Holt's linear exponential smoothing technique for forecasting time series with trend:
A)results in separate forecasts for level (L) and trend (T).
B)is relevant only for non-linear trend cases.
C)gives equal weight to all data points employed.
D)requires the retention of a large number of data points.

Question

Quizplus · Accepted Answer

Holt's linear exponential smoothing technique involves separate forecasts for both the level (L) and trend (T) of the time series. This allows for a better prediction of future values in the presence of a trend. Therefore, option A is correct. Option B is incorrect because this technique is specifically designed for time series data with linear trends. Option C is incorrect because Holt's linear exponential smoothing does not give equal weight to all data points; it assigns higher weights to more recent data points. Option D is incorrect because this technique does not require retention of a large number of data points; it focuses on recent data and assigns higher weights to these points.

Holt's Linear Exponential Smoothing Technique for Forecasting Time Series with Trend