Asset Allocation
| Position | Category/Sector | Target Weight |
|---|---|---|
GLD SPDR Gold Shares | Gold, Precious Metals | 15% |
TECL Direxion Daily Technology Bull 3X Shares | Leveraged Equities, Technology Equities | 15% |
NVDA NVIDIA Corporation | Technology | 15% |
TPL Texas Pacific Land Corporation | Energy | 15% |
HESAY Hermes International SA | Consumer Cyclical | 15% |
PGR The Progressive Corporation | Financial Services | 15% |
WM Waste Management, Inc. | Industrials | 10% |
Find the right asset allocation for Chatgpt O3 pro 6月12
Add portfolio to the optimizer to find optimal allocations for your target — whether that's maximizing returns, minimizing drawdowns, or balancing risk across holdings.
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Performance Chart
The chart shows the growth of an initial investment of $10,000 in Chatgpt O3 pro 6月12, comparing it to the performance of the S&P 500 index or another benchmark. All prices have been adjusted for splits and dividends. The portfolio is rebalanced Every 3 months.
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Returns By Period
As of Jun 13, 2026, the Chatgpt O3 pro 6月12 returned 31.72% Year-To-Date and 42.27% of annualized return in the last 10 years.
| Position | 1D | 1M | YTD | 6M | 1Y | 3Y* | 5Y* | 10Y* |
|---|---|---|---|---|---|---|---|---|
Benchmark S&P 500 Index | 1.65% | 1.97% | 10.35% | 10.82% | 26.39% | 19.66% | 12.33% | 13.81% |
Portfolio Chatgpt O3 pro 6月12 | 4.14% | 6.05% | 31.72% | 32.93% | 44.35% | 45.03% | 36.39% | 42.27% |
| Portfolio components: | ||||||||
GLD SPDR Gold Shares | 2.59% | -4.97% | 0.06% | 0.19% | 25.38% | 29.73% | 18.31% | 12.33% |
HESAY Hermes International SA | 1.42% | 9.10% | -18.99% | -20.48% | -23.55% | -1.78% | 7.50% | 19.32% |
NVDA NVIDIA Corporation | 3.54% | -5.60% | 14.05% | 20.66% | 49.84% | 70.84% | 64.29% | 68.59% |
PGR The Progressive Corporation | 0.19% | 1.89% | -4.91% | -8.39% | -19.09% | 19.66% | 19.62% | 23.78% |
TECL Direxion Daily Technology Bull 3X Shares | 11.01% | 22.64% | 103.81% | 109.85% | 222.44% | 68.74% | 39.49% | 53.63% |
TPL Texas Pacific Land Corporation | -4.26% | -5.67% | 26.65% | 29.97% | -2.18% | 35.41% | 17.26% | 35.75% |
WM Waste Management, Inc. | -1.14% | -0.88% | -0.44% | 0.20% | -6.80% | 11.24% | 10.90% | 15.28% |
Monthly Returns
Based on dividend-adjusted daily data since Aug 28, 2009, Chatgpt O3 pro 6月12's average daily return is +0.13%, while the average monthly return is +2.64%. At this rate, an investment would double in approximately 2.2 years.
Historically, 66% of months were positive and 34% were negative. The best month was Apr 2020 with a return of +18.8%, while the worst month was Mar 2020 at -14.1%. The longest winning streak lasted 13 consecutive months, and the longest losing streak was 5 months.
On a daily basis, Chatgpt O3 pro 6月12 closed higher 57% of trading days. The best single day was Oct 7, 2010 with a return of +13.6%, while the worst single day was Mar 16, 2020 at -11.0%.
| Jan | Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec | Total | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2026 | 4.34% | 8.61% | -9.36% | 12.82% | 14.21% | -0.47% | 31.72% | ||||||
| 2025 | 5.64% | 4.20% | -5.68% | 0.31% | 6.49% | 5.94% | -0.72% | -0.25% | 6.58% | 1.51% | -3.33% | 1.53% | 23.54% |
| 2024 | 5.44% | 12.90% | 7.41% | -4.02% | 8.21% | 8.08% | -0.22% | 5.38% | 2.41% | 4.27% | 10.79% | -9.72% | 61.18% |
| 2023 | 11.60% | 1.25% | 12.60% | -1.49% | 5.74% | 7.04% | 4.05% | 3.14% | -6.95% | 3.26% | 9.82% | 2.88% | 65.28% |
| 2022 | -10.27% | -1.58% | 7.82% | -12.17% | 2.08% | -8.13% | 16.28% | -6.29% | -11.43% | 11.72% | 14.09% | -8.81% | -12.02% |
| 2021 | -1.35% | 7.24% | 11.93% | 7.76% | 2.71% | 8.15% | 1.52% | 2.73% | -8.29% | 12.13% | 8.54% | 1.08% | 66.77% |
Benchmark Metrics
Chatgpt O3 pro 6月12 has an annualized alpha of 17.81%, beta of 1.16, and R2 of 0.75 versus S&P 500 Index. Calculated based on daily prices since August 28, 2009.
- This portfolio captured 183.32% of S&P 500 Index gains but only 92.26% of its losses - a favorable profile for investors.
- This portfolio generated an annualized alpha of 17.81% versus S&P 500 Index - delivering returns beyond what market exposure alone would predict.
- Alpha
- 17.81%
- Beta
- 1.16
- R²
- 0.75
- Upside Capture
- 183.32%
- Downside Capture
- 92.26%
Expense Ratio
Chatgpt O3 pro 6月12 has an expense ratio of 0.20%, which is considered low. Below, you can find the expense ratios of the portfolio's funds side by side and easily compare their relative costs.
Return for Risk
Risk / Return Rank
Chatgpt O3 pro 6月12 ranks 36 for risk / return — below 36% of Portfolios on our site. The returns aren't fully compensating for the risk involved. This isn't necessarily a dealbreaker, but factor it into your decision — especially if you're risk-averse.
Return / Risk — by metrics
The table below presents risk-adjusted performance metrics for Chatgpt O3 pro 6月12 and compares them with S&P 500 Index.
Values are calculated on a 1-year rolling basis and updated daily. Risk-adjusted metrics are more stable over longer periods — use the period switch above to explore them.
| Portfolio | Benchmark | Difference | |
|---|---|---|---|
| Sharpe ratioReturn per unit of total volatility | 1.97 | 2.14 | -0.17 |
| Sortino ratioReturn per unit of downside risk | 2.51 | 2.89 | -0.38 |
| Omega ratioGain probability vs. loss probability | 1.35 | 1.39 | -0.04 |
| Calmar ratioReturn relative to maximum drawdown | 3.32 | 2.91 | +0.40 |
| Martin ratioReturn relative to average drawdown | 12.29 | 13.08 | -0.79 |
How much return does each position deliver for the risk it carries? Higher values mean better reward for the risk taken.
| Position | Risk / Return Rank | Sharpe ratio | Sortino ratio | Omega ratio | Calmar ratio | Martin ratio |
|---|---|---|---|---|---|---|
GLD SPDR Gold Shares | 27 | 0.93 | 1.30 | 1.19 | 1.04 | 2.97 |
HESAY Hermes International SA | 14 | -0.78 | -0.98 | 0.89 | -0.65 | -1.16 |
NVDA NVIDIA Corporation | 78 | 1.43 | 2.00 | 1.24 | 2.48 | 5.89 |
PGR The Progressive Corporation | 11 | -0.85 | -1.10 | 0.87 | -0.80 | -1.23 |
TECL Direxion Daily Technology Bull 3X Shares | 83 | 3.29 | 3.03 | 1.41 | 4.81 | 13.42 |
TPL Texas Pacific Land Corporation | 39 | -0.05 | 0.27 | 1.03 | -0.07 | -0.14 |
WM Waste Management, Inc. | 25 | -0.36 | -0.38 | 0.95 | -0.41 | -0.90 |
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Dividends
Dividend yield
Chatgpt O3 pro 6月12 provided a 1.98% dividend yield over the last twelve months.
