Similar Search Results

The ability of artificial neural networks to exploit non-linearities by data mining models compared to statistical methods

Beinsen, Lutz; Brandl, Bernd - In: Operations research proceedings 2002 : selected papers …, (pp. 510-515). 2003

Persistent link: https://www.econbiz.de/10001752055

Application of Feed-Forward Neural Networks Smoothing Transition Autoregressive Models in Stock Returns Forecasting

Giovanis, Eleftherios - 2010

In this paper we propose and examine new approaches in smoothing transition autoregressive (STAR) models. Firstly, a new STAR function is proposed, which is the hyperbolic tangent sigmoid function. Secondly, we propose Feed-Forward Neural Networks Smoothing Transition Autoregressive (FFNN-STAR)...

Persistent link: https://www.econbiz.de/10013138095

Nonlinear Volatility Models in Economics : Smooth Transition and Neural Network Augmented GARCH, APGARCH, FI-GARCH and FIAGARCH Models

Bildirici, Melike - 2012

Recently, Donaldson and Kamstra (1997) proposed a class of NN-GARCH models which are extended to a class of NN-GARCH family by Bildirici and Ersin (2009). The study aims to analyze the nonlinear behavior and leptokurtic distribution in petrol prices by utilizing a newly developed family of...

Persistent link: https://www.econbiz.de/10013103072

Convolutional Neural Networks for Modeling and Forecasting Nonlinear Nonstationary Processes

Belas, Andrii; Bidyuk, Petro - 2021

The object of research: The object of research is modeling and forecasting nonlinear nonstationary processes presented in the form of time-series data.Investigated problem: There are several popular approaches to solving the problems of adequate model constructing and forecasting nonlinear...

Persistent link: https://www.econbiz.de/10013217370