Simple Decesion Matrix Classification Algorithm [SS]Hello everyone,
It has been a while since I posted an indicator, so thought I would share this project I did for fun.
This indicator is an attempt to develop a pseudo Random Forest classification decision matrix model for Pinescript.
This is not a full, robust Random Forest model by any stretch of the imagination, but it is a good way to showcase how decision matrices can be applied to trading and within Pinescript.
As to not market this as something it is not, I am simply calling it the "Simple Decision Matrix Classification Algorithm". However, I have stolen most of the aspects of this machine learning algo from concepts of Random Forest modelling.
How it works:
With models like Support Vector Machines (SVM), Random Forest (RF) and Gradient Boosted Machine Learning (GBM), which are commonly used in Machine Learning Classification Tasks (MLCTs), this model operates similarity to the basic concepts shared amongst those modelling types. While it is not very similar to SVM, it is very similar to RF and GBM, in that it uses a "voting" system.
What do I mean by voting system?
How most classification MLAs work is by feeding an input dataset to an algorithm. The algorithm sorts this data, categorizes it, then introduces something called a confusion matrix (essentially sorting the data in no apparently order as to prevent over-fitting and introduce "confusion" to the algorithm to ensure that it is not just following a trend).
From there, the data is called upon based on current data inputs (so say we are using RSI and Z-Score, the current RSI and Z-Score is compared against other RSI's and Z-Scores that the model has saved). The model will process this information and each "tree" or "node" will vote. Then a cumulative overall vote is casted.
How does this MLA work?
This model accepts 2 independent variables. In order to keep things simple, this model was kept as a three node model. This means that there are 3 separate votes that go in to get the result. A vote is casted for each of the two independent variables and then a cumulative vote is casted for the overall verdict (the result of the model's prediction).
The model actually displays this system diagrammatically and it will likely be easier to understand if we look at the diagram to ground the example:
In the diagram, at the very top we have the classification variable that we are trying to predict. In this case, we are trying to predict whether there will be a breakout/breakdown outside of the normal ATR range (this is either yes or no question, hence a classification task).
So the question forms the basis of the input. The model will track at which points the ATR range is exceeded to the upside or downside, as well as the other variables that we wish to use to predict these exceedences. The ATR range forms the basis of all the data flowing into the model.
Then, at the second level, you will see we are using Z-Score and RSI to predict these breaks. The circle will change colour according to "feature importance". Feature importance basically just means that the indicator has a strong impact on the outcome. The stronger the importance, the more green it will be, the weaker, the more red it will be.
We can see both RSI and Z-Score are green and thus we can say they are strong options for predicting a breakout/breakdown.
So then we move down to the actual voting mechanisms. You will see the 2 pink boxes. These are the first lines of voting. What is happening here is the model is identifying the instances that are most similar and whether the classification task we have assigned (remember out ATR exceedance classifier) was either true or false based on RSI and Z-Score.
These are our 2 nodes. They both cast an individual vote. You will see in this case, both cast a vote of 1. The options are either 1 or 0. A vote of 1 means "Yes" or "Breakout likely".
However, this is not the only voting the model does. The model does one final vote based on the 2 votes. This is shown in the purple box. We can see the final vote and result at the end with the orange circle. It is 1 which means a range exceedance is anticipated and the most likely outcome.
The Data Table Component
The model has many moving parts. I have tried to represent the pivotal functions diagrammatically, but some other important aspects and background information must be obtained from the companion data table.
If we bring back our diagram from above:
We can see the data table to the left.
The data table contains 2 sections, one for each independent variable. In this case, our independent variables are RSI and Z-Score.
The data table will provide you with specifics about the independent variables, as well as about the model accuracy and outcome.
If we take a look at the first row, it simply indicates which independent variable it is looking at. If we go down to the next row where it reads "Weighted Impact", we can see a corresponding percent. The "weighted impact" is the amount of representation each independent variable has within the voting scheme. So in this case, we can see its pretty equal, 45% and 55%, This tells us that there is a slight higher representation of z-score than RSI but nothing to worry about.
If there was a major over-respresentation of greater than 30 or 40%, then the model would risk being skewed and voting too heavily in favour of 1 variable over the other.
If we move down from there we will see the next row reads "independent accuracy". The voting of each independent variable's accuracy is considered separately. This is one way we can determine feature importance, by seeing how well one feature augments the accuracy. In this case, we can see that RSI has the greatest importance, with an accuracy of around 87% at predicting breakouts. That makes sense as RSI is a momentum based oscillator.
Then if we move down one more, we will see what each independent feature (node) has voted for. In this case, both RSI and Z-Score voted for 1 (Breakout in our case).
You can weigh these in collaboration, but its always important to look at the final verdict of the model, which if we move down, we can see the "Model prediction" which is "Bullish".
If you are using the ATR breakout, the model cannot distinguish between "Bullish" or "Bearish", must that a "Breakout" is likely, either bearish or bullish. However, for the other classification tasks this model can do, the results are either Bullish or Bearish.
Using the Function:
Okay so now that all that technical stuff is out of the way, let's get into using the function. First of all this function innately provides you with 3 possible classification tasks. These include:
1. Predicting Red or Green Candle
2. Predicting Bullish / Bearish ATR
3. Predicting a Breakout from the ATR range
The possible independent variables include:
1. Stochastics,
2. MFI,
3. RSI,
4. Z-Score,
5. EMAs,
6. SMAs,
7. Volume
The model can only accept 2 independent variables, to operate within the computation time limits for pine execution.
Let's quickly go over what the numbers in the diagram mean:
The numbers being pointed at with the yellow arrows represent the cases the model is sorting and voting on. These are the most identical cases and are serving as the voting foundation for the model.
The numbers being pointed at with the pink candle is the voting results.
Extrapolating the functions (For Pine Developers:
So this is more of a feature application, so feel free to customize it to your liking and add additional inputs. But here are some key important considerations if you wish to apply this within your own code:
1. This is a BINARY classification task. The prediction must either be 0 or 1.
2. The function consists of 3 separate functions, the 2 first functions serve to build the confusion matrix and then the final "random_forest" function serves to perform the computations. You will need all 3 functions for implementation.
