3 citations · 4 across the 7 of their papers we have counts for
7 papers
Explainable Patterns in Cryptocurrency Microstructure
Bartosz Bieganowski, Robert Ślepaczuk
We document stable cross-asset patterns in cryptocurrency limit-order-book microstructure: the same engineered order book and trade features exhibit remarkably similar predictive i…
EXFormer: A Multi-Scale Trend-Aware Transformer with Dynamic Variable Selection for Foreign Exchange Returns Prediction
Dinggao Liu, Robert Ślepaczuk, Zhenpeng Tang
Accurately forecasting daily exchange rate returns represents a longstanding challenge in international finance, as the exchange rate returns are driven by a multitude of correlate…
Stochastic Volatility Modelling with LSTM Networks: A Hybrid Approach for S&P 500 Index Volatility Forecasting
Anna Perekhodko, Robert Ślepaczuk
Accurate volatility forecasting is essential in banking, investment, and risk management, because expectations about future market movements directly influence current decisions. T…
Alternative Loss Function in Evaluation of Transformer Models
Jakub Michańków, Paweł Sakowski, Robert Ślepaczuk
The proper design and architecture of testing machine learning models, especially in their application to quantitative finance problems, is crucial. The most important aspect of th…
Hybrid Models for Financial Forecasting: Combining Econometric, Machine Learning, and Deep Learning Models
Dominik Stempień, Robert Ślepaczuk
This research systematically develops and evaluates various hybrid modeling approaches by combining traditional econometric models (ARIMA and ARFIMA models) with machine learning a…
Informer in Algorithmic Investment Strategies on High Frequency Bitcoin Data
Filip Stefaniuk, Robert Ślepaczuk
The article investigates the usage of Informer architecture for building automated trading strategies for high frequency Bitcoin data. Three strategies using Informer model with di…