{"id":{"repo_id":"essex","oai_identifier":"oai:repository.essex.ac.uk:25498"},"canonical_url":"https://search.dev.ndltd.org/etd/essex/oai:repository.essex.ac.uk:25498","repository":{"repo_id":"essex","name":"University of Essex","base_url":"https://repository.essex.ac.uk/cgi/oai2"},"display":{"title":"Essays on Term Structures","abstract":"This thesis explores two topics on terms structures in two different asset classes,the term structures fit and its predictive power. The second chapter researches the difference and relative goodness of fit of two term structure models, the Cox, Ingersoll and Ross (CIR hereafter) 2-factor model and a two factor essentially affine model, EA1(2). The latter model generates correlation between the factors and time-varying risk premia. However these characteristics increase the complexity of the model which makes the estimation computationally more intensive (up to 3 times more intensive). Applying the Kalman Filter to fit the models, using data that incorporates both Black Wednesday and the 2008 credit crisis, it is found that the added complexity of the essentially affine model only marginally improves the fit to the UK term structure not outweighing the tractability properties of the CIR model. The third and fourth chapters study the predictive power of the time varying shape of the credit default swap (CDS) term structure in the context of explaining changes in future implied and excess implied volatility and providing a leading signal of potential financial distress in a company. The shape of the CDS curve is captured by fitting the Nelson-Siegel model to the term structure and creating a new binary indicator (Shape Indicator) to distinguish between “good” and “bad” CDS curves. Applying the methodology to 20 US traded companies from both the financial and non-financial sectors, the credit market is found generally to be a leading indicator for movements in the volatility market during the sub-prime crisis. After confirming the strong link between the CDS and the implied volatility markets, a partial F-test is applied to test whether additional information is contained within the CDS markets over and above the volatility markets. For the period studied, this is the case for the majority of names and particularly significant for Lehman Brothers.","abstract_html":"This thesis explores two topics on terms structures in two different asset classes,the term structures fit and its predictive power. The second chapter researches the difference and relative goodness of fit of two term structure models, the Cox, Ingersoll and Ross (CIR hereafter) 2-factor model and a two factor essentially affine model, EA1(2). The latter model generates correlation between the factors and time-varying risk premia. However these characteristics increase the complexity of the model which makes the estimation computationally more intensive (up to 3 times more intensive). Applying the Kalman Filter to fit the models, using data that incorporates both Black Wednesday and the 2008 credit crisis, it is found that the added complexity of the essentially affine model only marginally improves the fit to the UK term structure not outweighing the tractability properties of the CIR model. The third and fourth chapters study the predictive power of the time varying shape of the credit default swap (CDS) term structure in the context of explaining changes in future implied and excess implied volatility and providing a leading signal of potential financial distress in a company. The shape of the CDS curve is captured by fitting the Nelson-Siegel model to the term structure and creating a new binary indicator (Shape Indicator) to distinguish between “good” and “bad” CDS curves. Applying the methodology to 20 US traded companies from both the financial and non-financial sectors, the credit market is found generally to be a leading indicator for movements in the volatility market during the sub-prime crisis. After confirming the strong link between the CDS and the implied volatility markets, a partial F-test is applied to test whether additional information is contained within the CDS markets over and above the volatility markets. For the period studied, this is the case for the majority of names and particularly significant for Lehman Brothers.","abstract_has_math":false,"creators":["Castellanos Pinzon, Jenny"],"institution":"University of Essex","degree_name":"phd","degree_level":"doctoral","degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2019,"date_issued":"2019-07","date_published":"2019-07","updated_at":"2026-07-24T02:18:29Z","subjects":[],"languages":["en"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":null,"outbound_label":null,"outbound_source":null},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Castellanos Pinzon, Jenny"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2019-07"]},{"key":"dc:date.issued","label":"Date","values":["2019-07"]},{"key":"dc:publisher.department","label":"Dc Publisher Department","values":["Centre for Computational Finance and Economic Agents"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["University of