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Information Journal Paper

Title

MODELING FINANCIAL RETURN WITH MARKOV TIME-VARYING MIXED NORMAL GARCH MODEL

Pages

  91-102

Abstract

 In previous studies, the normal mixture, as well as the MARKOV PROCESS, were used to model the FINANCIAL RETURN, separately. In this study, the normal mixture model is extended to the Markov mixture of normals. The mixture weights in every state are considered time-varying and as a function of past observations, so the limit of constant weight assumption is removed. The proposed model is estimated using BAYESIAN INFERENCE and a Gibbs sampling algorithm has been created to compute posterior density. The performance of algorithm is tested with simulation, then a two-state Markov time-varying Mixed Normal-GARCH model (MMN) with one and two components in every state, as well as limited cases (mean zero), were compared by comparison of their likelihood function. Finally, the model is applied to S& P500 and TEPIX daily return and results show that MMN models with two components provide better results than MMN model with one component which is so-called Markov switching GARCH model.

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    APA: Copy

    ALIPOUR, SHIRIN, AZIZZADEH, FATEMEH, & MANTEGHI, KHOSRO. (2018). MODELING FINANCIAL RETURN WITH MARKOV TIME-VARYING MIXED NORMAL GARCH MODEL. FINANCIAL KNOWLEDGE OF SECURITY ANALYSIS (FINANCIAL STUDIES), 11(37 ), 91-102. SID. https://sid.ir/paper/200228/en

    Vancouver: Copy

    ALIPOUR SHIRIN, AZIZZADEH FATEMEH, MANTEGHI KHOSRO. MODELING FINANCIAL RETURN WITH MARKOV TIME-VARYING MIXED NORMAL GARCH MODEL. FINANCIAL KNOWLEDGE OF SECURITY ANALYSIS (FINANCIAL STUDIES)[Internet]. 2018;11(37 ):91-102. Available from: https://sid.ir/paper/200228/en

    IEEE: Copy

    SHIRIN ALIPOUR, FATEMEH AZIZZADEH, and KHOSRO MANTEGHI, “MODELING FINANCIAL RETURN WITH MARKOV TIME-VARYING MIXED NORMAL GARCH MODEL,” FINANCIAL KNOWLEDGE OF SECURITY ANALYSIS (FINANCIAL STUDIES), vol. 11, no. 37 , pp. 91–102, 2018, [Online]. Available: https://sid.ir/paper/200228/en

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