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PRODID:-//Mathematical Finance - ECPv5.7.0//NONSGML v1.0//EN
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X-WR-CALNAME:Mathematical Finance
X-ORIGINAL-URL:https://www.math.ttu.edu/mathematicalfinance
X-WR-CALDESC:Events for Mathematical Finance
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TZID:America/Chicago
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TZOFFSETFROM:-0600
TZOFFSETTO:-0500
TZNAME:CDT
DTSTART:20240310T080000
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DTSTART:20241103T070000
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DTSTART;TZID=America/Chicago:20241025T100000
DTEND;TZID=America/Chicago:20241025T110000
DTSTAMP:20260417T104306
CREATED:20240801T143537Z
LAST-MODIFIED:20240801T143642Z
UID:1512-1729850400-1729854000@www.math.ttu.edu
SUMMARY:Estimation and backtesting of risk measures with emphasis on distortion risk measures
DESCRIPTION:Speaker: Prof. Hideatsu Tsukahara\, Dept.. of Economics\, Seijo University\, Tokyo \nAbstract: Statistical methodology has an important role to play in risk measurement. In this paper\, we will review and discuss some statistical issues on risk measures. Examples we consider are value-at-risk\, expected shortfall\, expectiles\, and distortion risk measures. Several methods of estimating these risk measures based on time series data have been proposed\, and we will try to explain in some detail. Another main issue we would like to address is a problem of backtesting: the evaluation of risk measurement procedures using historical data\, by comparing ex ante estimates of loss distributions or risk measures with the ex post realized losses. There have been several suggestions concerning backtestability of risk measures\, which will be discuss in detail. We also examine and suggest backtesting procedures for predictive distributions\, expected shortfall and distortion risk measures.
URL:https://www.math.ttu.edu/mathematicalfinance/event/estimation-and-backtesting-of-risk-measures-with-emphasis-on-distortion-risk-measures/
LOCATION:via Zoom
CATEGORIES:Fall 2024,Seminars
ATTACH;FMTTYPE=image/jpeg:https://www.math.ttu.edu/mathematicalfinance/wp-content/uploads/2024/08/Tsukahara.jpg
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