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Quant lab · Volatility

Volatility Z‑Score Z-Score

Paste your verified daily returns into the browser and observe where current rolling volatility sits relative to your own historical distribution. This is a research classifier, not a buy/sell signal.

Rolling σZ-ScoreClient‑side
Please paste at least 25 daily returns before starting.
Formula:rolling σ = sample standard deviation of window returns; Z =(current rolling σ − mean of all rolling σ)÷ standard deviation of all rolling σ. When samples are insufficient or volatility does not change, the tool preserves a visible error instead of producing a spurious Z value.
Regime lens

Position in the volatility distribution

Awaiting valid input
Current rolling volatility
Benchmark average
Sample count
number of rolling windows

rolling volatility series

Earlier observationsLatest observation
Data and limitations:Input data exists only in the current browser page; please state whether prices are adjusted close, the return frequency and the sample period. Z‑Score only describes relative position, not direction of volatility, future returns or a cap on risk. Z-Score

How to use this finance tool

This page turns a finance concept into checkable inputs, formulas, and scenarios. Read the variable definitions first, then compare conservative, base, and stress cases; one result is not a promise of return.

Suggested workflow: confirm units and time periods, enter your own assumptions, then review sensitivity, costs, and downside cases.

Limitations: the model does not forecast markets and may not include every tax, slippage, liquidity, credit, regulatory, or contract term. Verify important decisions with current primary information and a qualified professional.

Financial risk disclaimer

This page, its calculators, and examples are for education, research, and scenario estimation only. They are not personalized investment, trading, betting, tax, legal, or financial advice. Markets and local rules can change quickly; verify current primary information and take responsibility for your decisions. Past performance, model outputs, and simulations do not guarantee future results.