Value-at Risk under Measurement Error

Mohamed Doukali, Xiaojun Song and Abderrahim Taamouti

No 202209, Working Papers from University of Liverpool, Department of Economics

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, which might result in extreme leverage ratios within the held portfolios. 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.

Keywords: Deconvolution kernel; Fourier transform; measurement errors; market microstructure noise; optimization; Value-at-Risk (search for similar items in EconPapers)
JEL-codes: C14 C61 C63 G11 G19 (search for similar items in EconPapers)
Pages: 45 pages
Date: 2022-03
New Economics Papers: this item is included in nep-ecm and nep-rmg
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Forthcoming

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https://www.liverpool.ac.uk/media/livacuk/schoolof ... easurement,Error.pdf First version, 2022 (application/pdf)

Related works:
Journal Article: Value‐at‐Risk under Measurement Error (2024)
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Persistent link: https://EconPapers.repec.org/RePEc:liv:livedp:202209

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