Add to ORKGEl problema abordado por este trabajo es la predicción del precio de activos cotizados y la automatización de un sistema de inversión. El objetivo es comparar las estrategias de inversión tradicionales con las predicciones realizadas por una red neuronal recurrente.The problem addressed by this work is asset price prediction and automation of a trading system. The focus is on comparing traditional trading strategies with the predictions made by a Recurrent Neural Network
Technical and quantitative analysis in financial trading use mathematical and statistical tools to h...
Portfolio optimization is one of the most studied fields that have been researched with machine lear...
Over the last three decades, most of the world's stock exchanges have transitioned to electronic tra...
El problema abordado por este trabajo es la predicción del precio de activos cotizados y la automati...
More than 70% of today's stocks trade volume is attributable to automatic order execution by trading...
The emergence of artificial neural networks has given us some of the most impressive technological t...
Can we train a stock trading bot that can take decisions in high-entropy envi- ronments like stock m...
An algorithm that can learn an optimal policy to execute trade profitable is any market participant’...
Master's thesis in Industrial economicsThis thesis investigates how machine learning can be applied ...
Machine learning techniques have recently become the norm for detecting patterns in financial market...
In this study, a methodology is presented where a hybrid system combining an evolutionary algorithm ...
A major issue in financial market trading is knowing when to undertake a transaction for the purpose...
Recently, with the development of Artificial Intelligence in finance, using it in stock market tren...
This thesis investigates the forecasting ability of the artificial neural network (ANN) models on fi...
The rise of AI technology has popularized deep learning models for financial trading prediction, pro...
Technical and quantitative analysis in financial trading use mathematical and statistical tools to h...
Portfolio optimization is one of the most studied fields that have been researched with machine lear...
Over the last three decades, most of the world's stock exchanges have transitioned to electronic tra...
El problema abordado por este trabajo es la predicción del precio de activos cotizados y la automati...
More than 70% of today's stocks trade volume is attributable to automatic order execution by trading...
The emergence of artificial neural networks has given us some of the most impressive technological t...
Can we train a stock trading bot that can take decisions in high-entropy envi- ronments like stock m...
An algorithm that can learn an optimal policy to execute trade profitable is any market participant’...
Master's thesis in Industrial economicsThis thesis investigates how machine learning can be applied ...
Machine learning techniques have recently become the norm for detecting patterns in financial market...
In this study, a methodology is presented where a hybrid system combining an evolutionary algorithm ...
A major issue in financial market trading is knowing when to undertake a transaction for the purpose...
Recently, with the development of Artificial Intelligence in finance, using it in stock market tren...
This thesis investigates the forecasting ability of the artificial neural network (ANN) models on fi...
The rise of AI technology has popularized deep learning models for financial trading prediction, pro...
Technical and quantitative analysis in financial trading use mathematical and statistical tools to h...
Portfolio optimization is one of the most studied fields that have been researched with machine lear...
Over the last three decades, most of the world's stock exchanges have transitioned to electronic tra...