This portfolio is built around two broad equity funds plus a small allocation to gold. About three quarters sits in a global stock fund, one fifth in a US-focused fund, and 5% in a gold ETC. That means roughly 95% is in shares and 5% in an alternative asset. Structurally, this is a simple, concentrated line‑up where just three positions drive all returns and risk. Simpler portfolios are easier to monitor and understand, because each holding plays a clear role. Here, the structure suggests a growth‑oriented stance with a modest diversifier on the side, rather than a mix of many different strategies or asset types.
Over the last five years, €1,000 grew to about €1,774, which is a compound annual growth rate (CAGR) of 12.13%. CAGR is like your “average speed” over the journey, smoothing out bumps along the way. The portfolio slightly trailed the US market but beat the global market, so it has kept pace with strong conditions while still being globally spread. The worst drop from peak to trough was about -20%, recovering in roughly six months, which is a typical equity-style setback. Only 24 days made up 90% of returns, showing how a small number of very strong days can heavily influence long‑term results.
The forward projection uses a Monte Carlo simulation, which runs 1,000 random “what if” market paths based on historical behaviour. Think of it as re‑rolling the last few years in many different orders to see a range of possible futures. The median outcome turns €1,000 into about €2,722 over 15 years, with a wide but plausible band from roughly €1,036 to €7,032. The average simulated annual return of 7.81% reflects both good and bad scenarios. These numbers are not promises; they’re statistical estimates built from past data, and real markets can behave very differently, especially over long horizons.
By asset class, the portfolio is almost entirely in equities, with 95% in stocks and 5% in “other,” which here is gold. Equities are the main growth engine, while gold often acts more as a diversifier than a traditional investment that produces income or earnings. This kind of equity‑heavy mix naturally comes with more ups and downs than a blend that includes significant bonds or cash. The small gold allocation slightly offsets that, particularly in stress periods where gold can move differently from stocks. Overall, this structure leans clearly toward capital growth rather than income or capital stability.
This breakdown covers the equity portion of your portfolio only.
Sector exposure is led by technology at 29%, with financials, industrials and consumer areas making up much of the rest. This reflects how global equity markets are built today, where tech and related businesses take a large share of total value. A tech‑heavy mix often benefits during periods of innovation and low interest rates, but it can be more sensitive when rates rise or sentiment turns against growth companies. The presence of financials, healthcare, consumer staples and utilities shows decent spread across the economic cycle. This broad sector balance, while tilted to tech, is generally aligned with global benchmark compositions.
This breakdown covers the equity portion of your portfolio only.
Geographically, about 68% of the portfolio sits in North America, with Europe, Japan and other regions making up the rest. That US‑heavy pattern mirrors most global equity indices, where US companies dominate total market value. This alignment with global market weights is a positive sign for diversification, as it avoids large, active regional bets. At the same time, it means portfolio results are strongly linked to the US economy, currency and policy environment. Smaller, but still meaningful, slices in Europe and various Asian regions add exposure to different growth drivers and policy regimes, which can smooth regional booms and slowdowns over time.
This breakdown covers the equity portion of your portfolio only.
Market capitalization exposure is skewed toward mega-cap and large-cap companies, which together represent about 78% of the equity slice, with mid‑caps at 16%. Mega‑caps are the world’s biggest firms, often with diversified businesses and strong balance sheets, which can make them more resilient in downturns. Mid‑caps, being smaller, can be more volatile but sometimes grow faster. This tilt toward very large companies closely tracks global index construction and tends to reduce idiosyncratic risk from any single smaller firm. The relatively modest mid‑cap share adds some dynamism without turning the portfolio into a small‑company‑heavy strategy.
This breakdown covers the equity portion of your portfolio only.
Looking through the funds, the largest underlying exposures are to well‑known global giants such as NVIDIA, Apple, Microsoft, Amazon, Alphabet, Broadcom, Meta, Taiwan Semiconductor and Tesla. These names appear via multiple ETFs, which creates overlap and concentrates risk in a handful of big growth companies even though there are only three top-level holdings. The top‑10 look‑through holdings are already over 25% of the portfolio slice that’s visible, and true overlap is likely higher because only ETF top‑10s are counted. This means portfolio behaviour is meaningfully influenced by the fortunes of a relatively small group of large, mostly tech‑oriented firms.
Risk contribution measures how much each holding drives the portfolio’s overall ups and downs, which can differ from simple weights. Here, the global equity fund at 75% weight contributes about 77% of total risk, roughly in line with size. The US fund at 20% weight contributes slightly more risk than its share, at 22%, reflecting its pure equity and US focus. The 5% gold position adds less than 1% of total risk, so it barely moves the needle on volatility. This shows risk is effectively concentrated in the two stock funds, while gold acts more as a small diversifier than a major risk source.
The two equity funds are highly correlated, meaning they tend to move almost identically day to day. Correlation is a measure of how assets move together; when two lines on a chart overlap closely, diversification benefits between them are limited. In this case, the global fund and the US fund both respond strongly to broad equity market conditions, especially in the US. The main diversification therefore comes from gold rather than from differences between the two equity ETFs. This is typical when combining broad market funds that both cover large parts of the same underlying universe, just with different scopes.
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 risk vs. return analysis plots your portfolio against the “efficient frontier,” which shows the best achievable return for each risk level using only your current holdings in different mixes. The current portfolio has a Sharpe ratio of 0.63, while the optimal mix of the same three holdings reaches 1.3, meaning much better return per unit of risk. It also sits 4.52 percentage points below the frontier at its risk level, so it’s not using these holdings in the most efficient combination. The minimum‑variance mix is both less risky and has a higher Sharpe, suggesting there is room to improve risk/return by reweighting alone.
Total ongoing costs, measured by the weighted average TER of 0.16%, are impressively low. TER (Total Expense Ratio) is the annual fee charged by a fund, a bit like a management charge for running the portfolio. Low costs matter because they come off returns every year, and even small differences compound over time. Here, using broad, low‑fee index funds keeps the drag minimal, which is a strong structural advantage. In practice, this means more of the portfolio’s gross market return is kept rather than lost to fees, supporting better long‑term outcomes compared with higher‑cost, similar strategies.
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