Understanding the Time-Series Forecasting Hierarchy: Methods, Trends, and Seasonality

Understanding the Time-Series Forecasting Hierarchy

Forecasting is essential in numerous fields such as finance, economics, supply chain, and weather prediction. Time-series forecasting focuses on analyzing data collected over time to predict future values. Choosing the right forecasting method depends on whether your data shows a level, trend, or seasonality.
-Level: The baseline value for the series.
-Trend: The direction and rate of change over time.
-Seasonality: Regular, periodic fluctuations.

Method	Level	Trend	Seasonality
Simple Moving Average	✓	Double Moving Avg	✗
Weighted Moving Average	✓	✗	✗
Simple Exponential Smoothing	✓	✗	✗
Double Exponential (Holt's)	✓	✓	✗
Winter’s Method	✓	✓	✓