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Technical Studies Reference


Repulse

This study calculates and displays a Repulse indicator of the price data.

Let \(O\), \(H\), \(L\), and \(C\) be random variables denoting the Open, High, Low, and Close Prices, respectively, and let their respective values at Index \(t\) be \(O_t\), \(H_t\), \(L_t\), and \(C_t\).

We denote the Highest High and Lowest Low at Index \(t\) over \(n\) periods as \(\max_t(H,n)\) and \(\min_t(L,n)\), respectively, and we compute them for \(t \geq 0\) as follows.

\(\max_t(H,n) = \displaystyle{ \left\{ \begin{matrix} \max\{H_0,...,H_t\} & t < n - 1 \\ \max\{H_{t - n + 1},...,H_t\} & t \geq n - 1 \end{matrix}\right .}\)

\(\min_t(L,n) = \displaystyle{ \left\{ \begin{matrix} \min\{L_0,...,L_t\} & t < n - 1 \\ \min\{L_{t - n + 1},...,L_t\} & t \geq n - 1 \end{matrix}\right .}\)

Let the Length Input be denoted as \(n\). Then we denote the Bullish Weighting and the Bearish Weighting for the given Input as \(W^{(Bull)}_t(n)\) and \(W^{(Bear)}_t(n)\), respectively, and we compute them for \(t \geq 0\) as follows.

\(W^{(Bull)}_t(n) = \displaystyle{\left\{ \begin{matrix} 100\cdot\frac{3C_t - 2\min_t(L,n) - O_0}{C_t} & t < n - 1 \\ 100\cdot\frac{3C_t - 2\min_t(L,n) - O_{t - n + 1}}{C_t} & t \geq n - 1 \end{matrix}\right .}\)

\(W^{(Bear)}_t(n) = \displaystyle{\left\{ \begin{matrix} 100\cdot\frac{O_0 + 2\max_t(H,n) - 3C_t}{C_t} & t < n - 1 \\ 100\cdot\frac{O_{t - n + 1} + 2\max_t(H,n) - 3C_t}{C_t} & t \geq n - 1 \end{matrix}\right .}\)

Finally, we denote Repulse at Index \(t\) for the given Input as \(Repulse_t(n)\), and we compute it in terms of Exponential Moving Averages of the Bullish and Bearish Weightings for \(t \geq 0\) as follows.

\(Repulse_t(n) = EMA_t\left(W^{(Bull)}(n),5n\right) - EMA_t\left(W^{(Bear)}(n),5n\right)\)

Inputs

Spreadsheet

The spreadsheet below contains the formulas for this study in Spreadsheet format. Save this Spreadsheet to the Data Files Folder.

Open it through File >> Open Spreadsheet.

Repulse.392.scss


*Last modified Friday, 02nd February, 2018.