249 citations · 586 across the 43 of their papers we have counts for
6 papers · 1 filter
Predicting the State of Synchronization of Financial Time Series using Cross Recurrence Plots
Mostafa Shabani, Martin Magris, George Tzagkarakis +2
Cross-correlation analysis is a powerful tool for understanding the mutual dynamics of time series. This study introduces a new method for predicting the future state of synchroniz…
Bilinear Input Normalization for Neural Networks in Financial Forecasting
Dat Thanh Tran, Juho Kanniainen, Moncef Gabbouj +1
Data normalization is one of the most important preprocessing steps when building a machine learning model, especially when the model of interest is a deep neural network. This is…
Mid-price Prediction Based on Machine Learning Methods with Technical and Quantitative Indicators
Adamantios Ntakaris, Juho Kanniainen, Moncef Gabbouj +1
Stock price prediction is a challenging task, but machine learning methods have recently been used successfully for this purpose. In this paper, we extract over 270 hand-crafted fe…
Feature Engineering for Mid-Price Prediction with Deep Learning
Adamantios Ntakaris, Giorgio Mirone, Juho Kanniainen +2
Mid-price movement prediction based on limit order book (LOB) data is a challenging task due to the complexity and dynamics of the LOB. So far, there have been very limited attempt…
Option market (in)efficiency and implied volatility dynamics after return jumps
Juho Kanniainen, Martin Magris
In informationally efficient financial markets, option prices and this implied volatility should immediately be adjusted to new information that arrives along with a jump in underl…
Implied volatility smile dynamics in the presence of jumps
Martin Magris, Perttu Barholm, Juho Kanniainen
The main purpose of this work is to examine the behavior of the implied volatility smiles around jumps, contributing to the literature with a high-frequency analysis of the smile d…