Inference for volatility-type objects and implications for hedging

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Spot volatility estimation for high-frequency data ∗ (2008, background): “For spot volatility estimation, Foster and Nelson (1996) first showed that spot volatility can be estimated from high-frequency data by rolling and block sampling filters.”
Nonparametric Filtering of the Realised Spot Volatility: A Kernel-Based Approach (2007, unknown): “Our estimator includes as a special case the rolling window estimator proposed by Foster and Nelson (1996); see also Andreou and Ghysels (2002) and Mykland and Zhang (2003,2006) .”
Estimating the Spot Covariation of Asset Prices—Statistical Theory and Empirical Evidence (2014, background): “Here, examples include Mykland and Zhang (2008), Mancini, Mattiussi, and Reno (2015), Bos, Janus, and Koopman (2012), and Zu and Boswijk (2014).”
Estimating spot volatility with high-frequency financial data (2014, methodology): “This was the assumption used in Mykland and Zhang (2008) about the volatility process.”