Original Keltner with Support And ResistanceThis indicator is based on the original Keltner Channels using typical price and calculating the 10 period average of high - low
Typical price = (high + low + close)/3
In this case, I've taken Typical price as (open + high + low + close)/4 on the advice of John Bollinger from his book Bollinger on Bollinger Bands.
Buy Line = 10 Period Typical Price Average + 10 Period Average of (High - Low)
Sell Line = 10 Period Typical Price Average - 10 Period Average of (High - Low)
This is the basis for the indicator. I've added the highest of the Buy Line and lowest of the Sell Line for the same period which acts as Support and Resistance.
If price is trending below the Lowest of Sell Line, take only sell trades and the Lowest Line acts as resistance.
If price is trending above the Highest of Buy Line, take only buy trades and the Highest Line acts as support.
Keltnerchannel
MTF BB+KC Avg
Bollinger Bands (BB) are a widely used technical analysis created by John Bollinger in the early 1980’s. Bollinger Bands consist of a band of three lines which are plotted in relation to instrument prices. The line in the middle is usually a Simple Moving Average (SMA) set to a period of 20 days (The type of trend line and period can be changed by the trader; however a 20 day moving average is by far the most popular). This indicator does not plot the middle line. The Upper and Lower Bands are used as a way to measure volatility by observing the relationship between the Bands and price. Typically the Upper and Lower Bands are set to two standard deviations away from the middle line, however the number of standard deviations can also be adjusted in the indicator.
Keltner Channels (KC) are banded lines similar to Bollinger Bands and Moving Average Envelopes. They consist of an Upper Envelope above a Middle Line (not plotted in this indicator) as well as a Lower Envelope below the Middle Line. The Middle Line is a moving average of price over a user-defined time period. Either a simple moving average or an exponential moving average are typically used. The Upper and Lower Envelopes are set a (user-defined multiple) of a range away from the Middle Line. This can be a multiple of the daily high/low range, or more commonly a multiple of the Average True Range.
This indicator is built on AVERAGING the BB and KC values for each bar, so you have an efficient metric of AVERAGE volatility. The indicator visualizes changes in volatility which is of course dynamic.
What to look for
High/Low Prices
One thing that must be understood about this indicator's plots is that it averages by adding BB levels to KC levels and dividing by 2. So the plots provide a relative definition of high and low from two very popular indicators. Prices are almost always within the upper and lower bands. Therefore, when prices move up near the upper or lower bands or even break through the band, many traders would see that price action as OVER-EXTENDED (either overbought or oversold, as applicable). This would preset a possible selling or buying opportunity.
Cycling Between Expansion and Contraction
Volatility can generally be seen as a cycle. Typically periods of time with low volatility and steady or sideways prices (known as contraction) are followed by period of expansion. Expansion is a period of time characterized by high volatility and moving prices. Periods of expansion are then generally followed by periods of contraction. It is a cycle in which traders can be better prepared to navigate by using Bollinger Bands because of the indicators ability to monitor ever changing volatility.
Walking the Bands
Of course, just like with any indicator, there are exceptions to every rule and plenty of examples where what is expected to happen, does not happen. Previously, it was mentioned that price breaking above the Upper Band or breaking below the Lower band could signify a selling or buying opportunity respectively. However this is not always the case. “Walking the Bands” can occur in either a strong uptrend or a strong downtrend.
During a strong uptrend, there may be repeated instances of price touching or breaking through the Upper Band. Each time that this occurs, it is not a sell signal, it is a result of the overall strength of the move. Likewise during a strong downtrend there may be repeated instances of price touching or breaking through the Lower Band. Each time that this occurs, it is not a buy signal, it is a result of the overall strength of the move.
Keep in mind that instances of “Walking the Bands” will only occur in strong, defined uptrends or downtrends.
Inputs
TimeFrame
You can select any timeframe froom 1 minute to 12 months for the bar measured.
Length of the internal moving averages
You can select the period of time to be used in calculating the moving averages which create the base for the Upper and Lower Bands. 20 days is the default.
Basis MA Type
Determines the type of Moving Average that is applied to the basis plot line. Default is SMA and you can select EMA.
Source
Determines what data from each bar will be used in calculations. Close is the default.
StdDev/Multiplier
The number of Standard Deviations (for BB) or Multiplier (for KC) away from the moving averages that the Upper and Lower Bands should be. 2 is the default value for each indicator.
ATR Bands (Keltner Channel), Wick and SRSI Signals [MW]Introduction
This indicator uses a novel combination of ATR Bands, candle wicks crossing the ATR upper and lower bands, and baseline, and combines them with the Stochastic SRSI oscillator to provide early BUY and SELL signals in uptrends, downtrends, and in ranging price conditions.
How it’s unique
People generally understand Bollinger Bands and Keltner Channels. Buy at the bottom band, sell at the top band. However, because the bands themselves are not static, impulsive moves can render them useless. People also generally understand wicks. Candles with large wicks can represent a change in pattern, or volatile price movement. Combining those two to determine if price is reaching a pivot point is relatively novel. When Stochastic RSI (SRSI) filtering is also added, it becomes a genuinely unique combination that can be used to determine trade entries and exits.
What’s the benefit
The benefit of the indicator is that it can help potentially identify pivots WHEN THEY HAPPEN, and with potentially minimal retracement, depending on the trader’s time window. Many indicators wait for a trend to be established, or wait for a breakout to occur, or have to wait for some form of confirmation. In the interpretation used by this indicator, bands, wicks, and SRSI cycles provide both the signal and confirmation.
It takes into account 3 elements:
Price approaching the upper or lower band or the baseline - MEANING: Price is becoming extended based on calculations that use the candle trading range.
A candle wick of a defined proportion (e.g. wick is 1/2 the size of a full candle OR candle body) crosses a band or baseline, but the body does not cross the band or baseline - MEANING: Buyers and sellers are both very active.
The Stochastic RSI reading is above 80 for SELL signals and below 20 for BUY signals - MEANING: Additional confirmation that price is becoming extended based on the current cyclic price pattern.
How to Use
SIGNALS
Buy Signals - Green(ish):
B Signal - Potential pivot up from the lower band when using the preferred multiplier
B1 Signal - Potential pivot up from the lower band when using phi * multiplier
B2 Signal - Potential pivot up from the lower band when using 1/2 * multiplier
B3 Signal - Potential pivot up from baseline
Sell Signals - Red(ish):
S Signal - Potential pivot down from the upper band when using the preferred multiplier
S1 Signal - Potential pivot down from the upper band when using
S2 Signal - Potential pivot down from the upper band when using 1/2 * multiplier
S3 Signal - Potential pivot down from the baseline
DISCUSSION
During an uptrend or downtrend, signals from the baseline can help traders identify areas where they may enter the trending move with the least amount of drawdown. In both cases, entry points can occur with baseline signals in the direction of the trend.
For example, in an uptrend (when the price is forming higher highs and higher lows, or when the baseline is rising), price tends to oscillate between the upper band and baseline. In this case, the baseline BUY signal (B3) can show an entry point.
In a downtrend (when the price is forming lower highs and lower lows, or when the baseline is falling), price tends to oscillate between the baseline and the lower band. In this case, the baseline SELL signal (S3) can show an entry point.
During consolidation, when price is ranging, price tends to oscillate between the upper and lower bands, while crossing through the baseline unperturbed. Here, entry points can occur at the upper and lower bands.
When all conditions are met at the lower band during consolidation, a BUY signal (B), can occur. This signal may also occur prior to a break out of consolidation to the upside.
When all conditions are met at the upper band during consolidation, a SELL signal (S), can occur. This signal may also occur prior to a break out of consolidation to the downside.
Additional B1, B2, and S1, and S2 signals can be displayed that use the bands based on a multiplier that is half that of the primary one, and phi (0.618) times the primary multiplier as a way to quickly check for signals occurring along different, but related, bands.
