Example Data Table
This sample shows a simple three asset portfolio.
| Asset |
Weight |
Standard Deviation |
Correlation Notes |
| Equity Fund |
50% |
18% |
0.15 with bonds, 0.45 with real estate. |
| Bond Fund |
30% |
6% |
0.10 with real estate. |
| Real Estate Fund |
20% |
12% |
Moderate link with equities. |
Formula Used
The calculator uses the portfolio variance formula. It includes weights, individual risk, and pairwise correlation.
σp = √[ Σ wi²σi² + 2Σ wi wj σi σj ρij ]
Here, σp is portfolio standard deviation. wi is each asset weight.
σi is each asset standard deviation. ρij is the correlation between two assets.
The calculator also computes variance, diversification benefit, and risk contribution.
How to Use This Calculator
- Select the number of assets in your portfolio.
- Enter each asset name, portfolio weight, and standard deviation.
- Enter pairwise correlations between selected assets.
- Use normalization when weights do not total exactly 100%.
- Press the calculate button to view risk results.
- Download the result as CSV or PDF for records.
Understanding Portfolio Standard Deviation
Portfolio standard deviation measures total portfolio volatility. It shows how widely portfolio returns may move around their average value. A larger value means higher return uncertainty. A smaller value usually means steadier performance. This calculator helps investors compare that risk before changing an allocation.
Why Correlation Matters
Asset risk alone does not explain portfolio risk. Correlation also matters. Two risky assets can reduce total risk when they move differently. A negative or low correlation can improve diversification. A high positive correlation can make assets behave like one large position.
Weight Effects
Portfolio weights control how much each asset affects the result. A small position may have limited impact, even when it has high volatility. A large position can dominate risk. That is why the calculator shows both used weights and contribution percentages.
Advanced Risk Review
The variance result gives the squared risk value. Standard deviation converts it back into a percentage. Component volatility shows how much each asset adds to total volatility. This makes the output useful for allocation reviews, fund comparisons, and rebalancing checks.
Practical Interpretation
The result is not a return forecast. It is a risk estimate based on your inputs. Better inputs give better estimates. Use recent or long-term deviation values depending on your investment horizon. Review correlations often because markets can change during stress periods. A portfolio that looks diversified in calm markets may behave differently during large drawdowns.
Using the Export Options
The CSV file is useful for spreadsheet analysis. The PDF option is useful for reports and client notes. Keep a copy before and after rebalancing. This gives a clear record of how each change affected expected portfolio volatility.
FAQs
What is portfolio standard deviation?
It is a measure of total portfolio volatility. It estimates how much returns may vary around the average portfolio return.
Why do I need correlations?
Correlations show how assets move together. They help estimate diversification effects across the full portfolio.
Should weights total 100%?
Yes, portfolio weights should normally total 100%. You can enable normalization when the entered weights are slightly different.
Can correlations be negative?
Yes. Negative correlation means two assets often move in opposite directions. This can reduce portfolio volatility.
What does diversification benefit mean?
It is the difference between weighted average volatility and calculated portfolio volatility. A higher value suggests better diversification.
What is component volatility?
Component volatility estimates how much each asset contributes to total portfolio standard deviation.
Can this calculator predict losses?
No. It estimates volatility from inputs. It does not guarantee future returns, losses, or market behavior.
Why might my result look wrong?
Check weights, deviations, and correlations. Unrealistic correlations can create unreliable portfolio variance results.