Revisiting stock market index correlations
Comovement of stock market indices increases during volatile periods, and does not come down when the turmoil settles down. This paper explains formation of persistent comovements during high volatility periods with theories from Bayesian learning. My main conclusion is that the correlation that is formed during the high volatility period is persistent because it is learned during the turmoil. The belief that interdependence between markets are high during the volatile period turns into reality by correlated actions of traders in different markets avoiding correlation to fall to its previous level.
Year of publication: |
2009
|
---|---|
Authors: | Dalkir, Mehmet |
Published in: |
Finance Research Letters. - Elsevier, ISSN 1544-6123. - Vol. 6.2009, 1, p. 23-33
|
Publisher: |
Elsevier |
Keywords: | Stock market index correlations Bayesian learning Stochastic systems |
Saved in:
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