Earnings Gap UpsBased on research conducted by John Pocorobba and Jason Thompson, the Earnings Gap Ups Indicator is designed to identify three types of earnings gaps, key levels, and the "alpha window"—a period when stocks often outperform following a gap. These gaps are frequently observed in high-performing stocks.
What is an Earnings Gap?
An earnings gap occurs when a stock's price makes a significant jump, after the company reports earnings signifying the street (institutions) were caught off guard.
The three different types of gaps are as follows: [/b
PEG (Power Earnings Gap)
Price gain of 10% or more
Volume is greater than 200% above the 50-day average
EPS surprise of at least 20%
Monster Gap
Price gain of 20% or more
Volume is greater than 300% above the 50-day average
No fundamental requirement
Monster Peg
Price Gain of 20% or more
Volume is greater than 300% above the 50-day average
EPS surprise of at least 20%
Key Levels and the Alpha Window
In addition to spotting these gaps, the indicator marks key levels on the chart and extends them through the alpha window, which represents the time period when the stock tends to outperform after the gap.
Key levels include:
High volume close: The closing price on a day with unusually high trading volume
High volume close minus 5%: A potential support level below the high volume close
Gap day high: The highest price reached on the gap day
Gap day low: The lowest price reached on the gap day
By understanding and tracking these gaps and levels, traders can map out a playbook for trading earnings gaps.
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Pulse DPO: Major Cycle Tops and Bottoms█ OVERVIEW
Pulse DPO is an oscillator designed to highlight Major Cycle Tops and Bottoms .
It works on any market driven by cycles. It operates by removing the short-term noise from the price action and focuses on the market's cyclical nature.
This indicator uses a Normalized version of the Detrended Price Oscillator (DPO) on a 0-100 scale, making it easier to identify major tops and bottoms.
Credit: The DPO was first developed by William Blau in 1991.
█ HOW TO READ IT
Pulse DPO oscillates in the range between 0 and 100. A value in the upper section signals an OverBought (OB) condition, while a value in the lower section signals an OverSold (OS) condition.
Generally, the triggering of OB and OS conditions don't necessarily translate into swing tops and bottoms, but rather suggest caution on approaching a market that might be overextended.
Nevertheless, this indicator has been customized to trigger the signal only during remarkable top and bottom events.
I suggest using it on the Daily Time Frame , but you're free to experiment with this indicator on other time frames.
The indicator has Built-in Alerts to signal the crossing of the Thresholds. Please don't act on an isolated signal, but rather integrate it to work in conjunction with the indicators present in your Trading Plan.
█ OB SIGNAL ON: ENTERING OVERBOUGHT CONDITION
When Pulse DPO crosses Above the Top Threshold it Triggers ON the OB signal. At this point the oscillator line shifts to OB color.
When Pulse DPO enters the OB Zone, please beware! In this Area the Major Players usually become Active Sellers to the Public. While the OB signal is On, it might be wise to Consider Selling a portion or the whole Long Position.
Please note that even though this indicator aims to focus on major tops and bottoms, a strong trending market might trigger the OB signal and stay with it for a long time. That's especially true on young markets and on bubble-mode markets.
█ OB SIGNAL OFF: EXITING OVERBOUGHT CONDITION
When Pulse DPO crosses Below the Top Threshold it Triggers OFF the OB signal. At this point the oscillator line shifts to its normal color.
When Pulse DPO exits the OB Zone, please beware because a Major Top might just have occurred. In this Area the Major Players usually become Aggressive Sellers. They might wind up any remaining Long Positions and Open new Short Positions.
This might be a good area to Open Shorts or to Close/Reverse any remaining Long Position. Whatever you choose to do, it's usually best to act quickly because the market is prone to enter into panic mode.
█ OS SIGNAL ON: ENTERING OVERSOLD CONDITION
When Pulse DPO crosses Below the Bottom Threshold it Triggers ON the OS signal. At this point the oscillator line shifts to OS color.
When Pulse DPO enters the OS Zone, please beware because in this Area the Major Players usually become Active Buyers accumulating Long Positions from the desperate Public.
While the OS signal is On, it might be wise to Consider becoming a Buyer or to implement a Dollar-Cost Averaging (DCA) Strategy to build a Long Position towards the next Cycle. In contrast to the tops, the OS state usually takes longer to resolve a major bottom.
█ OS SIGNAL OFF: EXITING OVERSOLD CONDITION
When Pulse DPO crosses Above the Bottom Threshold it Triggers OFF the OS signal. At this point the oscillator line shifts to its normal color.
When Pulse DPO exits the OS Zone, please beware because a Major Bottom might already be in place. In this Area the Major Players become Aggresive Buyers. They might wind up any remaining Short Positions and Open new Long Positions.
This might be a good area to Open Longs or to Close/Reverse any remaining Short Positions.
█ WHY WOULD YOU BE INTERESTED IN THIS INDICATOR?
This indicator is built over a solid foundation capable of signaling Major Cycle Tops and Bottoms across many markets. Let's see some examples:
Early Bitcoin Years: From 0 to 1242
This chart is in logarithmic mode in order to properly display various exponential cycles. Pulse DPO is properly signaling the major early highs from 9-Jun-2011 at 31.50, to the next one on 9-Apr-2013 at 240 and the epic top from 29-Nov-2013 at 1242.
Due to the massive price movements, the OB condition stays pinned during most of the exponential price action. But as you can see, the OB condition quickly vanishes once the Cycle Top has been reached. As the market matures, the OB condition becomes more exceptional and triggers much closer from the Cycle Top.
With regards to Cycle Bottoms, the early bottom of 2 after having peaked at 31.50 doesn’t get captured by the indicator. That is the only cycle bottom that escapes the Pulse DPO when the bottom threshold is set at a value of 5. In that event, the oscillator low reached 6.95.
Bitcoin Adoption Spreading: From 257 to 73k
This chart is in logarithmic mode in order to properly display various exponential cycles. Pulse DPO is properly signaling all the major highs from 17-Dec-2017 at 19k, to the next one on 14-Apr-2021 at 64k and the most recent top from 9-Nov-2021 at 68k.
During the massive run of 2017, the OB condition still stayed triggered for a few weeks on each swing top. But on the next cycles it started to signal only for a few days before each swing top actually happened. The OB condition during the last cycle top triggered only for 3 days. Therefore the signal grows in focus as the market matures.
At the time of publishing this indicator, Bitcoin printed a new All Time High (ATH) on 13-Mar-2024 at 73k. That run didn’t trigger the OB condition. Therefore, if the indicator is correct the Bitcoin market still has some way to grow during the next months.
With regards to Cycle Bottoms, the bottom of 3k after having peaked at19k got captured within the wide OS zone. The bottom of 15k after having peaked at 68k got captured too within the OS accumulation area.
Gold
Pulse DPO behaves surprisingly well on a long standing market such as Gold. Moving back to the 197x years it’s been signaling most Cycle Tops and Bottoms with precision. During the last cycle, it shows topping at 2k and bottoming at 1.6k.
The current price action is signaling OB condition in the range of 2.5k to 2.7k. Looking at past cycles, it tends to trigger on and off at multiple swing tops until reaching the final cycle top. Therefore this might indicate the first wave within a potential gold run.
Oil
On the Oil market, we can see that most of the cycle tops and bottoms since the 80s got signaled. The only exception being the low from 2020 which didn’t trigger.
EURUSD
On Forex markets the Pulse DPO also behaves as expected. Looking back at EURUSD we can see the marketing triggering OB and OS conditions during major cycle tops and bottoms from recent times until the 80s.
S&P 500
On the S&P 500 the Pulse DPO catched the lows from 2016 and 2020. Looking at present price action, the recent ATH didn’t trigger the OB condition. Therefore, the indicator is allowing room for another leg up during the next months.
Amazon
On the Amazon chart the Pulse DPO is mirroring pretty accurately the major swings. Scrolling back to the early 2000s, this chart resembles early exponential swings in the crypto space.
Tesla
Moving onto a younger tech stock, Pulse DPO captures pretty accurately the major tops and bottoms. The chart is shown in logarithmic scale to better display the magnitude of the moves.
█ SETTINGS
This indicator is ideal for identifying major market turning points while filtering out short-term noise. You are free to adjust the parameters to align with your preferred trading style.
Parameters : This section allows you to customize any of the Parameters that shape the Oscillator.
Oscillator Length: Defines the period for calculating the Oscillator.
Offset: Shifts the oscillator calculation by a certain number of periods, which is typically half the Oscillator Length.
Lookback Period: Specifies how many bars to look back to find tops and bottoms for normalization.
Smoothing Length: Determines the length of the moving average used to smooth the oscillator.
Thresholds : This section allows you to customize the Thresholds that trigger the OB and OS conditions.
Top: Defines the value of the Top Threshold.
Bottom: Defines the value of the Bottom Threshold.
Savitzky-Golay Z-Score [BackQuant]Savitzky-Golay Z-Score
The Savitzky-Golay Z-Score is a powerful trading indicator that combines the precision of the Savitzky-Golay filter with the statistical strength of the Z-Score. This advanced indicator is designed to detect trend shifts, identify overbought or oversold conditions, and highlight potential divergences in the market, providing traders with a unique edge in detecting momentum changes and trend reversals.
Core Concept: Savitzky-Golay Filter
The Savitzky-Golay filter is a widely-used smoothing technique that preserves important signal features such as peak detection while filtering out noise. In this indicator, the filter is applied to price data (default set to HLC3) to smooth out volatility and produce a cleaner trend line. By specifying the window size and polynomial degree, traders can fine-tune the degree of smoothing to match their preferred trading style or market conditions.
Z-Score: Measuring Deviation
The Z-Score is a statistical measure that indicates how far the current price is from its mean in terms of standard deviations. In trading, the Z-Score can be used to identify extreme price moves that are likely to revert or continue trending. A positive Z-Score means the price is above the mean, while a negative Z-Score indicates the price is below the mean.
This script calculates the Z-Score based on the Savitzky-Golay filtered price, enabling traders to detect moments when the price is diverging from its typical range and may present an opportunity for a trade.
Long and Short Conditions
The Savitzky-Golay Z-Score generates clear long and short signals based on the Z-Score value:
Long Signals : When the Z-Score is positive, indicating the price is above its smoothed mean, a long signal is generated. The color of the bars turns green, signaling upward momentum.
Short Signals : When the Z-Score is negative, indicating the price is below its smoothed mean, a short signal is generated. The bars turn red, signaling downward momentum.
These signals allow traders to follow the prevailing trend with confidence, using statistical backing to avoid false signals from short-term volatility.
Standard Deviation Levels and Extreme Levels
This indicator includes several features to help visualize overbought and oversold conditions:
Standard Deviation Levels: The script plots horizontal lines at +1, +2, -1, and -2 standard deviations. These levels provide a reference for how far the current price is from the mean, allowing traders to quickly identify when the price is moving into extreme territory.
Extreme Levels: Additional extreme levels at +3 and +4 (and their negative counterparts) are plotted to highlight areas where the price is highly likely to revert. These extreme levels provide important insight into market conditions that are far outside the norm, signaling caution or potential reversal zones.
The indicator also adapts the color shading of these extreme zones based on the Z-Score’s strength. For example, the area between +3 and +4 is shaded with a stronger color when the Z-Score approaches these values, giving a visual representation of market pressure.
Divergences: Detecting Hidden and Regular Signals
A key feature of the Savitzky-Golay Z-Score is its ability to detect bullish and bearish divergences, both regular and hidden:
Regular Bullish Divergence: This occurs when the price makes a lower low while the Z-Score forms a higher low. It signals that bearish momentum is weakening, and a bullish reversal could be near.
Hidden Bullish Divergence: This divergence occurs when the price makes a higher low while the Z-Score forms a lower low. It signals that bullish momentum may continue after a temporary pullback.
Regular Bearish Divergence: This occurs when the price makes a higher high while the Z-Score forms a lower high, signaling that bullish momentum is weakening and a bearish reversal may be near.
Hidden Bearish Divergence: This divergence occurs when the price makes a lower high while the Z-Score forms a higher high, indicating that bearish momentum may continue after a temporary rally.
These divergences are plotted directly on the chart, making it easier for traders to spot when the price and momentum are out of sync and when a potential reversal may occur.
Customization and Visualization
The Savitzky-Golay Z-Score offers a range of customization options to fit different trading styles:
Window Size and Polynomial Degree: Adjust the window size and polynomial degree of the Savitzky-Golay filter to control how much smoothing is applied to the price data.
Z-Score Lookback Period: Set the lookback period for calculating the Z-Score, allowing traders to fine-tune the sensitivity to short-term or long-term price movements.
Display Options: Choose whether to display standard deviation levels, extreme levels, and divergence labels on the chart.
Bar Color: Color the price bars based on trend direction, with green for bullish trends and red for bearish trends, allowing traders to easily visualize the current momentum.
Divergences: Enable or disable divergence detection, and adjust the lookback periods for pivots used to detect regular and hidden divergences.
Alerts and Automation
To ensure you never miss an important signal, the indicator includes built-in alert conditions for the following events:
Positive Z-Score (Long Signal): Triggers an alert when the Z-Score crosses above zero, indicating a potential buying opportunity.
Negative Z-Score (Short Signal): Triggers an alert when the Z-Score crosses below zero, signaling a potential short opportunity.
Shifting Momentum: Alerts when the Z-Score is shifting up or down, providing early warning of changing market conditions.
These alerts can be configured to notify you via email, SMS, or app notification, allowing you to stay on top of the market without having to constantly monitor the chart.
Trading Applications
The Savitzky-Golay Z-Score is a versatile tool that can be applied across multiple trading strategies:
Trend Following: By smoothing the price and calculating the Z-Score, this indicator helps traders follow the prevailing trend while avoiding false signals from short-term volatility.
Mean Reversion: The Z-Score highlights moments when the price is far from its mean, helping traders identify overbought or oversold conditions and capitalize on potential reversals.
Divergence Trading: Regular and hidden divergences between the Z-Score and price provide early warning of trend reversals, allowing traders to enter trades at opportune moments.
Final Thoughts
The Savitzky-Golay Z-Score is an advanced statistical tool designed to provide a clearer view of market trends and momentum. By applying the Savitzky-Golay filter and Z-Score analysis, this indicator reduces noise and highlights key areas where the market may reverse or accelerate, giving traders a significant edge in understanding price behavior.
Whether you’re a trend follower or a reversal trader, this indicator offers the flexibility and insights you need to navigate complex markets with confidence.
Approximate Spectral Entropy-Based Market Momentum (SEMM)Overview
The Approximate Spectral Entropy-Based Market Momentum (SEMM) indicator combines the concepts of spectral entropy and traditional momentum to provide traders with insights into both the strength and the complexity of market movements. By measuring the randomness or predictability of price changes, SEMM helps traders understand whether the market is in a trending or consolidating state and how strong that trend or consolidation might be.
