One Trading Setup for Life ICT [TradingFinder] Sweep Session FVG🔵 Introduction
ICT One Trading Setup for Life is a trading strategy based on liquidity and market structure shifts, utilizing the PM Session Sweep to determine price direction. In this strategy, the market first forms a price range during the PM Session (from 13:30 to 16:00 EST), which includes the highest high (PM Session High) and lowest low (PM Session Low).
In the next session, the price first touches one of these levels to trigger a Liquidity Hunt before confirming its trend by breaking the Change in State of Delivery (CISD) Level. After this confirmation, the price retraces toward a Fair Value Gap (FVG) or Order Block (OB), which serve as the best entry points in alignment with liquidity.
In financial markets, liquidity is the primary driver of price movement, and major market participants such as institutional investors and banks are constantly seeking liquidity at key levels. This process, known as Liquidity Hunt or Liquidity Sweep, occurs when the price reaches an area with a high concentration of orders, absorbs liquidity, and then reverses direction.
In this setup, the PM Session range acts as a trading framework, where its highs and lows function as key liquidity zones that influence the next session’s price movement. After the New York market opens at 9:30 EST, the price initially breaks one of these levels to capture liquidity.
However, for a trend shift to be confirmed, the CISD Level must be broken.
Once the CISD Level is breached, the price retraces toward an FVG or OB, which serve as optimal trade entry points.
Bullish Setup :
Bearish Setup :
🔵 How to Use
In this strategy, the PM Session range is first identified, which includes the highest high (PM Session High) and lowest low (PM Session Low) between 13:30 and 16:00 EST. In the following session, the price touches one of these levels for a Liquidity Hunt, followed by a break of the Change in State of Delivery (CISD) Level. The price then retraces toward a Fair Value Gap (FVG) or Order Block (OB), creating a trading opportunity.
This process can occur in two scenarios : bearish and bullish setups.
🟣 Bullish Setup
In a bullish scenario, the PM Session High and PM Session Low are identified. In the following session, the price first breaks the PM Session Low, absorbing liquidity. This process results in a Fake Breakout to the downside, misleading retail traders into taking short positions.
After the Liquidity Hunt, the CISD Level is broken, confirming a trend reversal. The price then retraces toward an FVG or OB, offering an optimal long entry opportunity.
The initial take-profit target is the PM Session High, but if higher timeframe liquidity levels exist, extended targets can be set.
The stop-loss should be placed below the Fake Breakout low or the first candle of the FVG.
🟣 Bearish Setup
In a bearish scenario, the market first defines its PM Session High and PM Session Low. In the next session, the price initially breaks the PM Session High, triggering a Liquidity Hunt. This movement often causes a Fake Breakout, misleading retail traders into taking incorrect positions.
After absorbing liquidity, the CISD Level breaks, indicating a shift in market structure. The price then retraces toward an FVG or OB, offering the best short entry opportunity.
The initial take-profit target is the PM Session Low, but if additional liquidity exists on higher timeframes, lower targets can be considered.
The stop-loss should be placed above the Fake Breakout high or the first candle of the FVG.
🔵 Setting
CISD Bar Back Check : The Bar Back Check option enables traders to specify the number of past candles checked for identifying the CISD Level, enhancing CISD Level accuracy on the chart.
Order Block Validity : The number of candles that determine the validity of an Order Block.
FVG Validity : The duration for which a Fair Value Gap remains valid.
CISD Level Validity : The duration for which a CISD Level remains valid after being broken.
New York PM Session : Defines the PM Session range from 13:30 to 16:00 EST.
New York AM Session : Defines the AM Session range from 9:30 to 16:00 EST.
Refine Order Block : Enables finer adjustments to Order Block levels for more accurate price responses.
Mitigation Level OB : Allows users to set specific reaction points within an Order Block, including: Proximal: Closest level to the current price. 50% OB: Midpoint of the Order Block. Distal: Farthest level from the current price.
FVG Filter : The Judas Swing indicator includes a filter for Fair Value Gap (FVG), allowing different filtering based on FVG width: FVG Filter Type: Can be set to "Very Aggressive," "Aggressive," "Defensive," or "Very Defensive." Higher defensiveness narrows the FVG width, focusing on narrower gaps.
Mitigation Level FVG : Like the Order Block, you can set price reaction levels for FVG with options such as Proximal, 50% OB, and Distal.
Demand Order Block : Enables or disables bullish Order Block.
Supply Order Block : Enables or disables bearish Order Blocks.
Demand FVG : Enables or disables bullish FVG.
Supply FVG : Enables or disables bearish FVGs.
Show All CISD : Enables or disables the display of all CISD Levels.
Show High CISD : Enables or disables high CISD levels.
Show Low CISD : Enables or disables low CISD levels.
🔵 Conclusion
The ICT One Trading Setup for Life is a liquidity-based strategy that leverages market structure shifts and precise entry points to identify high-probability trade opportunities. By focusing on PM Session High and PM Session Low, this setup first captures liquidity at these levels and then confirms trend shifts with a break of the Change in State of Delivery (CISD) Level.
Entering a trade after a retracement to an FVG or OB allows traders to position themselves at optimal liquidity levels, ensuring high reward-to-risk trades. When used in conjunction with higher timeframe bias, order flow, and liquidity analysis, this strategy can become one of the most effective trading methods within the ICT Concept framework.
Successful execution of this setup requires risk management, patience, and a deep understanding of liquidity dynamics. Traders can enhance their confidence in this strategy by conducting extensive backtesting and analyzing past market data to optimize their approach for different assets.
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ICT Open Range Gap & 1st FVG (fadi)In his 2024 mentorship program, ICT detailed how price action interacts with Open Range Gaps and the initial 1-minute Fair Value Gap following the market open at 9:30 AM.
What is an Open Range Gap?
An Open Range Gap occurs when the market opens at 9:30 AM at a higher or lower level compared to the previous day's close at 4:14 PM, primarily relevant in futures trading. According to ICT, there is a statistical probability of 70% that the price action will close 50% or more of the Open Range Gap within the first 30 minutes of trading (9:30 AM to 10:00 AM).
What is the First 1-Minute Fair Value Gap?
ICT places significant emphasis on the first 1-minute Fair Value Gap (FVG) that forms after the market opens at 9:30 AM. The FVG must occur at 9:31 AM or later to be considered valid. This gap often presents key opportunities for traders, as it represents a temporary imbalance between supply and demand that the market seeks to correct.
Understanding and leveraging these patterns can enhance trading strategies by offering insights into potential price movements shortly after market open.
ICT Open Range Gap & 1st FVG
This indicator is engineered to identify and highlight the Open Range Gaps and the first 1-minute Fair Value Gap. Furthermore, it functions across multiple timeframes, from seconds to hours, catering to various trading preferences. This flexibility is particularly beneficial for traders who favor higher timeframes or wish to observe these patterns' application at broader intervals.
Settings
The Open Range Gap indicator offers flexible display settings. It identifies the quadrants and provides optional color coding to distinguish them. Additionally, it tracks the "fill" level to visualize how far the price action has progressed into the gap, enhancing traders' ability to monitor and analyze price movements effectively. By default, the Open Range Gap will stop extending at 10:00 AM; however, there is an option to continue extending until the end of the trading day.
The 1st Fair Value Gap (FVG) can be viewed on any timeframe the indicator is active on, offering various styling options to match each trader's preferences. While the 1st FVG is particularly relevant to the day it is created, previous 1st FVGs within the same week may provide additional value. This indicator allows traders to extend Monday's 1st FVG, marking the first FVG of the week, or to extend all 1st FVGs throughout the week.
Opening Range Breakout [UkutaLabs]█ OVERVIEW
The Opening Range Breakout is a powerful trading tool that indicates a strong range based on the high and low of the first fifteen or thirty minutes after market open. This range serves as a potential area of Support or Resistance that traders should be aware of during their trading. Because of this, the Opening Range Breakout is a versatile trading tool that can be included in a wide variety of trading strategies.
The aim of this script is to simplify the trading experience of users by automatically identifying and displaying price levels that they should be aware of.
█ USAGE
When the New York Market opens each day, the script will automatically identify and label the opening range in real time. The user can control whether the script measures the first 15 or 30 minutes of each trading day to fit each trader’s trading style.
Because there tends to be a spike in volume during this period, the range that is identified can serve as a powerful indication of overall market strength. Once the price breaks out of this range, it then can be used as an area of support or resistance depending on the direction of the breakout.
█ SETTINGS
Configuration
• Show Labels: Determines whether labels are drawn within the range.
• Display Mode: Determines the number of days the script should load.
Range Settings
• 15 Minute: Determines whether or not the 15 minute range is drawn.
• 15 Minute Color: Determines the color of the 15 minute range and labels.
• 30 Minute: Determines whether or not the 30 minute range is drawn.
• 30 Minute Color: Determines the color of the 30 minute range and labels.
@tk · fractal rsi levels█ OVERVIEW
This script is an indicator that helps traders to identify the RSI Levels for multiple fractals wherever the current timeframe is. This script was based on RSI Levels, 20-30 & 70-80 by abdomi indicator, that calculates the Relative Strenght Index levels based on the asset's price and plots it into the chart, creating a "wave" style indicator. The core feature of this indicator is the fractal rays, so trader can visualize each of the oversold and overbought levels of multiple timeframe on the current timeframe that he is on. The indicator will plots multiple rays after the chart bars. indicating where is the oversold and overbought levels for others fractals.
█ MOTIVATION
Since the RSI Levels, 20-30 & 70-80 by abdomi indicator helps a lot to identify the possible price levels when the asset is oversold or overbought, I saw myself drawing multiple horizontal lines on these levels in lower timeframes so, in an uptrend or downtrend, I can try to get a pullback of these trends when the asset reaches oversold or overboght levels. So, I get the idea to make those lines visible in multiple timeframes so I don't need to draw it myself manually anymore.
█ CONCEPT
The trading concept to use this indicator is the concept to make entries on uptrend or downtrend pullbacks when the asset price reaches oversold or overbought levels. But this strategy don't works alone. It needs to be aligned together with others indicators like Exponential Moving Averages, Chart Patterns, Support and Resistance, and so on... Even more confluences that you have, bigger are your chances to increase the probability for a successful trade. So, don't use this indicator alone. Compose a trading strategy and use it to improve your analysis.
█ CUSTOMIZATION
This indicator allows the trader to customize the following settings:
GENERAL
Text size
Changes the font size of the labels to improve accessibility.
Type: string
Options: `tiny`, `small`, `normal`, `large`.
Default: `small`
RSI LEVELS · SETTINGS
Pre-oversold Level
Changes the RSI Level to calculate the "pre-oversold" price level on the chart.
Type: int
Min: 1
Max: 49
Default: 33
Pre-overbought Level
Changes the RSI Level to calculate the "pre-overbought" price level on the chart.
Type: int
Min: 51
Max: 100
Default: 67
Show "Pre-over" Levels
Enables / Disables the pre-oversold and pre-overbought levels on the chart.
Type: bool
Default: true
FRACTAL RAYS · SETTINGS
Length
Changes the base length for the RSI calculation.
Type: int
Min: 1
Default: 14
Source
Changes the base source for the RSI calculation.
Type: float
Default: close
FRACTAL RAYS · STYLE
Ray Color
Changes the color of all fractal rays and its label.
Type: color
Default: color.rgb(187, 74, 207)
Ray Style
Changes the style of all fractal rays.
Type: string
Options: `line.style_solid`, `line.style_dashed`, `line.style_dotted`
Default: line.style_dotted
Ray Length
Changes the length of all fractal rays.
Type: int
Default: 15
FRACTAL RAYS · OVERSOLD
Oversold Level
Changes the base RSI Level for fractal rays calculation.
Type: int
Min: 1
Default: 30
Oversold Prefix
Customizes the fractal ray label with a prefix text.
Type: string
Default: 🚀
Oversold Suffix
Customizes the fractal ray label with a suffix text.
Type: string
Default: (empty)
FRACTAL RAYS · OVERBOUGHT
Overbought Level
Changes the base RSI Level for fractal rays calculation.
Type: int
Min: 1
Default: 70
Overbought Prefix
Customizes the fractal ray label with a prefix text.
Type: string
Default: 🐻
Overbought Suffix
Customizes the fractal ray label with a suffix text.
Type: string
Default: (empty)
FRACTAL RAYS · VISIBILITY RULES
These rules are applied for each of fractal rays so, the traders can choose what timeframes they wants to show the fractal rays for each of it. The rule will be applied as the following condition: `if timeframe != CURRENT_TIMEFRAME and timeframe <= CHOSEN_OPTION`. Actually, the fractal rays are on the chart but, isn't visible because it was applied a transparent color, so it is visually not on the chart to prevent chart's over polution.
LABELS
Show Labels on Price Scale
Shows labels on price scale.
Type: bool
Default: false
Show Price on Fractal Rays
Shows the RSI Level price on each of fractal rays respectively.
Type: bool
Default: false
█ EXTERNAL LIBRARIES
This script uses the `tk` library to calculate RSI Levels. It is a library that contains various functions that helps pine script developers to calculate RSI Levels.
█ FUNCTIONS
The library contains the following functions:
fn_fractalVisibilityRule(string visibilityRule)
Converts the fractal rays timeframe visibility rule label to timestamp int.
Parameters:
visibilityRule: (string) Fractal ray visibility rule label.
Returns: (int) Fractal ray visibility rule timestamp.
fn_requestFractal(string period, expression)
Converts the fractal rays timeframe visibility rule label to timestamp int.
Parameters:
period: (string) Timeframe period for the desired fractal.
expression: (mixed) Security expression that will be applied for calculation.
Returns: (mixed) A result determined by expression.
fn_plotRay(float y, string label, color color, int length)
Plots ray after chart bars for the current time.
Parameters:
period: (string) Timeframe period for the desired fractal.
expression: (mixed) Security expression that will be applied for calculation.
Returns: (void) This function only plots the elements into the chart
fn_plotRsiLevelRay(simple string period, simple int level, color color)
Plots RSI Levels ray after chart bars for the current time.
Parameters:
period: (simple string) Timeframe period.
level: (simple int) Relative Strength Index level.
color: (color) The color of both, ray and label text.
Returns: (void) This function only plots the elements into the chart
Any Oscillator Underlay [TTF]We are proud to release a new indicator that has been a while in the making - the Any Oscillator Underlay (AOU) !
