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Bayesian latent autoregressive stochastic volatility: an application of naira to eleven exchangeable currencies rates

R. O. Olanrewaju, Department of Statistics, University of Ibadan, 200284, Nigeria, J. F. Ojo, L. O. Adekola, Department of Statistics, University of Ibadan, 200284, Nigeria, Department of Physical Sciences, the Bells University of Technology, Ota, Nigeria
2020 Open Journal of Mathematical Sciences  

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This paper provides a procedure for estimating Stochastic Volatility (SV) in financial time series via latent autoregressive in a Bayesian setting. A Gaussian distributional combined prior and posterior of all hyper-parameters (autoregressive coefficients) were specified such that the Markov Chain Monte Carlo (MCMC) iterative procedure via the Gibbs and Metropolis-Hasting sampling method was used in estimating the resulting exponentiated forms (quadratic forms) from the posterior kernel
more » ... A case study of Naira to eleven (11) exchangeable currencies\(^,\) rates by Central Bank of Nigeria (CBN) was subjected to the estimated solutions of the autoregressive stochastic volatility. The posterior volatility estimates at 5%, 50%, and 95% quantiles of \({e^{\frac{\mu }{2}}}\) = (0.130041, 0.1502 and 0.1795) respectively unveiled that the Naira-US Dollar exchange rates has the highest rates bartered by fluctuations.
doi:10.30538/oms2020.0128 fatcat:xwdvbkuid5ej3itikh7wxidopm
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R. O. Olanrewaju, Department of Statistics, University of Ibadan, 200284, Nigeria, J. F. Ojo, L. O. Adekola, Department of Statistics, University of Ibadan, 200284, Nigeria, Department of Physical Sciences, the Bells University of Technology, Ota, Nigeria. "Bayesian latent autoregressive stochastic volatility: an application of naira to eleven exchangeable currencies rates." Open Journal of Mathematical Sciences 4.1 (2020) 386-396