Fair value measurement is an estimation process, not a scientific method: Uncertainty is key, what are the expected cash flows, what type of industry is concerned, at what stage of the Business Life Cycle is the business valued. Some (groups of) assets (and liabilities) or (business) units will therefore always have more precise estimates of fair value than others.
Bias will always mystify fair value estimates: Much as we pay lip service to the notion that we can estimate fair value objectively, bias will find its way into fair value estimates. Honesty about the bias is all that we can demand. A good estimate of fair value is one where you will be willing to be either buyer or seller with real money.
Simple models will trump more complex models: More rules and complexity will not always yield better estimates of fair value.
Two ways to mount the uncertainties surrounding the estimation process and bias mystification is the use of the fair value hierarchy and the sensitivity analysis.
Fair value hierarchy:
Fair value accounting, also called “mark-to-market,” is a way to measure assets and liabilities that appear on a company’s balance sheet and income statement. To increase the consistency and comparability in fair value measurements and related disclosures, IFRS 13 (paras 72-90) established a fair value hierarchy that categorises the inputs to valuation techniques into three levels.
Here is a reference to some Wikipedia-motivational explanations regarding the use of sensitivity analysis as a validation tool to evidence the robustness of a fair valuation model.
The sensitivity analysis is a ‘what if’ exercise, the financial model used to calculate a fair value has inputs, those inputs can be varied and then the question is what happens?
The first question to challenge the model is, for example: – what happens if inputs one-by-one change plus/minus 10%, 30% 50%?
This provides the answer to which inputs are most important to provide a significant change to the fair value calculation. Also question yourselves: does this what if relation make sense? is my model correct?
The next thing to do is consider some powerful scenarios for some combinations of the most important inputs, along the lines of the following question: – what happens if a combination of for example 1/3rd of the most important inputs changes plus/minus 10%, 30% 50%?
The development of some powerful scenarios in itself is a challenge to the validity of the fair value calculation model. Are you using the correct inputs if you cannot develop some meaningful scenarios?
Challenging the fair value calculation model this way will improve the quality of the model and as a result the relevance of its outcome and potential use!