Cross-Stock Comparisons of the Relative Contribution of Jumps to Total Price Variance

By Vivek Bhattacharya. 2012

753 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/bead40990aef60c1715aab5c12a0b2569f91905d

How researchers see this paper

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

Citations in the corpus

Self-Exciting Jumps, Learning, and Asset Pricing Implications (2015, background): “For example, Huang and Tauchen (2005) find that the jump component takes about 7% of total volatility, and Andersen, Bollerslev and Diebold (2007) find that it accounts for about 15% of total volatility.”
Fact or friction: jumps at ultra high frequency (2014, unknown): “…volatility model with leverage (SV2F-LEV) proposed by Chernov, Gallant, Ghysels, and Tauchen (2003), using calibrated parameter values reported in Huang and Tauchen (2005), (4) a Brownian motion plus jump (BMJ) model, in which we position a jump of random size at a random point in the series,…”
Forecasting realized volatility of agricultural commodity futures with infinite Hidden Markov HAR models (2019, unknown): “We apply the deﬁnitions of Huang & Tauchen (2005) and calculate the jump component as follows where Φ α refers to the critical value of the Gaussian distribution with and µ 1 = E ( Z ) = 2 /π .”
Data-based ranking of realised volatility estimators (2011, background): “The expression above is from Aït-Sahalia, et al. (2005), while the proportion of 20% is around the middle value considered in the simulation study of Huang and Tauchen (2005).”
Semiparametric Conditional Quantile Models for Financial Returns and Realized Volatility (2013, result): “Similar to previous empirical results (Huang & Tauchen, 2005) we find that jumps are relatively infrequent.”
Estimation of Jump Tails (2011, result): “This is directly in line with the recent non-parametric empirical evidence reported in BarndorffNielsen and Shephard (2004, 2006), Huang and Tauchen (2005), and Andersen et al. (2007), among others.”
Bootstrapping realized multivariate volatility measures (2010, unknown): “Both lower one-sided (where θ ≤ a for some random variable a and θ the parameter of interest) and upper one-sided (where θ ≥ b for some random variable b) intervals are considered.”
News - Good or Bad - and its Impact on Volatility Predictions over Multiple Horizons (2011, unknown): “Note two important issues, namely (1) we gain information since we do not aggregate intra- 3 On the subject of extracting jump see for instance, Aı̈t-Sahalia (2004), Aı̈t-Sahalia and Jacod (2007b), Aı̈t-Sahalia and Jacod (2007a), Andersen, Bollerslev, and Diebold (2006), Barndorff-Nielsen, Graversen”
Box–Cox transforms for realized volatility (2011, methodology): “The first model is the GARCH(1,1) diffusion of Andersen and Bollerslev (1998) and the second model is a two-factor diffusion model analyzed by Huang and Tauchen (2006).”