Note: There is a lot to discuss regarding this indicator, including its intent and some of how it operates, so please be sure to read this entire description before using this indicator to help ensure you understand both the intent and some limitations with this tool.
Our intent for building this indicator was to accomplish the following:
Combine all of the oscillators that we like to use into a single indicator
Take up a bit less screen space for the underlay indicators for strategies that utilize multiple oscillators
Provide a tool for newer traders to be able to leverage multiple oscillators in a single indicator
Features:
Includes 8 separate, fully-functional indicators combined into one
Ability to easily enable/disable and configure each included indicator independently
Clearly named plots to support user customization of color and styling, as well as manual creation of alerts
Ability to customize sub-indicator title position and color
Ability to customize sub-indicator divider lines style and color
Indicators that are included in this initial release:
TSI
2x RSIs (dubbed the Twin RSI )
Stochastic RSI
Stochastic
Ultimate Oscillator
Awesome Oscillator
MACD
Outback RSI (Color-coding only)
Quick note on OB/OS:
Before we get into covering each included indicator, we first need to cover a core concept for how we're defining OB and OS levels. To help illustrate this, we will use the TSI as an example.
The TSI by default has a mid-point of 0 and a range of -100 to 100. As a result, a common practice is to place lines on the -30 and +30 levels to represent OS and OB zones, respectively. Most people tend to view these levels as distance from the edges/outer bounds or as absolute levels, but we feel a more way to frame the OB/OS concept is to instead define it as distance ("offset") from the mid-line. In keeping with the -30 and +30 levels in our example, the offset in this case would be "30".
Taking this a step further, let's say we decided we wanted an offset of 25. Since the mid-point is 0, we'd then calculate the OB level as 0 + 25 (+25), and the OS level as 0 - 25 (-25).
Now that we've covered the concept of how we approach defining OB and OS levels (based on offset/distance from the mid-line), and since we did apply some transformations, rescaling, and/or repositioning to all of the indicators noted above, we are going to discuss each component indicator to detail both how it was modified from the original to fit the stacked-indicator model, as well as the various major components that the indicator contains.
TSI:
This indicator contains the following major elements:
TSI and TSI Signal Line
Color-coded fill for the TSI/TSI Signal lines
Moving Average for the TSI
TSI Histogram
Mid-line and OB/OS lines
Default TSI fill color coding:
Green : TSI is above the signal line
Red : TSI is below the signal line
Note: The TSI traditionally has a range of -100 to +100 with a mid-point of 0 (range of 200). To fit into our stacking model, we first shrunk the range to 100 (-50 to +50 - cut it in half), then repositioned it to have a mid-point of 50. Since this is the "bottom" of our indicator-stack, no additional repositioning is necessary.
Twin RSI:
This indicator contains the following major elements:
Fast RSI (useful if you want to leverage 2x RSIs as it makes it easier to see the overlaps and crosses - can be disabled if desired)
Slow RSI (primary RSI)
Color-coded fill for the Fast/Slow RSI lines (if Fast RSI is enabled and configured)
Moving Average for the Slow RSI
Mid-line and OB/OS lines
Default Twin RSI fill color coding:
Dark Red : Fast RSI below Slow RSI and Slow RSI below Slow RSI MA
Light Red : Fast RSI below Slow RSI and Slow RSI above Slow RSI MA
Dark Green : Fast RSI above Slow RSI and Slow RSI below Slow RSI MA
Light Green : Fast RSI above Slow RSI and Slow RSI above Slow RSI MA
Note: The RSI naturally has a range of 0 to 100 with a mid-point of 50, so no rescaling or transformation is done on this indicator. The only manipulation done is to properly position it in the indicator-stack based on which other indicators are also enabled.
Stochastic and Stochastic RSI:
These indicators contain the following major elements:
Configurable lengths for the RSI (for the Stochastic RSI only), K, and D values
Configurable base price source
Mid-line and OB/OS lines
Note: The Stochastic and Stochastic RSI both have a normal range of 0 to 100 with a mid-point of 50, so no rescaling or transformations are done on either of these indicators. The only manipulation done is to properly position it in the indicator-stack based on which other indicators are also enabled.
Ultimate Oscillator (UO):
This indicator contains the following major elements:
Configurable lengths for the Fast, Middle, and Slow BP/TR components
Mid-line and OB/OS lines
Moving Average for the UO
Color-coded fill for the UO/UO MA lines (if UO MA is enabled and configured)
Default UO fill color coding:
Green : UO is above the moving average line
Red : UO is below the moving average line
Note: The UO naturally has a range of 0 to 100 with a mid-point of 50, so no rescaling or transformation is done on this indicator. The only manipulation done is to properly position it in the indicator-stack based on which other indicators are also enabled.
Awesome Oscillator (AO):
This indicator contains the following major elements:
Configurable lengths for the Fast and Slow moving averages used in the AO calculation
Configurable price source for the moving averages used in the AO calculation
Mid-line
Option to display the AO as a line or pseudo-histogram
Moving Average for the AO
Color-coded fill for the AO/AO MA lines (if AO MA is enabled and configured)
Default AO fill color coding (Note: Fill was disabled in the image above to improve clarity):
Green : AO is above the moving average line
Red : AO is below the moving average line
Note: The AO is technically has an infinite (unbound) range - -∞ to ∞ - and the effective range is bound to the underlying security price (e.g. BTC will have a wider range than SP500, and SP500 will have a wider range than EUR/USD). We employed some special techniques to rescale this indicator into our desired range of 100 (-50 to 50), and then repositioned it to have a midpoint of 50 (range of 0 to 100) to meet the constraints of our stacking model. We then do one final repositioning to place it in the correct position the indicator-stack based on which other indicators are also enabled. For more details on how we accomplished this, read our section "Binding Infinity" below.
MACD:
This indicator contains the following major elements:
Configurable lengths for the Fast and Slow moving averages used in the MACD calculation
Configurable price source for the moving averages used in the MACD calculation
Configurable length and calculation method for the MACD Signal Line calculation
Mid-line
Note: Like the AO, the MACD also technically has an infinite (unbound) range. We employed the same principles here as we did with the AO to rescale and reposition this indicator as well. For more details on how we accomplished this, read our section "Binding Infinity" below.
Outback RSI (ORSI):
This is a stripped-down version of the Outback RSI indicator (linked above) that only includes the color-coding background (suffice it to say that it was not technically feasible to attempt to rescale the other components in a way that could consistently be clearly seen on-chart). As this component is a bit of a niche/special-purpose sub-indicator, it is disabled by default, and we suggest it remain disabled unless you have some pre-defined strategy that leverages the color-coding element of the Outback RSI that you wish to use.
Binding Infinity - How We Incorporated the AO and MACD (Warning - Math Talk Ahead!)
Note: This applies only to the AO and MACD at time of original publication. If any other indicators are added in the future that also fall into the category of "binding an infinite-range oscillator", we will make that clear in the release notes when that new addition is published.
To help set the stage for this discussion, it's important to note that the broader challenge of "equalizing inputs" is nothing new. In fact, it's a key element in many of the most popular fields of data science, such as AI and Machine Learning. They need to take a diverse set of inputs with a wide variety of ranges and seemingly-random inputs (referred to as "features"), and build a mathematical or computational model in order to work. But, when the raw inputs can vary significantly from one another, there is an inherent need to do some pre-processing to those inputs so that one doesn't overwhelm another simply due to the difference in raw values between them. This is where feature scaling comes into play.
With this in mind, we implemented 2 of the most common methods of Feature Scaling - Min-Max Normalization (which we call "Normalization" in our settings), and Z-Score Normalization (which we call "Standardization" in our settings). Let's take a look at each of those methods as they have been implemented in this script.
Min-Max Normalization (Normalization)
This is one of the most common - and most basic - methods of feature scaling. The basic formula is: y = (x - min)/(max - min) - where x is the current data sample, min is the lowest value in the dataset, and max is the highest value in the dataset. In this transformation, the max would evaluate to 1, and the min would evaluate to 0, and any value in between the min and the max would evaluate somewhere between 0 and 1.
The key benefits of this method are:
It can be used to transform datasets of any range into a new dataset with a consistent and known range (0 to 1).
It has no dependency on the "shape" of the raw input dataset (i.e. does not assume the input dataset can be approximated to a normal distribution).
But there are a couple of "gotchas" with this technique...
First, it assumes the input dataset is complete, or an accurate representation of the population via random sampling. While in most situations this is a valid assumption, in trading indicators we don't really have that luxury as we're often limited in what sample data we can access (i.e. number of historical bars available).
Second, this method is highly sensitive to outliers. Since the crux of this transformation is based on the max-min to define the initial range, a single significant outlier can result in skewing the post-transformation dataset (i.e. major price movement as a reaction to a significant news event).
You can potentially mitigate those 2 "gotchas" by using a mechanism or technique to find and discard outliers (e.g. calculate the mean and standard deviation of the input dataset and discard any raw values more than 5 standard deviations from the mean), but if your most recent datapoint is an "outlier" as defined by that algorithm, processing it using the "scrubbed" dataset would result in that new datapoint being outside the intended range of 0 to 1 (e.g. if the new datapoint is greater than the "scrubbed" max, it's post-transformation value would be greater than 1). Even though this is a bit of an edge-case scenario, it is still sure to happen in live markets processing live data, so it's not an ideal solution in our opinion (which is why we chose not to attempt to discard outliers in this manner).
Z-Score Normalization (Standardization)
This method of rescaling is a bit more complex than the Min-Max Normalization method noted above, but it is also a widely used process. The basic formula is: y = (x – μ) / σ - where x is the current data sample, μ is the mean (average) of the input dataset, and σ is the standard deviation of the input dataset. While this transformation still results in a technically-infinite possible range, the output of this transformation has a 2 very significant properties - the mean (average) of the output dataset has a mean (μ) of 0 and a standard deviation (σ) of 1.
The key benefits of this method are:
As it's based on normalizing the mean and standard deviation of the input dataset instead of a linear range conversion, it is far less susceptible to outliers significantly affecting the result (and in fact has the effect of "squishing" outliers).
It can be used to accurately transform disparate sets of data into a similar range regardless of the original dataset's raw/actual range.
But there are a couple of "gotchas" with this technique as well...
First, it still technically does not do any form of range-binding, so it is still technically unbounded (range -∞ to ∞ with a mid-point of 0).
Second, it implicitly assumes that the raw input dataset to be transformed is normally distributed, which won't always be the case in financial markets.
The first "gotcha" is a bit of an annoyance, but isn't a huge issue as we can apply principles of normal distribution to conceptually limit the range by defining a fixed number of standard deviations from the mean. While this doesn't totally solve the "infinite range" problem (a strong enough sudden move can still break out of our "conceptual range" boundaries), the amount of movement needed to achieve that kind of impact will generally be pretty rare.
The bigger challenge is how to deal with the assumption of the input dataset being normally distributed. While most financial markets (and indicators) do tend towards a normal distribution, they are almost never going to match that distribution exactly. So let's dig a bit deeper into distributions are defined and how things like trending markets can affect them.
Skew (skewness): This is a measure of asymmetry of the bell curve, or put another way, how and in what way the bell curve is disfigured when comparing the 2 halves. The easiest way to visualize this is to draw an imaginary vertical line through the apex of the bell curve, then fold the curve in half along that line. If both halves are exactly the same, the skew is 0 (no skew/perfectly symmetrical) - which is what a normal distribution has (skew = 0). Most financial markets tend to have short, medium, and long-term trends, and these trends will cause the distribution curve to skew in one direction or another. Bullish markets tend to skew to the right (positive), and bearish markets to the left (negative).
Kurtosis: This is a measure of the "tail size" of the bell curve. Another way to state this could be how "flat" or "steep" the bell-shape is. If the bell is steep with a strong drop from the apex (like a steep cliff), it has low kurtosis. If the bell has a shallow, more sweeping drop from the apex (like a tall hill), is has high kurtosis. Translating this to financial markets, kurtosis is generally a metric of volatility as the bell shape is largely defined by the strength and frequency of outliers. This is effectively a measure of volatility - volatile markets tend to have a high level of kurtosis (>3), and stable/consolidating markets tend to have a low level of kurtosis (<3). A normal distribution (our reference), has a kurtosis value of 3.
So to try and bring all that back together, here's a quick recap of the Standardization rescaling method:
The Standardization method has an assumption of a normal distribution of input data by using the mean (average) and standard deviation to handle the transformation
Most financial markets do NOT have a normal distribution (as discussed above), and will have varying degrees of skew and kurtosis
Q: Why are we still favoring the Standardization method over the Normalization method, and how are we accounting for the innate skew and/or kurtosis inherent in most financial markets?
A: Well, since we're only trying to rescale oscillators that by-definition have a midpoint of 0, kurtosis isn't a major concern beyond the affect it has on the post-transformation scaling (specifically, the number of standard deviations from the mean we need to include in our "artificially-bound" range definition).
Q: So that answers the question about kurtosis, but what about skew?
A: So - for skew, the answer is in the formula - specifically the mean (average) element. The standard mean calculation assumes a complete dataset and therefore uses a standard (i.e. simple) average, but we're limited by the data history available to us. So we adapted the transformation formula to leverage a moving average that included a weighting element to it so that it favored recent datapoints more heavily than older ones. By making the average component more adaptive, we gained the effect of reducing the skew element by having the average itself be more responsive to recent movements, which significantly reduces the effect historical outliers have on the dataset as a whole. While this is certainly not a perfect solution, we've found that it serves the purpose of rescaling the MACD and AO to a far more well-defined range while still preserving the oscillator behavior and mid-line exceptionally well.
The most difficult parts to compensate for are periods where markets have low volatility for an extended period of time - to the point where the oscillators are hovering around the 0/midline (in the case of the AO), or when the oscillator and signal lines converge and remain close to each other (in the case of the MACD). It's during these periods where even our best attempt at ensuring accurate mirrored-behavior when compared to the original can still occasionally lead or lag by a candle.
Note: If this is a make-or-break situation for you or your strategy, then we recommend you do not use any of the included indicators that leverage this kind of bounding technique (the AO and MACD at time of publication) and instead use the Trandingview built-in versions!
We know this is a lot to read and digest, so please take your time and feel free to ask questions - we will do our best to answer! And as always, constructive feedback is always welcome!
DR/IDR Candles [LuxAlgo]This indicator displays defining ranges (DR) and implied defining ranges (IDR) constructed from two user set sessions (RDR/ODR) as graphical candles on the chart. The script introduces additional graphical elements to the original DR/IDR concept and as such can be thought as a graphical method in addition to a technical indicator.
