Logarithmic Bollinger BandsLogarithmic Bollinger Bands
Published by Eric Thies on January 14, 2022
Summary
In this script I have taken the standard Bollinger band pinescript and made efforts to eliminate the behavior experienced in periods of high volatility in which we see the bands disappear completely off the chart by adding exponential plotting and logarithmic sourcing to the tool.
This tool will also show periods of Bearish and Bullish Expansion for users to see when volatility is running high in the market.
More On Bollinger Bands
Bollinger Bands consist of a center line representing the moving average of a security’s price over a certain period, and two additional parallel lines (called the upper and lower trading bands) one of which is just the moving average plus k-times the standard deviation over the selected time frame, and the other being the moving average minus k-times the standard deviation over that same timeframe. This technique has been developed in the 1980’s by John Bollinger, who lately registered the terms “Bollinger Bands” as a U.S. trademark in 2011. Technical analysts typically use 20 periods and k = 2 as default settings to build Bollinger Bands, while they can choose a simple or exponential moving average. Bollinger Bands provide a relative definition of high and low prices of a security. When the security is trading within the upper band, the price is considered high, while it is considered low when the security is trading within the lower band.
There is no general consensus on the use of Bollinger Bands among traders. Some traders see a buy signal when the price hits the lower Bollinger Band and close their position when the price hits the moving average. Some others buy when the price crosses over the upper band and sell when the price crosses below the lower band. We can see here two opposing interpretations based on different rationales, depending whether we are in a reversal or continuation pattern. Another interesting feature of the Bollinger Bands is that they give an indication of the volatility levels; a widening gap between the upper and lower bands indicates an increasing volatility, while a narrowing band indicates a decreasing volatility. Moreover, when the bands have an almost flat slope (parallel to the x-axis) the price will generally oscillate between the bands as if trading through a channel.
// © 2022 KINGTHIES THIS SOURCE CODE IS SUBJECT TO TERMS OF MOZILLA PUBLIC LICENSE 2.0 (MOZILLA.ORG/MPL/2.0)
//@version=5
//## !<---------------- © KINGTHIES --------------------->
indicator('Logarithmic Bollinger Bands (kingthies)',shorttitle='LogBands_KT',overlay=true)
// { BBANDS
src = math.log(input(close,title="Source"))
lenX = input(20,title='lenX')
highlights = input(false,title="Highlight Bear and Bull Expansions?")
mult = 2
bbandBasis = ta.sma(src,lenX)
dev = 2 * ta.stdev(src, 20)
upperBB = bbandBasis + dev
lowerBB = bbandBasis - dev
bbw = (upperBB-lowerBB)/bbandBasis
bbr = (src - lowerBB)/(upperBB - lowerBB)
// }
// { BBAND EXPANSIONS
bullExp= ta.rising(upperBB,1) and ta.falling(lowerBB,1) and ta.rising(bbandBasis,1) and ta.rising(bbw,1) and ta.rising(bbr,1)
bearExp= ta.rising(upperBB,1) and ta.falling(lowerBB,1) and ta.falling(bbandBasis,1) and ta.rising(bbw,1) and ta.falling(bbr,1)
// }
// { COLORS
greenBG = color.rgb(9,121,105,75), redBG = color.rgb(136,8,8,75)
bullCol = highlights and bullExp ? greenBG : na, bearCol = highlights and bearExp ? redBG : na
// }
// { INDICATOR PLOTTING
lowBB=plot(math.exp(lowerBB),title='Low Band',color=color.aqua),plot(math.exp(bbandBasis),title='BBand Basis',color=color.red),
highBB=plot(math.exp(upperBB),title='High Band',color=color.aqua),fill(lowBB,highBB,title='Band Fill Color',color=color.rgb(0,128,128,75))
bgcolor(bullCol,title='Bullish Expansion Highlights'),bgcolor(bearCol,title='Bearish Expansion Highlights')
// }
Indicator
Kelt + BBand Combination (kingthies) █ Overview
The Kelt-BBand Combo is a trading approach that I've used for multiple years now, and works on any timeframe, chart possible. There are various versions of this approach published by myself and others who find value in measuring the deviations of price and strategize market entries and exits. For an entry-level description of each component, I'll type them up below.
█ Using This Indicator
While there are various strategies to use this tool, I'll share the one that has yielded me the most success across traditional and cryptocurrency markets - first understand the different appearances of both....
