priceBands: Construct (optionally further smoothed and centered )... In TTR: Technical Trading Rules

Description

John Bollinger's famous adaptive volatility bands most often use the typical price of an HLC series, or may be calculated on a univariate price series (see `BBands`).

Usage

 ```1 2``` ```PBands(prices, n = 20, maType = "SMA", sd = 2, ..., fastn = 2, centered = FALSE, lavg = FALSE) ```

Arguments

 `prices` A univariate series of prices. `n` Number of periods to average over. `maType` A function or a string naming the function to be called. `sd` The number of standard deviations to use. `...` any other pass-thru parameters, usually for function named by `maType`. `fastn` Number of periods to use for smoothing higher-frequency 'noise'. `centered` Whether to center the bands around a series adjusted for high frequency noise, default `FALSE`. `lavg` Whether to use a longer `(n*2)` smoothing period for centering, default `FALSE`.

Details

This function applies a second moving average denoted by `fastn` to filter out higher-frequency noise, making the bands somewhat more stable to temporary fluctuations and spikes.

If `centered` is `TRUE`, the function also further smoothes and centers the bands around a centerline adjusted to remove this higher frequency noise. If `lavg` is also `TRUE`, the smoothing applied for the middle band (but not the volatility bands) is doubled to further smooth the price-response function.

If you have multiple different price series in `prices`, and want to use this function, call this functions using `lapply(prices,PBands,...)`.

Value

A object of the same class as `prices` or a matrix (if `try.xts` fails) containing the columns:

dn

The lower price volatility Band.

center

The smoothed centerline (see details).

up

The upper price volatility Band.

Author(s)

Brian G. Peterson

`BBands`
 ```1 2``` ``` data(ttrc) pbands.close <- PBands( ttrc[,"Close"] ) ```