Calculations
ATR Bands, or Keltner Channels, are a technical analysis tool that are used to measure market volatility and identify overbought or oversold conditions in the trading of financial instruments, such as stocks, bonds, commodities, and currencies. ATR Bands consist of three lines plotted on a price chart:
Middle Band, Basis, or Baseline: This is typically a simple moving average (SMA) of the closing prices over a certain period. It represents the intermediate-term trend of the asset's price.
Upper Band: This is calculated by adding a certain number of ATRs to the middle band (SMA). The upper band adjusts itself with the increase in volatility.
Lower Band: This is calculated by subtracting the same number of ATRs from the middle band (SMA). Like the upper band, the lower band adjusts to changes in volatility.
The candle wick signals occur if the wick is at the specified ratio compared to either the entire candle or the candle body. The upper band, lower band, and baseline signals happen if the wick is the specified ratio of the total candle size. For the major signals for upper and lower bands, these occur when the wick extends outside of the bands while closing a candle inside of the bands. For the baseline signals, they occur if a wick crosses a baseline but closes on the other side.
Settings
CHANNEL SETTINGS
Baseline EMA Period (Default: 21): Period length of the moving average basis line.
ATR Period (Default: 21): The number of periods over which the Average True Range (ATR) is calculated.
Basis MA Type (Default: SMA): The moving average type for the basis line.
Multiplier (Default: 2.5: The deviation multiplier used to calculate the band distance from the basis line.
ADDITIONAL CHANNELS
Half of Multiplier Offset (Default: True): Toggles the display of the ATR bands that are set a distance of half of the ATR multiplier.
Quarter of Multiplier Offset (Default: false): Toggles the display of the ATR bands that are set a distance of one quarter of the ATR multiplier.
Phi (Φ) Offset (Default: false): Toggles the display of the ATR bands that are set a distance of phi (Φ) times the ATR multiplier.
WICK SETTINGS FOR CANDLE FILTERS
Wick Ratio for Bands (Default: 0.4): The ratio of wick size to total candle size for use at upper and lower bands.
Wick Ratio for Baseline (Default: 0.4): The ratio of wick size to total candle size for use at baseline.
Use Candle Body (rather than full candle size) (Default: false): Determines whether wick calculations use the candle body or the entire candle size.
VISUAL PREFERENCES - SIGNALS
Show Signals (Default: true): Allows signal labels to be shown.
Show Signals from 1/2 Band Offset (Default: false): Toggle signals originating from 1/2 offset upper and lower bands.
Show Signals from Phi (Φ) Band Offset (Default: false): Toggle signals originating from phi (Φ) offset upper and lower bands.
Show Baseline Signals (Default: false): Toggle Baseline signals.
VISUAL PREFERENCES - BANDS
Show ATR (Keltner) Bands (Default: true): Use a background color inside the Bollinger Bands.
Fill Bands (Default: true): Use a background color inside the Bollinger Bands.
STOCHASTIC SETTINGS
Use Stochastic RSI Filtering (Default: False): This will only trigger some SELL signals when the stochastic RSI is above 80, and BUY signals when below 20.
K (Default: 3): The smoothing level for the Stochastic RSI.
RSI Length (Default: 14): The period length for the RSI calculation.
Stochastic Length (Default: 8): The period length over which the stochastic calculation is performed.
Other Usage Notes and Limitations
To understand future price movement, this indicator assumes that 3 things must be known:
Evidence of a change of market structure. This can be demonstrated by increased volatility, consolidation, volume spikes (which can be tracked with the MW Volume Impulse Indicator) or, in the case of this indicator, candle wicks.
The potential cause of the change. It could be a VWAP line (which can be tracked with the Multi VWAP , and Multi VWAP from Gaps indicators), an event, an important support or resistance level, a key moving average, or many other things. This indicator assumes the ATR bands can be a cause.
The current position in the price cycle. Oscillators like the RSI, and MACD, are typical measures of price oscillation (other oscillators like the Price and Volume Stochastic Divergence indicator can also be useful). This indicator uses the Stochastic RSI oscillator to determine overbought and oversold conditions.
When evidence of the change appears, and the potential cause of the change is identified, and the price oscillation is at a favorable position for the desired trading direction, this indicator will generate a signal.
ATR Bands (or Keltner Channels) are used to determine when price might “revert to the mean”. Crossing, or being near the upper or lower band, can indicate an overbought or oversold condition, which could lead to a price reversal. By tracking the behavior of candle wicks during these events, we can see how active the battle is between buyers and sellers.
If the top of a wick is large, it may indicate that sellers are aggressively attempting to bring the price down. Conversely, if the bottom wick is large, it can indicate that buyers are actively trying to counter the price action caused by selling pressure.
When this wicking action occurs at times when price is not near the upper band, lower band, or baseline, it could indicate the presence of an important level. That could mean a nearby VWAP line, a supply or demand zone, a round price number, or a number of other factors. In any case, this wick may be the first indication of a price reversal.
Shorter baseline periods may be better for short period trading like scalping or day trading, while longer period baselines can show signals that are better suited to swing trading, or longer term investing.
It's important for traders to be aware of the limitations of any indicator and to use them as part of a broader, well-rounded trading strategy that includes risk management, fundamental analysis, and other tools that can help with reducing false signals, determining trend direction, and providing additional confirmation for a trade decision. Diversifying strategies and not relying solely on one type of indicator or analysis can help mitigate some of these risks.
The TradingView platform allows a maximum of 500 labels per chart. This means that if your settings allow for a lot of signals, labels for earlier ones may not appear if the total number of labels exceeds 500 for the chart.
[KVA]Keltner Channel PercentageThe " Keltner Channel Percentage " (KC%) indicator, designed for TradingView's version 5 language, offers a unique perspective on market volatility and trend analysis, similar yet distinct from the well-known Bollinger Bands Percentage (BB%).
Audience and Applications:
This indicator is suited for traders who prefer a volatility-based approach but seek a smoother, trend-focused alternative to BB%.
It is especially valuable in markets where volatility is not just a byproduct but a central aspect of price dynamics.
In essence, the " Keltner Channel Percentage " stands as a complementary tool to Bollinger Bands Percentage. It offers a different lens through which to view market volatility and trends, providing traders with additional insights and strategies for navigating the financial markets. Its unique combination of simplicity and depth makes it a valuable addition to the technical analyst's toolkit, suitable for a variety of trading scenarios and market conditions.
LBR-Volatility Breakout BarsThe originator of this script is Linda Raschke of LBR Group.
This Pine Script code is the version 5 of LBR Paintbars for TradingView, called "LBR-Bars." It was originally coded for TradingView in version 3 by LazyBear. It is a complex indicator that combines various features such as coloring bars based on different conditions, displaying Keltner channels, and showing volatility lines.
Let me break down the key components and explain how it works:
1. Inputs Section: This section defines various input parameters that users can adjust when adding the indicator to their charts. These parameters allow users to customize the behavior and appearance of the indicator. Here are some of the key input parameters:
- Users can control whether to color bars under different conditions. For example,
they can choose to color LBR bars, color bars above/below Kelts, or color non-LBR
bars.
- Users can choose whether to show volatility lines or shade Keltner channels' area
with the Mid being the moving average on the chart.
- In the calculation of Keltner channels, users can set the length of the moving
average that the Keltner channels use as the mid and then set the Keltner multiplier.
If users want to use "True Range" to determine calculations, they can turn it on or
off; it defaults to off.
- Users can change the calculation of volatility lines and set the length for finding the
lowest and highest prices. The user sets the ATR length and multiplier for the ATR.
2. Calculation Section: This section defines the calculation of the upper and lower standard deviation bands based on the input parameters. It uses Exponential Moving Averages (EMAs) and optionally True Range to calculate these bands if turned on. These bands are used in the Keltner channel calculation.
3. Keltner Channel Section: This section calculates the upper, middle, and lower lines of the Keltner channels. It also plots these lines on the chart. The colors and visibility of these lines are controlled by user inputs.
