Original title:
Multifractal height cross-correlation analysis
Authors:
Krištoufek, Ladislav Document type: Research reports
Year:
2010
Language:
eng Series:
Research Report, volume: 2281 Abstract:
We introduce a new method for detection of long-range cross-correlations and cross-multifractality – multifractal height cross-correlation analysis (MF-HXA). We show that long-range cross-correlations can be caused by long-range dependence of separate processes and the correlations above them. Similar separation applies for cross-multifractality – standard sep- aration between distributional properties and correlations is enriched by division of correlations between auto-correlations and cross-correlations. Efficiency of the method is showed on two types of simulated series – ARFIMA and Mandelbrot’s Binomial Multifractal model. We further ap- ply the method on returns and volatility of NASDAQ and S&P500 indices and uncover some interesting results.
Keywords:
cross-correlations; long-range dependence; multifractality Project no.: CEZ:AV0Z10750506 (CEP), 118310, GD402/09/H045 (CEP), GA402/09/0965 (CEP) Funding provider: GA UK, GA ČR, GA ČR