Trend: SMA with ATR Bands and EMA [Oxyge]Brief introduction:
Easy to use trend indicator to help find entry positions
How it works:
1, short-term trend judgment: EMA is greatly influenced by short-term trends, so it is very good to use it as a tool for judging short-term trends. At the same time, the filtering function has been added:
Long: green
Short: red
No direction: blue
2, the general trend judgment: the use of 30SMA as the default trend line, while increasing the ATR band to increase the scope of judgment.
How do I use (assuming it is now a period of long market):
1, first look at the 30SMA and ATR band, if the slope is positive (> 45 °), then ready to go long!
2. When price comes to the ATR band, the ATR band is my point of interest
3. Wait for a test of the ATR band: the EMA turns green, which means that the short-term trend is already nice and long.
4. Stop Loss Placement: Stop Loss is placed at the most recent low.
Closing
Enjoy it!
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简单介绍：
简单易用的趋势指标，帮助寻找进场位置
它怎么工作：
1、短期趋势判断：EMA受短期趋势影响很大，因此把它作为判断短期趋势的工具非常好用。同时增加了过滤功能：
多头：绿色
空头：红色
无方向：蓝色
2、大趋势判断：使用30SMA作为默认趋势线，同时增加ATR带增加判断范围。
我是如何使用的（假设是现在是一段多头行情）：
1、先看30SMA和ATR带，如果斜率为正（>45°），那么准备做多
2、当价格来到ATR带时，ATR带是我的感兴趣的点
3、等待一次对于ATR带的测试：EMA变成绿色，代表短期已经是不错的多头趋势
4、止损放置：止损放置在最近的低点
结束
请享受它
Oscillators
Adaptive Schaff Trend Cycle (STC) [AlgoAlpha]Introducing the Adaptive Schaff Trend Cycle by AlgoAlpha: Elevate Your Trading Strategies 🚀
Discover precision and adaptability with the Adaptive Schaff Trend Cycle 🎯, meticulously crafted for traders seeking an edge in the markets. This advanced tool integrates sophisticated algorithms to offer clear insights and real-time analytics 📈.
Key Features:
⚙️Adaptive Signal Processing: Utilizes evolving calculations to adjust to market changes, offering highly responsive signals.
🔍Enhanced MACD Analysis: Innovates on the traditional MACD, providing new insights into market dynamics through an adaptive lens.
🎨Customizable Visual Experience: Features customizable up and down colors for tailored chart analysis.
🔔Real-Time Alerts: Stay informed with instant alerts on indicator changes.
Quick Guide to Using the Adaptive STC Indicator
1. 🔧 Adding the Indicator: Search for "Adaptive Schaff Trend Cycle (STC) " within TradingView's Indicators & Strategies and apply it to your chart. Customize the settings according to your trading style for optimum results.
2.👀 Market Analysis: Monitor the STC and Histogram values closely. The indicator's color gradients provide a visual representation of momentum shifts, helping you to identify trends more clearly.
3. 🚨 Set Alerts: Enable alerts for specific conditions like significant moves up or down, or when the histogram crosses zero. This feature ensures you never miss a potential trading opportunity.
How It Works:
The Adaptive Schaff Trend Cycle by AlgoAlpha introduces a dynamic approach to market analysis, refining traditional indicators through adaptive logic to align with fluctuating market conditions. Here's a concise overview of its operation:
🔄 Adaptive MACD Adjustment: The foundation of the indicator is an enhanced MACD calculation, which dynamically adjusts its parameters based on real-time market trends and momentum. This algorithmic adjustment aims to ensure the MACD's responsiveness to market changes, adapting its sensitivity to offer timely insights .
🌟 Integration of Schaff Trend Cycle (STC): After adjusting the MACD, the indicator calculates STC values to provide a smoothed representation of market trends. By normalizing and smoothing the MACD values on a scale from 0 to 100, the STC method helps in identifying market phases with a clear visualization. The smoothing process is designed to mitigate noise and focus on significant market movements .
📊 Visualization and Alerts: To aid in the interpretation of these insights, the Adaptive Schaff Trend Cycle employs color gradients and customizable visual settings to indicate momentum shifts. These visual cues, combined with alert functionalities, are structured to assist traders in monitoring market developments, enabling them to make informed decisions based on the presented data .
🛠️The Adaptive Schaff Trend Cycle thus merges adaptive MACD adjustments with STC methodology, supported by visual and alert features, to create a tool aimed at enhancing market analysis. By focusing on adaptability and current market conditions, it provides a nuanced view of market trends, intended to support traders in their decision-making processes without promising predictive accuracy or reliability .
LSMA Z-Score [BackQuant]LSMA Z-Score
Main Features and Use in the Trading Strategy
- The indicator normalizes the LSMA into a detrended Z-Score, creating an oscillator with standard deviation levels to indicate trend strength.
