Asset Allocation
| Position | Category/Sector | Target Weight |
|---|---|---|
SPLV Invesco S&P 500 Low Volatility ETF | S&P 500, Large Cap Blend Equities | 80% |
XYLD Global X S&P 500 Covered Call ETF | Derivative Income, S&P 500 | 20% |
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Performance Chart
The chart shows the growth of an initial investment of $10,000 in DIY JEPI, 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 9, 2026, the DIY JEPI returned 2.88% Year-To-Date and 8.14% of annualized return in the last 10 years.
| Position | 1D | 1M | YTD | 6M | 1Y | 3Y* | 5Y* | 10Y* |
|---|---|---|---|---|---|---|---|---|
Benchmark S&P 500 Index | 0.30% | 0.09% | 8.18% | 8.17% | 23.42% | 19.88% | 11.91% | 13.45% |
Portfolio DIY JEPI | -1.02% | 0.16% | 2.88% | 4.19% | 4.51% | 8.44% | 6.18% | 8.14% |
| Portfolio components: | ||||||||
SPLV Invesco S&P 500 Low Volatility ETF | -1.36% | -0.03% | 2.41% | 3.70% | 1.54% | 7.70% | 5.72% | 8.03% |
XYLD Global X S&P 500 Covered Call ETF | 0.27% | 0.88% | 4.47% | 5.83% | 16.60% | 10.96% | 7.62% | 8.23% |
Monthly Returns
Based on dividend-adjusted daily data since Jun 25, 2013, DIY JEPI's average daily return is +0.04%, while the average monthly return is +0.78%. At this rate, an investment would double in approximately 7.4 years.
Historically, 63% of months were positive and 37% were negative. The best month was Dec 2021 with a return of +8.5%, while the worst month was Mar 2020 at -13.7%. The longest winning streak lasted 8 consecutive months, and the longest losing streak was 3 months.
On a daily basis, DIY JEPI closed higher 55% of trading days. The best single day was Mar 24, 2020 with a return of +9.2%, while the worst single day was Mar 16, 2020 at -12.3%.
| Jan | Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec | Total | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2026 | 2.88% | 4.40% | -4.86% | 2.40% | -1.85% | 0.18% | 2.88% | ||||||
| 2025 | 2.05% | 3.57% | -0.56% | -2.29% | 1.01% | -0.03% | -0.07% | 1.44% | 0.44% | -2.48% | 3.47% | -1.43% | 5.01% |
| 2024 | 1.11% | 1.61% | 2.94% | -2.76% | 2.28% | 0.11% | 3.68% | 4.78% | 1.09% | -0.85% | 5.29% | -4.64% | 15.10% |
| 2023 | 0.94% | -2.71% | 1.62% | 2.32% | -4.00% | 3.59% | 1.03% | -2.72% | -3.56% | -0.53% | 4.84% | 2.26% | 2.63% |
| 2022 | -4.17% | -1.97% | 5.18% | -2.93% | -1.16% | -4.01% | 4.16% | -2.51% | -8.00% | 6.77% | 4.96% | -1.68% | -6.32% |
| 2021 | -1.38% | -0.77% | 6.53% | 3.42% | 1.23% | 0.39% | 3.01% | 1.95% | -4.34% | 4.67% | -1.41% | 8.48% | 23.24% |
Benchmark Metrics
DIY JEPI has an annualized alpha of 0.47%, beta of 0.69, and R2 of 0.72 versus S&P 500 Index. Calculated based on daily prices since June 25, 2013.
- This portfolio participated in 69.32% of S&P 500 Index downside but only 64.09% of its upside - more exposed to losses than it benefited from rallies.
- Beta of 0.69 indicates this portfolio moves significantly less than S&P 500 Index - a genuinely defensive profile with reduced participation in both market rallies and downturns.
- Alpha
- 0.47%
- Beta
- 0.69
- R²
- 0.72
- Upside Capture
- 64.09%
- Downside Capture
- 69.32%
Expense Ratio
DIY JEPI has an expense ratio of 0.32%, placing it in the medium range. 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
DIY JEPI ranks 8 for risk / return — in the bottom 8% of Portfolios on our site. This means you're taking on significantly more risk than the returns justify. Consider whether the potential upside is worth the volatility, or explore alternatives with better risk / return profiles.
