CEBA talks 2020-2022
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Value-at-Risk under Measurement Error

Authors: Abderrahim Taamouti, Mohamed Doukali and Xiaojun Song.

Abstract: We propose an optimization-based estimation of Value-at-Risk that corrects for the effect of measurement errors in prices. We show that measurement errors might pose serious problems for estimating risk measures like Value-at-Risk. In particular, when the stock prices are contaminated, the existing estimators of Value-at-Risk are inconsistent and might lead to an underestimation of risk. Using Fourier transform and a deconvolution kernel estimator of the probability distribution function of true latent prices, we derive a robust estimator of Value-at-Risk in the presence of measurement errors. Monte Carlo simulations and a real data analysis illustrate satisfactory performance of the proposed method.

Presentation slides