3. The model can only accept 2 independent variables.
I believe that is the function. Hopefully this wasn't too confusing, it is very statsy, but its a fun function for me! I use Random Forest excessively in R and always like to try to convert R things to Pinescript.
Hope you enjoy!
Safe trades everyone!
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ADX and DI Trend meter and status table IndicatorThis ADX (Average Directional Index) and DI (Directional Indicator) indicator helps identify:
Trend Direction & Strength:
LONG: +DI above -DI with ADX > 20
SHORT: -DI above +DI with ADX > 20
RANGE: ADX < 20 indicates choppy/sideways market
Trading Signals:
Bullish: +DI crosses above -DI (green triangle)
Bearish: -DI crosses below +DI (red triangle)
ADX Strength Levels:
Strong: ADX ≥ 50
Moderate: ADX 30-49
Weak: ADX 20-29
No Trend: ADX < 20
Best Uses:
Trend confirmation before entering trades
Identifying ranging vs trending markets
Exit signal when trend weakens
Works well on multiple timeframes
Most effective in combination with other indicators
The table displays current trend direction and ADX strength in real-time
Wick Length Display + Alert conditionsDescription of the Wick Length Display (Advanced) script
Originality and purpose of the script
The Wick Length Display (Advanced) script is an innovative tool for traders who want to gain detailed insights into the length of candle wicks. It stands out for its versatility and user-friendly customization options. It combines precise technical calculations with visual representation to provide important information about market movements and dynamics right on the chart.
Functionality
The script calculates and displays the length of the upper and lower wicks of each candle on the chart. It also provides additional visual cues such as:
• “Bull pressure”: When green candles do not have upper wicks, this indicates strong buying pressure.
• “Bear pressure”: When red candles do not have lower wicks, this indicates strong selling pressure.
• Threshold conditions: Only displays wicks that exceed a certain threshold (optional).
• Display in pips: Allows you to display wick lengths in pips, which is useful for forex traders.
How it works
The script analyzes each candle using the following calculations:
1. Wick length calculation:
◦ Upper wick length = High - (top of the body)
◦ Lower wick length = (bottom of the body) - Low
2. Display conditions:
◦ It distinguishes between bullish and bearish candles.
◦ It checks if the calculated wicks exceed the defined thresholds before displaying them.
3. Dynamic labels:
◦ Labels are placed above or below the respective candles.
◦ Size, color and type of labels are fully customizable.
4. Limitation of labels:
◦ To ensure clarity, a maximum number of labels is defined.
Usage
1. Customization:
◦ Open the script in the Pine Script Editor in TradingView.
◦ Use the input options to customize parameters such as color selection, label size, thresholds and other details according to your requirements.
2. Enable thresholds:
◦ Enable thresholds to show labels only for relevant wicks (default is 6).
◦ Define the minimum wick lengths for bullish (green) and bearish (red) candles.
3. Show in pips:
◦ Enable the “Show wick length in pips” option to show the results in pips (especially suitable for Forex).
4. Edit pressure labels:
◦ Turn the “Bull Pressure” and “Bear Pressure” features on or off depending on your analysis settings.
Concepts behind the calculations
• Technical market analysis: Wick lengths can indicate buying or selling pressure and provide important information on market psychology.
• Thresholds and filtering: The script uses thresholds to avoid visual overload and highlight only essential data.
• Label display: Dynamic labels improve chart readability and give the user instant feedback on market developments.
Usage
This script is great for:
• Intraday trading: Analyzing short-term movements using wick lengths.
• Forex trading: Tracking market momentum using the pip indicator.
• Swing trading: Identifying buying or selling pressure in key markets.
• Visual support: Ideal for traders who prefer a graphical display.
Description of the Wick Length Display (Advanced) script
Originality and purpose of the script
The Wick Length Display (Advanced) script is an innovative tool for traders who want to gain detailed insights into the length of candle wicks. It stands out for its versatility and user-friendly customization options. It combines precise technical calculations with visual representation to provide important information about market movements and dynamics right on the chart.
Functionality
The script calculates and displays the length of the upper and lower wicks of each candle on the chart. It also provides additional visual cues such as:
• “Bull pressure”: When green candles do not have upper wicks, this indicates strong buying pressure.
• “Bear pressure”: When red candles do not have lower wicks, this indicates strong selling pressure.
• Threshold conditions: Only displays wicks that exceed a certain threshold (optional).
• Display in pips: Allows you to display wick lengths in pips, which is useful for forex traders.
How it works
The script analyzes each candle using the following calculations:
1. Wick length calculation:
◦ Upper wick length = High - (top of the body)
◦ Lower wick length = (bottom of the body) - Low
2. Display conditions:
◦ It distinguishes between bullish and bearish candles.
◦ It checks if the calculated wicks exceed the defined thresholds before displaying them.
3. Dynamic labels:
◦ Labels are placed above or below the respective candles.
◦ Size, color and type of labels are fully customizable.
4. Limitation of labels
Alert conditions:
Alerts are triggered when the wick length of a bullish or bearish candle exceeds the defined thresholds.
Alert function:
alert() is used to issue messages with a frequency of once per candle when the conditions are met.
How to set up alerts
Save the script and add it to your chart.
Open the alert settings in TradingView.
Select the script's custom message as a trigger.
Adjust the frequency and notification type (popup, email, etc.).
Now you have a powerful tool with visual analysis and alert function!
Prometheus Markov ChainThe Prometheus Markov Chain Indicator is a custom-built tool designed to predict potential future price movements using a Markov Chain approach. A Markov Chain is a statistical model that assumes the probability of moving to a future state depends solely on the current state. In this indicator, states represent price movement classifications—bullish, bearish, or neutral—and are determined based on historical price changes (percentage returns). The indicator builds a transition matrix to calculate probabilities of transitioning from one state to another, enabling traders to identify patterns and forecast likely price actions.
