Juho Kanniainen

According to our database1, Juho Kanniainen authored at least 23 papers between 2007 and 2019.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.



In proceedings 
PhD thesis 



On csauthors.net:


Mid-price Prediction Based on Machine Learning Methods with Technical and Quantitative Indicators.
CoRR, 2019

Data-driven Neural Architecture Learning For Financial Time-series Forecasting.
CoRR, 2019

Deep Adaptive Input Normalization for Price Forecasting using Limit Order Book Data.
CoRR, 2019

Temporal Logistic Neural Bag-of-Features for Financial Time series Forecasting leveraging Limit Order Book Data.
CoRR, 2019

Feature Engineering for Mid-Price Prediction With Deep Learning.
IEEE Access, 2019

Machine Learning for Forecasting Mid-Price Movements Using Limit Order Book Data.
IEEE Access, 2019

Deep Temporal Logistic Bag-of-features for Forecasting High Frequency Limit Order Book Time Series.
Proceedings of the IEEE International Conference on Acoustics, 2019

Using Deep Learning for price prediction by exploiting stationary limit order book features.
CoRR, 2018

Machine Learning for Forecasting Mid Price Movement using Limit Order Book Data.
CoRR, 2018

Temporal Attention augmented Bilinear Network for Financial Time-Series Data Analysis.
CoRR, 2017

Tensor Representation in High-Frequency Financial Data for Price Change Prediction.
CoRR, 2017

Benchmark Dataset for Mid-Price Prediction of Limit Order Book data.
CoRR, 2017

Forecasting Stock Prices from the Limit Order Book Using Convolutional Neural Networks.
Proceedings of the 19th IEEE Conference on Business Informatics, 2017

Long-range auto-correlations in limit order book markets: Inter-and cross-event analysis.
Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, 2017

Using deep learning to detect price change indications in financial markets.
Proceedings of the 25th European Signal Processing Conference, 2017

Time-series classification using neural Bag-of-Features.
Proceedings of the 25th European Signal Processing Conference, 2017

A fast universal self-tuned sampler within Gibbs sampling.
Digital Signal Processing, 2015

Calibration of GARCH models using concurrent accelerated random search.
Applied Mathematics and Computation, 2013

Forecasting the Diffusion of Innovation: A Stochastic Bass Model With Log-Normal and Mean-Reverting Error Process.
IEEE Trans. Engineering Management, 2011

Option pricing under joint dynamics of interest rates, dividends, and stock prices.
Oper. Res. Lett., 2011

Can properly discounted projects follow geometric Brownian motion?
Math. Meth. of OR, 2009

Matrix-based numerical modelling of financial differential equations.
IJMNO, 2009

Solving financial differential equations using differentiation matrices.
Proceedings of the World Congress on Engineering, 2007