Additionally, this script can display various Fibonacci retracements from the constructed DR/IDR if enabled within the settings.
Settings
Regular Session: Enable/disable regular session's DR/IDR alongside setting the session time. By default, 09:30 - 10:30 am.
Overnight Session: Enable/disable overnight session's DR/IDR alongside setting the session time. By default, 03:00 - 04:00 am.
UTC Offset: UTC offset for the time zone, by default -5 (EST)
Retracements
Reverse: Inverts source range upper/lower value for constructing the retracements.
From: Source range used to construct the retracements, by default DR is used.
By default, the 0.5 retracement (average line) is displayed.
Usage
The used sessions are highlighted by a gray background. DRs are highlighted by dashed lines while IDRs are highlighted by solid ones. The maximum/minimum price between each user set session is highlighted by solid wicks.
The color of the DRs/IDRs/wicks are determined by the price position relative to the DR; if price is above the DR maximum, then a blue color is used. If price is below, then an orange color is used, and if price is within the DR range, then a gray color is used.
Additionally, the area of the DR range is used to highlight the number of time price is located within the DR, with a longer background highlighting a higher number of occurrences. This can help highlight if the DR levels were potentially useful as support/resistance.
When price is outside the IDR range, the area between the price and IDR is highlighted, in blue if price is above the IDR, and orange if it is under.
The original author of the DR/IDR concept describes 3 rules using the price position relative to the DR/IDR levels:
1.) If price on the 5-minute timeframe closes above the DR high after 10:30 AM or 04:00 AM then the DR low will likely be the low of the trading session.
2.) If price on the 5-minute timeframe closes below the DR low after 10:30 AM or 04:00 AM then the DR high will likely be the high of the trading session.
3.) If price closes above the IDR high after 10:30 AM or 04:00 AM it is an early indication that the low of the DR will be the low of the day and vice versa.
We can see that the above rules are cases of conditional probabilities.
There is no significant data supporting or regarding any statistical probability of the above rules to be true, which are more than uncertain given the stochastic nature of prices. The lack of precision of these rules is also a concern (time zone dependance, applicable markets, etc...).
Credits
Credits to trader TheMas7er who originally created the DR/IDR concept in November of 2022. This script was derived from his proposed session times & rules for trading.
Ichimoku Breakout Kumo SWING TRADER (By Insert Cheese)A simple strategy for long spot or long futures (swing traders) based on a basic method of Ichimoku Kinko Hyo strategies.
The strategy is simple:
- Buy when the price breaks the cloud
- Close the trade when the price closes again inside the cloud.
The parameters that work best on this strategy are 10,30,60,30 and 1 for Senkou-Span A
but you can try classic Ichimoku parameters (9,26,52,26,26) or whatever you want like (7,22,44,22,22), (10,30,60,30,30) and others.
-1D chart
I have removed everything from the interface except the cloud to make it visually more aesthetic :D (but if you want to see all the ichimoku indicator you can put in again into the chart)
I have also added several functions for you to do your own backtesting:
- Date range
- TP AND SL method
- Includes long or short trades
The strategy starts with 500 $ and use 100% for trade to make the power of the compounding :P
Remember that this is for only educational porpouse and you must to do your own research and backtested on your usually market..
I hope you like it enjoy and support this indicator :)
Donate (BEP20) 0xC118f1ffB3ac40875C13B3823C182eA2Af344c6d
RSI Trend Heatmap in Multi TimeframesRSI Trend Heatmap in Multi Timeframes
Description
Sometimes you want to look at the RSI Trend across multiple time frames.
You have to waste time browsing through them.
So we've put together every time frame you want to see in one indicator.
We have 10 layers of RSI Trend heatmap available for you.
You can set the timeframe as you want on the Settings page.
Description of Parameter RSI Setting ** You can change it by setting.
RSI Trend Length : (Default 50)
Source : (Default close)
RSI Sideways Length : (Default 2 = RSI between 48 .. 52)
Description of Parameter RSI Timeframe ** You can change it by setting.
""=None,
"M"=1Month, "2W"=2Weeks, "W"=1Week,
"3D"=3Days, "2D"=2Days, "D"=1Day,
"720"=12Hours, "480"=4Hours, "240"=4Hours, "180"=3Hours, "120"=2Hours,
"60"=60Minutes, "30"=30Minutes, "15"=15Minutes, "5"=5Minutes, "1"=1Minute
Default Configurate of RSI Timeframe (for a time frame of 1 hour to 1 day)
"W"= Timeframe 1 month shown in line 90-100 --> Represent Long Trend of RSI
---------------------------------------
"D2"= Timeframe 2 days shown in line 70-80 --> Represent Trend of RSI
"D"= Timeframe 1 day shown in line 60-70 --> Represent Trend of RSI
---------------------------------------
"240"= Timeframe 3 hours shown in line 40-50 --> Represent Signal Up/Signal Down/Divergence of RSI
"120"= Timeframe 2 hours shown in line 30-40 --> Represent Signal Up/Signal Down/Divergence of RSI
"60"= Timeframe 1 hour shown in line 20-30 --> Represent Signal Up/Signal Down/Divergence of RSI
"30"= Timeframe 30 minutes shown in line 10-20 --> Represent Signal Up/Signal Down/Divergence of RSI
"15"= Timeframe 15 minutes shown in line 00-10 --> Represent Signal Up/Signal Down/Divergence of RSI
Description of Colors
Dark Bule = Extreme Uptrend / Overbought / Bull Market (RSI > 67)
Light Bule = Uptrend (RSI between 50-52 .. 67)
Yellow = Sideways Trend / Trend Reversal (RSI between 48 .. 52) ** You can change it by setting.
Light Red = Downtrend (RSI between 33 .. 48-50)
Dark Red = Extreme Downtrend / Oversold / Bear Market (RSI < 33)
How to use
1. You must first know what the main trend of the RSI is (look at the 60-80 line). If it is red, it is a downtrend. and if it's blue shows that it is an uptrend
2. Throughout the period of the main trend There will always be a reversal of the sub-trend. (Can see from the 0-50 line), but eventually will return to follow the main trend.
3. Unless the sub trend persists for a long time until the main trend changes.
ICT Index Futures Session LinesICT Index Futures Session Lines
Description:
The script is based on one of ICT's concepts on trading Index Futures. The script lays out the daily range from an intraday basis.
Range:
00:00 - New York Midnight
08:30 – New York Open (News events come out)
12:00/13:00 - New York Lunch (No trade time period)
13:30 - (Algorithm)
16:30 - Close
* The open, high and low lines are plotted from 00:00 to 08:30
How To Use:
You will need to check the daily bias. Prior to 8:30 you are to look for previous swing points where liquidity may exist. During the open you want to see if a high or low is taken out, and then wait for an energetic break/displacement for a potential FVG/imbalance retracement entry.
Strategy is for LTF (1 to 15m)
Default time zone is set to America/New_York (UTC New York), so lines will be plotted correctly regardless of user’s local UTC chart setting.
RSI Levels, Multi-TimeframeThe relative strength index (RSI) is a momentum indicator that measures the magnitude of recent price changes to evaluate overbought or oversold conditions. RSI is normally displayed as an oscillator separately from price and can have a reading from 0 to 100. This indicator takes the RSI and plots the 30 & 70 levels onto the price chart so you can see when price is going to meet the 30 or 70 levels. The reason the 30 & 70 levels are important is because many traders (and bots) use those as signals to buy (at 30 RSI) or sell (at 70 RSI). Additionally, this indicator allows you to display not just the RSI levels of your currently viewed timeframe on the chart, but also shows the RSI levels of up to 6 different timeframes on the same chart. This allows you to quickly see if multiple RSI levels are aligning across different timelines, which is an even stronger indication that price is going to change direction when it meets those levels on the chart. There are a lot of nice configuration options, like:
Style customization (color, thickness, size)
Labels on the chart so you can tell which plots are the RSI levels
Optionally display the plot as a horizontal line if all you care about is the RSI level right now
Toggle overbought (RSI 70) or oversold (RSI 30) on/off completely
Hotch v1.02 RSI+Fractals/VWAP Bands/Smoothed Moving Average. In this script the RSI is used the limit number of displayed fractals to only those fractals that are triggered in the RSI Overbought and Oversold areas. This helps keep the chart cleaner looking when combined with other indicators so other icons that are plotted above and below candles are not covered up.
For example if the RSI drops below 30 the next fractal would be displayed.
If the RSI stays below 30 each fractal would be displayed.
If the RSI dips below 30 and returns above 30 before there is a fractal is displayed, the next valid fractal would still be displayed.
With optimization of the RSI values this indicator can be used in confluence with the included VWAP bands and Moving average to find trend reversal entry points for trades. Also recommended is to use a divergence identifying lower indicator as a secondary confirmation of trade entry.
Example of a potential long entry using the displayed chart.
1) RSI under 30
2) Price was recently outside of your chosen VWAP multiple.
3) a fractal was triggered.
Additionaly:
4) Use other indicators or other confluences for a stronger trade signal.
5) Use your preferred method of determining entry price stop loss and take profit.
NOTE: Fractals normally paint two bars behind the current bar. In this code, with the combination of the RSI and Fractal Trigger, the fractal paints an icon on the current bar.
User-Inputed Time Range & FibsGreetings Traders! I have decided to release a few scripts as open-source as I'm sure others can benefit from them and perhaps make them better.(Be sure to check my Profile for the other scripts as well: www.tradingview.com).
This one is called User-Inputed Time Range & Fibs.
The idea behind this script is to record the Range Highs and Lows of a User Defined Period, and plot potential Targets based on either Fibonacci Extensions or a Multiple of the Range Size. I created this originally for use with the US Session Initial Balance(From 9:30-10:30AM EST), however it can be set to any time period.
What is Initial Balance? In simple words, Initial Balance (IB) is the price data, which are formed during the first hour of a trading session. Activity of traders forms the so-called Initial Balance at this time. This concept was introduced for the first time by Peter Steidlmayer when he presented the market profile to traders(atas.net).
The IB is monitored as a break-out area for Range Extension traders. The IB High is also seen as an area of resistance and the IB Low as an area of support until it is broken(www.mypivots.com).
As a note, depending on the Time Zone you are in, you may need to manually add or subtract from the Timed Range to match the desired Time. For example in NY Eastern Time, I have to use 8:30-9:30AM to Capture the 9:30-10-30AM IB for ES and NQ. Similarly, I must use 14:30-15:30PM to Capture the 9:30-10-30AM IB for BTC. You will need to make adjustments based on the Time Zone you are located in.
I wanted to give a Special Thanks to @PineCoders for the Custom Rounding Function from Backtesting/Trading Engine--> (), Pinecoders.com for help with Tracking the Highs/Lows--> (www.pinecoders.com), and @TradeChartist for allowing me to use some of the code for the Fibonacci Extensions from his script here--> ().
If you like User-Inputed Time Range & Fibs, be sure to Like, Follow, and if you have any questions, don't be afraid to drop a comment below.
Realized VolatilityRealized / Historical Volatility
Calculates historical, i.e. realized volatility of any underlying. If frequency is not the daily, but for example 6h, 30min, weeks or months, it scales the initial setting to be suitable for the different time frame.
Examples with default settings (30 day volatility, 365 days per year):
A) Frequency = Daily:
Returns 30 day historical volatility, under the assumption that there are 365 trading days in a year.
B) Frequency = 6h:
Still returns 30 day historical volatility, under the assumption that there are 365 trading days in a year. However, since 6h granularity fits 4 times in 24 hours, it rescales the look back period to rather 30*4 = 120 units to still reflect 30 day historical volatility.
RSI3graf. 3 RSI in one window[wozdux] Three RSI indicator charts in one window. Plus, the resale area (green) and overbought area ( red) are highlighted. Indicator settings are periods of calculation of the RSI indicator (24, 14, 9). The fourth parameter (30) is the critical levels, which are at a distance of 30 units from the edges. If the parameter is 30, then the oversold level is 30 and the overbought level is 70 (100-30).
