Computer Applications in Industry and Engineering · 2010 · 10 citations · 10 references
ComputingData ScienceFinanceForecastingPredictive AnalyticsTime Series AnalysisFinancial ForecastingFinancial Time Series AnalysisForecasting MethodsTime Series AnalyticsTime Series ForecastingTime Series PredictionFinancial Time Series ForecastingGenetic Algorithm OptimizationGini Coefficient AnalysisStock Return ForecastingTrend Forecasting
In this paper, we propose a new fusion approach to predict time series based on Concordance and Genetic Algorithm. Different measures of concordances such as the Kendall’s Tau, Gini’s Mean Difference, Spearman’s Rho, and a weak interpretation of the Weak Concordance are used to identify these generic trends. The concept is validated using Financial Time Series data (S&P 500 Index) as the sample data set.
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