Using The AM/GM Inequality To Estimate Volatility

// This source code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © alexgrover
// ------------------------------------------------------------------------------------------------
// Original author:  alexgrover
// Original title:   Using The AM/GM Inequality To Estimate Volatility
// Licence:          MPL-2.0 (the header above is the original notice, kept verbatim)
// Pine version:     4
// Fetched:          2026-10-12
// Ported to FloScript by FloSignals; modifications under MPL-2.0.
// Converter:        @flosignals/floscript 0.1.0, strict mode, score 100/100
// ------------------------------------------------------------------------------------------------
//@floscript=1
//@version=5
// Converted by the FloScript converter from a Pine-compatible v4 source.

indicator("Using The AM/GM Inequality To Estimate Volatility")
length = input(14)
src = input(close)
//----
sma = ta.sma(src, length) // Our arithemtic moving average
g = 1. // We will use multiplication, you don't want to intialize "g" with 0
for i = 0 to length - 1
    g := g * src[i]
gma = math.pow(g, 1 / length) // A power using 1/n as exponent is equivalent to an nth square root
//----
//You can also compute the geometric moving average using:
//gma = exp(sma(log(src),length))
//It's shorter and allows for more efficient computations using a cumulative sum:
//csum = cum(log(close))
//gma = exp(mom(csum,length)/length)
//----
v = math.sqrt(sma - gma)
plot(v, "Plot", #009688)

This file is under the Mozilla Public License 2.0; it is a port of the original by alexgrover, with the original licence header kept and the changes made for FloScript noted in the file.

• v22026-10-14

  Library refresh 2026-10-14

• v12026-10-12

  Library refresh 2026-10-12