Frog (range volatility)
Frog is the population standard deviation of the daily High−Low range over the prior ~30 trading days, a measure of how erratic a symbol's daily bar size has been.
Frog measures the population volatility (standard deviation) of the daily High−Low range over roughly the last 30 trading days, excluding the current day. A large Frog means the bar size itself has been swinging widely; a small Frog means consistent daily ranges. Frog underpins position sizing on the Edge platform — it quantifies how much a single day's range can vary, which feeds risk-per-trade and stop placement decisions.
2.22e-16 on a 60-bar reference high/low series (canonical Python (edge-scan compute_frog_for_date) vs JavaScript (calcFrog30d), comparable positions).Pythonpermalink →
import numpy as np
def frog(high, low, n=30):
"""Frog — population standard deviation of the daily (High - Low) range
over the n trading days STRICTLY BEFORE the last bar.
Canonical math from edge-scan eod_indicators._frog_from_window /
compute_frog_for_date. The window is the n ranges preceding the final
bar (the current/target day is excluded — no look-ahead), and the
standard deviation is population (ddof=0).
Args:
high: sequence of daily highs, ascending by date.
low: sequence of daily lows, ascending by date (same length).
n: lookback window in trading days (default 30).
Returns:
float Frog value, or None if fewer than 2 observations in the window.
"""
high = np.asarray(high, dtype=float)
low = np.asarray(low, dtype=float)
ranges = high - low
# Window: up to n bars ending one position before the last bar.
# Excluding the final bar matches the chart-display / for_date convention.
idx = len(ranges) - 1
window = ranges[max(0, idx - n):idx]
if len(window) < 2:
return None
# Population standard deviation (ddof=0).
return float(np.std(window, ddof=0))
JavaScriptpermalink →
/**
* Frog — population standard deviation of the daily (High - Low) range over
* the last n trading days preceding the current day (the final bar excluded).
*
* Verbatim math from edge-canvas calcFrog30d. Bit-parity with the canonical
* Python (edge-scan compute_frog_for_date): population stddev (divide by N),
* window = the n bars strictly before the last/current bar.
*
* @param {Array<{high:number, low:number}>} eodCandles - Daily OHLC bars, ascending by date.
* @param {number} n - Lookback window in trading days (default 30).
* @returns {number|null} Frog value, or null if fewer than 2 observations.
*/
export function frog(eodCandles, n = 30) {
// Use up to n days PRECEDING the last bar (exclude the current day).
const win = Math.min(eodCandles.length - 1, n);
if (win < 2) return null;
// Window: the win bars ending one position before the final bar.
const window = eodCandles.slice(-(win + 1), -1);
const ranges = window.map((c) => c.high - c.low);
// Population variance (divide by N), then standard deviation.
const mean = ranges.reduce((s, v) => s + v, 0) / ranges.length;
const variance = ranges.reduce((s, v) => s + (v - mean) ** 2, 0) / ranges.length;
return Math.sqrt(variance);
}
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