Smoothing ATR bandThere are two bands calculated with the ATR and I added "Smoothing" into the script.
Smoothing ATR with multiplier can display two bands above and below the price.
We can ONLY find some ATR bands in Community Scripts with "Basic" setting which is used to set Stop Loss.
And yet , Smoothing ATR with multiplier is capable of making traders manifestly recognize OverBought & OverSold.
FurtherMore, I added a condition with "plotshape", which is "Stop Hunt"
Stop Hunt is an absolutely usual strategy to clean the leverage and it always makes high volatility moves.
When high> above band and close< above band , long signal, it means it had been abundantly bought but the larger traders weren't satisfied; therefore, they quickly sold out to lower the price. The sell condition is on the contrary.
The signals mainly make traders manifestly recognize OverBought & OverSold.
חפש סקריפטים עבור "band"
custom Bollinger bands with filters - indicator (AS)-----------Description-------------
This indicator is basically Bollinger bands with many ways to customize. It uses highest and lowest values of upper and lower band for exits. I think something is wrong with the script but cant find any mistakes – most probably smoothing. The ATR filter is implemented but is working incorrectly. In code you can also turn it into strategy but I do not recommend it for now as it is not ready yet.
So this is my first script and I am looking for any advice, ideas to improve this script, sets of parameters, markets to apply, logical mistakes in code or any ideas that you may have. Indicator was initially designed for EURUSD 5MIN but I would be interested in other ideas.
-----------SETTINGS--------------
---START - In starting settings we can choose
Line 1: what parts to use BB/DC/ATR
Line 2: what parts to plot on chart
Line 3 Whether or not apply smoothing to BB or ATR filter
Line 4 Calculate deviation for BB from price or Moving average
Line 5 Fill colors and plot other parts for debug (overlay=false)
Line 6:( for strategy) – enable Long/Short Trades
---BB and DC – here we modify Bollinger bands and Donchian
Line 1: Length and type of BB middle line and also length of DC from BB
Line 2: Length and type of BB standard deviation and multiplier
Line 3: Length and type of BB smoothing and %width for BB filter
---ATR filter – (not ready fully yet)
Line 1: type and length of ATR
Line 2: threshold and smoothing value of ATR
---DATE and SESSION
Line 1: apply custom date or session?
Line 2: session hours settings
Line 3:Custom starting date
Line 4: Custom Ending date
-----------HOW TO USE--------------
We open Long if BB width is bigger than threshold and close when upper band is no longer highest in the period set. Exact opposite with Short
Shorting when Bollinger Band Above Price with RSI (by Coinrule)The Bollinger Bands are among the most famous and widely used indicators. A Bollinger Band is a technical analysis tool defined by a set of trendlines plotted two standard deviations (positively and negatively) away from a simple moving average ( SMA ) of a security's price, but which can be adjusted to user preferences. They can suggest when an asset is oversold or overbought in the short term, thus providing the best time for buying and selling it.
The relative strength index ( RSI ) is a momentum indicator used in technical analysis. RSI measures the speed and magnitude of a security's recent price changes to evaluate overvalued or undervalued conditions in the price of that security. The RSI can do more than point to overbought and oversold securities. It can also indicate securities primed for a trend reversal or corrective pullback in price. It can signal when to buy and sell. Traditionally, an RSI reading of 70 or above indicates an overbought situation. A reading of 30 or below indicates an oversold condition.
The short order is placed on assets that present strong momentum when it's more likely that it is about to reverse. The rule strategy places and closes the order when the following conditions are met:
ENTRY
The closing price is greater than the upper standard deviation of the Bollinger Bands
The RSI is less than 70.
EXIT
The trade is closed when the RSI is less than 70
The lower standard deviation of the Bollinger Band is less than the closing price.
This strategy was backtested from the beginning of 2022 to capture how this strategy would perform in a bear market.
The strategy assumes each order to trade 70% of the available capital to make the results more realistic. A trading fee of 0.1% is taken into account. The fee is aligned to the base fee applied on Binance, which is the largest cryptocurrency exchange by volume.
Bollinger Band Alert with RSI Filter IndicatorThis code is for a technical analysis indicator called Bollinger Band Alert with RSI Filter. It uses two tools: Bollinger Bands and Relative Strength Index (RSI) to identify potential trading signals in the market.
Bollinger Bands are lines plotted two standard deviations away from a simple moving average of the price of a stock or asset. They help traders determine whether prices are high or low on a relative basis.
