Summarization: Financial management maximise investors’ return, seeking for stocks with increasing expected corporate value. Hidden information is included in vast accounting data and financial indices that are available in international financial markets. Methods of Econometrics and Artificial Intelligence- mainly in the field of Neural Networks- provide classifications of companies regarding their economic health. Radial Basis Function networks are examined in a hybrid form of Neural Network optimised with Genetic Algorithms and in a regular Neural Net form, to determine efficient methods of Financial Analysis. The regular Radial Basis Function network with 3 layers, Genetic Algorithms in all the layers and Cross Validation is superior to...
Stock market comprises of complex sample of data in time series. It has unique characteristics like...
This article deals with the usefulness of neuronal networks in the area of corporate finance. Firstl...
This paper presents an approach to the joint optimization of neural network structure and weights wh...
Summarization: Financial management implements a variety of effective techniques to determine the ec...
Abstract:-Portfolio managers, auditors and financial analysts process accounting data and financial ...
Abstract. Credit analysts generally assess the risk of credit applications based on their previous e...
We introduce a novel predictive statistical modeling technique called Hybrid Radial Basis Function N...
In this paper we present the Radial Basis Neural Network Function. We examine some simple numerical ...
Machine language is a sequence of algorithm assign to do a particular task. Neural Networking is ins...
In this preliminary work on the application of Hybrid Algorithms to FinancialForecasting (HAF2) we s...
There are problems in Finance and Accounting that cannot be solved easily through traditional techni...
Many researchers are interesting in applying the neural networks methods to financial data. In fact ...
Introduction We describe a neural-network-based aid to the financial analysis of companies, which i...
The Radial Basis Function (RBF) neural networks are nonparametric regression tools similar in formul...
The presented rigorosis thesis is focused on the stock markets returns analysis using a new type of ...
Stock market comprises of complex sample of data in time series. It has unique characteristics like...
This article deals with the usefulness of neuronal networks in the area of corporate finance. Firstl...
This paper presents an approach to the joint optimization of neural network structure and weights wh...
Summarization: Financial management implements a variety of effective techniques to determine the ec...
Abstract:-Portfolio managers, auditors and financial analysts process accounting data and financial ...
Abstract. Credit analysts generally assess the risk of credit applications based on their previous e...
We introduce a novel predictive statistical modeling technique called Hybrid Radial Basis Function N...
In this paper we present the Radial Basis Neural Network Function. We examine some simple numerical ...
Machine language is a sequence of algorithm assign to do a particular task. Neural Networking is ins...
In this preliminary work on the application of Hybrid Algorithms to FinancialForecasting (HAF2) we s...
There are problems in Finance and Accounting that cannot be solved easily through traditional techni...
Many researchers are interesting in applying the neural networks methods to financial data. In fact ...
Introduction We describe a neural-network-based aid to the financial analysis of companies, which i...
The Radial Basis Function (RBF) neural networks are nonparametric regression tools similar in formul...
The presented rigorosis thesis is focused on the stock markets returns analysis using a new type of ...
Stock market comprises of complex sample of data in time series. It has unique characteristics like...
This article deals with the usefulness of neuronal networks in the area of corporate finance. Firstl...
This paper presents an approach to the joint optimization of neural network structure and weights wh...