The wavelet variance is a scale-based decomposition of the process variance that is particularly well suited for analyzing intrinsically stationary processes. This decomposition has proven to be useful for studying various geophysical time series, including some related to sub-tidal sea level...

We introduce wavelet-based methodology for estimation of realized variance allowing its measurement in the time-frequency domain. Using smooth wavelets and Maximum Overlap Discrete Wavelet Transform, we allow for the decomposition of the realized variance into several investment horizons and...