- Adaptive coloring highlights the rate of change and potential reversals, with different colors for positive and negative changes above and below the midline.
- Extreme levels with adaptive coloring indicate the probability of a reversion, providing strategic entry or exit points.
- Alert conditions for crossing the midline or significant shifts in trend direction enhance its utility within a trading strategy.
1. What is an LSMA?
The Least Squares Moving Average (LSMA) is a technical indicator that smoothens price data to help identify trends. It uses the least squares regression method to fit a straight line through the selected price points over a specified period. This approach minimizes the sum of the squares of the distances between the line and the price points, providing a more statistically grounded moving average that can adapt more smoothly to price changes.
2. What is a Z-Score?
A Z-Score is a statistical measurement that describes a value's relationship to the mean of a group of values, measured in terms of standard deviations from the mean. If a Z-Score is 0, it indicates that the data point's score is identical to the mean score. A Z-Score helps in understanding if a data point is typical for a given data set or if it is atypical. In finance, a Z-Score is often used to measure how far a piece of data is from the average of a set, which can be helpful in identifying outliers or unusual data points.
3. Why Turning LSMA into a Z-Score is Innovative and Its Benefits
Converting LSMA into a Z-Score is innovative because it combines the trend identification capabilities of the LSMA with the statistical significance testing of Z-Scores. This transformation normalizes the LSMA, creating a detrended oscillator that oscillates around a mean (zero line), with standard deviation levels to show trend strength. This method offers several benefits:
Enhanced Trend Detection:
- By normalizing the LSMA, traders can more easily identify when the price is deviating significantly from its trend, which can signal potential trading opportunities.
Standardization:
- The Z-Score transformation allows for comparisons across different assets or time frames, as the score is standardized.
Objective Measurement of Trend Strength:
- The use of standard deviation levels provides an objective measure of trend strength and volatility.
4. How It Can Be Used in the Context of a Trading System
This indicator can serve as a versatile tool within a trading system for a range of things:
Trend Confirmation:
- A positive Z-Score can confirm an uptrend, while a negative Z-Score can confirm a downtrend, providing traders with signals to enter or exit trades.
Oversold/Overbought Conditions:
- Extreme Z-Score levels can indicate overbought or oversold conditions, suggesting potential reversals or pullbacks.
Volatility Assessment:
- The standard deviation levels can help traders assess market volatility, with wider bands indicating higher volatility.
5. How It Can Be Used for Trend Following
For trend following strategies, this indicator can be particularly useful:
Trend Strength Indicator:
- By monitoring the Z-Score's distance from zero, traders can gauge the strength of the current trend, with larger absolute values indicating stronger trends.
Directional Bias:
- Positive Z-Scores can be used to establish a bullish bias, while negative Z-Scores can establish a bearish bias, guiding trend following entries and exits.
Color-Coding for Trend Changes :
- The adaptive coloring of the indicator based on the rate of change and extreme levels provides visual cues for potential trend reversals or continuations.
Thus following all of the key points here are some sample backtests on the 1D Chart
Disclaimer: Backtests are based off past results, and are not indicative of the future.
This is using the Midline Crossover:
INDEX:BTCUSD
INDEX:ETHUSD
BINANCE:SOLUSD
Altered Money Flow Index by CoffeeShopCrypto**Use the comments section below to request access to the script**
Market Trends need to be confirmed each and every time.
Over the years the Money Flow Index has been a tool to find where the money is flowing
either long or short in market movements.
Long confirmation and false short
Confirming a long entry:
1. Wait for price to close above a previous swing high.
2. Look to see if the MFI is in UPCOLOR and above ZERO.
Confriming a short entry:
1. Wait for price to close below a previous swing low.
2. Look to see if the MFI is in DOWNCOLOR and below ZERO.
NON-Confirmed market: (Flat Market)
Anytime you believe you have a confirmation via price action, check the MFI to see if it is in FLAT MARKET color.
If this is true, do not enter until it is out of FLAT MARKET color.
Flat Market ALtered MFI
A Flat Market Altered MFI reading can do a few things for you.
It can help to confirm the following:
1. price action is moving sideways.
2. a pullback or market stall that was deep enough where dis-intrest in the market occured.
3. a sudden loss of momentum in the short term trend of closing prices.
Utilizing the Altered Money Flow Index indicator by CoffeeShopCrypto offers traders a nuanced approach to identifying market trends, including periods of flat market conditions. Alongside its directional bias indicating bullish or bearish activity based on whether values are above or below zero, respectively, the script incorporates a distinctive feature to recognize flat markets. When neither bullish nor bearish momentum dominates, the indicator designates a flat market, denoted by a distinct color. This feature enhances traders' ability to discern not only bullish and bearish phases but also periods of market consolidation or indecision.
