Extreme-quantile tracking for financial time series
نویسندگان
چکیده
Time series of financial asset values exhibit well known statistical features such as heavy tails and volatility clustering. We propose a nonparametric extension of the classical Peaks-Over-Threshold method from Extreme Value Theory to fit the time varying volatility in situations where the stationarity assumption may be violated by erratic changes of regime, say. As a result, we provide a method for estimating conditional risk measures applicable to both stationary and nonstationary series. A backtesting study for the UBS share price over the subprime crisis exemplifies our approach. JEL classification: C.11; C.14; C.22; G.10; G.21.
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