In this paper we apply neural network with denoising layer method for forecasting of Central European Stock Exchanges, namely Prague, Budapest and Warsaw
Stock movement prediction is important in the financial world because investors want to observe tren...
The paper considers the forecasting of the Warsaw Stock Exchange price index WIG20 by applying a sta...
Stock market is a highly volatile domain. Actually, it has always been a challenge to researchers ov...
Traditional prediction methods for time series often restrict on linear regression analysis, exponen...
This paper explores the application of a wavelet neural network (WNN), whose hidden layer is compris...
In this research, the total equities in Tehran Stock Exchange are predicted using different neural n...
Wavelet Neural Network prediction of Central European stock market returns series
The main aim of this report is to study the topic of Wavelet Neural Networks, and see how they are u...
Wavelet neural networks (WNN) have been applied successfully into many fields. The main purpose of t...
In this thesis we apply neural networks as nonparametric and nonlinear methods to the Central Europe...
Recently, a new decomposition method known as wavelet decomposition was introduced, which is accompl...
In this thesis we apply neural networks as nonparametric and nonlinear methods to the Central Europe...
In this paper, we apply neural networks as nonparametric and nonlinear methods to Cen-tral European ...
Due to the large amounts of risks and potential financial benefits involved, the ability to achieve ...
Stock price forecasting is highly important for the entire market economy as well as the investors t...
Stock movement prediction is important in the financial world because investors want to observe tren...
The paper considers the forecasting of the Warsaw Stock Exchange price index WIG20 by applying a sta...
Stock market is a highly volatile domain. Actually, it has always been a challenge to researchers ov...
Traditional prediction methods for time series often restrict on linear regression analysis, exponen...
This paper explores the application of a wavelet neural network (WNN), whose hidden layer is compris...
In this research, the total equities in Tehran Stock Exchange are predicted using different neural n...
Wavelet Neural Network prediction of Central European stock market returns series
The main aim of this report is to study the topic of Wavelet Neural Networks, and see how they are u...
Wavelet neural networks (WNN) have been applied successfully into many fields. The main purpose of t...
In this thesis we apply neural networks as nonparametric and nonlinear methods to the Central Europe...
Recently, a new decomposition method known as wavelet decomposition was introduced, which is accompl...
In this thesis we apply neural networks as nonparametric and nonlinear methods to the Central Europe...
In this paper, we apply neural networks as nonparametric and nonlinear methods to Cen-tral European ...
Due to the large amounts of risks and potential financial benefits involved, the ability to achieve ...
Stock price forecasting is highly important for the entire market economy as well as the investors t...
Stock movement prediction is important in the financial world because investors want to observe tren...
The paper considers the forecasting of the Warsaw Stock Exchange price index WIG20 by applying a sta...
Stock market is a highly volatile domain. Actually, it has always been a challenge to researchers ov...
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