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Information Journal Paper

Title

A NEW TIME SERIES ROBUST FORECASTING APPROACH WITH APPLICATION IN FINANCE

Pages

  97-114

Abstract

 To obtain reliable model for auto correlated and time series data, robust approach should be considered because OUTLIERS and contaminations can have bad effect on parameter estimation of these models. Since most finance data are auto correlated and they are affected by the previous data, they can be modeled by time series regression models. In this paper, the autoregressive (AR) model is investigated and novel robust procedure based on filtered S-estimator is proposed to estimate the parameters of AR model. This model is used to obtain robust forecasting procedure. We present 148 data gathered from a firm which are related to profit as a numerical example and show the efficiency of the proposed estimation approach. The robust model can forecast more accurate than classical model in presence of outlier.

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    Cite

    APA: Copy

    SHAHRIYARI, H., SHARIATI, N., & MOSLEMI, A.. (2012). A NEW TIME SERIES ROBUST FORECASTING APPROACH WITH APPLICATION IN FINANCE. FINANCIAL KNOWLEDGE OF SECURITY ANALYSIS (FINANCIAL STUDIES), 5(15), 97-114. SID. https://sid.ir/paper/200340/en

    Vancouver: Copy

    SHAHRIYARI H., SHARIATI N., MOSLEMI A.. A NEW TIME SERIES ROBUST FORECASTING APPROACH WITH APPLICATION IN FINANCE. FINANCIAL KNOWLEDGE OF SECURITY ANALYSIS (FINANCIAL STUDIES)[Internet]. 2012;5(15):97-114. Available from: https://sid.ir/paper/200340/en

    IEEE: Copy

    H. SHAHRIYARI, N. SHARIATI, and A. MOSLEMI, “A NEW TIME SERIES ROBUST FORECASTING APPROACH WITH APPLICATION IN FINANCE,” FINANCIAL KNOWLEDGE OF SECURITY ANALYSIS (FINANCIAL STUDIES), vol. 5, no. 15, pp. 97–114, 2012, [Online]. Available: https://sid.ir/paper/200340/en

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