Add to ORKGThe data science competition forum Kaggle, in conjunction with Two Sigma, proposed a financial modeling competition open to the public. The challenge is to predict an anonymous time-varying financial instrument based on anonymous features given in the dataset. To accomplish this task, we will demonstrate several machine learning techniques and show how well they perform in the prediction of the class variable. These techniques include Ridge Regression, Extreme Gradient Boosting, and Extremely Randomized Trees. We will review each of the techniques, and then show the results of how they worked independently and together
One of the most sought-after but equally complex and thus challenging areas in financial markets is ...
ABSTRACT Conjunct with the universal acceleration in information growth, financial services have bee...
This study investigates how modern machine learning (ML) techniques can be used to advance the field...
This article focuses on supervised learning and reinforcement learning. These areas overlap most wit...
Machine learning methods penetrate to applications in the analysis of financial data, particularly t...
This paper presents an overview of the procedures involved in prediction with machine learning model...
Machine Learning (ML) for finance is a fruitful approach to detect patterns in data. However, when i...
I, Tristan Fletcher, confirm that the work presented in this thesis is my own. Where information has...
The modeling of customer features has become a core component in modern financial analytics. There a...
In the dynamic world of financial markets, accurate price predictions are essential for informed dec...
Forecasting procedures have found applications in a wide variety of areas within finance and have fu...
The unparalleled success of machine learning is indisputable. It has transformed the world with unim...
In recent years, machine learning algorithms have been successfully employed to leverage the potenti...
The main aim and contribution of this study is to outline and demonstrate the usefulness of a machin...
Financial researchers, who often work with large volumes of financial data, need efficient tools to ...
One of the most sought-after but equally complex and thus challenging areas in financial markets is ...
ABSTRACT Conjunct with the universal acceleration in information growth, financial services have bee...
This study investigates how modern machine learning (ML) techniques can be used to advance the field...
This article focuses on supervised learning and reinforcement learning. These areas overlap most wit...
Machine learning methods penetrate to applications in the analysis of financial data, particularly t...
This paper presents an overview of the procedures involved in prediction with machine learning model...
Machine Learning (ML) for finance is a fruitful approach to detect patterns in data. However, when i...
I, Tristan Fletcher, confirm that the work presented in this thesis is my own. Where information has...
The modeling of customer features has become a core component in modern financial analytics. There a...
In the dynamic world of financial markets, accurate price predictions are essential for informed dec...
Forecasting procedures have found applications in a wide variety of areas within finance and have fu...
The unparalleled success of machine learning is indisputable. It has transformed the world with unim...
In recent years, machine learning algorithms have been successfully employed to leverage the potenti...
The main aim and contribution of this study is to outline and demonstrate the usefulness of a machin...
Financial researchers, who often work with large volumes of financial data, need efficient tools to ...
One of the most sought-after but equally complex and thus challenging areas in financial markets is ...
ABSTRACT Conjunct with the universal acceleration in information growth, financial services have bee...
This study investigates how modern machine learning (ML) techniques can be used to advance the field...