Member-only story
Fine Tune Sales Forecast with Prophet Regressors
This is a tutorial on how to add regressors to Prophet Forecast Model to hopefully increase forecast accuracy and reduce Mean Absolute Percentage Error (MAPE). This tutorial complements an existing tutorial — Forecast Sales Using Prophet where it adds Regressors.
To maintain the brevity of a tutorial, some of the important steps are not referenced in this tutorial. For a complete code walk-through, please refer to the Github repository referenced in the Resource section at the end of this tutorial. This tutorial was created for me as reference material, therefore the tutorial is heavy on how-to, not on algorithms.
Prerequisites
The following are prerequisites for this tutorial:
- Forecast Sales Using Prophet (https://sungkim11.medium.com/forecast-sales-using-prophet-90b6bbd18f8f)
- Data
Data
Three data sources were used for this tutorial where United Stated Census Bureau Monthly Retail Sales is used to forecast future sales and both FRED Data and OECD Data were used as Regressors data.
United States Census Bureau Monthly Retail Sales
United States Census Bureau maintains Monthly Retail Trade Report, from January 1992 to the present. This data was picked to illustrate forecasting because it has extensive historical data with the same monthly frequency. Data is available in Excel spreadsheet format at https://www.census.gov/retail/mrts/www/mrtssales92-present.xls
FRED Data: https://fred.stlouisfed.org/
FRED is economic data provided by Federal Reserve Bank of St. Louis.
- Inflation Rate: A measure of expected inflation derived from 10-Year Treasury Maturity Securities.
- CPI: Consumer Price Index for All Urban Consumers.
- M1: It consists of all money in circulation.
- M2: It consists of M1 plus savings
- Interest Rate: Federal fund rate.
OECD Data: https://data.oecd.org/leadind/composite-leading-indicator-cli.htm#indicator-chart
- Composite leading indicator (CLI)
- Business confidence index (BCI)
- Consumer confidence…
