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Extracting Market Trends from the Cross Correlation between Stock Time Series

Authors:
Mieko Tanaka-Yamawaki
Takemasa Kido

Keywords: Correlation; Eigenvalues; Principal Component; Stock Market; Trend

Abstract:
We apply the RMT-PCA, recently developed PCA in order to grasp temporal trends in a stock market, on daily-close stock prices of American Stocks in NYSE for 16 years from 1994 to 2009 and show the effectiveness and consistency of this method by analyzing the whole data of 16 years at once, as well as analyzing the cut data in various lengths between 2-8 years. The extracted trends are consistent to the actual history of the markets. We also discuss on the problem of setting the effective border between the noise and signals considering the artificial correlation created in the process of taking log-return in analyzing the price time series.

Pages: 14 to 19

Copyright: Copyright (c) IARIA, 2011

Publication date: September 25, 2011

Published in: conference

ISSN: 2308-3735

ISBN: 978-1-61208-154-0

Location: Rome, Italy

Dates: from September 25, 2011 to September 30, 2011