4. Volatility Lines Section: This section calculates the upper and lower volatility lines based on the lowest and highest prices over a specified period and the ATR. It also checks whether the current close price is above or below these lines accordingly. The colors and visibility of these lines are controlled by user inputs.
5. Bar Colors Section: This section determines the color of the bars on the chart based on various conditions. It checks whether the current bar meets conditions like being an LBR bar, being above or below volatility lines, or being in "No Man's Land." The color of the bars is set accordingly based on user inputs.
This Pine Script creates an indicator that provides visual cues on the chart based on Keltner channels, volatility lines, and other customizable conditions. Users can adjust the input parameters to tailor the indicator's behavior and appearance to their trading preferences.
[dharmatech] KBDR Mean ReversionBased on the criteria described in the book "Mean Revision Trading" by Nishant Pant.
Bullish signal criteria:
Bollinger Bands must be outside Keltner Channel
Price near bottom bband
DI+ increasing
DI- decreasing
RSI near bottom and increasing
Bearish signal criteria:
Bollinger Bands must be outside Keltner Channel
Price near upper bband
DI+ decreasing
DI- increasing
RSI near upper and decreasing
A single triangle indicates that all 4 criteria are met.
If letters appear with the triangle, this indicates that there was a partial criteria match.
K : bbands outside Keltner
B : bbands criteria met
D : DI criteria met
R : RSI criteria met
You can use the settings to turn off partial signals. For example:
"Partial 3" means show signals where 3 of the criteria are met.
If you want more insight into the underlying criteria, load these indicators as well:
Bollinger Bands (built-in to TradingView)
Keltner Channels (built-in to TradingView)
RSI (built-in to TradingView)
ADX and DI
Warning:
Not meant to be used as a stand-alone buy/sell signal.
It regularly provides signals which would not be profitable.
It's meant to be used in conjunction with other analysis.
Think of this as a time-saving tool. Instead of manually checking RSI, DI+/DI-, bbands, distance, etc. this does all of that for you on the fly.
IV Squeeze - Sunil Bhave This script calculates both Bollinger Bands and Keltner Channels on a 5-minute chart. It identifies IV squeeze conditions when the lower Bollinger Band is above the lower Keltner Channel and the upper Bollinger Band is below the upper Keltner Channel. When a squeeze is detected, it plots a red triangle below the chart bars and alerts you with a message.
Please note that this script is for educational purposes only.
Auto-Length Adaptive ChannelsIntroduction
The key innovation of the ALAC is the implementation of dynamic length identification, which allows the indicator to adjust to the "market beat" or dominant cycle in real-time.
The Auto-Length Adaptive Channels (ALAC) is a flexible technical analysis tool that combines the benefits of five different approaches to market band and price deviation calculations.
Traders often tend to overthink of what length their indicators should use, and this is the main idea behind this script. It automatically calculates length based on pivot points, averaging the distance that is in between of current market highs and lows.
This approach is very helpful to identify market deviations, because deviations are always calculated and compared to previous market behavior.
How it works
The indicator uses a Detrended Rhythm Oscillator (DRO) to identify the dominant cycle in the market. This length information is then used to calculate different market bands and price deviations. The ALAC combines five different methodologies to compute these bands:
1 - Bollinger Bands
2 - Keltner Channels
3 - Envelope
4 - Average True Range Channels
5 - Donchian Channels
By averaging these calculations, the ALAC produces an overall market band that generalizes the approaches of these five methods into a single, adaptive channel.
How to Use
When the price is at the upper band, this might suggest that the asset is overbought and may be due for a price correction. Conversely, when the price is at the lower band, the asset may be oversold and due for a price increase.
The space between the bands represents the market's volatility. Wider bands indicate higher volatility, while narrower bands suggest lower volatility.
Indicator Settings
The settings of the ALAC allow for customization to suit different trading strategies:
Use Autolength?: This allows the indicator to automatically adjust the length of the dominant cycle.
Usual Length: If "Use Autolength?" is disabled, this setting allows the user to manually specify the length of the cycle.
Moving Average Type: This selects the type of moving average to be used in the calculations. Options include SMA, EMA, ALMA, DEMA, JMA, KAMA, SMMA, TMA, TSF, VMA, VAMA, VWMA, WMA, and ZLEMA.
Channel Multiplier: This adjusts the distance between the bands.
Channel Multiplier Step: This changes the step size of the channel multiplier. Each next market band will be multiplied by a previous one. You can potentially use values below 1, which will plot bands inside the first, main channel.
Use DPO instead of source data?: This setting uses the DPO for calculations instead of the source data. Basically, this is how you can add or eliminate trend from calculation of an average leg-up / leg-down move.
Fast: This adjusts the fast length of the DPO.
Slow: This adjusts the slow length of the DPO.
Zig-zag Period: This adjusts the period of the zig-zag pattern used in the DPO.
(!) For more information about DPO visit official TradingView description here: link
Also, I want to say thanks to @StockMarketCycles for initial idea of Detrended Rhythm Oscillator (DRO) that I use in this script.
The Adaptive Average Channel is a powerful and versatile indicator that combines the strengths of multiple technical analysis methods.
In summary, with the ALAC, you can:
1 - Dynamically adapt to any asset and price action with automatic calculation of dominant cycle lengths.
2 - Identify potential overbought and oversold conditions with the adaptive market bands.
3 - Customize your analysis with various settings, including moving average type and channel multiplier.
4 - Enhance your trading strategy by using the indicator in conjunction with other forms of analysis.
Williams %R + Keltner chanells - indicator (AS)1)INDICATOR ---This indicator is a combination of Keltner channels and Williams %R.
It measures trend using these two indicators.
When Williams %R is overbought(above upper line (default=-20)) and Keltner lower line is below price indicator shows uptrend (green).
When Williams %R is oversold(below lower line (default=-80)) and Keltner upper line is above price indicator shows downtrend (red) .
Can be turned into a strategy quickly.
2) CALCULATIONS:
Keltner basis is a choosen type of moving average and upper line is basis + (ATR*multiplier). Same with lower but minus instead of plus so basiss – (ATR*multiplier)
Second indicator
Williams %R reflects the level of the close relative to the highest high for the lookback period
3)PLS-HELP-----Looking for tips, ideas, sets of parameters, markets and timeframes, rules for strategy -------OVERALL -every advice you can have
4) SIGNALS-----buy signal is when price is above upper KC and Williams %R is above OVB(-20). Short is exactly the other way around
5) CUSTOMIZATION:
-%R-------LENGTH/SMOOTHING/TYPE SMOOTHING MA
-%R-------OVS/MID/OVB -(MID-no use for now)
-KC -------LENGTH/TYPE OF MAIN MA
-KC-------MULTIPLIER,ATR LENGTH
-OTHER--LENGTH/TYPE OF MA - (for signal filters, not used for now)
-OTHER--SOURCE -src of calculations
-OTHER--OVERLAY - plots %R values for debugging etc(ON by default)
6)WARNING - do not use this indicator on its own for trading
7)ENJOY
Volatility Compression BreakoutThe Volatility Compression Breakout indicator is designed to identify periods of low volatility followed by potential breakout opportunities in the market. It aims to capture moments when the price consolidates within a narrow range, indicating a decrease in volatility, and anticipates a subsequent expansion in price movement. This indicator can be applied to any financial instrument and timeframe.
When the close price is above both the Keltner Middle line and the Exponential Moving Average (EMA), the bars are colored lime green, indicating a potential bullish market sentiment. When the close price is positioned above the Keltner Middle but below the EMA, or below the Keltner Middle but above the EMA, the bars are colored yellow, signifying a neutral or indecisive market condition. Conversely, when the close price falls below both the Keltner Middle and the EMA, the bars are colored fuchsia, suggesting a potential bearish market sentiment.