Market Regime# MARKET REGIME IDENTIFICATION & TRADING SYSTEM
## Complete User Guide
---
## 📋 TABLE OF CONTENTS
1. (#overview)
2. (#regimes)
3. (#indicator-usage)
4. (#entry-signals)
5. (#exit-signals)
6. (#regime-strategies)
7. (#confluence)
8. (#backtesting)
9. (#optimization)
10. (#examples)
---
## OVERVIEW
### What This System Does
This is a **complete market regime identification and trading system** that:
1. **Identifies 6 distinct market regimes** automatically
2. **Adapts trading tactics** to each regime
3. **Provides high-probability entry signals** with confluence scoring
4. **Shows optimal exit points** for each trade
5. **Can be backtested** to validate performance
### Two Components Provided
1. **Indicator** (`market_regime_indicator.pine`)
- Visual regime identification
- Entry/exit signals on chart
- Dynamic support/resistance
- Info tables with live data
- Use for manual trading
2. **Strategy** (`market_regime_strategy.pine`)
- Fully automated backtestable version
- Same logic as indicator
- Position sizing and risk management
- Performance metrics
- Use for backtesting and automation
---
## THE 6 MARKET REGIMES
### 1. 🟢 BULL TRENDING
**Characteristics:**
- Strong uptrend
- Price above SMA50 and SMA200
- ADX > 25 (strong trend)
- Higher highs and higher lows
- DI+ > DI- (bullish momentum)
**What It Means:**
- Market has clear upward direction
- Buyers in control
- Pullbacks are buying opportunities
- Strongest regime for long positions
**How to Trade:**
- ✅ **BUY dips to EMA20 or SMA20**
- ✅ Enter when RSI < 60 on pullback
- ✅ Hold through minor corrections
- ❌ Don't short against the trend
- ❌ Don't sell too early
**Expected Behavior:**
- Pullbacks are shallow (5-10%)
- Bounces are strong
- Support at moving averages holds
- Volume increases on rallies
---
### 2. 🔴 BEAR TRENDING
**Characteristics:**
- Strong downtrend
- Price below SMA50 and SMA200
- ADX > 25 (strong trend)
- Lower highs and lower lows
- DI- > DI+ (bearish momentum)
**What It Means:**
- Market has clear downward direction
- Sellers in control
- Rallies are selling opportunities
- Strongest regime for short positions
**How to Trade:**
- ✅ **SELL rallies to EMA20 or SMA20**
- ✅ Enter when RSI > 40 on bounce
- ✅ Hold through minor bounces
- ❌ Don't buy against the trend
- ❌ Don't cover shorts too early
**Expected Behavior:**
- Rallies are weak (5-10%)
- Selloffs are strong
- Resistance at moving averages holds
- Volume increases on declines
---
### 3. 🔵 BULL RANGING
**Characteristics:**
- Bullish bias but consolidating
- Price near or above SMA50
- ADX < 20 (weak trend)
- Trading in range
- Choppy price action
**What It Means:**
- Uptrend is pausing
- Accumulation phase
- Support and resistance zones clear
- Lower volatility
**How to Trade:**
- ✅ **BUY at support zone**
- ✅ Enter when RSI < 40
- ✅ Take profits at resistance
- ⚠️ Smaller position sizes
- ⚠️ Tighter stops
**Expected Behavior:**
- Range-bound oscillations
- Support bounces repeatedly
- Resistance rejections common
- Eventually breaks higher (usually)
---
### 4. 🟠 BEAR RANGING
**Characteristics:**
- Bearish bias but consolidating
- Price near or below SMA50
- ADX < 20 (weak trend)
- Trading in range
- Choppy price action
**What It Means:**
- Downtrend is pausing
- Distribution phase
- Support and resistance zones clear
- Lower volatility
**How to Trade:**
- ✅ **SELL at resistance zone**
- ✅ Enter when RSI > 60
- ✅ Take profits at support
- ⚠️ Smaller position sizes
- ⚠️ Tighter stops
**Expected Behavior:**
- Range-bound oscillations
- Resistance holds repeatedly
- Support bounces are weak
- Eventually breaks lower (usually)
---
### 5. ⚪ CONSOLIDATION
**Characteristics:**
- No clear direction
- Range compression
- Very low ADX (< 15 often)
- Price inside tight range
- Neutral sentiment
**What It Means:**
- Market is coiling
- Building energy for next move
- Indecision between buyers/sellers
- Calm before the storm
**How to Trade:**
- ✅ **WAIT for breakout direction**
- ✅ Enter on high-volume breakout
- ✅ Direction becomes clear
- ❌ Don't trade inside the range
- ❌ Avoid choppy scalping
**Expected Behavior:**
- Narrow range
- Low volume
- False breakouts possible
- Explosive move when it breaks
---
### 6. 🟣 CHAOS (High Volatility)
**Characteristics:**
- Extreme volatility
- No clear direction
- Erratic price swings
- ATR > 2x average
- Unpredictable
**What It Means:**
- Market panic or euphoria
- News-driven moves
- Emotion dominates logic
- Highest risk environment
**How to Trade:**
- ❌ **STAY OUT!**
- ❌ No positions
- ❌ Wait for stability
- ✅ Protect existing positions
- ✅ Reduce risk
**Expected Behavior:**
- Large intraday swings
- Gaps up/down
- Stop hunts
- Whipsaws
- Eventually calms down
---
## INDICATOR USAGE
### Visual Elements
#### 1. Background Colors
- **Light Green** = Bull Trending (go long)
- **Light Red** = Bear Trending (go short)
- **Light Teal** = Bull Ranging (buy dips)
- **Light Orange** = Bear Ranging (sell rallies)
- **Light Gray** = Consolidation (wait)
- **Purple** = Chaos (stay out!)
#### 2. Regime Labels
- Appear when regime changes
- Show new regime name
- Positioned at highs (bullish) or lows (bearish)
#### 3. Entry Signals
- **Green "LONG"** labels = Buy here
- **Red "SHORT"** labels = Sell here
- Number shows confluence score (X/5 signals)
- Hover for details (stop, target, RSI, etc.)
#### 4. Exit Signals
- **Orange "EXIT LONG"** = Close long position
- **Orange "EXIT SHORT"** = Close short position
- Shows exit reason in tooltip
#### 5. Support/Resistance Lines
- **Green line** = Dynamic support (buy zone)
- **Red line** = Dynamic resistance (sell zone)
- Adapts to regime automatically
#### 6. Moving Averages
- **Blue** = SMA 20 (short-term trend)
- **Orange** = SMA 50 (medium-term trend)
- **Purple** = SMA 200 (long-term trend)
### Information Tables
#### Top Right Table (Main Info)
Shows real-time market conditions:
- **Current Regime** - What regime we're in
- **Bias** - Long, Short, Breakout, or Stay Out
- **ADX** - Trend strength (>25 = strong)
- **Trend** - Strong, Moderate, or Weak
- **Volatility** - High or Normal
- **Vol Ratio** - Current vs average volatility
- **RSI** - Momentum (>70 overbought, <30 oversold)
- **vs SMA50/200** - Price position relative to MAs
- **Support/Resistance** - Exact price levels
- **Long/Short Signals** - Confluence scores (X/5)
#### Bottom Right Table (Regime Guide)
Quick reference for each regime:
- What action to take
- What strategy to use
- Color-coded for quick identification
---
## ENTRY SIGNALS EXPLAINED
### Confluence Scoring System (5 Factors)
Each entry signal is scored 0-5 based on how many factors align:
#### For LONG Entries:
1. ✅ **Regime Alignment** - In Bull Trending or Bull Ranging
2. ✅ **RSI Pullback** - RSI between 35-50 (not overbought)
3. ✅ **Near Support** - Price within 2% of dynamic support
4. ✅ **MACD Turning Up** - Momentum shifting bullish
5. ✅ **Volume Confirmation** - Above average volume
#### For SHORT Entries:
1. ✅ **Regime Alignment** - In Bear Trending or Bear Ranging
2. ✅ **RSI Rejection** - RSI between 50-65 (not oversold)
3. ✅ **Near Resistance** - Price within 2% of dynamic resistance
4. ✅ **MACD Turning Down** - Momentum shifting bearish
5. ✅ **Volume Confirmation** - Above average volume
### Confluence Requirements
**Minimum Confluence** (default = 2):
- 2/5 = Entry signal triggered
- 3/5 = Good signal
- 4/5 = Strong signal
- 5/5 = Excellent signal (rare)
**Higher confluence = Higher probability = Better trades**
### Specific Entry Patterns
#### 1. Bull Trending Entry
```
Requirements:
- Regime = Bull Trending
- Price pulls back to EMA20
- Close above EMA20 (bounce)
- Up candle (close > open)
- RSI < 60
- Confluence ≥ 2
```
#### 2. Bear Trending Entry
```
Requirements:
- Regime = Bear Trending
- Price rallies to EMA20
- Close below EMA20 (rejection)
- Down candle (close < open)
- RSI > 40
- Confluence ≥ 2
```
#### 3. Bull Ranging Entry
```
Requirements:
- Regime = Bull Ranging
- RSI < 40 (oversold)
- Price at or below support
- Up candle (reversal)
- Confluence ≥ 1 (more lenient)
```
#### 4. Bear Ranging Entry
```
Requirements:
- Regime = Bear Ranging
- RSI > 60 (overbought)
- Price at or above resistance
- Down candle (rejection)
- Confluence ≥ 1 (more lenient)
```
#### 5. Consolidation Breakout
```
Requirements:
- Regime = Consolidation
- Price breaks above/below range
- Volume > 1.5x average (explosive)
- Strong directional candle
```
---
## EXIT SIGNALS EXPLAINED
### Three Types of Exits
#### 1. Regime Change Exits (Automatic)
- **Long Exit**: Regime changes to Bear Trending or Chaos
- **Short Exit**: Regime changes to Bull Trending or Chaos
- **Reason**: Market character changed, strategy no longer valid
#### 2. Support/Resistance Break Exits
- **Long Exit**: Price breaks below support by 2%
- **Short Exit**: Price breaks above resistance by 2%
- **Reason**: Key level violated, trend may be reversing
#### 3. Momentum Exits
- **Long Exit**: RSI > 70 (overbought) AND down candle
- **Short Exit**: RSI < 30 (oversold) AND up candle
- **Reason**: Overextension, take profits
### Stop Loss & Take Profit
**Stop Loss** (Automatic in strategy):
- Placed at Entry - (ATR × 2)
- Adapts to volatility
- Protected from whipsaws
- Typically 2-4% for stocks, 5-10% for crypto
**Take Profit** (Automatic in strategy):
- Placed at Entry + (Stop Distance × R:R Ratio)
- Default 2.5:1 reward:risk
- Example: $2 risk = $5 reward target
- Allows winners to run
---
## TRADING EACH REGIME
### BULL TRENDING - Most Profitable Long Environment
**Strategy: Buy Every Dip**
**Entry Rules:**
1. Wait for pullback to EMA20 or SMA20
2. Look for RSI < 60
3. Enter when candle closes above MA
4. Confluence should be 2+
**Stop Loss:**
- Below the recent swing low
- Or 2 × ATR below entry
**Take Profit:**
- At previous high
- Or 2.5:1 R:R minimum
**Position Size:**
- Can use full size (2% risk)
- High win rate regime
**Example Trade:**
```
Price: $100, pulls back to $98 (EMA20)
Entry: $98.50 (close above EMA)
Stop: $96.50 (2 ATR)
Target: $103.50 (2.5:1)
Risk: $2, Reward: $5
```
---
### BEAR TRENDING - Most Profitable Short Environment
**Strategy: Sell Every Rally**
**Entry Rules:**
1. Wait for bounce to EMA20 or SMA20
2. Look for RSI > 40
3. Enter when candle closes below MA
4. Confluence should be 2+
**Stop Loss:**
- Above the recent swing high
- Or 2 × ATR above entry
**Take Profit:**
- At previous low
- Or 2.5:1 R:R minimum
**Position Size:**
- Can use full size (2% risk)
- High win rate regime
**Example Trade:**
```
Price: $100, rallies to $102 (EMA20)
Entry: $101.50 (close below EMA)
Stop: $103.50 (2 ATR)
Target: $96.50 (2.5:1)
Risk: $2, Reward: $5
```
---
### BULL RANGING - Buy Low, Sell High
**Strategy: Range Trading (Long Bias)**
**Entry Rules:**
1. Wait for price at support zone
2. Look for RSI < 40
3. Enter on reversal candle
4. Confluence should be 1-2+
**Stop Loss:**
- Below support zone
- Tighter than trending (1.5 ATR)
**Take Profit:**
- At resistance zone
- Don't hold through resistance
**Position Size:**
- Reduce to 1-1.5% risk
- Lower win rate than trending
**Example Trade:**
```
Range: $95-$105
Entry: $96 (at support, RSI 35)
Stop: $94 (below support)
Target: $104 (at resistance)
Risk: $2, Reward: $8 (4:1)
```
---
### BEAR RANGING - Sell High, Buy Low
**Strategy: Range Trading (Short Bias)**
**Entry Rules:**
1. Wait for price at resistance zone
2. Look for RSI > 60
3. Enter on rejection candle
4. Confluence should be 1-2+
**Stop Loss:**
- Above resistance zone
- Tighter than trending (1.5 ATR)
**Take Profit:**
- At support zone
- Don't hold through support
**Position Size:**
- Reduce to 1-1.5% risk
- Lower win rate than trending
**Example Trade:**
```
Range: $95-$105
Entry: $104 (at resistance, RSI 65)
Stop: $106 (above resistance)
Target: $96 (at support)
Risk: $2, Reward: $8 (4:1)
```
---
### CONSOLIDATION - Wait for Breakout
**Strategy: Breakout Trading**
**Entry Rules:**
1. Identify consolidation range
2. Wait for VOLUME SURGE (1.5x+ avg)
3. Enter on close outside range
4. Direction must be clear
**Stop Loss:**
- Opposite side of range
- Or 2 ATR
**Take Profit:**
- Measure range height, project it
- Example: $10 range = $10 move expected
**Position Size:**
- Reduce to 1% risk
- 50% false breakout rate
**Example Trade:**
```
Consolidation: $98-$102 (4-point range)
Breakout: $102.50 (high volume)
Entry: $103
Stop: $100 (back in range)
Target: $107 (4-point range projected)
Risk: $3, Reward: $4
```
---
### CHAOS - STAY OUT!
**Strategy: Preservation**
**What to Do:**
- ❌ NO new positions
- ✅ Close existing positions if near entry
- ✅ Tighten stops on profitable trades
- ✅ Reduce position sizes dramatically
- ✅ Wait for regime to stabilize
**Why It's Dangerous:**
- Stop hunts are common
- Whipsaws everywhere
- News-driven volatility
- No technical reliability
- Even "perfect" setups fail
**When Does It End:**
- Volatility ratio drops < 1.5
- ADX starts rising (direction appears)
- Price respects support/resistance again
- Usually 1-5 days
---
## CONFLUENCE SYSTEM
### How It Works
The system scores each potential entry on 5 factors. More factors aligning = higher probability.
