Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/297425 
Authors: 
Year of Publication: 
2023
Series/Report no.: 
Bank of Canada Staff Working Paper No. 2023-40
Publisher: 
Bank of Canada, Ottawa
Abstract: 
We introduce generalized autoregressive gamma (GARG) processes, a class of autoregressive and moving-average processes that extends the class of existing autoregressive gamma (ARG) processes in one important dimension: each conditional moment dynamic is driven by a different and identifiable moving average of the variable of interest. The paper provides ergodicity conditions for GARG processes and derives closed-form conditional and unconditional moments. The paper also presents estimation and inference methods, illustrated by an application to European option pricing where the daily realized variance follows a GARG dynamic. Our results show that using GARG processes reduces pricing errors by substantially more than using ARG processes does.
Subjects: 
Econometric and statistical methods
Asset pricing
JEL: 
C58
G12
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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