249 citations · 586 across the 43 of their papers we have counts for
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Prospects of Imitating Trading Agents in the Stock Market
Mateusz Wilinski, Juho Kanniainen
In this work we show how generative tools, which were successfully applied to limit order book data, can be utilized for the task of imitating trading agents. To this end, we propo…
Agent-based model of information diffusion in the limit order book trading
Mateusz Wilinski, Juho Kanniainen
There are multiple explanations for stylized facts in high-frequency trading, including adaptive and informed agents, many of which have been studied through agent-based models. Th…
Classifying and Clustering Trading Agents
Mateusz Wilinski, Anubha Goel, Alexandros Iosifidis +1
The rapid development of sophisticated machine learning methods, together with the increased availability of financial data, has the potential to transform financial research, but…
Deep Adaptive Input Normalization for Time Series Forecasting
Nikolaos Passalis, Anastasios Tefas, Juho Kanniainen +2
Deep Learning (DL) models can be used to tackle time series analysis tasks with great success. However, the performance of DL models can degenerate rapidly if the data are not appr…
Computational Analysis of the structural properties of Economic and Financial Networks
Frank Emmert-Streib, Aliyu Musa, Kestutis Baltakys +5
In recent years, methods from network science are gaining rapidly interest in economics and finance. A reason for this is that in a globalized world the interconnectedness among ec…