Estimation of continuous-time stochastic volatility models with jumps using high-frequency data

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Variance Risk-Premium Dynamics: The Role of Jumps (2010, methodology): “Under certain regularity conditions, as shown in Todorov (2009b), this has no asymptotic effect on the estimation results in this paper.”
The information content of high-frequency data for estimating equity return models and forecasting risk (2010, methodology): “…work such as Alizadeh, Brandt, and Diebold (2002), Barndorff-Nielsen and Shephard (2002), Bollerslev and Zhou (2002), Corradi and Distaso (2006), Todorov (2009) among others have used classical rather than Bayesian estimation methods and have focused on using high-frequency volatility measures…”
Estimation of Jump Tails (2011, methodology): “When the jump intensity is constant this estimation strategy corresponds directly to maximum likelihood, and it may be formalized more generally along the lines of the theoretical analysis in Todorov (2009).”
Understanding Systematic Risk: A High‐Frequency Approach (2020, unknown): “I use the TOD estimator of Bollerslev, Li and Todorov (2013) for separating the continuous from the jump movements.”
Large-dimensional factor modeling based on high-frequency observations (2019, unknown): “Bollerslev, Li and Todorov (2016) the predictable instantaneous quadratic covariation matrix of the residuals it is sufficient to assume that 1 N N ∑”