Simulation Modeling Using Markovian Decision Theory on Cash Flow Analysis of Central Bank of Nigeria

Abstract

This research aims to investigate the cash flow analysis of the Central Bank of Nigeria using Markovian decision theory. The specific objectives include determining the (i) cash flow solvency ratio, (ii) cash flow adequacy ratio, (iii) sufficiency ratio, (iv) cash flow profitability ratio, and (v) estimating the optimal policy of cash flow ratios performance in CBN. The identified problems are the effects of (i) insolvency, (ii) inadequacy, (iii) insufficiency, and (v) Unprofitability on Central Bank of Nigeria (CBN) cash flows performance.The methodology involves a research design tailored toward collecting, arranging, and determining cash flow data for model prediction and optimization. The Markov chain is introduced as an operator to evaluate the distribution of cash flow ratios in the long term, using initial state vectors and state transition probabilities for forecasting behavior. Data validation is performed using graphical and Pearson moment correlation coefficient methods. The pre-model analysis of CBN cash flows problem during the period of January 2012 to December 2017 identifies six finite current states. State-2012 cash flows performance was exceptional (above the zero line), reflecting 100%, while State-2013 and 2015 reflect 75%, and State-2014, 2016 & 2017 reflect 50% healthy cash flows status. The model results introduce the Markovian Cash Flow Ratios Monitoring Curve (MCFRMC), specifying the minimum values for healthy status. The research explores the present status of cash flow ratios, presenting forecasted ratios in the form of an optimum policy or solution. Pearson moment correlation coefficient validation of the prototype and model results in a coefficient of 1.0, indicating a 100% higher performance of the model. Further research reveals strategic cash inflows policy allocation to the cash flows indicators, with (i) operational activity receiving 24%, (ii) investment activ

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