Emergency Department Crowding with Advanced Machine Learning Models and Multivariable Input. CoRR abs/2308.16544 (2023) - [i18]Zaffar Zaffar, Fahad Sohrab, Juho Kanniainen, Moncef Gabbouj:
Credit Card Fraud Detection with Subspace Learning-based One-Class Classification. CoRR abs/2309.14880 (2023) - [i17]Quoc Minh Nguyen, Dat Thanh Tran, Juho Kanniainen, Alexandros Iosifidis, Moncef Gabbouj:
Cryptocurrency Portfolio Optimization by Neural Networks. CoRR abs/2310.01148 (2023) - [i16]Anubha Goel, Puneet Pasricha, Juho Kanniainen:
Sparse Index Tracking via Topological Learning. CoRR abs/2310.09578 (2023) - 2022
- [j16]Margarita Baltakiene, Kestutis Baltakys, Juho Kanniainen:
Trade synchronization and social ties in stock markets. EPJ Data Sci. 11(1): 54 (2022) - [c10]Mostafa Shabani, Dat Thanh Tran, Martin Magris, Juho Kanniainen, Alexandros Iosifidis:
Multi-head Temporal Attention-Augmented Bilinear Network for Financial time series prediction. EUSIPCO 2022: 1487-1491 - [i15]Mostafa Shabani, Dat Thanh Tran, Martin Magris, Juho Kanniainen, Alexandros Iosifidis:
Multi-head Temporal Attention-Augmented Bilinear Network for Financial time series prediction. CoRR abs/2201.05459 (2022) - [i14]Dat Thanh Tran, Juho Kanniainen, Alexandros Iosifidis:
How informative is the Order Book Beyond the Best Levels? Machine Learning Perspective. CoRR abs/2203.07922 (2022) - [i13]Mostafa Shabani, Dat Thanh Tran, Juho Kanniainen, Alexandros Iosifidis:
Augmented Bilinear Network for Incremental Multi-Stock Time-Series Classification. CoRR abs/2207.11577 (2022) - 2021
- [j15]Kestutis Baltakys, Hung Le Viet, Juho Kanniainen:
Structure of Investor Networks and Financial Crises. Entropy 23(4): 381 (2021) - [j14]Nikolaos Passalis, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis, Anastasios Tefas:
Forecasting Financial Time Series Using Robust Deep Adaptive Input Normalization. J. Signal Process. Syst. 93(10): 1235-1251 (2021) - [i12]Dat Thanh Tran, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis:
Bilinear Input Normalization for Neural Networks in Financial Forecasting. CoRR abs/2109.00983 (2021) - 2020
- [j13]Avraam Tsantekidis, Nikolaos Passalis, Anastasios Tefas, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis:
Using Deep Learning for price prediction by exploiting stationary limit order book features. Appl. Soft Comput. 93: 106401 (2020) - [j12]Nikolaos Passalis, Anastasios Tefas, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis:
Temporal logistic neural Bag-of-Features for financial time series forecasting leveraging limit order book data. Pattern Recognit. Lett. 136: 183-189 (2020) - [j11]Nikolaos Passalis, Anastasios Tefas, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis:
Temporal Bag-of-Features Learning for Predicting Mid Price Movements Using High Frequency Limit Order Book Data. IEEE Trans. Emerg. Top. Comput. Intell. 4(6): 774-785 (2020) - [j10]Nikolaos Passalis, Anastasios Tefas, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis:
Deep Adaptive Input Normalization for Time Series Forecasting. IEEE Trans. Neural Networks Learn. Syst. 31(9): 3760-3765 (2020) - [c9]Nikolaos Passalis, Anastasios Tefas, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis:
Adaptive Normalization for Forecasting Limit Order Book Data Using Convolutional Neural Networks. ICASSP 2020: 1713-1717 - [c8]Dat Thanh Tran, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis:
Data Normalization for Bilinear Structures in High-Frequency Financial Time-series. ICPR 2020: 7287-7292 - [i11]Dat Thanh Tran, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis:
Data Normalization for Bilinear Structures in High-Frequency Financial Time-series. CoRR abs/2003.00598 (2020)
2010 – 2019
- 2019
- [j9]Paraskevi Nousi, Avraam Tsantekidis, Nikolaos Passalis, Adamantios Ntakaris, Juho Kanniainen, Anastasios Tefas, Moncef Gabbouj, Alexandros Iosifidis:
Machine Learning for Forecasting Mid-Price Movements Using Limit Order Book Data. IEEE Access 7: 64722-64736 (2019) - [j8]Adamantios Ntakaris, Giorgio Mirone, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis:
Feature Engineering for Mid-Price Prediction With Deep Learning. IEEE Access 7: 82390-82412 (2019) - [j7]Dat Thanh Tran, Alexandros Iosifidis, Juho Kanniainen, Moncef Gabbouj:
Temporal Attention-Augmented Bilinear Network for Financial Time-Series Data Analysis. IEEE Trans. Neural Networks Learn. Syst. 30(5): 1407-1418 (2019) - [c7]Nikolaos Passalis, Anastasios Tefas, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis:
