Uses for machine learning methods have dramatically increased over the last decade. With a diverse array of industries making use of it, it is no surprise that the financial industry has been one of its first adopters and pioneer in its development. However, precise measurements must be considered when dealing with financial data extracted from the market. This work project is an execution of Professor Marcos López de Prado (Cornell University)data analysis techniques for financial machine learning algorithms. The prepared data was then used as an input in a deep neural network for multi class classification, with the objective of making price direction predictions. Bitcoin was the selected financial instrument for this study, ...
The emergence of cryptocurrencies has drawn significant investment capital in recent years with an e...
The most popular cryptocurrency used worldwide is bitcoin. Many everyday folks and investors are now...
This paper explores the use of machine learning algorithms and narrative sentiments when applied to ...
The financial risk of investing in Bitcoin is increasing, and everyone partic-ipating in the transac...
This study aims to evaluate forecasting properties of classic methodologies (ARCH and GARCH models) ...
This paper discusses, trying to accurately assess the price of Bitcoin by looking at differ-ent para...
Due to economic uncertainty and the financial crisis of 2008, a desire for an unregu-lated currency ...
Bitcoin has drawn a lot of interest recently as a possible high-earning investment. There are signif...
We consider a technique involving Neural Networks in order to try to predict trends for cryptocurren...
Computational intelligence in finance has been a very popular topic for both academia and financial ...
The cryptocurrency market is amongst the fastest-growing of all the financial markets in the world. ...
Cryptocurrency has captured the interest of financial scholars and become a major research topic in ...
The use of computationally intensive systems that employ machine learning algorithms is increasingly...
Machine learning techniques have found application in the study and development of quantitative tra...
Dissertation presented as the partial requirement for obtaining a Master's degree in Statistics and ...
The emergence of cryptocurrencies has drawn significant investment capital in recent years with an e...
The most popular cryptocurrency used worldwide is bitcoin. Many everyday folks and investors are now...
This paper explores the use of machine learning algorithms and narrative sentiments when applied to ...
The financial risk of investing in Bitcoin is increasing, and everyone partic-ipating in the transac...
This study aims to evaluate forecasting properties of classic methodologies (ARCH and GARCH models) ...
This paper discusses, trying to accurately assess the price of Bitcoin by looking at differ-ent para...
Due to economic uncertainty and the financial crisis of 2008, a desire for an unregu-lated currency ...
Bitcoin has drawn a lot of interest recently as a possible high-earning investment. There are signif...
We consider a technique involving Neural Networks in order to try to predict trends for cryptocurren...
Computational intelligence in finance has been a very popular topic for both academia and financial ...
The cryptocurrency market is amongst the fastest-growing of all the financial markets in the world. ...
Cryptocurrency has captured the interest of financial scholars and become a major research topic in ...
The use of computationally intensive systems that employ machine learning algorithms is increasingly...
Machine learning techniques have found application in the study and development of quantitative tra...
Dissertation presented as the partial requirement for obtaining a Master's degree in Statistics and ...
The emergence of cryptocurrencies has drawn significant investment capital in recent years with an e...
The most popular cryptocurrency used worldwide is bitcoin. Many everyday folks and investors are now...
This paper explores the use of machine learning algorithms and narrative sentiments when applied to ...