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Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp01q237hv31f
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dc.contributor.advisorFan, Jianqing-
dc.contributor.authorWu, Liukun-
dc.date.accessioned2015-07-29T16:49:02Z-
dc.date.available2015-07-29T16:49:02Z-
dc.date.created2015-04-13-
dc.date.issued2015-07-29-
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/dsp01q237hv31f-
dc.description.abstractThis paper investigates the interactions among the sovereign CDS daily log returns of ve major European Monetary Union countries (Germany, France, Italy, Portugal, and Spain) involved in the Eurozone debt crisis, from the period 2010 to 2014. We form a vector autoregression model (VAR) with the ve countries' CDS daily log returns as endogenous variables, and exogenous variables such as domestic factors (country's equity market return index), global risk factors (the VIX Index), and global macroeconomic factors (US Treasury daily yields) to account for the correlation among the sovereign CDS price series. We conditionally forecast the log returns three- month ahead using month by month rolling for maturities of 1, 5, and 10 years. We then calculate the root-mean-squared error (RSME) and compare that with the direct least squares and ARMA model forecast. We nd that the VAR model gives stable RMSE values of 0.03 on average for each sovereign for the 5 and 10 year maturities, 0.06 for the 1 year maturity, and performs slightly better than the direct least squares. The RMSE values from the ARMA model are similar to that of VAR model, but the VAR model is able to describe more characteristics in the return series and matches the volatility pattern better.en_US
dc.format.extent100 pages*
dc.language.isoen_USen_US
dc.titleVector Autoregression Analysis of the Sovereign Credit Default Swap Returns of Eurozone Economiesen_US
dc.typePrinceton University Senior Theses-
pu.date.classyear2015en_US
pu.departmentOperations Research and Financial Engineeringen_US
pu.pdf.coverpageSeniorThesisCoverPage-
Appears in Collections:Operations Research and Financial Engineering, 2000-2020

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