File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Conference Paper: Applications of Functional Dynamic Factor Models

TitleApplications of Functional Dynamic Factor Models
Authors
Issue Date2013
Citation
Springer Proceedings in Mathematics and Statistics, 2013, v. 55, p. 23-37 How to Cite?
AbstractAccurate forecasting of zero coupon bond yields for a continuum of maturities is paramount to bond portfolio management and derivative security pricing. Yet a universal model for yield curve forecasting has been elusive, and prior attempts often resulted in a tradeoff between goodness-of-fit and consistency with economic theory. To address this, herein we propose a novel formulation which connects the dynamic factor model (DFM) framework with concepts from functional data analysis: a DFM with functional factor loading curves. This results in a model capable of forecasting functional time series. Further, in the yield curve context we show that the model retains economic interpretation. We show that our model performs very well on forecasting actual yield data compared with existing approaches, especially in regard to profit-based assessment for an innovative trading exercise. We further illustrate the viability of our model to applications outside of yield forecasting. © Springer Science+Business Media New York 2013.
Persistent Identifierhttp://hdl.handle.net/10722/219718
ISSN

 

DC FieldValueLanguage
dc.contributor.authorHays, Spencer-
dc.contributor.authorShen, Haipeng-
dc.contributor.authorHuang, Jianhua Z.-
dc.date.accessioned2015-09-23T02:57:48Z-
dc.date.available2015-09-23T02:57:48Z-
dc.date.issued2013-
dc.identifier.citationSpringer Proceedings in Mathematics and Statistics, 2013, v. 55, p. 23-37-
dc.identifier.issn2194-1009-
dc.identifier.urihttp://hdl.handle.net/10722/219718-
dc.description.abstractAccurate forecasting of zero coupon bond yields for a continuum of maturities is paramount to bond portfolio management and derivative security pricing. Yet a universal model for yield curve forecasting has been elusive, and prior attempts often resulted in a tradeoff between goodness-of-fit and consistency with economic theory. To address this, herein we propose a novel formulation which connects the dynamic factor model (DFM) framework with concepts from functional data analysis: a DFM with functional factor loading curves. This results in a model capable of forecasting functional time series. Further, in the yield curve context we show that the model retains economic interpretation. We show that our model performs very well on forecasting actual yield data compared with existing approaches, especially in regard to profit-based assessment for an innovative trading exercise. We further illustrate the viability of our model to applications outside of yield forecasting. © Springer Science+Business Media New York 2013.-
dc.languageeng-
dc.relation.ispartofSpringer Proceedings in Mathematics and Statistics-
dc.titleApplications of Functional Dynamic Factor Models-
dc.typeConference_Paper-
dc.description.natureLink_to_subscribed_fulltext-
dc.identifier.doi10.1007/978-1-4614-7846-1_3-
dc.identifier.scopuseid_2-s2.0-84886075466-
dc.identifier.volume55-
dc.identifier.spage23-
dc.identifier.epage37-
dc.identifier.eissn2194-1017-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats