A Haar-Fisz technique for locally stationary volatility estimation

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Normalized least-squares estimation in time-varying ARCH models (2008, methodology): “Arguments for using such models were laid out, for example, in Fan, Jiang, Zhang and Zhou (2003), Mikosch and Stărică (2000, 2003, 2004), Mercurio and Spokoiny (2004a, 2004b), Stărică and Granger (2005) and Fryzlewicz et al. (2006).”
Detecting gradual changes in locally stationary processes (2013, background): “In this case, σ(u) ≈ σ(1) at future time points u ∈ (1, 1 + δ], which suggests to use the present volatility level σ(1) as a forecast for the near future [see Fryzlewicz et al. (2006) among others].”
Detection of Multiple Structural Breaks in Multivariate Time Series (2013, methodology): “Consequently numerous alternative models have been proposed to address model features of non-stationarity [see Jansen et al. (1981), Dahlhaus (1997), Adak (1998) or Ombao et al.”
Empirical spectral processes for locally stationary time series (2009, background): “Out of the large literature, we mention the work of Priestley (1965) on oscillatory processes, Dahlhaus (1997) on locally stationary processes, Neumann and von Sachs (1997) on wavelet estimation of evolutionary spectra, Nason, von Sachs and Kroisandt (2000) on a wavelet-based model of evolutionary s”