The risk profile, derived from past market volatility, reflects the level of risk the portfolio is exposed to. This assessment helps align your investments with your financial goals and comfort with market fluctuations.
The diversification assessment evaluates the spread of investments across asset classes, regions, and sectors. This ensures a balanced mix, reducing risk and maximizing returns by not concentrating in any single area.
The portfolio is very simple: roughly seventy percent sits in a global equity ETF and thirty percent in a single industrial stock. That creates a core–satellite structure, with the ETF acting as a diversified base and the individual share as a focused bet. Simplicity matters because fewer moving parts make it easier to understand what is driving returns and risk. However, a big position in one company means portfolio behaviour will be strongly influenced by that stock’s fortunes. The general takeaway is that this structure can deliver strong upside but relies heavily on one business, so comfort with company‑specific swings is essential.
Historically, the portfolio has delivered extremely strong returns: £1,000 grew to about £4,265 over less than three years, implying a compound annual growth rate (CAGR) of about 68.7%. CAGR is like the average yearly “speed” of your money over the whole journey. Both US and global markets were around 15.7% over the same period, so this mix massively outpaced broad benchmarks. The max drawdown, a peak‑to‑trough fall of about 21%, matches the US market’s worst drop but with much higher long‑term gains. This shows high reward for similar downside historically, but such exceptional outperformance is unlikely to be permanent.
The forward projection uses Monte Carlo simulation, which is a way of modelling many possible futures by scrambling and re‑using historical returns. Think of it as running 1,000 alternate timelines based on how similar investments behaved before. Here, a £1,000 investment has a median outcome of about £2,720 after 15 years, with a wide range between roughly £965 and £8,611. The average simulated annual return is around 8.2%. This highlights both upside potential and meaningful downside risk. Monte Carlo results are not forecasts; they are “what‑if” scenarios built from past patterns, which can change if markets or the single stock’s fortunes shift.
On the asset‑class view, around thirty percent is clearly in direct equities, while seventy percent shows as “no data” because the ETF’s asset breakdown is not provided in this dataset. That limits transparency on the precise mix between shares and any other instruments inside the fund. Asset‑class splits matter because combining things that behave differently, like stocks and cash, can smooth the ride. Here, what is clear is that the explicit stock slice already introduces meaningful equity risk. The general takeaway is that the portfolio behaves overwhelmingly like an equity‑heavy strategy, with little evidence of stabilising assets in the visible data.
Sector data shows a thirty percent allocation to industrials, reflecting the single company exposure. The rest of the ETF’s sector mix is not captured here, so the total sector picture is incomplete, but it is clear that industrials are a major driver. Sector exposure is important because some industries are more sensitive to economic cycles, interest rates, or regulation than others. An outsized tilt to a cyclical area can boost returns in recoveries but hurt during downturns or sector‑specific shocks. The positive here is that the broad ETF likely diversifies across many other sectors, but the visible industrial concentration still meaningfully shapes behaviour.
Geography data shows about thirty percent in developed Europe via the single stock. The global ETF’s regional breakdown is not visible here, but funds of that type typically hold companies across many regions. Geographic exposure matters because economies, currencies, and political environments can diverge sharply. Heavy reliance on one region can amplify the impact of local issues like energy prices or regulation. While the core ETF likely adds global breadth, the explicit European tilt from the stock means portfolio outcomes will be meaningfully influenced by European market and currency conditions. This can be a strength if that region does well but adds concentration risk if it lags.
On market capitalization, about thirty percent is in a large‑cap stock. Large‑caps are big, established companies that tend to be more stable and widely researched than smaller firms. This can moderate some company‑specific risk compared with a similarly sized bet in a small‑cap. Market‑cap mix is important because small‑caps often swing more but can offer higher long‑term growth, while large‑caps usually move less but are more tied to overall market trends. Given the data available, the visible picture is skewed toward a single large‑cap driver, with the ETF likely providing additional breadth across other size segments behind the scenes.
Risk contribution numbers are striking: the individual stock is 30% of the portfolio by weight but contributes about 70% of total volatility. Risk contribution measures how much each holding drives overall ups and downs, which can differ a lot from its size. Here, the risk‑to‑weight ratio of 2.35 signals that this single name is much more influential than its allocation suggests, while the ETF is relatively low‑risk per unit of weight. This concentrated risk can be intentional for those seeking high conviction exposure. Generally, if the goal is smoother performance, reducing reliance on a single position can better align risk with intended allocations.
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–return chart shows the current portfolio with a Sharpe ratio of about 1.7, close to the optimal Sharpe of 1.84 on the efficient frontier. The Sharpe ratio measures return per unit of risk, like how many miles you get out of each litre of fuel. Being on or near the efficient frontier means that, for this mix of holdings, the portfolio is using risk effectively. The minimum‑variance portfolio would be smoother but with much lower returns. The takeaway is that, despite the concentration, the chosen weights are delivering strong risk‑adjusted performance historically. Fine‑tuning the split could squeeze out a bit more efficiency, but the current setup is already well‑tuned.
Dividend yield is modest: the individual stock yields about 0.4%, and the overall portfolio yield sits near 0.12%. Dividends are cash payments companies make to shareholders and can be a steady component of total return, especially for income‑focused investors. Here, growth rather than income is clearly the main story. A low yield is not inherently bad; fast‑growing firms may reinvest profits instead of paying them out. The main implication is that most return expectations should come from price movements, not regular cash flows. That aligns with a more aggressive, total‑return‑oriented approach rather than a strategy built around steady income.
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