Additionally, the coloration of the Keltner Middle line and the EMA provides further visual cues for assessing the trend. When the close price is above the Keltner Middle, the line is colored lime green, indicating a bullish trend. Conversely, when the close price is below the Keltner Middle, the line is colored fuchsia, highlighting a bearish trend. Similarly, the EMA line is colored lime green when the close price is above it, representing a bullish trend, and fuchsia when the close price is below it, indicating a bearish trend.
Parameters
-- Compression Period : This parameter determines the lookback period used to calculate the volatility compression. A larger value will consider a longer historical period for volatility analysis, potentially capturing broader market conditions. Conversely, a smaller value focuses on more recent price action, providing a more responsive signal to current market conditions.
-- Compression Multiplier : The compression multiplier is a factor applied to the Average True Range (ATR) to determine the width of the Keltner Channels. Increasing the multiplier expands the width of the channels, allowing for a larger price range before a breakout is triggered. Decreasing the multiplier tightens the channels and requires a narrower price range for a breakout signal.
-- EMA Period : This parameter sets the period for the Exponential Moving Average (EMA), which acts as a trend filter. The EMA helps identify the overall market trend and provides additional confirmation for potential breakouts. Adjusting the period allows you to capture shorter or longer-term trends, depending on your trading preferences.
How Changing Parameters Can Be Beneficial
Modifying the parameters allows you to adapt the indicator to different market conditions and trading styles. Increasing the compression period can help identify broader volatility patterns and major market shifts. On the other hand, decreasing the compression period provides more precise and timely signals for short-term traders.
Adjusting the compression multiplier affects the width of the Keltner Channels. Higher multipliers increase the breakout threshold, filtering out smaller price movements and providing more reliable signals during significant market shifts. Lower multipliers make the indicator more sensitive to smaller price ranges, generating more frequent but potentially less reliable signals.
The EMA period in the trend filter helps you align your trades with the prevailing market direction. Increasing the EMA period smoothes out the trend, filtering out shorter-term fluctuations and focusing on more sustained moves. Decreasing the EMA period allows for quicker responses to changes in trend, capturing shorter-term price swings.
Potential Downsides
While the Volatility Compression Breakout indicator can provide valuable insights into potential breakouts, it's important to note that no indicator guarantees accuracy or eliminates risk. False breakouts and whipsaw movements can occur, especially in volatile or choppy market conditions. It is recommended to combine this indicator with other technical analysis tools and consider fundamental factors to validate potential trade opportunities.
Making It Work for You
To maximize the effectiveness of the Volatility Compression Breakout indicator, consider the following:
-- Combine it with other indicators : Use complementary indicators such as trend lines, oscillators, or support and resistance levels to confirm signals and increase the probability of successful trades.
-- Practice risk management : Set appropriate stop-loss levels to protect your capital in case of false breakouts or adverse price movements. Consider implementing trailing stops or adjusting stop-loss levels as the trade progresses.
-- Validate with price action : Analyze the price action within the compression phase and look for signs of building momentum or weakening trends. Support your decisions by observing candlestick patterns and volume behavior during the breakout.
-- Backtest and optimize : Test the indicator's performance across different timeframes and market conditions. Optimize the parameters based on historical data to find the most suitable settings for your trading strategy.
Remember, no single indicator can guarantee consistent profitability, and it's essential to use the Volatility Compression Breakout indicator as part of a comprehensive trading plan. Regularly review and adapt your strategy based on market conditions and your trading experience. Monitor the indicator's performance and make necessary adjustments to parameter values if the market dynamics change.
By adjusting the parameters and incorporating additional analysis techniques, you can customize the indicator to suit your trading style and preferences. However, it is crucial to exercise caution, conduct thorough analysis, and practice proper risk management to increase the likelihood of successful trades. Remember that no indicator can guarantee profits, and continuous learning and adaptation are key to long-term trading success.
BB Squeeze + SuperTrend + Keltner ChannelBollinger Bands and Keltner Channel are two of my favorite channels. When you use them correctly, they can bring great help to your trading.
I like to use Bollinger Bands and Keltner Channels to identify when you can trade and when you can not trade, which is also known as the "squeeze".
When the opening of the Bollinger Bands is very small, it is a range that you can enter a trade, the range is called "Squeeze Zone" or "Trade zone".
When the opening of the Bollinger Bands is very large, it is a range that you cannot enter a trade, because the market fluctuates big when BB's opening is large.
I use two ways to identify when the Bollinger Bands's opening is very small or large, one is the Bollinger Bands entering Keltner Bands and one is using specific ATR ranges,. The first one allows you to identify when the market is squeezing and the second one allows you to identify when the market has entered Squeeze zone, that is, the market is already in a trading range suitable for entering a trade.(see chart.)
When the market is squeezed and you enter the trade, you can also use ATR as the stop loss price of the trade, I recommend using 2 ATR as your stop loss, and I also display them on the chart (see chart).
In addition, I also added SuperTrend to this indicator. SuperTrend is a very suitable for identifying trends. You can use SuperTrend to help you identify whether to go long or short.
This is how I use this indicator(See chart):
1.Only trade when market is in Squeeze Zone. (Thick yellow line in chart)
2.When entry a trade, use 2 ATR as stop loss. (Label in Chart)
3.Use Super trend to know to go long or short.
4.Keltner Channel helps to know when the market is squeezing. (Thin yellow line in chart.)
======== 中文說明 (Chinese Explanation) ========
Bollinger Bands（布林帶）跟 Keltner Channel（肯特納通道）是我最喜歡的兩個通道，當你正確使用它們時，它們可以替你的交易帶來非常大的幫助。
我喜歡用 Bollinger Bands 跟 Keltner Channel 來識別何時可以交易，何時不能交易，這個又稱做“擠壓操作”。當布林帶的開口很小時，便是可以交易的區間，而當布林帶的開口很大時，對我來說此時就是不可以交易的區間，因為此時市場的波動很大。
我使用兩種方式來識別當布林帶開口很小的時候，一種是布林帶進入肯特納通道，一種則使用特定的ATR範圍，前者可以讓你識別市場正在擠壓，後者則可以識別市場已經進入擠壓區間，也就是市場已經處於適合進入交易的交易區間。
當市場進入擠壓之後，而你也進入了交易，你還可以使用ATR來作為交易的止損價格，我建議使用2個ATR 來當作你的止損，而我也將他們顯示在圖表上了（見圖表）。
另外，我還在這個指標中加入了 SuperTrend（超級趨勢），SuperTrend 是一個非常適合用來辨別趨勢的指標，你可以使用 SuperTrend 來幫助你識別要做多還是做空。
這是我使用該指標的方式（見圖表）：
1.僅在市場處於交易區間時進行交易。 （圖中黃色粗線）
2.入場時，使用2個ATR作為止損。 （圖表中的標籤）
3.使用超級趨勢知道做多或做空。
4.Keltner Channel 有助於了解市場何時擠壓。 （圖表中的黃色細線。）
Oliver Velez IndicatorOliver Velez is a well-known trader and educator who has developed multiple trading strategies. One of them is the 20-200sma strategy, which is a basic moving average crossover strategy. The strategy involves using two simple moving averages (SMAs) - a short-term SMA with a period of 20 and a long-term SMA with a period of 200 - on a 2-minute timeframe chart.
When the short-term SMA crosses above the long-term SMA, it signals a potential bullish trend and traders may look for opportunities to enter a long position. Conversely, when the short-term SMA crosses below the long-term SMA, it signals a potential bearish trend and traders may look for opportunities to enter a short position.
Traders using this strategy may also look for additional confirmations, such as price action signals or other technical indicators, before entering or exiting a trade. It is important to note that no trading strategy can guarantee profits, and traders should always use risk management techniques to limit potential losses.
This script is an implementation of the 2 SMA's (can also choose other types of MA's), with Elephant Bar Indicator (EBI) and the Tail Bars Indicator in TradingView.
