Abstract
Distributional assumptions of financial return data are an important issue for asset-pricing and portfolio management as well as risk controlling. In order to capture the departure of empirical observations of financial return data from normality the Student’s t-distribution has been proposed as an alternative fat-tailed distribution in the literature. In this paper we (i) briefly summarize the Student’s t-distribution; (ii) compare the tail behavior of the Student’s t-distribution with empirical data; and (iii) discuss some implications of the empirical results on the risk management based on Value-at-Risk. We also suggest a simple statistic as a measure of tail-thickness based on the sample quantile and the first absolute moment.
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© 1999 Springer-Verlag Berlin · Heidelberg
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Huschens, S., Kim, JR. (1999). Measuring Risk in Value-at-Risk Based on Student’s t-Distribution. In: Gaul, W., Locarek-Junge, H. (eds) Classification in the Information Age. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-60187-3_48
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DOI: https://doi.org/10.1007/978-3-642-60187-3_48
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