We used ChatGPT's Advanced data analysis tool to generate index fund recommendations.

In this essay, we will describe the technology, methodology, and results.

What is ChatGPT Code Interpreter / Advanced data analysis?

ChatGPT's Advanced data analysis is a beta tool that allows the user to perform specialized data analysis and programming tasks powered by GPT-4.

Key features include:

You can upload data files (e.g. CSV, PDF, etc.) for analysis:

It can write and execute code based on your requirement:

It can create charts and graphs:

It can perform longer tasks that require more computation:

How to enable and use ChatGPT's Code Interpreter?

To enable the Advanced Data Analysis feature you need to go to the "Settings & Beta" section on ChatGPT. Once you've enabled Advanced data analysis under settings, you can use the feature by selecting it under GPT-4.

Using ChatGPT Advanced data analysis to generate an index fund recommendation to maximize a 6-month timeline.

To generate the recommendation, we used a two-step approach.

As step one, we asked ChatGPT's GPT-4 powered Advanced data analysis tool to come up with the description of a hypothetical index fund.

For this step, along with a custom prompt, we created 3 datasets with data on various economic indicators in the US including:

FED Interest Rate:

US Unemployment Rate:

US GDP Growth Rate:

We then uploaded these 3 datasets in CSV format on ChatGPT using Advanced data analysis tool along with the following prompt.

Here's the response we received:

To provide the most plausible description of the hypothetical index fund X, it's important to first understand the current economic context. To that end, I'll analyze the data files you provided on the U.S. Civilian Unemployment Rate, the Effective Federal Funds Rate, and the U.S. Real GDP Quarter-over-Quarter Growth.

I'll start by loading and examining each dataset to get an idea of the trends and current economic conditions. After that, I'll proceed to use this information to construct the characteristics of index fund X, making sure to incorporate factors like market trends, technology, and political influences that could contribute to its high expected returns by February 2024.

The datasets contain the following information:

U.S. Civilian Unemployment Rate: This dataset provides monthly unemployment rates from May 2019 to an unspecified end date. The data is broken down into categories like 'Total,' 'Men, 20 years and over,' 'Women, 20 years and over,' and also by ethnicity.

Effective Federal Funds Rate: This dataset contains daily data, most recently up to August 24, 2023. The rate is currently at 5.33%.

U.S. Real GDP QoQ Growth: This dataset has quarter-end data for real GDP growth rates. The data shows that the growth rate was 2.4% for the quarter ending on June 30, 2023.

Next, I'll visualize these datasets to better understand the trends. This will involve:

Plotting the unemployment rate to see its trend over time.

Plotting the Effective Federal Funds Rate to understand its movement.

Plotting the Real GDP Growth rate to see how it's been changing.

After understanding these trends, I'll proceed to describe the hypothetical index fund X in detail.

Based on the visualizations, we can observe the following trends:

U.S. Civilian Unemployment Rate: The graph shows fluctuations, but we don't see an alarming spike in unemployment rates. The data is inconclusive without the complete timespan, but we can assume a relatively stable job market, which would be a positive indicator for the stock market.

Effective Federal Funds Rate: The rate is at 5.33% as of late August 2023. A high federal funds rate typically dampens investment and consumer spending but could indicate the Federal Reserve's confidence in a strong economy. In the context of an index fund, higher interest rates could impact companies differently, but they are generally seen as negative for high-growth tech stocks and positive for financials.

U.S. Real GDP QoQ Growth: We see fluctuations in growth, but the overall trend does not indicate a recession or booming economy. The most recent quarter shows a 2.4% growth, which is modest.

Hypothetical Index Fund X

Given the economic backdrop, let's construct our hypothetical index fund, which we'll call the "FutureTech Financial Stability Index Fund (FTFSIF)".

Focus

The FTFSIF focuses on a balanced mix of technology and financial stocks. The aim is to benefit from technological advancements while hedging against high interest rates through inclusion of financial stocks.

Composition

60% Technology Stocks: Companies in AI, cybersecurity, cloud computing, and semiconductor industries.

40% Financial Stocks: Major banks, insurance companies, and fintech startups.

Underlying Stocks

Technology: Apple, Amazon, NVIDIA, Salesforce, and smaller startups focused on AI and cybersecurity.

Financial: JPMorgan, Goldman Sachs, Berkshire Hathaway, and fintech firms like Square and Adyen.

Past Price History

1-Year Return: 35%

3-Year Return: 90%

Market, Macro, Micro, Political, Statistical, Technological Trends

Market: Bullish on tech and financials due to economic stability.

Macro: Modest GDP growth and high federal funds rate favor financials.

Micro: Individual companies in the fund have strong earnings forecasts.

Political: No major policy changes expected that could adversely affect tech or financial sectors.

Statistical: Historical volatility is lower than market average due to diversification.

Technological: Continued growth expected in AI, cybersecurity, and cloud computing sectors.

Projected Return by Feb 2024

Given the economic factors and the fund's focus, a 20% return is expected by February 2024.

This fund is built to capitalize on current economic conditions and expected trends, making it a strong candidate for high returns by February 2024.

As you can see, this first step generated the hypothetical index fund "FutureTech Financial Stability Index Fund (FTFSIF)" which we can use in the next step.

For step 2, we started a separate GPT-4 conversation on ChatGPT. We used the description we generated to find the closest match in the real world.

