Farley's Accumulation-Distribution Accelerator (ADA)Farley's ADA (From The Master Swing Trader)
What it is :
ADA is designed to track volume oscillations in the market and reduce the impact of shock events.
It observes the supply-demand dynamics within the market, which can trigger natural levels of price reversals.
How It Works
Volume and Price Relationship: ADA measures the lag between price and volume movements. It highlights when volume leads or lags behind price changes, helping traders identify potential reversals or trends.
Signal Generation: ADA can generate faster and cleaner signals compared to traditional indicators like On-Balance Volume (OBV).
Usage
Support and Resistance: ADA formations can help identify support and resistance levels and trendlines.
detect natural levels where price reversals might occur.
Trend Identification: Look for significant divergences between ADA and price action to identify potential trend reversals.
Volume Analysis: Use ADA to anticipate pauses in price movements when volume leads, and expect dynamic trends when ADA significantly moves ahead of price action.
Komut dosyalarını "trendline" için ara
Volumatic Variable Index Dynamic Average [BigBeluga]The Volumatic VIDYA (Variable Index Dynamic Average) indicator is a trend-following tool that calculates and visualizes both the current trend and the corresponding buy and sell pressure within each trend phase. Using the Variable Index Dynamic Average as the core smoothing technique, this indicator also plots volume levels of lows and highs based on market structure pivot points, providing traders with key insights into price and volume dynamics.
Additionally, it generates delta volume values to help traders evaluate buy-sell pressure balance during each trend, making it a powerful tool for understanding market sentiment shifts.
BTC:
TSLA:
🔵 IDEA
The Volumatic VIDYA indicator's core idea is to provide a dynamic, adaptive smoothing tool that identifies trends while simultaneously calculating the volume pressure behind them. The VIDYA line, based on the Variable Index Dynamic Average, adjusts according to the strength of the price movements, offering a more adaptive response to the market compared to standard moving averages.
By calculating and displaying the buy and sell volume pressure throughout each trend, the indicator provides traders with key insights into market participation. The horizontal lines drawn from the highs and lows of market structure pivots give additional clarity on support and resistance levels, backed by average volume at these points. This dual analysis of trend and volume allows traders to evaluate the strength and potential of market movements more effectively.
🔵 KEY FEATURES & USAGE
VIDYA Calculation:
The Variable Index Dynamic Average (VIDYA) is a special type of moving average that adjusts dynamically to the market’s volatility and momentum. Unlike traditional moving averages that use fixed periods, VIDYA adjusts its smoothing factor based on the relative strength of the price movements, using the Chande Momentum Oscillator (CMO) to capture the magnitude of price changes. When momentum is strong, VIDYA adapts and smooths out price movements quicker, making it more responsive to rapid price changes. This makes VIDYA more adaptable to volatile markets compared to traditional moving averages such as the Simple Moving Average (SMA) or the Exponential Moving Average (EMA), which are less flexible.
// VIDYA (Variable Index Dynamic Average) function
vidya_calc(src, vidya_length, vidya_momentum) =>
float momentum = ta.change(src)
float sum_pos_momentum = math.sum((momentum >= 0) ? momentum : 0.0, vidya_momentum)
float sum_neg_momentum = math.sum((momentum >= 0) ? 0.0 : -momentum, vidya_momentum)
float abs_cmo = math.abs(100 * (sum_pos_momentum - sum_neg_momentum) / (sum_pos_momentum + sum_neg_momentum))
float alpha = 2 / (vidya_length + 1)
var float vidya_value = 0.0
vidya_value := alpha * abs_cmo / 100 * src + (1 - alpha * abs_cmo / 100) * nz(vidya_value )
ta.sma(vidya_value, 15)
When momentum is strong, VIDYA adapts and smooths out price movements quicker, making it more responsive to rapid price changes. This makes VIDYA more adaptable to volatile markets compared to traditional moving averages
Triangle Trend Shift Signals:
The indicator marks trend shifts with up and down triangles, signaling a potential change in direction. These signals appear when the price crosses above a VIDYA during an uptrend or crosses below during a downtrend.
Volume Pressure Calculation:
The Volumatic VIDYA tracks the buy and sell pressure during each trend, calculating the cumulative volume for up and down bars. Positive delta volume occurs during uptrends due to higher buy pressure, while negative delta volume reflects higher sell pressure during downtrends. The delta is displayed in real-time on the chart, offering a quick view of volume imbalances.
Market Structure Pivot Lines with Volume Labels:
The indicator draws horizontal lines based on market structure pivots, which are calculated using the highs and lows of price action. These lines are extended on the chart until price crosses them. The indicator also plots the average volume over a 6-bar range to provide a clearer understanding of volume dynamics at critical points.
🔵 CUSTOMIZATION
VIDYA Length & Momentum: Control the sensitivity of the VIDYA line by adjusting the length and momentum settings, allowing traders to customize the smoothing effect to match their trading style.
Volume Pivot Detection: Set the number of bars to consider for identifying pivots, which influences the calculation of the average volume at key levels.
Band Distance: Adjust the band distance multiplier for controlling how far the upper and lower bands extend from the VIDYA line, based on the ATR (Average True Range).
Price & Volume Breakout Fibonacci Probability [TradeDots]📝 OVERVIEW
The "Price & Volume Breakout Fibonacci Probability" indicator is designed to detect the probability of the maximum run-up and drawdown of each breakout trade on an asset, assisting traders in optimizing their take profit and stop loss strategies.
🧮 CALCULATIONS
The algorithm detects price and volume breakouts to activate the Fibonacci levels displayed on the chart. It calculates these levels using the period pivot high and low, with the close price of the breakout bar as the reference price.
The indicator then forward-tests within an user-selected number of bars, detecting the maximum run-up and drawdown during that period. Consequently, it calculates the probability of the price hitting either side of the Fibonacci levels, showing the likelihood of reaching take profit and stop loss targets for each breakout trade.
📊 EXAMPLE
The above example shows two breakout trades, circled within the yellow rectangle zone.
The first trade has a maximum run-up above the +0.382 Fibonacci level zone and a maximum drawdown below the -0.618 Fibonacci level zone.
When the price reaches the maximum run-up, it only has a ~45% probability of moving further upward into the last two zones (25% + 19.44%). This indicates that setting a take profit at a higher level may have less than a 50% chance of success.
Conversely, when the price reaches its maximum drawdown, there is only an ~8% probability of moving further downward into the last drawdown zone. This could indicate a potential reversal.
⚙️ SETTINGS
Breakout Condition: Determines the type of breakout condition to track: "Price", "Volume", "Price & Volume".
Backtest Period: The maximum run-up and drawdown are detected within this bar period.
Price Breakout Period: Specifies the number of bars the price needs to break out from.
Volume Breakout Period: Specifies the number of bars the volume needs to break out from.
Trendline Confirmation: Confirms that the close price needs to be above the trendline.
📈 HOW TO USE
By understanding the probabilities of price movements to both the upside and downside, traders can set take profit and stop loss targets with greater accuracy.
For instance, placing a stop loss order below the zone with the highest probability minimizes the chances of being stopped out of a profitable trade. Conversely, setting a take profit target at the zone with the highest probability increases the win rate.
Additionally, if the price breaches multiple Fibonacci levels during the breakout period, it may indicate an abnormal state, signaling a potential reversal or pullback. This can help traders exit trades in a timely manner.
Traders can adjust their take profit and stop loss levels based on their individual risk tolerance.
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
Low Volatility Range Breaks [BigBeluga]Low Volatility Range Breaks
The Low Volatility Range Breaks indicator is an advanced technical analysis tool designed to identify periods of low volatility and potential breakout opportunities. By visualizing low volatility ranges as ranges and tracking subsequent price movements, this indicator helps traders spot potential high-probability trade setups.
