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Measuring the Intraday Jump Tail Risk of Financial Asset Price with Noisy High Frequency Data
School of Statistics, University of International Business and Economics, Beijing, China
School of International Trade and Economics, University of International Business and Economics, Beijing, China
School of Statistics, University of International Business and Economics, Beijing, China
- 1 School of Statistics, University of International Business and Economics, Beijing, China
- 2 School of International Trade and Economics, University of International Business and Economics, Beijing, China
- 3 School of Statistics, University of International Business and Economics, Beijing, China
Open Journal of Statistics·Volume 07 (2017)·Pages 72–83·Published 9 February 2017·DOI10.4236/ojs.2017.71006
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Abstract
This paper proposes a simple two-step nonparametric procedure to estimate the intraday jump tail and measure the jump tail risk in asset price with noisy high frequency data. We first propose the pre-averaging threshold approach to estimate the intraday jumps occurred, and then use the peaks-over-threshold (POT) method and generalized Pareto distribution (GPD) to model the intraday jump tail and further measure the jump tail risk. Finally, an empirical example further demonstrates the power of the proposed method to measure the jump tail risk under the effect of microstructure noise.
KeywordsHigh Frequency DataIntraday JumpMicrostructure NoiseJump Tail RiskPre-Averaging
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