Highly sophisticated artificial neural networks have achieved unprecedented performance across a variety of complex real-world problems over the past years, driven by the ability to detect significant patterns autonomously. Modern electronic stock markets produce large volumes of data, which are very suitable for use with these algorithms. This research explores new scientific ground by designing and evaluating a convolutional neural network in predicting future financial outcomes. A visually inspired transformation process translates high-frequency market microstructure data from the London Stock Exchange into four market-event based input channels, which are used to train six deep networks. Primary results indicate that con-volutional net...
Nowadays, Financial Markets represent a crucial part of the world economy. Financial Markets have gr...
We develop a large-scale deep learning model to predict price movements from limit order book (LOB) ...
In this study, deep learning will be used to test the predictability of stock trends. Stock markets ...
This article explores the application of advanced data analysis techniques in the financial sector u...
This thesis addresses practical, real-world problems in the financial services industry using Deep L...
This study explores the suitability of neural networks with a convolutional component as an alternat...
In this paper, we investigate market behaviors at high-frequency using neural networks trained with ...
We offer a systematic analysis of the use of deep learning networks for stock market analysis and pr...
Objective: This study's main goal is to investigate how deep learning approaches may be used to anal...
A major issue in financial market trading is knowing when to undertake a transaction for the purpose...
This research explores the application of four deep learning architectures—Multilayer Perceptron (ML...
In the last decade, market financial forecasting has attracted high interests amongst the researcher...
Financial market forecasting is used to assess the future value of financial instruments in various ...
We present an Artificial Neural Network (ANN) approach to predict stock market indices, particularly...
2019 IEEE Congress on Evolutionary Computation ( 2019: Wellington; New Zealand)Financial forecasting...
Nowadays, Financial Markets represent a crucial part of the world economy. Financial Markets have gr...
We develop a large-scale deep learning model to predict price movements from limit order book (LOB) ...
In this study, deep learning will be used to test the predictability of stock trends. Stock markets ...
This article explores the application of advanced data analysis techniques in the financial sector u...
This thesis addresses practical, real-world problems in the financial services industry using Deep L...
This study explores the suitability of neural networks with a convolutional component as an alternat...
In this paper, we investigate market behaviors at high-frequency using neural networks trained with ...
We offer a systematic analysis of the use of deep learning networks for stock market analysis and pr...
Objective: This study's main goal is to investigate how deep learning approaches may be used to anal...
A major issue in financial market trading is knowing when to undertake a transaction for the purpose...
This research explores the application of four deep learning architectures—Multilayer Perceptron (ML...
In the last decade, market financial forecasting has attracted high interests amongst the researcher...
Financial market forecasting is used to assess the future value of financial instruments in various ...
We present an Artificial Neural Network (ANN) approach to predict stock market indices, particularly...
2019 IEEE Congress on Evolutionary Computation ( 2019: Wellington; New Zealand)Financial forecasting...
Nowadays, Financial Markets represent a crucial part of the world economy. Financial Markets have gr...
We develop a large-scale deep learning model to predict price movements from limit order book (LOB) ...
In this study, deep learning will be used to test the predictability of stock trends. Stock markets ...