today, the discussion of regularity monetary policy in achieving inflation and output gap stabilization is important. in this paper, we investigated the persistence of the output gap in iran economy and then by using a hybrid new keynesian model based on quarterly data for 1990:1- 2011:3. we compared three alternative instrumental rules in monetary policy for iran economy. the results indicated...

The purpose of this work is to present a simple global solar irradiance forecasting framework based on the optimization of the k-nearest-neighbors (kNN) and artificial neural networks algorithms (ANN) for time horizons ranging from 15 min to 2 h. We apply the proposed forecasting models to irradiance from five locations and assessed the impact of different micro-climates on forecasting performa...

This paper analyzes the behaviour and motivation of fund managers in foreign exchange markets reflected in questionnaire evidence. We find that fund managers and FX dealers differ significantly. Fund managers rely more on fundamentals, basically due to their longer forecasting horizons, and reject non-fundamental influences on exchange rates more than FX dealers. However, neither can fund manag...

Price forecasting and trading strategies modeling are examined with major international stock indexes under different time horizons. Results demonstrate that an accurate prediction is equally important as a stable saving rate for long-term survivability. The best economic performances are achieved for a one-year investment horizon with longer training not necessarily leading to improved accurac...

Price forecasting and trading strategies modelling are examined with major international stock indexes under different time horizons. Results demonstrate that an accurate prediction is equally important as a stable saving rate for long-term survivability. The best economic performances are achieved for a one-year investment horizon with longer training not necessarily leading to improved accura...

We expand Nakamura’s (2005) neural network based inflation forecasting experiment to an alternative non-linear model; a Markov switching autoregressive (MS-AR) model. The two non-linear models perform approximately on par and outperform the linear autoregressive model on short forecast horizons of one and two quarters. Furthermore, the MS-AR model is the best performer on longer horizons of thr...

Extrapolation methods are reliable, objective, inexpensive, quick, and easily automated. As a result, they are widely used, especially for inventory and production forecasts, for operational planning for up to two years ahead, and for long-term forecasts in some situations, such as population forecasting. This paper provides principles for selecting and preparing data, making seasonal adjustmen...

The purpose of this study is to contrast the forecasting performance of two non-linear models, a regime-switching vector autoregressive model (RS-VAR) and a recurrent neural network (RNN), to that of a linear benchmark VAR model. Our specific forecasting experiment is UK inflation and we utilize monthly data from 1969-2003. The RS-VAR and the RNN perform approximately on par over both monthly a...