Deep Temporal Logistic Bag-of-features for Forecasting High Frequency Limit Order Book Time Series. ICASSP 2019: 7545-7549 - [i10]Nikolaos Passalis, Anastasios Tefas, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis:
Temporal Logistic Neural Bag-of-Features for Financial Time series Forecasting leveraging Limit Order Book Data. CoRR abs/1901.08280 (2019) - [i9]Nikolaos Passalis, Anastasios Tefas, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis:
Deep Adaptive Input Normalization for Price Forecasting using Limit Order Book Data. CoRR abs/1902.07892 (2019) - [i8]Dat Thanh Tran, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis:
Data-driven Neural Architecture Learning For Financial Time-series Forecasting. CoRR abs/1903.06751 (2019) - [i7]Adamantios Ntakaris, Giorgio Mirone, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis:
Feature Engineering for Mid-Price Prediction with Deep Learning. CoRR abs/1904.05384 (2019) - [i6]Adamantios Ntakaris, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis:
Mid-price Prediction Based on Machine Learning Methods with Technical and Quantitative Indicators. CoRR abs/1907.09452 (2019) - 2018
- [i5]Paraskevi Nousi, Avraam Tsantekidis, Nikolaos Passalis, Adamantios Ntakaris, Juho Kanniainen, Anastasios Tefas, Moncef Gabbouj, Alexandros Iosifidis:
Machine Learning for Forecasting Mid Price Movement using Limit Order Book Data. CoRR abs/1809.07861 (2018) - [i4]Avraam Tsantekidis, Nikolaos Passalis, Anastasios Tefas, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis:
Using Deep Learning for price prediction by exploiting stationary limit order book features. CoRR abs/1810.09965 (2018) - 2017
- [c6]Nikolaos Passalis, Avraam Tsantekidis, Anastasios Tefas, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis:
Time-series classification using neural Bag-of-Features. EUSIPCO 2017: 301-305 - [c5]Avraam Tsantekidis, Nikolaos Passalis, Anastasios Tefas, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis:
Using deep learning to detect price change indications in financial markets. EUSIPCO 2017: 2511-2515 - [c4]Martin Magris, Jiyeong Kim, Esa Räsänen, Juho Kanniainen:
Long-range auto-correlations in limit order book markets: Inter-and cross-event analysis. SSCI 2017: 1-7 - [c3]Dat Thanh Tran, Martin Magris, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis:
Tensor representation in high-frequency financial data for price change prediction. SSCI 2017: 1-7 - [c2]Avraam Tsantekidis, Nikolaos Passalis, Anastasios Tefas, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis:
Forecasting Stock Prices from the Limit Order Book Using Convolutional Neural Networks. CBI (1) 2017: 7-12 - [i3]Adamantios Ntakaris, Martin Magris, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis:
Benchmark Dataset for Mid-Price Prediction of Limit Order Book data. CoRR abs/1705.03233 (2017) - [i2]Dat Thanh Tran, Martin Magris, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis:
Tensor Representation in High-Frequency Financial Data for Price Change Prediction. CoRR abs/1709.01268 (2017) - [i1]Dat Thanh Tran, Alexandros Iosifidis, Juho Kanniainen, Moncef Gabbouj:
Temporal Attention augmented Bilinear Network for Financial Time-Series Data Analysis. CoRR abs/1712.00975 (2017) - 2015
- [j6]Luca Martino, H. Yang, David Luengo, Juho Kanniainen, Jukka Corander:
A fast universal self-tuned sampler within Gibbs sampling. Digit. Signal Process. 47: 68-83 (2015) - 2013
- [j5]Juliane Müller, Juho Kanniainen, Robert Piché:
Calibration of GARCH models using concurrent accelerated random search. Appl. Math. Comput. 221: 522-534 (2013) - 2011
- [j4]Juho Kanniainen:
Option pricing under joint dynamics of interest rates, dividends, and stock prices. Oper. Res. Lett. 39(4): 260-264 (2011) - [j3]Juho Kanniainen, Saku J. Mäkinen, Robert Piché, Alok Chakrabarti:
Forecasting the Diffusion of Innovation: A Stochastic Bass Model With Log-Normal and Mean-Reverting Error Process. IEEE Trans. Engineering Management 58(2): 228-249 (2011)
2000 – 2009
- 2009
- [j2]Robert Piché, Juho Kanniainen:
Matrix-based numerical modelling of financial differential equations. Int. J. Math. Model. Numer. Optimisation 1(1/2): 88-100 (2009) - [j1]Juho Kanniainen:
Can properly discounted projects follow geometric Brownian motion? Math. Methods Oper. Res. 70(3): 435-450 (2009) - 2007
- [c1]Robert Piché, Juho Kanniainen:
Solving financial differential equations using differentiation matrices. World Congress on Engineering 2007: 1016-1022
Coauthor Index
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last updated on 2024-10-07 21:25 CEST by the dblp team
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