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Performance evaluation of statistical methods for forecasting of unemployment rate
Čermáková, Anna; Biskup, Roman - 2012
The aim of this article is the accuracy evaluation of suitable models used for prediction of the unemployment rate development in Czech Republic under conditions of economic depression. Models were based on exponential smoothing and training of artificial neural networks. The most suitable...
Persistent link: https://www.econbiz.de/10011316083
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System economics: overcoming the pitfalls of forecasting models via a multidisciplinary approach
Orrell, David; McSharry, Patrick - 2009
In areas from medicine to climate change to economics, we are faced with huge challenges and a need for accurate forecasts, yet our ability to predict the future has been found wanting. The basic problem is that complex systems such as the atmosphere or the economy cannot be reduced to simple...
Persistent link: https://www.econbiz.de/10009441535
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Making progress in forecasting
Armstrong, J. Scott; Fildes, Robert - 2006
Twenty-five years ago, the International Institute of Forecasters was established “to bridge the gap between theory and practice.” Its primary vehicle was the Journal of Forecasting and is now the International Journal of Forecasting. The Institute emphasizes empirical comparisons of...
Persistent link: https://www.econbiz.de/10009439169
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Clustering ranked preference data using sociodemographic covariates
Gormley, Isobel Claire; Murphy, Thomas Brendan - 2010
models provide a framework in which covariates are included in mixture models. Covariates are included through the mixing … covariates enter the model. The mixing proportions and group specific parameters are potentially dependent on covariates. Model … through Irish election data. Results indicate mixture modelling using covariates is insightful when examining a population of …
Persistent link: https://www.econbiz.de/10009475695
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Time-varying risk aversion : an application to energy hedging
Cotter, John; Hanly, Jim - 2010
Risk aversion is a key element of utility maximizing hedge strategies; however, it hastypically been assigned an arbitrary value in the literature. This paper instead applies a GARCH-in-Mean (GARCH-M) model to estimate a time-varying measure of riskaversion that is based on the observed risk...
Persistent link: https://www.econbiz.de/10009475662
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Applying Bayesian Forecasting to Predict New Customers' Heating Oil Demand
Sakauchi, Tsuginosuke - 2011
This thesis presents a new forecasting technique that estimates energy demand by applying a Bayesian approach to forecasting. We introduce our Bayesian Heating Oil Forecaster (BHOF), which forecasts daily heating oil demand for individual customers who are enrolled in an automatic delivery...
Persistent link: https://www.econbiz.de/10009484448
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Predictions of monthly energy consumption and annual patterns of energy usage for convenience stores by using multiple and nonlinear regression models
Woods, Paul K. (contributor) - 2004
Thirty convenience stores in College Station, Texas, have been selected as the samples for an energy consumption prediction. The predicted models assist facility energy managers for making decisions of energy demand/supply plans. The models are applied to historical data for two years: 2001 and...
Persistent link: https://www.econbiz.de/10009465101
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Month-of-the-year and pre-holiday seasonality in African stock markets
Alagidede, Paul - 2008
Seasonal anomalies (calendar effects) may be loosely referred to as the tendency forfinancial asset returns to display systematic patterns at certain times of the day, week,month or year. Two popular calendar effects are investigated for African stock returns:the month-of-the-year and the...
Persistent link: https://www.econbiz.de/10009465883
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Empirical Calibration of Time Series Monitoring Methods Using Receiver Operating Characteristic Curves
Cohen, Jacqueline; Garman, Samuel; Gorr, Wilpen - 2008
Time series monitoring methods, such as the Brown and Trigg methods, have the purpose of detecting pattern breaks (or “signals”) in time series data reliably and in a timely fashion. Traditionally, researchers have used the average run length statistic (ARL) on results from generated signal...
Persistent link: https://www.econbiz.de/10009441237
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Enhancing Forecasting Capability of Excel with User Defined Functions
Subedi, Deepak K - 2008
We have developed seven user defined functions (UDF) related to forecasting. The first four functions are for exponential smoothing. These are simple exponential smoothing, Holt’s fit, Winter’s method and Holt-Winter method. The next three functions can be used to calculate forecasting...
Persistent link: https://www.econbiz.de/10009441807