This portfolio is made up of six individual stocks, with no funds or bonds, and uses fairly even weights. Two holdings sit at 20% each, while the remaining four are at 15%, so every position meaningfully drives overall results. The whole structure is basically a focused basket of technology and related names, with no exposure to broader market indices or defensive assets. That makes the portfolio simple to understand but also tightly tied to how these specific companies behave. In practice, this kind of concentrated stock list can deliver very different outcomes from the overall market, in both directions, because there is no “buffer” from other asset types or a wider set of companies.
Over the 2018–2026 period, $1,000 grew to about $9,097, a compound annual growth rate (CAGR) of 33%. CAGR is like the average speed of a car over a long trip, smoothing out all the bumps. This comfortably beat both the US and global market, which grew around 14% and 11% per year. The trade-off was a max drawdown over 52%, meaning the portfolio more than halved from peak to trough at one point. That’s a much deeper drop than the benchmarks. The fact that 90% of returns came from just 34 days shows results were driven by a handful of big moves, which is typical of volatile, growth-focused portfolios.
The Monte Carlo projection models many possible 15‑year paths by shuffling and reusing past return patterns. Think of it as running 1,000 alternate histories to see a range of plausible futures, not a forecast. The median outcome is about $2,735 from $1,000, with most scenarios falling between roughly $1,876 and $4,252. There are also more extreme paths, from close to flat to very strong growth. The average simulated annual return is 8.35%, noticeably below the backward‑looking 33% CAGR, which reflects the model’s more conservative expectations. As always, these simulations depend on historical data and assumptions, so real‑world results can land outside the shown ranges.
All of the portfolio is in stocks, with 0% in bonds, cash-like instruments, or alternatives. That creates a very “equity pure” profile, meaning returns are closely tied to the ups and downs of company earnings and market sentiment. From a diversification standpoint, this avoids the balancing effect that other asset classes can sometimes provide during equity sell‑offs. Compared with broad market benchmarks that usually hold a mix of sectors and sometimes additional asset types in balanced strategies, this structure is intentionally narrow. The upside is clear participation when stocks are strong; the flip side is that the portfolio fully absorbs equity market shocks with no built‑in cushion from other asset categories.
Sector-wise, about 85% sits in technology, with the remaining 15% classified as industrials. That’s a heavy tilt toward one area of the economy compared with broad benchmarks, which usually spread more evenly across multiple sectors. Tech-heavy portfolios can benefit a lot from innovation cycles, demand for computing power, and digital infrastructure growth. However, they may be more sensitive to changes in interest rates, regulation, and shifts in investor appetite for high‑growth stories. The industrial slice adds a bit of diversification but is still closely linked to innovation themes rather than traditional defensive areas. Overall, the sector mix clearly prioritizes growth and technological change over balance.
Geographically, about 85% of the portfolio is tied to North America, with the remaining 15% in developed Europe. This means performance is dominated by North American economic conditions, regulation, and currency movements, especially the $ as the reference currency. Compared with global benchmarks, which spread more widely across many regions, this exposure is more concentrated but still aligned with the fact that a large share of global technology companies are based in North America. The European portion offers some regional diversification but does not fundamentally change the North American leadership. This alignment with a major, innovation‑driven market has historically benefited returns, though it does cluster risk in that region.
The portfolio splits between mega‑cap and large‑cap stocks, with roughly 55% in the biggest global names and 45% in the next tier down. Mega‑caps often bring more stable business models and deeper resources, while large‑caps can still deliver meaningful growth with slightly higher volatility. Having no mid‑cap or small‑cap exposure means the portfolio skips the very high‑risk, high‑potential tail of the market. Relative to a broad equity index that includes all sizes, this mix is skewed toward established companies while still taking sizable risk through sector and stock concentration. It’s an interesting combination: large, well‑known firms paired with a very focused overall structure.
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 very low size, plus high momentum and high quality. Factors are like underlying “traits” of stocks that help explain performance patterns over time. The very low size reading means the portfolio leans strongly away from smaller companies and toward bigger ones. High momentum suggests it’s tilted toward stocks that have been recent winners, which often works in trending markets but can hurt during sharp reversals. High quality exposure points to companies with strong balance sheets or profitability metrics, which can sometimes cushion downside compared with lower‑quality peers. Low value and low low‑volatility readings indicate a limited tilt toward bargain‑priced or defensive characteristics, reinforcing the growth and trend‑focused profile.
Risk contribution highlights how much each stock drives the portfolio’s overall ups and downs, which can differ a lot from simple weights. Here, Bloom Energy is 15% of capital but almost 28% of total risk, making it the single biggest risk driver. Together with Advanced Micro Devices and Micron, the top three names account for over 73% of portfolio risk. That means day‑to‑day performance is largely dictated by this trio, especially Bloom. On the other side, Qualcomm and Nokia contribute less risk than their weights, acting as relatively calmer components. This pattern is common in concentrated portfolios where one or two more volatile holdings dominate the risk picture.
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 this portfolio’s risk‑return mix to the best combinations achievable using the same holdings. The current mix has a Sharpe ratio of 0.99, below the optimal portfolio’s 1.13, and sits about 1.63 percentage points under the frontier at its current risk level. The Sharpe ratio measures risk‑adjusted return, like asking how much return you get for each unit of volatility. Being below the frontier suggests that a different weighting of these six stocks — without adding anything new — could historically have offered a better balance between risk and return. Still, a Sharpe near 1 indicates the existing allocation has delivered solid compensation for the volatility taken on.
Dividend yield for the portfolio sits at about 0.94%, which is modest compared with many income‑oriented strategies. A few holdings, like IBM and Qualcomm, contribute meaningful yields above 2%, while others pay little or nothing. Dividends are the cash payouts companies make to shareholders and can be an important part of total return over long periods, especially when reinvested. In this case, most of the portfolio’s historical performance has come from price movement rather than income. That’s consistent with its growth‑and‑momentum character. The presence of a couple of higher‑yielding names does, however, provide a small ongoing cash flow stream alongside the more growth‑driven positions.
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