A New Journal for Forecasting Research
Journal Title: Turkish Journal of Forecasting - Year 2017, Vol 1, Issue 2
Abstract
The Turkish Journal of Forecasting (TJF) is an open access international journal and it is published semi-annually. The aim of the TJF is to procure a platform to integrate the research subjects and fields, and to bridge over the between theory and practice dealing with any aspect of forecasting. The first issue is regular, the second issue is a special issue for International Web Conference on Forecasting. There is no any subscription fee, submission fee or publishing fee. All submitted papers will go through the blind review process, and the Associate Editors assign the manuscripts to at least two reviewers, depending on article type. First two issues of the TJF are published in 2017 and a comprehensive summary of the issues are given in this editorial.
Authors and Affiliations
Erol Egrioglu, Ufuk Yolcu, Eren Bas, Ali Zafer Dalar, Ozge Cagcag Yolcu
Keywords
Related Articles
- EP ID EP300062
- DOI -
- Views 121
- Downloads 0
A Fuzzy Modelling Approach to Robust Design via Loss Functions
Especially in a world where industrial development is reinforced by globalization tendencies, competitive companies know that satisfying customers' needs and running a successful operation requires a process that is reli...
BIST 100 Index Estimation Using Bayesian Regression Modelling
Identification of factors, determining the fluctuations of stock indices in the market, possesses great importance for the capital market actors. Not only specifying the factors and market but also explaining the relatio...
Time Series Prediction with Direct and Recurrent Neural Networks
This article presents a comparative study of the prediction of time series for the Consumer Price Index (CPI) using a recurrent neural network (RNN). For this, three models are designed for recurrent networks, with chang...
Multi-layer Perceptron and Pruning
A Multi-Layer Perceptron (MLP) defines a family of artificial neural networks often used in TS modeling and forecasting. Because of its “black box” aspect, many researchers refuse to use it. Moreover, the optimization (o...
Stock Market Prediction Using Nonparametric Fuzzy and Parametric GARCH Methods
Prediction of stock market value is one the most complicated issue during the past decades. Due to its importance, in this research, we consider the prediction of stock values based on non-parametric and parametric metho...