### Confluence Requirements by Regime
**Trending Regimes** (strictest):
- Minimum 2/5 required
- 3/5 = Good
- 4-5/5 = Excellent
**Ranging Regimes** (moderate):
- Minimum 1-2/5 required
- 2/5 = Good
- 3+/5 = Excellent
**Consolidation** (breakout only):
- Volume is most critical
- Direction confirmation
- Less confluence needed
### Adjusting Minimum Confluence
**If too few signals:**
- Lower from 2 to 1
- More trades, lower quality
**If too many false signals:**
- Raise from 2 to 3
- Fewer trades, higher quality
**Recommendation:**
- Start at 2
- Adjust based on win rate
- Aim for 55-65% win rate
---
## STRATEGY BACKTESTING
### Loading the Strategy
1. Copy `market_regime_strategy.pine`
2. Open Pine Editor in TradingView
3. Paste and "Add to Chart"
4. Strategy Tester tab opens at bottom
### Initial Settings
```
Risk Per Trade: 2%
ATR Stop Multiplier: 2.0
Reward:Risk Ratio: 2.5
Trade Longs: ✓
Trade Shorts: ✓
Trade Trending Only: ✗ (test both)
Avoid Chaos: ✓
Minimum Confluence: 2
```
### What to Look For
**Good Results:**
- Win Rate: 50-60%
- Profit Factor: 1.8-2.5
- Net Profit: Positive
- Max Drawdown: <20%
- Consistent equity curve
**Warning Signs:**
- Win Rate: <45% (too many losses)
- Profit Factor: <1.5 (barely profitable)
- Max Drawdown: >30% (too risky)
- Erratic equity curve (unstable)
### Testing Different Regimes
**Test 1: Trending Only**
```
Trade Trending Only: ✓
Result: Higher win rate, fewer trades
```
**Test 2: All Regimes**
```
Trade Trending Only: ✗
Result: More trades, potentially lower win rate
```
**Test 3: Long Only**
```
Trade Longs: ✓
Trade Shorts: ✗
Result: Works in bull markets
```
**Test 4: Short Only**
```
Trade Longs: ✗
Trade Shorts: ✓
Result: Works in bear markets
```
---
## SETTINGS OPTIMIZATION
### Key Parameters to Adjust
#### 1. Risk Per Trade (Most Important)
- **0.5%** = Very conservative
- **1.0%** = Conservative (recommended for beginners)
- **2.0%** = Moderate (recommended)
- **3.0%** = Aggressive
- **5.0%** = Very aggressive (not recommended)
**Impact:** Higher risk = higher returns BUT bigger drawdowns
#### 2. Reward:Risk Ratio
- **2:1** = More wins needed, hit target faster
- **2.5:1** = Balanced (recommended)
- **3:1** = Fewer wins needed, hold longer
- **4:1** = Very patient, best in trending
**Impact:** Higher R:R = can have lower win rate
#### 3. Minimum Confluence
- **1** = More signals, lower quality
- **2** = Balanced (recommended)
- **3** = Fewer signals, higher quality
- **4** = Very selective
- **5** = Almost never triggers
**Impact:** Higher = fewer but better trades
#### 4. ADX Thresholds
- **Trending: 20-30** (default 25)
- Lower = detect trends earlier
- Higher = only strong trends
- **Ranging: 15-25** (default 20)
- Lower = identify ranging earlier
- Higher = only weak trends
#### 5. Trend Period (SMA)
- **20-50** = Short-term trends
- **50** = Medium-term (default, recommended)
- **100-200** = Long-term trends
**Impact:** Longer period = slower regime changes, more stable
### Optimization Workflow
**Step 1: Baseline**
- Use all default settings
- Test on 3+ years
- Record: Win Rate, PF, Drawdown
**Step 2: Risk Optimization**
- Test 1%, 1.5%, 2%, 2.5%
- Find best risk-adjusted return
- Balance profit vs drawdown
**Step 3: R:R Optimization**
- Test 2:1, 2.5:1, 3:1
- Check which maximizes profit factor
- Consider holding time
**Step 4: Confluence Optimization**
- Test 1, 2, 3
- Find sweet spot for win rate
- Aim for 55-65% win rate
**Step 5: Regime Filter**
- Test with/without trend filter
- Test with/without chaos filter
- Find what works for your asset
---
## REAL TRADING EXAMPLES
### Example 1: Bull Trending - SPY
**Setup:**
- Regime: BULL TRENDING
- Price pulls back from $450 to $445
- EMA20 at $444
- RSI drops to 45
- Confluence: 4/5
**Entry:**
- Price closes at $445.50 (above EMA20)
- LONG signal appears
- Enter at $445.50
**Risk Management:**
- Stop: $443 (2 ATR = $2.50)
- Target: $451.75 (2.5:1 = $6.25)
- Risk: $2.50 per share
- Position: 80 shares (2% of $10k = $200 risk)
**Outcome:**
- Price rallies to $452 in 3 days
- Target hit
- Profit: $6.50 × 80 = $520
- Return: 2.6 × risk (excellent)
---
### Example 2: Bear Ranging - AAPL
**Setup:**
- Regime: BEAR RANGING
- Range: $165-$175
- Price rallies to $174
- Resistance at $175
- RSI at 68
- Confluence: 3/5
**Entry:**
- Rejection candle at $174
- SHORT signal appears
- Enter at $173.50
**Risk Management:**
- Stop: $176 (above resistance)
- Target: $166 (support)
- Risk: $2.50
- Position: 80 shares
**Outcome:**
- Price drops to $167 in 2 days
- Target hit
- Profit: $6.50 × 80 = $520
- Return: 2.6 × risk
---
### Example 3: Consolidation Breakout - BTC
**Setup:**
- Regime: CONSOLIDATION
- Range: $28,000 - $30,000
- Compressed for 2 weeks
- Volume declining
**Breakout:**
- Price breaks $30,000
- Volume surges 200%
- Close at $30,500
- LONG signal
**Entry:**
- Enter at $30,500
**Risk Management:**
- Stop: $29,500 (back in range)
- Target: $32,000 (range height = $2k)
- Risk: $1,000
- Position: 0.2 BTC ($200 risk on $10k)
**Outcome:**
- Price runs to $33,000
- Target exceeded
- Profit: $2,500 × 0.2 = $500
- Return: 2.5 × risk
---
### Example 4: Avoiding Chaos - Tesla
**Setup:**
- Regime: BULL TRENDING
- LONG position from $240
- Elon tweets something crazy
- Regime changes to CHAOS
**Action:**
- EXIT signal appears
- Close position immediately
- Current price: $242 (small profit)
**Outcome:**
- Next 3 days: wild swings
- High $255, Low $230
- By staying out, avoided:
- Potential stop out
- Whipsaw losses
- Stress
**Result:**
- Small profit preserved
- Capital protected
- Re-enter when regime stabilizes
---
## ALERTS SETUP
### Available Alerts
1. **Bull Trending Regime** - Market goes bullish
2. **Bear Trending Regime** - Market goes bearish
3. **Chaos Regime** - High volatility, stay out
4. **Long Entry Signal** - Buy opportunity
5. **Short Entry Signal** - Sell opportunity
6. **Long Exit Signal** - Close long
7. **Short Exit Signal** - Close short
### How to Set Up
1. Click **⏰ (Alert)** icon in TradingView
2. Select **Condition**: Choose indicator + alert type
3. **Options**: Popup, Email, Webhook, etc.
4. **Message**: Customize notification
5. Click **Create**
### Recommended Alert Strategy
**For Active Traders:**
- Long Entry Signal
- Short Entry Signal
- Long Exit Signal
- Short Exit Signal
**For Position Traders:**
- Bull Trending Regime (enter longs)
- Bear Trending Regime (enter shorts)
- Chaos Regime (exit all)
**For Conservative:**
- Only regime change alerts
- Manually review entries
- More selective
---
## TIPS FOR SUCCESS
### 1. Start Small
- Paper trade first
- Then 0.5% risk
- Build to 1-2% over time
### 2. Follow the Regime
- Don't fight it
- Adapt your style
- Different tactics for each
### 3. Trust the Confluence
- 4-5/5 = Best trades
- 2-3/5 = Good trades
- 1/5 = Skip unless desperate
### 4. Respect Exits
- Don't hope and hold
- Cut losses quickly
- Take profits at targets
### 5. Avoid Chaos
- Seriously, just stay out
- Protect your capital
- Wait for clarity
### 6. Keep a Journal
- Record every trade
- Note regime and confluence
- Review weekly
- Learn patterns
### 7. Backtest Thoroughly
- 3+ years minimum
- Multiple market conditions
- Different assets
- Walk-forward test
### 8. Be Patient
- Best setups are rare
- 1-3 trades per week is normal
- Quality over quantity
- Compound over time
---
## COMMON QUESTIONS
**Q: How many trades per month should I expect?**
A: Depends on timeframe and settings. Daily chart: 5-15 trades/month. 4H chart: 15-30 trades/month.
**Q: What's a good win rate?**
A: 55-65% is excellent. 50-55% is good. Below 50% needs adjustment.
**Q: Should I trade all regimes?**
A: Beginners: Only trending. Intermediate: Trending + ranging. Advanced: All except chaos.
**Q: Can I use this on any timeframe?**
A: Best on Daily and 4H. Works on 1H with more noise. Not recommended <1H.
**Q: What if I'm in a trade and regime changes?**
A: Exit immediately (if using indicator) or let strategy handle it automatically.
**Q: How do I know if I'm over-optimizing?**
A: If results are perfect on one period but fail on another. Use walk-forward testing.
**Q: Should I always take 5/5 confluence trades?**
A: Yes, but they're rare (1-2/month). Don't wait only for these.
**Q: Can I combine this with other indicators?**
A: Yes, but keep it simple. RSI, MACD already included. Maybe add volume profile.
**Q: What assets work best?**
A: Liquid stocks, major crypto, futures. Avoid forex spot (use futures), penny stocks.
**Q: How long to hold positions?**
A: Trending: Days to weeks. Ranging: Hours to days. Breakout: Days. Let the regime guide you.
---
## FINAL THOUGHTS
This system gives you:
- ✅ Clear market context (regime)
- ✅ High-probability entries (confluence)
- ✅ Defined exits (automatic signals)
- ✅ Adaptable tactics (regime-specific)
- ✅ Backtestable results (strategy version)
**Success requires:**
- 📚 Understanding each regime
- 🎯 Following the signals
- 💪 Discipline to wait
- 🧠 Emotional control
- 📊 Proper risk management
**Start your journey:**
1. Load the indicator
2. Watch for 1 week (no trading)
3. Identify regime patterns
4. Paper trade for 1 month
5. Go live with small size
6. Scale up as you gain confidence
**Remember:** The market will always be here. There's no rush. Master one regime at a time, and you'll be profitable in all conditions!
Good luck! 🚀
Razzere Cloned! EzAlgo V.8.1showBuySell = input(true, "Show Buy & Sell", group="BUY & SELL SIGNALS")
hassasiyet = input.float(3, "Hassasiyet (1-6)", 0.1, 99999, group="BUY & SELL SIGNALS")
percentStop = input.float(1, "Stop Loss % (0 to Disable)", 0, group="BUY & SELL SIGNALS")
offsetSignal = input.float(5, "Signals Offset", 0, group="BUY & SELL SIGNALS")
showRibbon = input(true, "Show Trend Ribbon", group="TREND RIBBON")
smooth1 = input.int(5, "Smoothing 1", 1, group="TREND RIBBON")
smooth2 = input.int(8, "Smoothing 2", 1, group="TREND RIBBON")
showreversal = input(true, "Show Reversals", group="REVERSAL SIGNALS")
showPdHlc = input(false, "Show P.D H/L/C", group="PREVIOUS DAY HIGH LOW CLOSE")
lineColor = input.color(color.yellow, "Line Colors", group="PREVIOUS DAY HIGH LOW CLOSE")
lineWidth = input.int(1, "Width Lines", group="PREVIOUS DAY HIGH LOW CLOSE")
lineStyle = input.string("Solid", "Line Style", )
labelSize = input.string("normal", "Label Text Size", )
labelColor = input.color(color.yellow, "Label Text Colors")
showEmas = input(false, "Show EMAs", group="EMA")
srcEma1 = input(close, "Source EMA 1")
lenEma1 = input.int(7, "Length EMA 1", 1)
srcEma2 = input(close, "Source EMA 2")
lenEma2 = input.int(21, "Length EMA 2", 1)
srcEma3 = input(close, "Source EMA 3")
lenEma3 = input.int(144, "Length EMA 3", 1)
showSwing = input(false, "Show Swing Points", group="SWING POINTS")
prdSwing = input.int(10, "Swing Point Period", 2, group="SWING POINTS")
colorPos = input(color.new(color.green, 50), "Positive Swing Color")
colorNeg = input(color.new(color.red, 50), "Negative Swing Color")
showDashboard = input(true, "Show Dashboard", group="TREND DASHBOARD")
locationDashboard = input.string("Middle Right", "Table Location", , group="TREND DASHBOARD")
tableTextColor = input(color.white, "Table Text Color", group="TREND DASHBOARD")
tableBgColor = input(#2A2A2A, "Table Background Color", group="TREND DASHBOARD")
sizeDashboard = input.string("Normal", "Table Size", , group="TREND DASHBOARD")
showRevBands = input.bool(true, "Show Reversal Bands", group="REVERSAL BANDS")
lenRevBands = input.int(30, "Length", group="REVERSAL BANDS")
// Fonksiyonlar
smoothrng(x, t, m) =>
wper = t * 2 - 1
avrng = ta.ema(math.abs(x - x ), t)
smoothrng = ta.ema(avrng, wper) * m
rngfilt(x, r) =>
rngfilt = x
rngfilt := x > nz(rngfilt ) ? x - r < nz(rngfilt ) ? nz(rngfilt ) : x - r : x + r > nz(rngfilt ) ? nz(rngfilt ) : x + r
percWidth(len, perc) => (ta.highest(len) - ta.lowest(len)) * perc / 100
securityNoRep(sym, res, src) => request.security(sym, res, src, barmerge.gaps_off, barmerge.lookahead_on)
swingPoints(prd) =>
pivHi = ta.pivothigh(prd, prd)
pivLo = ta.pivotlow (prd, prd)
last_pivHi = ta.valuewhen(pivHi, pivHi, 1)
last_pivLo = ta.valuewhen(pivLo, pivLo, 1)
hh = pivHi and pivHi > last_pivHi ? pivHi : na
lh = pivHi and pivHi < last_pivHi ? pivHi : na
hl = pivLo and pivLo > last_pivLo ? pivLo : na
ll = pivLo and pivLo < last_pivLo ? pivLo : na
f_chartTfInMinutes() =>
float _resInMinutes = timeframe.multiplier * (
timeframe.isseconds ? 1 :
timeframe.isminutes ? 1. :
timeframe.isdaily ? 60. * 24 :
timeframe.isweekly ? 60. * 24 * 7 :
timeframe.ismonthly ? 60. * 24 * 30.4375 : na)
f_kc(src, len, hassasiyet) =>
basis = ta.sma(src, len)
span = ta.atr(len)
wavetrend(src, chlLen, avgLen) =>
esa = ta.ema(src, chlLen)
d = ta.ema(math.abs(src - esa), chlLen)
ci = (src - esa) / (0.015 * d)
wt1 = ta.ema(ci, avgLen)
wt2 = ta.sma(wt1, 3)
f_top_fractal(src) => src < src and src < src and src > src and src > src
f_bot_fractal(src) => src > src and src > src and src < src and src < src
f_fractalize (src) => f_top_fractal(src) ? 1 : f_bot_fractal(src) ? -1 : 0
f_findDivs(src, topLimit, botLimit) =>
fractalTop = f_fractalize(src) > 0 and src >= topLimit ? src : na
fractalBot = f_fractalize(src) < 0 and src <= botLimit ? src : na
highPrev = ta.valuewhen(fractalTop, src , 0)
highPrice = ta.valuewhen(fractalTop, high , 0)
lowPrev = ta.valuewhen(fractalBot, src , 0)
lowPrice = ta.valuewhen(fractalBot, low , 0)
bearSignal = fractalTop and high > highPrice and src < highPrev
bullSignal = fractalBot and low < lowPrice and src > lowPrev
// Bileşen...
