Login Page - Create Account

Technical Studies Reference


Gann HiLo Activator

This study calculates and displays a Gann HiLo Activator of the Price Data. The indicator was introduced by Robert Krausz in his book W.D. Gann - Treasure Discovered.

Let \(H\), \(L\), and \(C\) be random variables denoting the High, Low, and Close Prices, respectively, and let \(H_t\), \(L_t\), and \(C_t\) be their respective values at Index \(t\). Let the Input Length be denoted as \(n\).

We introduce a function \(HiLo_t(n)\) and compute it for \(t \geq n\) in terms of Simple Moving Averages as follows.

\(\displaystyle{HiLo_t(n) = \left\{ \begin{matrix} 1 & C_t > SMA_{t - 1}(H,n) \\ 0 & SMA_{t - 1}(L,n) \leq C_t \leq SMA_{t - 1}(H,n) \\ -1 & C_t < SMA_{t - 1}(L,n) \end{matrix}\right .}\)

Note: Depending on the setting of the Input Moving Average Type, the Simple Moving Averages in the above formula could be replaced with Exponential Moving Averages, Linear Regression Moving Averages, Weighted Moving Averages, Wilders Moving Averages, Simple Moving Averages - Skip Zeros, or Smoothed Moving Averages.

We denote the Gann HiLo Activator as \(GHLA_t(n)\), and we compute it as follows.

\(\displaystyle{GHLA_t(n) = \left\{ \begin{matrix} SMA_{t - 1}(L,n) & HiLo_t(n) = 1 \\ GHLA_{t - 1}(n) & HiLo_t(n) = 0 \\ SMA_{t - 1}(H,n) & HiLo_t(n) = -1 \end{matrix}\right .}\)

The Subgraph of the Gann HiLo Activator is colored as follows.

  • \(HiLo_t(n) = 1 \Rightarrow\) Green
  • \(HiLo_t(n) = -1 \Rightarrow\) Red
  • \(HiLo_t(n) = 0 \Rightarrow\) Color at previous chart bar

Inputs


*Last modified Wednesday, 26th June, 2019.