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Description

This study calculates and displays the Inertia 2 study for the Price Data.

Let $C$ be a random variable denoting the Close Price, and let the Standard Deviation Length, Relative Volatility Index Length, and Linear Regression Length Inputs be denoted as $n_\sigma$, $n_{RVIX}$, and $n_{LR}$, respectively. We denote the Relative Volatility Index Up and Relative Volatility Index Down at Index $t$ as $RVIX^{(U)}_t(n_\sigma)$ and $RVIX^{(D)}_t(n_\sigma)$, respectively, and we compute them in terms of a Standard Deviation for $t \geq \max\{n_\sigma, n_{RVIX}, n_{LR}\}$ as follows.

Next we compute the Smoothed Relative Volatility Index Up and Smoothed Relative Volatility Index Down. The values of these at Index $t$ are denoted as $\overline{RVIX}^{(U)}_t(n_\sigma,n_{RVIX})$ and $\overline{RVIX}^{(D)}_t(n_\sigma,n_{RVIX})$, respectively. These both have the value $0$ for $t < \max\{n_\sigma, n_{RVIX}, n_{LR}\}$. We compute them for $t \geq \max\{n_\sigma, n_{RVIX}, n_{LR}\}$ as follows.

We denote the Relative Volatility Index at Index $t$ as $RVIX_t(n_\sigma,n_{RVIX})$, and we compute it for $t \geq \max\{n_\sigma, n_{RVIX}, n_{LR}\}$ as follows.

Finally, we denote Inertia 2 at Index $t$ as $Inertia^{(2)}_t(n_\sigma,n_{RVIX},n_{LR})$. It is a Moving Linear Regression of the Relative Volatility Index, and we compute it for $t \geq \max\{n_\sigma,n_{RVIX},n_{LR}\}$ as follows.