A Model for Implementation of Fair Value Accounting in Corporate Financial Reporting

This study examined a mark-to model valuation of fair value measurement in corporate financial reporting in Nigeria. The objective of this study was to determine the best model that fits the estimation of share value in the Nigerian market during the pre meltdown and post meltdown period. The source of data for this study was secondary data collected from journals and published annual financial statement of certified banks or clean banks (according to the CBN Classification); for a period of five years (2005-2009). The statistical tools employed include curve fit analysis, regression analysis, correlation analysis and line graph analysis. The result of the analysis showed that the best fitted model for pre meltdown, post meltdown and general meltdown periods was the cubic regression model. It was found that cash flow was able to explain better variability in the measure of share value for the pre meltdown period with a coefficient of determination value of 19.1% followed by the general meltdown period with a coefficient of determination value of 7.1%. Also, it was revealed that the extent of relationship between the share value and cash flow for the pre meltdown, post meltdown and the general meltdown periods was obtained as 43.7%, 18.4% and 26.6% respectively. This result connotes that the extent of association between share value and cash flow is stronger during the pre meltdown period followed by the general meltdown period. In addition, the result showed that cash flow contributed significantly to the cubic regression model during the pre meltdown period but did not have significant impact during the post meltdown and the general meltdown period assuming a 95% confidence level. Furthermore, it was found that the estimated residuals or errors obtained using the cubic regression models were good estimates. This was because the estimated errors were found to fall within the upper and lower class limit at 95% confidence bound. In conclusion, the researchers were able to design three models, one for a period of economic boom called pre meltdown model, one for a period of economic meltdown called post meltdown model and another a combination of the two periods known as general meltdown