Abstract
PurposeThis paper aims to investigate possibility of statistical detection of market completeness for continuous time diffusion stock market models.Design/methodology/approachThe paper uses theory of forecasting to find criteria of predictability of market parameters such as volatilities and the appreciation rates.FindingsIt is known that the market completeness is not a robust property: small random deviations of the coefficients convert a complete market model into an incomplete one. The paper shows that market incompleteness is also non-robust: for any incomplete market from a wide class of models, there exists a complete market model with arbitrarily close paths of the stock prices and the market parameters.Originality/valueThe paper results lead to a counterintuitive conclusion that the incomplete markets are indistinguishable in the terms of the market statistics.
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