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 …

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

Regressive Fractionally Integrated Moving Average model which is based on Fractional Integration Approach) in forecasting daily …-of-sample forecasting performance. Besides, fractal markets hypothesis was examined and according to the findings, fractal structure was … network model had the best performance in out-of-sample forecasting based on the criteria introduced for calculating …

research on detecting and forecasting business cycle turning points. …

There is no standard economic forecasting procedure that systematically outperforms the others at all horizons and with … forecasting purposes where the traditional ARMA specification is preferred. Accounting for the Easter effect improves the forecast …

forecasting accuracy within factor modelling framework. Nested data means disaggregated data or sub-components of aggregated … mean square error is employed as the standard tool to measure forecasting accuracy. According to this empirical study we … enhance Latvian GDP forecasting accuracy. The efficiency gain improving forecasts is about 0.15-0.20 percentage points of year …

from internet search queries performed on the search engine Google. The forecasting performance of the Google Inflation …, Survey of Professional Forecasters, and the Michigan Survey. While useful in developing models of forecasting inflation …

, are relevant to forecasting economic growth and stock returns, and whether they contain information that is orthogonal to …

Michigan Surveys of Consumers. While these measures have been useful in developing models of forecasting inflation, the data …