Abstract
It is well known that while daily price returns of financial markets are uncorrelated, their absolute values ('volatility') are long-term correlated. Here we provide evidence that certain subsequences of the returns themselves also exhibit long-term memory. These subsequences consist of maxima (or minima) of returns in consecutive time windows of R days. Our analysis shows that for both stocks and currency exchange rates, long-term correlations are significant for R ≥ 4. We argue that this long-term memory which is similar to that observed in volatility clustering sheds further insight on price dynamics that might be used for risk estimation.
Original language | English |
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Pages (from-to) | 4145-4150 |
Number of pages | 6 |
Journal | Physica A: Statistical Mechanics and its Applications |
Volume | 388 |
Issue number | 19 |
DOIs | |
State | Published - 1 Oct 2009 |
Externally published | Yes |
Keywords
- Econophysics
- Extreme values
- Long-term correlation
- Long-term memory
- Volatility