Core Functionality and Transition Matrix
The transition matrix is the backbone of the Markov Chain. It captures the frequency of transitions between states in the historical price data and normalizes these counts into probabilities. For example, if the price was in a bearish state and transitioned to a bullish state 3 out of 10 times, the probability of transitioning from bearish to bullish would be 0.3. The matrix is created dynamically using the stateFunc function to classify states, which can use either dynamic thresholds (highest and lowest returns over a lookback period) or a user-defined percent return threshold. Below is the snippet that updates the transition matrix:
transitionMatrix = matrix.new(dimension, dimension, 0.0)
for i = 0 to array.size(vec) - 2
fromState = array.get(vec, i)
toState = array.get(vec, i + 1)
transitionMatrix.set(fromState, toState, transitionMatrix.get(fromState, toState) + 1)
for i = 0 to dimension - 1
rowSum = 0.0
for j = 0 to dimension - 1
rowSum += transitionMatrix.get(i, j)
for j = 0 to dimension - 1
prob = transitionMatrix.get(i, j) / rowSum
transitionMatrix.set(i, j, prob)
This snippet iterates through historical price movements, counts state transitions, and then normalizes each row of the matrix so that the sum of probabilities for all possible transitions from a given state equals 1.
How the Indicator Predicts Future States
After constructing the transition matrix, the indicator calculates the current state of the price based on the latest percentage return and then uses the matrix to compute probabilities for transitioning to other states. The state with the highest probability is predicted as the next state, which is displayed on the chart using color-coded labels: green for bullish and red for bearish. The following snippet demonstrates how the current state and predictions are calculated:
current_chng = (close - close ) / close
var int current_state = na
if not use_custom_thresh
highest_chng = ta.highest(current_chng, int(size) * 2)
lowest_chng = ta.lowest(current_chng, int(size) * 2)
current_state := stateFunc(current_chng, highest_chng, lowest_chng)
else
current_state := stateFunc(current_chng, custom_thresh)
predicted_probs = array.new(dimension, 0.0)
for j = 0 to dimension - 1
array.set(predicted_probs, j, transitionMatrix.get(current_state, j))
The indicator evaluates which state has the highest transition probability (highest_prob) and places corresponding labels on the chart. For example, if the next state is predicted to be bullish, a green "Bullish" label is placed below the current bar. This predictive functionality helps traders anticipate potential reversals or continuations in price trends based on historical behavior patterns.
Usage:
Here we see the indicator at work on $PLTR. The states predicted are bullish then bearish. In this example we then see price move in a way that verifies those predictions.
On this 4 Hour NASDAQ:AMZN chart we see predictions play out in a short trade style. States quickly move from one to another but not without giving traders a way to take advantage.
This is the perspective we aim to provide. We encourage traders to not follow indicators blindly. No indicator is 100% accurate. This one can give you a different perspective market state. We encourage any comments about desired updates or criticism!
Super CCI By Baljit AujlaThe indicator you've shared is a custom CCI (Commodity Channel Index) with multiple types of Moving Averages (MA) and Divergence Detection. It is designed to help traders identify trends and reversals by combining the CCI with various MAs and detecting different types of divergences between the price and the CCI.
Key Components of the Indicator:
CCI (Commodity Channel Index):
The CCI is an oscillator that measures the deviation of the price from its average price over a specific period. It helps identify overbought and oversold conditions and the strength of a trend.
The CCI is calculated by subtracting a moving average (SMA) from the price and dividing by the average deviation from the SMA. The CCI values fluctuate above and below a zero centerline.
Multiple Moving Averages (MA):
The indicator allows you to choose from a variety of moving averages to smooth the CCI line and identify trend direction or support/resistance levels. The available types of MAs include:
SMA (Simple Moving Average)
EMA (Exponential Moving Average)
WMA (Weighted Moving Average)
HMA (Hull Moving Average)
RMA (Running Moving Average)
SMMA (Smoothed Moving Average)
TEMA (Triple Exponential Moving Average)
DEMA (Double Exponential Moving Average)
VWMA (Volume-Weighted Moving Average)
ZLEMA (Zero-Lag Exponential Moving Average)
You can select the type of MA to use with a specified length to help identify the trend direction or smooth out the CCI.
Divergence Detection:
The indicator includes a divergence detection mechanism to identify potential trend reversals. Divergences occur when the price and an oscillator like the CCI move in opposite directions, signaling a potential change in price momentum.
Four types of divergences are detected:
Bullish Divergence: Occurs when the price makes a lower low, but the CCI makes a higher low. This indicates a potential reversal to the upside.
Bearish Divergence: Occurs when the price makes a higher high, but the CCI makes a lower high. This indicates a potential reversal to the downside.
Hidden Bullish Divergence: Occurs when the price makes a higher low, but the CCI makes a lower low. This suggests a continuation of the uptrend.
Hidden Bearish Divergence: Occurs when the price makes a lower high, but the CCI makes a higher high. This suggests a continuation of the downtrend.
Each type of divergence is marked on the chart with arrows and labels to alert traders to potential trading opportunities. The labels include the divergence type (e.g., "Bull Div" for Bullish Divergence) and have customizable text colors.
Visual Representation:
The CCI and its associated moving average are plotted on the indicator panel below the price chart. The CCI is plotted as a line, and its color changes depending on whether it is above or below the moving average:
Green when the CCI is above the MA (indicating bullish momentum).
Red when the CCI is below the MA (indicating bearish momentum).
Horizontal lines are drawn at specific levels to help identify key CCI thresholds:
200 and -200 levels indicate extreme overbought or oversold conditions.
75 and -75 levels represent less extreme levels of overbought or oversold conditions.
The 0 level acts as a neutral or baseline level.
A background color fill between the 75 and -75 levels helps highlight the neutral zone.
Customization Options:
CCI Length: You can customize the length of the CCI, which determines the period over which the CCI is calculated.
MA Length: The length of the moving average applied to the CCI can also be adjusted.
MA Type: Choose from a variety of moving averages (SMA, EMA, WMA, etc.) to smooth the CCI.
Divergence Detection: The indicator automatically detects the four types of divergences (bullish, bearish, hidden bullish, hidden bearish) and visually marks them on the chart.
How to Use the Indicator:
Trend Identification: When the CCI is above the selected moving average, it suggests bullish momentum. When the CCI is below the moving average, it suggests bearish momentum.
Overbought/Oversold Conditions: The CCI values above 100 or below -100 indicate overbought and oversold conditions, respectively.
Divergence Analysis: The detection of bullish or bearish divergences can signal potential trend reversals. Hidden divergences may suggest trend continuation.
Trading Signals: You can use the divergence markers (arrows and labels) as potential buy or sell signals, depending on whether the divergence is bullish or bearish.
Practical Application:
This indicator is useful for traders who want to:
Combine the CCI with different moving averages for trend-following strategies.
Identify overbought and oversold conditions using the CCI.
Use divergence detection to anticipate potential trend reversals or continuations.
Have a highly customizable tool for various trading strategies, including trend trading, reversal trading, and divergence-based trading.
Overall, this is a comprehensive tool that combines multiple technical analysis techniques (CCI, moving averages, and divergence) in a single indicator, providing traders with a robust way to analyze price action and spot potential trading opportunities.
Advanced BB Bands with PlotThis code implements an advanced version of Bollinger Bands with additional moving averages, ATR-based bands, step lines, market direction indicators, and real-time data display. Here’s a breakdown of the functionality:
1. Inputs and Parameters:
length: The base period used for calculating the moving averages and the typical price.
atr_length: The length used for calculating the Average True Range (ATR).
step_length: The period for calculating step lines (highest high and lowest low over a given period).
2. Core Calculations:
Typical Price: (high + low + close) / 3 is the base for the moving averages.
ATR: ta.atr(atr_length) is used to create dynamic bands around the moving averages.
PL Dot: An average of the typical prices from the current and past two bars. This provides a short-term trend indicator.
3. Multiple Moving Averages (MAs):
Three simple moving averages (ma1, ma2, ma3) are calculated using different multiples of the base length. These help indicate short-, mid-, and long-term trends.
4. Step Lines:
Step Up: Highest close over the step_length.
Step Down: Lowest close over the step_length. These act as short-term support and resistance levels.
5. Outer Bands:
Upper Band: ma1 + 2 * ATR, an upper boundary based on ATR volatility.
Lower Band: ma1 - 2 * ATR, a lower boundary. Together, these form a dynamic range around the short-term moving average.
6. Market Direction:
Bullish or Bearish condition is determined by comparing ma1 and ma2. If ma1 is above ma2, the market is bullish; otherwise, it's bearish. This decision is displayed on the TradingView chart using a table.
7. Visual Elements:
Moving Averages (ma1, ma2, ma3): Plotted in different colors (blue, purple, white) to indicate different timeframes.
PL Dot: A step line plot for the PL Dot, which helps in spotting short-term trends.
Step Lines: Step-up and step-down levels plotted in lime and red, respectively.
Outer Bands: Upper and lower ATR-based bands plotted in aqua, with a filled region between the bands for easy visualization of price volatility.
Candlestick Coloring: Green bars for bullish and red for bearish price action.
8. Real-Time Board Display:
A table is created in the top-right corner of the chart to display:
The current closing price.
The market direction ("Bullish" or "Bearish").
The PL Dot value. The table updates on the most recent bar (barstate.islast).
9. Dynamic Labels:
On the most recent bar, labels are added dynamically to the upper and lower bands and the ma1. These labels help in identifying the values of key indicators directly on the chart.
10. Signals and Alerts:
Bullish and Bearish Cross: Visual signals are plotted on the chart when ma1 crosses above or below ma2. These are represented as up and down triangles, providing potential buy/sell signals.
Key Features Summarized:
Multi-Timeframe Moving Averages: 3 MAs based on different timeframes.
Dynamic ATR Bands: ATR-based upper and lower boundaries for volatility measurement.
Step Lines: Short-term high and low lines for support/resistance.
PL Dot: A short-term trend identifier.
Real-Time Dashboard: Live updates of price, trend, and PL Dot on the chart.
Visual Alerts: Dynamic labeling and crossover signals to assist in decision-making.
This script is designed for traders who want to track price movement within bands, evaluate trends across multiple timeframes, and visualize short-term market direction with dynamic alerts.
Adaptive bollinger bands cloud v1 trend & trade signalsadaptive bollinger bands cloud:
the script extends the concept of bollinger bands by creating a "cloud" between the upper and lower bands. this cloud visually represents market conditions, with its color dynamically adjusting based on trend strength and volatility.
the gradient fill between the bands changes according to the deviation of the price from its basis, offering a visual cue for trend momentum.
trend detection logic:
a trend variable determines whether the price is in a bullish, bearish, or neutral state. if the price is above the upper band and the basis, the trend is marked bullish. if it's below the lower band and the basis, the trend is bearish. otherwise, it's neutral.
this trend logic is further enhanced with visual markers like arrows to indicate potential trend reversals.
extended take-profit bands:
additional upper and lower bands are calculated using a higher multiplier. these extended bands help identify potential take-profit levels, signaling when the price may have reached an overextended state.
gradient calculation:
the script computes a gradient based on the deviation of the price from its basis and normalizes it over a lookback period. this normalized gradient is smoothed to reflect volatility intensity and used to color the cloud dynamically.
signal generation:
buy and sell signals are generated based on crossovers of the trend variable. for instance, when the trend shifts from negative to positive, it signals a bullish opportunity. conversely, a shift from positive to negative indicates bearish conditions.
take-profit markers ("x") are plotted when the price crosses the extended bands, suggesting potential exit points.
trade entry tracking:
the script includes a table to display real-time entry signals and prices for long (buy) or short (sell) trades. this feature helps traders keep track of signals without needing to reference the chart visually.
customizable inputs:
users can adjust the bb period, multiplier, and colors to suit their trading preferences. this flexibility allows for tuning the indicator based on different market conditions or asset classes.
overall, the indicator blends traditional bollinger bands with innovative visualization, trend identification, and trading signals to enhance decision-making.
how to use this indicator
trend detection:
watch for arrows indicating trend shifts:
an upward arrow (green) signals a bullish trend; consider buying or entering a long position.
a downward arrow (red) signals a bearish trend; consider selling or entering a short position.
use the gradient-colored cloud to assess trend strength:
bright and strong colors indicate significant momentum.
fading colors suggest weakening trends or consolidation.
entry signals:
refer to the table in the top-right corner of the chart for real-time buy or sell entry signals.
when a "buy" signal is displayed with the price, it suggests a potential entry point for a long trade.
when a "sell" signal is displayed, consider shorting or exiting long positions.
take-profit signals:
look for the "x" markers near the extended bands (upper1 and lower1):
an "x" above the price suggests taking profit on long positions.
an "x" below the price suggests taking profit on short positions.
background gradient analysis:
observe the dynamic background color:
a strong purple gradient indicates significant price movement or volatility.
a lighter gradient suggests reduced momentum, signaling caution or a potential reversal.
alerts for automation:
set alerts using the predefined conditions:
bullish trend start, bearish trend start, and take-profit levels can be used to automate notifications for trade actions.
why to use this indicator
enhanced decision-making:
the adaptive cloud and gradient provide visual insights into trend strength and volatility, allowing traders to assess market conditions at a glance.
precise signals:
the indicator uses crossover logic and extended bollinger bands to generate clear buy, sell, and take-profit signals, reducing guesswork.
trend confirmation:
combining the bollinger bands with the trend variable ensures that traders only act on confirmed market trends rather than noise.
dynamic volatility assessment:
the normalized gradient calculation highlights periods of high or low volatility, helping traders adjust their strategies accordingly.
customizable settings:
adjustable parameters (period, multiplier, colors) allow the indicator to fit various markets, timeframes, and trading styles.
all-in-one tool:
integrates trend detection, entry signals, and take-profit levels into a single indicator, minimizing the need for multiple tools.
this indicator is especially useful for traders seeking a balance between simplicity and precision, whether scalping, day trading, or swing trading. it not only identifies trends but also highlights actionable entry and exit points, making it a versatile addition to any trading strategy.
Indicator DashboardThis script creates an 'Indicator Dashboard' designed to assist you in analyzing financial markets and making informed decisions. The indicator provides a summary of current market conditions by presenting various technical analysis indicators in a table format. The dashboard evaluates popular indicators such as Moving Averages, RSI, MACD, and Stochastic RSI. Below, we'll explain each part of this script in detail and its purpose:
### Overview of Indicators
1. **Moving Averages (MA)**:
- This indicator calculates Simple Moving Averages (“SMA”) for 5, 14, 20, 50, 100, and 200 periods. These averages provide a visual summary of price movements. Depending on whether the price is above or below the moving average, it determines the market direction as either “Bullish” or “Bearish.”
2. **RSI (Relative Strength Index)**:
- The RSI helps identify overbought or oversold market conditions. Here, the RSI is calculated for a 14-period window, and this value is displayed in the table. Additionally, the 14-period moving average of the RSI is also included.
3. **MACD (Moving Average Convergence Divergence)**:
- The MACD indicator is used to determine trend strength and potential reversals. This script calculates the MACD line, signal line, and histogram. The MACD condition (“Bullish,” “Bearish,” or “Neutral”) is displayed alongside the MACD and signal line values.
4. **Stochastic RSI**:
- Stochastic RSI is used to identify momentum changes in the market. The %K and %D lines are calculated to determine the market condition (“Bullish” or “Bearish”), which is displayed along with the calculated values for %K and %D.
### Table Layout and Presentation
The dashboard is presented in a vertical table format in the top-right corner of the chart. The table contains two columns: “Indicator” and “Status,” summarizing the condition of each technical indicator.
- **Indicator Column**: Lists each of the indicators being tracked, such as SMA values, RSI, MACD, etc.
- **Status Column**: Displays the current status of each indicator, such as “Bullish,” “Bearish,” or specific values like the RSI or MACD.
The table also includes rounded indicator values for easier interpretation. This helps traders quickly assess market conditions and make informed decisions based on multiple indicators presented in a single location.
### Detailed Indicator Status Calculations
1. **SMA Status**: For each moving average (5, 14, 20, 50, 100, 200), the script checks if the current price is above or below the SMA. The status is determined as “Bullish” if the price is above the SMA and “Bearish” if below, with the value of the SMA also displayed.
2. **RSI and RSI Average**: The RSI value for a 14-period is displayed along with its 14-period SMA, which provides an average reading of the RSI to smooth out volatility.
3. **MACD Indicator**: The MACD line, signal line, and histogram are calculated using standard parameters (12, 26, 9). The status is shown as “Bullish” when the MACD line is above the signal line, and “Bearish” when it is below. The exact values for the MACD line, signal line, and histogram are also included.
4. **Stochastic RSI**: The %K and %D lines of the Stochastic RSI are used to determine the trend condition. If %K is greater than %D, the condition is “Bullish,” otherwise it is “Bearish.” The actual values of %K and %D are also displayed.
### Conclusion
The 'Indicator Dashboard' provides a comprehensive overview of multiple technical indicators in a single, easy-to-read table. This allows traders to quickly gauge market conditions and make more informed decisions. By consolidating key indicators like Moving Averages, RSI, MACD, and Stochastic RSI into one dashboard, it saves time and enhances the efficiency of technical analysis.
This script is particularly useful for traders who prefer a clean and organized overview of their favorite indicators without needing to plot each one individually on the chart. Instead, all the crucial information is available at a glance in a consolidated format.
Trend Speed Analyzer (Zeiierman)█ Overview
The Trend Speed Analyzer by Zeiierman is designed to measure the strength and speed of market trends, providing traders with actionable insights into momentum dynamics. By combining a dynamic moving average with wave and speed analysis, it visually highlights shifts in trend direction, market strength, and potential reversals. This tool is ideal for identifying breakout opportunities, gauging trend consistency, and understanding the dominance of bullish or bearish forces over various timeframes.
█ How It Works
The indicator employs a Dynamic Moving Average (DMA) enhanced with an Accelerator Factor, allowing it to adapt dynamically to market conditions. The DMA is responsive to price changes, making it suitable for both long-term trends and short-term momentum analysis.
Key components include:
Trend Speed Analysis: Measures the speed of market movements, highlighting momentum shifts with visual cues.
Wave Analysis: Tracks bullish and bearish wave sizes to determine market strength and bias.
Normalized Speed Values: Ensures consistency across different market conditions by adjusting for volatility.
⚪ Average Wave and Max Wave
These metrics analyze the size of bullish and bearish waves over a specified Lookback Period:
Average Wave: This represents the mean size of bullish and bearish movements, helping traders gauge overall market strength.
Max Wave: Highlights the largest movements within the period, identifying peak momentum during trend surges.
