Range-Based Estimation of Quadratic Variation

Kim Christensen () and Mark Podolskij ()

No 2006,37, Technical Reports from Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen

Abstract: This paper proposes using realized range-based estimators to draw inference about the quadratic variation of jump-diffusion processes. We also construct a range-based test of the hypothesis that an asset price has a continuous sample path. Simulated data shows that our approach is efficient, the test is well-sized and more powerful than a return-based t-statistic for sampling frequencies normally used in empirical work. Applied to equity data, we show that the intensity of the jump process is not as high as previously reported.

Keywords: Bipower Variation; Finite-Activity Counting Processes; Jump Detection; Quadratic Variation; Range-Based Bipower Variation; Semimartingale Theory (search for similar items in EconPapers)
JEL-codes: C10 C22 C80 (search for similar items in EconPapers)
Date: 2006
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Citations: View citations in EconPapers (27)

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Persistent link: https://EconPapers.repec.org/RePEc:zbw:sfb475:200637

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