Exam 17: Time-Series Analysis and Forecasting

The following linear trend was estimated using a time series regression with the origin in the year 2000. ŷ = 76.80 + 3.14t. Which of the following is the forecast for the year 2013?

A time series regression model using quarterly time periods will only use three quarters as the indicator variables.

The time-series component that reflects a long-term, relatively smooth pattern or direction exhibited by a time series over a long time period is called trend.

A company selling swimming goggles wants to analyze the company's Australian sales figure. Describe the 4 components of the line graph of Swimming goggle quarterly sales (in $000's) given below.

In an exponentially smoothed time series, the smoothing constant w is chosen on the basis of how much smoothing is required. In general, a small value of w such as 0.1 results in a great deal of smoothing, while a large value of w, such as 0.9, results in very little smoothing.

The effect that business recessions and prosperity have on time-series values is an example of the disaster component of a time series.

One application of seasonal indexes is to remove the seasonal variation in a time series. The process is called deseasonalising, and the result is called a seasonally adjusted time series.

Given the following time series, compute the seasonal (quarterly) indexes, using the four-quarter centred moving averages. Quarter 2011 2012 2013 2014 2015 1 62 48 50 43 57 2 51 45 46 39 32 3 53 44 46 37 31 4 46 37 42 32 29

Which of the following models might be appropriate to describe a new product that has experienced a rapid early growth rate followed by the inevitable levelling-off?

Forecasts based on trend and seasonality are generated by:

If data for a time-series analysis are collected on a monthly basis only, which component of the time series may be ignored?

For which of the following values of the smoothing constant w will the smoothed series catch up most quickly whenever the original time series changes direction?

a. Apply exponential smoothing with w = 0.1 and w = 0.8 to help detect the components of the following time series. Period t yt 1 40 2 45 3 44 4 47 5 48 6 50 7 52 8 51 9 48 10 47 b. Draw the time series and the two sets of exponentially smoothed values. Does there appear to be a trend component in the time series?

The following seasonal indexes and trend line were computed from five years of quarterly sales data. Trend line: ŷt = 325 + 18.5t, t = 1, 2, 3, …20. Quarter Seasonal index 1 1.35 2 1.22 3 0.88 4 0.55 Forecast the sales for the next four quarters.

Of the four components of the multiplicative time-series model, the ratio of the time series to the moving average isolates the:

In measuring the cyclical effect of a time series, cycles need to be isolated. The measure we use to identify cyclical variation is the:

Use exponential smoothing, with w = 0.23 to forecast the next value of the time series below. t 1 20 2 16 3 24 4 25 5 22 6 21

Smoothing time-series data by the moving average method or exponential smoothing method is an attempt to remove the effect of the:

The most commonly used measures of forecast accuracy are the mean absolute deviation (MAD) and the sum of squares for forecast error (SSE).

The trend line ŷt = 125 + 2t and seasonal indexes shown below were computed from 10 years of quarterly data. Forecast the values for the next four quarters. Quarter S 1 0.6 2 1.3 3 1.6 4 0.5