Top 10 AI Stocks: 5-Year Overview

Project Summary: AI Companies vs. S&P 500 and Dow Jones

This project examined the performance of top AI companies in comparison to the S&P 500 and Dow Jones indices over the last five years (2019-2024). We analyzed daily and cumulative returns, as well as volatility (risk), to evaluate profitability and risk associated with each investment option.

Link to the PowerPoint Presentation with All Plots

https://docs.google.com/presentation/d/1MZZu5sHH3Ji32wZJKGbBLBBZm3hhA7Cn/edit?usp=drive_web&ouid=111933235987222785321&rtpof=true

Data Sources

• Top 10 AI companies Kaggle dataset (1990 through present) as selected by Forbes
• S&P 500 and Dow Jones index ETF funds gathered through alphavantage.co API

Research Questions and Hypotheses

Question

Does the growth of AI stocks over the last 5 years indicate a more profitable and safer investment compared to the S&P 500 and Dow Jones indices?

Hypotheses

• Null Hypothesis (H0): There is no significant difference between the returns of AI stocks and market indices from 2019 to 2024.
• Alternative Hypothesis (H1): AI stocks show a significant difference in returns compared to the market indices during the same period.

Background and Key Metrics

We acknowledge that stock analysis is a multifaceted field influenced by various factors. This project focuses on average stock prices, daily and cumulative returns, and volatility (standard deviation) to assess stock performance. We categorized risk based on volatility as follows:

• Low Risk: Volatility less than 10%
• Medium Risk: Volatility between 10% and 20%
• High Risk: Volatility greater than 20%

Statistical Analysis and Findings

Plots

• Bar and Line Graphs: Displayed the average cumulative and daily returns for AI companies and indices.
• Volatility Analysis: Showed daily returns with error bars indicating volatility.
• Violin Plots: Illustrated the distribution of returns to support ANOVA results.

Below some of the plots. Please find more graphs in the presenation (see the link above).

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Statistical Testing

• Repeated Measures ANOVA: Found no significant differences between AI companies and indices, failing to reject the null hypothesis.
• Post-hoc Pairwise T-tests: Identified significant differences between individual companies (e.g., Nvidia and Amazon).

Conclusions

The analysis indicates that AI companies, while having periods of high returns, do not consistently outperform or exhibit lower risk than the S&P 500 and Dow Jones indices. The overall market performance of AI stocks does not significantly differ from these indices, leading to the conclusion that investments in these AI companies are comparable in risk and profitability to traditional market index investments.

Additional Observations

• Average Closing Prices: AI stock prices fluctuated more than those of the indices, suggesting higher volatility and potentially higher risk for conservative investors.
• This comprehensive study underscores that while specific AI companies may occasionally outperform, as a group they align closely with broader market behaviors.
• Notably, eight of the ten AI companies analyzed are listed in the S&P 500, with the exception of those represented by the tickers "PATH" and "AI." Addtional information of the materials included in this project

File Structure of the Repository

Project Partners:

• Nathan Sheibley
• Olga Sabrina Linden
• Melissa Glover
• Krissy Knight
• Dante Parcon
• Andrea Moncada