🔵 KEY FEATURES
● Low Volatility Detection
Identifies periods of low volatility based on highest and lowest periods and user-defined sensitivity
Uses a combination of highest/lowest price calculations and ATR for dynamic adaptation
● Volatility Box Visualization
Creates a box to represent the low volatility range
Box height is adjustable based on ATR multiplier
Includes a mid-line for reference within the box
● Breakout Detection
Identifies when price breaks above or below the volatility box
Labels breakouts as "Break Up" or "Break Dn" on the chart
Changes box appearance to indicate a completed breakout
● Probability Tracking
Counts the number of closes above and below the box's mid-line
Displays probability counters for potential upward and downward moves
Resets counters after a confirmed breakout
🔵 HOW TO USE
● Identifying Low Volatility Periods
Watch for the formation of volatility boxes on the chart
These boxes represent periods where price movement has been confined
● Anticipating Breakouts
Monitor price action as it approaches the edges of the volatility box
Use the probability counters to gauge the likely direction of the breakout
● Trading Breakouts
Consider posible entering trades when price breaks above or below the volatility box
Use the breakout labels ("Break Up" or "Break Dn") as a trading opportunity
● Managing Risk
Use the opposite side of the volatility box as a potential invalidation level
Consider the box height for position sizing and risk management
● Trend Analysis
Multiple upward breakouts may indicate a developing uptrend
Multiple downward breakouts may suggest a forming downtrend
Use in conjunction with other trend indicators for confirmation
🔵 CUSTOMIZATION
The Low Volatility Box Breaks indicator offers several customization options:
Adjust the volatility length to change the period for highest/lowest price calculations
Modify the volatility level to fine-tune the sensitivity of low volatility detection
Adjust the box height multiplier to change the size of volatility boxes
By fine-tuning these settings, traders can adapt the indicator to various market conditions and personal trading strategies.
The Low Volatility Range Breaks indicator provides a unique approach to identifying potential breakout opportunities following periods of consolidation. By visually representing low volatility periods and tracking subsequent price movements, it offers traders a powerful tool for spotting high-probability trade setups.
This indicator can be particularly useful for traders focusing on breakout strategies, mean reversion tactics, or those looking to enter trades at the beginning of new trends. The combination of visual cues (boxes and breakout labels) and quantitative data (probability counters) provides a comprehensive view of market dynamics during and after low volatility periods.
As with all technical indicators, it's recommended to use the Low Volatility Range Breaks indicator in conjunction with other forms of analysis and within the context of a well-defined trading strategy. While this indicator can provide valuable insights into potential breakouts, it should be considered alongside other factors such as overall market trends, volume, and fundamental analysis when making trading decisions.
Jurik Price Bands and Range Box [BigBeluga]Jurik Price Bands and Range Box
The Jurik Price Bands and Range Box - BigBeluga indicator is an advanced technical analysis tool that combines Jurik Moving Average (JMA) based price bands with a dynamic range box. This versatile indicator is designed to help traders identify trends, potential reversal points, and price ranges over a specified period.
🔵 KEY FEATURES
● Jurik Price Bands
Utilizes Jurik Moving Average for smoother, more responsive bands
//@function Calculates Jurik Moving Average
//@param src (float) Source series
//@param len (int) Length parameter
//@param ph (int) Phase parameter
//@returns (float) Jurik Moving Average value
jma(src, len, ph) =>
var float jma = na
var float e0 = 0.0
var float e1 = 0.0
var float e2 = 0.0
phaseRatio = ph < -100 ? 0.5 : ph > 100 ? 2.5 : ph / 100 + 1.5
beta = 0.45 * (len - 1) / (0.45 * (len - 1) + 2)
alpha = math.pow(beta, phaseRatio)
e0 := (1 - alpha) * src + alpha * nz(e0 )
e1 := (src - e0) * (1 - beta) + beta * nz(e1 )
e2 := (e0 + phaseRatio * e1 - nz(jma )) * math.pow(1 - alpha, 2) + math.pow(alpha, 2) * nz(e2 )
jma := e2 + nz(jma )
jma
Consists of an upper band, lower band, and a smooth price line
Bands adapt to market volatility using Jurik MA on ATR
Helps identify potential trend reversal points and overextended market conditions
● Dynamic Range Box
Displays a box representing the price range over a specified period
Calculates high, low, and mid-range prices
Option for adaptive mid-range calculation based on average price
Provides visual representation of recent price action and volatility
● Price Position Indicator
Shows current price position relative to the mid-range
Displays percentage difference from mid-range
Color-coded for quick trend identification
● Dashboard
Displays key information including current price, range high, mid, and low
Shows trend direction based on price position relative to mid-range
Provides at-a-glance market context
🔵 HOW TO USE
● Trend Identification
Use the middle of the Range Box as the primary trend reference point
Price above the middle of the Range Box indicates an uptrend
Price below the middle of the Range Box indicates a downtrend
The bar on the right shows the percentage distance of the close from the middle of the box
This percentage indicates both trend direction and strength
Refer to the dashboard for quick trend direction confirmation
● Potential Reversal Points
Upper and lower Jurik Bands can indicate potential trend reversal points
Price reaching or exceeding these bands may suggest overextended conditions
Watch for price reaction at these levels for possible trend shifts or pullbacks
Range Box high and low can serve as additional reference points for price action
● Range Analysis
Use Range Box to gauge recent price volatility and trading range
Mid-range line can act as a pivot point for short-term price movements
Percentage difference from mid-range helps quantify price position strength
🔵 CUSTOMIZATION
The Jurik Price Bands and Range Box indicator offers several customization options:
Adjust Range Box length for different timeframe analysis
Toggle between standard and adaptive mid-range calculation
Standard:
Adaptive:
Modify Jurik MA length and deviation for band calculation
Toggle visibility of Jurik Bands
By fine-tuning these settings, traders can adapt the indicator to various market conditions and personal trading strategies.
The Jurik Price Bands and Range Box indicator provides a multi-faceted approach to market analysis, combining trend identification, potential reversal point detection, and range analysis in one comprehensive tool. The use of Jurik Moving Average offers a smoother, more responsive alternative to traditional moving averages, potentially providing more accurate signals.
This indicator can be particularly useful for traders looking to understand market context quickly, identify potential reversal points, and assess current market volatility. The combination of dynamic bands, range analysis, and the informative dashboard provides traders with a rich set of data points to inform their trading decisions.
As with all technical indicators, it's recommended to use the Jurik Price Bands and Range Box in conjunction with other forms of analysis and within the context of a well-defined trading strategy. While this indicator provides valuable insights, it should be considered alongside other factors such as overall market conditions, volume, and fundamental analysis when making trading decisions.
DSL Oscillator [BigBeluga]DSL Oscillator BigBeluga
The DSL (Discontinued Signal Lines) Oscillator is an advanced technical analysis tool that combines elements of the Relative Strength Index (RSI), Discontinued Signal Lines, and Zero-Lag Exponential Moving Average (ZLEMA). This versatile indicator is designed to help traders identify trend direction, momentum, and potential reversal points in the market.
What are Discontinued Signal Lines (DSL)?
Discontinued Signal Lines are an extension of the traditional signal line concept used in many indicators. While a standard signal line compares an indicator's value to its smoothed (slightly lagging) state, DSL takes this idea further by using multiple adaptive lines that respond to the indicator's current value. This approach provides a more nuanced view of the indicator's state and momentum, making it easier to determine trends and desired states of the indicator.
🔵 KEY FEATURES
● Discontinued Signal Lines (DSL)
Uses multiple adaptive lines that respond to the indicator's value
Provides a more nuanced view of the indicator's state and momentum
Helps determine trends and desired states of the indicator more effectively
Available in "Fast" and "Slow" modes for different responsiveness
Acts as dynamic support and resistance levels for the oscillator
● DSL Oscillator
Based on a combination of RSI and Discontinued Signal Lines
// Discontinued Signal Lines
dsl_lines(src, length)=>
UP = 0.
DN = 0.