The Elephant Bar Indicator is a technical indicator used in trading to identify potential trend reversals in the market. It is named after the large size of the bullish or bearish candlestick that it represents. The Tail Bars Indicator is a pattern recognition technique that identifies candlestick patterns with long tails or wicks.
The script starts by defining the input parameters for both indicators. For the Elephant Bar Indicator, the user inputs the lookback period and the size multiplier. For the Tail Bars Indicator, the user inputs the tail ratio and opposite wick ratio.
Next, the script calculates the moving averages of the closing price over the defined short and long periods using the Moving Average function. The script then calculates the average candle size and volume over the lookback period.
The script then identifies the Elephant Bars and Tail Bars using the input parameters and additional conditions. For Elephant Bars, the script identifies bullish and bearish bars that meet certain criteria, such as a size greater than the average candle size and volume greater than the average volume.
For Tail Bars, the script identifies bullish and bearish bars that have long tails or wicks and meet certain criteria such as opposite wick size less than or equal to the tail size multiplied by the input opposite wick ratio.
Finally, the script plots the Elephant Bar and Tail Bar signals on the chart using different colors and shapes. The script also plots the moving averages and Keltner Channels to help traders identify potential trend reversals.
It is still under development, so please, if someone has ideas to add, more than welcome
LNL Keltner CandlesLNL Keltner Candles
This indicator plots mean reversion (reversal) arrows with custom painted candles based on the price touch or close above or below keltner channel limits (upper & lower bands). This study was created primarily for swing trading & higher time frames such as daily and weekly. Lower time frames might result in more false signals.
Mean Reversal Arrows:
1. Reversal Arrow Up - If the price drops below the lower band extremes, reversal up is the trigger for a bullish mean reversion.
2. Reversal Arrow Down - Once the price reach the higher band extremes, reversal down is the trigger for a bearish mean reversion.
The Concept of Mean Reversion:
There are just two types of moves in any market: The market is either expanding from the mean or retracing back to the mean. These reversions & epxansions are happening across all types of markets. The goal of this study is to catch the powerful mean reversion from extremes back to the mean. Once the candles light up green / red, it is time to look for the reversal (purple) arrow which triggers the mean reversion setup. Mean reversion is not about catching the next big swing turn to new highs or lows. It is all about the base hits = the mean. So the target here is always the average price. The idea here is to catch the average market ebbs & flows, not the next home run.
What Do I Mean by Mean?
Mean is usually the average price from the last 20-30 bars. Basically something like a 20 MA or Keltner Channel or Bollinger Band midline are really good visual representators of the mean (average price).
Hope it helps.
Channels Strategy [Dimkud]Channels trading Strategy. Based on "Channels Strategy" by JoseMetal.
To the original strategy added additional options and filters : Static SL/TP in percents (%), time delay between orders, ATR Filter, second Keltner Channel (Multi TimeFrame).
Interface translated to English.
Were good backtest results on many crypto tokens on 15m - 45m - 1h periods.
Mostly with configuration: Keltner Channel (optimise parameters for every token) + Static SL/TP (optimise values for every token) + "Enter Condition" = "Wick out of band".
The better is to optimise paramaters separately for Short and Long trading. And run two separate bots (in settings enable only Long or only Short.)
Tested on real automated trading on few online bot platforms. (3comm, revenuebot, veles).
Later I will make tutorial how to connect strategy to these platforms or contact me if you need help.
Wunder Keltner botWunder Keltner bot
1. Wunder Keltner bot is based on the breakout of the Keltner channel. For calculation, 2 channels are used, one for long trades, and the other for short trades. The division into 2 channels is used for more accurate entry calculations depending on trend directions.
2. The ADX indicator is used to filter signals and determine the trend strength. ADX determines the strength of the trend and confirms the entry into the strategy if the value is greater than the level indicated in the settings.
3. There are 3 ways to calculate Stop Loss and Take Profit. You can choose one of them:
Classic Stop Loss and Take Profit in a fixed percentage
ATR Stop Loss
Keltner. Stop Loss, which is set on the opposite Keltner’s Channel Band from Keltner breakout.
4. ATR and Keltner use Risk Reward (R:R) to calculate Take Profit. The script calculates Risk Reward based on the determined Stop loss level and uses the ration to calculate Take Profit.
5. A function for calculating risk on the portfolio (your deposit) has been added to the script. When this option is enabled, you get a calculation of the entry amount in dollars relative to your Stop Loss. In the settings, you can select the risk percentage on your portfolio. The loss will be calculated from the amount that will be displayed on the chart.
For example. Deposit - $1000, you set the risk to 1%. SL 5%. Entry volume will be $200. The loss at SL will be $10.10$ this is your 1% risk or 1% of the deposit.
Important! The risk per trade must be less than the Stop Loss value. If the risk is greater than SL, then you should use leverage.
The amount of funds entering the trade is calculated in dollars. This option was created if you want to send the dollar amount from Tradingview to the exchange. However, putting your volume in dollars you get the incorrect net profit and drawdown indication in the backtest results, as TradingView calculates the backtest volume in contracts.
To display the correct net profit and drawdown values in Tradingview Backtest results, use the ”Volume in contract” option.
Channels Strategy [JoseMetal]============
ENGLISH
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- Description:
This strategy is based on Bollinger Bands / Keltner Channel price "rebounds" (the idea of price bouncing from one band to another).
The strategy has several customizable options, which allows you to refine the strategy for your asset and timeframe.
You can customize settings for ALL indicators, Bollinger Bands (period and standard deviation), Keltner Channel (period and ATR multiplier) and ATR (period).
- AVAILABLE INDICATORS:
You can pick Bollinger Bands or Keltner Channels for the strategy, the chosen indicator will be plotted as well.
- CUSTOM CONDITIONS TO ENTER A POSITION:
1. Price breaks the band (low below lower band for LONG or high above higher band for SHORT).
2. Same as 1 but THEN (next candle) price closes INSIDE the bands.
3. Price breaks the band AND CLOSES OUT of the band (lower band for LONG and higher band for SHORT).
4. Same as 3 but THEN (next candle) price closes INSIDE the bands.
- STOP LOSS OPTIONS:
1. Previous wick (low of previous candle if LONG and high or previous candle if SHORT).
2. Extended band, you can customize settings for a second indicator with larger values to use it as STOP LOSS, for example, Bollinger Bands with 2 standard deviations to open positions and 3 for STOP LOSS.
3. ATR: you can pick average true ratio from a source (like closing price) with a multiplier to calculate STOP LOSS.
- TAKE PROFIT OPTIONS:
1. Opposite band (top band for LONGs, bottom band for SHORTs).
2. Moving average: Bollinger Bands simple moving average or Keltner Channel exponential moving average .
3. ATR: you can pick average true ratio from a source (like closing price) with a multiplier to calculate TAKE PROFIT.
- OTHER OPTIONS:
You can pick to trade only LONGs, only SHORTs, both or none (just indicator).
You can enable DYNAMIC TAKE PROFIT, which updates TAKE PROFIT on each candle, for example, if you pick "opposite band" as TAKE PROFIT, it'll update the TAKE PROFIT based on that, on every single new candle.
- Visual:
Bands shown will depend on the chosen indicator and it's settings.
ATR is only printed if used as STOP LOSS and/or TAKE PROFIT.
- Recommendations:
Recommended on DAILY timeframe , it works better with Keltner Channels rather than Bollinger Bands .
- Customization:
As you can see, almost everything is customizable, for colors and plotting styles check the "Style" tab.
Enjoy!
============
ESPAÑOL
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- Descripción:
Esta estrategia se basa en los "rebotes" de precios en las Bandas de Bollinger / Canal de Keltner (la idea de que el precio rebote de una banda a otra).
La estrategia tiene varias opciones personalizables, lo que le permite refinar la estrategia para su activo y temporalidad favoritas.
Puedes personalizar la configuración de TODOS los indicadores, Bandas de Bollinger (periodo y desviación estándar), Canal de Keltner (periodo y multiplicador ATR) y ATR (periodo).