The RSI is a momentum indicator that measures the strength of recent price changes to evaluate whether an asset is overbought or oversold.
The code has some input parameters that a user can change, such as length and multiplier, which are used to calculate the Bollinger Bands, and upper and lower RSI levels to define the overbought and oversold zones.
The code then uses if statements to generate alerts if certain conditions are met. The alert condition is triggered if the close price of an asset crosses above or below the upper or lower Bollinger Bands, and if the RSI is either above or below the overbought or oversold threshold levels.
Finally, the code generates plots to visualize the Bollinger Bands and displays triangles above or below the bars indicating when to enter a long or short position based on the strategy's criteria.
Faytterro Bandswhat is Faytterro Bands?
it is a channel indicator like "Bollinger Bands".
what it does?
creates a channel using standard deviations and means. thus giving users an idea about the expensive and cheap zones. It uses a special weighted moving average different from standard bollinger bands, it also averages not only price but also deviations.
how it does it?
it uses this formulas:
how to use it?
its usage is the same as "bollinger band".
length represents the number of candles to be taken into account, source represents the source of those candles and stdev represents the coefficient of the standard deviation.
you can use it with other indicators:
Chebyshevs BandsThis script calculates upper and lower bands using Chebyshev's inequality formula.
The main pros.: the band doesn't depend on particular distribution. It fits to any type of random variables. Also it allows to calculate bands for instruments with extremely high volatility.
Cons.: formula provides a rough estimation in some special cases like lognormal distribution.
Correlated ATR Bands | AdulariHow do I use it?
Never use this indicator as standalone trading signal, it should be used as confluence.
It is highly recommended to use this indicator on the 15m timeframe and above, try experimenting with the inverse feature and multipliers as well.
When the price is above the moving average this shows the bullish trend is strong.
When the price is below the moving average this shows the bearish trend is strong.
When the moving average is purple, the trend is bullish , when it is gray, the trend is bearish.
When price is above the upper band this may indicate a bearish reversal.
When price is below the lower band this may indicate a bullish reversal.
Features:
Purple line for bullish trend and gray line for bearish trend.
Custom formula combining an ATR and Hull MA to clearly indicate trend strength and direction.
Unique approach to moving averages and bands by taking the average of 2 types of MA's combined with custom ATR's, then multiplying these by correlation factors.
Bands to indicate possible trend reversals when price crosses them.
How does it work?
1 — ATR value is calculated, then the correlation between the source and ATR is calculated.
2 — Final value is calculated using the following formula:
correlation * atr + (1 - correlation) * nz(atr , atr)
3 — Moving average is calculated with the following formula:
ta.hma((1-(correlation/100*(1+weight/10)))*(ta.sma(source+value, smoothing)+ta.sma(source-value,smoothing))/2,flength)
4 — Bands calculation using multipliers.
Distance Bands Oscillator_KT █ OVERVIEW
This tool is based on both Bollinger Bands and Keltner Channels, and measures 3 distances between the two, respectively.
Upper Kelt to Upper Bollinger Band
Lower Kelt to Lower Bollinger Band
Kelt Basis to Bollinger Basis Basis
Similar to the Band Width indicator, this can be used as a measure of volatility, and can be used to measure uptrend, downtrend and chop regions on a given chart.
Happy Trading,
ET
BOLLY BandsThis is a strategy using Bollinger Bands. The strategy is predicated around having low volatility in price action and then looking to capture a move when price starts to trend outside of the Bollinger bands. This strategy has only been backtested for 1 month but it has promising results so I will be sharing it looking for feedback. I run this strategy on the ERUSD 1 min chart.
MTF MA Ribbon and Bands + BB, Gaussian F. and R. VWAP with StDev█ Multi Timeframe Moving Average Ribbon and Bands + Bollinger Bands, Gaussian Filter and Rolling Volume Weighted Average Price with Standard Deviation Bands
Up to 9 moving averages can be independently applied.
The length , type and timeframe of each moving average are configurable .
The lines, colors and background fill are customizable too.
This script can also display:
Moving Average Bands
Bollinger Bands
Gaussian Filter
Rolling VWAP and Standard Deviation Bands
Types of Moving Averages:
Simple Moving Average (SMA)
Exponential Moving Average (EMA)
Smoothed Moving Average (SMMA)
Weighted Moving Average (WMA)
Volume Weighted Moving Average (VWMA)
Least Squares Moving Average (LSMA)
Hull Moving Average (HMA)
Arnaud Legoux Moving Average (ALMA)
█ Moving Average
Moving Averages are price based, lagging (or reactive) indicators that display the average price of a security over a set period of time.
A Moving Average is a good way to gauge momentum as well as to confirm trends, and define areas of support and resistance.
█ Bollinger Bands
Bollinger Bands consist of a band of three lines which are plotted in relation to security 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, a 20 day moving average is by far the most popular).
The SMA then serves as a base for the Upper and Lower Bands which are used as a way to measure volatility by observing the relationship between the Bands and price.
█ Gaussian Filter
Gaussian filter can be used for smoothing.
It rejects high frequencies (fast movements) better than an EMA and has lower lag.
A Gaussian filter is one whose transfer response is described by the familiar Gaussian bell-shaped curve.
In the case of low-pass filters, only the upper half of the curve describes the filter.
The use of gaussian filters is a move toward achieving the dual goal of reducing lag and reducing the lag of high-frequency components relative to the lag of lower-frequency components.
█ Rolling VWAP
The typical VWAP is designed to be used on intraday charts, as it resets at the beginning of the day.
Such VWAPs cannot be used on daily, weekly or monthly charts. Instead, this rolling VWAP uses a time period that automatically adjusts to the chart's timeframe.
You can thus use the rolling VWAP on any chart that includes volume information in its data feed.
Because the rolling VWAP uses a moving window, it does not exhibit the jumpiness of VWAP plots that reset.
Made with the help from scripts of: adam24x, VishvaP, loxx and pmk07.
Ichimoku Cloud and Bollinger Bands (by Coinrule)The Ichimoku Cloud is a collection of technical indicators that show support and resistance levels, as well as momentum and trend direction. It does this by taking multiple averages and plotting them on a chart. It also uses these figures to compute a “cloud” that attempts to forecast where the price may find support or resistance in the future.
The Ichimoku Cloud was developed by Goichi Hosoda, a Japanese journalist, and published in the late 1960s. It provides more data points than the standard candlestick chart. While it seems complicated at first glance, those familiar with how to read the charts often find it easy to understand with well-defined trading signals.
The Ichimoku Cloud is composed of five lines or calculations, two of which comprise a cloud where the difference between the two lines is shaded in.
The lines include a nine-period average, a 26-period average, an average of those two averages, a 52-period average, and a lagging closing price line.
The cloud is a key part of the indicator. When the price is below the cloud, the trend is down. When the price is above the cloud, the trend is up.
The above trend signals are strengthened if the cloud is moving in the same direction as the price. For example, during an uptrend, the top of the cloud is moving up, or during a downtrend, the bottom of the cloud is moving down.
The Bollinger Bands are among the most famous and widely used indicators. A Bollinger Band is a technical analysis tool defined by a set of trendlines plotted two standard deviations (positively and negatively) away from a simple moving average ( SMA ) of a security's price, but which can be adjusted to user preferences. They can suggest when an asset is oversold or overbought in the short term, thus providing the best time for buying and selling it.
This strategy combines the Ichimoku Cloud with Bollinger Bands to better enter trades.
Long orders are placed when these basic signals are triggered.
Long Position:
Tenkan-Sen is above the Kijun-Sen
Chikou-Span is above the close of 26 bars ago
Close is above the Kumo Cloud
The closing price is greater than the upper standard deviation of the Bollinger Bands
Short Position:
Tenkan-Sen is below the Kijun-Sen
Chikou-Span is below the close of 26 bars ago
Close is below the Kumo Cloud
The upper standard deviation of the Bollinger Band is greater than the closing price
The script is backtested from 1 January 2022 and provides good returns.
The strategy assumes each order is using 30% of the available coins to make the results more realistic and to simulate you only ran this strategy on 30% of your holdings. A trading fee of 0.1% is also taken into account and is aligned to the base fee applied on Binance.
This script also works well on BTC 30m/1h, ETH 2h, MATIC 2h/30m, AVAX 1h/2h, SOL 45m timeframes
Impatient TS VWAP BandsImpatient VWAP bands are based of Traderskew's VWAP bands but are for more impatient traders.
Wicking or crossing down through the upper band indicates a good short trade entry for range-bound trading periods while wicking or crossing up through the lower band indicates a good long entry in range-bound conditions.