⚪ Current Wave Ratio
This feature compares the current wave's size against historical data:
Average Wave Ratio: Indicates if the current momentum exceeds historical averages. A value above 1 suggests the trend is gaining strength.
Max Wave Ratio: Shows whether the current wave surpasses previous peak movements, signaling potential breakouts or trend accelerations.
⚪ Dominance
Dominance metrics reveal whether bulls or bears have controlled the market during the Lookback Period:
Average Dominance: Compares the net difference between average bullish and bearish wave sizes.
Max Dominance: Highlights which side had the stronger individual waves, indicating key power shifts in market dynamics.
Positive values suggest bullish dominance, while negative values point to bearish control. This helps traders confirm trend direction or anticipate reversals.
█ How to Use
Identify Trends: Leverage the color-coded candlesticks and dynamic trend line to assess the overall market direction with clarity.
Monitor Momentum: Use the Trend Speed histogram to track changes in momentum, identifying periods of acceleration or deceleration.
Analyze Waves: Compare the sizes of bullish and bearish waves to identify the prevailing market bias and detect potential shifts in sentiment. Additionally, fluctuations in Current Wave ratio values should be monitored as early indicators of possible trend reversals.
Evaluate Dominance: Utilize dominance metrics to confirm the strength and direction of the current trend.
█ Settings
Maximum Length: Sets the smoothing of the trend line.
Accelerator Multiplier: Adjusts sensitivity to price changes.
Lookback Period: Defines the range for wave calculations.
Enable Table: Displays statistical metrics for in-depth analysis.
Enable Candles: Activates color-coded candlesticks.
Collection Period: Normalizes trend speed values for better accuracy.
Start Date: Limits calculations to a specific timeframe.
Timer Option: Choose between using all available data or starting from a custom date.
-----------------
Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Adaptive DEMA Momentum Oscillator (ADMO)Overview:
The Adaptive DEMA Momentum Oscillator (ADMO) is an open-source technical analysis tool developed to measure market momentum using a Double Exponential Moving Average (DEMA) and adaptive standard deviation. By dynamically combining price deviation from the moving average with normalized standard deviation, ADMO provides traders with a powerful way to interpret market conditions.
Key Features:
Double Exponential Moving Average (DEMA):
The core calculation of the indicator is based on DEMA, which is known for being more responsive to price changes compared to traditional moving averages. This makes the ADMO capable of capturing trend momentum effectively.
Standard Deviation Integration:
A normalized standard deviation is used to adaptively weight the oscillator. This makes the indicator more sensitive to market volatility, enhancing responsiveness during high volatility and reducing sensitivity during calmer periods.
Oscillator Representation:
The final oscillator value is derived from the combination of the DEMA-based Z-score and the normalized standard deviation. This final value is visualized as a color-coded histogram, reflecting bullish or bearish momentum.
Color-Coded Histogram:
Bullish Momentum: Values above zero are colored using a customizable bullish color (default: light green).
Bearish Momentum: Values below zero are colored using a customizable bearish color (default: red).
How It Works:
Inputs:
DEMA Length: Defines the period used for calculating the Double Exponential Moving Average. It can be adjusted from 1 to 200 to suit different trading styles.
Standard Deviation Length: Sets the lookback period for standard deviation calculations, which influences the responsiveness of the oscillator.
Standard Deviation Weight (StdDev Weight): Controls the weight given to the normalized standard deviation, allowing customization of the oscillator's sensitivity to volatility.
Calculation Steps:
Double Exponential Moving Average Calculation:
The DEMA is calculated using two exponential moving averages, which helps in reducing lag compared to a simple moving average.
Z-score Calculation:
The Z-score is derived by comparing the difference between the DEMA and its smoothed average (LSMA) to the standard deviation. This indicates how far the current value is from the mean in units of standard deviation.
Normalized Standard Deviation:
The standard deviation is normalized by subtracting the mean standard deviation and dividing by the standard deviation of the values. This helps to make the oscillator adaptive to recent changes in volatility.
Final Oscillator Value:
The final value is calculated by multiplying the Z-score with a factor based on the normalized standard deviation, resulting in a momentum indicator that adapts to different market conditions.
Visualization:
Histogram: The oscillator is plotted as a histogram, with color-coded bars showing the strength and direction of market momentum.
Positive (bullish) values are shown in green, indicating upward momentum.
Negative (bearish) values are shown in red, indicating downward momentum.
Zero Line: A zero line is plotted to provide a reference point, helping users quickly determine whether the current momentum is bullish or bearish.
Example Use Cases:
Momentum Identification:
ADMO helps identify the current market momentum by dynamically adapting to changes in market volatility. When the histogram is above zero and green, it indicates bullish conditions, whereas values below zero and red suggest bearish momentum.
Volatility-Adjusted Signals:
The normalized standard deviation weighting allows the ADMO to provide more reliable signals during different market conditions. This makes it particularly useful for traders who want to be responsive to market volatility while avoiding false signals.
Trend Confirmation and Divergence:
ADMO can be used to confirm the strength of a trend or identify potential divergences between price and momentum. This helps traders spot potential reversal points or continuation signals.
Summary:
The Adaptive DEMA Momentum Oscillator (ADMO) offers a unique approach by combining momentum analysis with adaptive standard deviation. The integration of DEMA makes it responsive to price changes, while the standard deviation adjustment helps it stay relevant in both high and low volatility environments. It's a versatile tool for traders who need an adaptive, momentum-based approach to technical analysis.
Feel free to explore the code and adapt it to your trading strategy. The open-source nature of this tool allows you to adjust the settings and visualize the output to fit your personal trading preferences.
Wick Trend Analysis with Supertrend and RSI -AYNETScientific Explanation
1. Wick Trend Analysis
Upper and Lower Wicks:
Calculated based on the difference between the high or low price and the candlestick body (open and close).
The trend of these wick lengths is derived using the Simple Moving Average (SMA) over the defined trend_length period.
Trend Direction:
Positive change (ta.change > 0) indicates an increasing trend.
Negative change (ta.change < 0) indicates a decreasing trend.
