Asset Allocation
| Position | Category/Sector | Target Weight |
|---|---|---|
QQQ Invesco QQQ ETF | Large Cap Growth Equities | 30% |
SCHD Schwab U.S. Dividend Equity ETF | Dividend | 15% |
SCHG Schwab U.S. Large-Cap Growth ETF | Large Cap Growth Equities | 20% |
SMH VanEck Semiconductor ETF | Semiconductors, Technology Equities | 20% |
VGT Vanguard Information Technology ETF | Technology Equities | 15% |
Performance
Performance Chart
The chart shows the growth of an initial investment of $10,000 in ChatGPT Growth Tilted Core Model, 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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The earliest data available for this chart is Oct 20, 2011, corresponding to the inception date of SCHD
Returns By Period
As of Apr 1, 2026, the ChatGPT Growth Tilted Core Model returned -1.78% Year-To-Date and 20.62% of annualized return in the last 10 years.
| 1D | 1M | YTD | 6M | 1Y | 3Y* | 5Y* | 10Y* | |
|---|---|---|---|---|---|---|---|---|
Benchmark S&P 500 Index | 2.91% | -5.09% | -4.63% | -2.39% | 16.33% | 16.69% | 10.18% | 12.16% |
Portfolio ChatGPT Growth Tilted Core Model | 3.59% | -4.56% | -1.78% | 1.88% | 32.49% | 25.32% | 15.42% | 20.62% |
| Portfolio components: | ||||||||
SCHD Schwab U.S. Dividend Equity ETF | 0.66% | -2.61% | 12.79% | 14.49% | 13.97% | 12.05% | 8.44% | 12.31% |
QQQ Invesco QQQ ETF | 3.39% | -4.84% | -5.93% | -3.62% | 23.68% | 22.32% | 12.88% | 18.85% |
SMH VanEck Semiconductor ETF | 5.76% | -5.65% | 6.46% | 17.84% | 81.87% | 43.47% | 25.59% | 31.28% |
SCHG Schwab U.S. Large-Cap Growth ETF | 3.67% | -5.12% | -10.59% | -8.51% | 16.81% | 21.91% | 12.55% | 16.83% |
VGT Vanguard Information Technology ETF | 4.34% | -3.89% | -7.34% | -6.36% | 29.19% | 22.58% | 14.54% | 21.35% |
Monthly Returns
Based on dividend-adjusted daily data since Oct 21, 2011, ChatGPT Growth Tilted Core Model's average daily return is +0.08%, while the average monthly return is +1.59%. At this rate, your investment would double in approximately 3.7 years.
Historically, 66% of months were positive and 34% were negative. The best month was Apr 2020 with a return of +14.3%, while the worst month was Apr 2022 at -12.1%. The longest winning streak lasted 10 consecutive months, and the longest losing streak was 3 months.
On a daily basis, ChatGPT Growth Tilted Core Model closed higher 56% of trading days. The best single day was Apr 9, 2025 with a return of +12.3%, while the worst single day was Mar 16, 2020 at -12.5%.
| Jan | Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec | Total | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2026 | 3.59% | -0.65% | -4.56% | -1.78% | |||||||||
| 2025 | 1.34% | -2.57% | -7.23% | -0.26% | 8.96% | 8.33% | 2.74% | 1.52% | 5.90% | 5.24% | -1.78% | 0.36% | 23.56% |
| 2024 | 2.65% | 6.84% | 3.00% | -4.60% | 7.03% | 6.26% | -1.04% | 0.94% | 1.94% | -0.73% | 4.82% | -0.68% | 29.00% |
| 2023 | 10.31% | -0.54% | 7.95% | -0.94% | 7.53% | 6.08% | 4.02% | -1.74% | -5.63% | -2.58% | 11.52% | 6.17% | 48.91% |
| 2022 | -8.16% | -3.61% | 3.39% | -12.08% | 0.59% | -10.23% | 12.21% | -5.79% | -10.80% | 5.33% | 8.30% | -8.01% | -28.10% |
| 2021 | 0.44% | 2.47% | 2.52% | 4.35% | 0.07% | 5.15% | 2.19% | 3.47% | -5.28% | 7.39% | 3.12% | 2.40% | 31.59% |
Benchmark Metrics
ChatGPT Growth Tilted Core Model has an annualized alpha of 4.89%, beta of 1.15, and R² of 0.90 versus S&P 500 Index. Calculated based on daily prices since October 21, 2011.
- This portfolio captured 129.96% of S&P 500 Index gains but only 99.97% of its losses — a favorable profile for investors.
- This portfolio generated an annualized alpha of 4.89% versus S&P 500 Index — delivering returns beyond what market exposure alone would predict.
- With beta of 1.15 and R² of 0.90, this portfolio moves broadly in line with S&P 500 Index — much of its variation is explained by market exposure rather than independent behavior.
- Alpha
- 4.89%
- Beta
- 1.15
- R²
- 0.90
- Upside Capture
- 129.96%
- Downside Capture
- 99.97%
Expense Ratio
ChatGPT Growth Tilted Core Model has an expense ratio of 0.15%, 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 Growth Tilted Core Model ranks 72 for risk / return — better than 72% of portfolios on our site. You're getting solid returns for the risk taken. A good sign, especially for investors who want growth without excessive volatility.
Return / Risk — by metrics
| Portfolio | Benchmark | Difference | |
|---|---|---|---|
Sharpe ratioReturn per unit of total volatility | 1.37 | 0.90 | +0.48 |
Sortino ratioReturn per unit of downside risk | 2.02 | 1.39 | +0.63 |
Omega ratioGain probability vs. loss probability | 1.30 | 1.21 | +0.08 |
Calmar ratioReturn relative to maximum drawdown | 2.40 | 1.40 | +1.00 |
Martin ratioReturn relative to average drawdown | 10.64 | 6.61 | +4.04 |
Data is calculated on a 1-year rolling basis and updated daily. The trend shows the change in the indicator over the past month. | |||
How much return does each position deliver for the risk it carries? Higher values mean better reward for the risk taken.
| Risk / Return Rank | Sharpe ratio | Sortino ratio | Omega ratio | Calmar ratio | Martin ratio | |
|---|---|---|---|---|---|---|
SCHD Schwab U.S. Dividend Equity ETF | 52 | 0.89 | 1.35 | 1.19 | 1.19 | 3.99 |
QQQ Invesco QQQ ETF | 69 | 1.05 | 1.63 | 1.23 | 1.88 | 6.95 |
SMH VanEck Semiconductor ETF | 95 | 2.23 | 2.85 | 1.40 | 5.10 | 18.29 |
SCHG Schwab U.S. Large-Cap Growth ETF | 46 | 0.75 | 1.23 | 1.17 | 1.03 | 3.54 |
VGT Vanguard Information Technology ETF | 67 | 1.08 | 1.65 | 1.23 | 1.77 | 5.47 |
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Dividends
Dividend yield
ChatGPT Growth Tilted Core Model provided a 0.87% dividend yield over the last twelve months.
| TTM | 2025 | 2024 | 2023 | 2022 | 2021 | 2020 | 2019 | 2018 | 2017 | 2016 | 2015 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Portfolio | 0.87% | 0.90% | 0.97% | 1.02% | 1.23% | 0.83% | 1.01% | 1.30% | 1.56% | 1.28% | 1.32% | 1.61% |
| Portfolio components: | ||||||||||||
SCHD Schwab U.S. Dividend Equity ETF | 3.44% | 3.82% | 3.64% | 3.49% | 3.39% | 2.78% | 3.16% | 2.98% | 3.06% | 2.63% | 2.89% | 2.97% |
QQQ Invesco QQQ ETF | 0.49% | 0.45% | 0.56% | 0.62% | 0.80% | 0.43% | 0.55% | 0.74% | 0.91% | 0.84% | 1.06% | 0.99% |
SMH VanEck Semiconductor ETF | 0.29% | 0.31% | 0.44% | 0.60% | 1.18% | 0.51% | 0.69% | 1.50% | 1.88% | 1.43% | 0.80% | 2.14% |
SCHG Schwab U.S. Large-Cap Growth ETF | 0.43% | 0.36% | 0.39% | 0.46% | 0.55% | 0.42% | 0.52% | 0.82% | 1.27% | 1.01% | 1.04% | 1.22% |
VGT Vanguard Information Technology ETF | 0.44% | 0.40% | 0.60% | 0.65% | 0.91% | 0.64% | 0.82% | 1.11% | 1.29% | 0.99% | 1.31% | 1.28% |
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 Growth Tilted Core Model. 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 Growth Tilted Core Model was 34.14%, occurring on Oct 14, 2022. Recovery took 289 trading sessions.
The current ChatGPT Growth Tilted Core Model drawdown is 6.84%.
Depth | Start | To Bottom | Bottom | To Recover | End | Total |
|---|---|---|---|---|---|---|
| -34.14% | Dec 28, 2021 | 202 | Oct 14, 2022 | 289 | Dec 8, 2023 | 491 |
| -30.74% | Feb 20, 2020 | 23 | Mar 23, 2020 | 53 | Jun 8, 2020 | 76 |
| -23.78% | Jan 24, 2025 | 52 | Apr 8, 2025 | 52 | Jun 24, 2025 | 104 |
| -21.72% | Aug 30, 2018 | 80 | Dec 24, 2018 | 59 | Mar 21, 2019 | 139 |
| -14.99% | Dec 7, 2015 | 46 | Feb 11, 2016 | 80 | Jun 7, 2016 | 126 |
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 5 assets, with an effective number of assets of 4.65, reflecting the diversification based on asset allocation. This number of effective assets suggests a highly concentrated portfolio, where a few assets dominate the allocation, potentially increasing the portfolio's risk due to lack of diversification.
Asset Correlations Table
| Benchmark | SCHD | SMH | QQQ | SCHG | VGT | Portfolio | |
|---|---|---|---|---|---|---|---|
| Benchmark | 1.00 | 0.83 | 0.77 | 0.90 | 0.94 | 0.89 | 0.93 |
| SCHD | 0.83 | 1.00 | 0.58 | 0.63 | 0.66 | 0.63 | 0.70 |
| SMH | 0.77 | 0.58 | 1.00 | 0.83 | 0.79 | 0.86 | 0.92 |
| QQQ | 0.90 | 0.63 | 0.83 | 1.00 | 0.96 | 0.96 | 0.97 |
| SCHG | 0.94 | 0.66 | 0.79 | 0.96 | 1.00 | 0.94 | 0.95 |
| VGT | 0.89 | 0.63 | 0.86 | 0.96 | 0.94 | 1.00 | 0.97 |
| Portfolio | 0.93 | 0.70 | 0.92 | 0.97 | 0.95 | 0.97 | 1.00 |