We study time-varying realized volatility and related correlation measures as proxies for
the true volatility and correlation. We investigate measures of Two-Scale realized
Absolute Volatility (TSAV) and correlation (TSACORxy) which are helpful to cope
effectively with the problem of market microstructure effects at very high frequency
financial time series. The measures are constructed based on subsampling and averaging
method so that they possess rather less bias even in presence of market microstructure
noise. Absolute transformation of return values has been proved in literature to be more
robust than squared transformation when considering large values. With respect to some
stylized facts of markets, realized squared correlation does not display dynamic behavior.
Motivated by robustness of realized absolute volatility, we study an alternative measure
of correlation, built on absolute-transformed volatility. This measure of correlation
exhibits experimentally some dynamics and hence some predictability capability on
minute-by-minute frequency exchange market data. We show that the distribution of
realized correlation series computed based on TSACORxy tends to comply a rightward
asymmetric shape implying that upside co-movements are greater than downside ones.
Moreover we study the association between realized volatility and correlation. According
to the two-scale measure, our findings empirically suggest that when returns in Euro/USD
exchange rate are highly volatile, the relation between Euro/USD and Euro/GBP
exchange markets is strong, and when Euro/USD calms down, the relationship relaxes