Key Features
Entropy Measurement: Calculates the approximate spectral entropy of price movements to quantify market randomness.
Momentum Analysis: Integrates entropy with rate-of-change (ROC) to highlight periods of strong or weak momentum.
Dynamic Market Insight: Provides a dual perspective on market behavior—both the trend strength and the underlying complexity.
Customizable Parameters: Adjustable window length for entropy calculation, allowing for fine-tuning to suit different market conditions.
Concepts Underlying the Calculations
The indicator utilizes Shannon entropy, a concept from information theory, to approximate the spectral entropy of price returns. Spectral entropy traditionally involves a Fourier Transform to analyze the frequency components of a signal, but due to Pine Script limitations, this indicator uses a simplified approach. It calculates log returns over a rolling window, normalizes them, and then computes the Shannon entropy. This entropy value represents the level of disorder or complexity in the market, which is then multiplied by traditional momentum measures like the rate of change (ROC).
How It Works
Price Returns Calculation: The indicator first computes the log returns of price data over a specified window length.
Entropy Calculation: These log returns are normalized and used to calculate the Shannon entropy, representing market complexity.
Momentum Integration: The calculated entropy is then multiplied by the rate of change (ROC) of prices to generate the SEMM value.
Signal Generation: High SEMM values indicate strong momentum with higher randomness, while low SEMM values indicate lower momentum with more predictable trends.
How Traders Can Use It
Trend Identification: Use SEMM to identify strong trends or potential trend reversals. Low entropy values can indicate a trending market, whereas high entropy suggests choppy or consolidating conditions.
Market State Analysis: Combine SEMM with other indicators or chart patterns to confirm the market's state—whether it's trending, ranging, or transitioning between states.
Risk Management: Consider high SEMM values as a signal to be cautious, as they suggest increased market unpredictability.
Example Usage Instructions
Add the Indicator: Apply the "Approximate Spectral Entropy-Based Market Momentum (SEMM)" indicator to your chart.
Adjust Parameters: Modify the length parameter to suit your trading timeframe. Shorter lengths are more responsive, while longer lengths smooth out the signal.
Analyze the Output: Observe the blue line for entropy and the red line for SEMM. Look for divergences or confirmations with price action to guide your trades.
Combine with Other Tools: Use SEMM alongside moving averages, support/resistance levels, or other indicators to build a comprehensive trading strategy.
Weekday Signal [QuantAlchemy]### Weekday Signal Indicator
#### Overview
The "Weekday Signal " indicator offers a method for triggering entry and exit signals based on specific weekdays and defined trading sessions. This allows traders to tailor their strategies to time slots and days, ensuring strategic execution and optimal trading periods.
Additionally, this indicator exposes signals for external use in other scripts, enabling integration with additional trading strategies or indicators, thereby enhancing its utility and flexibility for trading systems.
#### Definitions
- **Weekday Signal**: An indicator designed to trigger entry and exit signals based on specific weekdays within defined trading sessions.
- **Time Zone**: The local or preferred time zone setting to match market hours across global exchanges.
- **Trading Session**: The specific hours within a day when the trading signals are active.
#### Plots
- **Enter Signal**: Plots a signal when the conditions for entering a trade are met.
- **Exit Signal**: Plots a signal when the conditions for exiting a trade are met.
#### Properties
- **Flexible Time Zones**: Allows users to set their preferred time zone to align with global market hours.
- **Customizable Entry and Exit Days**: Users can select specific weekdays for entry and exit signals.
- **Defined Trading Sessions**: Users can define trading session hours to restrict signals to optimal market times.
- **Visual Indicators**: Provides clear visual plots and background colors on the chart to indicate when entry and exit criteria are met.
- **Dual Group Configuration**: Separate controls for entry and exit setups, offering flexibility in managing trading signals.
#### How to Read
1. **Green Background**: Indicates a potential entry signal.
2. **Red Background**: Indicates a potential exit signal.
3. **Status Line and Data Window**: Shows a value of 1 when an entry or exit condition is met and 0 otherwise.
#### Proposed Interpretations
- **Entry Signals**: When the background turns green and the status line/data window shows a value of 1, it indicates a potential time to enter a trade based on the selected weekday and session.
- **Exit Signals**: When the background turns red and the status line/data window shows a value of 1, it indicates a potential time to exit a trade based on the selected weekday and session.
#### Essential Knowledge
- **Weekdays and Trading Sessions**: Understanding the significance of specific trading days and sessions can help in optimizing trade timings.
- **Time Zones**: Correctly setting the time zone ensures alignment with market hours and accurate signal generation.
#### Deeper Concepts
- **Signal Filtering**: The script uses the `time_filter` library to determine if the current time falls within the defined entry or exit periods.
#### Typical Use Cases
- **Intraday Trading**: Traders who want to restrict their trades to specific weekdays and trading sessions.
- **Strategy Integration**: Users can integrate the signals from this indicator into broader trading strategies or other Pine Scripts using the signals as an external reference to an input.
#### Limitations
- **Time Zone Settings**: Incorrect time zone settings can lead to misaligned signals.
- **Trading Sessions**: Signals are limited to the defined trading session hours, which may not cover all market conditions.
#### Final Thoughts
The "Weekday Signal " indicator is a tool for traders looking to refine their entry and exit points based on specific days and sessions. By leveraging customizable time zones and trading sessions, traders can refine their strategic execution.
#### Disclaimer
This indicator is for educational purposes only and should not be construed as financial advice. Trading involves risk, and you should consult with a qualified financial advisor before making any trading decisions.
Nadaraya-Watson Probability [Yosiet]The script calculates and displays probability bands around price movements, offering insights into potential market trends.
Setting Up the Script
Window Size: Determines the length of the window for the Nadaraya-Watson estimation. A larger window smooths the data more but might lag current market conditions.
Bandwidth: Controls the bandwidth for the kernel regression, affecting the smoothness of the probability bands.
Reading the Data Table
The script dynamically updates a table positioned at the bottom right of your chart, providing real-time insights into market probabilities. Here's how to interpret the table:
Table Columns: The table is organized into three columns:
Up: Indicates the probability or relative change percentage for the upper band.
Down: Indicates the probability or relative change percentage for the lower band.
Table Rows: There are two main rows of interest:
P%: Shows the price change percentage difference between the bands and the closing price. A positive value in the "Up" column suggests the upper band is above the current close, indicating potential upward momentum. Conversely, a negative value in the "Down" column suggests downward momentum.
R%: Displays the relative inner change percentage difference between the bands, offering a measure of the market's volatility or stability within the bands.
Utilizing the Insights
Market Trends: A widening gap between the "Up" and "Down" percentages in the "P%" row might indicate increasing market volatility. Traders can use this information to adjust their risk management strategies accordingly.
Entry and Exit Points: The "R%" row provides insights into the relative position of the current price within the probability bands. Traders might consider positions closer to the lower band as potential entry points and positions near the upper band as exit points or take-profit levels.
Conclusion
The Nadaraya-Watson Probability script offers a sophisticated tool for traders looking to incorporate statistical analysis into their trading strategy. By understanding and utilizing the data presented in the script's table, traders can gain insights into market trends and volatility, aiding in decision-making processes. Remember, no indicator is foolproof; always consider multiple data sources and analyses when making trading decisions.
