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예시 포트폴리오 — 미국 분산 (AAPL · MSFT · SPY · TLT)
●Markowitz · Portfolio personality
The Easygoing Stroller평화주의 산책꾼
Spreading assets wide brings you peace of mind as you head, slowly, toward your destination.
Key metrics · annualized
Annual σ
15.43%
Prices swing an average of 15.4% up and down per year.
Expected μ
+11.45%
Past average implies +11.4% return per year.
Efficiency (Sharpe)
0.48
Earns 0.48 per unit of risk — moderate.
95% VaR
-13.92%
A 95% chance annual loss stays within 13.9%.
Activation Guide
Guide: 4 ways to use the analysis result
Markowitz · Quick guide
Focus on your portfolio’s volatility and diversification. Set a volatility target that fits your strategy and adjust the portfolio accordingly. Use assets that are farther apart on the correlation map to improve the efficiency measure.
Visualization
Max return at the same risk level
The efficient frontier traces the maximum expected return achievable at each level of volatility. If your portfolio sits below the curve, a different weight combination could yield more return at the same risk; on the curve means already efficient.
Current diversification · 19.9%Sharpe · 0.48
Interpretation
3 takeaways
RiskLow volatility · in line with market — σ 15.43%
An annual σ of 15.43% is, in absolute terms, a bond-blended balanced profile or a low-volatility broad index. It sits essentially in line with the market benchmark (σ 15.6%, ~1.0×). (Annual 95% VaR -13.9%. σ assumes a normal distribution, so real losses can exceed it.)
EfficiencySharpe 0.48 — modest
Sharpe 0.48 sits in the range typical of long-run global equities (about 0.25–0.40 by empirical work like Dimson-Marsh-Staunton) — roughly the market's historical efficiency, not above it. Often one or two laggards in your larger positions are quietly dragging on this number.
DiversificationDiversification 19.9% — moderate
Diversification of 19.9% is the normal range for a portfolio that mixes asset classes — stocks with bonds, or domestic with overseas. There's enough low-correlation material in the mix that one leg can cushion another when conditions turn.
Next step
How much of this return came from the market?
Run the same portfolio through the Market Check (CAPM) to split your return and risk into the part the market explains and the alpha it does not.
FAQ
Frequently asked questions
Questions newcomers to this model commonly ask. Click any question to expand the answer.
Can I trade exactly the way the analysis suggests?
No, that is not recommended. Every analysis here is a statistical estimate based on historical market data, and it does not guarantee future returns or losses. Trading costs, taxes, FX costs, market impact, and your own investment goals and horizon are also not reflected. Use the results as a diagnostic of "what kind of risk and return profile this portfolio has", and before any real investment decision review your own situation and consider consulting a qualified professional.
I re-ran the analysis on the same tickers but the result is slightly different — why?
That is expected. Each run fetches the latest prices from yfinance and recalculates. When new trading days arrive or the factor data is updated between runs, the sample changes and the means, variances and regression coefficients shift slightly. The risk-free rate used for the Sharpe ratio (the US 13-week T-bill yield) is also refreshed daily. If the change is large (e.g. alpha flips sign, or a beta moves more than 0.3), the sample may be too short for stable results — check the analysis reliability score at the top of the result page.
How are Korean and US stocks handled together?
Holding amounts are converted to KRW at the FX rate at analysis time to set the weights. Returns, however, are calculated from each holding's local-currency price, so the returns and volatility of US holdings do not include KRW/USD exchange-rate moves. If you invest in won, your actual account can swing more or less than shown, by the amount the exchange rate moves. Markowitz and HRP analyze holdings from both markets as one portfolio. Fama–French (3- / 5-factor) regresses Korean holdings on DIVA's own Korea factors and US holdings on factors from the Kenneth French Data Library, then combines the two by portfolio weight into a single result.
How is the "analysis reliability" score calculated?
A 0–100 measure of how much the numbers could shift because of limited data or chance (not whether the portfolio is good). For Markowitz and HRP it averages ① the risk estimate (data window, and window length relative to the number of holdings) and ② the return estimate (the 95% error range of the past average return), so the same portfolio over the same window scores the same in both. Fama–French averages the beta estimate (window and beta error range) and explanatory power (R²). 75+ reliable, 55+ worth referencing, 35+ read conservatively, below that interpret with care. A heuristic for reference, not an academic standard.
My portfolio dot sits far to the left (lower volatility) of my holdings' average — is that a bug?
It is not a bug — it is diversification working exactly as the theory predicts. Portfolio volatility is not the average of each holding's volatility; it also reflects how much the holdings move together (correlation). When assets from different sectors and markets swing at different times, their swings partially cancel out, trimming the portfolio's overall volatility. With low enough correlations, the portfolio can end up less volatile than the average — and even less volatile than the single calmest holding. That is the core result of Markowitz's theory. The further left the dot sits, the better diversified you are, and the gap versus the average is the "diversification benefit" figure in your result.
Why isn't a single "optimal weight set" shown in the result?
The efficient frontier is a curve, not a point, and there are infinitely many "optimal" points along it. Which one to recommend — max Sharpe (tangency), min variance, target-return — depends on the goal, and mean-variance optimization is famously sensitive to the input estimates of means and covariance. We deliberately do not push a single "optimal weight" recommendation. Instead, we plot your portfolio on the efficient-frontier curve so you can see "how much room there is to improve return at the same risk", and we leave the rebalancing call to you.
Is a Sharpe ratio above 1 always good?
Industry convention is that an annualized Sharpe above 1.0 is "healthy" and above 2.0 is "excellent", but if the window leans bull-market it will overstate the true ratio. Sharpe is (return − risk-free) / volatility, so any window where volatility happened to be unusually low gets a flattering numerator-to-denominator ratio. The normal-distribution assumption behind volatility also underweights tail risk (black swans), so realized risk-adjusted rewards can be lower than Sharpe suggests. Check the analysis window and the return-estimate error range on the reliability card. DIVA uses up to 72 months (6 years), and the window shrinks to the holding with the shortest history — the shorter the window, the wider the error on Sharpe.
Does "VaR 95% = −10%" mean a 5% chance of losing 10% in a year?
More precisely: "under normal market conditions, the probability of losing more than 10% within one year is 5% or less". We use parametric VaR with a normal-distribution assumption, which fits typical markets but underestimates realized losses during shocks (financial crises, wars, pandemics — i.e. tail risk). Read VaR as a "normal-market lower bound", not a worst-case ceiling, and pair it with a more conservative scenario for real money management.
Is diversification near 0% always bad?
It depends on the intent. Low diversification means your holdings move almost in lockstep — usually a sign of sector / theme / country concentration. If "diversify" is the goal, add assets or rebalance to lift the effect. If you intentionally bet on a single sector or theme, low diversification is a natural consequence and not a problem in itself — just be aware that single-name blow-up risk rises with concentration.
How can I tell whether my portfolio sits exactly on the efficient frontier?
On the "Efficient frontier" chart you can visually see whether your portfolio sits on the curve (green marker) or below it (red marker). Below the curve means there is a weight mix that achieves higher return at the same volatility, and a dashed line illustrates the gap. Important: "on the curve" does not mean "perfect" — the curve itself depends on the sample's mean / covariance estimates, and out-of-sample the curve can take a different shape.