Project Overview
This project involves building demand forecasting models to predict store customer count using various statistical and machine learning methods. The goal was to decompose data trends and identify the best-fit model to optimize future demand predictions.
Key Objectives
- Calculate average return and standard deviation for Stock 1 and Stock 2.
- Determine the correlation between the two stocks.
- Develop a portfolio model with optimized weights for minimum variance.
- Visualize the efficient frontier with risk-free investment options.
Tools Used
- Microsoft Excel
- Statistical Analysis Techniques
- Exponential Smoothing Models
- Data Visualization
Download Results
Click the links below to access the Excel files containing detailed analysis and forecasting results:
Download Results