Stock/ETF Risk Analysis: 4 Calculated Metrics
This tool calculates four standard risk metrics from historical close prices you paste manually. All calculations run locally in your browser — no data is sent to any server or API.
Daily Volatility (σ_daily)
Standard deviation of all daily returns in the selected period. Formula: σ = √( Σ(rᵢ − r̄)² / (n−1) ). Reflects day-to-day price movement size.
Annualized Volatility
σ_daily × √252 (252 = standard trading days/year). The universal benchmark for comparing volatility across assets and time horizons.
Average Daily Return (r̄)
Arithmetic mean of all daily returns. Positive = net upward trend in the selected period; negative = downward. Not an annualized figure.
Sharpe Ratio
(r̄_daily − rf_daily) ÷ σ_daily. Measures return per unit of risk. Enter your risk-free rate (e.g. ECB deposit rate) in the "Risk-free rate" field; leave at 0 to get a pure return/vol ratio.
How to Read the Risk Traffic Light
The traffic light classifies the annualized volatility into three zones. The default thresholds are calibrated for standard equity instruments. You can switch to Conservative or Aggressive presets in the settings:
| Signal | Standard Threshold | Conservative | Aggressive | Typical for |
|---|---|---|---|---|
| 🟢 Low Risk | < 15% p.a. | < 10% p.a. | < 20% p.a. | Bond ETFs, Money Market, Low-Vol Equity |
| 🟡 Medium Risk | 15–30% p.a. | 10–25% p.a. | 20–40% p.a. | Broad equity ETFs (MSCI World ~14–18%), Blue Chips |
| 🔴 High Risk | > 30% p.a. | > 25% p.a. | > 40% p.a. | Single tech stocks, Crypto-adjacent, Emerging Markets, Small Caps |
Historical reference (2024): MSCI World ~14–17% annualized vol, S&P 500 ~13–16%, Bitcoin ~55–70%. These change constantly — the value of entering your own data is that you see the actual realized volatility for your specific holding period, not a generalized estimate.
Supported Data Formats
The tool accepts manual data entry. You can export closing prices from any broker, Yahoo Finance, or Google Finance and paste them directly. Supported formats:
| Format | Example | Use case |
|---|---|---|
| Date + Close (2 columns) | 2025-12-02, 100.5 or 2025-12-02; 100,5 | Volatility & Sharpe — sufficient for all metrics |
| OHLC (4 columns) | 2025-12-02, 99.0, 102.1, 98.5, 100.5 | Enables Candlestick chart in addition to bar chart |
| Separator | Comma, semicolon (Excel DE), or Tab | Auto-detected; no manual setting needed |
| Decimal | Period (100.5) or comma (100,5) | Auto-detected; works with German Excel exports |
Tip: Use the "Load Example Data" button to see a correctly formatted dataset before entering your own. The calculation updates live as you type or paste — no submit button needed.
Frequently Asked Questions
Why does the tool use 252 trading days and not 365?
Stock markets are closed on weekends and public holidays, which means a typical year has approximately 252 actual trading days. Using 252 is the industry standard for annualizing daily volatility and returns. Using 365 would overstate the annualized volatility because it counts non-trading days as if they contributed to price movement. The calculator uses a fixed 252 regardless of the input date range.
What risk-free rate should I enter for the Sharpe Ratio?
Enter the annualized risk-free rate as a percentage. The tool converts it to a daily equivalent (rf ÷ 252) internally. For a eurozone investor as of early 2026, the ECB deposit rate (~3.0–3.5%) or the yield of a short-term German government bond (Bundesanleihe) are common choices. If you set it to 0, the Sharpe ratio simply shows return divided by volatility without subtracting a risk premium — useful for comparison purposes but not the strict finance-textbook definition.
How many data points do I need for a meaningful result?
At minimum 10–15 data points for a rough estimate; 60+ (about 3 months of daily data) for a reasonably stable volatility estimate; 252+ (1 year) for a meaningful annualized volatility. The tool labels each analysis with the actual number of observations. For very short series (< 20 points), treat results as directional indicators only — the standard deviation estimate has high uncertainty.
Can I analyze weekly or monthly data instead of daily?
Yes, but you need to change the annualization factor manually in your interpretation. The tool always multiplies by √252 (daily assumption). If you enter weekly data, the correct annualization would be ×√52; monthly data ×√12. Currently the calculator does not auto-detect data frequency — treat the output accordingly if you use non-daily prices.
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