On the jump activity index for semimartingales

75 citations recorded by the source corpus.

Subfields: Finance

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Analyzing the Spectrum of Asset Returns: Jump and Volatility Components in High Frequency Data (2010, unknown): “Refinements of the approach are starting to be developed (see Fan and Fan 2011 and Jing et al. 2012).”
Testing for pure-jump processes for high-frequency data (2015, unknown): “…a continuous local martingale with σs being an adapted process and Ws a standard Brownian motion and the last term is a pure-jump component with the jump activity index β defined by β = inf { r; ∑ 0≤s≤T |∆sX|r ≤∞ } ,(1.1) where ∆sX =Xs −Xs−; see Aı̈t-Sahalia and Jacod (2009) and Jing et al. (2012).”
On the number of common factors with high‐frequency data (2017, methodology): “These are commonly used in the literature (see, e.g., Wang & Zou, 2010; Jing et al., 2012a,b; Jacod & Podolskij, 2013; Jacod & Rosenbaum, 2013).”