Market Structure Volume Distribution [LuxAlgo]The Market Structure Volume Distribution tool allows traders to identify the strength behind breaks of market structure at defined price ranges to measure de correlation of forces between bulls and bears visually and easily.
🔶 USAGE
This tool has three main features: market structure highlighting, grid levels, and volume profile. Each feature is covered more in depth below:
🔹 Market Structure
The basic unit of market structure is a swing point, the period of the swing point is user-defined, so traders can identify longer-term market structures. Price breaking a prior swing point will confirm the occurrence of a market structure.
The tool will plot a line after a market structure is confirmed, by default the lines on bullish MS will be green (indicative of an uptrend), and red in case of bearish MS (indicative of a downtrend).
🔹 Grid Levels
The Grid visually divides the price range contained inside the tool execution window, into equal size rows, the number of rows is user-defined so users can divide the full price range up to 100 rows.
The main objective of this feature is to help identify the execution window and the limits of each row in the volume profile so traders can know in a simple look what BoMS belongs to each row.
There is however another use for the grid, by dividing the range into equal-sized parts, this feature provides automatic support and resistance levels as good as any other.
Grid provides a visual help to know what our execution window is and to associate MS with their rows in the profile. It can provide S/R levels too.
🔹 Volume Profile
The volume profile feature shows in a visually easy way the volume behind each MS aggregated by rows and divided into buy and sell volume to spot the differences in a simple look.
This tool allows users to spot the liquidity associated with the event of a market structure in a specific price range, allowing users to know which price areas where associated with the most trading activity during the occurrence of a market structutre.
🔶 SETTINGS
🔹 Data Gathering
Execute on all visible range: Activate this to use all visible bars on the calculations. This disables the use of the next parameter "Execute on the last N bars". Default false.
Execute on the last N bars: Use last N bars on the calculations. To use this parameter "Execute on all visible range" must be disabled. Values from 20 to 5000, default 500.
Pivot Length: How many bars will be used to confirm a pivot. The bigger this parameter is the fewer breaks of structure will detect. Values from 1, default 2
🔹 Profile
Profile Rows: Number of rows in the volume profile. Values from 2 to 100, default 10.
Profile Width: Maximum width of the volume profile. Values from 25 to 500, default 200.
Profile Mode: How the volume will be displayed on each row. "TOTAL VOLUME" will aggregate buy & sell volume per row, "BUY&SELL VOLUME" will separate the buy volume from the sell volume on each row. Default BUY&SELL VOLUME.
🔹 Style
Buy Color: This is the color for the buy volume on the profile when the "BUY&SELL VOLUME" mode is activated. Default green.
Sell Color: This is the color for the sell volume on the profile when the "BUY&SELL VOLUME" mode is activated. Default red.
Show dotted grid levels: Show dotted inner grid levels. Default true.
Alert on Candle CloseAlert on Candle Close is a simple indicator allowing you to set alerts when a candlestick closes.
Instructions for use
From the chart window, click on "Indicators" and search for "Alert on Candle Close".
Click on "Alert on Candle Close" to add the indicator to your chart. Click on the star icon to add it to your favourites to easily access later.
Set your chart timeframe to the timeframe you wish to alert on. For example, to create an alert when a 4h candlestick closes, set your chart to the "4h" timeframe.
Hover over the "Alert on Candle Close" indicator which has been added to your chart and click the ellipsis "..." icon, then click "Add alert on Alert on Candle Close" or use the keyboard shortcut "Alt+A" from the chart.
In the alert pop-up window, make sure "Condition" is set to "Alert on Candle Close" and "Trigger" is set to "Once Per Bar".
Optionally, you can set a custom expiry for the alert, give the alert a name and customise the alert message. You can configure notification settings from the "Notifications" tab.
Click "Create" and your alert is set up!
Each alert is tied to the timeframe and chart it was created on, so you can change the timeframe or asset and create more alerts by repeating the above process.
Note : this indicator is only designed to work with time-based chart types, such as Bars, Candles or Heikin Ashi. It will not work for non-time charts such as Renko.
FAQs
Why do my alerts sometimes not fire as soon as the candle closes?
This is a limitation with Pine Script's execution model. Indicators are calculated whenever a price or volume change occurs i.e. when a new trade happens. For illiquid or slow moving markets, there may be some time between when a candle closes and the next trade, leading to a delay in the alert triggering. The alert will trigger on the next tick of data on the chart.
Why can't I create more alerts?
TradingView has a limit on the number of active technical alerts you can have based on your membership tier. To configure more alerts, consider upgrading your TradingView plan to a higher tier. See a comparison of TradingView plans at www.tradingview.com
My alert only fired once, how can I get it to keep working?
When configuring the alert in the alert pop-up window, make sure you set "Trigger" to "Once Per Bar" and "Expiration" to "Open-ended alert".
Machine Learning Regression Trend [LuxAlgo]The Machine Learning Regression Trend tool uses random sample consensus (RANSAC) to fit and extrapolate a linear model by discarding potential outliers, resulting in a more robust fit.
🔶 USAGE
The proposed tool can be used like a regular linear regression, providing support/resistance as well as forecasting an estimated underlying trend.
Using RANSAC allows filtering out outliers from the input data of our final fit, by outliers we are referring to values deviating from the underlying trend whose influence on a fitted model is undesired. For financial prices and under the assumptions of segmented linear trends, these outliers can be caused by volatile moves and/or periodic variations within an underlying trend.
Adjusting the "Allowed Error" numerical setting will determine how sensitive the model is to outliers, with higher values returning a more sensitive model. The blue margin displayed shows the allowed error area.
The number of outliers in the calculation window (represented by red dots) can also be indicative of the amount of noise added to an underlying linear trend in the price, with more outliers suggesting more noise.
Compared to a regular linear regression which does not discriminate against any point in the calculation window, we see that the model using RANSAC is more conservative, giving more importance to detecting a higher number of inliners.
🔶 DETAILS
RANSAC is a general approach to fitting more robust models in the presence of outliers in a dataset and as such does not limit itself to a linear regression model.
This iterative approach can be summarized as follow for the case of our script:
Step 1: Obtain a subset of our dataset by randomly selecting 2 unique samples
Step 2: Fit a linear regression to our subset
Step 3: Get the error between the value within our dataset and the fitted model at time t , if the absolute error is lower than our tolerance threshold then that value is an inlier
Step 4: If the amount of detected inliers is greater than a user-set amount save the model
Repeat steps 1 to 4 until the set number of iterations is reached and use the model that maximizes the number of inliers
🔶 SETTINGS
Length: Calculation window of the linear regression.
Width: Linear regression channel width.
Source: Input data for the linear regression calculation.
🔹 RANSAC
Minimum Inliers: Minimum number of inliers required to return an appropriate model.
Allowed Error: Determine the tolerance threshold used to detect potential inliers. "Auto" will automatically determine the tolerance threshold and will allow the user to multiply it through the numerical input setting at the side. "Fixed" will use the user-set value as the tolerance threshold.
Maximum Iterations Steps: Maximum number of allowed iterations.
Previous Day High Low Strategy only for LongWelcome to the "Previous Day High Low Strategy only for Long"!.
This strategy aims to identify potential long trading opportunities based on the previous day's high and low prices, along with certain market strength conditions.
Key Features:
Entry Conditions: The strategy triggers a long position when the current day's closing price crosses above the previous day's high or low.
