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Found 10 papers, 0 papers with code
A Hypothesis on Good Practices for AI-based Systems for Financial Time Series Forecasting: Towards Domain-Driven XAI Methods
In this context, this paper explores good practices for deploying explainability in AI-based systems for finance, emphasising the importance of data quality, audience-specific methods, consideration of data properties, and the stability of explanations.
Explainable artificial intelligence
Explainable Artificial Intelligence (XAI)
+3
The Great Deception: A Comprehensive Study of Execution Strategies in Corporate Share Buy-Backs
This lack of research into the execution phase is surprising, especially when compared to the extensive literature on other capital allocation decisions, such as acquisition pricing.
Feature Selection via the Intervened Interpolative Decomposition and its Application in Diversifying Quantitative Strategies
In this paper, we propose a probabilistic model for computing an interpolative decomposition (ID) in which each column of the observed matrix has its own priority or importance, so that the end result of the decomposition finds a set of features that are representative of the entire set of features, and the selected features also have higher priority than others.
Applications of Reinforcement Learning in Finance -- Trading with a Double Deep Q-Network
We use a proven setup as the foundation for our environment with multiple extensions.
AI for trading strategies
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) perform compared to already successfully applied trading strategies such as Cross Signal Trading and a conventional statistical time series model ARMA-GARCH.
The Efficient Market Hypothesis for Bitcoin in the context of neural networks
This study examines the weak form of the efficient market hypothesis for Bitcoin using a feedforward neural network.
Deep reinforcement learning on a multi-asset environment for trading
Our trading strategy is trained and tested both on real and simulated price series and we compare the results with an index benchmark.
Generative Adversarial Networks in finance: an overview
Modelling in finance is a challenging task: the data often has complex statistical properties and its inner workings are largely unknown.
Explainable AI in Credit Risk Management
Artificial Intelligence (AI) has created the single biggest technology revolution the world has ever seen.
BIG-bench Machine Learning
Explainable Artificial Intelligence (XAI)
+1
The VIX index under scrutiny of machine learning techniques and neural networks
Using subset selection approaches on top of the original CBOE methodology, as well as building machine learning and neural network models including Random Forests, Support Vector Machines, feed-forward neural networks, and long short-term memory (LSTM) models, we will show that a small number of options is sufficient to replicate the VIX index.
