This portfolio has only about 1 months of historical data, based on the youngest asset in the portfolio. Some metrics, projections, and AI insights may be less reliable and should be interpreted with caution.

Multi factor equity portfolio blending value momentum and crypto with strong US and technology tilt

Report created on May 8, 2026

Risk profile Info

4/7
Balanced
Less risk More risk

Diversification profile Info

4/5
Broadly Diversified
Less diversification More diversification

Positions

This portfolio is mainly a mix of broad equity ETFs with a small but meaningful slice in bitcoin. Around half sits in US large‑cap funds linked to a major US index, with another fifth in international stocks and a notable 15% in a US small‑cap value strategy. Bitcoin takes up 10%, and two focused thematic ETFs together add 5%. Structurally, this is a stock‑heavy, growth‑oriented mix with a dash of high‑octane assets. Because weights are assumed buy‑and‑hold, their share will drift over time as some parts grow faster than others. With only about a month of history, any impression of how this structure behaves over full cycles should be treated as tentative, not a stable pattern.

Growth Info

Over the short one‑month window, the portfolio turned $1,000 into about $1,128, which looks extremely strong but is based on a very brief and unusually favorable period. The reported compound annual growth rate (CAGR) of over 300% is a mathematical artifact of annualizing one hot month, not a realistic long‑term expectation. Max drawdown, the worst peak‑to‑trough drop, was shallow at about ‑1.3%, smaller than many equity pullbacks. The portfolio also beat both US and global equity benchmarks over this span. However, with only seven days producing 90% of returns and hardly any history, these results mostly show that the portfolio had a good start, not a reliable long‑run pattern.

Projection Info

The forward projection uses a Monte Carlo simulation, which is basically a thousand “what if” reruns of the next 15 years using patterns drawn from history. Here it suggests a median outcome of roughly $2,924 from $1,000, with a wide range around that. The average simulated annual return of about 8.6% is in the ballpark of long‑term equity assumptions. But because the underlying history for this specific mix is only about a month, the engine is extrapolating short‑term behavior into a long horizon. That makes these numbers more of an educational illustration of uncertainty than a dependable forecast. They mainly highlight that outcomes can differ a lot even with the same starting portfolio.

Asset classes Info

  • Stocks
    88%
  • Crypto
    10%
  • No data
    2%

By asset class, about 88% is in stocks, 10% in crypto, and 2% falls into a “no data” bucket where classification isn’t available. This is clearly an equity‑centric portfolio with a bolt‑on allocation to bitcoin rather than a blend of stocks and bonds. A stock‑heavy structure tends to move more with economic cycles and company earnings, while crypto can add extra ups and downs. Relative to many broad market portfolios that include bonds or cash, this mix leans further toward growth potential and day‑to‑day volatility. Because the historical window is so short, it’s not yet possible to see how these asset classes would have interacted through a full bull‑and‑bear cycle.

Sectors Info

  • Technology
    28%
  • Financials
    13%
  • Industrials
    11%
  • Crypto
    10%
  • Consumer Discretionary
    7%
  • Telecommunications
    6%
  • Health Care
    6%
  • Energy
    6%
  • Consumer Staples
    4%
  • Basic Materials
    3%
  • Utilities
    2%
  • Real Estate
    1%

This breakdown covers the equity portion of your portfolio only.

Sector exposure is led by technology at 28%, with financials, industrials, and consumer sectors making up much of the rest, plus a clearly separated 10% in crypto. This is more tech‑tilted than a typical global index, reflecting the use of momentum and semiconductor ETFs, which are often heavy in fast‑growing companies. Tech‑heavy allocations can do very well in periods of innovation and low interest rates but may swing more when markets reset growth expectations. The presence of all major sectors, even if unevenly, is a positive for diversification across business types. Still, the recent strong performance in tech during this short window may overstate how smooth this tilt feels over longer, more varied conditions.

Regions Info

  • North America
    69%
  • Europe Developed
    8%
  • Asia Developed
    3%
  • Japan
    3%
  • Asia Emerging
    3%
  • Australasia
    1%
  • Africa/Middle East
    1%
  • Latin America
    1%

This breakdown covers the equity portion of your portfolio only.