Market Strength Filter: The strategy incorporates a market strength filter using the Average Directional Index (ADX). It only takes long positions when the ADX value is above a specific threshold and when there is a predominance of upward movement.
Trade Timing: The strategy operates within a specified trade window, starting at 09:30 and ending at 15:10. Positions are closed at 15:15 if still active.
Risk Management: The strategy employs dynamic stop-loss and profit-taking levels based on a user-defined Max Profit value. It has three profit targets (T1, T2, T3) and a stop-loss level to manage risk effectively.
Rules:
Ensure that the strategy idea is clearly understandable. Provide an easy-to-read title and a thoughtful description explaining the reasoning behind the strategy.
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Publish in the same language as the TradingView subdomain you're on, except for script titles, which must be in English.
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Be respectful, kind, and constructive when engaging with others.
Zero tolerance for contentious political discourse, defamatory, threatening, or discriminatory remarks.
Avoid sharing harmful, misleading, or inappropriate content.
Respect the moderators' work and address complaints privately.
Use only your original account and avoid creating duplicate or fake accounts.
Do not attempt to manipulate the reputation system or engage in like-for-like schemes.
Explanation of how the strategy works
1. Previous Day's High and Low (HH, LL):
In this strategy, we start by obtaining the high and low prices of the previous day (not the current day) using the request.security function. This function allows us to access historical data for a specific time frame. The high and low prices are stored in the variables HH and LL, respectively.
2. Entry Conditions:
The strategy uses two conditions to trigger a long position:
Condition 1 (Long Condition 1): If the closing price of the current day crosses above the previous day's high (HH), it generates a long signal. This is achieved using the ta.crossover function, which detects when a crossover occurs.
Condition 2 (Long Condition 2): Similarly, if the closing price of the current day crosses above the previous day's low (LL), it also generates a long signal.
Combined Condition: To take long positions, the strategy combines both long conditions using the logical OR operator (or). This means that if either of the two conditions is met, a long position will be initiated.
3. Market Strength Filter:
The strategy also includes a filter based on the Average Directional Index (ADX) to gauge the market's strength before taking long positions. The ADX measures the strength of a trend in the market. The higher the ADX value, the stronger the trend.
Calculation of ADX: The ADX is calculated using the adx function, which takes two parameters: LWdilength (DMI Length) and LWadxlength (ADX period).
Strength Condition (strength_up): The strategy requires that the ADX value should be above a threshold (11 in this case) and that there is a predominance of upward movement (up > down) before initiating a long position. The LWADX value is multiplied by 2.5 and compared to the highest value of LWADX from the last 4 periods using ta.highest(LWADX , 4). If these conditions are met, the variable strength_up is set to true.
Combined Condition: The strength_up condition is then combined with the long conditions using the logical AND operator (and). This means that the strategy will only take a long position if both the long conditions and the market strength condition are met.
4. Trade Timing:
The strategy sets a specific trade window between 09:30 and 15:10. It will only execute trades within this time frame (TradeTime).
5. Risk Management:
The strategy implements dynamic stop-loss (SL) and profit-taking levels (T1, T2, T3) based on a user-defined Max Profit value. The stop-loss is set as a percentage of the Max Profit value. As the position moves in favor of the trader, the profit targets are adjusted accordingly.
6. Position Management:
The strategy uses the strategy.entry function to enter long positions based on the combined entry conditions. Once a position is open, the script uses strategy.exit to define the exit condition when either the profit target or stop-loss level is hit. The strategy.close function is used to close any open position at the end of the trade window (15:15).
7. Plotting:
The strategy uses the plot function to visualize the previous day's high and low prices, as well as the stop-loss (SL) and profit-taking (T1, T2, T3) levels on the chart.
Overall, the "Previous Day High Low Strategy only for Long" aims to identify potential long trading opportunities based on the previous day's price action and market strength conditions. However, as with any trading strategy, it's essential to thoroughly test it and consider risk management before applying it to real-world trading scenarios.
Disclaimer:
The information presented by this strategy is for educational purposes only and should not be considered as investment advice. The strategy is not designed for qualified investors. Always conduct your own research and consult with a financial advisor before making any trading decisions.
Remember, the success of any trading strategy depends on various factors, including market conditions, risk management, and individual trading skills. Past performance is not indicative of future results.
Volume Profile Matrix [LuxAlgo]The Volume Profile Matrix indicator extends from regular volume profiles by also considering calculation intervals within the calculation window rather than only dividing the calculation window in rows.
Note that this indicator is subject to repainting & back-painting, however, treating the indicator as a tool for identifying frequent points of interest can still be very useful.
🔶 SETTINGS
Lookback: Number of most recent bars used to calculate the indicator.
Columns: Number of columns (intervals) used to calculate the volume profile matrix.
Rows: Number of rows (intervals) used to calculate the volume profile matrix.
🔶 USAGE
The Volume Profile Matrix indicator can be used to obtain more information regarding liquidity on specific time intervals. Instead of simply dividing the calculation window into equidistant rows, the calculation is done through a grid.
Grid cells with trading activity occurring inside them are colored. More activity is highlighted through a gradient and by default, cells with a color that are closer to red indicate that more trading activity took place within that cell. The cell with the highest amount of trading activity is always highlighted in yellow.
Each interval (column) includes a point of control which highlights an estimate of the price level with the highest traded volume on that interval. The level with the highest traded volume of the overall grid is extended to the most recent bar.
Smoothing R-Squared ComparisonIntroduction
Heyo guys, here I made a comparison between my favorised smoothing algorithms.
I chose the R-Squared value as rating factor to accomplish the comparison.
The indicator is non-repainting.
Description
In technical analysis, traders often use moving averages to smooth out the noise in price data and identify trends. While moving averages are a useful tool, they can also obscure important information about the underlying relationship between the price and the smoothed price.
One way to evaluate this relationship is by calculating the R-squared value, which represents the proportion of the variance in the price that can be explained by the smoothed price in a linear regression model.
This PineScript code implements a smoothing R-squared comparison indicator.
It provides a comparison of different smoothing techniques such as Kalman filter, T3, JMA, EMA, SMA, Super Smoother and some special combinations of them.
The Kalman filter is a mathematical algorithm that uses a series of measurements observed over time, containing statistical noise and other inaccuracies, and produces estimates of unknown variables that tend to be more accurate than those based on a single measurement.
The input parameters for the Kalman filter include the process noise covariance and the measurement noise covariance, which help to adjust the sensitivity of the filter to changes in the input data.
The T3 smoothing technique is a popular method used in technical analysis to remove noise from a signal.
The input parameters for the T3 smoothing method include the length of the window used for smoothing, the type of smoothing used (Normal or New), and the smoothing factor used to adjust the sensitivity to changes in the input data.
The JMA smoothing technique is another popular method used in technical analysis to remove noise from a signal.
The input parameters for the JMA smoothing method include the length of the window used for smoothing, the phase used to shift the input data before applying the smoothing algorithm, and the power used to adjust the sensitivity of the JMA to changes in the input data.
The EMA and SMA techniques are also popular methods used in technical analysis to remove noise from a signal.
The input parameters for the EMA and SMA techniques include the length of the window used for smoothing.
The indicator displays a comparison of the R-squared values for each smoothing technique, which provides an indication of how well the technique is fitting the data.
Higher R-squared values indicate a better fit. By adjusting the input parameters for each smoothing technique, the user can compare the effectiveness of different techniques in removing noise from the input data.
Usage
You can use it to find the best fitting smoothing method for the timeframe you usually use.