By default, impatience is disabled. If it is turned on, adjusting impatience determines how quickly the bands approach price: higher impatience approaches price faster. Rebound indicates how far from price the bands bounce after hitting price.
MTF VWAP & StDev BandsMulti Timeframe Volume Weighted Average Price with Standard Deviation Bands
I used the script "Koalafied VWAP D/W/M/Q/Y" by Koalafied_3 and made some changes, such as adding more standard deviation bands.
The script can display the daily, weekly, monthly, quarterly and yearly VWAP.
Standard deviation bands values can be changed (default values are 0.618, 1, 1.618, 2, 2.618, 3).
Also the previous standard deviation bands can be displayed.
SMA VWAP BANDS [qrsq]Description
This indicator is used to find support and resistance utilizing both SMA and VWAP. It can be used on lower and higher time frames to understand where price is likely to reject or bounce.
How it works
Rather than using the usual calculation for the VWAP, instead this script smooths the volume first with the SMA and then respectively calculates the smoothed multiplication of high, low and close price with the volume individually. These values are then divided by the smoothed volume to find individual VWAP's for each of the sources. The standard deviations of these are calculated, resulting in an upper, lower and middle band. It is essentially VWAP bands with some smoothed calculations in the middle.
How to use it
I like to use the bands for LTF scalping as well as HTF swings.
For scalping:
I tend to use either the 5m or 15m TF
I then set the indicator's TF to 1m
I will take a scalp based on the bands confluence with other PA methods, if price is being either supported or rejected.
For swings:
I tend to use a variety of TFs, including: 30m, 1H, 4H, D
I then set the indicator's TF to "Chart"
I will take a swing based on the bands confluence with other PA methods, if price is being either supported or rejected.
I also tend to use them on perpetual contracts as the volume seems to be more consistent and hence results in more accurate support and resistance.
[blackcat] L2 SVE Volatility BandsLevel 2
Background
Sylvain Vervoort’s articles in the July issues on 2018,“The V-Trade, Part 5: Technical Analysis—Moving Average Support & Resistance And Volatility Bands”
Function
In “The V-Trade, Part 5: Technical Analysis—Moving Average Support & Resistance And Volatility Bands” in the July 2018 STOCKS & COMMODITIES, author Sylvain Vervoort introduced a new type of price band that he calls the SVEVolatilityBand. He created this new type of band to better highlight volatility changes when using non-time-related charts. According to the author, when using charts such as renko, traditional bands may fail to effectively highlight these changes.
Remarks
Feedbacks are appreciated.
VWAP Band TrendThis indicator combines two features: VWAP bands for range trading and trends for trend-following.
The white bands offer support/resistance levels ideal for range trading: short when rejecting off the upper band, long when rejecting off the lower. Take profit either when hitting the (faint gray) midline and/or when hitting the band on the far side.
The trend analysis shows green or red ranges above or below the bands to indicate trend strength - larger swaths of green or red indicates strong trend while shorter swathes indicate weak. If the upper trend color doesn't match the lower trend color, the trend is undecided or transitioning.
Optionally, trend initiation indicators can be turned on to show above/below candles where a trend switch is taking place.
Z-Score Bands + SignalsZ-Score Statistical Market Analyzer
A multi-dimensional market structure indicator based on standardized deviation & regime logic
English Description
Concept
This indicator builds a statistical model of price behaviour by converting every candle’s movement into a Z-score — how many standard deviations each close is away from its moving average.
It visualizes the normal distribution structure of returns and provides adaptive entry signals for both Mean Reversion and Breakout regimes.
Rather than predicting price direction, it measures statistical displacement from equilibrium and dynamically adjusts the decision logic according to the market’s volatility regime.
⚙️ Main Components
Z-Score Bands (±1σ, ±2σ, ±3σ)
– The core structure visualizes volatility boundaries based on rolling mean and standard deviation.
– Price outside ±2σ often indicates statistical extremes.
Dual Signal Systems
Mean Reversion (MRL / MRS): when price (or return z-score) crosses back inside ±2σ bands.
Breakout (BOL / BOS): when price continues to expand beyond ±2σ.
Volatility Regime Classification
The indicator detects whether the market is currently in a low-vol or high-vol regime using percentile statistics of σ.