Geographically, the portfolio is dominated by North America at 69%, with the rest spread across developed Europe, Japan, developed Asia, and several emerging regions. Compared with a global market baseline, this is a pronounced US tilt, which is common given the US‑focused ETFs and bitcoin being priced in dollars. A strong home bias can benefit from domestic economic strength and familiar markets but also ties results closely to one region’s growth, policy, and currency. The additional exposure to Europe and parts of Asia does add global reach, which supports the strong diversification score. With only a month of returns, though, it’s too early to judge how this regional mix behaves when different economies move out of sync.

Market capitalization Info

  • Mega-cap
    32%
  • Large-cap
    28%
  • Mid-cap
    11%
  • Small-cap
    9%
  • Micro-cap
    7%

This breakdown covers the equity portion of your portfolio only.

By company size, the portfolio leans toward bigger firms: roughly a third in mega‑caps, another chunk in large‑caps, and the rest spread across mid, small, and micro‑caps. This resembles a broad equity core with a deliberate tilt into smaller companies via the small‑cap value ETF. Larger firms often provide stability and deep markets, while smaller ones can be more sensitive to economic news but offer more company‑specific growth potential. Having all size buckets represented supports diversification across different business stages. Given the short performance history, it’s not yet visible how the small‑cap sleeve behaves in a real downturn or strong recovery, where size effects tend to show up more clearly.

True holdings Info

  • NVIDIA Corporation
    4.61%
    Part of fund(s):
    • Invesco S&P 500® Momentum ETF
    • VanEck Semiconductor ETF
    • Vanguard S&P 500 ETF
  • Broadcom Inc
    2.87%
    Part of fund(s):
    • Invesco S&P 500® Momentum ETF
    • VanEck Semiconductor ETF
    • Vanguard S&P 500 ETF
  • Alphabet Inc Class A
    2.10%
    Part of fund(s):
    • Invesco S&P 500® Momentum ETF
    • Vanguard S&P 500 ETF
  • Micron Technology Inc
    1.96%
    Part of fund(s):
    • Invesco S&P 500® Momentum ETF
    • VanEck Semiconductor ETF
  • Alphabet Inc Class C
    1.68%
    Part of fund(s):
    • Invesco S&P 500® Momentum ETF
    • Vanguard S&P 500 ETF
  • Apple Inc
    1.67%
    Part of fund(s):
    • Vanguard S&P 500 ETF
  • Microsoft Corporation
    1.23%
    Part of fund(s):
    • Vanguard S&P 500 ETF
  • Johnson & Johnson
    1.07%
    Part of fund(s):
    • Invesco S&P 500® Momentum ETF
  • Advanced Micro Devices Inc
    0.95%
    Part of fund(s):
    • Invesco S&P 500® Momentum ETF
    • VanEck Semiconductor ETF
  • Lam Research Corp
    0.93%
    Part of fund(s):
    • Invesco S&P 500® Momentum ETF
    • VanEck Semiconductor ETF
  • Top 10 total 19.06%

This breakdown covers the equity portion of your portfolio only.

Looking through fund holdings, the biggest underlying names include NVIDIA, Broadcom, Alphabet, Micron, Apple, Microsoft, and a few others, together making up a noticeable slice of total exposure. These companies appear across multiple ETFs, especially those tracking broad US indexes and tech‑focused themes. When the same stock shows up in different funds, it can create hidden concentration: the portfolio may be more tied to a few large growth and semiconductor names than the top‑level fund list suggests. Because only ETF top‑10 positions are used, true overlap is likely higher than reported. With such limited historical data, the short‑term outperformance could be heavily driven by how these specific names did in this particular month.

Factors Info

Value
Preference for undervalued stocks
Very high
Data availability: 25%
Size
Exposure to smaller companies
Very low
Data availability: 88%
Momentum
Exposure to recently outperforming stocks
High
Data availability: 25%
Quality
Preference for financially healthy companies
No data
Data availability: 0%
Yield
Preference for dividend-paying stocks
Neutral
Data availability: 98%
Low Volatility
Preference for stable, lower-risk stocks
Neutral
Data availability: 88%

Factor exposures are estimated using statistical models based on historical data and measure systematic (market-relative) tilts, not absolute portfolio characteristics. Results may vary depending on the analysis period, data availability, and currency of the underlying assets.

Factor exposure shows a very high tilt toward value and a very low tilt toward size, plus a strong leaning to momentum. Factors are characteristics, like “cheap vs expensive” (value) or “small vs large” (size), that research links to long‑term return patterns. A very high value score suggests the portfolio holds more companies trading at lower prices relative to fundamentals than the broad market, which can help when sentiment shifts toward bargains. The very low size exposure means the overall mix still behaves more like larger companies despite the small‑cap sleeve. High momentum exposure points to stocks that have been recent winners, which can help in trending markets but may amplify reversals. With just a month of returns, these tilts are more structural descriptions than proven behavior patterns.

Risk contribution Info

  • Invesco S&P 500® Momentum ETF
    Weight: 25.00%
    28.1%
  • Vanguard Total International Stock Index Fund ETF Shares
    Weight: 20.00%
    23.7%
  • Vanguard S&P 500 ETF
    Weight: 25.00%
    17.3%
  • Fidelity Wise Origin Bitcoin Trust
    Weight: 10.00%
    14.3%
  • Avantis® U.S. Small Cap Value ETF
    Weight: 15.00%
    7.1%
  • Top 5 risk contribution 90.4%

Risk contribution shows how much each holding drives overall ups and downs, which can differ from simple weight. Here, the US momentum ETF and the international stock ETF together contribute more than half of total risk, more than their combined 45% weight. Bitcoin, at 10% weight, adds over 14% of risk, reflecting its higher volatility. In contrast, the small‑cap value ETF has 15% of the portfolio but contributes only about 7% of risk in this brief window, suggesting its recent behavior has been relatively calm versus others. The top three positions account for about 69% of total risk, underlining that headline weights understate where most of the movement currently comes from.

Risk vs. return

This chart shows the Efficient Frontier, calculated using your current assets with different allocation combinations. It highlights the best balance between risk and return based on historical data. "Efficient" portfolios maximize returns for a given risk or minimize risk for a given return. Portfolios below the curve are less efficient. This is informational and not a recommendation to buy or sell any assets.

Click on the colored dots to explore allocations.

The efficient frontier analysis compares the current portfolio to the best possible risk‑return mixes using the same holdings. The current allocation sits below the efficient frontier, with a Sharpe ratio (return per unit of risk) lower than both the optimal and minimum‑variance portfolios. In plain terms, the model suggests that, based on this short return history, a different combination of the existing funds could have delivered either higher expected return for similar risk or similar return for less risk. However, these optimization results rely heavily on the one‑month sample, which is far too short to capture stable relationships between the assets. So the “gap” to the frontier should be viewed as a mathematical curiosity for now, not a firm conclusion about long‑term efficiency.

Dividends Info

  • Avantis® U.S. Small Cap Value ETF 1.30%
  • VanEck Semiconductor ETF 0.20%
  • Invesco S&P 500® Momentum ETF 0.70%
  • Vanguard S&P 500 ETF 1.10%
  • Vanguard Total International Stock Index Fund ETF Shares 2.70%
  • Weighted yield (per year) 1.19%

The portfolio’s overall dividend yield is about 1.19%, coming mainly from the broad US and international equity ETFs and the small‑cap value fund. Yield is basically the cash income paid out each year as a percentage of the investment, separate from price moves. This level is modest and typical for a growth‑leaning equity mix, especially one containing momentum strategies, thematic ETFs, and crypto, which usually focus more on capital gains than income. Dividends can help smooth total returns over time, particularly in flat markets, but in this portfolio they’re a secondary contributor compared with price performance. With only a month of data, the stability of these payouts and any pattern of reinvestment can’t yet be evaluated meaningfully.

Ongoing product costs Info

  • Avantis® U.S. Small Cap Value ETF 0.25%
  • Fidelity Wise Origin Bitcoin Trust 0.25%
  • VanEck Semiconductor ETF 0.35%
  • Invesco S&P 500® Momentum ETF 0.13%
  • Vanguard S&P 500 ETF 0.03%
  • Vanguard Total International Stock Index Fund ETF Shares 0.05%
  • Weighted costs total (per year) 0.12%

On costs, the weighted ongoing fee (TER) is about 0.12%, which is impressively low for a portfolio combining broad index funds with more specialized strategies and a crypto product. Lower fees mean less return is sacrificed each year just to keep the portfolio running, and that difference adds up when compounded over many years. The core index ETFs are especially cheap, pulling the overall cost down, while the more focused and crypto funds are pricier but still moderate. Relative to many mixed portfolios using active funds, this fee level is a structural strength. Over long horizons, keeping costs this low can matter as much as small differences in performance, even though the short one‑month history doesn’t yet show that compounding effect.

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