Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/2133
Title: | Periodic dynamic conditional correlations between stock markets in Europe and the US | Authors: | Osborn, Denise R. Gill, Len Savva, Christos S. |
Major Field of Science: | Social Sciences | Field Category: | SOCIAL SCIENCES | Keywords: | Day-of-the-week-effect;Dynamic conditional correlations;Periodic models;Volatility | Issue Date: | 2008 | Source: | Journal of Financial Econometrics, 2008, vol. 6, iss. 3, pp. 307-325 | Volume: | 6 | Issue: | 3 | Start page: | 307 | End page: | 325 | Journal: | Journal of Financial Econometrics | Abstract: | This study extends the dynamic conditional correlation model of Engle (2002, Journal of Business and Economic Statistics 20, 339-350) to allow periodic (day-specific) conditional correlations of shocks across international stock markets. The properties of the resulting periodic dynamic conditional correlation (PDCC) model are examined, focusing particularly on stationarity and the implications for unconditional shock correlations. When applied to the intraweek interactions between six developed European stock markets and the United States over 1993-2005, we find very strong evidence of periodic conditional correlations for the shocks. The highest correlations are generally observed on Thursdays, with these sometimes being twice those on Monday or Tuesday. In addition to these PDCC effects, strong day-of-the-week effects are found in mean returns for the French, Italian, and Spanish stock markets, while periodic effects are also present in volatility for all stock markets except Italy. | URI: | https://hdl.handle.net/20.500.14279/2133 | ISSN: | 14798409 | DOI: | 10.1093/jjfinec/nbn005 | Rights: | © The Author. Published by Oxford University Press | Type: | Article | Affiliation: | University of Cyprus | Affiliation : | The University of Manchester University of Cyprus |
Publication Type: | Peer Reviewed |
Appears in Collections: | Άρθρα/Articles |
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nbn005.pdf | Open Access | 357.45 kB | Adobe PDF | View/Open |
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