Low vol → Mean Reversion preferred
High vol → Breakout preferred
🧠 Adaptive Switches
A. Freeze MA/σ - Use previous-bar stats to avoid repainting and lag.
B. Confirm on Close - Only generate signals once the base-timeframe bar closes (eliminates look-ahead bias).
C. Return-based Signal - Use log-return Z-score instead of price deviation — normalizes volatility across assets.
D. Outlier Filter - Exclude bars with abnormal single-bar returns (e.g., >20%). Reduces false spikes.
E. Regime Gating - Automatically switch between Mean Reversion and Breakout logic depending on volatility percentile.
Each module can be toggled individually to test different statistical behaviours or tailor to a specific market condition.
📊 Interpretation
When the histogram of returns approximates a normal distribution, mean-reversion logic is often more effective.
When price persistently drifts beyond ±2σ or ±3σ, the distribution becomes leptokurtic (fat-tailed) — a breakout structure dominates.
Hence, this tool can help you:
Identify whether an asset behaves more “Gaussian” or “fat-tailed”;
Select the correct trading regime (MR or BO);
Quantitatively measure market tension and volatility clusters.
🧩 Recommended Use
Works on any timeframe and any asset.
Best used on liquid instruments (e.g., XAU/USD, indices, major FX pairs).
Combine with volume, sentiment or structural filters to confirm signals.
For strategy automation, pair with the companion script:
🧠 “Z-Score Strategy • Multi-Source Confirm (MRL/MRS/BOL/BOS)”.
⚠️ Disclaimer
This script is designed for educational and research purposes.
Statistical deviation ≠ directional prediction — use with sound risk management.
Past distribution patterns may shift under new volatility regimes.
==================================================================================
中文说明（简体）
概念简介
该指标基于价格的统计分布原理，将每根 K 线的波动转化为标准化的 Z-Score（标准差偏离值），用于刻画市场处于均衡或偏离状态。
它同时支持 均值回归（Mean Reversion） 与 突破延展（Breakout） 两种逻辑，并可根据市场波动结构自动切换策略模式。
⚙️ 主要功能模块
Z-Score 通道（±1σ / ±2σ / ±3σ）
用滚动均值与标准差动态绘制的统计波动带，价格超出 ±2σ 区域通常意味着极端偏离。
双信号系统
MRL / MRS（均值回归多空）：价格重新回到 ±2σ 以内时触发。
BOL / BOS（突破延展多空）：价格持续运行在 ±2σ 之外时触发。
波动率分层
自动识别市场处于高波动还是低波动区间：
低波动期 → 适合均值回归逻辑；
高波动期 → 适合突破趋势逻辑。
🧠 A–E 模块说明
A. 固定统计参数：使用上一根 K 线的均值和标准差，防止重绘。
B. 收盘确认信号：仅在当前时间框架收盘后生成信号，避免前视偏差。
C. 收益率信号模式：采用对数收益率的 Z-Score，更具普适性。
D. 异常波过滤：忽略单根极端波动（如 >20%）的噪声信号。
E. 波动率调节逻辑：根据市场处于高/低波动区间，自动切换 MRL/MRS 或 BOL/BOS。
📊 应用解读
如果收益率分布接近正态分布 → 市场倾向震荡，MRL/MRS 效果较佳；
若价格频繁偏离 ±2σ 或 ±3σ → 市场呈现“肥尾”分布，趋势延展占主导。
因此，该指标的核心目标是：
识别当前市场的统计结构类型；
根据波动特征自动切换交易逻辑；
提供结构化、可量化的市场状态刻画。
💡 使用建议
适用于所有时间框架与金融品种。
建议结合成交量或结构性指标过滤。
若用于策略回测，可搭配同名 “Z-Score Strategy • Multi-Source Confirm” 策略脚本。
⚠️ 免责声明
本指标仅用于研究与教学，不构成任何投资建议。
统计偏离 ≠ 趋势预测，实际市场行为可能在不同波动结构下改变。
Daily EMAs (8, 21 & 50) with BandDescription:
This script plots the Daily EMAs (8, 21, and 50) on any intraday or higher timeframe chart. It provides a clear, multi-timeframe view of market trends by using daily exponential moving averages (EMAs) and a dynamic visual band. I use this on the major indexes to decide if I should be mostly longing or shorting assets.
-In addition to identifying the trend structure, the 8-Day EMA often serves as a key area where buyers or sellers may become active, depending on the market direction:
-In an uptrend, the 8 EMA can act as a dynamic support zone, where buyers tend to re-enter on pullbacks.
-In a downtrend, the same EMA may act as resistance, where sellers become more aggressive.
