Decomposing the stock market intraday dynamics

Abstract

The correlation matrix formalism is used to study temporal aspects of the stock market evolution. This formalism allows to decompose the financial dynamics into noise as well as into some coherent repeatable intraday structures. The present study is based on the high-frequency Deutsche Aktienindex (DAX) data over the time period between November 1997 and September 1999, and makes use of both, the corresponding returns as well as volatility variations. One principal conclusion is that a bulk of the stock market dynamics is governed by the uncorrelated noise-like processes. There exists however a small number of components of coherent short term repeatable structures in fluctuations that may generate some memory effects seen in the standard autocorrelation function analysis. Laws that govern fluctuations associated with those various components are different, which indicates an extremely complex character of the financial fluctuations.

15 pages, 13 PostScript figures

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• The foreign exchange market: return distributions, multifractality, anomalous multifractality and Epps effect
• The bulk of the stock market correlation matrix is not pure noise
• Financial multifractality and its subtleties: an example of DAX
• Minimum spanning tree filtering of correlations for varying time scales and size of fluctuations
• Time scales involved in market emergence
• Alternation of different fluctuation regimes in the stock market dynamics