Indicator Lab · STOCHRSI · Momentum
Stochastic RSI
Applies stochastic range normalization to RSI rather than directly to prices.
BTCUSDC · 1h · latest 30 complete days · shared snapshot · no account required
Where is current RSI within its own recent range?
Applies stochastic range normalization to RSI rather than directly to prices.
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: 3,139.7 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.
Number of confirmed hourly candles. Warm-up history stays fixed; only this parameter changes.
Number of confirmed hourly candles. Warm-up history stays fixed; only this parameter changes.
Number of confirmed hourly candles. Warm-up history stays fixed; only this parameter changes.
Directional rule · long or cash
BUY on re-entry from ≤20 to >20; SELL from ≥80 to <80. Confirmed closes only; cash start, no shorts/pyramiding. Fills no earlier than the next open with fees and slippage. Thresholds are analysis conventions, not optimized recommendations.
Shared capital and cost model
Includes the buy fee; the remainder stays in cash.
One adverse markup/markdown. Do not add spread a second time.
1 = next open. No retroactive trade at the signal close.
Preparing the calculation module. The shared market snapshot is already available.
Calculation and interpretation of the same candle
A high value means RSI is near its local high even when absolute RSI itself is not extreme.
Raw=100·(RSI−min RSI)/(max RSI−min RSI); K=SMA(Raw,k); D=SMA(K,d)
TA-Lib RSI followed by separate rolling stochastic normalization and K/D SMA smoothing; zero RSI range is unavailable.
Double processing can amplify small RSI differences; a flat RSI range requires an explicit denominator convention.
Checked sources and reproducibility
- TA-Lib · STOCHRSI · v0.6.4
Original C reference implementation. Custom scaling and additional lines are described separately. · checked 2026-10-11
- pandas-ta 0.4.71b0 · pandas_ta/momentum/stochrsi.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.