Here's the response we received:

Finding a real-world index fund that matches the exact criteria of the hypothetical "FutureTech Financial Stability Index Fund (FTFSIF)" is a challenging task. This is because the investment landscape is vast and specialized funds may not precisely align with these detailed parameters.

Background Context

Index funds usually track a market index like the S&P 500, rather than being actively managed to target specific sectors or types of stocks. The hypothetical fund described aims for a very specific, almost actively managed approach, with a targeted allocation of stocks from specific sectors (60% Tech and 40% Financials) along with other specific conditions like past returns and volatility characteristics. This makes it more similar to a thematic or sector ETF rather than a traditional index fund.

Assumptions

The fund needs to be traded on the NYSE or NASDAQ.
The focus is on technology and financial stocks.
Past and projected returns should align closely with the hypothetical model.
Step-by-Step Thinking

Type of Fund: First, we need to look for funds that are more thematic or sector-based rather than broadly diversified index funds.

Composition: A 60-40 split between technology and financial stocks would be ideal, but even funds focusing on both these sectors might suffice. Individual stock components should align closely with the ones mentioned in the description.

Returns: The fund should have strong historical returns that roughly align with the 1-Year and 3-Year returns mentioned.

Other Factors: Market, macro, and micro trends should align, and the fund should have a lower-than-average historical volatility, as per the hypothetical description.

Result

Upon researching, there doesn't appear to be a single index fund that perfectly matches all the given criteria. However, one could potentially create a portfolio mix using separate technology and financial index funds to simulate the hypothetical fund. Here are some examples:

Technology Funds

Invesco QQQ Trust (QQQ)

Technology Select Sector SPDR Fund (XLK)

Financial Funds

Financial Select Sector SPDR Fund (XLF)

iShares U.S. Financials ETF (IYF)

Note: The above funds do not perfectly match the description. For instance, QQQ has a broader focus than just technology, and XLK may not include all the types of technology companies listed in the hypothetical fund. Similarly, financial sector funds may include a broader array of financial companies than described.

Conclusion

While a perfect match for the hypothetical index fund does not seem to exist, an investor could approximate its behavior by creating a custom blend of existing technology and financial sector funds. This would entail purchasing these funds in a 60-40 ratio and periodically rebalancing the portfolio to maintain this ratio. Note that this strategy will not perfectly replicate the hypothetical fund but may provide a similar risk/return profile.

Since the model came up with 4 different index funds, we asked it to score the 4 index funds to find the best match.

Here's the response we received:

Certainly, assigning a match score can help in comparing how closely these funds align with the hypothetical "FutureTech Financial Stability Index Fund (FTFSIF)" based on certain criteria.

Criteria and Scoring Methodology

Focus on Sector (Technology or Financials): A score of 0-10, with 10 indicating a perfect alignment with the target sectors (technology and financials).

Stock Composition: A score of 0-10 to reflect how closely the individual stock holdings match those specified in the hypothetical fund description.

Historical Returns: A score of 0-10 for how closely the fund's 1-Year and 3-Year returns match the hypothetical fund’s.

Risk Profile: A score of 0-10 based on how closely the fund’s historical volatility aligns with the lower-than-average historical volatility mentioned for the hypothetical fund.

Projected Future Returns: Since predicting future returns is speculative, this criteria will be left out.

Fund Scoring

I'll apply the scoring criteria to the four funds mentioned.

Invesco QQQ Trust (QQQ)

Focus: 8 (Primarily tech, but also includes some non-tech companies)

Composition: 6 (Includes major tech stocks like Apple and Amazon, but not much in financials)

Historical Returns: 8 (Known for strong returns, although exact figures would need to be checked)

Risk Profile: 7 (Generally lower volatility than broader market due to large-cap focus)Total Score: 29

Technology Select Sector SPDR Fund (XLK)

Focus: 9 (Exclusively tech)

Composition: 7 (Includes many of the specified tech stocks)

Historical Returns: 8 (Strong but need to verify exact figures)

Risk Profile: 7 (Similar to QQQ)Total Score: 31

Financial Select Sector SPDR Fund (XLF)

Focus: 9 (Exclusively financials)

Composition: 6 (Includes major financial stocks like JPMorgan but lacks fintech)

Historical Returns: 6 (Variable depending on economic conditions)

Risk Profile: 5 (Higher volatility compared to broader market)Total Score: 26

iShares U.S. Financials ETF (IYF)

Focus: 9 (Exclusively financials)

Composition: 7 (Broader array of financial stocks including major banks)

Historical Returns: 6 (Variable like XLF)

Risk Profile: 5 (Similar to XLF)Total Score: 27

Conclusion

Based on the scoring, the Technology Select Sector SPDR Fund (XLK) has the highest total score of 31. It exclusively focuses on technology stocks and includes many of the large-cap tech companies specified in the hypothetical fund. While it does not include financial stocks, it aligns well with the technology side of the hypothetical fund’s composition, offering strong historical returns and a lower-than-average risk profile.

What is the Technology Select Sector SPDR Fund?

The Technology Select Sector SPDR® Fund aims to replicate the performance of the Technology Select Sector Index, which is designed to represent the technology segment of the S&P 500 Index. The fund focuses on providing exposure to various technology-related industries like hardware, software, semiconductors, and IT services, among others. It allows investors to take more targeted strategic or tactical positions compared to traditional investment styles. The companies in the index are selected based on general industry classifications within the S&P 500.

Click to see more details involving The Technology Select Sector SPDR® Fund