In addition to its ability to recognize bullish and bearish trends, the Altered Money Flow Index indicator by CoffeeShopCrypto incorporates a unique feature to signify potential pullbacks or pauses in market momentum. This is particularly evident when the MFI crosses below zero while displaying a flat market color. Such occurrences suggest that although the short-term movement may appear bearish, it's likely a temporary pullback rather than a sustained trend reversal. Similarly, when the MFI crosses above zero amidst a flat market color, it indicates a potential pause in bullish momentum, urging traders to exercise caution and await confirmation of a sustained uptrend. By incorporating these nuanced observations, traders can effectively discern between short-term fluctuations and significant trend changes, enabling them to make more judicious trading decisions and avoid premature entries or exits.
Alongside its directional bias indicating bullish or bearish activity based on whether values are above or below zero, respectively, the script integrates the Relative Strength Index (RSI) to further refine market analysis. When the Altered MFI and RSI are both above zero, it suggests a strong bullish trend, indicating significant buying pressure. Conversely, when both indicators are below zero, it indicates a strong bearish trend, signifying heightened selling pressure. By observing the confluence between the Altered MFI and RSI, traders can gain valuable confirmation of bullish or bearish money flow in the market, enabling them to make more informed trading decisions.
Z Score & Trend FollowingIntroduction:
The Z Score & Trend Following indicator is a tool used in financial markets to assess the standard deviation of a data point from its mean value over a specified period. It calculates the Z score, which is a measure of how many standard deviations an element is from the mean. This indicator also incorporates trend-following characteristics, allowing traders to visualize trends based on the Z score.
Indicator Parameters:
Standard Deviation Length: Determines the length of the standard deviation calculation.
Average Length: Specifies the length of the moving average used for the mean calculation.
Calculation Type: Allows users to choose between different types of moving averages (SMA, EMA, WMA, VMA, TMA).
Standard Deviations: Sets the number of standard deviations to be used for trend analysis.
Bar Color: Option to enable or disable bar coloring based on trend conditions.
Calculations:
Z Score Calculation: The Z score is calculated as the difference between the source data point and the moving average divided by the standard deviation.
zscore = (src - (getMA(src, length))) / ta.stdev(src, slength)
Plots:
Z Score Plot: Plots the Z score values, typically in green.
Inverted Z Score Plot: Plots the inverted Z score values (multiplied by -1), typically in red.
Lines:
Zero Line: A horizontal dotted line indicating zero.
Upper Threshold Line: A dotted line representing the upper threshold defined by the number of standard deviations.
Lower Threshold Line: A dotted line representing the lower threshold defined by the negative number of standard deviations.
Bar Color:
The bar color changes based on the Z score values and the predefined standard deviation thresholds. Green bars indicate values above the upper threshold, red bars indicate values below the lower threshold, lime bars indicate positive Z scores, and maroon bars indicate negative Z scores. Neutral values are represented by black bars.
Conclusion:
The Z Score & Trend Following indicator combines the statistical concept of Z score with trend-following characteristics to provide traders with insights into market trends and potential reversal points. By visualizing Z scores alongside trend analysis, traders can make more informed decisions regarding market entry and exit points.
ka66: Externally-Sourced MACDThis indicator generalises the idea of MACD to take any arbitrary series available on the chart, using input.source values .
To provide an overview of the MACD indicator:
You have two EMAs, one with a faster period, usually 12, another with a slower period, usually 26.
You calculate a MACD line, by doing (fastEMA - slowEMA)
You then calculate a Signal Line by taking a moving average of the MACD line over some period.
With this indicator, you can analyse momentum between any 2 series (not just EMAs), they could be raw close prices, other moving averages on the chart including specialised ones, that most MACD implementations won't provide a facility for, for example Kaufman Moving Average.
The chart shows this indicator sourcing 2 inputs from the chart:
A Hull Moving Average as the fast series
And a Simple Moving Average as the slow series
It then calculates the MACD (Series1 - Series2), and a Signal line from the resulting MACD.
A signal series is still calculated manually by the indicator, and thus will be restricted to the provided moving average options (this indicator provides a few like EMA, SMA, Hull, and so on).
Uses of this indicator are essentially what you will use a MACD for:
Evaluate momentum of a strength.
Crossover Signals: MACD vs. Signal, MACD vs. Zero Line, MACD Histogram gradation.
Evaluate overbought/oversold conditions.
As a low-resolution view to confirm price action.
Divergences
MOST on RSIMOST is applied on this RSI moving average with an extra default option added VAR/VIDYA (Variable Index Dynamic Moving Average)
MOST added on RSI has a Moving Average of RSI and a trailing percent stop level of the Moving Average that can be adjusted by changing the length of the MA and %percent of the stop level.
