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Description

This study calculates and displays the Connors RSI, as developed by Connors Research.

Let \(X\) be a random variable denoting the Input Data Input. Let the Inputs RSI Length and Rate of Change Length be denoted as \(n_{RSI}\) and \(n_{ROC}\), respectvely.

We begin by computing the standard RSI using the Wilders Moving Average by default. This can be changed by appropriately setting the RSI Average Type Input.

We then define the Up-Down Length, denoted as \(UDL_t(X)\). This is a backward-looking calculation of the number of consecutive bars (starting with the current two bars) that the value of \(X\) has been either higher or lower than than the previous bar. Let \(N\) denote this number. We then compute \(UDL_t(X)\) as follows.

We then compute \(RSI_t(UDL(X),2)\).

Next we define the Rate of Change, denoted as \(ROC_t(X,n_{ROC})\) This is the percentage of the previous \(n_{ROC}\) bars for which the price change from one bar to the next is less than the current price change. Denote the current price change as \(Delta X_t = X_t - X_{t - 1}\), and denote the price change \(i\) bars ago as \(\Delta X_{t - i} = X_{t - i} - X_{t - i - 1}\). Define \(n_i\) as follows.

We then compute \(ROC_t(X,n_{ROC})\) as follows.

Finally, we denote the Connors RSI as \(RSI^{(C)}_t(X,n_{RSI},n_{ROC})\) and compute it as follows.

In addition to displaying the Subgraph for \(RSI^{(C)}_t(X,n_{RSI},n_{ROC})\), it also displays horizontal lines at levels determined by the Line 1 Value and Line 2 Value Inputs.