BAN430 Forecasting
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6 Judgemental forecast
Judgmental adjustment
Course overview
1 R and Rstudio
Installing R and Rstudio
Recap R
2 Time series basics
What is time series data
Stationarity
3 Adjustments and decomposition
Adjustments and transformations
Calender adjustments
Population adjustment
Inflation adjustment
Mathematical Transformations
Time series components and Seasonal adjustment
Moving averages and Decomposition
Moving averages
Classical decomposition
Statistics agencies: X11 and SEATS
STL: Seasonal and Trend decomposition using Loess
Exercises
4 Time series features
Time series features
Features
Exploring Australian tourism example
Exercises
5 Forecasters toolbox
Forecasters toolbox
6 Judgemental forecast
The delphi method
Forecasting by analogy
Other methods
Judgmental adjustment
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
Labs
Time series graphics
Time series decomposition
Workshops
tsibble, graphics and decomposition
Bergen traffic forecast
Electricity prices
Walmart’s Weekly Sales
Appendix
Data
References
6 Judgemental forecast
Judgmental adjustment
Judgmental adjustment
Other methods
Regression models