Just apply it on your preferred timeframe and look for the highlighted table cell.
Conclusion
It seems like the T3 works best on timeframes under 4H.
There's where I am active, so I will use this one more in the future.
Thank you for checking this out. Enjoy your day and leave me a like or comment. 🧙♂️
---
Credits to:
▪@loxx – T3
▪@balipour – Super Smoother
▪ChatGPT – Wrote 80 % of this article and helped with the research
Rolling HTF Liquidity Levels [CHE]█ OVERVIEW
This indicator displays a Rolling HTF Liquidity Levels . Contrary to HTF Liquidity Levels indicators which use a fix time segment, Rolling HTF Liquidity Levels calculates using a moving window defined by a time period (not a simple number of bars), so it shows better results.
This indicator is inspired by
The indicator introduces a new representation of the previous rolling time frame highs & lows (DWM HL) with a focus on untapped levels.
█ CONCEPTS
Untapped Levels
It is popularly known that the liquidity is located behind swing points or beyond higher time frames highs/lows.
Rolling HTF Liquidity Levels uses a moving window, it does not exhibit the static of the HTF Liquidity Levels plots.
█ HOW TO USE IT
Load the indicator on an active chart (see the Help Center if you don't know how).
Time period
By default, the script uses an auto-stepping mechanism to adjust the time period of its moving window to the chart's timeframe. The following table shows chart timeframes and the corresponding time period used by the script. When the chart's timeframe is less than or equal to the timeframe in the first column, the second column's time period is used to calculate the Rolling HTF Liquidity Levels:
Chart Time
timeframe period
1min 🠆 1H
5min 🠆 4H
1H 🠆 1D
4H 🠆 3D
12H 🠆 1W
1D 🠆 1M
1W 🠆 3M
By default, the time period currently used is displayed in the lower-right corner of the chart. The script's inputs allow you to hide the display or change its size and location.
This indicator should make trading easier and improve analysis. Nothing is worse than indicators that give confusingly different signals.
I hope you enjoy my new ideas
best regards
Chervolino
z_score_bgd
Z-score indicator for volatile currency pairs, showing STRONG BUY, BUY, SELL, STRONG SELL zones by shading the chart background.
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Background
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Based on mean reversion, a theory that after a swing in price the price will tend back to the mean. This offers some ability to predict future trends.
The formula for calculating a z-score is is z = (x-μ)/σ, where x is the pair price, μ is the mean for a population, and σ is the population standard deviation.
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Set up
---------------------------------
The user can define their own value for the "window" or population, which is the number of preceding days to evaluate. This value will affect the frequency and magnitude of trades, with higher "window" values reducing the frequency of reversions but increasing their magnitude.
Where the value for "window" is left at 99, the default values below will be applied in the background. Otherwise the user's selection will be in effect.
atombtc 18
avaxbtc 21
ethbtc 18
ftmbtc 11
maticbtc 11
solbtc 11
soleth 16
The default values above are intended for the daily time-frame.
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Interpreting the indicator
---------------------------------
Dark green -> large deviation below mean price (strong buy)
Green -> moderate deviation below mean price (buy)
Red -> moderate deviation below mean price (sell)
Dark red -> large deviation below mean price (strong sell)
Z-score is an imperfect indicator, as with all indiciators and trading decisions must be confirmed by multiple indicators and consider other factors.
CommonFiltersLibrary "CommonFilters"
Collection of some common Filters and Moving Averages. This collection is not encyclopaedic, but to declutter my other scripts. Suggestions are welcome, though. Many filters here are based on the work of John F. Ehlers
sma(src, len) Simple Moving Average
Parameters:
src : Series to use
len : Filtering length
Returns: Filtered series
ema(src, len) Exponential Moving Average
Parameters:
src : Series to use
len : Filtering length
Returns: Filtered series
rma(src, len) Wilder's Smoothing (Running Moving Average)
Parameters:
src : Series to use
len : Filtering length
Returns: Filtered series
hma(src, len) Hull Moving Average
Parameters:
src : Series to use
len : Filtering length
Returns: Filtered series
vwma(src, len) Volume Weighted Moving Average
Parameters:
src : Series to use
len : Filtering length
Returns: Filtered series
hp2(src) Simple denoiser
Parameters:
src : Series to use
Returns: Filtered series
fir2(src) Zero at 2 bar cycle period by John F. Ehlers
Parameters:
src : Series to use
Returns: Filtered series
fir3(src) Zero at 3 bar cycle period by John F. Ehlers
Parameters:
src : Series to use
Returns: Filtered series
fir23(src) Zero at 2 bar and 3 bar cycle periods by John F. Ehlers
Parameters:
src : Series to use
Returns: Filtered series
fir234(src) Zero at 2, 3 and 4 bar cycle periods by John F. Ehlers
Parameters:
src : Series to use
Returns: Filtered series
hp(src, len) High Pass Filter for cyclic components shorter than langth. Part of Roofing Filter by John F. Ehlers
Parameters:
src : Series to use
len : Filtering length
Returns: Filtered series
supers2(src, len) 2-pole Super Smoother by John F. Ehlers
Parameters:
src : Series to use
len : Filtering length
Returns: Filtered series
filt11(src, len) Filt11 is a variant of 2-pole Super Smoother with error averaging for zero-lag response by John F. Ehlers
Parameters:
src : Series to use
len : Filtering length
Returns: Filtered series
supers3(src, len) 3-pole Super Smoother by John F. Ehlers
Parameters:
src : Series to use
len : Filtering length
Returns: Filtered series
hannFIR(src, len) Hann Window Filter by John F. Ehlers
Parameters:
src : Series to use
len : Filtering length
Returns: Filtered series
hammingFIR(src, len) Hamming Window Filter (inspired by John F. Ehlers). Simplified implementation as Pedestal input parameter cannot be supplied, so I calculate it from the supplied length
Parameters:
src : Series to use
len : Filtering length
Returns: Filtered series
triangleFIR(src, len) Triangle Window Filter by John F. Ehlers
Parameters:
src : Series to use
len : Filtering length
Returns: Filtered series
doPrefilter(type, src) Execute a particular Prefilter from the list
Parameters:
type : Prefilter type to use
src : Series to use
Returns: Filtered series
doMA(type, src, len) Execute a particular MA from the list
Parameters:
type : MA type to use
src : Series to use
len : Filtering length
Returns: Filtered series
VPA - 5.0 This is a upgraded version of the vpa analysis script which basically implements Volume Spread Analysis (aka Volume Price analysis). It has been rechristened as VPA 5.0 to be inline with version released for Amiboker package so that all future upgrades will go hand in hand. All most all featured of the Amibroker version has been incorporated in this version. Some important additions are as follows
1. A status window for the bar and Trend Description added. No need to plot the trend bands or additional trend Indicator any more.
2. The most important upgrade would be the addition of a Alert window which provides description of the VSA signals. It is also a log window which provides up to 10 last signals
(Credits to Quantnomad for this wonderful piece of code. This feature is an adaptation of his public code)
3. Added facility to plot EMAs / PEMAs with changable parameters
4. Added facility to plot VWAP
5. Facility to switch on and Off the VSA signals. Also tool tip provides description of the signals
6. Facility to plot Resistance and Volume Lines (Credits to @margepadu)
Hope this script will be helpful to everyone. Please do provide your feedback and suggestions for improvements
Fast Fourier Transform (FFT) FilterDear friends!
