Investment Behavior Analysis Using Excel

This project focuses on uncovering patterns and insights in financial investment behavior using Exploratory Data Analysis (EDA). The analysis involved 4 levels comprising of 10 tasks.

Table of Contents

• Project Overview
• Tools & Techniques Used
• Levels of Analysis
• Insights
• Conclusion
• Author

Project Overview

This project investigates:

• Gender distribution
• Investment preferences
• Savings objectives
• Correlations between key factors

We explore these areas using descriptive statistics, visualizations, and correlation analysis.

Tools & Techniques Used

Tools:

• Excel: Data cleaning, statistical analysis, visualizations, and correlation analysis using functions like COUNTA(), COUNTIF(), SUMPRODUCT(), and CORREL() functions.
• Power Query: Data type identification and transformation.
• Data Analysis Toolpak (Excel Add-In): Correlation analysis & descriptive statistics.

Techniques:

• Descriptive Statistics: Used for analyzing central tendencies (mean, median) and variability (standard deviation).
• Visualization: Clustered bar charts, pie charts, and other visual aids to highlight patterns.
• Correlation Analysis: Explored relationships between variables like age, investment duration, and return expectations.
• Weighted Averages: Applied to calculate average investment durations.

Levels of Analysis

1. Beginner: Dataset structure and gender distribution.
2. Intermediate: Descriptive statistics and investment avenue preferences.
3. Advanced: Reasons for investment choices and savings objectives.
4. Expert: Investment information sources, durations, expectations, and correlations.

Insights

• Trusted Sources: Financial consultants are most relied upon.
• Goals: Wealth creation (80%) dominates over future savings (15%).
• Popular Avenues: PPF and Fixed Deposits.
• Duration: 1-5 years with a 3-year average.
• Returns: Most participants target a 20%-30% range.

Basic Statistics of the investment avenues:

Correlation Analysis using Data analysis tool Pak:

Investment duration preferences of the participants:

Most Preferred Investment:

Reasons for investment and their gender distribution:

Conclusion

• In conclusion, this project provided valuable insights into the financial preferences and behaviors of participants.
• By analyzing factors such as trusted sources for investment advice, preferred investment duration, and return expectations, we identified key trends such as a strong focus on retirement savings, short to mid term investments, and a preference for secure investment avenues like PPF and Fixed Deposits.
• The correlation analysis further helped uncover relationships between age, investment duration, and return expectations, providing a deeper understanding of how participants approach their financial goals.
• Overall, this project emphasized the importance of data analysis in uncovering meaningful patterns to guide financial decision-making

Author

Deepthi G Das
📧 deepthigdas@243@gmail.com
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