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<title>Journal of Financial Econometrics - Advance Access</title>
<link>http://jfec.oxfordjournals.org</link>
<description>Journal of Financial Econometrics - RSS feed of articles</description>
<prism:eIssn>1479-8417</prism:eIssn>
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<prism:issn>1479-8409</prism:issn>
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<item rdf:about="http://jfec.oxfordjournals.org/cgi/content/short/nbn006v1?rss=1">
<title><![CDATA[Are There Structural Breaks in Realized Volatility?]]></title>
<link>http://jfec.oxfordjournals.org/cgi/content/short/nbn006v1?rss=1</link>
<description><![CDATA[
<p>Constructed from high-frequency data, realized volatility (RV) provides an accurate estimate of the unobserved volatility of financial markets. This paper uses a Bayesian approach to investigate the evidence for structural breaks in reduced form time-series models of RV. We focus on the popular heterogeneous autoregressive (HAR) models of the logarithm of realized volatility. Using Monte Carlo simulations we demonstrate that our estimation approach is effective in identifying and dating structural breaks. Applied to daily S, and P 500 data from 1993-2004, we find strong evidence of a structural break in early 1997. The main effect of the break is a reduction in the variance of log-volatility. The evidence of a break is robust to different models including a GARCH specification for the conditional variance of log(<I>RV</I>).</p>
]]></description>
<dc:creator><![CDATA[Liu, C., Maheu, J. M.]]></dc:creator>
<dc:date>2008-05-08</dc:date>
<dc:identifier>info:doi/10.1093/jjfinec/nbn006</dc:identifier>
<dc:title><![CDATA[Are There Structural Breaks in Realized Volatility?]]></dc:title>
<dc:publisher>Oxford University Press</dc:publisher>
<prism:publicationDate>2008-05-08</prism:publicationDate>
<prism:section>Articles</prism:section>
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<item rdf:about="http://jfec.oxfordjournals.org/cgi/content/short/nbn005v1?rss=1">
<title><![CDATA[Periodic Dynamic Conditional Correlations between Stock Markets in Europe and the US]]></title>
<link>http://jfec.oxfordjournals.org/cgi/content/short/nbn005v1?rss=1</link>
<description><![CDATA[
<p>This study extends the dynamic conditional correlation model of Engle (2002, <I>Journal of Business and Economic Statistics 20</I>, 339&ndash;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&ndash;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.</p>
]]></description>
<dc:creator><![CDATA[Osborn, D. R., Savva, C. S., Gill, L.]]></dc:creator>
<dc:date>2008-05-08</dc:date>
<dc:identifier>info:doi/10.1093/jjfinec/nbn005</dc:identifier>
<dc:title><![CDATA[Periodic Dynamic Conditional Correlations between Stock Markets in Europe and the US]]></dc:title>
<dc:publisher>Oxford University Press</dc:publisher>
<prism:publicationDate>2008-05-08</prism:publicationDate>
<prism:section>Articles</prism:section>
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<item rdf:about="http://jfec.oxfordjournals.org/cgi/content/short/nbn004v1?rss=1">
<title><![CDATA[VAR Modeling for Dynamic Loadings Driving Volatility Strings]]></title>
<link>http://jfec.oxfordjournals.org/cgi/content/short/nbn004v1?rss=1</link>
<description><![CDATA[
<p>The implied volatility of an option as a function of strike price and time to maturity forms a volatility surface. Traders price according to the dynamics of this high dimensional surface. Recent developments that employ semiparametric models approximate the implied volatility surface (IVS) in a finite dimensional function space, allowing for a low dimensional factor representation of these dynamics. This paper presents an investigation into the stochastic properties of the factor loading time series using the vector autoregressive (VAR) framework and analyzes the dynamic relationship of these factors with economic indicators.</p>
]]></description>
<dc:creator><![CDATA[Bruggemann, R., Hardle, W., Mungo, J., Trenkler, C.]]></dc:creator>
<dc:date>2008-04-08</dc:date>
<dc:identifier>info:doi/10.1093/jjfinec/nbn004</dc:identifier>
<dc:title><![CDATA[VAR Modeling for Dynamic Loadings Driving Volatility Strings]]></dc:title>
<dc:publisher>Oxford University Press</dc:publisher>
<prism:publicationDate>2008-04-08</prism:publicationDate>
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