BUY SIGNAL when the Moving Average Line crosses above the MOST Line
LONG CONDITION when the Moving Average is above the MOST
SELL SIGNAL when Moving Average Line crosses below MOST Line
SHORT CONDITION when the Moving Average is below MOST
-MOST indicator advised to use with Variable Moving Average in the sideways market by its developer Anıl Özekşi, so there are a couple of alternative Moving Average OPTIONS to use in the calculation of MOST:
"SMA", "Bollinger Bands", "EMA", "SMMA (RMA)", "WMA", "VWMA", "VAR"
SMA: Simple Moving Average
EMA: Exponential Movin Average
SMMA (RMA: Smoothed Moving Average, Rolling/Running Moving Average
WMA: Weighted Moving Average
WWMA: Welles Wilder's Moving Average
VAR: Variable Index Dynamic Moving Average aka VIDYA
The Moving Average length and stop loss percent values must be increased for less reliable but late signals. Conversely, it must be decreased to have more and faster signals.
As this indicator is derived from TradingView's built-in RSI, it has Bollinger Bands bounding RSI and a tool that can be used for Bullish & Bearish divergences between the price and RSI. (Show Divergence option)
Finally, users may check the box "Show Signals" to visually see the BUY & SELL signals.
Hull AMA SignalsThis script is a comprehensive trading indicator named "Hull AMA Signals", which combines AMA and HSO by LuxAlgo and ther video based strategy techniques to provide buy (long) and sell (short) signals. It overlays directly on the price chart, offering a dynamic and visually intuitive trading aid. The core components of this indicator are Adaptive Moving Averages (AMA), Hull Moving Average (HMA), and a unique Hull squeeze oscillator (HSO), each configured with customizable parameters for flexibility and adaptability to various market conditions.
Features and Components
Adaptive Moving Averages (AMA): This indicator employs two sets of AMAs, each with distinct lengths, multipliers, lags, and overshoot parameters. The AMAs are designed to adapt their sensitivity based on the market's volatility, making them more responsive during significant price movements and less prone to false signals during periods of consolidation.
Hull Moving Average (HMA): The HMA is calculated using a sophisticated algorithm that aims to reduce the lag commonly associated with traditional moving averages. It provides a smoother and more responsive moving average line, which helps in identifying the prevailing market trend more accurately.
Hull Squeeze Oscillator (HSO): A novel component of this indicator, the HSO, is designed to identify potential market breakouts. It does so by comparing the Hull Moving Average's direction and momentum against a dynamically calculated mean, generating bullish or bearish signals based on the crossover and divergence from this mean.
Buy (Long) and Sell (Short) Signals: The script intelligently combines signals from the AMA crossovers and the Hull squeeze oscillator to pinpoint potential buy and sell opportunities. Bullish signals are generated when there's a positive crossover in the AMAs accompanied by a bullish dot from the HSO, whereas bearish signals are indicated by a negative crossover in the AMAs along with a bearish dot from the HSO.
Customization and Style Options: Users have the ability to adjust various parameters such as the length of the moving averages, multipliers, and source data, enabling customization for different trading strategies and asset classes. Additionally, color-coded visual elements like gradients and shapes enhance the readability and instant recognition of trading signals.
Use Cases
Trend Identification: By analyzing the direction and position of the AMAs and HMA, traders can easily discern the prevailing market trend, helping them to align their trades with the market momentum.
Signal Confirmation: The combination of AMA crossovers and HSO signals provides a robust framework for confirming trade entries and exits, potentially increasing the reliability of the trading signals.
Volatility Adaptation: The adaptive nature of the AMAs and the dynamic calculation of the HSO mean allow this indicator to adjust to changing market volatility, making it suitable for a wide range of market environments.
This indicator is suitable for traders looking for a comprehensive and dynamic technical analysis tool that combines trend analysis with signal generation, offering both visual appeal and practical trading utility.
RSI Strategy with Manual TP and SL 19/03/2024This TradingView script implements a simple RSI (Relative Strength Index) strategy with manual take profit (TP) and stop-loss (SL) levels. Let's break down the script and analyze its components:
RSI Calculation: The script calculates the RSI using the specified length parameter. RSI is a momentum oscillator that measures the speed and change of price movements. It ranges from 0 to 100 and typically values above 70 indicate overbought conditions while values below 30 indicate oversold conditions.
Strategy Parameters:
length: Length of the RSI period.
overSold: Threshold for oversold condition.
overBought: Threshold for overbought condition.
trail_profit_pct: Percentage for trailing profit.
Entry Conditions:
For a long position: RSI crosses above 30 and the daily close is above 70% of the highest close in the last 50 bars.
For a short position: RSI crosses below 70 and the daily close is below 130% of the lowest close in the last 50 bars.
Entry Signals:
Long entry is signaled when both conditions for a long position are met.
Short entry is signaled when both conditions for a short position are met.
Manual TP and SL:
Take profit and stop-loss levels are calculated based on the entry price and the specified percentage.
For long positions, the take profit level is set above the entry price and the stop-loss level is set below the entry price.
For short positions, the take profit level is set below the entry price and the stop-loss level is set above the entry price.
Strategy Exits:
Exit conditions are defined for both long and short positions using the calculated take profit and stop-loss levels.
Chart Analysis:
This strategy aims to capitalize on short-term momentum shifts indicated by RSI crossings combined with daily price movements.
It utilizes manual TP and SL levels, providing traders with flexibility in managing their positions.
The strategy may perform well in ranging or oscillating markets where RSI signals are more reliable.
However, it may encounter challenges in trending markets where RSI can remain overbought or oversold for extended periods.
Traders should backtest this strategy thoroughly on historical data and consider optimizing parameters to suit different market conditions.
Risk management is crucial, so traders should carefully adjust TP and SL percentages based on their risk tolerance and market volatility.
Overall, this strategy provides a structured approach to trading based on RSI signals while allowing traders to customize their risk management. However, like any trading strategy, it should be used judiciously and in conjunction with other forms of analysis and risk management techniques.
RSI-HeatmapThis unique indicator is a comprehensive tool designed for traders seeking to gain an edge in the market. It consists of three main components: a revised RSI, a dynamic heatmap, and an integrated alert system.
1.Modified RSI:
Unlike the traditional RSI that calculates delta as the difference between the current price and the previous price (Δ = {price} - {previous price}), this version computes delta by comparing the current price with the price n periods ago (Δ = {price} - {n-th previous price}). This delta is then smoothed using a Volume Weighted Moving Average (VWMA) with a short length to preserve the RSI's core characteristics while adapting it to capture longer-term momentum shifts more effectively.
2.Heatmap:
The heatmap feature introduces a novel approach to visualize market conditions, with 5 high levels and 5 low levels identified around the current price. When the price crosses these thresholds, the RSI-based heatmap changes colors, ranging from blue (indicative of oversold conditions) to red (signaling overbought conditions). This visual tool helps traders quickly gauge the strength and potential reversal points in the market.
3.Alert:
The Alert system employs MACD (Moving Average Convergence Divergence) and CCI (Commodity Channel Index) indicators to signal potential buy or sell opportunities. It categorizes alerts into four color-coded recommendations:
Green and Lighter Green: Strong buy signal, suggesting favorable conditions for entering buy positions.
Blue and Lighter Blue: Moderate buy signal, indicating less robust but potentially profitable buy conditions.
Red and Lighter Red: Strong sell signal, advising traders to consider taking sell positions.
Orange and Lighter Orange: Moderate sell signal, hinting at sell conditions that are not as compelling as those indicated by red.
NASDAQ 100 Peak Hours StrategyNASDAQ 100 Peak Hours Trading Strategy
Description
Our NASDAQ 100 Peak Hours Trading Strategy leverages a carefully designed algorithm to trade within specific hours of high market activity, particularly focusing on the first two hours of the trading session from 09:30 AM to 11:30 AM GMT-5. This period is identified for its increased volatility and liquidity, offering numerous trading opportunities.
The strategy incorporates a blend of technical indicators to identify entry and exit points for both long and short positions. These indicators include:
Exponential Moving Averages (EMAs) : A short-term 9-period EMA and a longer-term 21-period EMA to determine the market trend and momentum.
Relative Strength Index (RSI) : A 14-period RSI to gauge the market's momentum.
Average True Range (ATR) : A 14-period ATR to assess market volatility and to set dynamic stop losses and trailing stops.
Volume Weighted Average Price (VWAP) : To identify the market's average price weighted by volume, serving as a benchmark for the trading day.
Our strategy uniquely applies a volatility filter using the ATR, ensuring trades are only executed in conditions that favor our setup. Additionally, we consider the direction of the EMAs to confirm the market's trend before entering trades.
Originality and Usefulness
This strategy stands out by combining these indicators within the NASDAQ 100's peak hours, exploiting the specific market conditions that prevail during these times. The inclusion of a volatility filter and dynamic stop-loss mechanisms based on the ATR provides a robust method for managing risk.
By focusing on the early trading hours, the strategy aims to capture the initial market movements driven by overnight news and the opening rush, often characterized by higher volatility. This approach is particularly useful for traders looking to maximize gains from short-term fluctuations while limiting exposure to longer-term market uncertainty.
Strategy Results
To ensure the strategy's effectiveness and reliability, it has undergone rigorous backtesting over a significant dataset to produce a sample size of more than 100 trades. This testing phase helps in identifying the strategy's potential in various market conditions, its consistency, and its risk-to-reward ratio.
Our backtesting adheres to realistic trading conditions, accounting for slippage and commission to reflect actual trading scenarios accurately. The strategy is designed with a conservative approach to risk management, advising not to risk more than 5-10% of equity on a single trade. The default settings in the script align with these principles, ensuring that users can replicate our tested conditions.
Using the Strategy
The strategy is designed for simplicity and ease of use:
Trade Hours : Focuses on 09:30 AM to 11:30 AM GMT-5, during the NASDAQ 100's peak activity hours.
Entry Conditions : Trades are initiated based on the alignment of EMAs, RSI, VWAP, and the ATR's volatility filter within the designated time frame.
Exit Conditions : Includes dynamic trailing stops based on ATR, a predefined time exit strategy, and a trend reversal exit condition for risk management.
This script is a powerful tool for traders looking to leverage the NASDAQ 100's peak hours, providing a structured approach to navigating the early market hours with a robust set of criteria for making informed trading decisions.
OBV 1min Volume SqueezeIn the vast realm of trading strategies, few terms evoke as much intrigue as the word "squeeze." It conjures images of pent-up energy, ready to burst forth in a sudden and decisive move. In this blog post, we'll delve into a new trading idea titled the "OBV 1-Minute Volume Squeeze" which aims to catch bigger market movements by fetching 1 minute OBV data on higher time charts.
The Essence of Squeeze
In trading parlance, a "squeeze" typically denotes a scenario where volatility contracts, and prices consolidate within a narrow range. Translating this concept to volume dynamics, a "volume squeeze" suggests a period of compressed volume activity. It is unclear if the Bulls or the Bears are at winning hand and price is thus consolidating. The script calculates buying and selling pressure by fetching 1 min data. The total volume presure is the sum of absolute values of the buying and selling pressure added up. By deviding the Buying volume by the total volume we know the Buying Pressure.
The trading theory suggest that when the buying pressure exceeds a certain value eg. 50% (default value in the script is 55%) it is likely the trend will continue to go up for a longer period of time. Vice Versa when selling pressure is higher, the trend is likely to continue down. In the script you can adjust the sensitivity in such way a higher "Volume Pressure %" result in less trading signals.
Fetching 1 min data
The OBV is a wonderful indicator to measure the buying and selling pressure. A disadvantage of the script is that the total volume pressure is presented as a positive (buying) or negative value (selling) value in the Oscillator. It does not offset the Bulls power against the Bears power at given time. The script aims to do measure the directional volume power by defining a volume pressure % (oulier value) by fetching 1 min OBV data on higher time frame charts comparing the Bulls power against the Bears Power. The code is included below:
// Fetch Lower Timeframe Data in an array
// nV = ZeroValue, sV = Selling Volume, bV = Buying Volume, tV = Total Volume
= request.security_lower_tf(syminfo.tickerid, '1', )
sum_bV_Lengthbars = array.sum(bV)
sum_sV_Lengthbars = array.sum(sV)
sum_tV_Lengthbars = sum_bV_Lengthbars + sum_sV_Lengthbars // Combine buying and selling volumes to get total volume
// Calculate buying and selling volume as percentage of the total volume, but ensure the denominator isn't zero.
buying_percentage = sum_tV_Lengthbars != 0 ? sum_bV_Lengthbars / sum_tV_Lengthbars * 100 : na
selling_percentage = sum_tV_Lengthbars != 0 ? -(sum_sV_Lengthbars / sum_tV_Lengthbars * 100) : na
OBV Oscillator Explanation
The On Balance Volume (OBV) indicator is a technical analysis tool used to measure buying and selling pressure in the market. It does this by keeping a running total of volume flows. OBV is typically calculated by adding the volume on a candle when the price closes higher than the previous candle's close and subtracting the volume on candles when the price closes lower than the previous candles close. If the price closes unchanged from the previous candle, the volume is not added to or subtracted from the OBV. The OBV can be presented as an oscillator. Positve value is the buying pressure and negative values is the selling pressure. In the settings the OBV is calculated based on 1 min data and comes with the following input options for visualization on the chart:
Higher Time Frame Settings (make sure the HTF is higher than the chart you have open)
Type of MA being: EMA, DEMA, TEMA, SMA, WMA, HMA, McGinley
Volume Pressure % (outlier value)
Length of number of bars (of the choosen HTF settings)
Smoothing of number candles of hte opened timechart. Note that higher number of bars to smoothen the indicator results in less signals, but lag of the indicator increases.
The Oscilator contains 3 main lines which are used to determin the entry signals:
Orange Line = the Outlier value in settings described as "Volume Pressure %"
Green Line = Total Buying Pressure OBV
Red Line = Total Selling Pressure OBV
If the Green or Red line is in between the zero line and the orange line the volume is squeezed and waiting for a directional break out.
If the Green line crosses over the orange line the buying pressure is > 55% and triggers a long entry position (green dot). If the Red line crosses under the orange line the selling pressure is > 55% and triggers an short entry (red dot). In the strategy settings this option is called: "Wait for total volume to increase?".
Alternative Strategy Options
In order to play around with different settings users can opt for two more strategy entry settings, called:
"Wait for total volume to deacrease?" --> Only gives a signal when total volume is declining, but buying or selling pressure maintains and crosses % threshold.
"Wait for Pull Back?" --> After a pullback occured and opposite buy/sell pressure gets lower than threshold (direction is shifting)
Turning on all options will logically result into more signals. Note these strategy ideas are experimental and can best be used in confirmation with other indicators.
Moving Average Filter (HTF)
The Oscillator has a horizontal line at the bottom. The line is green when the moving average is in a uptrend and red when the moving average is in a downtrend. The MA Filter comes with the following settings:
Higher Time Frame Setting
Type of MA being: EMA, DEMA, TEMA, SMA, WMA, HMA, McGinley
Length of number of bars (of the choosen HTF settings)
At last I hope you like this volume trading idea and if you have any comments let me know!
MBAND 200 4H BTC/USDT - By MGS-TradingMBAND 200 4H BTC/USDT with RSI and Volume by MGS-Trading: A Neural Network-Inspired Indicator
Introduction:
The MBAND 200 4H BTC/USDT with RSI and Volume represents a groundbreaking achievement in the integration of artificial intelligence (AI) into cryptocurrency market analysis. Developed by MGS-Trading, this indicator is the culmination of extensive research and development efforts aimed at leveraging AI's power to enhance trading strategies. By synthesizing neural network concepts with traditional technical analysis, the MBAND indicator offers a dynamic, multi-dimensional view of the market, providing traders with unparalleled insights and actionable signals.
Innovative Approach:
Our journey to create the MBAND indicator began with a simple question: How can we mimic the decision-making prowess of a neural network in a trading indicator? The answer lay in the weighted aggregation of Exponential Moving Averages (EMAs) from multiple timeframes, each serving as a unique input akin to a neuron in a neural network. These weights are not arbitrary; they were painstakingly optimized through backtesting across various market conditions to ensure they reflect the significance of each timeframe’s contribution to overall market dynamics.
Core Features:
Neural Network-Inspired Weights: The heart of the MBAND indicator lies in its AI-inspired weighting system, which treats each timeframe’s EMA as an input node in a neural network. This allows the indicator to process complex market data in a nuanced and sophisticated manner, leading to more refined and informed trading signals.
Multi-Timeframe EMA Analysis: By analyzing EMAs from 15 minutes to 3 days, the MBAND indicator captures a comprehensive snapshot of market trends, enabling traders to make informed decisions based on a broad spectrum of data.
RSI and Volume Integration: The inclusion of the Relative Strength Index (RSI) and volume data adds layers of confirmation to the signals generated by the EMA bands. This multi-indicator approach helps in identifying high-probability setups, reinforcing the neural network’s concept of leveraging multiple data points for decision-making.
Usage Guidelines:
Signal Interpretation: The MBAND bands provide a visual representation of the market’s momentum and direction. A price moving above the upper band signals strength and potential continuation of an uptrend, while a move below the lower band suggests weakness and a possible downtrend.
Overbought/Oversold Conditions: The RSI component identifies when the asset is potentially overbought (>70) or oversold (<30). Traders should watch for these conditions near the MBAND levels for potential reversal opportunities.
Volume Confirmation: An increase in volume accompanying a price move towards or beyond an MBAND level serves as confirmation of the strength behind the move. This can indicate whether a breakout is likely to sustain or if a reversal has substantial backing.
Strategic Entry and Exit Points: Combine the MBAND readings with RSI and volume indicators to pinpoint strategic entry and exit points. For example, consider entering a long position when the price is near the lower MBAND, RSI indicates oversold conditions, and there is a notable volume increase.
About MGS-Trading:
At MGS-Trading, we are passionate about harnessing the transformative power of AI to revolutionize cryptocurrency trading. Our indicators and tools are designed to provide traders with advanced analytics and insights, drawing on the latest AI techniques and methodologies. The MBAND 200 4H BTC/USDT with RSI and Volume indicator is a prime example of our commitment to innovation, offering traders a sophisticated, AI-enhanced tool for navigating the complexities of the cryptocurrency markets.
Disclaimer:
The MBAND indicator is provided for informational purposes only and does not constitute investment advice. Trading cryptocurrencies involves significant risk and can result in the loss of your investment. We recommend conducting your own research and consulting with a qualified financial advisor before making any trading decisions.
Kalman Filtered RSI Oscillator [BackQuant]Kalman Filtered RSI Oscillator
The Kalman Filtered RSI Oscillator is BackQuants new free indicator designed for traders seeking an advanced, empirical approach to trend detection and momentum analysis. By integrating the robustness of a Kalman filter with the adaptability of the Relative Strength Index (RSI), this tool offers a sophisticated method to capture market dynamics. This indicator is crafted to provide a clearer, more responsive insight into price trends and momentum shifts, enabling traders to make informed decisions in fast-moving markets.
Core Principles
Kalman Filter Dynamics:
At its core, the Kalman Filtered RSI Oscillator leverages the Kalman filter, renowned for its efficiency in predicting the state of linear dynamic systems amidst uncertainties. By applying it to the RSI calculation, the tool adeptly filters out market noise, offering a smoothed price source that forms the basis for more accurate momentum analysis. The inclusion of customizable parameters like process noise, measurement noise, and filter order allows traders to fine-tune the filter’s sensitivity to market changes, making it a versatile tool for various trading environments.
RSI Adaptation:
The RSI is a widely used momentum oscillator that measures the speed and change of price movements. By integrating the RSI with the Kalman filter, the oscillator not only identifies the prevailing trend but also provides a smoothed representation of momentum. This synergy enhances the indicator's ability to signal potential reversals and trend continuations with a higher degree of reliability.
Advanced Smoothing Techniques:
The indicator further offers an optional smoothing feature for the RSI, employing a selection of moving averages (HMA, THMA, EHMA, SMA, EMA, WMA, TEMA, VWMA) for traders seeking to reduce volatility and refine signal clarity. This advanced smoothing mechanism is pivotal for traders looking to mitigate the effects of short-term price fluctuations on the RSI's accuracy.
Empirical Significance:
Empirically, the Kalman Filtered RSI Oscillator stands out for its dynamic adjustment to market conditions. Unlike static indicators, the Kalman filter continuously updates its estimates based on incoming price data, making it inherently more responsive to new market information. This dynamic adaptation, combined with the RSI's momentum analysis, offers a powerful approach to understanding market trends and momentum with a depth not available in traditional indicators.
Trend Identification and Momentum Analysis:
Traders can use the Kalman Filtered RSI Oscillator to identify strong trends and momentum shifts. The color-coded RSI columns provide immediate visual cues on the market's direction and strength, aiding in quick decision-making.
Optimal for Various Market Conditions:
The flexibility in tuning the Kalman filter parameters makes this indicator suitable for a wide range of assets and market conditions, from volatile to stable markets. Traders can adjust the settings based on empirical testing to find the optimal configuration for their trading strategy.
Complementary to Other Analytical Tools:
While powerful on its own, the Kalman Filtered RSI Oscillator is best used in conjunction with other analytical tools and indicators. Combining it with volume analysis, price action patterns, or other trend-following indicators can provide a comprehensive view of the market, allowing for more nuanced and informed trading decisions.
The Kalman Filtered RSI Oscillator is a groundbreaking tool that marries empirical precision with advanced trend analysis techniques. Its innovative use of the Kalman filter to enhance the RSI's performance offers traders an unparalleled ability to navigate the complexities of modern financial markets. Whether you're a novice looking to refine your trading approach or a seasoned professional seeking advanced analytical tools, the Kalman Filtered RSI Oscillator represents a significant step forward in technical analysis capabilities.
Thus following all of the key points here are some sample backtests on the 1D Chart
Disclaimer: Backtests are based off past results, and are not indicative of the future.
INDEX:BTCUSD
INDEX:ETHUSD
BINANCE:SOLUSD
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.
Bollinger Band Wick and SRSI Signals [MW]Introduction
This indicator uses a novel combination of Bollinger Bands, candle wicks crossing the upper and lower Bollinger 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 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 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 and S1 signals can be displayed that use the baseline as the pivot level.
Settings
SIGNALS
Show Bollinger Band Signals (Default: True): Allows signal labels to be shown.
Hide Baseline Signals (Default: False): Baseline signals are on by default. This will turn them off.
Show Wick Signals (Defau
lt: True): Displays signals when wicking occurs.
BOLLINGER BAND SETTINGS
Period length for Bollinger Band Basis (Default: 21): Length of the Bollinger Band (BB) moving average basis line.
Basis MA Type (Default: SMA): The moving average type for the BB Basis line.
Source (Default: “close”): The source of time series data.
Standard Deviation Multiplier (Default: 2.5: The deviation multiplier used to calculate the band distance from the basis line.
WICK SETTINGS FOR BOLLINGER BANDS
Wick Ratio for Bands (Default: 0.3): The ratio of wick size to total candle size for use at upper and lower bands.
Wick Ratio for Baseline (Default: 0.3): The ratio of wick size to total candle size for use at baseline.
WICK SETTINGS FOR CANDLE SIGNALS
Upper Wick Threshold (Default: 50): The percent of upper wick compared to the full candle size or candle body size.
Lower Wick Threshold (Default: 50): The percent of lower wick compared to the full candle size or candle body size.
Use Candle Body (Default: false): Toggles the use of the full candle size versus the candle body size when calculating the wick signal.
VISUAL PREFERENCES
Fill Bands (Default: true): Use a background color inside the Bollinger Bands.
Show Signals (Default: true): Toggle the Bollinger Band upper band, lower band, and baseline signals.
Show Bollinger Bands (Default: true): Show 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.
Calculations
Bollinger Bands 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. Bollinger 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 standard deviations 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 standard deviations 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.
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.
