Other
Scientific paper
Jun 2000
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2000aipc..519..711f&link_type=abstract
STATISTICAL PHYSICS: Third Tohwa University International Conference. AIP Conference Proceedings, Volume 519, pp. 711-713 (2000
Other
Stochastic Processes, Other Topics In Areas Of Applied And Interdisciplinary Physics, Monte Carlo Methods
Scientific paper
It is known that, in an intermediate time-scale such as days, stock market fluctuations possess several statistical properties that are common to different markets. Namely, logarithmic returns of an asset price have (i) truncated Pareto-Lévy distribution, (ii) vanishing linear correlation, (iii) volatility clustering and its power-law autocorrelation. The fact (ii) is a consequence of nonexistence of arbitragers with simple strategies, but this does not mean statistical independence of market fluctuations. Little attention has been paid to temporal structure of higher-order statistics, although it contains some important information on market dynamics. We applied a signal separation technique, called Independent Component Analysis (ICA), to actual data of daily stock prices in Tokyo and New York Stock Exchange (TSE/NYSE). ICA does a linear transformation of lag vectors from time-series to find independent components by a nonlinear algorithm. We obtained a similar impulse response for these dataset. If it were a Martingale process, it can be shown that impulse response should be a delta-function under a few conditions that could be numerically checked and as was verified by surrogate data. This result would provide information on the market dynamics including speculative bubbles and arbitrating processes. .
Fujiwara Yoshi
Maekawa Satoshi
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