2. Supertrend Indicator
ATR Bands:
The Supertrend uses the Average True Range (ATR) to calculate dynamic upper and lower bands:
upper_band
=
hl2
+
(
supertrend_atr_multiplier
×
ATR
)
upper_band=hl2+(supertrend_atr_multiplier×ATR)
lower_band
=
hl2
−
(
supertrend_atr_multiplier
×
ATR
)
lower_band=hl2−(supertrend_atr_multiplier×ATR)
Trend Detection:
If the price is above the upper band, the Supertrend moves to the lower band.
If the price is below the lower band, the Supertrend moves to the upper band.
The Supertrend helps identify the prevailing market trend.
3. RSI (Relative Strength Index)
The RSI measures the momentum of price changes and ranges between 0 and 100:
Overbought Zone (Above 70): Indicates that the price may be overextended and due for a pullback.
Oversold Zone (Below 30): Indicates that the price may be undervalued and due for a reversal.
Visualization Features
Wick Trend Lines:
Upper wick trend (green) and lower wick trend (red) show the relative strength of price rejection on both sides.
Wick Trend Area:
The area between the upper and lower wick trends is filled dynamically:
Green: Upper wick trend is stronger.
Red: Lower wick trend is stronger.
Supertrend Line:
Displays the Supertrend as a blue line to highlight the market's directional bias.
RSI:
Plots the RSI line, with horizontal dotted lines marking the overbought (70) and oversold (30) levels.
Applications
Trend Confirmation:
Use the Supertrend and wick trends together to confirm the market's directional bias.
For example, a rising lower wick trend with a bullish Supertrend suggests strong bullish sentiment.
Momentum Analysis:
Combine the RSI with wick trends to assess the strength of price movements.
For example, if the RSI is oversold and the lower wick trend is increasing, it may signal a potential reversal.
Signal Generation:
Generate entry signals when all three indicators align:
Bullish Signal:
Lower wick trend increasing.
Supertrend bullish.
RSI rising from oversold.
Bearish Signal:
Upper wick trend increasing.
Supertrend bearish.
RSI falling from overbought.
Future Improvements
Alert System:
Add alerts for alignment of Supertrend, RSI, and wick trends:
pinescript
Kodu kopyala
alertcondition(upper_trend_direction == 1 and supertrend < close and rsi > 50, title="Bullish Signal", message="Bullish alignment detected.")
alertcondition(lower_trend_direction == 1 and supertrend > close and rsi < 50, title="Bearish Signal", message="Bearish alignment detected.")
Custom Thresholds:
Add thresholds for wick lengths and RSI levels to filter weak signals.
Multiple Timeframes:
Incorporate multi-timeframe analysis for more robust signal generation.
Conclusion
This script combines wick trends, Supertrend, and RSI to create a comprehensive framework for analyzing market sentiment and detecting potential trading opportunities. By visualizing trends, market bias, and momentum, traders can make more informed decisions and reduce reliance on single-indicator strategies.
EMA 50 + 200 Trend Signal TableEMA 50 + 200 Trend Signal Table (ETT)
This indicator provides a multi-timeframe trend signal table based on the 50-period and 200-period Exponential Moving Averages (EMAs). It visually plots the EMA 50 and EMA 200 on the chart, along with a customizable, compact table that indicates the trend direction across multiple timeframes. This tool is useful for traders looking to quickly identify market trends and momentum on various timeframes.
How It Works
- EMA Trend Analysis: The script compares the EMA 50 and EMA 200 values to determine the trend. When EMA 50 is above EMA 200, the trend is considered Bullish; if EMA 50 is below EMA 200, the trend is Bearish. If EMA 200 data is unavailable (e.g., on very short timeframes), the trend status will display as Neutral.
- Multi-Timeframe Trend Signals: The table displays the trend signals across five user-defined timeframes, updating in real time. Each timeframe row shows either Bullish, Bearish, or Neutral, with colors customizable to your preference.
Features
- EMA 50 and EMA 200 Visualization: Plots EMA 50 and EMA 200 lines directly on the chart. Users can customize the color and line thickness for each EMA to fit their charting style.
- Trend Signal Table: A table positioned on the chart (with options for positioning in the corners) shows the trend direction for the selected timeframes.
Bullish Trend: Highlighted in green (default) with 50% opacity.
Bearish Trend: Highlighted in red (default) with 50% opacity.
Neutral Trend: Highlighted in gray (default) with 50% opacity.
- Customizable Table Appearance: Allows users to select the position of the table (top-right, top-left, bottom-right, or bottom-left) and choose between compact sizes (Extra Small, Small, Normal).
- Adjustable Colors: Users can specify custom colors for each trend status (Bullish, Bearish, Neutral) as well as for the text and table border colors.
Inputs and Customizations
- Timeframes: Choose up to five different timeframes for trend analysis.
- EMA Colors and Line Widths: Customize the color and line width of EMA 50 and EMA 200 plotted on the chart.
- Table Settings: Control the position, size, and color options of the trend signal table for improved visibility and integration with your chart layout.
Use Case This indicator is ideal for traders who employ a multi-timeframe approach to confirm trends and filter entries. By monitoring the relative positions of EMA 50 and EMA 200 across various timeframes, traders can get a quick snapshot of trend strength and direction, aiding in informed trading decisions.
Exposure Oscillator (Cumulative 0 to ±100%)
Exposure Oscillator (Cumulative 0 to ±100%)
This Pine Script indicator plots an "Exposure Oscillator" on the chart, which tracks the cumulative market exposure from a range of technical buy and sell signals. The exposure is measured on a scale from -100% (maximum short exposure) to +100% (maximum long exposure), helping traders assess the strength of their position in the market. It provides an intuitive visual cue to aid decision-making for trend-following strategies.
