There have been multiple attempts to predict stock returns using machine learning, which have largely used historical time series data on share prices to make these predictions. Those attempts create networks which only work on one firm\u27s data, and cannot be applied generally. This study uses a neural network to predict stock returns based on financial and economic data. The method that is employed here predicts whether a given stock will beat the S&P 500 index over a future time period. This method has reached prediction accuracy of 64.5%. A method which makes consistently accurate predictions helps to identify additional factors that determine a firm’s value beyond what is generally accepted in the literature
The process of predicting stock market movements may initially appear to be non-statistical due to t...
In this study, we examine existing stock market prediction algorithms before proposing new ones. We ...
Companies in the S&P 500 produce quarterly financial statements that are closely studied by investor...
Can Machines Explain Stock Returns? Thesis Abstract Karolína Chalupová January 5, 2021 Recent resear...
Neural Networks are very good in learning patterns from a lot of information. Thus, it is generally ...
Machine learning approaches to stock market forecasting have become increasingly popular th...
Abstract — Neural networks, as an intelligent data mining method, have been used in many different c...
In recent years, neural networks have become increasingly popular in making stock market predictions...
With the development of science and technology, people pay more attention to predicting the price of...
M.Comm.The availability of large amounts of information and increases in computing power have facili...
The financial market and stock market have experienced great changes during the past decades, which ...
Generally, stock investors tend to implement different analysis tools on stock prediction, in order ...
Accurate prediction of stock prices plays an increasingly prominent role in the stock market where r...
This report analyzes new and existing stock market prediction techniques. Traditional technical anal...
The first part of this thesis discusses the application of artificial intelligence to stock price pr...
The process of predicting stock market movements may initially appear to be non-statistical due to t...
In this study, we examine existing stock market prediction algorithms before proposing new ones. We ...
Companies in the S&P 500 produce quarterly financial statements that are closely studied by investor...
Can Machines Explain Stock Returns? Thesis Abstract Karolína Chalupová January 5, 2021 Recent resear...
Neural Networks are very good in learning patterns from a lot of information. Thus, it is generally ...
Machine learning approaches to stock market forecasting have become increasingly popular th...
Abstract — Neural networks, as an intelligent data mining method, have been used in many different c...
In recent years, neural networks have become increasingly popular in making stock market predictions...
With the development of science and technology, people pay more attention to predicting the price of...
M.Comm.The availability of large amounts of information and increases in computing power have facili...
The financial market and stock market have experienced great changes during the past decades, which ...
Generally, stock investors tend to implement different analysis tools on stock prediction, in order ...
Accurate prediction of stock prices plays an increasingly prominent role in the stock market where r...
This report analyzes new and existing stock market prediction techniques. Traditional technical anal...
The first part of this thesis discusses the application of artificial intelligence to stock price pr...
The process of predicting stock market movements may initially appear to be non-statistical due to t...
In this study, we examine existing stock market prediction algorithms before proposing new ones. We ...
Companies in the S&P 500 produce quarterly financial statements that are closely studied by investor...