the main purpose of the present research is to determine the relationship between the management earnings forecast errors and conservatism level and then surveying about the effects of forecast difficulty, and external financing on this relationship. regarding this, the financial information related to 147 stock firms, available during the period of study (2003-2015) were collected and analyzed...

Gold price forecast is of great importance. Many models were presented by researchers to forecast gold price. It seems that although different models could forecast gold price under different conditions, the new factors affecting gold price forecast have a significant importance and effect on the increase of forecast accuracy. In this paper, different factors were studied in comparison to the p...

in the paper a model to predict the concentrations of particulate matter pm10, pm2.5, so2, no, co and o3 for a chosen number of hours forward is proposed. the method requires historical data for a large number of points in time, particularly weather forecast data, actual weather data and pollution data. the idea is that by matching forecast data with similar forecast data in the historical data...

Energy price forecast is the key information for generating companies to prepare their bids in the electricity markets. However, this forecasting problem is complex due to nonlinear, non-stationary, and time variant behavior of electricity price time series. Accordingly, in this paper a new strategy is proposed for electricity price forecast. The forecast strategy includes Wavelet Transform (WT...

the purpose of this research is to investigate the relationship between earnings variabilityand earnings forecast using neural networks in companies listed on tehran stock exchange. theresearch is of the library and analytical-causal study type, and is based on panel data analysis andneural networks. in this research, financial information of 98 companies from 19 industries intehran stock excha...

We explain that revisions to successive density forecasts of the same outcome, as measured by the Kullback-Leibler Information Criterion, need not be unpredictable, unlike those to conditional mean forecasts, even when the forecaster uses information efficiently. However one can still test the efficiency of fixed-event conditional density forecasts, similarly to conditional mean forecasts, by t...

In the paper a model to predict the concentrations of particulate matter PM10, PM2.5, SO2, NO, CO and O3 for a chosen number of hours forward is proposed. The method requires historical data for a large number of points in time, particularly weather forecast data, actual weather data and pollution data. The idea is that by matching forecast data with similar forecast data in the historical data...

energy price forecast is the key information for generating companies to prepare their bids in the electricity markets. however, this forecasting problem is complex due to nonlinear, non-stationary, and time variant behavior of electricity price time series. accordingly, in this paper a new strategy is proposed for electricity price forecast. the forecast strategy includes wavelet transform (wt...

abstract the aim of this study was to selecting the suitable model for forecast land, production and price of sugar beet in iran. for this purpose, models applied to forecast are arima, single and double exponential smoothing, harmonic, artificial neural network and arch for period 1993-2008. results of durbin-watson tests, land, production and price of sugar beet series were found non stochast...