UP := (src > ta.sma(src, length)) ? nz(UP ) + dsl_mode / length * (src - nz(UP )) : nz(UP )
DN := (src < ta.sma(src, length)) ? nz(DN ) + dsl_mode / length * (src - nz(DN )) : nz(DN )
Smoothed using Zero-Lag Exponential Moving Average for reduced lag
// Zero-Lag Exponential Moving Average function
zlema(src, length) =>
lag = math.floor((length - 1) / 2)
ema_data = 2 * src - src
ema2 = ta.ema(ema_data, length)
ema2
Oscillates between 0 and 100
Color-coded for easy interpretation of market conditions
● Signal Generation
Generates buy signals when the oscillator crosses above the lower DSL line below 50
Generates sell signals when the oscillator crosses below the upper DSL line above 50
Signals are visualized on both the oscillator and the main chart
● Visual Cues
Background color changes on signal occurrences for easy identification
Candles on the main chart are colored based on the latest signal
Oscillator line color changes based on its position relative to the DSL lines
🔵 HOW TO USE
● Trend Identification
Use the color and position of the DSL Oscillator relative to its Discontinued Signal Lines to determine the overall market trend
● Entry Signals
Look for buy signals (green circles) when the oscillator crosses above the lower DSL line
Look for sell signals (blue circles) when the oscillator crosses below the upper DSL line
Confirm signals with the triangles on the main chart and background color changes
● Exit Signals
Consider exiting long positions on exit signals and short positions on Entery signals
Watch for the oscillator crossing back between the DSL lines as a potential early exit signal
● Momentum Analysis
Strong momentum is indicated when the oscillator moves rapidly towards extremes and away from the DSL lines
Weakening momentum can be spotted when the oscillator struggles to reach new highs or lows, or starts converging with the DSL lines
The space between the DSL lines can indicate potential momentum strength - wider gaps suggest stronger trends
● Confirmation
Use the DSL lines as dynamic support/resistance levels for the oscillator
Look for convergence between oscillator signals and price action on the main chart
Combine signals with other technical indicators or chart patterns for stronger confirmation
🔵 CUSTOMIZATION
The DSL Oscillator offers several customization options:
Adjust the main calculation length for the DSL lines
Choose between "Fast" and "Slow" modes for the DSL lines calculation
By fine-tuning these settings, traders can adapt the DSL Oscillator to various market conditions and personal trading strategies.
The DSL Oscillator provides a multi-faceted approach to market analysis, combining trend identification, momentum assessment, and signal generation in one comprehensive tool. Its dynamic nature and visual cues make it suitable for both novice and experienced traders across various timeframes and markets. The integration of RSI, Discontinued Signal Lines, and ZLEMA offers traders a sophisticated yet intuitive tool to inform their trading decisions.
The use of Discontinued Signal Lines sets this oscillator apart from traditional indicators by providing a more adaptive and nuanced view of market conditions. This can potentially lead to more accurate trend identification and signal generation, especially in markets with varying volatility.
Traders can use the DSL Oscillator to identify trends, spot potential reversals, and gauge market momentum. The combination of the oscillator, dynamic signal lines, and clear visual signals provides a holistic view of market conditions. As with all technical indicators, it's recommended to use the DSL Oscillator in conjunction with other forms of analysis and within the context of a well-defined trading strategy.
Power Trends [UkutaLabs]█ OVERVIEW
The Power Trends Indicator is a versatile trading toolkit that offers unique insight into key price levels in the market. This script uses currently relevant price-action information to automatically detect pivot levels and use them to create powerful trendlines.
The aim of this script is to improve the trading experience of users by offering a versatile toolkit that can be used in a wide variety of trading strategies to help simplify the complexities of the market.
█ USAGE
The Power Trends Indicator will automatically identify pivot points in real-time using recent price-action information to ensure that all points being identified are relevant. Using these pivot points, the script then draws powerful trend lines that can be used as levels of resistance and support.
To ensure that only the most relevant information is being presented, only the most recent trend lines will be displayed on the user’s charts. As new trend lines are being drawn, older trend lines will become thinner so that traders can identify the most relevant lines at a glance.
The price of the most recent high and low pivot points will also be displayed on the chart and can be used as further levels of resistance and support.
When a recent pivot level is broken, it will be identified as a Break of Structure. This signifies that there may have been a change in market strength.
The Power Trends Indicator also supports multiple time frame mapping, allowing you to mirror the trend lines that would be drawn on higher time frame charts onto lower time frame charts. This feature allows traders to be aware of the market structure of multiple charts at a glance from a single chart.
When mirroring some higher time frame trend lines, lines may appear to not align properly with current time frame bars. This is done intentionally to ensure lines are being drawn accurately to their position on the higher time frame charts.
█ SETTINGS
Current Time Frame
• Display (On/Off): Determines whether or not trend lines are drawn from the current time frame.
• High Color: Determines the color of trend lines drawn on high pivots.
• Low Color: Determines the color of trend lines drawn on low pivots.
5 Minute (Higher Time Frame)
• Display (On/Off): Determines whether or not trend lines are drawn from the 5 minute higher time frame.
• High Color: Determines the color of trend lines drawn on high pivots from the 5 minute higher time frame.
• Low Color: Determines the color of trend lines drawn on low pivots from the 5 minute higher time frame.
15 Minute (Higher Time Frame)
• Display (On/Off): Determines whether or not trend lines are drawn from the 15 minute higher time frame.
• High Color: Determines the color of trend lines drawn on high pivots from the 15 minute higher time frame.
• Low Color: Determines the color of trend lines drawn on low pivots from the 15 minute higher time frame.
30 Minute (Higher Time Frame)
• Display (On/Off): Determines whether or not trend lines are drawn from the 30 minute higher time frame.
• High Color: Determines the color of trend lines drawn on high pivots from the 30 minute higher time frame.
• Low Color: Determines the color of trend lines drawn on low pivots from the 30 minute higher time frame.
60 Minute (Higher Time Frame)
• Display (On/Off): Determines whether or not trend lines are drawn from the 60 minute higher time frame.
• High Color: Determines the color of trend lines drawn on high pivots from the 60 minute higher time frame.
• Low Color: Determines the color of trend lines drawn on low pivots from the 60 minute higher time frame.
240 Minute (Higher Time Frame)
• Display (On/Off): Determines whether or not trend lines are drawn from the 240 minute higher time frame.
• High Color: Determines the color of trend lines drawn on high pivots from the 240 minute higher time frame.
• Low Color: Determines the color of trend lines drawn on low pivots from the 240 minute higher time frame.
Daily (Higher Time Frame)
• Display (On/Off): Determines whether or not trend lines are drawn from the daily time frame.
• High Color: Determines the color of trend lines drawn on high pivots from the daily higher time frame.
• Low Color: Determines the color of trend lines drawn on low pivots from the daily higher time frame.
Lin Reg (Linear Regression) Support and Resistance by xxMargauxLin Reg (Linear Regression) Support & Resistance by xxMargaux 💸
This indicator plots three linear regression lines (Lin Reg) on the price chart, providing insights into potential support and resistance levels. It calculates Lin Reg lines based on user-defined lengths and sources.
This indicator's settings were initially configured for MNQ1! (E-Mini Nasdaq 100 futures contracts). But works as intended on any security and on any timeframe.
When price is below a given Lin Reg line, that line will be red and may serve as resistance as price moves up towards the line. That is, it may be a potential short entry opportunity. When price is above a given Lin Reg line, that line will be green and may serve as support as price continues up from the line. That is, it may be a potential long entry opportunity.
When price starts to break sideways or down through the Lin Reg lines, this may signal a reversal from uptrend to downtrend. When price starts to break sideways or up through the Lin Reg Lines, this may signal a reversal from downtrend to uptrend. In very strong trends, breaking through the lines briefly may provide an entry opportunity, but be cautious because a trend reversal may also be possible.
Inputs:
Length of Price Lin Reg Lines: Customize the lengths of the three Lin Reg lines.
Source for Price Lin Reg Lines: Choose the source for each Lin Reg line.
Source for Security Price: Select the price source for the security.
Features:
Trend Analysis: Assists in visualizing price trends based on the relationship between the security price and Lin Reg lines, which will be colored according to whether price is above or below each Lin Reg line.
Customizable Colors: When price is above a Lin Reg line that line will be green. When price is below a Lin Reg line, that line will be red.
Here's a beginner-friendly explanation of linear regression lines 💡
Best-Fit Line: Imagine you have a scatter plot of closing prices on a chart. Linear regression aims to find the straight line that best fits the overall trend of these data points. It's like drawing a line through the center of the data that minimizes the distance between the line and each data point.
Trend Identification: Once the linear regression line is plotted on a price chart, it provides a visual representation of the trend. If the price is generally rising, the linear regression line will slope upwards. If the price is falling, the line will slope downwards. This helps traders identify whether the trend is bullish (upward) or bearish (downward).
Support and Resistance: Linear regression lines can also act as dynamic support and resistance levels. When the price is above the linear regression line, it may act as support, meaning the price tends to bounce off the line and continue higher. Conversely, when the price is below the line, it may act as resistance, with the price encountering selling pressure and potentially reversing lower.
Reversal Signals: Changes in the slope or direction of the linear regression line can signal potential trend reversals. For example, if the price breaks above a downward-sloping linear regression line, it may indicate a shift from a downtrend to an uptrend, and vice versa.
Adjustable Parameters: Traders can customize the length of the linear regression line by adjusting the period over which it's calculated. Shorter periods may be more sensitive to recent price changes, while longer periods may provide a smoother trend line.
RSI Confirm Trend with Williams (W%R)RSI Confirm Trend with Williams (W%R)
This is the "RSI Confirm Trend with Williams (W%R)" indicator
This is a modification of the "RSI Trends" indicator by zzzcrypto123.
What Is the Relative Strength Index (RSI)?
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.
What is Williams %R?
Williams %R, also known as the Williams Percent Range, is a type of momentum indicator that moves between 0 and -100 and measures overbought and oversold levels. The Williams %R may be used to find entry and exit points in the market. The indicator is very similar to the Stochastic oscillator and is used in the same way. It was developed by Larry Williams and it compares a stock’s closing price to the high-low range over a specific period, typically 14 days or periods.
How Does "RSI Confirm Trend with Williams (W%R)" work?
This indicator combines the momentum of both RSI and Williams %R by adding upper and lower thresholds. When the thresholds are broken, this indicator changes color from gray to either green or red.
What Are The Thresholds?
The default RSI thresholds are 55 and 45. These values are configurable.
The default Williams %R thresholds are 80 and 20. These values are configurable and made positive so it can be plotted against the RSI line.
How To Use?
When the RSI exceeded the upper/lower thresholds, the RSI line color will change from gray to lighter green/red color.
When the Williams %R exceeded the upper/lower thresholds, the RSI color will change to darker green/red color signifying a strong momentum in that direction.
When the RSI color is gray, this means the RSI and Williams %R thresholds are not broken which can also signify as no trend or consolidation.
The Williams %R line is not displayed by default but can be enabled using the checkbox provided in the Style tab.
This "RSI Confirm Trend with Williams (W%R)" indicator can be combined with other technical indicators to verify the idea behind this theory.
-----------------
Disclaimer
The information contained in this indicator does not constitute any financial advice or a solicitation to buy or sell any securities of any type.
My scripts/indicators/ideas are for educational purposes only!
ZigZag Library [TradingFinder]🔵 Introduction
The "Zig Zag" indicator is an analytical tool that emerges from pricing changes. Essentially, it connects consecutive high and low points in an oscillatory manner. This method helps decipher price changes and can also be useful in identifying traditional patterns.
By sifting through partial price changes, "Zig Zag" can effectively pinpoint price fluctuations within defined time intervals.
🔵 Key Features
1. Drawing the Zig Zag based on Pivot points :
The algorithm is based on pivots that operate consecutively and alternately (switch between high and low swing). In this way, zigzag lines are connected from a swing high to a swing low and from a swing low to a swing high.
Also, with a very low probability, it is possible to have both low pivots and high pivots in one candle. In these cases, the algorithm tries to make the best decision to make the most suitable choice.
You can control what period these decisions are based on through the "PiPe" parameter.
2.Naming and labeling each pivot based on its position as "Higher High" (HH), "Lower Low" (LL), "Higher Low" (HL), and "Lower High" (LH).
Additionally, classic patterns such as HH, LH, LL, and HL can be recognized. All traders analyzing financial markets using classic patterns and Elliot Waves can benefit from the "zigzag" indicator to facilitate their analysis.
" HH ": When the price is higher than the previous peak (Higher High).
" HL ": When the price is higher than the previous low (Higher Low).
" LH ": When the price is lower than the previous peak (Lower High).
" LL ": When the price is lower than the previous low (Lower Low).
🔵 How to Use
First, you can add the library to your code as shown in the example below.
import TFlab/ZigZagLibrary_TradingFinder/1 as ZZ
Function "ZigZag" Parameters :
🟣 Logical Parameters
1. HIGH : You should place the "high" value here. High is a float variable.
2. LOW : You should place the "low" value here. Low is a float variable.
3. BAR_INDEX : You should place the "bar_index" value here. Bar_index is an integer variable.
4. PiPe : The desired pivot period for plotting Zig Zag is placed in this parameter. For example, if you intend to draw a Zig Zag with a Swing Period of 5, you should input 5.
PiPe is an integer variable.
Important :
Apart from the "PiPe" indicator, which is part of the customization capabilities of this indicator, you can create a multi-time frame mode for the indicator using 3 parameters "High", "Low" and "BAR_INDEX". In this way, instead of the data of the current time frame, use the data of other time frames.
Note that it is better to use the current time frame data, because using the multi-time frame mode is associated with challenges that may cause bugs in your code.
🟣 Setting Parameters
5. SHOW_LINE : It's a boolean variable. When true, the Zig Zag line is displayed, and when false, the Zig Zag line display is disabled.
6. STYLE_LINE : In this variable, you can determine the style of the Zig Zag line. You can input one of the 3 options: line.style_solid, line.style_dotted, line.style_dashed. STYLE_LINE is a constant string variable.
7. COLOR_LINE : This variable takes the input of the line color.
8. WIDTH_LINE : The input for this variable is a number from 1 to 3, which is used to adjust the thickness of the line that draws the Zig Zag. WIDTH_LINE is an integer variable.
9. SHOW_LABEL : It's a boolean variable. When true, labels are displayed, and when false, label display is disabled.
10. COLOR_LABEL : The color of the labels is set in this variable.
11. SIZE_LABEL : The size of the labels is set in this variable. You should input one of the following options: size.auto, size.tiny, size.small, size.normal, size.large, size.huge.
12. Show_Support : It's a boolean variable that, when true, plots the last support line, and when false, disables its plotting.
13. Show_Resistance : It's a boolean variable that, when true, plots the last resistance line, and when false, disables its plotting.
Suggestion :
You can use the following code snippet to import Zig Zag into your code for time efficiency.
//import Library
import TFlab/ZigZagLibrary_TradingFinder/1 as ZZ
// Input and Setting
// Zig Zag Line
ShZ = input.bool(true , 'Show Zig Zag Line', group = 'Zig Zag') //Show Zig Zag
PPZ = input.int(5 ,'Pivot Period Zig Zag Line' , group = 'Zig Zag') //Pivot Period Zig Zag
ZLS = input.string(line.style_dashed , 'Zig Zag Line Style' , options = , group = 'Zig Zag' )
//Zig Zag Line Style
ZLC = input.color(color.rgb(0, 0, 0) , 'Zig Zag Line Color' , group = 'Zig Zag') //Zig Zag Line Color
ZLW = input.int(1 , 'Zig Zag Line Width' , group = 'Zig Zag')//Zig Zag Line Width
// Label
ShL = input.bool(true , 'Label', group = 'Label') //Show Label
LC = input.color(color.rgb(0, 0, 0) , 'Label Color' , group = 'Label')//Label Color
LS = input.string(size.tiny , 'Label size' , options = , group = 'Label' )//Label size
Show_Support= input.bool(false, 'Show Last Support',
tooltip = 'Last Support' , group = 'Support and Resistance')
Show_Resistance = input.bool(false, 'Show Last Resistance',
tooltip = 'Last Resistance' , group = 'Support and Resistance')
//Call Function
ZZ.ZigZag(high ,low ,bar_index ,PPZ , ShZ ,ZLS , ZLC, ZLW ,ShL , LC , LS , Show_Support , Show_Resistance )
Heikin Ashi and Optimized Trend Tracker and PVSRA [Erebor]Heikin Ashi Candles
Let's consider a modification to the traditional “Heikin Ashi Candles” where we introduce a new parameter: the period of calculation. The traditional HA candles are derived from the open , high low , and close prices of the underlying asset.
Now, let's introduce a new parameter, period, which will determine how many periods are considered in the calculation of the HA candles. This period parameter will affect the smoothing and responsiveness of the resulting candles.
In this modification, instead of considering just the current period, we're averaging or aggregating the prices over a specified number of periods . This will result in candles that reflect a longer-term trend or sentiment, depending on the chosen period value.
For example, if period is set to 1, it would essentially be the same as traditional Heikin Ashi candles. However, if period is set to a higher value, say 5, each candle will represent the average price movement over the last 5 periods, providing a smoother representation of the trend but potentially with delayed signals compared to lower period values.
Traders can adjust the period parameter based on their trading style, the timeframe they're analyzing, and the level of smoothing or responsiveness they prefer in their candlestick patterns.
Optimized Trend Tracker
The "Optimized Trend Tracker" is a proprietary trading indicator developed by TradingView user ANIL ÖZEKŞİ. It is designed to identify and track trends in financial markets efficiently. The indicator attempts to smooth out price fluctuations and provide clear signals for trend direction.
The Optimized Trend Tracker uses a combination of moving averages and adaptive filters to detect trends. It aims to reduce lag and noise typically associated with traditional moving averages, thereby providing more timely and accurate signals.
Some of the key features and applications of the OTT include:
• Trend Identification: The indicator helps traders identify the direction of the prevailing trend in a market. It distinguishes between uptrends, downtrends, and sideways consolidations.
• Entry and Exit Signals: The OTT generates buy and sell signals based on crossovers and direction changes of the trend. Traders can use these signals to time their entries and exits in the market.
• Trend Strength: It also provides insights into the strength of the trend by analyzing the slope and momentum of price movements. This information can help traders assess the conviction behind the trend and adjust their trading strategies accordingly.
• Filter Noise: By employing adaptive filters, the indicator aims to filter out market noise and false signals, thereby enhancing the reliability of trend identification.
• Customization: Traders can customize the parameters of the OTT to suit their specific trading preferences and market conditions. This flexibility allows for adaptation to different timeframes and asset classes.
Overall, the OTT can be a valuable tool for traders seeking to capitalize on trending market conditions while minimizing false signals and noise. However, like any trading indicator, it is essential to combine its signals with other forms of analysis and risk management strategies for optimal results. Additionally, traders should thoroughly back-test the indicator and practice using it in a demo environment before applying it to live trading.
PVSRA (Price, Volume, S&R Analysis)
“PVSRA” (Price, Volume, S&R Analysis) is a trading methodology and indicator that combines the analysis of price action, volume, and support/resistance levels to identify potential trading opportunities in financial markets. It is based on the idea that price movements are influenced by the interplay between supply and demand, and analyzing these factors together can provide valuable insights into market dynamics.
Here's a breakdown of the components of PVSRA:
• Price Action Analysis: PVSRA focuses on analyzing price movements and patterns on price charts, such as candlestick patterns, trendlines, chart patterns (like head and shoulders, triangles, etc.), and other price-based indicators. Traders using PVSRA pay close attention to how price behaves at key support and resistance levels and look for patterns that indicate potential shifts in market sentiment.
• Volume Analysis: Volume is an essential component of PVSRA. Traders monitor changes in trading volume to gauge the strength or weakness of price movements. An increase in volume during a price move suggests strong participation and conviction from market participants, reinforcing the validity of the price action. Conversely, low volume during price moves may indicate lack of conviction and potential reversals.
• Support and Resistance (S&R) Analysis: PVSRA incorporates the identification and analysis of support and resistance levels on price charts. Support levels represent areas where buying interest is expected to be strong enough to prevent further price declines, while resistance levels represent areas where selling interest may prevent further price advances. These levels are often identified using historical price data, trendlines, moving averages, pivot points, and other technical analysis tools.
The PVSRA methodology combines these three elements to generate trading signals and make trading decisions. Traders using PVSRA typically look for confluence between price action, volume, and support/resistance levels to confirm trade entries and exits. For example, a bullish reversal signal may be considered stronger if it occurs at a significant support level with increasing volume.
It's important to note that PVSRA is more of a trading approach or methodology rather than a specific indicator with predefined rules. Traders may customize their analysis based on their preferences and trading style, incorporating additional technical indicators or filters as needed. As with any trading strategy, risk management and proper trade execution are essential components of successful trading with PVSRA.
The following types of moving average have been included: "SMA", "EMA", "SMMA (RMA)", "WMA", "VWMA", "HMA", "KAMA", "LSMA", "TRAMA", "VAR", "DEMA", "ZLEMA", "TSF", "WWMA". Thanks to the authors.
Thank you for your indicator “Optimized Trend Tracker”. © kivancozbilgic
Thank you for your indicator “PVSRA Volume Suite”. © creengrack
Thank you for your programming language, indicators and strategies. © TradingView
Kind regards.
© Erebor_GIT
Percent Rank HistogramThis Pine script indicator is designed to create a visual representation of the percent rank for multiple financial instruments. Here's a breakdown of its key features:
Percent Rank Calculation:
The core functionality of this Pine script indicator revolves around the calculation of the percent rank for each selected financial instrument.
The percent rank is a statistical measure that indicates the percentage of historical data points that are less than or equal to the current value in a given series.
Symbol Selection:
The script allows the user to select up to 10 financial instruments (tickers) for analysis. The default symbols include various cryptocurrencies such as BTCUSD, ETHUSD etc., and TOTAL market cap at ticker 1, to show overal trend of crypto market.
(Top 9 Coins by market cap).
Columns and Colors:
The script visually represents the percent rank using columns based on lines.
The color of each column is determined by a gradient from red to green based on the calculated percent rank, providing a quick visual indication of the instrument's relative performance.
BTC Trending Up while other coins are underperformance:
Labels:
Labels are displayed on the chart, indicating the symbol name and the corresponding percent rank percentage.
The labels include directional arrows (▲ or ▼) to denote whether the percent rank is increasing or decreasing.
Customization:
Users can customize parameters such as the percent rank length and column width to adapt the indicator to their specific preferences, or select needed assets to compare them to each other.
Chart Desk and Scales:
The script includes the visualization of a chart desk with scale lines to provide additional context to the chart. When Percent Rank above middle scale line (50) usually it signaling about asset trending up and below 50 asset trending down.
Mozilla Public License:
The script is subject to the terms of the Mozilla Public License 2.0.
This indicator is useful for traders and analysts interested in visually assessing the percent rank of multiple financial instruments simultaneously, helping them identify potential opportunities or trends in the market.
Price SextantThe provided Pine Script™ code is for a technical analysis indicator called "Price Sextant." This indicator helps visualize the price position relative to its linear regression and standard deviation levels. Here's a brief description:
Price Sextant Indicator:
Purpose:
The Price Sextant indicator aims to show the current price's deviation from the linear regression line by dividing the price chart into different zones or sextants.
Components:
Linear Regression: The script calculates a linear regression line based on the closing prices over a specified length (default is 50 bars).
Standard Deviation Sections: It then computes standard deviation levels from the linear regression, creating upper and lower sections around the regression line.
Scoring: Each section is assigned a numerical score, and labels with corresponding scores are displayed on the chart.
Arrow and Midline: An arrow is drawn to indicate the current price's position in relation to the regression line and standard deviation bands. It changes color based in what section it is:
orange section shows a ranging price, below orange section -1 arrow turns red and show down trend and if arrow above +1 section it turns green and show strong up trend of price.
A midline is plotted to mark the position of the linear regression line.
Sextant Description:
In navigation, a sextant is an instrument used to measure the angle between two visible objects.
In the context of this indicator, the term "Sextant" is likely used metaphorically to describe the division of the price chart into six sections or zones based on the linear regression and standard deviation bands.
This indicator can help traders identify potential overbought or oversold conditions, as well as assess the strength and direction of the trend.
Please note that the effectiveness of the indicator depends on various factors, and it's advisable to use it in conjunction with other analysis tools for a comprehensive trading strategy.
Machine Learning: Trend Lines [YinYangAlgorithms]Trend lines have always been a key indicator that may help predict many different types of price movements. They have been well known to create different types of formations such as: Pennants, Channels, Flags and Wedges. The type of formation they create is based on how the formation was created and the angle it was created. For instance, if there was a strong price increase and then there is a Wedge where both end points meet, this is considered a Bull Pennant. The formations Trend Lines create may be powerful tools that can help predict current Support and Resistance and also Future Momentum changes. However, not all Trend Lines will create formations, and alone they may stand as strong Support and Resistance locations on the Vertical.
The purpose of this Indicator is to apply Machine Learning logic to a Traditional Trend Line Calculation, and therefore allowing a new approach to a modern indicator of high usage. The results of such are quite interesting and goes to show the impacts a simple KNN Machine Learning model can have on Traditional Indicators.
Tutorial:
There are a few different settings within this Indicator. Many will greatly impact the results and if any are changed, lots will need ‘Fine Tuning’. So let's discuss the main toggles that have great effects and what they do before discussing the lengths. Currently in this example above we have the Indicator at its Default Settings. In this example, you can see how the Trend Lines act as key Support and Resistance locations. Due note, Support and Resistance are a relative term, as is their color. What starts off as Support or Resistance may change when the price crosses over / under them.
In the example above we have zoomed in and circled locations that exhibited markers of Support and Resistance along the Trend Lines. These Trend Lines are all created using the Default Settings. As you can see from the example above; just because it is a Green Upwards Trend Line, doesn’t mean it’s a Support Line. Support and Resistance is always shifting on Trend Lines based on the prices location relative to them.
We won’t go through all the Formations Trend Lines make, but the example above, we can see the Trend Lines formed a Downward Channel. Channels are when there are two parallel downwards Trend Lines that are at a relatively similar angle. This means that they won’t ever meet. What may happen when the price is within these channels, is it may bounce between the upper and lower bounds. These Channels may drive the price upwards or downwards, depending on if it is in an Upwards or Downwards Channel.
If you refer to the example above, you’ll notice that the Trend Lines are formed like traditional Trend Lines. They don’t stem from current Highs and Lows but rather Machine Learning Highs and Lows. More often than not, the Machine Learning approach to Trend Lines cause their start point and angle to be quite different than a Traditional Trend Line. Due to this, it may help predict Support and Resistance locations at are more uncommon and therefore can be quite useful.
In the example above we have turned off the toggle in Settings ‘Use Exponential Data Average’. This Settings uses a custom Exponential Data Average of the KNN rather than simply averaging the KNN. By Default it is enabled, but as you can see when it is disabled it may create some pretty strong lasting Trend Lines. This is why we advise you ZOOM OUT AS FAR AS YOU CAN. Trend Lines are only displayed when you’ve zoomed out far enough that their Start Point is visible.
As you can see in this example above, there were 3 major Upward Trend Lines created in 2020 that have had a major impact on Support and Resistance Locations within the last year. Lets zoom in and get a closer look.
We have zoomed in for this example above, and circled some of the major Support and Resistance locations that these Upward Trend Lines may have had a major impact on.
Please note, these Machine Learning Trend Lines aren’t a ‘One Size Fits All’ kind of thing. They are completely customizable within the Settings, so that you can get a tailored experience based on what Pair and Time Frame you are trading on.
When any values are changed within the Settings, you’ll likely need to ‘Fine Tune’ the rest of the settings until your desired result is met. By default the modifiable lengths within the Settings are:
Machine Learning Length: 50
KNN Length:5
Fast ML Data Length: 5
Slow ML Data Length: 30
For example, let's toggle ‘Use Exponential Data Averages’ back on and change ‘Fast ML Data Length’ from 5 to 20 and ‘Slow ML Data Length’ from 30 to 50.
As you can in the example above, all of the lines have changed. Although there are still some strong Support Locations created by the Upwards Trend Lines.
We will conclude our Tutorial here. Hopefully you’ve learned how to use Machine Learning Trend Lines and will be able to now see some more unorthodox Support and Resistance locations on the Vertical.
Settings:
Use Machine Learning Sources: If disabled Traditional Trend line sources (High and Low) will be used rather than Rational Quadratics.
Use KNN Distance Sorting: You can disable this if you wish to not have the Machine Learning Data sorted using KNN. If disabled trend line logic will be Traditional.
Use Exponential Data Average: This Settings uses a custom Exponential Data Average of the KNN rather than simply averaging the KNN.
Machine Learning Length: How strong is our Machine Learning Memory? Please note, when this value is too high the data is almost 'too' much and can lead to poor results.
K-Nearest Neighbour (KNN) Length: How many K-Nearest Neighbours are allowed with our Distance Clustering? Please note, too high or too low may lead to poor results.
Fast ML Data Length: Fast and Slow speed needs to be adjusted properly to see results. 3/5/7 all seem to work well for Fast.
Slow ML Data Length: Fast and Slow speed needs to be adjusted properly to see results. 20 - 50 all seem to work well for Slow.
If you have any questions, comments, ideas or concerns please don't hesitate to contact us.
HAPPY TRADING!
Ehlers DecyclerJohn F. Ehlers introuced Decycler in his book "Cycle Analytics for Traders", chapter 4.
The decycler is designed to remove the influence of shorter cycle fluctuations, resulting in an output that closely resembles a one-pole low-pass filter.
A standout feature of the decycler is its notably minimal lag. The most extended cycle elements experience a delay of less than five bars. When considering a frequency of 0.05 cycles per bar (equivalent to a 20-bar cycle period), the lag approximates 1.5 bars. Components with a higher frequency face even lesser delays. Consequently, any higher-frequency variations that pass the filter's attenuation align closely with the price fluctuations. This makes the decycler an optimal "immediate trend detector," giving a true depiction of the data's trend.
While the SuperSmoother filter can yield a comparably smoothed output, the decycler typically exhibits less lag when the two are juxtaposed. It's worth noting that the decycler operates as a one-pole filter, implying it doesn't have the best filtering capabilities. It's not advisable to use the decycler as a smoothing filter to eliminate aliasing disturbances. Instead, its application should focus on generating an immediate trend representation, especially when choosing a larger cutoff period. The broad cutoff period equips the decycler with the ability to reduce aliasing disturbances, given that it's significantly distant from the Nyquist frequency.
There are already several decycler indicators on Tradingview, but I like to structure the code and highlight the main components as functions rather than hiding them in the code. I hope this is useful for those who are starting to learn Pine Script.
Traders Trend DashboardThe Traders Trend Dashboard (TTD) is a comprehensive trend analysis tool designed to assist traders in making informed trading decisions across various markets and timeframes. Unlike conventional trend-following scripts, TTD goes beyond simple trend detection by incorporating a unique combination of moving averages and a visual dashboard, providing traders with a clear and actionable overview of market trends. Here's how TTD stands out from the crowd:
Originality and Uniqueness:
TTD doesn't rely on just one moving average crossover to detect trends. Instead, it employs a dynamic approach by comparing two moving averages of distinct periods across multiple timeframes. This innovative methodology enhances trend detection accuracy and reduces false signals commonly associated with single moving average systems.
Market Applicability:
TTD is versatile and adaptable to various financial markets, including forex, stocks, cryptocurrencies, and commodities. Its flexibility ensures that traders can utilize it across different asset classes and capitalize on market opportunities.
Optimal Timeframe Utilization:
Unlike many trend indicators that work best on specific timeframes, TTD caters to traders with diverse trading preferences. It offers support for intraday trading (1m, 3m, 5m), short-term trading (15m, 30m, 1h), and swing trading (4h, D, W, M), making it suitable for a wide range of trading styles.
Underlying Conditions and Interpretation:
TTD is particularly effective during trending markets, where its multi-timeframe approach helps identify consistent trends across various time horizons. In ranging markets, TTD can indicate potential reversals or areas of uncertainty when moving averages converge or cross frequently.
How to Use TTD:
1. Timeframe Selection: Choose the relevant timeframes based on your trading style and preferences. Enable or disable timeframes in the settings to focus on the most relevant ones for your strategy.
2. Dashboard Interpretation: The TTD dashboard displays green (🟢) and red (🔴) symbols to indicate the relationship between two moving averages. A green symbol suggests that the shorter moving average is above the longer one, indicating a potential bullish trend. A red symbol suggests the opposite, indicating a potential bearish trend.
3. Confirmation and Strategy: Consider TTD signals as confirmation for your trading strategy. For instance, in an uptrend, look for long opportunities when the dashboard displays consistent green symbols. Conversely, in a downtrend, focus on short opportunities when red symbols dominate.
4. Risk Management: As with any indicator, use TTD in conjunction with proper risk management techniques. Avoid trading solely based on indicator signals; instead, integrate them into a comprehensive trading plan.
Conclusion:
The Traders Trend Dashboard (TTD) offers traders a powerful edge in trend analysis, combining innovation, versatility, and clarity. By understanding its unique methodology and integrating its signals with your trading strategy, you can make more informed trading decisions across various markets and timeframes. Elevate your trading with TTD and unlock a new level of trend analysis precision.
Linear On MACDUnlocking the Magic of Linear Regression in TradingView
In the ever-evolving world of financial markets, traders and investors seek effective tools to gauge price movements, make informed decisions, and achieve their financial goals. One such tool that has proven its worth over time is linear regression, a mathematical concept that has found its way into technical analysis and trading strategies. In this blog post, we will explore the magic behind linear regression, delve into its history, and understand how it's widely used as a technical indicator.
The Birth of Linear Regression: From Mathematics to Trading
Linear regression is a statistical method that aims to model the relationship between two variables by fitting a linear equation to observed data. The formula for a linear regression line is typically expressed as y = a + bx, where y is the dependent variable, x is the independent variable, a is the intercept, and b is the slope.
While the roots of linear regression trace back to the field of statistics, it didn't take long for traders and investors to recognize its potential in the financial world. By applying linear regression to historical price data, traders can identify trends, assess the relationship between variables, and even predict potential future price levels.
The Linear On MACD Strategy
Let's take a closer look at a powerful example of how linear regression is employed in a trading strategy right within TradingView. The "Linear On MACD" strategy harnesses the potential of linear regression in conjunction with the Moving Average Convergence Divergence (MACD) indicator. The goal of this strategy is to generate buy and sell signals based on the interactions between the predicted stock price and the MACD indicator.
Here's a breakdown of the strategy's components:
Calculation of Linear Regression: The strategy begins by calculating linear regression coefficients for the historical stock price based on volume. This helps predict potential future price levels.
Predicted Stock Price: The linear regression results are then used to plot the predicted stock price on the chart. This provides a visual representation of where the price could trend based on historical data.
Buy and Sell Signals: The strategy generates buy signals when certain conditions are met. These conditions include the predicted stock price being between the open and close prices, a rising MACD, and other factors that suggest a potential bullish trend. On the other hand, sell signals are generated based on MACD trends and predicted price levels.
Risk Management: The strategy also incorporates risk tolerance levels to determine entry and exit points. This ensures that traders take into account their risk appetite when making trading decisions.
Embracing the Magic of Linear Regression
As we explore the "Linear On MACD" strategy, we uncover the power of linear regression in aiding traders and investors. Linear regression, a mathematical marvel, seamlessly merges with technical analysis to provide insights into potential price movements. Its historical significance in statistics blends perfectly with the demands of modern financial markets.
Whether you're a seasoned trader or a curious investor, the Linear On MACD strategy exemplifies how a robust mathematical concept can be harnessed to make informed trading decisions. By embracing the magic of linear regression, you're tapping into a tool that continues to evolve alongside the financial world it empowers.
Disclaimer: The information provided in this blog post is for educational purposes only and does not constitute financial advice. Trading and investing carry risks, and it's important to conduct thorough research and consider seeking professional advice before making any trading decisions.
TrendGuard Flag Finder - Strategy [presentTrading]
Introduction and How It Is Different
In the vast world of trading strategies, the TrendGuard Flag Finder stands out as a unique blend of traditional flag pattern detection and the renowned SuperTrend indicator.
- A significant portion of the Flag Pattern detection is inspired by the "Flag Finder" code by @Amphibiantrading, which serves as one of foundational element of this strategy.
- While many strategies focus on either trend-following or pattern recognition, this strategy harmoniously combines both, offering traders a more holistic view of the market.
- The integration of the SuperTrend indicator not only provides a clear direction of the prevailing trend but also offers potential stop-loss levels, enhancing the strategy's risk management capabilities.
AAPL 1D chart
ETHBTC 6hr chart
Strategy: How It Works
The TrendGuard Flag Finder is primarily built on two pillars:
1. Flag Pattern Detection : At its core, the strategy identifies flag patterns, which are continuation patterns suggesting that the prevailing trend will resume after a brief consolidation. The strategy meticulously detects both bullish and bearish flags, ensuring traders can capitalize on opportunities in both rising and falling markets.
What is a Flag Pattern? A flag pattern consists of two main components:
1.1 The Pole : This is the initial strong price move, which can be either upwards (for bullish flags) or downwards (for bearish flags). The pole represents a strong surge in price in a particular direction, driven by significant buying or selling momentum.
1.2 The Flag : Following the pole, the price starts consolidating, moving against the initial trend. This consolidation forms a rectangular shape and is characterized by parallel trendlines. In a bullish flag, the consolidation will have a slight downward tilt, while in a bearish flag, it will have a slight upward tilt.
How the Strategy Detects Flags:
Identifying the Pole: The strategy first identifies a strong price movement over a user-defined number of bars. This movement should meet a certain percentage change to qualify as a pole.
Spotting the Flag: After the pole is identified, the strategy looks for a consolidation phase. The consolidation should be counter to the prevailing trend and should be contained within parallel lines. The depth (for bullish flags) or rally (for bearish flags) of this consolidation is calculated to ensure it meets user-defined criteria.
2. SuperTrend Integration : The SuperTrend indicator, known for its simplicity and effectiveness, is integrated into the strategy. It provides a dynamic line on the chart, signaling the prevailing trend. When prices are above the SuperTrend line, it's an indication of an uptrend, and vice versa. This not only confirms the flag pattern's direction but also offers a potential stop-loss level for trades.
When combined, these components allow traders to identify potential breakout (for bullish flags) or breakdown (for bearish flags) scenarios, backed by the momentum indicated by the SuperTrend.
Usage
To use the SuperTrend Enhanced Flag Finder:
- Inputs : Begin by setting the desired parameters. The strategy offers a range of user-controlled settings, allowing for customization based on individual trading preferences and risk tolerance.
- Visualization : Once the parameters are set, the strategy will identify and visually represent flag patterns on the chart. Bullish flags are represented in green, while bearish flags are in red.
- Trade Execution : When a breakout or breakdown is identified, the strategy provides entry signals. It also offers exit signals based on the SuperTrend, ensuring that traders can capitalize on the momentum while managing risk.
Default Settings
The strategy comes with a set of default settings optimized for general use:
- SuperTrend Parameters: Length set to 10 and Factor set to 5.0.
- Bull Flag Criteria: Max Flag Depth at 7, Max Flag Length at 10 bars, Min Flag Length at 3 bars, Prior Uptrend Minimum at 9%, and Flag Pole Length between 7 to 13 bars.
- Bear Flag Criteria: Similar settings adjusted for bearish patterns.
- Display Options: By default, both bullish and bearish flags are displayed, with breakout and breakdown points highlighted.
BRAHMA_ALARMThe indicator is an update to the "HMA-Kahlman Trend & Trendlines" script by capissimo, which is available at the following link: The update includes the integration of an alarm function to provide additional functionality.
The indicator continues to be based on the combination of the HMA (Hull Moving Average)-SMA (Simple Moving Average) method and the Kalman filter to generate precise trading signals. The original script by capissimo serves as the foundation for the SIMSOIL indicator, which has been enhanced by the addition of the alarm function to keep traders informed of potential trading opportunities.
It is important to emphasize that indicator is developed as an update to the original script by capissimo. I would like to thank capissimo for their original work on the script, and I have added the alarm function as an extension.
Donchian Channel Oscillator (DonOsc) Preface
DonOsc stands for Donchian Channel Oscillator. This channel envelopes all prices, so if you set the height of the channel to 100 percent, you can plot the prices as percent in between, creating this sub-pane oscillator. For clarity the example chart shows a Donchian channel in the main-pane with the same look-back as the DonOsc, this way you can see how both are related.
Price River
Not only the close is plotted, but also the high and the low of the bar. Thus you get a structure that can be associated with a river, streaming from left to right, in which the price moves between the left bank (i.e. the plotted highs) and the right bank (i.e. the plotted lows), which meanders between the high border (100%) and the low border (0%) of the oscillator. The surface of the price river is gray. The price line is blue when up and dark red when down. The river has also color patches dark red, light red, blue and aqua. Stochastic patches; up: aqua, down: light red
If you look at the price river, you may notice that the price line is closer to the left bank (highs) when moving up and to the right bank (lows) when moving down. Because this phenomenon is used in the stochastic indicator, I named these stochastic patches. These are depicted on the wide side for visibility, so the aqua patches are to the right of the price line and the light-red patches to the left.
Widening patches; up: blue, down: red
If you look at tops or bottoms in bar charts, you may notice that long bars (wide range) tend to be there. You may say that prices turn with a ‘range bang’. This causes a widening of the price river, depicted as a patch on the wide side.
Channel Features
High (76.4 %) and low (23.6 %) Fibonacci levels.
In the oscillator there is no need to calculate Fibonacci levels, we can just plot them. If the price is above 50% the low level is shown with a green color, when below the high level with a pink color. When the price river crosses a level a ‘near border’ highlighter will flash, lime near the high border and orange near the low one.
New high and new low markers.
A flaw in the oscillator is that is doesn’t show actual new lows and new highs in the Donchian Channel, because everything is made relative. This is ‘repaired’ by adding markers, dark red for new low depicted between the high fib and border, blue for new high depicted between low fib and border. Used are the same colors as in the widening patches, because new highs and lows also lead to widening of the actual Channel.
Uptrend and downtrend highlighters.
If in the actual Channel the bars run in the upper half, an uptrend is happening as long as these remain there, a downtrend when the bars remain in the lower half. In the oscillator a yellow highlighter flashes when the price is higher than 50%, a red highlighter below 50%.
Interpretation of the DonOsc
This sub-pane indicator provides a wealth of useful information about what is going on in the market. First of all you immediately see whether there is an up or down trend and whether these lead to new highs or lows. Second of all you can estimate the importance of price movements in the context of the look-back period. Thirdly the width of the price river reveals the emotions in the market. The higher the emotions run, the more risk is involved in a postilion in the charted instrument.
Settings of the DonOsc
Look-back settings.
By default the script sets the look-back, depending on the time frame. This overrules the standard manual setting. If you switch this off, the manual setting will work. A feed-back label can by shown which informs about the current setting.
Smoothing
This concerns the price river. Default is 2, if you increase this setting, the river will loose its touch with the channel borders. O.t.o.h. the river wil be wider and better visible. Maximum setting is 5.
Colors
The momentum colors set both the river widening patches and new high and low markers.
Take care, Eykpunter.
Market Meanness Index [CC]The Market Meanness Index was created by Johann Christian Lotter and I added some smoothing of my own, so feel free to try it without any smoothing to see the differences. This indicator relies on the mean reversion theory that all prices will eventually revert to the mean over a long period of time. Obviously there is more to the theory but the basic idea is if you plot a sma or other typical moving average, you will see the price moving up or below the long term moving average such as a 200 day sma but usually heads back to the average in the short term. This is a good statistical analysis used for volatility which is where this indicator comes in. Simply put, we calculate volatility based on how often a price is both above the median and above the previous price or vice versa.
A rising Market Meanness Index means that the market is becoming more volatile and that there is a high likelihood of a change in the underlying trend. A falling Market Meanness Index means that the current trend is dying and there is a high likelihood of a trend reversal. Typically I put general buy and sell signals in red or green but in this particular case, this indicator works best as a overall trend filter and you would want to place a trade when this indicator has a peak or valley. Let me know if you find a good overall buy and sell signal system of course.
I know I keep saying that I will get active again and post more indicators but life is very hectic for me. For those who have been following my updates, my twins were finally born a little over a month ago and as you can imagine, they keep me up at all hours of the day so it is hard to create new indicator scripts when I'm getting no sleep lol. I will do my best to start publishing the giant backlog of scripts I have created but in the meantime, please be patient with me. This indicator was a special request so let me know if you have any special requests of your own!
Bitcoin Best Value CorridorHere is my interpretation of the "Best Time To Buy" Bitcoin over its lifetime using a logarithmic regression trendline. The upper and lower lines are 10% deviations from the centre line. I calculated the trendline in excel and then coded my results into pine script.
Overbought & Oversold TrackerAbout this indicator:
- This indicator is basically a stochastic indicator that shows to you the crossover in an Overbought or Oversold area DIRECTLY on the chart
How does it works:
- When Stochastic crosses at Oversold area, a Blue Triangle will appear below the candle with a Blue Dotted Line at the low of the current candle
- The Blue Triangle is to help you to see easily the candle where the crossover is occurring
- At the same time, the Blue Dotted Line will act as a minor Support for the current price
- If the current candle breaks the Blue Dotted Line (minor Support), the candle will be displayed in a red color
- Same things will occur if Stochastic crosses at the Overbought area, but at this time, a Red Triangle with Red Dotted Line will appear just to differentiate between Overbought and Oversold crossover
The advantage of using this indicator:
- You can easily see the point of stochastic crossover DIRECTLY on the chart without analyzing the stochastic indicator
- At the same time, it helps you to see clearly either the price is at the bottom / reversal by combining it with S&R / trendlines or other indicators
Personally, I will combine this indicator with:
a. Support and Resistance or Trendlines
b. Fibonacci retracement
c. Candlestick indicator (see my script list)
d. Ultimate MACD (see my script list)
e. Volume indicator
These combinations personally increase the possibility for me to buy exactly at the point of reversal in a pullback
- This indicator is preset at the value of 25 (oversold) and 75 (overbought) k line, it's my own preference. You can change these values at the setting menu to suit your trading style.
- Once again, I am opening the script for anyone to modify/alter it based on you own preference. Have a good day!