- INDICADORES DISPONIBLES:
Puedes elegir las Bandas de Bollinger o los Canales de Keltner para la estrategia, el indicador elegido será mostrado en pantalla.
- CONDICIONES PERSONALIZADAS PARA ENTRAR EN UNA POSICIÓN:
1. El precio rompe la banda (mínimo por debajo de la banda inferior para LONG o máximo por encima de la banda superior para SHORT).
2. Lo mismo que en el punto 1 pero ADEMÁS (en la siguiente vela) el precio cierra DENTRO de las bandas.
3. El precio rompe la banda Y CIERRA FUERA de la banda (banda inferior para LONG y banda superior para SHORT).
4. Igual que el 3 pero ADEMÁS (siguiente vela) el precio cierra DENTRO de las bandas.
- OPCIONES DE STOP LOSS:
1. Mecha anterior (mínimo de la vela anterior si es LONGy máximo de la vela anterior si es SHORT).
2. Banda extendida, puedes personalizar la configuración de un segundo indicador con valores más extensos para utilizarlo como STOP LOSS, por ejemplo, Bandas de Bollinger con 2 desviaciones estándar para abrir posiciones y 3 para STOP LOSS.
3. ATR: puedes elegir el average true ratio de una fuente (como el precio de cierre) con un multiplicador para calcular el STOP LOSS.
- OPCIONES DE TAKE PROFIT:
1. Banda opuesta (banda superior para LONGs, banda inferior para SHORTs).
2. Media móvil: media móvil simple de las Bandas de Bollinger o media móvil exponencial del Canal de Keltner .
3. ATR: se puede escoger el average true ratio de una fuente (como el precio de cierre) con un multiplicador para calcular el TAKE PROFIT.
- OTRAS OPCIONES:
Puedes elegir operar sólo con LONGs, sólo con SHORTs, ambos o ninguno (sólo el indicador).
Puedes activar el TAKE PROFIT DINÁMICO, que actualiza el TAKE PROFIT en cada vela, por ejemplo, si eliges "banda opuesta" como TAKE PROFIT, actualizará el TAKE PROFIT basado en eso, en cada nueva vela.
- Visual:
Las bandas mostradas dependerán del indicador elegido y de su configuración.
El ATR sólo se muestra si se utiliza como STOP LOSS y/o TAKE PROFIT.
- Recomendaciones:
Recomendada para temporalidad de DIARIO, funciona mejor con los Canales de Keltner que con las Bandas de Bollinger .
- Personalización:
Como puedes ver, casi todo es personalizable, para los colores y estilos de dibujo comprueba la pestaña "Estilo".
¡Que lo disfrutes!
True Range ScoreTrue Range Score:
This study transforms the price similar to how z-score works. Instead of using the standard deviation to divide the difference of the source and the mean to determine the sources deviation from the mean we use the true range. This results in a score that directly relates to what multiplier you would be using with the Keltner Channel. This is useful for many applications.
One is the fact that it shows you the momentum of the price and how strong the price movement is. This is also a great metric of volatility. With this you can make a smart Keltner channel by multiplying the mean by the average true range 75th percentile of this score. I in fact do this in my automatic Keltner channel script. I hope this script is useful for you. Thank you for checking this out.
(Source - Mean)/True Range instead of (Source - Mean)/Standard Deviation
SSL + Wave Trend StrategyStrategy incorporates the following features:
Risk management:
Configurable X% loss per stop loss
Configurable R:R ratio
Trade entry:
Based on strategy conditions below
Trade exit:
Based on strategy conditions below
Backtesting:
Configurable backtesting range by date
Trade drawings:
Each entry condition indicator can be turned on and off
TP/SL boxes drawn for all trades. Can be turned on and off
Trade exit information labels. Can be turned on and off
NOTE: Trade drawings will only be applicable when using overlay strategies
Alerting:
Alerts on LONG and SHORT trade entries
Debugging:
Includes section with useful debugging techniques
Strategy conditions
Trade entry:
LONG
C1: SSL Hybrid baseline is BLUE
C2: SSL Channel crosses up (green above red)
C3: Wave Trend crosses up (represented by pink candle body)
C4: Entry candle height is not greater than configured threshold
C5: Entry candle is inside Keltner Channel (wicks or body depending on configuration)
C6: Take Profit target does not touch EMA (represents resistance)
SHORT
C1: SSL Hybrid baseline is RED
C2: SSL Channel crosses down (red above green)
C3: Wave Trend crosses down (represented by orange candle body)
C4: Entry candle height is not greater than configured threshold
C5: Entry candle is inside Keltner Channel (wicks or body depending on configuration)
C6: Take Profit target does not touch EMA (represents support)
Trade exit:
Stop Loss: Size configurable with NNFX ATR multiplier
Take Profit: Calculated from Stop Loss using R:R ratio
Credits
Strategy is based on the YouTube video "This Unique Strategy Made 47% Profit in 2.5 Months " by TradeSmart.
It combines the following indicators to determine trade entry/exit conditions:
Wave Trend: Indicator: WaveTrend Oscillator by @LazyBear
SSL Channel: SSL channel by @ErwinBeckers
SSL Hybrid: SSL Hybrid by @Mihkel00
Keltner Channels: Keltner Channels Bands by @ceyhun
Candle Height: Candle Height in Percentage - Columns by @FreeReveller
NNFX ATR: NNFX ATR by @sueun123
Ultimate IndicatorThis is a combination of all the price chart indicators I frequently switch between. It contains my day time highlighter (for day trading), multi-timeframe long-term trend indicator for current commodity in the bottom right, customizable trend EMA which also has multi-timeframe drawing capabilities, VWAP, customizable indicators with separate settings from the trend indicator including: EMA, HL2 over time, Donchian Channels, Keltner Channels, Bollinger Bands, and Super Trend. The settings for these are right below the trend settings and can have their length and multiplier adjusted. All of those also have multi-timeframe capabilities separate from the trend multi-time settings.
The Day Trade Highlight option will draw faint yellow between 9:15-9:25, red between 9:25-9:45, yellow between 9:45-10:05. There will be one white background at 9:30am to show the opening of the market. while the market is open there will be a very faint blue background. For the end of the day there will be yellow between 15:45-15:50, red between 15:50-16:00, and yellow between 16:00-16:05. During the night hours, there is no coloring. The purpose of this highlight is to show the opening / closing times of the market and the hot times for large moves.
The indicators can also be colored in the following ways:
1. Simple = Makes all colors for the indicator Gray
2. Trend = Will use the Donchian Channels to get the short-trend direction and by default will color the short-term direction as Blue or Red. Unless using Super Trend, the Donchian Channel is used to find short-term trend direction.
3. Trend Adv = Will use the Donchian Channels to get the short-trend direction and by default will color the short-term direction as Blue or Red. Unless using Super Trend, the Donchian Channel is used to find short-term trend direction. If there is a short-term up-trend during a long-term down-trend, the Blue will become Navy. If short-term down-trend during long-term up-trend, the Red will be Brown.
4. Squeeze = Compares the Bollinger Bands width to the Keltner Channels width and will color based on relative squeeze of the market: Teal = no squeeze. Yellow = little squeeze. Red = decent squeeze. White = huge squeeze. if you do not understand this one, try drawing the Bollinger Bands while using the Squeeze color option and it should become more apparent how this works. I also recommend leaving the length and multiplier to the default 20 and 2 if using this setting and only changing the timeframe to get longer/shorter lengths as I've seen that changing the length or multiplier can more or less make it not work at all.
Along with the indicator settings are options to draw lines/labels/fills for the indicator. I enjoy having only fills for a cleaner look.
The Labels option will show Buy/Sell signals when the short-term trend flips to agree with the long-term trend.
The Trend Bars option will do the same as the Labels option but instead will color the bars white when a Buy/Sell option is given.