IF the bbands are inside the kelts, the squeeze is on. In 90% of cases this is often a bullish leaning event
IF the bbands are pinching (regardless of slope or kelt behavior),these are your primary support and resistances, respectively
When trending up, HA candles will touch between the upper kelt and upper bband on every candle, across all timeframes
When trending down, HA candles will touch between the lower kelt and lower bband on every candle, across all timeframes
If one timeframe is not giving clear indicator of trend direction or s/r to follow, zoom out. the higher timeframe will always win and show you the true direction
█ Intro to Bollinger Bands
Bollinger Bands consists of a center line representing the moving average of a security’s price over a certain period, and two additional parallel lines (called the trading bands) one of which is just the moving average plus k-times the standard deviation over the selected time frame, and the other being the moving average minus k-times the standard deviation over that same timeframe. This technique has been developed in the 1980’s by John Bollinger, who lately registered the terms “Bollinger Bands” as a U.S. trademark in 2011. Technical analysts typically use 20 periods and k = 2 as default settings to build Bollinger Bands, while they can choose a simple or exponential moving average. Bollinger Bands provide a relative definition of high and low prices of a security. When the security is trading within the upper band, the price is considered high, while it is considered low when the security is trading within the lower band.
There is no general consensus on the use of Bollinger Bands among traders. Some traders see a buy signal when the price hits the lower Bollinger Band and close their position when the price hits the moving average. Some others buy when the price crosses over the upper band and sell when the price crosses below the lower band. We can see here two opposing interpretations based on different rationales, depending whether we are in a reversal or continuation pattern. Another interesting feature of the Bollinger Bands is that they give an indication of the volatility levels; a widening gap between the upper and lower bands indicates an increasing volatility, while a narrowing band indicates a decreasing volatility. Moreover, when the bands have an almost flat slope (parallel to the x-axis) the price will generally oscillate between the bands as if trading through a channel.
█ Intro to Keltner Channels
Keltner Channels aka Kelts were first described by a Chicago grain trader called Chester W. Keltner in his 1960 book How to Make Money in Commodities. Though Keltner claimed no ownership of the original idea and simply called it the ten-day moving average trading rule, his name was applied by those who heard of this concept through his books.
Similarly to the Bollinger Bands, Keltner channel is a technical analysis tool based on three parallel lines. In fact, the Keltner indicator consists of a central moving average in addition to channel lines spread above and below it. The central line represents a 10-day simple moving average of what Chester W. Keltner called typical price. The typical price is defined as the average of the high, low and close. The distance between the central line and the upper, or lower line, is equivalent to the simple moving average of the preceding 10 days' trading ranges.
One way to interpret the Keltner Channel would be to consider the price breakouts outside of the channel. A trader would track price movement and consider any close above the upper line as a strong buy signal. Equivalently, any close below the lower line would be considered a strong sell signal. The trader would follow the trend emphasized by the indicator while complementing his analysis with the use of other indicators as well. However, the breakout method only works well when the market moves from a range-bound setting to an established trend. In a trend-less configuration, the Keltner Channel is better used as an overbought/oversold indicator. Thus, as the price breaks out below the lower band, a trader waits for the next close inside the Keltner Channel and considers this price behavior as an oversold situation indicating a potential buy signal. Similarly, as the price breaks out above the upper band, the trader waits for the next close inside the Keltner Channel and considers this price movement as an overbought situation indicating a potential sell signal. By waiting for the price to close within the Channel, the trader avoids getting caught in a real upside or downside breakout.
Happy Trading!
Indicator
Consolidation Ranges [kingthies] Consolidation Range Analysis
Published by Eric Thies, January 2021
█ Indicator Summary
This tool calculates, analyzes and plots the visualization of a relative range over a given period of time
By adding to charts, users are enabled to see the impulsive nature of market cycles, along with their efforts to consolidate thereafter
The default period is 30, and should be adjusted to users preference
The default input is the current close price, on the chosen timeframe of the chart
█ Script Source
//
//@version=4
//© kingthies || This source code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org
study("Consolidation Ranges ", shorttitle="CR ", overlay=true)
// !<------ User Inputs ----->
src = input(close, title='Range Input (Default set to Close'), lengthEMA=input(30,title='Length'),zoneToggle = input(true, title="Toggle Zone Highlights"), iCol = color.new(#FFFFFF, 100),
// !<---- Declarations & Calculations ---- >
trndUp = float(na),trndDwn = float(na), mid = float(na), e = ema(src, lengthEMA)
trndUp := src < nz(trndUp ) and src > trndDwn ? nz(trndUp ) : high, trndDwn := src < nz(trndUp ) and src > trndDwn ? nz(trndDwn ) : low, mid := avg(trndUp, trndDwn)
// !< ---- Plotting ----->
highRange = plot(trndUp == nz(trndUp ) ? trndUp : na, color=color.white, linewidth=2, style=plot.style_linebr, title="Top of Period Range")
lowRange = plot(trndDwn == nz(trndDwn ) ? trndDwn : na, color=color.white, linewidth=2, style=plot.style_linebr, title="Bottom of Period Range")
xzone = plot(zoneToggle ? src > e ? trndDwn : trndUp : na, color=iCol, style=plot.style_circles, linewidth=0, editable=false)
fill(highRange, xzone, color=color.lime,transp=70), fill(xzone, lowRange, color=color.red,transp=70)
//
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