Essex"]},{"key":"dc:relation.isreferencedby","label":"Dc Relation Isreferencedby","values":["https://repository.essex.ac.uk/25498/"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["doctoral"]},{"key":"dc:type.qualificationname","label":"Dc Type Qualificationname","values":["phd"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://repository.essex.ac.uk/25498/1/Thesis_v1.pdf"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["This thesis explores two topics on terms structures in two different asset classes,the term structures fit and its predictive power. The second chapter researches the difference and relative goodness of fit of two term structure models, the Cox, Ingersoll and Ross (CIR hereafter) 2-factor model and a two factor essentially affine model, EA1(2). The latter model generates correlation between the factors and time-varying risk premia. However these characteristics increase the complexity of the model which makes the estimation computationally more intensive (up to 3 times more intensive). Applying the Kalman Filter to fit the models, using data that incorporates both Black Wednesday and the 2008 credit crisis, it is found that the added complexity of the essentially affine model only marginally improves the fit to the UK term structure not outweighing the tractability properties of the CIR model. The third and fourth chapters study the predictive power of the time varying shape of the credit default swap (CDS) term structure in the context of explaining changes in future implied and excess implied volatility and providing a leading signal of potential financial distress in a company. The shape of the CDS curve is captured by fitting the Nelson-Siegel model to the term structure and creating a new binary indicator (Shape Indicator) to distinguish between “good” and “bad” CDS curves. Applying the methodology to 20 US traded companies from both the financial and non-financial sectors, the credit market is found generally to be a leading indicator for movements in the volatility market during the sub-prime crisis. After confirming the strong link between the CDS and the implied volatility markets, a partial F-test is applied to test whether additional information is contained within the CDS markets over and above the volatility markets. For the period studied, this is the case for the majority of names and particularly significant for Lehman Brothers."]},{"key":"dc:format","label":"Dc Format","values":["text"]},{"key":"dc:title","label":"Title","values":["Essays on Term Structures"]}]}],"canonical_facts":{"dc:creator":["Castellanos Pinzon, Jenny"],"dc:date":["2019-07"],"dc:date.issued":["2019-07"],"dc:description.abstract":["This thesis explores two topics on terms structures in two different asset classes,the term structures fit and its predictive power. The second chapter researches the difference and relative goodness of fit of two term structure models, the Cox, Ingersoll and Ross (CIR hereafter) 2-factor model and a two factor essentially affine model, EA1(2). The latter model generates correlation between the factors and time-varying risk premia. However these characteristics increase the complexity of the model which makes the estimation computationally more intensive (up to 3 times more intensive). Applying the Kalman Filter to fit the models, using data that incorporates both Black Wednesday and the 2008 credit crisis, it is found that the added complexity of the essentially affine model only marginally improves the fit to the UK term structure not outweighing the tractability properties of the CIR model. The third and fourth chapters study the predictive power of the time varying shape of the credit default swap (CDS) term structure in the context of explaining changes in future implied and excess implied volatility and providing a leading signal of potential financial distress in a company. The shape of the CDS curve is captured by fitting the Nelson-Siegel model to the term structure and creating a new binary indicator (Shape Indicator) to distinguish between “good” and “bad” CDS curves. Applying the methodology to 20 US traded companies from both the financial and non-financial sectors, the credit market is found generally to be a leading indicator for movements in the volatility market during the sub-prime crisis. After confirming the strong link between the CDS and the implied volatility markets, a partial F-test is applied to test whether additional information is contained within the CDS markets over and above the volatility markets. For the period studied, this is the case for the majority of names and particularly significant for Lehman Brothers."],"dc:format":["text"],"dc:identifier.uri":["https://repository.essex.ac.uk/25498/1/Thesis_v1.pdf"],"dc:language":["en"],"dc:publisher.department":["Centre for Computational Finance and Economic Agents"],"dc:publisher.institution":["University of Essex"],"dc:relation.isreferencedby":["https://repository.essex.ac.uk/25498/"],"dc:title":["Essays on Term Structures"],"dc:type":["Thesis"],"dc:type.qualificationlevel":["doctoral"],"dc:type.qualificationname":["phd"]},"updated_at":"2026-07-24T02:18:29Z"}