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spctkd

Slow stochastics

Syntax

```[spctk, spctd] = spctkd(fastpctk, fastpctd)
[spctk, spctd] = spctkd([fastpctk fastpctd])
[spctk, spctd] = spctkd(fastpctk, fastpctd, dperiods, dmamethod)
[spctk, spctd] = spctkd([fastpctk fastpctd], dperiods, dmamethod)
skdts = spctkd(tsobj)
skdts = spctkd(tsobj, dperiods, dmamethod)
skdts = spctkd(tsobj, dperiods, dmamethod, 'ParameterName',ParameterValue, ...)
```

Arguments

 `fastpctk` Fast stochastic F%K (vector). `fastpctd` Fast stochastic F%D (vector). `dperiods` (Optional) %D periods. Default = `3`. `dmamethod` (Optional) %D moving average method. Default = `'e'` (exponential). `tsobj` Financial time series object.

Description

`[spctk, spctd] = spctkd(fastpctk, fastpctd)` calculates the slow stochastics S%K and S%D. `spctk` and `spctd` are column vectors representing the respective slow stochastics. The inputs must be single column-oriented vectors containing the fast stochastics F%K and F%D.

`[spctk, spctd] = spctkd([fastpctk fastpctd])` accepts a two-column matrix as input. The first column contains the fast stochastic F%K values, and the second contains the fast stochastic F%D values.

```[spctk, spctd] = spctkd(fastpctk, fastpctd, dperiods, dmamethod)``` calculates the slow stochastics, S%K and S%D, using the value of `dperiods` to set the number of periods and `dmamethod` to indicate the moving average method. The inputs `fastpctk` and `fastpctk` must contain the fast stochastics, F%K and F%D, in column orientation. `spctk` and `spctd` are column vectors representing the respective slow stochastics.

Valid moving average methods for %D are exponential (`'e'`), triangular (`'t'`), and modified (`'m'`). See `tsmovavg` for explanations of these methods.

```[spctk, spctd] = spctkd([fastpctk fastpctd], dperiods, dmamethod)``` accepts a two-column matrix rather than two separate vectors. The first column contains the F%K values, and the second contains the F%D values.

`skdts = spctkd(tsobj)` calculates the slow stochastics, S%K and S%D. `tsobj` must contain the fast stochastics, F%K and F%D, in data series named `PercentK` and `PercentD`. The `skdts` output is a financial time series object with the same dates as `tsobj`. Within `tsobj` the two series `SlowPctK` and `SlowPctD` represent the respective slow stochastics.

`skdts = spctkd(tsobj, dperiods, dmamethod)` lets you specify the length and the method of the moving average used to calculate S%D values.

```skdts = spctkd(tsobj, dperiods, dmamethod, 'ParameterName', ParameterValue, ...)``` accepts parameter name/parameter value pairs as input. These pairs specify the name(s) for the required data series if it is different from the expected default name(s). Valid parameter names are

• `KName`: F%K series name

• `DName`: F%D series name

Parameter values are the character vectors that represent the valid parameter names.

Examples

collapse all

This example shows how to calculate the slow stochastics for Disney stock and plot the results.

```load disney.mat dis_FastStoch = fpctkd(dis); dis_SlowStoch = spctkd(dis_FastStoch); plot(dis_SlowStoch) title('Slow Stochastics for Disney') ```

References

Achelis, Steven B. Technical Analysis from A to Z. Second Edition. McGraw-Hill, 1995, pp. 268–271.