Add to ORKGThis paper applies non-linear methods to analyze and predict the daily open S&P index which is one of the most important stock index in the world. The aim of the analysis is to quantitatively show if the corresponding time series is a deterministic chaotic one and if one or more days ahead prediction can be achieved. These results make the present work a valuable tool for traders investors and funds
Recent empirical evidence suggests that stock market index returns are predictable from a variety of...
In the process of data analysis, the investigator is often facing highly-volatile and random-appeari...
Understanding stock market price fluctuations plays an important role in economic policy and in corp...
Abstract: This paper applies non-linear methods to analyze and predict the daily open S&P index ...
This paper applies non-linear methods to analyze and predict the daily open S&P index which is...
This paper investigates the use of a flexible forecasting method based on non-linear Markov modellin...
The extent to which daily return data from the Athens' Stock Exchange Index exhibits nonlinear and c...
By systematically applying different engineering methods, difficult financial problems become approa...
Efficiency and predictability of financial markets are inherently linked to the statistical properti...
The attractive possibility that financial indices may be chaotic has been the subject of much study....
Research background: The application of non-linear analysis and chaos theory modelling on financial ...
We developed in this paper a method to predict time series with non-linear tools. The specificity of...
[[abstract]]This article tests for nonlinear dependence and chaos in real-time returns on the world'...
This article tests for nonlinear dependence and chaos in real-time returns on the world's four most ...
We present evidence of nonlinearity and fractality from a small European equity market, the Athens s...
Recent empirical evidence suggests that stock market index returns are predictable from a variety of...
In the process of data analysis, the investigator is often facing highly-volatile and random-appeari...
Understanding stock market price fluctuations plays an important role in economic policy and in corp...
Abstract: This paper applies non-linear methods to analyze and predict the daily open S&P index ...
This paper applies non-linear methods to analyze and predict the daily open S&P index which is...
This paper investigates the use of a flexible forecasting method based on non-linear Markov modellin...
The extent to which daily return data from the Athens' Stock Exchange Index exhibits nonlinear and c...
By systematically applying different engineering methods, difficult financial problems become approa...
Efficiency and predictability of financial markets are inherently linked to the statistical properti...
The attractive possibility that financial indices may be chaotic has been the subject of much study....
Research background: The application of non-linear analysis and chaos theory modelling on financial ...
We developed in this paper a method to predict time series with non-linear tools. The specificity of...
[[abstract]]This article tests for nonlinear dependence and chaos in real-time returns on the world'...
This article tests for nonlinear dependence and chaos in real-time returns on the world's four most ...
We present evidence of nonlinearity and fractality from a small European equity market, the Athens s...
Recent empirical evidence suggests that stock market index returns are predictable from a variety of...
In the process of data analysis, the investigator is often facing highly-volatile and random-appeari...
Understanding stock market price fluctuations plays an important role in economic policy and in corp...