-The script also includes a colored band between the 8 and 21 EMAs to highlight the short-term trend bias:
-Green fill = 8 EMA is above the 21 EMA (bullish structure).
Blue fill = 8 EMA is below the 21 EMA (bearish structure).
The 50-Day EMA is included to give additional context for intermediate-term trend direction.
Features:
- Daily EMA levels (8, 21, and 50) calculated regardless of current chart timeframe.
- 8 EMA acts as a potential buyer/seller zone based on trend direction.
- Color-coded band between 8 and 21 EMAs:
- Green = Bullish short-term bias
- Blue = Bearish short-term bias
- Customizable price source and EMA offset.
- Suitable for trend trading, pullback entries, and higher-timeframe confirmation.
Use Cases:
Identify key dynamic support/resistance areas using the 8 EMA.
Assess short-, medium-, and intermediate-term trend structure at a glance.
Enhance confluence for entry/exit signals on lower timeframes.
M2 GLI SD BandsHighly customizable M2 Global Liquidity Index with adaptive standard deviation bands.
The SD bands incorporate data from M2 with varying lags to capture M2's full impact on the price of Bitcoin spread across multiple weeks.
EMAs are used for smoothing. Offset, smoothing, and other features are customizable.
Volatility with Sigma BandsOverview
The Volatility Analysis with Sigma Bands indicator is a powerful and flexible tool designed for traders who want to gain deeper insights into market price fluctuations. It calculates historical volatility within a user-defined time range and displays ±1σ, ±2σ, and ±3σ standard deviation bands, helping traders identify potential support, resistance levels, and extreme price behaviors.
Key Features
Multiple Volatility Band Displays:
±1σ Range (Yellow line): Covers approximately 68% of price fluctuations.
±2σ Range (Blue line): Covers approximately 95% of price fluctuations.
±3σ Range (Fuchsia line): Covers approximately 99% of price fluctuations.
Dynamic Probability Mode:
Toggle between standard normal distribution probabilities (68.2%, 95.4%, 99.7%) and actual historical probability calculations, allowing for more accurate analysis tailored to varying market conditions.
Highly Customizable Label Display:
The label shows:
Real-time volatility
Annualized volatility
Current price
Price ranges for each σ level
Users can adjust the label’s position and horizontal offset to prevent it from overlapping key price areas.
Real-Time Calculation & Visualization:
The indicator updates in real-time based on the selected time range and current market data, making it suitable for day trading, swing trading, and long-term trend analysis.
Use Cases
Risk Management:
Understand the distribution probabilities of price within different standard deviation bands to set more effective stop-loss and take-profit levels.
Trend Confirmation:
Determine trend strength or spot potential reversals by observing whether the price breaks above or below ±1σ or ±2σ ranges.
Market Sentiment Analysis:
Price movement beyond the ±3σ range often indicates extreme market sentiment, providing potential reversal opportunities.
Backtesting and Historical Analysis:
Utilize the customizable time range feature to backtest volatility during various periods, providing valuable insights for strategy refinement.
The Volatility Analysis with Sigma Bands indicator is an essential tool for traders seeking to understand market volatility patterns. Whether you're a day trader looking for precise entry and exit points or a long-term investor analyzing market behavior, this indicator provides deep insights into volatility dynamics, helping you make more confident trading decisions.
MACD Bands - Multi Timeframe [TradeMaster Lite]We present a customizable MACD indicator, with the following features:
Multi-timeframe
Deviation bands to spot unusual volatility
9 Moving Average types
Conditional coloring and line crossings
👉 What is MACD?
MACD is a classic, trend-following indicator that uses moving averages to identify changes in momentum. It can be used to identify trend changes, overbought and oversold conditions, and potential reversals.
👉 Multi-timeframe:
This feature allows to analyze the same market data on multiple time frames, which can be in help to identify trends and patterns that would not be visible on a single time frame. When using the multi-timeframe feature, it is important to start with the higher time frame and then look for confirmation on the lower time frames. This will help you to avoid false signals. Please note that only timeframes higher than the chart timeframe is supported currently with this feature enabled. Might get updated in the future.
👉 Deviation bands to spot unusual volatility:
Deviation bands are plotted around the Signal line that can be in help to identify periods of unusual volatility. When the MACD line crosses outside of the deviation bands, it suggests that the market is becoming more volatile and a strong trend may form in that direction.