| Position | TTM | 2025 | 2024 | 2023 | 2022 | 2021 | 2020 | 2019 | 2018 | 2017 | 2016 | 2015 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Portfolio | 1.98% | 1.84% | 0.64% | 0.47% | 0.55% | 1.31% | 1.08% | 0.98% | 0.85% | 0.72% | 0.96% | 1.21% |
| Portfolio components: | ||||||||||||
GLD SPDR Gold Shares | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% |
HESAY Hermes International SA | 1.05% | 1.18% | 1.13% | 0.67% | 0.57% | 0.31% | 0.46% | 0.68% | 0.91% | 1.55% | 1.81% | 2.54% |
NVDA NVIDIA Corporation | 0.13% | 0.02% | 0.03% | 0.03% | 0.11% | 0.05% | 0.12% | 0.27% | 0.46% | 0.29% | 0.45% | 1.20% |
PGR The Progressive Corporation | 6.83% | 2.15% | 0.48% | 0.25% | 0.31% | 6.23% | 2.68% | 3.89% | 1.86% | 1.21% | 2.50% | 2.16% |
TECL Direxion Daily Technology Bull 3X Shares | 3.49% | 7.19% | 0.29% | 0.28% | 0.22% | 0.32% | 0.52% | 0.25% | 0.47% | 0.10% | 0.00% | 0.00% |
TPL Texas Pacific Land Corporation | 0.62% | 0.74% | 1.37% | 0.83% | 1.37% | 0.88% | 2.20% | 0.22% | 0.55% | 0.30% | 0.10% | 0.22% |
WM Waste Management, Inc. | 1.63% | 1.50% | 1.49% | 1.56% | 1.66% | 1.38% | 1.85% | 1.80% | 2.09% | 1.97% | 2.31% | 2.89% |
Drawdowns
Drawdowns Chart
The Drawdowns chart displays portfolio losses from any high point along the way. Drawdowns are calculated considering price movements and all distributions paid, if any.
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Worst Drawdowns
The table below displays the maximum drawdowns of the Chatgpt O3 pro 6月12. A maximum drawdown is a measure of risk, indicating the largest reduction in portfolio value due to a series of losing trades.
The maximum drawdown for the Chatgpt O3 pro 6月12 was 35.11%, occurring on Mar 23, 2020. Recovery took 52 trading sessions.
The current Chatgpt O3 pro 6月12 drawdown is 8.54%.
Related event | Drawdown | Fall | Recovery | Underwater |
|---|---|---|---|---|
COVID crash2020 | -35.11%Mar 2020 | 1mo 2d | 2mo 14d | 3mo 16dFeb 2020 - Jun 2020 |
Rate-hike selloffLate 2018 | -30.70%Dec 2018 | 2mo 23d | 3mo 15d | 6mo 8dOct 2018 - Apr 2019 |
Bear market2022 | -25.91%Sep 2022 | 9mo 2d | 4mo 9d | 1y 1moDec 2021 - Feb 2023 |
2025 selloff2025 | -21.41%Apr 2025 | 1mo 16d | 1mo 7d | 2mo 23dFeb 2025 - May 2025 |
2011 correction2011 | -18.89%Oct 2011 | 2mo 10d | 3mo 26d | 6mo 6dJul 2011 - Jan 2012 |
Volatility
Volatility Chart
The chart below shows the rolling one-month volatility.
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Diversification
Diversification Metrics
Number of Effective Assets
The portfolio contains 7 assets, with an effective number of assets of 6.90, reflecting the diversification based on asset allocation. Your capital is spread almost evenly across your holdings, indicating a well-balanced allocation. Note that true diversification also depends on the correlations between assets — check the diversification ratio below.
Diversification Ratio
1Y | 3Y | 5Y | 10Y | All Time | |
|---|---|---|---|---|---|
Diversification Ratio | 1.92 | 1.65 | 1.54 | 1.49 | 1.55 |
The portfolio has a diversification ratio of 1.55, in line with the typical range across portfolios. There's room to improve by adding less correlated assets.
Chatgpt O3 pro 6月12 correlation to the S&P 500 Index
| Correlation | |
|---|---|
Correlation (1Y) Calculated over the trailing 1-year period | 0.78 |
Correlation (3Y) Calculated over the trailing 3-year period | 0.81 |
Correlation (5Y) Calculated over the trailing 5-year period | 0.86 |
Correlation (10Y) Calculated over the trailing 10-year period | 0.84 |
Correlation (All Time) Calculated using the full available price history since Aug 28, 2009 | 0.83 |
Benchmark Correlations
Correlation vs. S&P 500 Index. TECL has the highest benchmark correlation at 0.89, while GLD has the lowest at 0.06.
Asset Correlations Table
Find what Chatgpt O3 pro 6月12 is missing
See which holdings overlap, where Chatgpt O3 pro 6月12 is concentrated, and which low-correlation assets could fill the gaps.
Analyze Diversification