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Designing realized kernels to measure the ex post variation of equity prices in the presence of noise. (English) Zbl 1153.91416
Summary: This paper shows how to use realized kernels to carry out efficient feasible inference on the ex post variation of underlying equity prices in the presence of simple models of market frictions. The weights can be chosen to achieve the best possible rate of convergence and to have an asymptotic variance which equals that of the maximum likelihood estimator in the parametric version of this problem. Realized kernels can also be selected to (i) be analyzed using endogenously spaced data such as that in data bases on transactions, (ii) allow for market frictions which are endogenous, and (iii) allow for temporally dependent noise. The finite sample performance of our estimators is studied using simulation, while empirical work illustrates their use in practice.

MSC:
91B24 Microeconomic theory (price theory and economic markets)
91B84 Economic time series analysis
62P05 Applications of statistics to actuarial sciences and financial mathematics
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