Return / Risk — by metrics
The table below presents risk-adjusted performance metrics for DIY JEPI and compares them with S&P 500 Index.
| Portfolio | Benchmark | Difference | |
|---|---|---|---|
| Sharpe ratioReturn per unit of total volatility | 0.54 | 1.94 | -1.39 |
| Sortino ratioReturn per unit of downside risk | 0.82 | 2.63 | -1.80 |
| Omega ratioGain probability vs. loss probability | 1.10 | 1.35 | -0.26 |
| Calmar ratioReturn relative to maximum drawdown | 0.72 | 2.59 | -1.87 |
| Martin ratioReturn relative to average drawdown | 1.99 | 11.84 | -9.85 |
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.
| Position | Risk / Return Rank | Sharpe ratio | Sortino ratio | Omega ratio | Calmar ratio | Martin ratio |
|---|---|---|---|---|---|---|
SPLV Invesco S&P 500 Low Volatility ETF | 11 | 0.15 | 0.29 | 1.03 | 0.21 | 0.50 |
XYLD Global X S&P 500 Covered Call ETF | 84 | 2.53 | 3.58 | 1.59 | 3.15 | 16.73 |
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Dividends
Dividend yield
DIY JEPI provided a 3.87% dividend yield over the last twelve months.
| Position | TTM | 2025 | 2024 | 2023 | 2022 | 2021 | 2020 | 2019 | 2018 | 2017 | 2016 | 2015 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Portfolio | 3.87% | 3.73% | 3.81% | 4.06% | 4.38% | 3.02% | 3.29% | 2.81% | 3.17% | 2.66% | 2.27% | 2.75% |
| Portfolio components: | ||||||||||||
SPLV Invesco S&P 500 Low Volatility ETF | 2.20% | 2.04% | 1.88% | 2.45% | 2.11% | 1.51% | 2.12% | 2.08% | 2.18% | 2.03% | 2.03% | 2.28% |
XYLD Global X S&P 500 Covered Call ETF | 10.57% | 10.51% | 11.54% | 10.51% | 13.43% | 9.07% | 7.93% | 5.76% | 7.12% | 5.18% | 3.23% | 4.65% |
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 DIY JEPI. 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 DIY JEPI was 35.71%, occurring on Mar 23, 2020. Recovery took 269 trading sessions.
The current DIY JEPI drawdown is 4.26%.
Related event | Drawdown | Fall | Recovery | Underwater |
|---|---|---|---|---|
COVID crash2020 | -35.71%Mar 2020 | 1mo 4d | 1y 24d | 1y 1moFeb 2020 - Apr 2021 |
Bear market2022 | -17.49%Oct 2022 | 5mo 24d | 1y 7mo | 2y 26dApr 2022 - May 2024 |
Rate-hike selloffLate 2018 | -12.30%Dec 2018 | 3mo 11d | 1mo 23d | 5mo 4dSep 2018 - Feb 2019 |
2015 correction2015 | -11.04%Aug 2015 | 6d | 2mo 4d | 2mo 10dAug 2015 - Oct 2015 |
2025 selloff2025 | -9.80%Apr 2025 | 1mo 5d | 4mo 14d | 5mo 19dMar 2025 - Aug 2025 |
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 2 assets, with an effective number of assets of 1.47, reflecting the diversification based on asset allocation. Your capital is well-distributed across most of your holdings, with only mild concentration in a few names. True diversification also depends on the correlations between assets — check the diversification ratio below.
Diversification Ratio
1Y | 3Y | 5Y | 10Y | All Time | |
|---|---|---|---|---|---|
Diversification Ratio | 1.11 | 1.09 | 1.07 | 1.04 | 1.04 |
The portfolio has a diversification ratio of 1.04, placing it in the bottom quartile across portfolios — positions are highly correlated. Consider adding assets from different classes or sectors to reduce risk.
DIY JEPI correlation to the S&P 500 Index
| Correlation | |
|---|---|
Correlation (1Y) Calculated over the trailing 1-year period | 0.27 |
Correlation (3Y) Calculated over the trailing 3-year period | 0.48 |
Correlation (5Y) Calculated over the trailing 5-year period | 0.61 |
Correlation (10Y) Calculated over the trailing 10-year period | 0.70 |
Correlation (All Time) Calculated using the full available price history since Jun 25, 2013 | 0.75 |
Benchmark Correlations
Correlation vs. S&P 500 Index. XYLD has the highest benchmark correlation at 0.81, while SPLV has the lowest at 0.68.
Asset Correlations Table
Find what DIY JEPI is missing
See which holdings overlap, where DIY JEPI is concentrated, and which low-correlation assets could fill the gaps.
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