fintech-algorithms
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Using a coding agent? Give it the skill: npx skills add IslamBaraka90/Fintech-Algorithms-Library What it does →

Historical Estimators

5 algorithms in Volatility and Covariance · 5 with asserted arithmetic.

In this family#

  1. Close-to-Close Volatility verified

    Observe a close shock enter and leave centered return dispersion. Supplied-parameter educational reference; no fitted performance claim.

    calculate(data)
  2. Parkinson Volatility verified

    Change intraday range while keeping endpoint prices fixed. Supplied-parameter educational reference; no fitted performance claim.

    calculate(data)
  3. Garman-Klass Volatility verified

    See the range term and body correction under valid OHLC geometry. Supplied-parameter educational reference; no fitted performance claim.

    calculate(data)
  4. Rogers-Satchell Volatility verified

    Track the upper and lower log-distance products. Supplied-parameter educational reference; no fitted performance claim.

    calculate(data)
  5. Yang-Zhang Volatility verified

    Separate overnight, weighted body and weighted range contributions. Supplied-parameter educational reference; no fitted performance claim.

    calculate(data)

What they share#

Every topic here is a record-transform, so once you have called one the rest follow the same shape. Import paths differ only in the final segment:

ts
import { calculate } from "fintech-algorithms/volatility-and-covariance/historical-estimators/close-to-close-volatility";
import { calculate } from "fintech-algorithms/volatility-and-covariance/historical-estimators/parkinson-volatility";

Read them in the order above — the sequence is pedagogical, not alphabetical.

Where this sits#

Volatility and Covariance collects 22 algorithms across 4 families. For the concept behind this family rather than the call signatures, see the concept guides.