performance and on this basis different types of these models have been used in forecasting. Now, there is this question that … which kind of these models has more explanatory power in forecasting the future processes of the stock. In line with this …, the present paper made a comparison between static and dynamic neural network models in forecasting the return of Tehran …

directional component of the market returns because, for investment purposes, forecasting the direction of return correctly is … in forecasting the direction of the market return. Finally, we test trading strategies and find that a number of industry …

In this paper, we study main problems and practical issues of modeling and forecasting of macroeconomic variables in … variables and employ two forecasting methodologies (Waggoner and Zha (1999), Banbura, Giannone and Lenza (2014)) to construct … modeling and forecasting of macroeconomic variables and provide some policy recommendations to improve quality of statistical …

setting. Monte Carlo evidence and an empirical forecasting exercise show clear and important gains of the new priors compared …

In this study, we investigate forecasting performance of various univariate and multivariate models in predicting … forecasting ability of the different models with that of naïve ones. We find that for all forecast horizons simple naïve models … have equal forecasting ability with relatively sophisticated models which allow for richer economic dynamics. To check …

This study aims to introduce an ideal model for forecasting crude oil price volatility. For this purpose, the …

forecasting one-month ahead, especially with Bayesian VARs. Furthermore, for both real and nominal variables, the direct pooling …

individual operational units. This study introduces a stochastic, multi-stage, optimization technique for short-term forecasting …