👉 9 Moving Average types can be used in the script. Each type of moving average offers a unique perspective and can be used in different scenarios to identify market trends.
SMA (Simple Moving Average): This calculates the average of a selected range of values, by the number of periods in that range.
SMMA (Smoothed Moving Average): This takes into account all data available and assigns equal weighting to the values.
EMA (Exponential Moving Average): This places a greater weight and significance on the most recent data points.
DEMA (Double Exponential Moving Average): This is a faster-moving average that uses a proprietary calculation to reduce the lag in data points.
TEMA (Triple Exponential Moving Average): This is even quicker than the DEMA, helping traders respond more quickly to changes in trend.
LSMA (Least Squares Moving Average): This moving average applies least squares regression method to determine the future direction of the trend.
HMA (Hull Moving Average): This moving average is designed to reduce lag and improve smoothness, providing quicker signals for short-term market movements.
VWMA (Volume Weighted Moving Average): This assigns more weight to candles with a high volume, reflecting the true average values more accurately in high volume periods.
WMA (Weighted Moving Average): This assigns more weight to the latest data, but not as much as the EMA.
👉 Conditional coloring :
This feature colors the MACD line line based on it's direction and fills the area between the MACD line and Deviation band edges to highlight the potential volatility and the strength of the momentum. This can be useful to identify when the market is trending strongly and when it is in a more neutral or choppy state.
👉 MACD Line - Signal Line crossings:
This is a classic MACD trading signal that occurs when the MACD line crosses above or below the signal line. Crossovers can be used to identify potential trend reversals. This can be a bullish or bearish signal, depending on the direction of the crossover.
👉 General advice
Confirming Signals with other indicators:
As with all technical indicators, it is important to confirm potential signals with other analytical tools, such as support and resistance levels, as well as indicators like RSI, MACD, and volume. This helps increase the probability of a successful trade.
Use proper risk management:
When using this or any other indicator, it is crucial to have proper risk management in place. Consider implementing stop-loss levels and thoughtful position sizing.
Combining with other technical indicators:
The indicator can be effectively used alongside other technical indicators to create a comprehensive trading strategy and provide additional confirmation.
Keep in Mind:
Thorough research and backtesting are essential before making any trading decisions. Furthermore, it's crucial to have a solid understanding of the indicator and its behavior. Additionally, incorporating fundamental analysis and considering market sentiment can be vital factors to take into account in your trading approach.
Limitations:
This is a lagging indicator. Please note that the indicator is using moving averages, which are lagging indicators.
The indicators within the TradeMaster Lite package aim for simplicity and efficiency, while retaining their original purpose and value. Some settings, functions or visuals may be simpler than expected.
⭐ Conclusion
We hold the view that the true path to success is the synergy between the trader and the tool, contrary to the common belief that the tool itself is the sole determinant of profitability. The actual scenario is more nuanced than such an oversimplification. Our aim is to offer useful features that meet the needs of the 21st century and that we actually use.
🛑 Risk Notice:
Everything provided by trademasterindicator – from scripts, tools, and articles to educational materials – is intended solely for educational and informational purposes. Past performance does not assure future returns.
ATR Daily BandThis indicator draws an upper and lower band for each day. It uses the Average True Range calculation (with configurable lookback) and places the band at 1ATR above and 1ATR below the daily open.
I use this indicator as a simple gauge to tell how significant price movement is, and get a feel for the daily volatility. Due to the fractal nature of price action, it can be difficult to determine if a price movement is significant while zoomed in on a single intraday chart. Using this indicator, I can tell if the price action is approaching the ATR or if it's just staying within the band.
Strategies: Useful for both mean reversion and momentum strategies. It's up to you to decide how this metric will fit into your trading strategy. I currently use this indicator to look for mean reversion setups, but that is due to the current market conditions and my personal trading style.
ATR Trend Bands [Misu]█ This indicator shows an upper and lower band based on price action and ATR (Average True Range)
The average true range (ATR) is a market volatility indicator used in technical analysis.
█ Usages:
The purpose of this indicator is to identify changes in trends and price action.
It is mainly used to identify breaking points and trend reversals.
But it can also be used to show resistance or support levels.
█ Features:
> Buy & Sell Alerts
> Buy & Sell Labels
> Color Bars
> Show Bands
█ Parameters:
Length: Length is used to calculate ATR.
Atr Multiplier: A factor used to balance the impact of the ATR on the Trend Bands calculation.
