Description
Statistical analysis and econometric techniques applied to financial data. Topics will include learning to use financial data, statistical diagnostics, forecasting, data mining for large data, asset allocation (copulas, GARCH, and DCC), hedging with derivatives, credit risk modeling, basic programming in Finance (Python or R).
Prerequisites
- Prerequisite(s): enrolment in the M.Finance program. Not open to students in the M.A. Economics program.
Conditions and arrangements
- Prerequisite(s): enrolment in the M.Finance program. Not open to students in the M.A. Economics program.
Reference text in its original language
Statistical analysis and econometric techniques applied to financial data. Topics will include learning to use financial data, statistical diagnostics, forecasting, data mining for large data, asset allocation (copulas, GARCH, and DCC), hedging with derivatives, credit risk modeling, basic programming in Finance (Python or R).
- Prerequisite(s): enrolment in the M.Finance program. Not open to students in the M.A. Economics program.
Sources and references
Dates and sources are retained to help you verify the information. Translations are provided to facilitate reading; the official source governs conditions and requirements.
Source reference : https://calendar.carleton.ca/grad/courses/ECON/