Quantitiative Techniques (2)

Question 1

What is trend?

Answer 1

The underlying long-term movement over time in values of the data recorded

Question 2

How can trend be found?

Answer 2

Using moving averages

Question 3

What are seasonal variations?

Answer 3

Short-term fluctuations in recorded values, due to deifferent circumstances that affect results at different times of the day or week or year or any regularly repeating pattern

Question 4

What are cyclical variations?

Answer 4

Recurring patterns over a longer period of time, not generally of a fixed nature

Question 5

What are random variations?

Answer 5

Irregular varations due to rare/chance occurences

Question 6

What is the additive model?

Answer 6

Components are assumed to add together to give TS

Question 7

When is the additive model valid?

Answer 7

If the components are independent

Question 8

What is the multiplicative model?

Answer 8

Components are assumed to multiply together to give TS

Question 9

When is the multiplicative model useful?

Answer 9

When trend is increasing or decreasing over time because seasonal variation is likely to be increasing or decreasing

Question 10

What is the use of moving averages?

Answer 10

Main method for calculating a trend from a time series

Question 11

What does moving averages work?

Answer 11

Averages all of the results of a fixed number of periods and relates to the mid-point of the overall period

Question 12

How do most appropriate number of periods for a moving average depend on?

Answer 12

Circumstances and nature of the time series

Question 13

Sum of seasonal variations and additive time series model?

Answer 13

Sum of seasonal variations over the period must equal zero

Question 14

Sum of seasonal variations and multiplicative time series model?

Answer 14

Sum of seasonal variations must equal the number of periods over which seasonality occurs prior to repeat (e.g. quartely equals 4)

Question 15

Advantages of time series analysis (Trend lines)

Answer 15

Trend lines can be reviewed and assessed after each period for reliability, possibly leading to improved forecasts with experience

Question 16

Advantages of time series analysis (Time series)

Answer 16

TIme series components and theory is relatively easy for non-financial managers to udnerstand

Question 17

Disadvantages of time series analysis (Unreliable)

Answer 17

Further into future, the more unreliable the forecast is likely to be

Question 18

Disadvantages of time series analysis (Less data)

Answer 18

The less data available on which to base the forecast, the less reliable the forecast

Question 19

Disadvantages of time series analysis (Guarantee)

Answer 19

Pattern of trend and seasonal variation cannot be guaranteed to continue

Question 20

Disadvantages of time series analysis (Pattern)

Answer 20

Pattern of trend and seasonal variation cannot be guaranteed to continue

Question 21

Disadvantages of time series analysis (random variations)

Answer 21

There is always the danger of random variations upsetting the pattern of trend and seasonal variations