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Mfumo wa Bayesian EGARCH

Mfumo wa Bayesian EGARCH unachanganya vipimo vya Exponential GARCH vya Nelson (1991) — ambavyo huunda logaritmi ya kiwango cha kutofautiana kwa masharti na huonyesha athari ya kujiinua — na uchambuzi wa makadirio ya Bayesian kupitia Markov Chain Monte Carlo (MCMC). Hii inaruhusu uhakiki kamili wa kutokuwa na uhakika wa vigezo vyote vya kutofautiana, ikiwa ni pamoja na mgawo wa kutokuwa na uwiano, bila kuhitaji utoshelevu wa sampuli kubwa wa makadirio.

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Vyanzo

  1. Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. DOI: 10.2307/2938260
  2. Nakatsuma, T. (2000). Bayesian analysis of ARMA-GARCH models: A Markov chain sampling approach. Journal of Econometrics, 95(1), 57–69. DOI: 10.1016/S0304-4076(99)00029-9

Jinsi ya kunukuu ukurasa huu

ScholarGate. (2026, June 3). Bayesian Exponential Generalized Autoregressive Conditional Heteroscedasticity Model. ScholarGate. https://scholargate.app/sw/econometrics/bayesian-egarch

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Imerejelewa na

ScholarGateBayesian EGARCH (Bayesian Exponential Generalized Autoregressive Conditional Heteroscedasticity Model). Imepatikana 2026-06-15 kutoka https://scholargate.app/sw/econometrics/bayesian-egarch · Seti ya data: https://doi.org/10.5281/zenodo.20539026