A simple two ETF global equity portfolio tilted toward developed market and US exposure
Report created on Nov 22, 2024Risk profile
3/7
Diversification profile
3/5
Positions
-
FW Invesco FTSE All-World UCITS ETF USD Accumalation
FWRG - IE000716YHJ7 70.00% -
SP Invesco S&P 500 UCITS ETF
SPXP - IE00B3YCGJ38 30.00%
The portfolio is built from two ETFs with a dominant 70% allocation to a global accumulation ETF and 30% to a US large cap ETF. This creates a straightforward structure concentrated in equities rather than a mix of bonds and alternatives. A typical balanced benchmark would include fixed income and wider asset class exposure so this allocation is noticeably equity‑heavy. Recommendation: if the aim is cautious or mixed risk objectives, consider introducing lower volatility asset classes or a third ETF that provides reliable bond or cash exposure to smooth returns and lower short term drawdowns.
Growth
Historic returns show a Compound Annual Growth Rate (CAGR) of 16.83% and a maximum drawdown of −18.67%. CAGR measures average annual growth like the steady speed of a car over a trip and here implies strong past growth. For example a £10,000 investment growing at 16.83% would be roughly £22,150 in five years and about £46,650 in ten years. The drawdown highlights that even with strong returns the portfolio experienced a sizable fall at some point. Recommendation: accept that high equity exposure can yield strong long term growth but also produce sharp interim losses; align allocations to the investor’s loss tolerance.
Projection
A Monte Carlo simulation was run with 1,000 trials to project possible outcomes using historical return and volatility patterns. Monte Carlo means running many randomised paths to estimate a range of futures rather than a single guess. The simulation shows end values at the 5th percentile ~369% and median ~972% of the start suggesting a high probability of positive long term outcomes under historical dynamics. Limitations: simulations assume past return distributions and correlations remain similar which may not hold. Recommendation: use these projections as scenario guides not guarantees and stress test with different market assumptions.
Asset classes
- No data 70%
- Stocks 30%
Assigned asset class metadata appears incomplete but the portfolio functions effectively as an equity only allocation given both ETFs are stock-based. Equity concentration increases growth potential but reduces traditional diversification benefits that come from fixed income or cash. Compared with cautious portfolio norms which usually include a meaningful bond sleeve, this mix is aggressive by asset class. Recommendation: to align with a cautious profile introduce a low-cost bond ETF or cash buffer to reduce overall volatility and improve capital preservation during negative market environments.
Sectors
- No data 70%
- Technology 11%
- Financials 4%
- Consumer Discretionary 3%
- Telecommunications 3%
- Health Care 3%
- Industrials 2%
- Consumer Staples 1%
- Energy 1%
- Utilities 1%
- Real Estate 1%
Sector breakdown shows a technology tilt at about 11% with smaller exposures across financials and consumer categories and minimal allocation to materials and energy. Sector balance close to benchmark weights supports diversification though the tech tilt can raise volatility, especially when interest rates rise or growth expectations change. Recommendation: review sector exposures periodically; if the goal is steadier returns consider modest rebalancing toward historically defensive sectors or increasing non equity holdings to buffer sector swings without attempting to time sector moves.
Regions
- No data 70%
- North America 30%
Geographic data indicates a meaningful North American emphasis alongside a large portion of global allocation that is not fully classified in the metadata. Heavy US exposure is common because US markets dominate global indices, but it can create single‑market risk. Geography affects currency, economic cycle and regulatory risk. Recommendation: confirm actual country and regional weights inside the global ETF and, if international or emerging market diversification is desired, consider topping up underrepresented regions to reduce dependence on one economy.
Market capitalization
- No data 70%
- Mega-cap 14%
- Large-cap 10%
- Mid-cap 5%
Market cap breakdown shows a strong large cap bias with combined mega and big cap exposure dominating and minimal small cap weight. Large caps typically offer greater liquidity and lower volatility than small caps but may limit potential excess returns that smaller companies can provide. This structure aligns with a quality and stability orientation but may underweight growth and recovery opportunities found in smaller firms. Recommendation: if the objective is higher long term growth and the investor can tolerate more volatility, consider a measured allocation to small or mid cap exposure.
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.
Efficient Frontier analysis identifies portfolios that offer the best expected return for a given level of risk where efficiency means an optimal risk‑return trade‑off given the available assets. With only two closely correlated equity ETFs the scope to materially improve efficiency by reweighting is limited; meaningful frontier shifts require adding lowly correlated asset classes like bonds or alternatives. Recommendation: for true optimization expand the asset set first then run mean‑variance optimization to find an allocation that better matches the desired risk profile and return target.
Ongoing product costs
- Invesco S&P 500 UCITS ETF 0.05%
- Weighted costs total (per year) 0.02%
The ETF expense data indicates very low costs with headline TER figures around a few basis points which is highly favourable. TER, or Total Expense Ratio, is the annual fee expressed as a percentage of assets and works like a maintenance charge that compounds over time; lower TERs directly improve net returns. Keeping costs low is a best practice and this portfolio aligns well with that principle. Recommendation: maintain low cost focus and periodically verify the effective blended expense ratio including trading spreads and any platform fees to preserve long term performance.
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