Choosing a data frequency to forecast the quarterly yen-dollar exchange rate

dc.contributor.authorCann, Benjamin
dc.contributor.supervisorGiles, David E. A.
dc.date.accessioned2016-10-03T19:57:58Z
dc.date.available2016-10-03T19:57:58Z
dc.date.copyright2016en_US
dc.date.issued2016-10-03
dc.degree.departmentDepartment of Economicsen_US
dc.degree.levelMaster of Arts M.A.en_US
dc.description.abstractPotentially valuable information about the underlying data generating process of a dependent variable is often lost when an independent variable is transformed to fit into the same sampling frequency as a dependent variable. With the mixed data sampling (MIDAS) technique and increasingly available data at high frequencies, the issue of choosing an optimal sampling frequency becomes apparent. We use financial data and the MIDAS technique to estimate thousands of regressions and forecasts in the quarterly, monthly, weekly, and daily sampling frequencies. Model fit and forecast performance measurements are calculated from each estimation and used to generate summary statistics for each sampling frequency so that comparisons can be made between frequencies. Our regression models contain an autoregressive component and five additional independent variables and are estimated with varying lag length specifications that incrementally increase up to five years of lags. Each regression is used to forecast a rolling, one and two-step ahead, static forecast of the quarterly Yen and U.S Dollar spot exchange rate. Our results suggest that it may be favourable to include high frequency variables for closer modeling of the underlying data generating process but not necessarily for increased forecasting performance.en_US
dc.description.proquestcode0501en_US
dc.description.proquestcode0508en_US
dc.description.proquestcode0511en_US
dc.description.proquestemailbenjamincann@gmail.comen_US
dc.description.scholarlevelGraduateen_US
dc.identifier.urihttp://hdl.handle.net/1828/7587
dc.languageEnglisheng
dc.language.isoenen_US
dc.rightsAvailable to the World Wide Weben_US
dc.rights.urihttp://creativecommons.org/licenses/by-nd/2.5/ca/*
dc.subjectmixed data samplingen_US
dc.subjectforecastingen_US
dc.subjectmodel selection criteriaen_US
dc.subjecttime-seriesen_US
dc.subjectyen dollar exchange rateen_US
dc.subjecteconometricsen_US
dc.subjecteconomicsen_US
dc.subjectMIDASen_US
dc.subjectforeign exchange ratesen_US
dc.titleChoosing a data frequency to forecast the quarterly yen-dollar exchange rateen_US
dc.typeThesisen_US

Files

Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Cann_Benjamin_MA_2016.pdf
Size:
1.44 MB
Format:
Adobe Portable Document Format
Description:
Thesis
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.74 KB
Format:
Item-specific license agreed upon to submission
Description: