Order Block Detection By Zia (StockWiz)What is an Order Block?
An order block is a concept used in technical analysis, particularly in price action trading and supply and demand analysis. It refers to a significant area on a price chart where institutional traders, such as banks and hedge funds, have placed large orders. These blocks of orders often create strong support or resistance levels, as they represent areas where the "smart money" has shown interest in buying or selling an asset.
Characteristics of Order Blocks:
1. High Volume: Order blocks are typically associated with high trading volume, indicating strong participation from large players in the market.
2. Price Rejection: They often lead to sharp reversals or consolidations in price, as the large orders absorb the market's liquidity and push the price in the opposite direction.
3. Formation: Order blocks are usually formed after significant price movements, such as strong bullish or bearish trends, and can be identified by clusters of candles with long wicks or significant body sizes.
4. Support and Resistance: Once identified, order blocks can serve as potential support or resistance levels in future price movements. Prices often return to these areas, where new orders can be executed.
Identifying Order Blocks:
To identify order blocks, traders look for specific patterns and price actions on the chart. Here is a step-by-step guide to finding order blocks:
1. Identify a Strong Move: Look for strong bullish or bearish moves, which are often the result of large institutional orders.
2. Find Consolidation : After the strong move, find areas where the price consolidates. This is where large orders were likely placed.
3. Look for Rejections: Identify areas where the price has been rejected multiple times, creating a clear support or resistance zone.
4. Mark the Order Block: Draw a rectangle around the consolidation area to mark the order block on your chart.
Student of Parag Mehta (StockWiz)
With Regards
Zia Rahim
스크립트에서 "demand"에 대해 찾기
Weighted Moving Range with Trend Signals (WMR-TS)Weighted Moving Range with Trend Signals (WMR-TS)
Technical analysis involves analyzing statistical trends from trading activity , such as price movement and volume, to make trading decisions. Technical indicators are mathematical calculations based on the price, volume, or open interest of a security or contract. They are used by traders to analyze price movements and predict future market behavior. The WMR-TS indicator combines weighted moving averages and range calculations to identify key trading levels and generate buy/sell signals. It dynamically adjusts to market conditions, offering traders insights into potential support, resistance, and trend reversal points. Key levels are color-coded for quick interpretation. It utilizes weighted moving averages (WMA) and range calculations to determine these levels, making it a robust tool for both trending and ranging markets.
SUMMARY
Parameters :
WMA Length : Determines the length for the primary weighted moving average.
Highest High Length : Sets the period for calculating the highest high.
Lowest Low Length : Sets the period for calculating the lowest low.
Range Corrector : Adjusts the range calculation slightly for fine-tuning.
Top Level : Multiplier for determining the top level from the calculated range.
Bottom Level : Multiplier for determining the bottom level from the calculated range.
Levels Visibility : Sets how many recent bars will display the levels.
Trading Zones :
Short Area : Highlighted zone indicating potential shorting opportunities.
Long Area : Highlighted zone indicating potential buying opportunities.
The Levels :
Wave (Yellow): Midpoint of the calculated range, adjusted by WMA.
Top Level (Red): Calculated upper boundary of the trading range.
Sell Level (Pink): Intermediate sell level.
Resistance Level (Magenta): Immediate resistance level.
Support Level (Cyan): Immediate support level.
Buy Level (Light Green): Intermediate buy level.
Bottom Level (Dark Green): Calculated lower boundary of the trading range.
Interpreting the Signals :
Hammer Signal : Red circles above bars indicate potential sell signals.
Rocket Signal : Green circles below bars indicate potential buy signals.
KEY CONCEPTS
Highest High and Lowest Low :
These values represent the highest high ( HH ) and lowest low ( LL ) over a specified number of periods.
Support Level :
This is the lower boundary of the trading range. It is a price level where demand is strong enough to prevent the price from falling further. As the price approaches the support level, it is likely to bounce back up.
Resistance Level :
This is the upper boundary of the trading range. It is a price level where supply is strong enough to prevent the price from rising further. As the price approaches the resistance level, it is likely to pull back down.
THE USE OF MULTIPLIERS :
The script uses several multipliers to adjust and fine-tune the calculated support and resistance levels, as well as to control the range and sensitivity of these levels. Here is a detailed explanation of these multipliers and their purpose:
Range Corrector : This multiplier adjusts the calculated high ( H ) and low ( L ) levels, adding flexibility to how these levels are positioned relative to the highest high and lowest low. It ranges from -1 to 1 , with a default value of 0 . The use of positive values increase the range, making the calculated levels further apart. Thus, using negative values decrease the range, bringing the calculated levels closer together.
Top Level : This multiplier adjusts the distance of the top level from the calculated high H ) level. It fluctuates from 0 to 2 , with a default value of 0.382 . Higher values will push the top level further above the high level, while lower values will bring it closer.
Bottom Level : This multiplier adjusts the distance of the bottom support level from the calculated low support level. Ranging from 0 to 2, with a default value of 0.214, the higher values will push the bottom level further below the low level, while lower values will bring it closer.
The script plots the support and resistance levels on the chart, allowing traders to visualize the trading range. Color-coded zones are used to indicate areas where buying or selling opportunities may arise based on the current price relative to the trading range. A trading range refers to the area between a price's support and resistance levels over a specific period of time. Within this range, the price of the security fluctuates up and down but does not break out above the resistance or below the support. Support and resistance levels to make trading decisions. Buying near the support level and selling near the resistance level is a common strategy. When the price moves above the resistance level, it is called a breakout . A breakout often indicates that the price may start a new upward trend . Conversely, when the price moves below the support level, it is called a breakdown . A breakdown often indicates that the price may start a new downward trend . By understanding and utilizing trading ranges, traders can make more informed decisions, optimize their trading strategies, and manage risk more effectively.
Understanding Moving Averages
A moving average (MA) is a widely used technical indicator that helps smooth out price data by creating a constantly updated average price. The main purpose of using a moving average is to identify the direction of the trend and to reduce the "noise" of random price fluctuations. The Weighted Moving Average ( WMA ) assigns different weights to each period, with more recent periods typically given more weight. A 10-day WMA might give the most recent day a weight of 10, the second most recent day a weight of 9, and so on. It is useful for traders who want to emphasize recent price data more than older data. When the price is above the moving average, it suggests an Bullish trend . A Bearish Trend is expected to take place when the price is below the moving average. Understanding the price reactions around these levels can be used to make trading decisions.
APPLYING CONCEPTS
Support and Resistance Calculations in the Script :
The script calculates dynamic support and resistance levels using weighted moving averages ( WMA s) and the highest high and lowest low over specified periods. Buy ( Rocket ) and sell ( Hammer ) signals are generated based on the crossing of the price with calculated top and bottom levels.These signals help traders identify potential entry and exit points within the trading range .
Weighted Moving Average (WMA) Application in the Script
This script calculates a special trendWMA using the close price that helps in creating a more dynamic moving average that considers both high and low price actions. This modified WMA is used in conjunction with highest high and lowest low values over specified periods to calculate dynamic support and resistance levels.
Explanation of the Levels in the Script
By understanding these levels, traders can make more informed decisions about where to enter and exit trades, manage risk, and anticipate potential market movements. The script incorporates several key levels levels that traders can use to better anticipate price movements and make more informed trading decisions. Leveraging the principles of Fibonacci retracement ratios ( 23.6%, 38.2%, 50%, 61.8%, and 100% ) to identify key support and resistance zones can also serve for gauging the overall market sentiment.
Top Level and Sell Leve l: Used to identify potential resistance zones where the price may reverse or pause.
Support Level and Buy Level : Used to identify potential support zones where the price may bounce.
Upper and Lower Pivot Values : Serve as intermediate levels for possible price retracements or extensions within the trading range.
Wave Level : Indicates the central trend direction, which can be useful for gauging the overall market sentiment.
Alerts are a crucial part of the script as they notify traders of potential buy and sell signals based on predefined conditions. There are two main alerts: one for a " Hammer " signal (sell condition) and one for a " Rocket " signal (buy condition).
Adjust the input parameters to fit your trading style and the specific asset being analyzed. Shorter lengths may be more responsive to price changes but can produce more false signals , while longer lengths provide smoother signals but may lag . Always backtest the indicator on historical data to understand its behavior and performance. Also remember that different markets may require different parameter settings for optimal performance.
Keep in mind that by nature like all moving averages, WMAs lag behind price action. This means that signals may be delayed. The indicator performs differently in various market conditions. Always consider the overall market context when interpreting signals.
Adjusting parameters like the range corrector and visibility can help tailor the indicator to specific market conditions or trading strategies, improving its effectiveness. The script uses the calculated levels to plot lines and fill zones on the chart, helping traders visualize potential support, resistance, and trend reversal points. The use of multipliers allows for dynamic adjustment of these levels, making the indicator flexible and adaptable to different market conditions.
I think traders can make more informed decisions about where to enter and exit trades, manage risk, and anticipate potential market movements following this code. Stay safe and always remember that market is always changing. Use this tool if you want, please stay informed and plan safe trades,
D.
ICT Setup 01 [TradingFinder] FVG + Liquidity Sweeps/Hunt Alerts🔵 Introduction
The ICT (Inner Circle Trader) style of trading involves analyzing the behavior of market participants and market makers to identify areas where fake buy and sell activities occur. This trading style helps retail traders align with market maker behavior and avoid falling into market traps.
A key aspect of the ICT strategy is focusing on liquidity hunts. This involves searching for trading opportunities in areas of the market with low liquidity or where other traders have little activity. The ICT method leverages market inefficiencies and weaknesses, allowing traders to profit from small price movements that might go unnoticed by others.
In "ICT Setup 01," our focus is on these liquidity areas and stop hunts that form in Fair Value Gaps (FVGs). Trading within FVGs, combined with confirmations from "Hunts" and "Sweeps," can enhance trader performance.
🔵 How to Use
The presence of Fair Value Gaps (FVGs) in the market indicates rapid, powerful movements likely caused by the influx of smart money. When the price returns to these levels, a market reaction is expected.
Combining this with the complex and deceptive behavior of smart money—such as "Liquidity Sweeps" and "Stop Hunts"—forms an ICT-based price action setup that we expect to perform well.
Components of "ICT Setup 01" :
● Fair Value Gap (FVG)
● Premium and Discount
● Hunts / Sweeps
Whenever the price returns to an FVG area and reacts in such a way that only the wicks of the candles remain in the area and the candle bodies are outside the FVG, the first condition for creating the setup is met.
If subsequent candles hunt the wick that has penetrated the deepest into the FVG, a buy or sell signal is issued. In the format where hunting is based on Sweeps, penetrations that extend even outside the area are considered signals, provided they do not form a body within the area.
Additionally, a refining system exists for cases where a candle body forms in the area, optimizing the proximal levels of the FVG.
Bullish Setup :
Bearish Setup :
🔵 Features and Settings of "ICT Setup 01"
You can Find out more in Setting :
● FVG Detector Multiplier Factor
● FVG Validity Period
● Level in Low-Risk Zone
● Issuing Signals Method
● Number of Signals Allowed from a Zone
● Signal after Hunts/Sweeps
● How Many Hunts/Sweeps
● Show or Hide
● Alert Sender
FVG Detector Multiplier Factor :
This feature allows you to determine the size of the moves forming the FVGs based on the ATR (Average True Range). The default value is 1 to identify the majority of setups. You can increase this value according to the symbol and market you are trading in to achieve better results.
FVG Validity Period :
This shows the validity period of an FVG based on the number of candles. By default, an FVG area is valid for up to 15 candles. However, you can increase or decrease this period.
Level in Low-Risk Zone :
This feature helps reduce your risk. The method works by identifying the entire length of the three candles forming the FVG and dividing it into two equal areas. The upper area is "Premium," and the lower area is "Discount." To reduce risk, it is better for "Demand FVG" to be in the "Discount" and "Supply FVG" in the "Premium." This feature is off by default.
Issuing Signals Method :
This feature allows you to specify whether the hunt should occur only within the FVG area or if the wicks can extend outside the area.
If set to "Hunts," only signals where the wicks are within the area are issued, and the area loses its validity if the wicks extend outside.
In "Sweeps" mode, wicks can extend outside the area as long as they do not form a body within the area.
Number of Signals Allowed from a Zone :
This feature allows you to specify how many valid signals can be issued from one area.
Signal after Hunts/Sweeps :
In markets or symbols with a tendency for frequent stop hunts, this feature allows you to specify how many hunts should occur before you receive a signal to avoid receiving potentially failed signals.
How Many Hunts/Sweeps :
Enter the number of hunts you want to set for the "Signal after Hunts/Sweeps" feature here.
Show or Hide :
The number of setups formed may be very large, and displaying all of them on the chart can be distracting and messy. By default, only the last setup is displayed, but if you want to see all setups, you can turn on the relevant options.
Alert Sender :
You cannot constantly monitor multiple charts to identify trading opportunities. Using the alert sending feature can save time and improve performance.
Alerts Name : Customize the alert name to your preference.
Message Frequency : Determines the frequency of alert messages. Options include 'All' (triggers every time the function is called), 'Once Per Bar' (triggers only on the first call within the bar), and 'Once Per Bar Close' (triggers only on the final script execution of the real-time bar upon closure). The default is 'Once per Bar.'
Show Alert Time by Time Zone : Configure the alert messages to reflect any chosen time zone. For instance, input 'UTC+1' for London time. The default is 'UTC.'
By configuring these settings, traders can effectively utilize ICT setups to improve their trading strategies and outcomes.
Turbo Oscillator [RunRox]Introducing Turbo Oscillator by RunRox, our new indicator that combines a multitude of useful and unique features, which we will detail in this post.
List of Advanced Technologies:
Real-Time Divergences: Detects discrepancies between price movements and oscillator indicators to forecast potential price reversals.
Real-Time Hidden Divergences: We identify hidden divergences in real-time. These are not the standard type of divergences; they are opposite to regular divergences, providing unique insights into potential market movements.
Overbought and Oversold Zones: Identifies areas where the market is potentially overextended, suggesting possible entry and exit points.
Signal Line: Indicates the market direction, helping traders to quickly understand current trends.
Money Flow Histogram: Shows the flow of money into and out of the market, providing insights into buying and selling pressure.
Predicted Reversal Zones: Pinpoints areas where the market might experience reversals, aiding in strategic planning and risk management. These zones also serve as potential areas for taking profits, enhancing their utility for exit strategy planning.
Customizable Alerts: You can flexibly set up alerts for any events detected by our indicator, ensuring you stay informed about critical market movements.
To begin with, I would like to describe the difference between classic divergences and hidden divergences.
As you can see, these are opposite situations. Our oscillator identifies both types of divergences and displays them in real-time.
Divergences can serve as points where the price might reverse in the opposite direction, making both classic and hidden divergences powerful tools for spotting reversal points. I'll show a few examples of how divergences are used in our oscillator.
Classic Divergences - which we identify in real-time. As you can see, the price often reacts strongly to the formation of these divergences, frequently changing its direction.
Hidden Divergences - we also observe frequent movement in the opposite direction on the chart. The advantage of our indicator is that we show divergences in real-time without delays, allowing you to react immediately to trend changes.
Overbought and Oversold Zones - These zones allow you to see trend changes when the price is clearly overbought or oversold. When the color changes from a contrasting shade to a neutral one, you can observe the trend shift. The lines work by combining the positivity/negativity of the histogram, the positivity/negativity of the signal line, and the direction of the signal line (red/green). This sophisticated interaction provides precise insights into market conditions, making it an invaluable tool for traders.
Signal Line - This provides insights into trend changes and price reversals. The points on the line better indicate the beginning of a trend shift. These points can vary in size, offering a clearer understanding of the strength of the emerging trend. This feature works in combination with RSI, Stochastic, and MFI. RSI and MFI are top-tier indicators, while Stochastic adds responsiveness and sensitivity to trend changes, ensuring you capture every market movement accurately and promptly.
Money Flow Histogram - As shown in the example, our histogram displays the divergence between money flow and the actual price. You can see that while the price is rising, the money flow is decreasing, indicating insufficient demand for the asset and an imminent trend change. This feature uses MFI with an extended period, providing a more comprehensive and accurate analysis of market conditions. The extended period enhances the reliability of the Money Flow Index, making it an essential tool for identifying subtle shifts in market dynamics.
Predicted Reversal Zones - We automatically identify potential price reversal zones and display them above our overbought and oversold zones. In cases of strong overbought or oversold conditions, we detect potential price pullbacks and mark the beginning of a trend change. This helps you better identify trend shifts. We recommend considering these zones as potential take profit points for your trades.
Customizable Alerts - Our flexible alert system allows you to receive notifications only for the events you are interested in. These can include:
1. Classic Divergences
2. Hidden Divergences
3. Overbought or Oversold conditions on the status line
4. Strong Overbought or Oversold conditions on the status line
5. Signals from the signal line
6. Reversal zones in any direction
Our oscillator is a unique indicator that provides a comprehensive understanding of price movements. It can be used as a standalone tool for analyzing price action.
Here are a few examples of using our Oscillator in practice:
In the example above, you can see three conditions that have formed for a potential trade:
1. Clear overbought condition with a formed reversal point.
2. Decreasing Money Flow Index diverging from the rising price.
3. Formed classic divergence.
The entry point could be the formed divergence, while the exit point could be the overbought condition at the bottom of the oscillator along with the reversal points.
Here's another example of using hidden divergence, where you can see three conditions for a potential trade:
1. Overbought zone
2. Formed hidden divergence
3. Start of bearish movement indicated by the signal line
You can enter the trade either when the hidden divergence forms or wait for confirmation of the trend change by the signal line and enter the trade when the corresponding signal forms on the signal line. The exit point could be the opposite reversal point or the formation of a new hidden divergence.
We have demonstrated a few examples of how you can use our indicator, but we are confident that you will find many more applications in your own strategies.
Oscillator offers a variety of customizable parameters to tailor the indicator to your trading preferences. Here’s what our settings include:
Signal Line
Turn On/Off: Enable or disable the signal line.
Length: Set the length period for the signal line calculation.
Smooth: Adjust the smoothing level of the signal line for more accurate display.
Histogram
Turn On/Off: Enable or disable the histogram.
Length: Set the length period for the histogram calculation.
Smooth: Adjust the smoothing level of the histogram.
Other
Show Divergence Line: Display divergence lines on the chart.
Show Hidden Divergence: Display hidden divergences.
Show Status Line: Show the status line indicating overbought or oversold conditions.
Show TP Signal: Display signals for take profit.
Show Reversal Points: Display potential trend reversal points.
Delete Broken Divergence Lines: Remove broken divergence lines from the chart.
Alerts Customization
Signal Line Bull/Bear: Set alerts for bullish or bearish signals from the signal line.
TP Bull/Bear: Set alerts for take profit signals.
Status Bull/Bear: Set alerts for bullish or bearish status conditions.
Status Bull+/Bear+: Set enhanced alerts for stronger bullish or bearish status conditions.
Divergence Bull/Bear: Set alerts for bullish or bearish divergences.
Hidden Divergence Bull/Bear: Set alerts for hidden bullish or bearish divergences.
With these comprehensive settings, you can fine-tune the Oscillator to perfectly fit your trading strategy and preferences.
Our indicator utilizes technologies such as RSI, Stochastic, and Money Flow Index, with numerous enhancements from our team. It includes exclusive features such as real-time detection of hidden and classic divergences, identification of reversal points using our unique methodology, and much more.
Disclaimer:
While we consider our Turbo Oscillator to be an excellent tool, it is important to understand that past performance is not indicative of future results. We recommend approaching market analysis comprehensively, using a combination of tools and techniques to make well-informed trading decisions. Always consider the full range of market data and risks when using any trading indicator.
KillZones Hunt + Sessions [TradingFinder] Alert & Volume Ranges🟣 Introduction
🔵 Session
Financial markets are divided into various time segments, each with its own characteristics and activity levels. These segments are called sessions, and they are active at different times of the day.
The most important active sessions in financial markets are :
1. Asian Session
2. European Session
3. New York Session
The timing of these major sessions based on the UTC time zone is as follows :
1. Asian Session: 23:00 to 06:00
2. European Session: 07:00 to 16:30
3. New York Session: 13:00 to 22:00
Note
To avoid overlap between sessions and interference in kill zones, we have adjusted the session timings as follows :
• Asian Session: 23:00 to 06:00
• European Session: 07:00 to 14:25
• New York Session: 14:30 to 22:55
🔵 Kill Zones
Kill zones are parts of a session where trader activity is higher than usual. During these periods, trading volume increases and price fluctuations are more intense.
The timing of the major kill zones based on the UTC time zone is as follows :
• Asian Kill Zone: 23:00 to 03:55
• European Kill Zone: 07:00 to 09:55
• New York Morning Kill Zone: 14:30 to 16:55
• New York Evening Kill Zone: 19:30 to 20:55
This indicator focuses on tracking the kill zone and its range. For example, once a kill zone ends, the high and low formed during it remain unchanged.
If the price reaches the high or low of the kill zone while the session is still active, the corresponding line is not drawn any further. Based on this information, various strategies can be developed, and the most important ones are discussed below.
🟣 How to Use
There are three main ways to trade based on the kill zone :
• Kill Zone Hunt
• Breakout and Pullback to Kill Zone
• Trading in the Trend of the Kill Zone
🔵 Kill Zone Hunt
According to this strategy, once the kill zone ends and its high and low lines no longer change, if the price reaches one of these lines within the same session and is strongly rejected, a trade can be entered.
🔵 Breakout and Pullback to Kill Zone
According to this strategy, once the kill zone ends and its high and low lines no longer change, if the price breaks one of these lines strongly within the same session, a trade can be entered on the pullback to that level.
Trading in the Trend of the Kill Zone
We know that kill zones are areas where high-volume trading occurs and powerful trends form. Therefore, trades can be made in the direction of the trend. For example, when an upward trend dominates this area, you can enter a buy trade when the price reaches a demand order block.
🟣 Features
🔵 Alerts
You can set alerts to be notified when the price hits the high or low lines of the kill zone.
🔵 More Information
By enabling this feature, you can view information such as the time and trading volume within the kill zone. This allows you to compare the trading volume with the same period on the previous day or other kill zones.
🟣 Settings
Through the settings, you have access to the following options :
• Show or hide additional information
• Enable or disable alerts
• Show or hide sessions
• Show or hide kill zones
• Set preferred colors for displaying sessions
• Customize the time range of sessions
• Customize the time range of kill zones
ZigZag Smart Trend [TradingFinder] Major & Minor Structured Wave🔵 Introduction
🟣 Zigzag
Zigzag is a lagging indicator; this indicator identifies points on a price chart that have more significant changes than its previous wave and then by connecting these lines to each other, it assists traders in trend detection.
This indicator reduces random price fluctuations and attempts to make the primary price trend clearer.
🟣 Pivot
Pivots are points where the price chart changes direction. Pivots, also called reversal points, form when supply and demand forces dominate one another.
Different types of technical analysis pivots can be introduced into two categories, minor pivots, and major pivots, each of which has a specific meaning in analysis.
Major Pivot : These pivots actually indicate major changes in the direction of the chart and occur at the end of trends. Analysts seeking to reach the primary analysis focus more on major pivot points. In fact, most technical analysis tools are examined and determined based on major pivots.
Minor Pivot : This type of pivot focuses more on small and subsidiary points and directions. Therefore, it occurs at the end of corrections. Analysts focusing on minor pivots represent small trends, and it should be noted that minor pivots are not suitable for use in primary technical tools.
How to identify minor and major pivots :
Minor pivots are pivots formed between two major pivots and fail to break the opposite major pivot.
Major pivots are pivots that have either successfully broken the opposite pivot or have moved more than the previous pivot of the same type.
🔵 How to use
Based on identifying pivots and drawing zigzag lines, you can have various uses for this indicator.
Identifying support and resistance levels :
Identifying Elliott Waves :
Identifying classic patterns :
Identifying pivots with higher validity :
Identifying internal and external breakouts :
Identifying trends and range areas :
Identifying pivot types along with major and minor recognition :
MHH : Major Higher High
MLH : Major Lower High
MLL : Major Lower Low
MHL : Major Higher Low
mHH : Minor Higher High
mLH : Minor Lower High
mLL : Minor Lower Low
mHL : Minor Higher Low
🔵 Settings
Pivot Period Zigzag Line : Using this input, you can determine the pivot period for identifying zigzag swings.
Show Zigzag Line : To show or not to show the zigzag line.
Zigzag Line Color : Change the color of the zigzag line.
Zigzag Line Style : Change the Style of the zigzag line.
Zigzag Line Width : Change the Width of the zigzag line.
Show Label : To show or not to show Pivot Type.
Color Label : Change the color of the Pivot Type Label.
Net Buying/Selling Flows Toolkit [AlgoAlpha]🌟📊 Introducing the Net Buying/Selling Flows Toolkit by AlgoAlpha 📈🚀
🔍 Explore the intricate dynamics of market movements with the Net Buying/Selling Flows Toolkit designed for precision and effectiveness in visualizing money inflows and outflows and their impact on asset prices.
🔀 Multiple Display Modes : Choose from "Flow Comparison", "Net Flow", or "Sum of Flows" to view the data in the most relevant way for your analysis.
📏 Adjustable Unit Display : Easily manage the magnitude of the values displayed with options like "1 Billion", "1 Million", "1 Thousand", or "None".
🔧 Lookback Period Customization : Tailor the sum calculation window with a configurable lookback period, applicable in "Sum of Flows" mode.
📊 Deviation Thresholds : Set up lower and upper deviation thresholds to identify significant changes in flow data.
🔄 Reversal Signals and Deviation Bands : Enable signals for potential reversals and visualize deviation bands for comparative analysis.
🎨 Color-coded Visualization : Distinct colors for upward and downward movements make it easy to distinguish between buying and selling pressures.
🚀 Quick Guide to Using the Net Buying/Selling Flows Toolkit :
🔍 Add the Indicator : Add the indicator to you favorites. Customize the settings to fit your trading requirements.
👁️🗨️ Data Analysis : Compare the trend of Buying and Selling to help indicate whether bulls or bears are in control of the market. Utilize the different display modes to present the data in different form to suite your analysis style.
🔔 Set Alerts : Activate alerts for reversal conditions to keep abreast of significant market movements without having to monitor the charts constantly.
🌐 How It Works :
The toolkit processes volume data on a lower timeframe to distinguish between buying and selling pressures based on intra-bar price closing higher or lower than it opened. It aggregates these transactions and finds the net selling and buying that took place during that bar, offering a clearer view of market fundamentals. The indicator then plots this data visually with multiple modes including comparisons between buying/selling and the net flow of the asset. Deviation thresholds help in identifying significant changes, allowing traders to spot potential buying or selling opportunities based on the money flow dynamics. The "Sum of Flows" mode is unique from other trend following indicators as it does not determine trend based on price action, but rather based on the net buying/selling. Therefore in some cases the "Sum of Flows" mode can be a leading indicator showing bullish/bearish net flows even before the prices move significantly.
Embark on a more informed trading journey with this dynamic and insightful tool, tailor-made for those who demand precision and clarity in their trading strategies. 🌟📉📈
Normalised T3 Oscillator [BackQuant]Normalised T3 Oscillator
The Normalised T3 Oscillator is an technical indicator designed to provide traders with a refined measure of market momentum by normalizing the T3 Moving Average. This tool was developed to enhance trading decisions by smoothing price data and reducing market noise, allowing for clearer trend recognition and potential signal generation. Below is a detailed breakdown of the Normalised T3 Oscillator, its methodology, and its application in trading scenarios.
1. Conceptual Foundation and Definition of T3
The T3 Moving Average, originally proposed by Tim Tillson, is renowned for its smoothness and responsiveness, achieved through a combination of multiple Exponential Moving Averages and a volume factor. The Normalised T3 Oscillator extends this concept by normalizing these values to oscillate around a central zero line, which aids in highlighting overbought and oversold conditions.
2. Normalization Process
Normalization in this context refers to the adjustment of the T3 values to ensure that the oscillator provides a standard range of output. This is accomplished by calculating the lowest and highest values of the T3 over a user-defined period and scaling the output between -0.5 to +0.5. This process not only aids in standardizing the indicator across different securities and time frames but also enhances comparative analysis.
3. Integration of the Oscillator and Moving Average
A unique feature of the Normalised T3 Oscillator is the inclusion of a secondary smoothing mechanism via a moving average of the oscillator itself, selectable from various types such as SMA, EMA, and more. This moving average acts as a signal line, providing potential buy or sell triggers when the oscillator crosses this line, thus offering dual layers of analysis—momentum and trend confirmation.
4. Visualization and User Interaction
The indicator is designed with user interaction in mind, featuring customizable parameters such as the length of the T3, normalization period, and type of moving average used for signals. Additionally, the oscillator is plotted with a color-coded scheme that visually represents different strength levels of the market conditions, enhancing readability and quick decision-making.
5. Practical Applications and Strategy Integration
Traders can leverage the Normalised T3 Oscillator in various trading strategies, including trend following, counter-trend plays, and as a component of a broader trading system. It is particularly useful in identifying turning points in the market or confirming ongoing trends. The clear visualization and customizable nature of the oscillator facilitate its adaptation to different trading styles and market environments.
6. Advanced Features and Customization
Further enhancing its utility, the indicator includes options such as painting candles according to the trend, showing static levels for quick reference, and alerts for crossover and crossunder events, which can be integrated into automated trading systems. These features allow for a high degree of personalization, enabling traders to mold the tool according to their specific trading preferences and risk management requirements.
7. Theoretical Justification and Empirical Usage
The use of the T3 smoothing mechanism combined with normalization is theoretically sound, aiming to reduce lag and false signals often associated with traditional moving averages. The practical effectiveness of the Normalised T3 Oscillator should be validated through rigorous backtesting and adjustment of parameters to match historical market conditions and volatility.
8. Conclusion and Utility in Market Analysis
Overall, the Normalised T3 Oscillator by BackQuant stands as a sophisticated tool for market analysis, providing traders with a dynamic and adaptable approach to gauging market momentum. Its development is rooted in the understanding of technical nuances and the demand for a more stable, responsive, and customizable trading indicator.
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
price action reversion bands - [SigmaStreet]█ OVERVIEW
The "Price Action Reversion Bands" is designed to help traders identify potential reversal zones through the integration of polynomial regression, fractal analysis, and pinbar detection. This tool overlays directly onto the price chart, providing dynamic visual cues and signals for market reversals. Its unique synthesis of these methodologies offers traders a powerful, multifaceted approach to market analysis.
█ CONCEPTS
Polynomial Regression Bands:
What It Does:
Models the main trend using a polynomial equation to create a middle trend line with dynamic support and resistance bands.
How It Works:
Calculates polynomial coefficients to plot a regression line and adjusts the bands according to market volatility and conditions.
Fibonacci Retracement Levels:
What It Does:
Provides additional lines inside the regression bands at key Fibonacci ratios to identify potential support and resistance areas.
How It Works:
Calculates retracement levels by identifying high and low points over the same period used to calculate the regression bands, applying Fibonacci ratios to these points.
Fractal Analysis:
What It Does: Identifies natural resistance and support levels, indicating potential reversal zones.
How It Works: Detects fractals based on a specific pattern of price action, using Williams Fractal methodology.
Pinbar Detection:
What It Does: Signals potential price reversals through pinbar candlestick patterns.
How It Works: Analyzes
candlesticks to identify pinbars which show a rejection of prices, suggesting possible reversals.
█ ORIGINALITY AND USEFULNESS
The price action reversion bands distinguishes itself through its innovative integration of several advanced analytical methods, providing traders with a holistic view of potential market reversals:
Unique Combination:
While many tools use these techniques in isolation, this indicator synergistically combines polynomial regression, Fibonacci retracement levels, fractal analysis, and pinbar detection. This multi-faceted approach allows traders to assess strength, potential reversal zones, and price rejection more effectively than using traditional single-method indicators.
Advanced Polynomial Regression Application:
Unlike standard regression tools that offer static insights, this indicator dynamically adjusts its regression bands based on real-time market volatility, providing a more accurate reflection of market conditions.
Enhanced Signal Reliability:
By using fractals and pinbars in conjunction to validate each other, the indicator significantly increases the reliability of its reversal signals. This dual-validation method filters out less probable signals, focusing on high-probability trading opportunities.
Customization and Flexibility:
It offers unprecedented customization options, allowing traders to fine-tune the tool according to their trading style and market conditions. Traders can adjust the polynomial degree, the sensitivity of the Fibonacci retracements, and even the definition of what constitutes a significant pinbar, making it highly adaptable to various trading scenarios.
Educational Value:
The indicator not only aids in trading but also serves as an educational tool that helps traders understand the interaction between different types of market analysis techniques. This contributes to a deeper knowledge base and better trading decisions over time.
These distinctive features make the "Price Action Reversion Bands - " not just another indicator but a comprehensive trading tool that enhances decision-making through a well-rounded analysis of market dynamics.
█ HOW TO USE
Installation and Setup:
Apply the indicator to your TradingView chart from the "Indicators" menu.
Select either polynomial regression or Fibonacci retracement as the basis for the bands through the indicator settings.
Reading the Indicator:
Monitor the approach of price to the upper and lower bands which indicate potential reversal zones.
Look for fractal and pinbar formations near these bands for additional signal confirmation.
Customization:
Adjust settings such as the polynomial degree, data window length, and engagement zones to tailor the bands to your trading style.
Modify visual aspects like color and line type for better clarity and personal preference.
█ FEATURES
Dynamic Adjustment:
Bands adjust in real-time based on incoming price data and selected settings.
Multiple Analysis Techniques: Combines several analytical techniques to provide a comprehensive view of potential market movements. The integration of polynomial regression with Fibonacci levels, supplemented by fractal and pinbar analysis, marks this tool as particularly innovative, offering a level of synthesis that enhances predictive accuracy and usability.
User-Friendly Customization: Allows for extensive customization to suit individual trading strategies and preferences.
█ LIMITATIONS
Market Dependency:
Performance may vary significantly across different markets and conditions.
Parameter Sensitivity: Requires fine-tuning of parameters to ensure optimal performance, which might demand a steep learning curve for new users.
█ NOTES
For best results, combine this tool with other forms of analysis, such as fundamental analysis and other technical indicators, to confirm signals and enhance decision-making.
█ THANKS
Special thanks to the PineCoders community the Pine Coders themselves for their foundational contributions to the concepts used in this script. Their pioneering work in the fields of technical analysis and Pine Script development has been invaluable. This script is a testament to the collaborative spirit of the TradingView developer community, integrating analytical techniques with innovative approaches to offer a tool that is both modern and cutting-edge.
Multiple Indicators Screener v2After taking the approval of Mr. QuantNomad
Multiple Indicators Screener by QuantNomad
New lists have been modified and added
Built-in indicators:
RSI (Relative Strength Index): Provides trading opportunities based on overbought or oversold market conditions.
MFI (Cash Flow Index): Measures the flow of cash into or from assets, which helps in identifying buying and selling areas.
Williams Percent Range (WPR): Measures how high or low the price has been in the last time period, giving signals of periods of saturation.
Supertrend: Used to determine market direction and potential entry and exit locations.
Volume Change Percentage: Provides an analysis of the volume change percentage, which helps in identifying demand and supply changes for assets.
How to use:
Users can choose which symbols they want to monitor and analyze using a variety of built-in indicators.
The indicator provides visual signals that help traders identify potential trading opportunities based on the selected settings.
RSI in purple = buy weak liquidity (safe entry).
MFI in yellow = Liquidity
WPR in blue = RSI, MFI and WPR in oversold areas for all.
Allows users to customize the display locations and appearance of the cursor to their personal preferences.
Disclaimer
Please remember that past performance may not be indicative of future results.
Due to various factors, including changing market conditions, the strategy may no longer perform as well as in historical backtesting.
This post and the script don’t provide any financial advice.
=========================================================================
فاحص لمؤشرات متعددة مع مخرجات جدول شاملة لتسهيل مراقبة الكثير من العملات تصل الى 99 في وقت واحد
بختصر الشرح
ظهور اللون البنفسجي يعني كمية الشراء ضعف السيولة .
ظهور اللون الازرق جميع المؤشرات وصلة الى مرحلة التشبع البيعي ( دخول آمن )
ظهور اللون الاصفر يعني السيولة ضعفين الشراء ( عكس اتجاه قريب ) == ركزو على هاللون خصوصا مع عملات الخفيفة
Price alert multi symbols (Miu)This indicator won't plot anything to the chart.
Please follow steps below to set your alarms based on multiple symbols' prices:
1) Add indicator to the chart
2) Go to settings
3) Check symbols you want to receive alerts (choose up to 8 different symbols)
4) Set price for each symbol
5) Once all is set go back to the chart and click on 3 dots to set alert in this indicator, rename your alert and confirm
6) You can remove indicator after alert is set and it'll keep working as expected
What does this indicator do?
This indicator will generate alerts based on following conditions:
- If price set is met for any symbol
Once condition is met it will send an alert with the following information:
- Symbol name (e.g: BTC, ETH, LTC)
- Price reached
This script requests current price for each symbol through request.security() built-in function. It also requests amount of digits (mintick) for each symbol to send alerts with correct value.
This script was developed to attend a demand from a comment in other published script.
Feel free to give feedbacks on comments section below.
Enjoy!
Smart Money Setup 05 [TradingFinder] Minor OB & Trend Proof🔵 Introduction
The "Smart Money Concept" transcends the realm of mere technical trading strategies to embody a comprehensive philosophy on the dynamics of market operations. It posits that key market participants engage in price manipulation, thereby complicating the trading landscape for smaller, retail traders.
Under this doctrine, retail traders are advised to tailor their strategies in alignment with the maneuvers of "Smart Money" - essentially, the capital operated by market makers.
To this end, one should endeavor to mirror the trading patterns of these influential market participants, who are adept at navigating through the nuances of supply, demand, and overall market structure. As a proponent of Smart Money trading, these elements are pivotal in your decision-making process for trade entries.
🟣 Key Insights
The core principle of this strategy hinges on misleading other traders. A sudden market movement against the prevailing trend that results in the formation of either a lower low or a higher high, followed by a pullback where a divergence pattern emerges, sets the stage.
Subsequently, the market may form another lower low or higher high. Traders, persuaded that the market will continue along the trajectory of the new movement, are caught off-guard when the price abruptly reverses direction. Following a "Stop Hunt" of the traders' open positions, the market resumes its initial trend.
To grasp the essence of this setup, observe the following illustrations.
"Bullish Setup" :
"Bearish Setup" :
🔵 How to Use
The setups can be customized based on the desired formation period. This adjustment can be made through the indicator's price setting options, where the default period is set at 2.
Upon configuring your preferred period, the signals become actionable. Once a setup forms, the subsequent step involves waiting for the price to reach the "Order Block".
"Bullish Setup" :
"Bearish Setup" :
Smart Money Setup 04 [TradingFinder] Three Drive (Harmonic) + OB🔵 Introduction
The "Three Drive" pattern is a well-known formation in technical analysis, recognized for its ability to signal potential trend reversals in price action. Within the realm of trading, particularly in the context of "Reversal Patterns," the Three Drive pattern holds significance as a reliable indicator of shifts in market sentiment.
🟣 Bullish 3 Drive
This pattern typically manifests at a price bottom, where a sequence of lower lows suggests a prevailing negative trend. However, within the structure of the Three Drive pattern, a notable occurrence unfolds.
The second low breaches the range of the first low, followed by the third low surpassing the range of the second low. These penetrations signify a diminishing selling pressure and an emerging buying interest.
Traders often await the confirmation of the third low surpassing the second low as an entry point, with price targets set at the highs formed within the Three Drive pattern.
🟣 Bearish 3 Drive
Conversely, the Bearish Three Drive pattern emerges at a price top, characterized by a sequence of higher highs indicating an upward trend. Yet, amidst this apparent bullish momentum, a shift occurs.
The second high breaks beyond the range of the first high, succeeded by the third high exceeding the range of the second high. These breaches signify a waning buying strength and a resurgence in selling pressure.
Entry into a trade is often executed after the confirmation of the third high surpassing the second high, with targets set at the lows formed within the Three Drive pattern.
Importance :
Understanding the Three Drive pattern's significance extends beyond mere technical analysis. It bears resemblance to other established patterns, such as the Harmonic Pattern and Ending Diagonal within the Elliott Wave Theory.
Recognizing these parallels aids traders in comprehending broader market dynamics and potential price movements.
🔵 Formation of 3 Drive in Order Block Zone
The convergence of the Three Drive pattern with the concept of the Order Block Zone introduces a nuanced layer to traders' analytical approach.
In "Price Action" methodology, Order Blocks represent areas on the price chart where significant market players, such as institutional traders, have executed notable orders.
These zones often act as barriers, with price encountering resistance or support upon reaching them.
When the Three Drive pattern forms within an Order Block Zone, it signifies a confluence of market dynamics.
The completion of the pattern within this zone suggests a potential reversal in the prevailing trend, augmented by the presence of significant institutional orders.
Traders incorporate these Order Blocks into their analysis to identify probable levels where price may change direction, enhancing the reliability of their trading decisions.
🔵 How to Use :
To effectively utilize the Three Drive pattern within the Order Block Zone, traders seek alignment between the completion of the pattern and the presence of significant Order Blocks.
This convergence enhances the reliability of the pattern's signals, increasing the likelihood of successful trade outcomes.
Bullish Three Drive in Demand Zone :
Bearish Three Drive in Supply Zone :
Settings :
You can set your desired "Pivot Period" via settings for the indicator to identify setups based on it.
Smart Money Setup 03 [TradingFinder] Minor OB & Trend Proof🔵 Introduction
The "Smart Money Concept" transcends mere technical trading strategies; it embodies a comprehensive philosophy elucidating market dynamics. Central to this concept is the acknowledgment that influential market participants manipulate price actions, presenting challenges for retail traders.
As a "retail trader", aligning your strategy with the behavior of "Smart Money," primarily market makers, is paramount. Understanding their trading patterns, which revolve around supply, demand, and market structure, forms the cornerstone of your approach. Consequently, decisions to enter trades should be informed by these considerations.
🟣 Important Note
In this setup, pattern formation revolves around the robustness of the "Stop Hunt" targeting retail traders.
When this stop hunt occurs, if the price tests below the minor pivot or above the minor pivot, a "Minor Order Block" is formed.
Similarly, if the price tests below the major pivot or above the major pivot, a "Major Order Block" is formed.
Since the price hasn't successfully broken the major pivots before breaking the Top or Bottom, it can be inferred that the minor pivots formed within a leg of price movement exhibit a "Range" structure.
For a deeper comprehension of this setup, refer to the accompanying visual aids below.
Bullish Setup Details :
Bearish Setup Details :
🔵 How to Use
Upon integrating the indicator into your chart, exercise patience as you await the evolution of the trading setup.
Experiment with different trading positions by adjusting both the "Time Frame" and "Pivot Period". Typically, setups materializing over longer "Time Frames" and "Pivot Periods" carry heightened validity.
Bullish Setup Details on Chart :
Bearish Setup Details on Chart :
Within the settings, you possess the flexibility to modify the "Pivot Period" input to tailor the indicator to your preferences.
Market Structure (Intrabar) [LuxAlgo]The Market Structure (Intrabar) indicator is designed to automatically detect and highlight real-time intrabar market structures, a core component of the Smart Money Concepts methodology.
🔶 USAGE
The proposed indicator gives a detailed picture of the most recent candle lower timeframe trends, highlighting market structures within them.
This can be particularly useful to assess the price dynamic within the most recent candle. For example, we can see how pronounced a trend is by the number of opposite bullish/bearish market structures formed within the candle.
Users can select the intrabar timeframe of interest from the "Intrabar Timeframe" setting, using a timeframe significantly lower than the chart timeframe will return more intrabar candles and potentially more market structures.
🔹 Dashboard
Users have access to a dashboard returning useful statistics such as the number of formed CHoCH's and BOS's from the intrabar prices. These can be indicative of how predominant a trend is within the intrabar data or if there exist multiple trends.
🔶 DETAILS
Market structures allow determining trend continuations as well as trend reversals in the market through two distinct structures:
🔹 Change of Character (CHoCH)
A change of character (CHoCH) refers to a shift in the market behavior of a security that is driven by changes in the underlying supply and demand dynamics. CHoCH's are indicative of confirmed reversals.
🔹 Break of Structure (BoS)
The break of structure (BoS) refers to the point at which a key level of support or resistance is broken. BOS's are indicative of confirmed trend continuations.
🔶 SETTINGS
🔹Inside the Bar Market Structure
Intrabar Timeframe: Lower timeframe setting option, if set to 'Auto' the script will determine the lower timeframe based on the chart timeframe.
Intrabar Market Structure, Length: Toggles the visibility of the break of structures and change of characters. Length defines the detection length of the swing levels.
Intrabar Swing Levels: Toggles the visibility of the swing levels, including a color customization option for highs and lows.
Intrabar Statistics: Toggles the visibility of the dashboard. Some further statistical details are presented in the tooltips of the table cells
🔹 General
Market Structure Colors: Color customization option for the break of structure and change of character lines and labels.
Intrabar Candle Colors: Color customization option for intrabar candles.
Intrabar Candles Horizontal Offset: Adjusting the intrabar candles horizontal position
Dashboard: Dashboard position and size customization option
🔶 LIMITATIONS
Please note that seconds-based intervals are available for premium and professional plan holders, which implies that the seconds-based intervals usage of the indicator may not be available for all users depending on their subscription plan.
🔶 RELATED SCRIPTS
Smart-Money-Concepts
ICT-Concepts
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.
Gaps Profile [vnhilton]Note: If you get an error preventing indicator from executing due to a loop running longer than >500ms, please lower the amount of boxes shown and/or increase the minimum gap % threshold.
OVERVIEW
The Gaps Profile (GP) simply shows the remaining gaps on the chart that have yet to be closed. Gaps are created where there's a distance between the current open and the previous close. Big gaps suggest change in sentiment and volatility causing prices to pull away thereby creating gaps. Gaps can be used as pivot areas where price may attempt to close the inefficiency entirely and/or serve as supply/demand zones.
(FEATURES)
- 3 to 499 remaining up/down gaps can be displayed on the chart (furthest gaps away from price are removed to make way for new gaps)
- Minimum gap % threshold
- Ability to highlight largest or newest up/down gap
- 4 GP color themes: Mono, Up/Down, Up/Down Largest Gradients, Up/Down Newest Gradients
- GP Type: Left, Right (how it is built - overlapping gaps plotted from left/right to right/left)
- GP offset from current bar
- Box border width
- Box border style for up/down: Dashed, Dotted, Solid
- Toggles to hide border/box with ease
Order-Block Detector ICT/SMT + FVG + SignalsOrderBlock-Finder
This script shows order-blocks (OB) and fair-value-gaps (FVG). Additionaly there are entry signals for OB and FVG. The Dist-Parameter tell how many candles should exist between the beginning of the OB or FVG and the pullback.
Order-Blocks
An order block in trading typically refers to a significant grouping of buy or sell orders at a particular price level within a financial market. These blocks of orders can influence price movement when they are executed. Here's a breakdown:
Buy Order Block: This occurs when there's a large concentration of buy orders at a specific price level. It indicates a significant interest among traders to purchase the asset if the price reaches that level.
Sell Order Block: Conversely, a sell order block happens when there's a notable accumulation of sell orders at a particular price level. This suggests that many traders are willing to sell the asset if the price reaches that level.
Impact on Price: Order blocks can influence price movement because when the market approaches these levels, the orders within the block may be triggered, leading to increased buying or selling pressure, depending on the type of block. This surge in trading activity can cause the price to either bounce off the level or break through it.
Support and Resistance: Order blocks are often associated with support and resistance levels. A buy order block may act as support, preventing the price from falling further, while a sell order block may serve as resistance, hindering upward price movement.
Fair-Value-Gap
The fair value gap in trading refers to the difference between the current market price of an asset and its calculated fair value. This concept is often used in financial markets, especially in the context of stocks and other securities. Here's a breakdown:
Market Price: The market price is the price at which an asset is currently trading in the market. It is determined by the interaction of supply and demand forces, as well as various other factors such as news, sentiment, and economic conditions.
Fair Value: Fair value represents the estimated intrinsic value of an asset based on fundamental analysis, which includes factors such as earnings, dividends, cash flow, growth prospects, and prevailing interest rates. It's essentially what an asset should be worth based on its fundamentals.
Fair Value Calculation: Analysts and investors use various methods to calculate the fair value of an asset. Common approaches include discounted cash flow (DCF) analysis, comparable company analysis (CCA), and dividend discount models (DDM), among others.
Fair Value Gap: The fair value gap is the numerical difference between the calculated fair value of an asset and its current market price. If the market price is higher than the fair value, it suggests that the asset may be overvalued. Conversely, if the market price is lower than the fair value, it indicates that the asset may be undervalued.
Trading Implications: Traders and investors often pay attention to the fair value gap to identify potential trading opportunities. If the market price deviates significantly from the fair value, it may present opportunities to buy or sell the asset with the expectation that the market price will eventually converge towards its fair value.
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
Dark Cloud [TradingFinder] Piercing Line Reversal chart Pattern
🔵 Introduction
"Reversal candlestick patterns" are among the Japanese candlestick patterns considered as alerts for a potential change in the current price trend. It is often assumed that by identifying reversal candlestick patterns, the price trend will definitely change, either from bullish to bearish or from bearish to bullish. However, this claim is not entirely accurate, and a change in price trend does not always mean a reversal.
Nonetheless, the importance of reversal candlestick patterns remains significant. By recognizing these patterns, you can better predict changes in the trend with higher probability and make better trading decisions.
🔵 Dark Cloud
The "Dark Cloud" pattern occurs when, after an upward trend, buyers continue to drive the price up in the first candle. However, in the next candle, with sellers entering and increasing selling pressure, the price starts to decrease compared to the close of the previous candle.
This price decrease is significant enough that in the last candle, the price goes lower than the open of the previous candle, serving as a warning sign for a potential change in price trend.
The fundamental principles for the formation of the "Dark Cloud" pattern include :
1.Two candles consisting of a positive candle (first candle) and a negative candle (second candle) whose main body should be above the halfway point of the first candle's main body but does not completely cover it.
2.The color of the main body of the second candle should be opposite to the color of the main body of the first candle.
Factors affecting the strength of the "Dark Cloud" pattern include :
1.The length of the bodies of both candles, especially the second candle, which increases the strength of the pattern.
2.The gap between the two bodies can also indicate the strength of the pattern.
3.The absence of a lower shadow in the second candle also indicates the strength of the pattern.
4.If the pattern forms in a price resistance range, it has more strength.
🔵 Piercing Line
The "Piercing Line" pattern occurs when, after a downward trend, sellers decrease the price by offering their shares on the first day. However, on the next day, with buyers entering and increasing demand, the price starts to increase compared to the close of the previous day.
This increase is significant enough that in the last candle, the price goes higher than the open of the previous day, serving as a warning sign for a reversal in the price trend. Overall, this pattern is the opposite of the "Dark Cloud" pattern and occurs under a bearish trend.
The fundamental principles for the formation of the "Piercing Line" pattern include :
1.Two candles consisting of a negative candle (first candle) and a positive candle (second candle) whose main body should be above the halfway point of the first candle's main body but does not completely cover it.
2.The color of the main body of the second candle should be opposite to the color of the main body of the first candle.
Factors affecting the strength of the "Piercing Line" pattern include :
1.The length of the bodies of both candles, especially the second candle, which increases the strength of the pattern.
2.The gap between the two bodies can also indicate the strength of the pattern.
3.The absence of an upper shadow in the second candle also indicates the strength of the pattern.
4.If the pattern forms in a price support range, it has more strength.
🔵 How to Use
The "green circle" symbol corresponds to the "Strong Piercing Line" signal, the "blue triangle" symbol corresponds to the "Weak Piercing Line" signal, the "red circle" symbol corresponds to the "Strong Dark Cloud" signal, and the "red triangle" symbol corresponds to the "Weak Dark Cloud" signal.
🔵 Setting
Using the "Show Dark Cloud" and "Show Piercing Line" buttons, you can enable or disable the display of Dark Cloud and Piercing Line.
Fair Value Gaps Mitigation Oscillator [LuxAlgo]The Fair Value Gaps Mitigation Oscillator is an oscillator based on the traditional Fair Value Gaps (FVGs) imbalances. The oscillator displays the current total un-mitigated values for the number of FVGs chosen by the user.
The indicator also displays each New FVG as a bar representing the current ratio of the New FVG in relation to the current un-mitigated total for its direction.
🔶 USAGE
When an FVG forms, it is often interpreted as strong market sentiment in the direction of the gap. For example, an upward FVG during an uptrend is typically seen as a confirmation of the strength and continuation of the trend, as it indicates that buyers are willing to purchase at higher prices without much resistance, suggesting strong demand and positive sentiment.
By analyzing the mitigation (or lack thereof), we can visualize the increase of directional strength in a trend. This is where the proposed oscillator is useful.
🔶 DETAILS
The oscillator's values are expressed as Percentages (%). Each FVG is allocated 100% of the total of its width with a max potential value of 100 and minimum potential value of 0.
Based on the "FVG Lookback" Input, the FVGs are scaled to fit within the range of +1 to -1. Using a higher "FVG Lookback" value will allow you to get indications of longer-term trends.
A higher value of the normalized bullish FVG areas suggest a stronger and cleaner uptrend, while lower values of the bearish the normalized bullish FVG areas suggest a stronger and cleaner downtrend.
+1 or -1 indicates that there is a Full Lookback of FVGs, and each one is fully un-mitigated, and the opposite direction of FVGs is entirely Mitigated.
When the price closes over/under or within an FVG it begins to get mitigated, when this happens the % of mitigation is subtracted from the total.
When a New FVG is formed, a Histogram bar is created representing the ratio of the current FVG's width to the total width off all un-mitigated FVGs.
The entire bar represents 100% of total un-mitigated FVG Width.
The filled area represents the current FVG's width relative to the whole.
A 50% hash mark is also displayed for reference.
🔶 SETTINGS
FVG Lookback - Determines the number of FVGs (Bullish and Bearish Pairs) to keep in memory for analysis.
BAERMThe Bitcoin Auto-correlation Exchange Rate Model: A Novel Two Step Approach
THIS IS NOT FINANCIAL ADVICE. THIS ARTICLE IS FOR EDUCATIONAL AND ENTERTAINMENT PURPOSES ONLY.
If you enjoy this software and information, please consider contributing to my lightning address
Prelude
It has been previously established that the Bitcoin daily USD exchange rate series is extremely auto-correlated
In this article, we will utilise this fact to build a model for Bitcoin/USD exchange rate. But not a model for predicting the exchange rate, but rather a model to understand the fundamental reasons for the Bitcoin to have this exchange rate to begin with.
This is a model of sound money, scarcity and subjective value.
Introduction
Bitcoin, a decentralised peer to peer digital value exchange network, has experienced significant exchange rate fluctuations since its inception in 2009. In this article, we explore a two-step model that reasonably accurately captures both the fundamental drivers of Bitcoin’s value and the cyclical patterns of bull and bear markets. This model, whilst it can produce forecasts, is meant more of a way of understanding past exchange rate changes and understanding the fundamental values driving the ever increasing exchange rate. The forecasts from the model are to be considered inconclusive and speculative only.
Data preparation
To develop the BAERM, we used historical Bitcoin data from Coin Metrics, a leading provider of Bitcoin market data. The dataset includes daily USD exchange rates, block counts, and other relevant information. We pre-processed the data by performing the following steps:
Fixing date formats and setting the dataset’s time index
Generating cumulative sums for blocks and halving periods
Calculating daily rewards and total supply
Computing the log-transformed price
Step 1: Building the Base Model
To build the base model, we analysed data from the first two epochs (time periods between Bitcoin mining reward halvings) and regressed the logarithm of Bitcoin’s exchange rate on the mining reward and epoch. This base model captures the fundamental relationship between Bitcoin’s exchange rate, mining reward, and halving epoch.
where Yt represents the exchange rate at day t, Epochk is the kth epoch (for that t), and epsilont is the error term. The coefficients beta0, beta1, and beta2 are estimated using ordinary least squares regression.
Base Model Regression
We use ordinary least squares regression to estimate the coefficients for the betas in figure 2. In order to reduce the possibility of over-fitting and ensure there is sufficient out of sample for testing accuracy, the base model is only trained on the first two epochs. You will notice in the code we calculate the beta2 variable prior and call it “phaseplus”.
The code below shows the regression for the base model coefficients:
\# Run the regression
mask = df\ < 2 # we only want to use Epoch's 0 and 1 to estimate the coefficients for the base model
reg\_X = df.loc\ [mask, \ \].shift(1).iloc\
reg\_y = df.loc\ .iloc\
reg\_X = sm.add\_constant(reg\_X)
ols = sm.OLS(reg\_y, reg\_X).fit()
coefs = ols.params.values
print(coefs)
The result of this regression gives us the coefficients for the betas of the base model:
\
or in more human readable form: 0.029, 0.996869586, -0.00043. NB that for the auto-correlation/momentum beta, we did NOT round the significant figures at all. Since the momentum is so important in this model, we must use all available significant figures.
Fundamental Insights from the Base Model
Momentum effect: The term 0.997 Y suggests that the exchange rate of Bitcoin on a given day (Yi) is heavily influenced by the exchange rate on the previous day. This indicates a momentum effect, where the price of Bitcoin tends to follow its recent trend.
Momentum effect is a phenomenon observed in various financial markets, including stocks and other commodities. It implies that an asset’s price is more likely to continue moving in its current direction, either upwards or downwards, over the short term.
The momentum effect can be driven by several factors:
Behavioural biases: Investors may exhibit herding behaviour or be subject to cognitive biases such as confirmation bias, which could lead them to buy or sell assets based on recent trends, reinforcing the momentum.
Positive feedback loops: As more investors notice a trend and act on it, the trend may gain even more traction, leading to a self-reinforcing positive feedback loop. This can cause prices to continue moving in the same direction, further amplifying the momentum effect.
Technical analysis: Many traders use technical analysis to make investment decisions, which often involves studying historical exchange rate trends and chart patterns to predict future exchange rate movements. When a large number of traders follow similar strategies, their collective actions can create and reinforce exchange rate momentum.
Impact of halving events: In the Bitcoin network, new bitcoins are created as a reward to miners for validating transactions and adding new blocks to the blockchain. This reward is called the block reward, and it is halved approximately every four years, or every 210,000 blocks. This event is known as a halving.
The primary purpose of halving events is to control the supply of new bitcoins entering the market, ultimately leading to a capped supply of 21 million bitcoins. As the block reward decreases, the rate at which new bitcoins are created slows down, and this can have significant implications for the price of Bitcoin.
The term -0.0004*(50/(2^epochk) — (epochk+1)²) accounts for the impact of the halving events on the Bitcoin exchange rate. The model seems to suggest that the exchange rate of Bitcoin is influenced by a function of the number of halving events that have occurred.
Exponential decay and the decreasing impact of the halvings: The first part of this term, 50/(2^epochk), indicates that the impact of each subsequent halving event decays exponentially, implying that the influence of halving events on the Bitcoin exchange rate diminishes over time. This might be due to the decreasing marginal effect of each halving event on the overall Bitcoin supply as the block reward gets smaller and smaller.
This is antithetical to the wrong and popular stock to flow model, which suggests the opposite. Given the accuracy of the BAERM, this is yet another reason to question the S2F model, from a fundamental perspective.
The second part of the term, (epochk+1)², introduces a non-linear relationship between the halving events and the exchange rate. This non-linear aspect could reflect that the impact of halving events is not constant over time and may be influenced by various factors such as market dynamics, speculation, and changing market conditions.
The combination of these two terms is expressed by the graph of the model line (see figure 3), where it can be seen the step from each halving is decaying, and the step up from each halving event is given by a parabolic curve.
NB - The base model has been trained on the first two halving epochs and then seeded (i.e. the first lag point) with the oldest data available.
Constant term: The constant term 0.03 in the equation represents an inherent baseline level of growth in the Bitcoin exchange rate.
In any linear or linear-like model, the constant term, also known as the intercept or bias, represents the value of the dependent variable (in this case, the log-scaled Bitcoin USD exchange rate) when all the independent variables are set to zero.
The constant term indicates that even without considering the effects of the previous day’s exchange rate or halving events, there is a baseline growth in the exchange rate of Bitcoin. This baseline growth could be due to factors such as the network’s overall growth or increasing adoption, or changes in the market structure (more exchanges, changes to the regulatory environment, improved liquidity, more fiat on-ramps etc).
Base Model Regression Diagnostics
Below is a summary of the model generated by the OLS function
OLS Regression Results
\==============================================================================
Dep. Variable: logprice R-squared: 0.999
Model: OLS Adj. R-squared: 0.999
Method: Least Squares F-statistic: 2.041e+06
Date: Fri, 28 Apr 2023 Prob (F-statistic): 0.00
Time: 11:06:58 Log-Likelihood: 3001.6
No. Observations: 2182 AIC: -5997.
Df Residuals: 2179 BIC: -5980.
Df Model: 2
Covariance Type: nonrobust
\==============================================================================
coef std err t P>|t| \
\------------------------------------------------------------------------------
const 0.0292 0.009 3.081 0.002 0.011 0.048
logprice 0.9969 0.001 1012.724 0.000 0.995 0.999
phaseplus -0.0004 0.000 -2.239 0.025 -0.001 -5.3e-05
\==============================================================================
Omnibus: 674.771 Durbin-Watson: 1.901
Prob(Omnibus): 0.000 Jarque-Bera (JB): 24937.353
Skew: -0.765 Prob(JB): 0.00
Kurtosis: 19.491 Cond. No. 255.
\==============================================================================
Below we see some regression diagnostics along with the regression itself.
Diagnostics: We can see that the residuals are looking a little skewed and there is some heteroskedasticity within the residuals. The coefficient of determination, or r2 is very high, but that is to be expected given the momentum term. A better r2 is manually calculated by the sum square of the difference of the model to the untrained data. This can be achieved by the following code:
\# Calculate the out-of-sample R-squared
oos\_mask = df\ >= 2
oos\_actual = df.loc\
oos\_predicted = df.loc\
residuals\_oos = oos\_actual - oos\_predicted
SSR = np.sum(residuals\_oos \*\* 2)
SST = np.sum((oos\_actual - oos\_actual.mean()) \*\* 2)
R2\_oos = 1 - SSR/SST
print("Out-of-sample R-squared:", R2\_oos)
The result is: 0.84, which indicates a very close fit to the out of sample data for the base model, which goes some way to proving our fundamental assumption around subjective value and sound money to be accurate.
Step 2: Adding the Damping Function
Next, we incorporated a damping function to capture the cyclical nature of bull and bear markets. The optimal parameters for the damping function were determined by regressing on the residuals from the base model. The damping function enhances the model’s ability to identify and predict bull and bear cycles in the Bitcoin market. The addition of the damping function to the base model is expressed as the full model equation.
This brings me to the question — why? Why add the damping function to the base model, which is arguably already performing extremely well out of sample and providing valuable insights into the exchange rate movements of Bitcoin.
Fundamental reasoning behind the addition of a damping function:
Subjective Theory of Value: The cyclical component of the damping function, represented by the cosine function, can be thought of as capturing the periodic fluctuations in market sentiment. These fluctuations may arise from various factors, such as changes in investor risk appetite, macroeconomic conditions, or technological advancements. Mathematically, the cyclical component represents the frequency of these fluctuations, while the phase shift (α and β) allows for adjustments in the alignment of these cycles with historical data. This flexibility enables the damping function to account for the heterogeneity in market participants’ preferences and expectations, which is a key aspect of the subjective theory of value.
Time Preference and Market Cycles: The exponential decay component of the damping function, represented by the term e^(-0.0004t), can be linked to the concept of time preference and its impact on market dynamics. In financial markets, the discounting of future cash flows is a common practice, reflecting the time value of money and the inherent uncertainty of future events. The exponential decay in the damping function serves a similar purpose, diminishing the influence of past market cycles as time progresses. This decay term introduces a time-dependent weight to the cyclical component, capturing the dynamic nature of the Bitcoin market and the changing relevance of past events.
Interactions between Cyclical and Exponential Decay Components: The interplay between the cyclical and exponential decay components in the damping function captures the complex dynamics of the Bitcoin market. The damping function effectively models the attenuation of past cycles while also accounting for their periodic nature. This allows the model to adapt to changing market conditions and to provide accurate predictions even in the face of significant volatility or structural shifts.
Now we have the fundamental reasoning for the addition of the function, we can explore the actual implementation and look to other analogies for guidance —
Financial and physical analogies to the damping function:
Mathematical Aspects: The exponential decay component, e^(-0.0004t), attenuates the amplitude of the cyclical component over time. This attenuation factor is crucial in modelling the diminishing influence of past market cycles. The cyclical component, represented by the cosine function, accounts for the periodic nature of market cycles, with α determining the frequency of these cycles and β representing the phase shift. The constant term (+3) ensures that the function remains positive, which is important for practical applications, as the damping function is added to the rest of the model to obtain the final predictions.
Analogies to Existing Damping Functions: The damping function in the BAERM is similar to damped harmonic oscillators found in physics. In a damped harmonic oscillator, an object in motion experiences a restoring force proportional to its displacement from equilibrium and a damping force proportional to its velocity. The equation of motion for a damped harmonic oscillator is:
x’’(t) + 2γx’(t) + ω₀²x(t) = 0
where x(t) is the displacement, ω₀ is the natural frequency, and γ is the damping coefficient. The damping function in the BAERM shares similarities with the solution to this equation, which is typically a product of an exponential decay term and a sinusoidal term. The exponential decay term in the BAERM captures the attenuation of past market cycles, while the cosine term represents the periodic nature of these cycles.
Comparisons with Financial Models: In finance, damped oscillatory models have been applied to model interest rates, stock prices, and exchange rates. The famous Black-Scholes option pricing model, for instance, assumes that stock prices follow a geometric Brownian motion, which can exhibit oscillatory behavior under certain conditions. In fixed income markets, the Cox-Ingersoll-Ross (CIR) model for interest rates also incorporates mean reversion and stochastic volatility, leading to damped oscillatory dynamics.
By drawing on these analogies, we can better understand the technical aspects of the damping function in the BAERM and appreciate its effectiveness in modelling the complex dynamics of the Bitcoin market. The damping function captures both the periodic nature of market cycles and the attenuation of past events’ influence.
Conclusion
In this article, we explored the Bitcoin Auto-correlation Exchange Rate Model (BAERM), a novel 2-step linear regression model for understanding the Bitcoin USD exchange rate. We discussed the model’s components, their interpretations, and the fundamental insights they provide about Bitcoin exchange rate dynamics.
The BAERM’s ability to capture the fundamental properties of Bitcoin is particularly interesting. The framework underlying the model emphasises the importance of individuals’ subjective valuations and preferences in determining prices. The momentum term, which accounts for auto-correlation, is a testament to this idea, as it shows that historical price trends influence market participants’ expectations and valuations. This observation is consistent with the notion that the price of Bitcoin is determined by individuals’ preferences based on past information.
Furthermore, the BAERM incorporates the impact of Bitcoin’s supply dynamics on its price through the halving epoch terms. By acknowledging the significance of supply-side factors, the model reflects the principles of sound money. A limited supply of money, such as that of Bitcoin, maintains its value and purchasing power over time. The halving events, which reduce the block reward, play a crucial role in making Bitcoin increasingly scarce, thus reinforcing its attractiveness as a store of value and a medium of exchange.
The constant term in the model serves as the baseline for the model’s predictions and can be interpreted as an inherent value attributed to Bitcoin. This value emphasizes the significance of the underlying technology, network effects, and Bitcoin’s role as a medium of exchange, store of value, and unit of account. These aspects are all essential for a sound form of money, and the model’s ability to account for them further showcases its strength in capturing the fundamental properties of Bitcoin.
The BAERM offers a potential robust and well-founded methodology for understanding the Bitcoin USD exchange rate, taking into account the key factors that drive it from both supply and demand perspectives.
In conclusion, the Bitcoin Auto-correlation Exchange Rate Model provides a comprehensive fundamentally grounded and hopefully useful framework for understanding the Bitcoin USD exchange rate.