The Range Bars option shows will color a bar white when the Close of a candle is outside of a respective ranging indicator option (Bollinger or Keltner).
The Trend Bars will draw white candles no matter which indicator selection you make (even "Off"). However, Range Bars will only draw white when either Bollinger or Keltner are selected.
The Donchian Channels and Super Trend are trending indicators and should be used during trending markets. I like to use the MACD in conjunction with these indicators for possibly earlier entries.
The Bollinger Bands and Keltner Channel are ranging indicators and should be used during ranging markets. I like to use the RSI in conjunction with these indicators and will use 60/40 for overbought and oversold areas rather than 70/30. During a range, I wait for an overbought or oversold indication and will buy/sell when it crosses back into the middle area and close my position when it touches the opposite band.
I have a MACD/RSI combination indicator if you'd like that as well :D
As always, trade at your own risk. This is not some secret indicator that will 100% win. As always, the trades you see in the picture use a 1:1.5 or 1:2 risk to reward ratio, for today (August 8, 2022) it won 5/6 times with one trade still open at the end of the day. Manage your account correctly and you'll win in the long term. Hit me up with any questions or suggestions. Happy Trading!
Relative Andean ScalpingThis is an experimental signal providing script for scalper that uses 2 of open source indicators.
First one provides the signals for us called Andean Oscillator by @alexgrover . We use it to create long signals when bull line crosses over signal line while being above the bear line. And reverse is true for shorts where bear line crosses over signal line while being above bull line.
Second one is used for filtering out low volatility areas thanks to great idea by @HeWhoMustNotBeNamed called Relative Bandwidth Filter . We use it to filter out signals and create signals only when the Relative Bandwith Line below middle line.
The default values for both indicators changed a bit, especially used linreg values to create relatively better signals. These can be changed in settings. Please be aware that i did not do extensive testing with this indicator in different market conditions so it should be used with caution.
STD-Adaptive T3 Channel w/ Ehlers Swiss Army Knife Mod. [Loxx]STD-Adaptive T3 Channel w/ Ehlers Swiss Army Knife Mod. is an adaptive T3 indicator using standard deviation adaptivity and Ehlers Swiss Army Knife indicator to adjust the alpha value of the T3 calculation. This helps identify trends and reduce noise. In addition. I've included a Keltner Channel to show reversal/exhaustion zones.
What is the Swiss Army Knife Indicator?
John Ehlers explains the calculation here: www.mesasoftware.com
What is the T3 moving average?
Better Moving Averages Tim Tillson
November 1, 1998
Tim Tillson is a software project manager at Hewlett-Packard, with degrees in Mathematics and Computer Science. He has privately traded options and equities for 15 years.
Introduction
"Digital filtering includes the process of smoothing, predicting, differentiating, integrating, separation of signals, and removal of noise from a signal. Thus many people who do such things are actually using digital filters without realizing that they are; being unacquainted with the theory, they neither understand what they have done nor the possibilities of what they might have done."
This quote from R. W. Hamming applies to the vast majority of indicators in technical analysis . Moving averages, be they simple, weighted, or exponential, are lowpass filters; low frequency components in the signal pass through with little attenuation, while high frequencies are severely reduced.
"Oscillator" type indicators (such as MACD , Momentum, Relative Strength Index ) are another type of digital filter called a differentiator.
Tushar Chande has observed that many popular oscillators are highly correlated, which is sensible because they are trying to measure the rate of change of the underlying time series, i.e., are trying to be the first and second derivatives we all learned about in Calculus.
We use moving averages (lowpass filters) in technical analysis to remove the random noise from a time series, to discern the underlying trend or to determine prices at which we will take action. A perfect moving average would have two attributes:
It would be smooth, not sensitive to random noise in the underlying time series. Another way of saying this is that its derivative would not spuriously alternate between positive and negative values.
It would not lag behind the time series it is computed from. Lag, of course, produces late buy or sell signals that kill profits.
The only way one can compute a perfect moving average is to have knowledge of the future, and if we had that, we would buy one lottery ticket a week rather than trade!
Having said this, we can still improve on the conventional simple, weighted, or exponential moving averages. Here's how:
Two Interesting Moving Averages
We will examine two benchmark moving averages based on Linear Regression analysis.
In both cases, a Linear Regression line of length n is fitted to price data.
I call the first moving average ILRS, which stands for Integral of Linear Regression Slope. One simply integrates the slope of a linear regression line as it is successively fitted in a moving window of length n across the data, with the constant of integration being a simple moving average of the first n points. Put another way, the derivative of ILRS is the linear regression slope. Note that ILRS is not the same as a SMA ( simple moving average ) of length n, which is actually the midpoint of the linear regression line as it moves across the data.
We can measure the lag of moving averages with respect to a linear trend by computing how they behave when the input is a line with unit slope. Both SMA (n) and ILRS(n) have lag of n/2, but ILRS is much smoother than SMA .
Our second benchmark moving average is well known, called EPMA or End Point Moving Average. It is the endpoint of the linear regression line of length n as it is fitted across the data. EPMA hugs the data more closely than a simple or exponential moving average of the same length. The price we pay for this is that it is much noisier (less smooth) than ILRS, and it also has the annoying property that it overshoots the data when linear trends are present.
However, EPMA has a lag of 0 with respect to linear input! This makes sense because a linear regression line will fit linear input perfectly, and the endpoint of the LR line will be on the input line.
These two moving averages frame the tradeoffs that we are facing. On one extreme we have ILRS, which is very smooth and has considerable phase lag. EPMA has 0 phase lag, but is too noisy and overshoots. We would like to construct a better moving average which is as smooth as ILRS, but runs closer to where EPMA lies, without the overshoot.
A easy way to attempt this is to split the difference, i.e. use (ILRS(n)+EPMA(n))/2. This will give us a moving average (call it IE /2) which runs in between the two, has phase lag of n/4 but still inherits considerable noise from EPMA. IE /2 is inspirational, however. Can we build something that is comparable, but smoother? Figure 1 shows ILRS, EPMA, and IE /2.
Filter Techniques
Any thoughtful student of filter theory (or resolute experimenter) will have noticed that you can improve the smoothness of a filter by running it through itself multiple times, at the cost of increasing phase lag.
There is a complementary technique (called twicing by J.W. Tukey) which can be used to improve phase lag. If L stands for the operation of running data through a low pass filter, then twicing can be described by:
L' = L(time series) + L(time series - L(time series))
That is, we add a moving average of the difference between the input and the moving average to the moving average. This is algebraically equivalent to:
2L-L(L)
This is the Double Exponential Moving Average or DEMA , popularized by Patrick Mulloy in TASAC (January/February 1994).
In our taxonomy, DEMA has some phase lag (although it exponentially approaches 0) and is somewhat noisy, comparable to IE /2 indicator.
We will use these two techniques to construct our better moving average, after we explore the first one a little more closely.
Fixing Overshoot
An n-day EMA has smoothing constant alpha=2/(n+1) and a lag of (n-1)/2.
Thus EMA (3) has lag 1, and EMA (11) has lag 5. Figure 2 shows that, if I am willing to incur 5 days of lag, I get a smoother moving average if I run EMA (3) through itself 5 times than if I just take EMA (11) once.
This suggests that if EPMA and DEMA have 0 or low lag, why not run fast versions (eg DEMA (3)) through themselves many times to achieve a smooth result? The problem is that multiple runs though these filters increase their tendency to overshoot the data, giving an unusable result. This is because the amplitude response of DEMA and EPMA is greater than 1 at certain frequencies, giving a gain of much greater than 1 at these frequencies when run though themselves multiple times. Figure 3 shows DEMA (7) and EPMA(7) run through themselves 3 times. DEMA^3 has serious overshoot, and EPMA^3 is terrible.
