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Regression modelEconometrics / time series

Mfumo wa GARCH wa Fourier

Mfumo wa GARCH wa Fourier huunganisha vipengele vya Fourier vya trigonometric katika mfumo wa kawaida wa GARCH ili kukamata mabadiliko laini, yanayoendelea katika mchakato wa kiwango tofauti cha masharti bila kuhitaji kujua tarehe kamili za mabadiliko ya kimuundo. Kwa kukadiria ruwaza za mabadiliko ambazo hazijulikani kwa utendaji wa sinusoidal, huunganisha pamoja nguzo za kutokuwa na utulivu na kiwango tofauti cha masharti kinachobadilika kwa wakati.

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Vyanzo

  1. Ludlow, J., & Enders, W. (2000). Estimating non-linear ARMA models using Fourier coefficients. International Journal of Forecasting, 16(3), 333–347. DOI: 10.1016/S0169-2070(00)00048-0
  2. Enders, W., & Lee, J. (2012). A unit root test using a Fourier series to approximate smooth breaks. Oxford Bulletin of Economics and Statistics, 74(4), 574–599. DOI: 10.1111/j.1468-0084.2011.00662.x

Jinsi ya kunukuu ukurasa huu

ScholarGate. (2026, June 3). Fourier-Flexible Generalized Autoregressive Conditional Heteroscedasticity Model. ScholarGate. https://scholargate.app/sw/econometrics/fourier-garch-model

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Imerejelewa na

ScholarGateFourier GARCH Model (Fourier-Flexible Generalized Autoregressive Conditional Heteroscedasticity Model). Imepatikana 2026-06-15 kutoka https://scholargate.app/sw/econometrics/fourier-garch-model · Seti ya data: https://doi.org/10.5281/zenodo.20539026