I'm happy to present an implementation of the Fast Fourier Transform (FFT) algorithm. The script uses the FFT procedure to decompose the input time series into its cyclical constituents, in other words, its frequency components , and convert it back to the time domain with modified frequency content, that is, to filter it.
Input Description and Usage
Source and Length :
Indicates where the data comes from and the size of the lookback window used to build the dataset.
Standardize Input Dataset :
If enabled, the dataset is preprocessed by subtracting its mean and normalizing the result by the standard deviation, which is sometimes useful when analyzing seasonalities. This procedure is not recommended when using the FFT filter for smoothing (see below), as it will not preserve the average of the dataset.
Show Frequency-Domain Power Spectrum :
When enabled, the results of Fourier analysis (for the last price bar!) are plotted as a frequency-domain power spectrum , where “power” is a measure of the significance of the component in the dataset. In the spectrum, lower frequencies (longer cycles) are on the right, higher frequencies are on the left. The graph does not display the 0th component, which contains only information about the mean value. Frequency components that are allowed to pass through the filter (see below) are highlighted in magenta .
Dominant Cycles, Rows :
If this option is activated, the periods and relative powers of several dominant cyclical components that is, those that have a higher power, are listed in the table. The number of the component in the power spectrum (N) is shown in the first column. The number of rows in the table is defined by the user.
Show Inverse Fourier Transform (Filtered) :
When enabled, the reconstructed and filtered time-domain dataset (for the last price bar!) is displayed.
Apply FFT Filter in a Moving Window :
When enabled, the FFT filter with the same parameters is applied to each bar. The last data point of the reconstructed and filtered dataset is used to build a new time series. For example, by getting rid of high-frequency noise, the FFT filter can make the data smoother. By removing slowly evolving low-frequency components (including non-periodic constituents), one can reveal and analyze shorter cycles. Since filtering is done in real-time in a moving window (similar to the moving average), the modified data can potentially be used as part of a strategy and be subjected to other technical indicators.
Lowest Allowed N :
Indicates the number of the lowest frequency component used in the reconstructed time series.
Highest Allowed N :
Indicates the number of the highest frequency component used in the reconstructed time series.
Filtering Time Range block:
Specifies the time range over which real-time FFT filtering is applied. The reason for the presence of this block is that the FFT procedure is relatively computationally intensive. Therefore, the script execution may encounter the time limit imposed by TradingView when all historical bars are processed.
As always, I look forward to your feedback!
Also, leave a comment if you'd be interested in the tutorial on how to use this tool and/or in seeing the FFT filter in a strategy.
[blackcat] L2 Ehlers Center of GravityLevel: 2
Background
John F. Ehlers introuced center of gravity (CG) in his "Cybernetic Analysis for Stocks and Futures" chapter 5 on 2004.
Function
The center of gravity (CG) of a physical object is its balance point. For example, if you balance a 12-inch ruler on your finger, the CG will be at its 6-inch point. If you change the weight distribution of the ruler by putting a paper clip on one end, then the balance point (i.e., the CG) shifts toward
the paper clip. Moving from the physical world to the trading world, we can substitute the prices over our window of observation for the units of weight along the ruler. Using this analogy, we see that the CG of the window moves to the right when prices increase sharply. Correspondingly, the CG of the window moves to the left when prices decrease.
The idea of computing the center of gravity of Dr. Ehlers arose from observing how the lags of various finite impulse response (FIR) filters vary according to
the relative amplitude of the filter coefficients. A simple moving average (SMA) is an FIR filter where all the filter coefficients have the same value (usually unity). As a result, the CG of the SMA is exactly in the center of the filter. A weighted moving average (WMA) is an FIR filter where the most recent price is weighted by the length of the filter, the next most recent price is weighted by the length of the filter less 1, and so on. The weighting terms are the filter coefficients. The filter coefficients of a WMA describe the outline of a triangle. It is well known that the CG of a triangle is located at one-third the length of the base of the triangle. In other words, the CG of the WMA has shifted to the right relative to the CG of an SMA of equal length, resulting in less lag. In all FIR filters, the sum of the product of the coefficients and prices must be divided by the sum of the coefficients so that the scale of the original prices is retained.
Key Signal
CG ---> CG fast line
CG (2) ---> CG slow line
Pros and Cons
100% John F. Ehlers definition translation of original work, even variable names are the same. This help readers who would like to use pine to read his book. If you had read his works, then you will be quite familiar with my code style.
Remarks
The 26th script for Blackcat1402 John F. Ehlers Week publication.
Readme
In real life, I am a prolific inventor. I have successfully applied for more than 60 international and regional patents in the past 12 years. But in the past two years or so, I have tried to transfer my creativity to the development of trading strategies. Tradingview is the ideal platform for me. I am selecting and contributing some of the hundreds of scripts to publish in Tradingview community. Welcome everyone to interact with me to discuss these interesting pine scripts.
The scripts posted are categorized into 5 levels according to my efforts or manhours put into these works.
Level 1 : interesting script snippets or distinctive improvement from classic indicators or strategy. Level 1 scripts can usually appear in more complex indicators as a function module or element.
Level 2 : composite indicator/strategy. By selecting or combining several independent or dependent functions or sub indicators in proper way, the composite script exhibits a resonance phenomenon which can filter out noise or fake trading signal to enhance trading confidence level.
Level 3 : comprehensive indicator/strategy. They are simple trading systems based on my strategies. They are commonly containing several or all of entry signal, close signal, stop loss, take profit, re-entry, risk management, and position sizing techniques. Even some interesting fundamental and mass psychological aspects are incorporated.
Level 4 : script snippets or functions that do not disclose source code. Interesting element that can reveal market laws and work as raw material for indicators and strategies. If you find Level 1~2 scripts are helpful, Level 4 is a private version that took me far more efforts to develop.
Level 5 : indicator/strategy that do not disclose source code. private version of Level 3 script with my accumulated script processing skills or a large number of custom functions. I had a private function library built in past two years. Level 5 scripts use many of them to achieve private trading strategy.
Enhanced Instantaneous Cycle Period - Dr. John EhlersThis is my first public release of detector code entitled "Enhanced Instantaneous Cycle Period" for PSv4.0 I built many months ago. Be forewarned, this is not an indicator, this is a detector to be used by ADVANCED developers to build futuristic indicators in Pine. The origins of this script come from a document by Dr. John Ehlers entitled "SIGNAL ANALYSIS CONCEPTS". You may find this using the NSA's reverse search engine "goggles", as I call it. John Ehlers' MESA used this measurement to establish the data window for analysis for MESA Cycle computations. So... does any developer wish to emulate MESA Cycle now??
I decided to take instantaneous cycle period to another level of novel attainability in this public release of source code with the following methods, if you are curious how I ENHANCED it. Firstly I reduced the delay of accurate measurement from bar_index==0 by quite a few bars closer to IPO. Secondarily, I provided a limit of 6 for a minimum instantaneous cycle period. At bar_index==0, it would provide a period of 0 wrecking many algorithms from the start. I also increased the instantaneous cycle period's maximum value to 80 from 50, providing a window of 6-80 for the instantaneous cycle period value window limits. Thirdly, I replaced the internal EMA with another algorithm. It reduces the lag while extracting a floating point number, for algorithms that will accept that, compared to a sluggish ordinary EMA return. You will see the excessive EMA delay with adding plot(ema(ICP,7)) as it was originally designed. Lastly it's in one simple function for reusability in a nice little package comprising of less than 40 lines of code. I hope I explained that adequately enough and gave you the reader a glimpse of the "Power of Pine" combined with ingenuity.
