Business Forecasting Topic 1

Question 1

why forecast?

Answer 1

• uncertainty in future
• mitigate impact of uncertainty

Question 2

poor forecasts lead to
3 consequences

Answer 2

• too much stock
• unnecessarily poor service
• over or under

Question 3

Finding a forecast

Answer 3

• underlying pattern in past data
• not explicit

Question 4

components of observations

Answer 4

1. systematic element (signal)
2. random element (noise)

Question 5

Actual value formulae

Answer 5

signal + noise

Question 6

noise in forecasts

Answer 6

• irregular, random events
• filter out noise
• isolate systematic pattern (forecast future development)

Question 7

Quantitative forecasting techniques

Answer 7

• assume of continuity (past pattern in signal = continue to future)

1. time series extrapolation
2. explanatory

Question 8

assumption of continuity

Answer 8

use quantitative methods when….
- sufficient past data
- info quantified
- valid assumption of continuity

Question 9

time series forecasts

Answer 9

univariate method
- analyse and extrapolate past pattern
- no past data (explanatory variables) - expensive
- no idea what influences variable or explaining behaviour
- no expertise to have elaborate model, not justified by extra accuracy “might” yield
- cheap and simple

Question 10

explanatory forecasts

Answer 10

linking variable with other variables (independent & dependent variables)

• factor explains past through relationships with other variable

Question 11

judgmental forecasts

Answer 11

• subjective using expertise

1- little/no relevant past data
2- forecaster knowledgable about unique event

• most widely used

Question 12

five ways of combining forecasts from different methods

Answer 12

• statistical and judgment
  1. apply judgment adj to stats forecasts
  2. simple av forecast from diff methods
  3. weighted av of forcast from diff methods
  4. bayesian - judgement estimate incorporated in stats
  5. rule based - weighted av from methods used weights based on particular conditions at time of forecast

Question 13

Basic Steps in the forecasting task

Answer 13

1. Define the problem
2. Gather information
3. Exploratory data analysis
4. Choose method
5. Evaluate chosen forecasting methods

Question 14

Explanatory data analysis (preliminary)

Answer 14

graph variable
- consistency of patterns
- trend and seasonality
- economic cycles/outliers are present

Question 15

Overfitting

Answer 15

model fits past data well doesn’t guarantee accurate forecasts

• method is seeing systematic patterns in the noise

Question 16

two ways of evaluating methods

Answer 16

fitting period = obtain model
hold out periods = tests accuracy “out of sample” “hold out”

Question 17

four ways of presenting forecasts

Answer 17

1. Point forecast (single figure)
2. Prediction interval (indication of confidence)
3. Fan charts/diagram (several prediction intervals at once)
4. Density forecasts (normal probability distribution - large sample)

Question 18

self negating forecasts

Answer 18

• forecast deliberate to scare people into action (change world)
  e.g. forecast loss = act as stimulus = behaviour change = avoid
  e.g opinion poll based = political party win = supporters no vote = rival wins