Question

Which one of the following time-series forecasting methods will generate the most accurate forecasts when demands have a consistent trend pattern?

a. Exponential smoothing method
b. Seasonal index method
c. Weighted moving average method
d. Regression

Answer 1

The most accurate forecasting method for demands with a consistent trend is regression, which excels at modeling linear relationships and interpreting trend patterns. So the correct answer is option d.

Step-by-step explanation:

The method that will generate the most accurate forecasts when demands have a consistent trend pattern is regression. Regression analysis is a statistical tool for predicting future values of a dependent variable based on the values of independent variable(s). It is particularly useful for modeling and analyzing several variables where the relationship between variables is linear and involves trend patterns.

In the scenario described, where an economist is modeling outcomes on the stock market and comparing expected points with actual points, regression will assess the strength of the trend and produce forecasts that consider the consistent pattern. The other options, such as exponential smoothing and weighted moving average, are better suited for data without a trend, while the seasonal index method is best for data with clear seasonal variations but not necessarily trends.

The weighted moving average method will generate the most accurate forecasts when demands have a consistent trend pattern. In this method, recent data points are given more weight than older data points. This allows the forecast to adapt to changing trends over time. For example, if demand for a product has been steadily increasing over the past few months, the weighted moving average method will be able to capture this trend and generate more accurate forecasts compared to other methods.

Answer 2

The most accurate forecasting method for consistent trend patterns in demand is the Regression method.

Step-by-step explanation:

When demands have a consistent trend pattern, the most accurate forecasting method would be the Regression method. Regression analysis allows for the identification and evaluation of the relationship between the dependent variable (demand) and one or more independent variables (such as time in this case). It can capture both linear and non-linear trends in the data, making it suitable for forecasting demands with consistent trends.

In the context of time-series forecasting, other methods like exponential smoothing, seasonal index, and weighted moving average are more suitable for capturing specific patterns like seasonality and short-term fluctuations. However, for consistent trend patterns, regression is the recommended method.

For example, the economist in the given scenario could apply a regression model to predict the points on the stock market index based on various factors or variables that influence the market's performance over time.