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Sovereign debt markets in developing economies exhibit complex non-linear volatilities driven by monetary policy adjustments and liquidity shocks. Traditional univariate forecasting frameworks often fail when economic systems undergo structural shocks. This study formulates an advanced computational econometric architecture integrating MATLAB-based simulation algorithms with Box-Jenkins Transfer Function models to analyze monthly Nigerian Treasury Bill rates from 2006 to 2019. By establishing rigorous mathematical derivations for rational lag structures, pre-whitening filters, and impulse response weights, we construct a high-precision forecasting engine. Empirical results demonstrate that the transfer function model significantly outperforms standard ARIMA and SARIMA benchmarks, yielding superior predictive accuracy with minimized Root Mean Square Error (RMSE = 1.885). The integrated MATLAB simulation scripts provide real-time telemetry and robust out-of-sample projections through 2024, offering vital decision-support tools for central bank policy formulation and macroeconomic stabilization.
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Anselam et al. (2026) studied this question.
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