Time Series (Intermediate)
Dublin City University
Area of Study
Taught In English
Course Level Recommendations
ISA offers course level recommendations in an effort to facilitate the determination of course levels by credential evaluators.We advice each institution to have their own credentials evaluator make the final decision regrading course levels.
Recommended U.S. Semester Credits3
Recommended U.S. Quarter Units5
Hours & Credits
The module introduces the main concepts underlying the analysis of Time Series models, studying the stationarity of linear time series and some related models. It also includes an introduction to Monte Carlo simulation and introduces dynamic discrete time financial models. The module does not render students eligible for exemptions from professional actuarial examinations, and therefore assessment differs somewhat from a corresponding module delivered to actuarial students (MS447).
1. prove whether given time series models are weakly or strictly stationary
2. establish the important properties of moving average models
3. characterise the class of linear autoregressive models which possess unique attracting stationary solutions, and to apply these processes to model financial phenomena
4. reduce time series data and models to the stationary case, and to decide whether certain data sets fit a given stationary linear time series model
5. analyse vector autoregressive models
6. establish the validity of important general methods for generating random variates, to apply these methods, and analyse their efficiency