https://journalajpas.com/index.php/AJPAS <p style="text-align: justify;"><strong>Asian Journal of Probability and Statistics</strong> <strong>(ISSN: <a href="https://nsl.niscpr.res.in/ISSNPROCESS/issnassignedinfo.jsp">2582-0230</a>) </strong>aims to publish high-quality papers (<a href="https://journalajpas.com/index.php/AJPAS/general-guideline-for-authors">Click here for Types of paper</a>) in all areas of ‘Probability and Statistics’. By not excluding papers based on novelty, this journal facilitates the research and wishes to publish papers as long as they are technically correct and scientifically motivated. The journal also encourages the submission of useful reports of negative results. This is a quality controlled, OPEN peer-reviewed, open-access INTERNATIONAL journal.</p> en-US [email protected] (Asian Journal of Probability and Statistics) [email protected] (Asian Journal of Probability and Statistics) Fri, 23 Oct 2026 05:43:46 +0000 OJS 3.3.0.21 http://blogs.law.harvard.edu/tech/rss 60 https://journalajpas.com/index.php/AJPAS/article/view/967 <p>This study models daily USD/NGN exchange-rate volatility using an autoregressive moving-average–generalised autoregressive conditional heteroskedasticity (ARMA–GARCH) framework. The analytical series covers December 2024 through July 2026. The imported file contained 403 rows; duplicate-date screening yielded 397 unique exchange-rate observations and 396 percentage log returns. The Augmented Dickey–Fuller test rejected a unit root in the return series (test statistic = −8.6721, p &lt; .001), while ARCH–LM tests at lags 5, 10 and 15 detected conditional heteroskedasticity (all p &lt; .001). Among the reported low-order ARMA candidates, ARMA(2,2) was retained because it was the only specification with a Ljung–Box Q(10) p-value above .05, despite not minimising the information criteria. The reported Gaussian ARMA(2,2)–GARCH(1,1) fit produced ARCH and GARCH estimates of α = 0.366944 and β = 0.316000, giving α + β = 0.682944. This value is below unity and therefore indicates a finite-variance, mean-reverting conditional-volatility process under the fitted specification. Post-estimation ARCH–LM tests did not detect remaining ARCH effects at the examined lags. Point volatility forecasts increased from 0.3598% at one trading day ahead to 0.5058% at ten trading days ahead and approached the model-implied long-run daily volatility of approximately 0.5100% over a 30-trading-day horizon. The findings support the presence of time-varying but mean-reverting USD/NGN volatility during the study window. Because the analysis does not include an out-of-sample forecast-accuracy exercise or coefficient-level inferential statistics, the conclusions are limited to the reported sample, diagnostics and point forecasts.</p> H. B. Buari, O. R. Oyebanjo Copyright (c) 2026 Author(s). The licensee is the journal publisher. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. https://creativecommons.org/licenses/by/4.0 https://journalajpas.com/index.php/AJPAS/article/view/967 Fri, 23 Oct 2026 00:00:00 +0000