source = close
smrng1 = smoothrng(source, 27, 1.5)
smrng2 = smoothrng(source, 55, hassasiyet)
smrng = (smrng1 + smrng2) / 2
filt = rngfilt(source, smrng)
up = 0.0, up := filt > filt ? nz(up ) + 1 : filt < filt ? 0 : nz(up )
dn = 0.0, dn := filt < filt ? nz(dn ) + 1 : filt > filt ? 0 : nz(dn )
bullCond = bool(na), bullCond := source > filt and source > source and up > 0 or source > filt and source < source and up > 0
bearCond = bool(na), bearCond := source < filt and source < source and dn > 0 or source < filt and source > source and dn > 0
lastCond = 0, lastCond := bullCond ? 1 : bearCond ? -1 : lastCond
bull = bullCond and lastCond == -1
bear = bearCond and lastCond == 1
countBull = ta.barssince(bull)
countBear = ta.barssince(bear)
trigger = nz(countBull, bar_index) < nz(countBear, bar_index) ? 1 : 0
ribbon1 = ta.sma(close, smooth1)
ribbon2 = ta.sma(close, smooth2)
rsi = ta.rsi(close, 21)
rsiOb = rsi > 70 and rsi > ta.ema(rsi, 10)
rsiOs = rsi < 30 and rsi < ta.ema(rsi, 10)
dHigh = securityNoRep(syminfo.tickerid, "D", high )
dLow = securityNoRep(syminfo.tickerid, "D", low )
dClose = securityNoRep(syminfo.tickerid, "D", close )
ema1 = ta.ema(srcEma1, lenEma1)
ema2 = ta.ema(srcEma2, lenEma2)
ema3 = ta.ema(srcEma3, lenEma3)
= swingPoints(prdSwing)
ema = ta.ema(close, 144)
emaBull = close > ema
equal_tf(res) => str.tonumber(res) == f_chartTfInMinutes() and not timeframe.isseconds
higher_tf(res) => str.tonumber(res) > f_chartTfInMinutes() or timeframe.isseconds
too_small_tf(res) => (timeframe.isweekly and res=="1") or (timeframe.ismonthly and str.tonumber(res) < 10)
securityNoRep1(sym, res, src) =>
bool bull_ = na
bull_ := equal_tf(res) ? src : bull_
bull_ := higher_tf(res) ? request.security(sym, res, src, barmerge.gaps_off, barmerge.lookahead_on) : bull_
bull_array = request.security_lower_tf(syminfo.tickerid, higher_tf(res) ? str.tostring(f_chartTfInMinutes()) + (timeframe.isseconds ? "S" : "") : too_small_tf(res) ? (timeframe.isweekly ? "3" : "10") : res, src)
if array.size(bull_array) > 1 and not equal_tf(res) and not higher_tf(res)
bull_ := array.pop(bull_array)
array.clear(bull_array)
bull_
TF1Bull = securityNoRep1(syminfo.tickerid, "1" , emaBull)
TF3Bull = securityNoRep1(syminfo.tickerid, "3" , emaBull)
TF5Bull = securityNoRep1(syminfo.tickerid, "5" , emaBull)
TF15Bull = securityNoRep1(syminfo.tickerid, "15" , emaBull)
TF30Bull = securityNoRep1(syminfo.tickerid, "30" , emaBull)
TF60Bull = securityNoRep1(syminfo.tickerid, "60" , emaBull)
TF120Bull = securityNoRep1(syminfo.tickerid, "120" , emaBull)
TF240Bull = securityNoRep1(syminfo.tickerid, "240" , emaBull)
TF480Bull = securityNoRep1(syminfo.tickerid, "480" , emaBull)
TFDBull = securityNoRep1(syminfo.tickerid, "1440", emaBull)
= f_kc(close, lenRevBands, 3)
= f_kc(close, lenRevBands, 4)
= f_kc(close, lenRevBands, 5)
= f_kc(close, lenRevBands, 6)
= wavetrend(hlc3, 9, 12)
= f_findDivs(wt2, 15, -40)
= f_findDivs(wt2, 45, -65)
wtDivBull = wtDivBull1 or wtDivBull2
wtDivBear = wtDivBear1 or wtDivBear2
// Renkler
cyan = #00DBFF, cyan30 = color.new(cyan, 70)
pink = #E91E63, pink30 = color.new(pink, 70)
red = #FF5252, red30 = color.new(red , 70)
// Plotlar
off = percWidth(300, offsetSignal)
plotshape(showBuySell and bull ? low - off : na, "Buy Label" , shape.labelup , location.absolute, cyan, 0, "Buy" , color.white, size=size.normal)
plotshape(showBuySell and bear ? high + off : na, "Sell Label", shape.labeldown, location.absolute, pink, 0, "Sell", color.white, size=size.normal)
plotshape(ta.crossover(wt1, wt2) and wt2 <= -53, "Mild Buy" , shape.xcross, location.belowbar, cyan, size=size.tiny)
plotshape(ta.crossunder(wt1, wt2) and wt2 >= 53, "Mild Sell", shape.xcross, location.abovebar, pink, size=size.tiny)
plotshape(wtDivBull, "Divergence Buy ", shape.triangleup , location.belowbar, cyan, size=size.tiny)
plotshape(wtDivBear, "Divergence Sell", shape.triangledown, location.abovebar, pink, size=size.tiny)
barcolor(up > dn ? cyan : pink)
plotshape(showreversal and rsiOs, "Reversal Buy" , shape.diamond, location.belowbar, cyan30, size=size.tiny)
plotshape(showreversal and rsiOb, "Reversal Sell", shape.diamond, location.abovebar, pink30, size=size.tiny)
lStyle = lineStyle == "Solid" ? line.style_solid : lineStyle == "Dotted" ? line.style_dotted : line.style_dashed
lSize = labelSize == "small" ? size.small : labelSize == "normal" ? size.normal : size.large
dHighLine = showPdHlc ? line.new(bar_index, dHigh, bar_index + 1, dHigh , xloc.bar_index, extend.both, lineColor, lStyle, lineWidth) : na, line.delete(dHighLine )
dLowLine = showPdHlc ? line.new(bar_index, dLow , bar_index + 1, dLow , xloc.bar_index, extend.both, lineColor, lStyle, lineWidth) : na, line.delete(dLowLine )
dCloseLine = showPdHlc ? line.new(bar_index, dClose, bar_index + 1, dClose, xloc.bar_index, extend.both, lineColor, lStyle, lineWidth) : na, line.delete(dCloseLine )
dHighLabel = showPdHlc ? label.new(bar_index + 100, dHigh , "P.D.H", xloc.bar_index, yloc.price, #000000, label.style_none, labelColor, lSize) : na, label.delete(dHighLabel )
dLowLabel = showPdHlc ? label.new(bar_index + 100, dLow , "P.D.L", xloc.bar_index, yloc.price, #000000, label.style_none, labelColor, lSize) : na, label.delete(dLowLabel )
dCloseLabel = showPdHlc ? label.new(bar_index + 100, dClose, "P.D.C", xloc.bar_index, yloc.price, #000000, label.style_none, labelColor, lSize) : na, label.delete(dCloseLabel )
plot(showEmas ? ema1 : na, "EMA 1", color.green , 2)
plot(showEmas ? ema2 : na, "EMA 2", color.purple, 2)
plot(showEmas ? ema3 : na, "EMA 3", color.yellow, 2)
plotshape(showSwing ? hh : na, "", shape.triangledown, location.abovebar, color.new(color.green, 50), -prdSwing, "HH", colorPos, false)
plotshape(showSwing ? hl : na, "", shape.triangleup , location.belowbar, color.new(color.green, 50), -prdSwing, "HL", colorPos, false)
plotshape(showSwing ? lh : na, "", shape.triangledown, location.abovebar, color.new(color.red , 50), -prdSwing, "LH", colorNeg, false)
plotshape(showSwing ? ll : na, "", shape.triangleup , location.belowbar, color.new(color.red , 50), -prdSwing, "LL", colorNeg, false)
srcStop = close
atrBand = srcStop * (percentStop / 100)
atrStop = trigger ? srcStop - atrBand : srcStop + atrBand
lastTrade(src) => ta.valuewhen(bull or bear, src, 0)
entry_y = lastTrade(srcStop)
stop_y = lastTrade(atrStop)
tp1_y = (entry_y - lastTrade(atrStop)) * 1 + entry_y
tp2_y = (entry_y - lastTrade(atrStop)) * 2 + entry_y
tp3_y = (entry_y - lastTrade(atrStop)) * 3 + entry_y
labelTpSl(y, txt, color) =>
label labelTpSl = percentStop != 0 ? label.new(bar_index + 1, y, txt, xloc.bar_index, yloc.price, color, label.style_label_left, color.white, size.normal) : na
label.delete(labelTpSl )
labelTpSl(entry_y, "Entry: " + str.tostring(math.round_to_mintick(entry_y)), color.gray)
labelTpSl(stop_y , "Stop Loss: " + str.tostring(math.round_to_mintick(stop_y)), color.red)
labelTpSl(tp1_y, "Take Profit 1: " + str.tostring(math.round_to_mintick(tp1_y)), color.green)
labelTpSl(tp2_y, "Take Profit 2: " + str.tostring(math.round_to_mintick(tp2_y)), color.green)
labelTpSl(tp3_y, "Take Profit 3: " + str.tostring(math.round_to_mintick(tp3_y)), color.green)
lineTpSl(y, color) =>
line lineTpSl = percentStop != 0 ? line.new(bar_index - (trigger ? countBull : countBear) + 4, y, bar_index + 1, y, xloc.bar_index, extend.none, color, line.style_solid) : na
line.delete(lineTpSl )
lineTpSl(entry_y, color.gray)
lineTpSl(stop_y, color.red)
lineTpSl(tp1_y, color.green)
lineTpSl(tp2_y, color.green)
lineTpSl(tp3_y, color.green)
var dashboard_loc = locationDashboard == "Top Right" ? position.top_right : locationDashboard == "Middle Right" ? position.middle_right : locationDashboard == "Bottom Right" ? position.bottom_right : locationDashboard == "Top Center" ? position.top_center : locationDashboard == "Middle Center" ? position.middle_center : locationDashboard == "Bottom Center" ? position.bottom_center : locationDashboard == "Top Left" ? position.top_left : locationDashboard == "Middle Left" ? position.middle_left : position.bottom_left
var dashboard_size = sizeDashboard == "Large" ? size.large : sizeDashboard == "Normal" ? size.normal : sizeDashboard == "Small" ? size.small : size.tiny
var dashboard = showDashboard ? table.new(dashboard_loc, 2, 15, tableBgColor, #000000, 2, tableBgColor, 1) : na
dashboard_cell(column, row, txt, signal=false) => table.cell(dashboard, column, row, txt, 0, 0, signal ? #000000 : tableTextColor, text_size=dashboard_size)
dashboard_cell_bg(column, row, col) => table.cell_set_bgcolor(dashboard, column, row, col)
if barstate.islast and showDashboard
dashboard_cell(0, 0 , "EzAlgo")
dashboard_cell(0, 1 , "Current Position")
dashboard_cell(0, 2 , "Current Trend")
dashboard_cell(0, 3 , "Volume")
dashboard_cell(0, 4 , "Timeframe")
dashboard_cell(0, 5 , "1 min:")
dashboard_cell(0, 6 , "3 min:")
dashboard_cell(0, 7 , "5 min:")
dashboard_cell(0, 8 , "15 min:")
dashboard_cell(0, 9 , "30 min:")
dashboard_cell(0, 10, "1 H:")
dashboard_cell(0, 11, "2 H:")
dashboard_cell(0, 12, "4 H:")
dashboard_cell(0, 13, "8 H:")
dashboard_cell(0, 14, "Daily:")
dashboard_cell(1, 0 , "V.8.1")
dashboard_cell(1, 1 , trigger ? "Buy" : "Sell", true), dashboard_cell_bg(1, 1, trigger ? color.green : color.red)
dashboard_cell(1, 2 , emaBull ? "Bullish" : "Bearish", true), dashboard_cell_bg(1, 2, emaBull ? color.green : color.red)
dashboard_cell(1, 3 , str.tostring(volume))
dashboard_cell(1, 4 , "Trends")
dashboard_cell(1, 5 , TF1Bull ? "Bullish" : "Bearish", true), dashboard_cell_bg(1, 5 , TF1Bull ? color.green : color.red)
dashboard_cell(1, 6 , TF3Bull ? "Bullish" : "Bearish", true), dashboard_cell_bg(1, 6 , TF3Bull ? color.green : color.red)
dashboard_cell(1, 7 , TF5Bull ? "Bullish" : "Bearish", true), dashboard_cell_bg(1, 7 , TF5Bull ? color.green : color.red)
dashboard_cell(1, 8 , TF15Bull ? "Bullish" : "Bearish", true), dashboard_cell_bg(1, 8 , TF15Bull ? color.green : color.red)
dashboard_cell(1, 9 , TF30Bull ? "Bullish" : "Bearish", true), dashboard_cell_bg(1, 9 , TF30Bull ? color.green : color.red)
dashboard_cell(1, 10, TF60Bull ? "Bullish" : "Bearish", true), dashboard_cell_bg(1, 10, TF60Bull ? color.green : color.red)
dashboard_cell(1, 11, TF120Bull ? "Bullish" : "Bearish", true), dashboard_cell_bg(1, 11, TF120Bull ? color.green : color.red)
dashboard_cell(1, 12, TF240Bull ? "Bullish" : "Bearish", true), dashboard_cell_bg(1, 12, TF240Bull ? color.green : color.red)
dashboard_cell(1, 13, TF480Bull ? "Bullish" : "Bearish", true), dashboard_cell_bg(1, 13, TF480Bull ? color.green : color.red)
dashboard_cell(1, 14, TFDBull ? "Bullish" : "Bearish", true), dashboard_cell_bg(1, 14, TFDBull ? color.green : color.red)
plot(showRevBands ? upperKC1 : na, "Rev.Zone Upper 1", red30)
plot(showRevBands ? upperKC2 : na, "Rev.Zone Upper 2", red30)
plot(showRevBands ? upperKC3 : na, "Rev.Zone Upper 3", red30)
plot(showRevBands ? upperKC4 : na, "Rev.Zone Upper 4", red30)
plot(showRevBands ? lowerKC4 : na, "Rev.Zone Lower 4", cyan30)
plot(showRevBands ? lowerKC3 : na, "Rev.Zone Lower 3", cyan30)
plot(showRevBands ? lowerKC2 : na, "Rev.Zone Lower 2", cyan30)
plot(showRevBands ? lowerKC1 : na, "Rev.Zone Lower 1", cyan30)
fill(plot(showRibbon ? ribbon1 : na, "", na, editable=false), plot(showRibbon ? ribbon2 : na, "", na, editable=false), ribbon1 > ribbon2 ? cyan30 : pink30, "Ribbon Fill Color")
// Alarmlar
alert01 = ta.crossover(ribbon1, ribbon2)
alert02 = bull
alert03 = wtDivBull
alert04 = wtDivBear
alert05 = bull or bear
alert06 = ta.crossover(wt1, wt2) and wt2 <= -53
alert07 = ta.crossunder(wt1, wt2) and wt2 >= 53
alert08 = ta.crossunder(ribbon1, ribbon2)
alert09 = rsiOb or rsiOs
alert10 = bear
alert11 = ta.cross(ribbon1, ribbon2)
alerts(sym) =>
if alert02 or alert03 or alert04 or alert06 or alert07 or alert10
alert_text = alert02 ? "Buy Signal EzAlgo" : alert03 ? "Strong Buy Signal EzAlgo" : alert04 ? "Strong Sell Signal EzAlgo" : alert06 ? "Mild Buy Signal EzAlgo" : alert07 ? "Mild Sell Signal EzAlgo" : "Sell Signal EzAlgo"
alert(alert_text, alert.freq_once_per_bar_close)
alerts(syminfo.tickerid)
alertcondition(alert01, "Blue Trend Ribbon Alert", "Blue Trend Ribbon, TimeFrame={{interval}}")
alertcondition(alert02, "Buy Signal", "Buy Signal EzAlgo")
alertcondition(alert03, "Divergence Buy Alert", "Strong Buy Signal EzAlgo, TimeFrame={{interval}}")
alertcondition(alert04, "Divergence Sell Alert", "Strong Sell Signal EzAlgo, TimeFrame={{interval}}")
alertcondition(alert05, "Either Buy or Sell Signal", "EzAlgo Signal")
alertcondition(alert06, "Mild Buy Alert", "Mild Buy Signal EzAlgo, TimeFrame={{interval}}")
alertcondition(alert07, "Mild Sell Alert", "Mild Sell Signal EzAlgo, TimeFrame={{interval}}")
alertcondition(alert08, "Red Trend Ribbon Alert", "Red Trend Ribbon, TimeFrame={{interval}}")
alertcondition(alert09, "Reversal Signal", "Reversal Signal")
alertcondition(alert10, "Sell Signal", "Sell Signal EzAlgo")
alertcondition(alert11, "Trend Ribbon Color Change Alert", "Trend Ribbon Color Change, TimeFrame={{interval}}")
ORB Pro - NY Opening Range Breakout [Elev8+]**ORB Pro - NY Opening Range Breakout ** is a comprehensive, professional-grade toolkit designed for intraday traders who rely on the **Opening Range Breakout (ORB)** strategy.
