Myths of Market Consistent Valuation

    Guest Post from Elliot Varnell

    Myth 1: An arbitrage free model will by itself give a market consistent valuation.

    An arbitrage-free model which is calibrated to deep and liquid market data will give a market consistent valuation. An arbitrage-free model which ignores available deep and liquid market data does not give a market consistent valuation. Having said this there is not a tight definition of what constitutes deep and liquid market data, therefore there is no tight definition of what constitutes market consistent valuation. For example a very relevant question is whether calibrating to historic volatility can be considered market consistent if there is a marginally liquid market in options. CEIOPs CP39 published in July 2009 appears to leave open the questions of which volatility could be used, while CP41 requires that a market is deep and liquid, transparent and that these properties are permanent.

    Myth 2: A model calibrated to deep and liquid market data will give a Market Consistent Valuation.

    A model calibrated to deep and liquid market data will only give a market consistent valuation if the model is also arbitrage free. If a model ignores arbitrage free dynamics then it could still be calibrated to replicate certain prices. However this would not be a sensible framework marking to model the prices of other assets and liabilities as is required for the valuation of many participating life insurance contracts Having said this the implementation of some theoretically arbitrage free models are not always fully arbitrage free themselves, due to issues such as discretisation, although they can be designed to not be noticeably arbitrage free within the level of materiality of the overall technical provision calculation.

    Myth 3: Market Consistent Valuation gives the right answer.

    Market consistent valuation does not give the right answer, per se, but an answer conditional on the model and the calibration parameters. The valuation is only as good as these underlying assumptions. One thing we can be sure of is that the model will be wrong in some way. This is why understanding and documenting the weakness of an ESG model and its calibration is as important as the actual model design and calibration itself.

    Myth 4: Market Consistent Valuation gives the amount that a 3rd party will pay for the business.

    Market Consistent Valuation (as calculated using an ESG) gives a value based on pricing at the margin. As with many financial economic models the model is designed to provide a price based on a small scale transaction, ignoring trading costs, and market illiquidity. The assumption is made that the marginal price of the liability can be applied to the entire balance sheet. Separate economic models are typically required to account for micro-market features; for example the illiquidity of markets or the trading and frictional costs inherent from following an (internal) dynamic hedge strategy. Micro-market features can be most significant in the most extreme market conditions; for example a 1-in-200 stress event.

    Even allowing for the micro-market features a transaction price will account (most likely in much less quantitative manner than using an ESG) the hard to value assets (e.g. franchise value) or hard to value liabilities (e.g. contingent liabilities).

    Myth 5: Market Consistent Valuation is no more accurate than Discounted Cash Flow techniques using long term subjective rates of return.

    The previous myths could have suggested that market consistent valuation is in some way devalued or not useful. This is certainly the viewpoint of some actuaries especially in the light of the recent financial crisis. However it could be argued that market consistent valuation, if done properly, gives a more economically meaningful value than traditional DCF techniques and provides better disclosure than traditional DCF. It does this by breaking down the problem into clear assumptions about what economic theory is being applied and clear assumption regarding what assumptions are being made. By breaking down the models and assumptions weaknesses are more readily identified and economic theory can be applied.


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