In Oct/2024 I asked ChatGPT for a portfolio that could survive a messy world (original post here). I expected the Israel–Palestine conflict (on top of Russia–Ukraine) to be the main driver.
Fourteen months later, the conflicts are still there, but the volatility came from a different menu: U.S. surprises, Trump’s tariff war, a U.S. strike on an Iranian nuclear facility, and most recently Maduro’s capture.
This post is my promised check-in: I re-ran the original constraints using a 2024 model snapshot, converted the answer into a real ETF portfolio, and measured what happened.
The portfolio setup
The original post suggested a broad allocation. To make it testable, I re-ran a prompt in the old GPT-4o model…
In Oct/2024 I asked ChatGPT for a portfolio that could survive a messy world (original post here). I expected the Israel–Palestine conflict (on top of Russia–Ukraine) to be the main driver.
Fourteen months later, the conflicts are still there, but the volatility came from a different menu: U.S. surprises, Trump’s tariff war, a U.S. strike on an Iranian nuclear facility, and most recently Maduro’s capture.
This post is my promised check-in: I re-ran the original constraints using a 2024 model snapshot, converted the answer into a real ETF portfolio, and measured what happened.
The portfolio setup
The original post suggested a broad allocation. To make it testable, I re-ran a prompt in the old GPT-4o model (via OpenAI’s API, specifically gpt-4o-2024-08-06 to avoid lookahead bias) to generate a concrete, investable portfolio, using the exact constraints from that post.
Construct a portfolio of stock indices, US bonds, corporate bond indices, and commodities, adhering to the following percentages:
50% Equities: Diversify across geographies and sectors (some growth-oriented, some defensive).
30% Bonds: Split between safe-haven government bonds and investment-grade corporate bonds.
20% Commodities & Alternative Investments: This portion can include gold, oil, and possibly some real estate or infrastructure investments that are less correlated with traditional assets.
Suggest only assets accessible to an individual investor via a US investment account.
Here’s the generated response:
Creating a diversified portfolio as per your specifications involves selecting specific ETFs and index funds that are accessible to retail investors. Here’s a suggested portfolio:
50% Equities
US Equities (25%)
- SPDR S&P 500 ETF Trust (SPY): Covers large-cap U.S. equities.
International Equities (15%)
- iShares MSCI ACWI ex U.S. ETF (ACWX): Provides exposure to large and mid-cap stocks outside the U.S.
Emerging Markets (10%)
- Vanguard FTSE Emerging Markets ETF (VWO): Targets growth-potential markets.
30% Bonds
US Government Bonds (15%)
- iShares 7-10 Year Treasury Bond ETF (IEF): Focuses on U.S. Treasury bonds, providing a safe-haven investment.
Corporate Bonds (15%)
- iShares iBoxx $ Investment Grade Corporate Bond ETF (LQD): Offers exposure to investment-grade U.S. corporate bonds.
20% Commodities & Alternative Investments
Gold (10%)
- SPDR Gold Trust (GLD): Direct exposure to gold prices.
Oil (5%)
- United States Oil Fund (USO): Tracks the daily price movements of West Texas Intermediate (WTI) light, sweet crude oil.
Real Estate & Infrastructure (5%)
- Vanguard Real Estate ETF (VNQ): Provides exposure to U.S. real estate investment trusts (REITs).
Considerations
- Diversification: The selection covers multiple geographies, sectors, and asset classes, reducing risk through diversification.
- Accessibility: All assets are available through major U.S. brokerages.
- Liquidity: ETFs and index funds offer liquidity, making it easier to enter and exit positions.
- Risk Tolerance: Adjust weights as needed based on individual risk tolerance and investment horizon.
Before investing, consider consulting with a financial advisor to tailor the portfolio to your personal financial situation and goals.
This gave me a realistic, investable snapshot of “what ChatGPT would have done” at the time.
The results (Oct 4, 2024 → Jan 27, 2026)
A couple of days ago I pulled the adjusted prices (dividends, splits, capital gains) from Yahoo Finance (e.g., GLD history) and calculated the ROI for each sleeve.
| Asset | Weight | 2024-10-04 | 2026-01-27 | ROI |
|---|---|---|---|---|
| SPDR S&P 500 ETF Trust (SPY) | 25% | 564.43 | 695.49 | 23.22% |
| iShares MSCI ACWI ex U.S. ETF (ACWX) | 15% | 54.59 | 71.97 | 31.84% |
| Vanguard FTSE Emerging Markets ETF (VWO) | 10% | 46.56 | 57.64 | 23.80% |
| iShares 7-10 Year Treasury Bond ETF (IEF) | 15% | 92.01 | 95.98 | 4.31% |
| iShares iBoxx $ Investment Grade Corporate Bond ETF (LQD) | 15% | 105.48 | 110.81 | 5.05% |
| SPDR Gold Trust (GLD) | 10% | 245.00 | 476.10 | 94.33% |
| United States Oil Fund (USO) | 5% | 76.35 | 75.66 | -0.90% |
| Vanguard Real Estate ETF (VNQ) | 5% | 90.63 | 90.39 | -0.26% |
Portfolio result: +23.74% over 14 months. Not bad.
Closing thoughts
Net result: the portfolio held up. Most of it came from a surprisingly good gold run, with stocks doing their job and everything else mostly hovering. That’s encouraging, since diversification did its job, and also a warning, because one lucky ingredient can dominate the outcome.
So: would you trust an AI to build your portfolio, or are you already using it (even if just as a second opinion)?