Unlike standard ORB indicators that simply draw lines, this suite offers a complete dashboard-driven system that monitors **four distinct sessions** simultaneously, providing real-time status updates and precision alerts.
### 🎯 What is the Opening Range Breakout (ORB)?
The Opening Range is the price range established during the first period of the trading session (e.g., the first 15 or 30 minutes). This period represents the initial balance between buyers and sellers. A breakout from this range often signals the likely trend direction for the remainder of the session.
### 🚀 Key Features
**1. Multi-ORB Monitoring**
Stop switching settings constantly. This suite monitors four key ranges at once:
* **Pre-Market 15m** (08:00 – 08:15 ET)
* **Pre-Market 30m** (08:00 – 08:30 ET)
* **NY Cash Open 15m** (09:30 – 09:45 ET)
* **NY Cash Open 30m** (09:30 – 10:00 ET)
**2. Smart Status Dashboard**
A compact panel in the bottom-right corner gives you the live state of every session:
* **⏳ Waiting:** The session has not started yet.
* **⚡ Forming:** The range is currently being built.
* **↔️ Range:** The range has formed, but price is still contained within the range.
* **🚀 BULL / 📉 BEAR:** A confirmed breakout has occurred.
* **⛔ OFF:** The session is disabled in settings.
**3. "Dynamic Resolution" Technology**
This is a unique pro feature.
* **Precision:** The script *always* calculates the High/Low levels using 1-minute data, ensuring your support/resistance lines are pixel-perfect regardless of your chart timeframe.
* **Flexibility:** Breakout signals (Alerts/Labels) are triggered based on your *current* chart timeframe. This allows you to trade a 5m or 15m breakout strategy while keeping 1m-level precision on your levels.
**4. Visual Clarity**
* **Breakout Labels:** Automatically plots "BULL" or "BEAR" labels on the exact candle that confirms a breakout.
* **Profit Targets:** Optional toggle to show 1x and 2x profit targets projected from the breakout level.
* **Time-Bound Signals:** Signals are strictly time-bound to the active window to prevent late, low-quality alerts.
### 🛠️ How to Use
1. **Add to Chart:** Works best on intraday timeframes (1m, 5m, 15m).
2. **Configure:** Enable the sessions you trade (e.g., NY 15m) in the settings.
3. **Wait for Forming:** Watch the box form live. The dashboard will show "⚡ Forming".
4. **Trade the Break:** Wait for a candle **Close** outside the range. The dashboard will flip to "BULL" or "BEAR" and a label will appear.
5. **Manage Risk:** Use the opposite side of the range or the midline as your stop loss.
### ⚙️ Settings Overview
* **Global Settings:** Toggle forming boxes, dashboard, and label visibility.
* **Breakout Method:** Choose between **Close** (safer) or **Wick** (aggressive) for signal triggers.
* **Session Groups:** Individually enable/disable the 4 distinct sessions and customize their colors/styles.
---
*Disclaimer: This tool is for educational and analytical purposes only. Past performance of a strategy does not guarantee future results. Always manage your risk.*
Al Brooks - Bar CountIndicator Purpose:
This indicator displays bar counts on the chart to help traders identify important time nodes and cycle transitions
Features smart session filtering with automatic futures/stock detection and appropriate trading session counting
Core Features:
Smart asset detection: Auto-detect futures and stocks
Session filter toggle: Choose all-day or session-specific counting
Auto timezone handling: Chicago time for futures, NY time for stocks
Flexible display control: Customizable display frequency and label size
Session Settings:
8:30-15:15 (CT) / Futures mode: Chicago time 8:30-15:15 (CT)
9:30-16:00 (ET) / Stock mode: New York time 9:30-16:00 (ET)
All-day mode: Count from first bar of the day
Timeframe Correspondence:
Multiples of 3: Correspond to 15-minute chart update cycles
Multiples of 12: Correspond to 1-hour chart update cycles
18: Key nodes, important time turning points
DR/IDR Break .5 TPDR/IDR Extension Breakout with Custom Stop
This strategy is a systematic, counter-trend, and momentum-based system designed for intraday trading. It operates on the principle of an Opening Range Breakout (ORB), utilizing the initial market consolidation to project high-probability targets, while offering multiple methods for managing risk.
1. Market Identification (The Opening Range)
The strategy begins by defining the market's initial boundaries and volatility:
Session Window: The strategy calculates the Opening Range (OR) over a user-defined time period (default: 9:30 AM to 10:30 AM New York Time).
ORB Levels: Two key price levels are established and locked once the time window closes:
Wick High/Low: The absolute highest and lowest prices of the session. These serve as the entry trigger lines.
Body High/Low (Shaded Range): The highest and lowest open/close prices of the session. The height of this range is used to calculate the Take Profit and Stop Loss levels.
2. Entry Rule (The Breakout)
The strategy is passive until the range is violated, looking for a strong move out of the consolidation area.
Trigger Condition: A trade is signaled when a candle closes either:
Above the Wick High (for a Long entry).
Below the Wick Low (for a Short entry).
Execution: The entry is a Market Order executed on the candle that meets the trigger condition, subject to a user-defined Entry Delay (default 0 bars, meaning the entry is taken immediately upon the breakout candle's close).
Direction Control: The user can select to trade Long Only, Short Only, or Both.
3. Exit and Risk Management
All trades are placed with simultaneous Take Profit and Stop Loss orders (a bracket order) once the entry is filled.
A. Take Profit (TP)
The Take Profit is set at the 0.5 Extension of the Shaded Range (Body Range).
Calculation: The distance from the Body High/Low to the TP level is exactly 50% of the total height of the Shaded Range.
B. Stop Loss (SL)
The Stop Loss is dynamically calculated based on a user-selected method for risk control:
Range 0.5 (Body Range): The Stop Loss is placed an equal distance (0.5 times the Body Range height) outside the opposite side of the Body Range.
Example (Long): If entry is above the Wick High, the SL is set 0.5 times the Body Range height below the Body Low.
ATR Multiple: The Stop Loss distance is determined by the asset's recent volatility.
Calculation: The distance is calculated as a user-defined Multiplier (default 2.0) times the Average True Range (ATR).
Recent Swing Low/High: The Stop Loss is placed based on a structural level defined by recent price action.
Long Entry: SL is placed at the Lowest Swing Low within a user-defined lookback period.
Short Entry: SL is placed at the Highest Swing High within a user-defined lookback period.
Summary of Workflow
The market sets the Wick and Body boundaries (e.g., 9:30–10:30 AM).
Price breaks and closes beyond a Wick boundary, triggering a signal.
The trade enters after the specified delay.
A bracket order is placed: TP is fixed at the 0.5 Extension, and SL is set based on the user's chosen risk method.
The trade is closed upon reaching either the TP or the SL level.
DR/IDR, fractals, break + EMA Clouds + VWAPThis indicator is a powerful, multi-layered trading tool that combines three distinct forms of market analysis—volume, trend, and opening volatility—onto a single chart.
1. Opening Range Breakout (ORB) System
This is the foundation of the indicator, designed to capture the initial volatility and set key price boundaries for the trading day.
Time Focus: The indicator's primary analysis is centered on a specific, user-defined time period (default is 9:30 AM to 10:30 AM New York Time). Nothing related to the ORB drawing will appear on the chart before this session starts.
Wick High/Low (The Trigger): These lines track the absolute highest and lowest prices reached during the time window. They define the full extent of the initial range and are used to determine when a genuine breakout occurs.
Body High/Low (The Range & Targets): These lines track the highest and lowest open/close prices of the candles within the session. This area forms the central, shaded zone, representing the core consolidation area.
Range Shading: The background between the Body High and Body Low is shaded, but this visual feature only appears during the active forming time window (e.g., 9:30 AM to 10:30 AM) to maintain chart clarity.
Fractals: While the range is forming, the indicator detects 5-bar Williams Fractal patterns that occur inside the range. These small triangles (▲ or ▼) highlight minor reversal points established by the early trading action.
Breakout Signal: After the user-defined time window closes, the indicator waits. If a subsequent candle's price moves above the Wick High or below the Wick Low, a "BREAK" label is displayed on that candle. It is programmed to label only the first decisive break in each direction per day.
Extension Targets: When a breakout occurs, target lines are automatically projected above the Body High (for a bullish break) or below the Body Low (for a bearish break). The distance between these targets is calculated based on a user-defined fraction (e.g., 0.5 steps) of the total height of the Body Range.
Line Cutoff: For tidiness, you can set a "Stop Time" (e.g., 4:00 PM) after which the ORB lines will automatically disappear.
2. EMA Clouds (Trend and Momentum)
Four distinct Exponential Moving Average (EMA) clouds are plotted to provide a dynamic, multi-speed view of the market's trend and momentum.
Structure: Each "Cloud" is the shaded area between two EMAs (one shorter length and one longer length). The indicator includes four customizable pairs (defaulting to common settings like 8/9, 8/14, 34/50, and 14/21).
Trend Coloring: The clouds are color-coded:
Bullish (Greenish): The shorter EMA is trading above the longer EMA, signaling upward momentum.
Bearish (Reddish): The shorter EMA is trading below the longer EMA, signaling downward momentum.
Application: These clouds are used to confirm the overall market direction or identify potential zones of support and resistance.
3. Volume-Weighted Average Price (VWAP)
The VWAP is a crucial anchor for measuring the market's efficiency throughout the trading day.
Function: It calculates the average price of the asset, giving more weight to prices where higher volume was traded.
Context: It helps traders quickly determine if the current price is trading at a premium (above VWAP) or a discount (below VWAP) relative to the day's volume.
Reset: The VWAP line automatically resets at the beginning of each trading day.
Customization: The VWAP line can be toggled on or off, and its color and width are fully adjustable.
DR/IDR fractals break candle (ChadAnt)This indicator is an Opening Range Breakout (ORB) tool. It identifies the high and low price range established during a specific time window (e.g., the first hour of trading, 9:30–10:30 AM NY time). Once that time window closes, it watches for the price to "break out" of that range and projects profit targets based on the size of the initial range.
Key Features & How They Work
1. The Opening Range (The Box)
Time Window: The indicator waits for your specific start time (default 9:30 AM NY). It does not draw anything before this time.
The "Wicks": It tracks the absolute highest and lowest prices reached during this time (the Wicks). These act as your Breakout Triggers.
The "Body": It tracks the highest and lowest candle closes/opens during this time. This creates a shaded "zone" on your chart, representing the core area where most trading occurred.
Shading: To keep your chart clean, the background shading only appears during the forming time window.
2. Breakout Signals
Once the time window ends (e.g., 10:30 AM), the indicator "locks" the levels.
It then waits for a candle to move above the Wick High or below the Wick Low.
The Signal: When this happens, a label ("BREAK") appears on the chart.
Green Label: Bullish breakout (price went above the range).
Red Label: Bearish breakout (price went below the range).
Note: It only signals the first breakout of the day to avoid false alarms during choppy markets.
3. Extension Targets (Profit Levels)
When a breakout signal occurs, the indicator automatically draws target lines (extensions).
Calculation: These targets are based on the height of the "Body" zone (the shaded area).
