BAN430 Forecasting
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10 Practical forecasting issues
Practicle forecasting issues
Course overview
1 R and Rstudio
Installing R and Rstudio
Recap R
2 Time series basics
Time series basics
3 Adjustments and decomposition
Transformations and adjustments
Moving averages and Decomposition
Exercises
4 Time series features
Time series features
Features
Exploring Australian tourism example
Exercises
5 Forecasters toolbox
Forecasters toolbox
6 Judgemental forecast
Judgemental forecast
7 Regression models
Regression models
8 ARIMA models
ARIMA models
9 Volatility forecasting
ARCH models
GARCH models
Forecasting with GARCH
Forecasting volatility in R
10 Practical forecasting issues
Practicle forecasting issues
Workshops
tsibble, graphics and decomposition
Bergen traffic forecast
Electricity prices
Walmart’s Weekly Sales
Appendix
Data
References
Practicle forecasting issues
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Forecasting volatility in R
tsibble, graphics and decomposition