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Stochastic


Double Stochastic

This study calculates and displays the Double Stochastic study.

Inputs

Double Stochastic - Bressert

This study calculates and displays the Double Stochastic using the Bressert calculation method.

Inputs

KD - Fast

The Stochastic study compares where a symbols price closed relative to its price range over a given time period as specified by the Length Inputs.

Inputs

KD - Slow

The Stochastic study compares where a symbols price closed relative to its price range over a given time period as specified by the Length Inputs.

The Stochastic-Slow study differs from Stochastic-Fast, by calculating a moving average of the Fast %D line. This result is known as the Slow %D. The study displays the Fast %D (Slow %K) line and the Slow %D line.

Inputs

Preferred Stochastic - DiNapoli

This study calculates a special Stochastic.

Stochastic - Fast

The Stochastic oscillator compares where a symbol's price closed relative to its price range over a given time period.

Stochastic - Percentile

The study calculates at each chart bar the percentile rank of the most recent price as specified by the Input Data Input, in a group of prices going back from the current bar by the number of bars specified by the Length Input \(n\).

The prices are arranged in ascending order and ranked from lowest to highest, starting with a rank of 0. The maximum rank will have a value of Length - 1.

The rank \(R\) of the most recent price is used to calculate the Stochastic - Percentile \(S\) as follows.

$$S = \frac{100R}{n - 1}$$

Stochastic - Slow

The Stochastic oscillator compares where a symbol's price closed relative to its price range over a given time period. The Stochastic-Slow study differs from Stochastic-Fast, by calculating a moving average of the Fast %D line. This result is known as the Slow %D. The study displays the Fast %D (Slow %K) line and the Slow %D line.

Inputs

Stochastic Crossover System

The Stochastic Crossover System is a study which displays Up and Down Arrows representing Buy and Sell signals, on the chart based upon the crossover of the Stochastic Slow %K and Slow %D lines.

If Slow %K crosses Slow %D from the bottom and (Slow %K is below Line 2 or Use Buy/Sell Lines is set to No), then a Buy signal is given with an Up Arrow below the Low of the current bar.

If Slow %K crosses Slow %D from the top and (Slow %K is above Line 1 or Use Buy/Sell Lines is set to No), then a Sell signal is given with a Down Arrow above the High of the current bar.

Inputs

Stochastic Momentum Indicator

The Stochastic Momentum Indicator study calculates and displays the Stochastic Momentum Indicator.

Inputs

Stochastic RSI

Calculates and displays the Stochastic RSI study for Close (Last) Price data. The RSI is used in the calculation.

Let \(C\) be a random variable denoting the Close Price, and let \(C_t\) be the value of the Close Price at chart bar \(t\). Then the RSI of \(C\) with RSI Length \(n\) at chart bar \(t\) is denoted as \(RSI_t(C,n)\). The type of Moving Average used in the RSI calculation is determined by the RSI Average Type Input.

Let the RSI HighestLowest Length Input be denoted as \(n_{HL}\). We denote the maximum and minimum values of \(RSI_t(C,n)\) over a sliding window of Length \(n_{HL}\) at chart bar \(t\) as \(MaxRSI_t\left(C,n,n_{HL}\right)\) and \(MinRSI_t\left(C,n,n_{HL}\right)\), respectively. We compute them as follows.

\(MaxRSI_t\left(C,n,n_{HL}\right) = \max\{RSI_{t - n_{HL} + 1}(C,n), RSI_{t - n_{HL} + 2}(C,n), ... , RSI_t(C,n)\}\)

\(MinRSI_t\left(C,n,n_{HL}\right) = \min\{RSI_{t - n_{HL} + 1}(C,n), RSI_{t - n_{HL} + 2}(C,n), ... , RSI_t(C,n)\}\)

We denote the Stochastic RSI for the given Inputs at chart bar \(t\) as \(StochRSI_t\left(C,n,n_{HL}\right)\), and we compute it with the following recursion relation.

\(StochRSI_0\left(C,n,n_{HL}\right) = 0\)

\(\displaystyle{StochRSI_t\left(C,n,n_{HL}\right) = \left\{ \begin{matrix} \frac{RSI_t(C,n) - MinRSI_t\left(C,n,n_{HL}\right)}{MaxRSI_t\left(C,n,n_{HL}\right) - MinRSI_t\left(C,n,n_{HL}\right)} & MaxRSI_t\left(C,n,n_{HL}\right) - MinRSI_t\left(C,n,n_{HL}\right) \neq 0 \\ StochRSI_{t - 1}\left(C,n,n_{HL}\right) & MaxRSI_t\left(C,n,n_{HL}\right) - MinRSI_t\left(C,n,n_{HL}\right) = 0 \end{matrix}\right .}\)

Inputs


*Last modified Thursday, 20th April, 2017.