Semiparametric generalized long-memory modeling of some mena stock market returns: A wavelet approach
Heni Boubaker and
Economic Modelling, 2015, vol. 50, issue C, 254-265
This paper proposes a new class of semiparametric generalized long-memory models with FIAPARCH errors that extends the conventional GARMA model to incorporate nonlinear deterministic trend and allows for time-varying volatility. To estimate the parameters, we implement a wavelet theory. We provide an empirical application to some MENA stock markets and find that the proposed model offers an interesting framework to describe seasonal long-range dependence and nonlinear trend in return as well as persistence to shocks in conditional volatility. The predictive results also indicate that this model outperforms the traditional FARMA-FIAPARCH process.
Keywords: SEMIGARMA process; FIAPARCH errors; Wavelet domain; Stock markets (search for similar items in EconPapers)
JEL-codes: C13 C22 C32 G15 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecmode:v:50:y:2015:i:c:p:254-265
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