3 citations · 8 across the 5 of their papers we have counts for
5 papers
A Hypothesis on Good Practices for AI-based Systems for Financial Time Series Forecasting: Towards Domain-Driven XAI Methods
Branka Hadji Misheva, Joerg Osterrieder
Machine learning and deep learning have become increasingly prevalent in financial prediction and forecasting tasks, offering advantages such as enhanced customer experience, democ…
The Great Deception: A Comprehensive Study of Execution Strategies in Corporate Share Buy-Backs
Michael Seigne, Joerg Osterrieder
We delve into the intricate world of share buy-backs, a strategic corporate capital allocation tool that has gained significant prominence over the past few decades. Despite being…
The Efficient Market Hypothesis for Bitcoin in the context of neural networks
Mike Kraehenbuehl, Joerg Osterrieder
This study examines the weak form of the efficient market hypothesis for Bitcoin using a feedforward neural network. Due to the increasing popularity of cryptocurrencies in recent…
AI for trading strategies
Danijel Jevtic, Romain Deleze, Joerg Osterrieder
In this bachelor thesis, we show how four different machine learning methods (Long Short-Term Memory, Random Forest, Support Vector Machine Regression, and k-Nearest Neighbor) perf…
Applications of Reinforcement Learning in Finance -- Trading with a Double Deep Q-Network
Frensi Zejnullahu, Maurice Moser, Joerg Osterrieder
This paper presents a Double Deep Q-Network algorithm for trading single assets, namely the E-mini S&P 500 continuous futures contract. We use a proven setup as the foundation for…