The solution to the overshoot problem is to recall what we are doing with twicing:
DEMA (n) = EMA (n) + EMA (time series - EMA (n))
The second term is adding, in effect, a smooth version of the derivative to the EMA to achieve DEMA . The derivative term determines how hot the moving average's response to linear trends will be. We need to simply turn down the volume to achieve our basic building block:
EMA (n) + EMA (time series - EMA (n))*.7;
This is algebraically the same as:
EMA (n)*1.7-EMA( EMA (n))*.7;
I have chosen .7 as my volume factor, but the general formula (which I call "Generalized Dema") is:
GD (n,v) = EMA (n)*(1+v)-EMA( EMA (n))*v,
Where v ranges between 0 and 1. When v=0, GD is just an EMA , and when v=1, GD is DEMA . In between, GD is a cooler DEMA . By using a value for v less than 1 (I like .7), we cure the multiple DEMA overshoot problem, at the cost of accepting some additional phase delay. Now we can run GD through itself multiple times to define a new, smoother moving average T3 that does not overshoot the data:
T3(n) = GD ( GD ( GD (n)))
In filter theory parlance, T3 is a six-pole non-linear Kalman filter. Kalman filters are ones which use the error (in this case (time series - EMA (n)) to correct themselves. In Technical Analysis , these are called Adaptive Moving Averages; they track the time series more aggressively when it is making large moves.
Included:
Bar coloring
Signals
Alerts
Loxx's Expanded Source Types
FATL, SATL, RFTL, & RSTL Digital Signal Filter Smoother [Loxx]FATL, SATL, RFTL, & RSTL Digital Signal Filter (DSP) Smoother is is a baseline indicator with DSP processed source inputs
What are digital indicators: distinctions from standard tools, types of filters.
To date, dozens of technical analysis indicators have been developed: trend instruments, oscillators, etc. Most of them use the method of averaging historical data, which is considered crude. But there is another group of tools - digital indicators developed on the basis of mathematical methods of spectral analysis. Their formula allows the trader to filter price noise accurately and exclude occasional surges, making the forecast more effective in comparison with conventional indicators. In this review, you will learn about their distinctions, advantages, types of digital indicators and examples of strategies based on them.
Two non-standard strategies based on digital indicators
Basic technical analysis indicators built into most platforms are based on mathematical formulas. These formulas are a reflection of market behavior in past periods. In other words, these indicators are built based on patterns that were discovered as a result of statistical analysis, which allows one to predict further trend movement to some extent. But there is also a group of indicators called digital indicators. They are developed using mathematical analysis and are an algorithmic spectral system called ATCF (Adaptive Trend & Cycles Following). In this article, I will tell you more about the components of this system, describe the differences between digital and regular indicators, and give examples of 2 strategies with indicator templates.
ATCF - Market Spectrum Analysis Method
There is a theory according to which the market is chaotic and unpredictable, i.e. it cannot be accurately analyzed. After all, no one can tell how traders will react to certain news, or whether some large investor will want to play against the market like George Soros did with the Bank of England. But there is another theory: many general market trends are logical, and have a rationale, causes and effects. The economy is undulating, which means it can be described by mathematical methods.
Digital indicators are defined as a group of algorithms for assessing the market situation, which are based exclusively on mathematical methods. They differ from standard indicators by the form of analysis display. They display certain values: price, smoothed price, volumes. Many standard indicators are built on the basis of filtering the minute significant price fluctuations with the help of moving averages and their variations. But we can hardly call the MA a good filter, because digital indicators that use spectral filters make it possible to do a more accurate calculation.
Simply put, digital indicators are technical analysis tools in which spectral filters are used to filter out price noise instead of moving averages.
The display of traditional indicators is lines, areas, and channels. Digital indicators can be displayed both in the form of lines and in digital form (a set of numbers in columns, any data in a text field, etc.). The digital display of the data is more like an additional source of statistics; for trading, a standard visual linear chart view is used.
All digital models belong to the category of spectral analysis of the market situation. In conventional technical indicators, price indications are averaged over a fixed period of time, which gives a rather rough result. The use of spectral analysis allows us to increase trading efficiency due to the fact that digital indicators use a statistical data set of past periods, which is converted into a “frequency” of the market (period of fluctuations).
Fourier theory provides the following spectral ranging of the trend duration:
low frequency range (0-4) - a reflection of a long trend of 2 months or more
medium frequency range (5-40) - the trend lasts 10-60 days, thus it is referred to as a correction
high frequency range (41-130) - price noise that lasts for several days
The ATCF algorithm is built on the basis of spectral analysis and includes a set of indicators created using digital filters. Its consists of indicators and filters:
FATL: Built on the basis of a low-frequency digital trend filter
SATL: Built on the basis of a low-frequency digital trend filter of a different order
RFTL: High frequency trend line
RSTL: Low frequency trend line
Inclucded:
4 DSP filters
Bar coloring
Keltner channels with variety ranges and smoothing functions
Bollinger bands
40 Smoothing filters
33 souce types
Variable channels
LNL Pullback ArrowsBuying the dip has never been easier! LNL Pullback Arrows are here to pinpoint the best possible entries for the trend following setups. With the Pullback Arrows, trader can pick his own approach and risk level thanks to four different types of arrows. The goal of these arrows is to force the traders to scale in & out of trades which is in my opinion crucial when it comes to trend following strategies. These arrows were designed primarily for the daily & weekly time frame (swing trading).
Four Types of Pullback Arrows:
1. Aggro Arrows - Ideal for aggresive approach during parabolic trends. Sometimes trends are so strong that the price barely revisits the daily 8 EMA. This is where the aggro arrows can perfectly pinpoint the aggresive high risk entries. Ideal for halfsize or 1/4 size of the full position. Aiming for quick 1-2 day moves targeting the recent high/low. These arrows could be also named as scalping arrows for the swing traders. A quick In & Out.
2. HalfSize Arrows - Medium risk approach. First arrows to scale in. HalfSize arrows are the first sign that the pullback might be ending, yet there is still some space left for an even deeper pullback. That is the reason why they are called half-size. Ideally taken with half-sized position. When trading the HalfSize Arrows, It is better to have some "spare ammo in the gun" ready to use.
3. FullSize Arrows - Regular risk approach. These arrows represent a zone where the core of the posititon should be taken. The point of validity for the trend is not that far away, meaning the risk can be kept tight. Ideal for scailing the other halfs or quarters of the full position. Also great for more conservative traders or environments with higher volatility.
4. Rare Arrows - Offer the best risk to reward entries during the trend. Rare Arrows should be the "last kick" of the retracement, therefore stops can be positioned really tight. They either trigger the stop immidiately or they provide another juicy leg up or down in the direction of the trend. However, they really do appear rarely.
Simple EMA Cloud:
A simple cloud based on 21 and 55 exponential moving averages. This default length creates a pullback zone that is wide enough for the conservative traders but also give the opportunities to more aggresive traders. Alternatives such as 8 & 21, or 21 & 34 are forming the zone that is too aggresive and usually too thin. Of course, cloud can be fully adjusted or turned off completely. The only role of the cloud is to gauge the trend.
Tips & Tricks:
1.Importance of the Scailing
- As already stated, scailing is crucial to this since there is no way of knowing the exact level at which the price magically bounce every time. It is hard to tell where and which EMA will be respected. How can we know it will be 21 EMA every time? or 34 EMA or 10 EMA or 100 SMA or 50 DMA ... Single MA does not make a trend. This is the reason why scailing is so important. Scailing can make a difference.
2. Nothing is Perfect
- Same as any other study, nothing works 100% perfectly. Sometimes the setup will go right against you and sometimes the price will fade away sideways and breaks off the structure of the trend. This is not a magic certainty tool. This is just another probability tool.
3. Point of Validity & Other Studies
- Even though the pullback arrows can be a stand-alone strategy. It is important to use other indicators that visualize the actual trend. Whether its EMA Cloud or EMAs or DMI Bars or Keltner Channels, there should be something that validates the trend, something that tells the trend is over. (Pullback Arrows are not showing the actual stops!).
Hope it helps.
