IDENTIFYING THE BROWNIAN COVARIATION FROM THE CO-JUMPS GIVEN DISCRETE OBSERVATIONS

By Cecilia Mancini, F. Gobbi. Econometric Theory, 2012

73 citations recorded by the source corpus.

How researchers see this paper

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

Adaptive estimation of continuous-time regression models using high-frequency data (2017, methodology): “The second is the estimator in Barndorff-Nielsen and Shephard (2004), Todorov and Bollerslev (2010) and Gobbi and Mancini (2012).”
Systemic Co-Jumps (2017, unknown): “Consider first the case with the indicator kernel: Ãn,1 := n∑ j=1 ( ∆jX (i) )2 N∏ k=1 I{|∆jX(k)|>H(k)j∆,n} (A.14) which tends to zero on Ω N T [Mancini and Gobbi, 2012, straightforward generalization of Theorem 4.2].”
Econometrics of co-jumps in high-frequency data with noise (2015, methodology): “An important step for considering co-jumps in a multi-dimensional framework and extending truncation methods has been laid by Jacod and Todorov (2009) and Gobbi and Mancini (2012).”
Is the diurnal pattern sufficient to explain intraday variation in volatility? A nonparametric assessment (2017, unknown): “Note that ˇΣ n is related to recent work on asymptotic variance estimation by Mykland and Zhang (2017); see also, e.g., Christensen, Podolskij, Thamrongrat, and Veliyev (2017); Jacod and Todorov (2009); Mancini and Gobbi (2012).”