Be forewarned again, that most of Pine's built-in functions will not accept a floating-point number or dynamic integers for the "length" of it's calculation. You will have to emulate the built-in functions by creating Pine based custom functions, and I assure you, this is very possible in many cases, but not all without array support. You may use int(ICP) to extract an integer from the smoothICP return variable, which may be favorable compared to the choppiness/ringing if ICP alone.
This is commonly what my dense intricate code looks like behind the veil. If you are wondering why there is barely any notation, that's because the notation is in the variable naming and this is intended primarily for ADVANCED developers too. It does contain lines of code that explore techniques in Pine that may be applicable in other Pine projects for those learning or wishing to excel with Pine.
Showcased in the chart below is my free to use "Enhanced Schaff Trend Cycle Indicator", having a common appeal to TV users frequently. If you do have any questions or comments regarding this indicator, I will consider your inquiries, thoughts, and ideas presented below in the comments section, when time provides it. As always, "Like" it if you simply just like it with a proper thumbs up, and also return to my scripts list occasionally for additional postings. Have a profitable future everyone!
NOTICE: Copy pasting bandits who may be having nefarious thoughts, DO NOT attempt this, because this may violate Tradingview's terms, conditions and/or house rules. "WE" are always watching the TV community vigilantly for mischievous behaviors and actions that exploit well intended authors for the purpose of increasing brownie points in reputation scores. Hiding behind a "protected" wall may not protect you from investigation and account penalization by TV staff. Be respectful, and don't just throw an ma() in there branding it as "your" gizmo. Fair enough? Alrighty then... I firmly believe in "innovating" future state-of-the-art indicators, and please contact me if you wish to do so.
GLD GC Price ConverterIt’s a tool for traders who want to monitor key price levels in the gold market (GLD and GC) directly on their primary trading chart, without having to switch between different windows.
Initial Balance Wave MapThis indicator visualizes the Initial Balance (IB) range for any session, marking the first hour's high and low. It includes optional midpoints, extensions (e.g. 1.5x IB, 2x IB), and customizable time windows. Additional features allow users to display session open, high, low, close, and VWAP reference points. Designed to support price action and session structure analysis, it adapts to various global futures and FX market opens. All display elements are optional and fully configurable.
This updated indicator builds upon the open-source foundation by @noop-noop with enhancements and user-facing labels tailored for Auction Market Theory, scalping, and structure-based trade setups.
Key updated Featured: Multiple previous day's IB levels carry forward into the current day's chart, as opposed to just the previous day's levels carrying forward to the new IB time.
🙌 Credits:
This script builds upon the excellent open-source work by @noop-noop. Original script available here .
Time Period Highlighter V2This indicator highlights custom time periods on any intraday chart in TradingView, making it easier to visualize your preferred trading sessions.
You can define up to three separate time ranges per day, each with precise start and end times down to the minute (e.g., 08:30 - 12:15, 14:00 - 16:45, and 20:00 - 22:30). The indicator shades the background of your chart during these periods, helping you quickly identify when you're most active or when specific market conditions occur.
Key Features:
Set start and end times (hours and minutes) for up to three trading sessions.
Automatically highlights these periods across any intraday timeframe.
Uses 24-hour time format aligned with your TradingView chart timezone.
Perfect for day traders, scalpers, or anyone needing clear visual cues for their trading windows.
This tool is especially useful for reviewing trading strategies, backtesting, or ensuring you're focusing on high-probability market hours.
Tip: Double-check that your chart timezone matches your desired session times for accurate highlighting.
BK AK-SILENCER🚨 Introducing BK AK-SILENCER — Volume Footprint Warfare, Right on the Price Bars 🚨
This isn’t a traditional indicator.
This is a tactical weapon — engineered to expose institutional behavior directly in the bar data, using volume logic, CVD divergence, and spike detection to pinpoint who’s really in control of the tape.
No panels. No clutter.
Just silent execution — built directly into price itself.
🔥 Why "SILENCER"?
Because real power moves in silence.
Institutions don’t chase — they build positions quietly, in size, beneath the surface.
BK AK-SILENCER gives you a real-time edge by visually revealing their footprints through color-coded bar behavior, divergence signals, and volume spike alerts — all directly on your chart.
🔹 “AK” honors my mentor A.K., whose training forged my trading discipline.
🔹 “SILENCER” represents the institutional mindset — high impact, low visibility. This tool lets you trade like them: without noise, without hesitation, with deadly clarity.
🧠 What Is BK AK-SILENCER?
A bar-level institutional detection tool, purpose-built to:
✅ Color-code bars based on volume aggression and close-location inside range
✅ Detect real-time bullish and bearish divergences between price and volume delta
✅ Tag volume spikes with a $ symbol to expose potential traps or silent position builds
✅ Overlay VWAP for real-time mean-reversion biasing
No extra windows.
No indicators talking over each other.
Just pure volume-logic weaponry embedded into price.
⚙️ What This Weapon Deploys
🔸 Bar Coloring Logic (Volume Footprint)
🟢 Power Buy = Strong close near highs on elevated volume
🟩 Accumulation = Weak close but still heavy volume
🔴 Power Sell = Strong close near lows on heavy selling
🟥 Distribution / Weakness = Low close without commitment
❗ Extreme Volume Spikes marked with $ — using standard deviation to highlight institutional bursts
🔸 CVD Divergence Detection
→ Tracks cumulative volume delta and compares it to price pivot behavior
Bullish Divergence = Price makes lower lows, CVD makes higher lows → hidden accumulation
Bearish Divergence = Price makes higher highs, CVD makes lower highs → hidden distribution
All plotted directly on bars with triangle markers.
🔸 VWAP Overlay (Optional)
→ Anchored VWAP gives immediate context for intraday bias — above VWAP = demand, below = supply
🎯 How to Use BK AK-SILENCER
🔹 Silent Reversal Detection
Bullish divergence + Power Buy bar + VWAP reclaim = sniper entry
Bearish divergence + Power Sell bar + VWAP rejection = trap confirmation
🔹 Volume-Based Entry Triggers
Look for Power Buy + $ spike after a pullback → watch for quiet reversal
Accumulation colors clustering? Institutions are likely loading silently
🔹 Institutional Trap Warnings
$ spike + red distribution bar at highs = time to exit or flip
Weakness bar below VWAP? Don’t chase the long.
🛡️ Why It Matters
✅ Clean — it integrates into price action, no separate panels
✅ Silent — tracks institutions who build without alerts or indicators
✅ Tactical — no fluff, no lag, just real-time behavior recognition
This tool is ideal for:
🔸 Scalpers reading bar-by-bar
🔸 Intraday swing traders using VWAP and structure
🔸 Professionals who need volume behavior decoded in real-time
🔸 Anyone who wants signal without clutter
🙏 Final Thoughts
This tool isn’t just about trading — it’s about tactical awareness.
🔹 Dedicated to my mentor A.K., whose wisdom runs deep in every logic tree.
🔹 Above all, I give thanks to Gd, the source of clarity, courage, and conviction.
Without Him, even the sharpest system is blind.
With Him, we execute with structure, purpose, and divine alignment.
⚡ No noise. No clutter. No delay. Just raw, silent execution.
🔥 BK AK-SILENCER — Bar-Level Volume Footprint Precision 🔥
Gd bless every step you take in this market.
Trade with clarity, move with intention. 🙏