Example: If your setting is 1.0, the indicator measures the height of the shaded body range and projects that exact distance above the breakout point. This is often used as a "Measured Move" target.
You can customize how many lines appear and how far apart they are (e.g., 0.5, 1.0, 1.5 times the range size).
4. Williams Fractals
During the opening range time, the indicator looks for specific price patterns called "Williams Fractals" (a 5-candle pattern that highlights potential turning points).
If a fractal peak or valley occurs inside your opening range, it marks it with a small triangle (▲ or ▼). Traders often use these as early signs of support or resistance forming inside the range.
5. Clean Visuals
Line Cutoff: You can set a "Stop Time" (e.g., 16:00 or 4:00 PM). The lines will stop drawing at that time so they don't clutter your chart overnight.
Gap Handling: The lines are programmed to break cleanly between days, so you don't see messy diagonal lines connecting yesterday's close to today's open.
Summary of Settings You Can Change
Session Time: When the range starts and ends.
Line Stop Time: When the lines should disappear for the day.
Visuals: Colors, line width, and style (solid, dotted, dashed).
Extensions: How many target lines to draw and the step size (e.g., 0.5x, 1.0x).
Fractals: Toggle the triangle icons on/off.
LuxyEnergyIndexThe Luxy Energy Index (LEI) library provides functions to measure price movement exhaustion by analyzing three dimensions: Extension (distance from fair value), Velocity (speed of movement), and Volume (confirmation level).
LEI answers a different question than traditional momentum indicators: instead of "how far has price gone?" (like RSI), LEI asks "how tired is this move?"
This library allows Pine Script developers to integrate LEI calculations into their own indicators and strategies.
How to Import
//@version=6
indicator("My Indicator")
import OrenLuxy/LuxyEnergyIndex/1 as LEI
Main Functions
`lei(src)` → float
Returns the LEI value on a 0-100 scale.
src (optional): Price source, default is `close`
Returns : LEI value (0-100) or `na` if insufficient data (first 50 bars)
leiValue = LEI.lei()
leiValue = LEI.lei(hlc3) // custom source
`leiDetailed(src)` → tuple
Returns LEI with all component values for detailed analysis.
= LEI.leiDetailed()
Returns:
`lei` - Final LEI value (0-100)
`extension` - Distance from VWAP in ATR units
`velocity` - 5-bar price change in ATR units
`volumeZ` - Volume Z-Score
`volumeModifier` - Applied modifier (1.0 = neutral)
`vwap` - VWAP value used
Component Functions
| Function | Description | Returns |
|-----------------------------------|---------------------------------|---------------|
| `calcExtension(src, vwap)` | Distance from VWAP / ATR | float |
| `calcVelocity(src)` | 5-bar price change / ATR | float |
| `calcVolumeZ()` | Volume Z-Score | float |
| `calcVolumeModifier(volZ)` | Volume modifier | float (≥1.0) |
| `getVWAP()` | Auto-detects asset type | float |
Signal Functions
| Function | Description | Returns |
|---------------------------------------------|----------------------------------|-----------|
| `isExhausted(lei, threshold)` | LEI ≥ threshold (default 70) | bool |
| `isSafe(lei, threshold)` | LEI ≤ threshold (default 30) | bool |
| `crossedExhaustion(lei, threshold)` | Crossed into exhaustion | bool |
| `crossedSafe(lei, threshold)` | Crossed into safe zone | bool |
Utility Functions
| Function | Description | Returns |
|----------------------------|-------------------------|-----------|
| `getZone(lei)` | Zone name | string |
| `getColor(lei)` | Recommended color | color |
| `hasEnoughHistory()` | Data check | bool |
| `minBarsRequired()` | Required bars | int (50) |
| `version()` | Library version | string |
Interpretation Guide
| LEI Range | Zone | Meaning |
|-------------|--------------|--------------------------------------------------|
| 0-30 | Safe | Low exhaustion, move may continue |
| 30-50 | Caution | Moderate exhaustion |
| 50-70 | Warning | Elevated exhaustion |
| 70-100 | Exhaustion | High exhaustion, increased reversal risk |
Example: Basic Usage
//@version=6
indicator("LEI Example", overlay=false)
import OrenLuxy/LuxyEnergyIndex/1 as LEI
// Get LEI value
leiValue = LEI.lei()
// Plot with dynamic color
plot(leiValue, "LEI", LEI.getColor(leiValue), 2)
// Reference lines
hline(70, "High", color.red)
hline(30, "Low", color.green)
// Alert on exhaustion
if LEI.crossedExhaustion(leiValue) and barstate.isconfirmed
alert("LEI crossed into exhaustion zone")
Technical Details
Fixed Parameters (by design):
Velocity Period: 5 bars
Volume Period: 20 bars
Z-Score Period: 50 bars
ATR Period: 14
Extension/Velocity Weights: 50/50
Asset Support:
Stocks/Forex: Uses Session VWAP (daily reset)
Crypto: Uses Rolling VWAP (50-bar window) - auto-detected
Edge Cases:
Returns `na` until 50 bars of history
Zero volume: Volume modifier defaults to 1.0 (neutral)
Credits and Acknowledgments
This library builds upon established technical analysis concepts:
VWAP - Industry standard volume-weighted price measure
ATR by J. Welles Wilder Jr. (1978) - Volatility normalization
Z-Score - Statistical normalization method
Volume analysis principles from Volume Spread Analysis (VSA) methodology
Disclaimer
This library is provided for **educational and informational purposes only**. It does not constitute financial advice. Past performance does not guarantee future results. The exhaustion readings are probabilistic indicators, not guarantees of price reversal. Always conduct your own research and use proper risk management when trading.
ALT Risk Metric StrategyHere's a professional write-up for your ALT Risk Strategy script:
ALT/BTC Risk Strategy - Multi-Crypto DCA with Bitcoin Correlation Analysis
Overview
This strategy uses Bitcoin correlation as a risk indicator to time entries and exits for altcoins. By analyzing how your chosen altcoin performs relative to Bitcoin, the strategy identifies optimal accumulation periods (when alt/BTC is oversold) and profit-taking opportunities (when alt/BTC is overbought). Perfect for traders who want to outperform Bitcoin by strategically timing altcoin positions.
Key Innovation: Why Alt/BTC Matters
Most traders focus solely on USD price, but Alt/BTC ratios reveal true altcoin strength:
When Alt/BTC is low → Altcoin is undervalued relative to Bitcoin (buy opportunity)
When Alt/BTC is high → Altcoin has outperformed Bitcoin (take profits)
This approach captures the rotation between BTC and alts that drives crypto cycles
Key Features
📊 Advanced Technical Analysis
RSI (60% weight): Primary momentum indicator on weekly timeframe
Long-term MA Deviation (35% weight): Measures distance from 150-period baseline
MACD (5% weight): Minor confirmation signal
EMA Smoothing: Filters noise while maintaining responsiveness
All calculations performed on Alt/BTC pairs for superior market timing
💰 3-Tier DCA System
Level 1 (Risk ≤ 70): Conservative entry, base allocation
Level 2 (Risk ≤ 50): Increased allocation, strong opportunity
Level 3 (Risk ≤ 30): Maximum allocation, extreme undervaluation
Continuous buying: Executes every bar while below threshold for true DCA behavior
Cumulative sizing: L3 triggers = L1 + L2 + L3 amounts combined
📈 Smart Profit Management
Sequential selling: Must complete L1 before L2, L2 before L3
Percentage-based exits: Sell portions of position, not fixed amounts
Auto-reset on re-entry: New buy signals reset sell progression
Prevents premature full exits during volatile conditions
🤖 3Commas Automation
Pre-configured JSON webhooks for Custom Signal Bots
Multi-exchange support: Binance, Coinbase, Kraken, Bitfinex, Bybit
Flexible quote currency: USD, USDT, or BUSD
Dynamic order sizing: Automatically adjusts to your tier thresholds
Full webhook documentation compliance
🎨 Multi-Asset Support
Pre-configured for popular altcoins:
ETH (Ethereum)
SOL (Solana)
ADA (Cardano)
LINK (Chainlink)
UNI (Uniswap)
XRP (Ripple)
DOGE
RENDER
Custom option for any other crypto
How It Works
Risk Metric Calculation (0-100 scale):
Fetches weekly Alt/BTC price data for stability
Calculates RSI, MACD, and deviation from 150-period MA
Normalizes MACD to 0-100 range using 500-bar lookback
Combines weighted components: (MACD × 0.05) + (RSI × 0.60) + (Deviation × 0.35)
Applies 5-period EMA smoothing for cleaner signals
Color-Coded Risk Zones:
Green (0-30): Extreme buying opportunity - Alt heavily oversold vs BTC
Lime/Yellow (30-70): Accumulation range - favorable risk/reward
Orange (70-85): Caution zone - consider taking initial profits
Red/Maroon (85-100+): Euphoria zone - aggressive profit-taking
Entry Logic:
Buys execute every candle when risk is below threshold
As risk decreases, position sizing automatically scales up
Example: If risk drops from 60→25, you'll be buying at L1 rate until it hits 50, then L2 rate, then L3 rate
Exit Logic:
Sells only trigger when in profit AND risk exceeds thresholds
Sequential execution ensures partial profit-taking
If new buy signal occurs before all sells complete, sell levels reset to L1
Configuration Guide
Choosing Your Altcoin:
Select crypto from dropdown (or use CUSTOM for unlisted coins)
Pick your exchange
Choose quote currency (USD, USDT, BUSD)
Risk Metric Tuning:
Long Term MA (default 150): Higher = more extreme signals, Lower = more frequent
RSI Length (default 10): Lower = more volatile, Higher = smoother
Smoothing (default 5): Increase for less noise, decrease for faster reaction
Buy Settings (Aggressive DCA Example):
L1 Threshold: 70 | Amount: $5
L2 Threshold: 50 | Amount: $6
L3 Threshold: 30 | Amount: $7
Total L3 buy = $18 per candle when deeply oversold
Sell Settings (Balanced Exit Example):
L1: 70 threshold, 25% position
L2: 85 threshold, 35% position
L3: 100 threshold, 40% position (final exit)
3Commas Setup
Bot Configuration:
Create Custom Signal Bot in 3Commas
Set trading pair to your altcoin/USD (e.g., ETH/USD, SOL/USDT)
Order size: Select "Send in webhook, quote" to use strategy's dollar amounts
Copy Bot UUID and Secret Token
Script Configuration:
Paste credentials into 3Commas section inputs
Check "Enable 3Commas Alerts"
Save and apply to chart
TradingView Alert:
Create Alert → Condition: "alert() function calls only"
Webhook URL: api.3commas.io
Enable "Webhook URL" checkbox
Expiration: Open-ended
Strategy Advantages
✅ Outperform Bitcoin: Designed specifically to beat BTC by timing alt rotations
✅ Capture Alt Seasons: Automatically accumulates when alts lag, sells when they pump
✅ Risk-Adjusted Sizing: Buys more when cheaper (better risk/reward)
✅ Emotional Discipline: Systematic approach removes fear and FOMO
✅ Multi-Asset: Run same strategy across multiple altcoins simultaneously
✅ Proven Indicators: Combines RSI, MACD, and MA deviation - battle-tested tools
Backtesting Insights
Optimal Timeframes:
Daily chart: Best for backtesting and signal generation
Weekly data is fetched internally regardless of display timeframe
Historical Performance Characteristics:
Accumulates heavily during bear markets and BTC dominance periods
Captures explosive altcoin rallies when BTC stagnates
Sequential selling preserves capital during extended downtrends
Works best on established altcoins with multi-year history
Risk Considerations:
Requires capital reserves for extended accumulation periods
Some altcoins may never recover if fundamentals deteriorate
Past correlation patterns may not predict future performance
Always size positions according to personal risk tolerance
Visual Interface
Indicator Panel Displays:
Dynamic color line: Green→Lime→Yellow→Orange→Red as risk increases
Horizontal threshold lines: Dashed lines mark your buy/sell levels
Entry/Exit labels: Green labels for buys, Orange/Red/Maroon for sells
Real-time risk value: Numerical display on price scale
Customization:
All threshold lines are adjustable via inputs
Color scheme clearly differentiates buy zones (green spectrum) from sell zones (red spectrum)
Line weights emphasize most extreme thresholds (L3 buy and L3 sell)
Strategy Philosophy
This strategy is built on the principle that altcoins move in cycles relative to Bitcoin. During Bitcoin rallies, alts often bleed against BTC (high sell, accumulate). When Bitcoin consolidates, alts pump (take profits). By measuring risk on the Alt/BTC chart instead of USD price, we time these rotations with precision.
The 3-tier system ensures you're always averaging in at better prices and scaling out at better prices, maximizing your Bitcoin-denominated returns.
Advanced Tips
Multi-Bot Strategy:
Run this on 5-10 different altcoins simultaneously to:
Diversify correlation risk
Capture whichever alt is pumping
Smooth equity curve through rotation
Pairing with BTC Strategy:
Use alongside the BTC DCA Risk Strategy for complete portfolio coverage:
BTC strategy for core holdings
ALT strategies for alpha generation
Rebalance between them based on BTC dominance
Threshold Calibration:
Check 2-3 years of historical data for your chosen alt
Note where risk metric sat during major bottoms (set buy thresholds)
Note where it peaked during euphoria (set sell thresholds)
Adjust for your risk tolerance and holding period
Credits
Strategy Development & 3Commas Integration: Claude AI (Anthropic)
Technical Analysis Framework: RSI, MACD, Moving Average theory
Implementation: pommesUNDwurst
Disclaimer
This strategy is for educational purposes only. Cryptocurrency trading involves substantial risk of loss. Altcoins are especially volatile and many fail completely. The strategy assumes liquid markets and reliable Alt/BTC price data. Always do your own research, understand the fundamentals of any asset you trade, and never risk more than you can afford to lose. Past performance does not guarantee future results. The authors are not financial advisors and assume no liability for trading decisions.
Additional Warning: Using leverage or trading illiquid altcoins amplifies risk significantly. This strategy is designed for spot trading of established cryptocurrencies with deep liquidity.
Tags: Altcoin, Alt/BTC, DCA, Risk Metric, Dollar Cost Averaging, 3Commas, ETH, SOL, Crypto Rotation, Bitcoin Correlation, Automated Trading, Alt Season
Feel free to modify any sections to better match your style or add specific backtesting results you've observed! 🚀Claude is AI and can make mistakes. Please double-check responses. Sonnet 4.5
