Indicator Lab · RVI · Volatility
Relative Volatility Index
Assigns standard-deviation contributions by movement direction and normalizes their smoothed sums.
BTCUSDC · 1h · latest 30 complete days · shared snapshot · no account required
How is smoothed price dispersion distributed across positive and negative price changes?
Assigns standard-deviation contributions by movement direction and normalizes their smoothed sums.
One dataset, the same parameters and the same candle for application and explanation.
BTCUSDC · confirmed hourly candles
Snapshot retrieved: 11 Oct 2026, 15:52 UTC · stored snapshot · background refresh scheduled · age when opened: 3,138.6 min
11 Sept 2026, 15:00 — 11 Oct 2026, 15:00 UTC · 720 evaluation candles · 3000 earlier candles for warm-up only. Your opened snapshot stays fixed. A visit can refresh a stale cache in the background for later visitors; fetching fresh is not a tick stream.
Parameters and precise application
Number of confirmed hourly candles. Warm-up history stays fixed; only this parameter changes.
Explicit formula parameter of the calculation convention described below.
Measurement and diagnosis · no trading direction
Inspect the actual value at each confirmed candle. This analysis produces no buy or sell orders. Quoted thresholds refer to scalar=100 and are rescaled by scalar/100.
Preparing the calculation module. The shared market snapshot is already available.
Calculation and interpretation of the same candle
The dimensionless value describes the relative distribution of assigned dispersion, not an absolute stop distance.
scalar·EMAₙ(SDₙ(C)·1[ΔC>0]) / EMAₙ(SDₙ(C)·1[ΔC≠0])
Relative Volatility Index, close-only EMA variant. Rolling sample SD, not Relative Vigor.
RVI is not the Relative Vigor Index RVGI. It is neither annualized return volatility nor a future loss probability.
Checked sources and reproducibility
- pandas-ta 0.4.71b0 · pandas_ta/volatility/rvi.py
Verified original file from the versioned library; the implemented convention and deliberate differences accompany the formula. · checked 2026-10-11
- The Probability of Backtest Overfitting
Why selection across many historical trials can produce misleading results. This tool does not estimate PBO or claim out-of-sample profitability. · checked 2026-10-11
Data source, versions and hash
- Market data source
- https://data-api.binance.vision/api/v3/klines?symbol=BTCUSDC&interval=1h&startTime=1778338800000&endTime=1791730799999
- Specification
- indicator-library-1.0.0
- Execution model
- signal-simulation-1.0.0
- Data hash
- 42ac75e03e017bcac023d319dabb0928e0562fda0e51f4bfa5549ac50e3e8be4
- Disclosed candles including warm-up
- 3720
The sources support definitions and methodological limits. They do not establish profit for this specific BTCUSDC rule. This analysis is descriptive; parameter trials on the same history are not independent out-of-sample evidence. Parity with a deployed unCoded engine is not claimed.