Buy Signals (Increase Exposure Score by +10%)
Buy Signal 1 (Cross Above 21 EMA):
This signal is triggered when the price crosses above the 21-period Exponential Moving Average (EMA), where the current bar closes above the EMA21, and the previous bar closed below the EMA21. This indicates a potential upward price movement as the market shifts into a bullish trend.
buySignal1 = ta.crossover(close, ema21)
Buy Signal 2 (Trending Above 21 EMA):
This signal is triggered when the price closes above the 21-period EMA for each of the last 5 bars, indicating a sustained bullish trend. It confirms that the price is consistently above the EMA21 for a significant period.
buySignal2 = ta.barssince(close <= ema21) > 5
Buy Signal 3 (Living Above 21 EMA):
This signal is triggered when the price has closed above the 21-period EMA for each of the last 15 bars, demonstrating a strong, prolonged uptrend.
buySignal3 = ta.barssince(close <= ema21) > 15
Buy Signal 4 (Cross Above 50 SMA):
This signal is triggered when the price crosses above the 50-period Simple Moving Average (SMA), where the current bar closes above the 50 SMA, and the previous bar closed below it. It indicates a shift toward bullish momentum.
buySignal4 = ta.crossover(close, sma50)
Buy Signal 5 (Cross Above 200 SMA):
This signal is triggered when the price crosses above the 200-period Simple Moving Average (SMA), where the current bar closes above the 200 SMA, and the previous bar closed below it. This suggests a long-term bullish trend.
buySignal5 = ta.crossover(close, sma200)
Buy Signal 6 (Low Above 50 SMA):
This signal is true when the lowest price of the current bar is above the 50-period SMA, indicating strong bullish pressure as the price maintains itself above the moving average.
buySignal6 = low > sma50
Buy Signal 7 (Accumulation Day):
An accumulation day occurs when the closing price is in the upper half of the daily range (greater than 50%) and the volume is larger than the previous bar's volume, suggesting buying pressure and accumulation.
buySignal7 = (close - low) / (high - low) > 0.5 and volume > volume
Buy Signal 8 (Higher High):
This signal occurs when the current bar’s high exceeds the highest high of the previous 14 bars, indicating a breakout or strong upward momentum.
buySignal8 = high > ta.highest(high, 14)
Buy Signal 9 (Key Reversal Bar):
This signal is generated when the stock opens below the low of the previous bar but rallies to close above the previous bar’s high, signaling a potential reversal from bearish to bullish.
buySignal9 = open < low and close > high
Buy Signal 10 (Distribution Day Fall Off):
This signal is triggered when a distribution day (a day with high volume and a close near the low of the range) "falls off" the rolling 25-bar period, indicating the end of a bearish trend or selling pressure.
buySignal10 = ta.barssince(close < sma50 and close < sma50) > 25
Sell Signals (Decrease Exposure Score by -10%)
Sell Signal 1 (Cross Below 21 EMA):
This signal is triggered when the price crosses below the 21-period Exponential Moving Average (EMA), where the current bar closes below the EMA21, and the previous bar closed above it. It suggests that the market may be shifting from a bullish trend to a bearish trend.
sellSignal1 = ta.crossunder(close, ema21)
Sell Signal 2 (Trending Below 21 EMA):
This signal is triggered when the price closes below the 21-period EMA for each of the last 5 bars, indicating a sustained bearish trend.
sellSignal2 = ta.barssince(close >= ema21) > 5
Sell Signal 3 (Living Below 21 EMA):
This signal is triggered when the price has closed below the 21-period EMA for each of the last 15 bars, suggesting a strong downtrend.
sellSignal3 = ta.barssince(close >= ema21) > 15
Sell Signal 4 (Cross Below 50 SMA):
This signal is triggered when the price crosses below the 50-period Simple Moving Average (SMA), where the current bar closes below the 50 SMA, and the previous bar closed above it. It indicates the start of a bearish trend.
sellSignal4 = ta.crossunder(close, sma50)
Sell Signal 5 (Cross Below 200 SMA):
This signal is triggered when the price crosses below the 200-period Simple Moving Average (SMA), where the current bar closes below the 200 SMA, and the previous bar closed above it. It indicates a long-term bearish trend.
sellSignal5 = ta.crossunder(close, sma200)
Sell Signal 6 (High Below 50 SMA):
This signal is true when the highest price of the current bar is below the 50-period SMA, indicating weak bullishness or a potential bearish reversal.
sellSignal6 = high < sma50
Sell Signal 7 (Distribution Day):
A distribution day is identified when the closing range of a bar is less than 50% and the volume is larger than the previous bar's volume, suggesting that selling pressure is increasing.
sellSignal7 = (close - low) / (high - low) < 0.5 and volume > volume
Sell Signal 8 (Lower Low):
This signal occurs when the current bar's low is less than the lowest low of the previous 14 bars, indicating a breakdown or strong downward momentum.
sellSignal8 = low < ta.lowest(low, 14)
Sell Signal 9 (Downside Reversal Bar):
A downside reversal bar occurs when the stock opens above the previous bar's high but falls to close below the previous bar’s low, signaling a reversal from bullish to bearish.
sellSignal9 = open > high and close < low
Sell Signal 10 (Distribution Cluster):
This signal is triggered when a distribution day occurs three times in the rolling 7-bar period, indicating significant selling pressure.
sellSignal10 = ta.valuewhen((close < low) and volume > volume , 1, 7) >= 3
Theme Mode:
Users can select the theme mode (Auto, Dark, or Light) to match the chart's background or to manually choose a light or dark theme for the oscillator's appearance.
Exposure Score Calculation: The script calculates a cumulative exposure score based on a series of buy and sell signals.
Buy signals increase the exposure score, while sell signals decrease it. Each signal impacts the score by ±10%.
Signal Conditions: The buy and sell signals are derived from multiple conditions, including crossovers with moving averages (EMA21, SMA50, SMA200), trend behavior, and price/volume analysis.
Oscillator Visualization: The exposure score is visualized as a line on the chart, changing color based on whether the exposure is positive (long position) or negative (short position). It is limited to the range of -100% to +100%.
Position Type: The indicator also indicates the position type based on the exposure score, labeling it as "Long," "Short," or "Neutral."
Horizontal Lines: Reference lines at 0%, 100%, and -100% visually mark neutral, increasing long, and increasing short exposure levels.
Exposure Table: A table displays the current exposure level (in percentage) and position type ("Long," "Short," or "Neutral"), updated dynamically based on the oscillator’s value.
Inputs:
Theme Mode: Choose "Auto" to use the default chart theme, or manually select "Dark" or "Light."
Usage:
This oscillator is designed to help traders track market sentiment, gauge exposure levels, and manage risk. It can be used for long-term trend-following strategies or short-term trades based on moving average crossovers and volume analysis.
The oscillator operates in conjunction with the chart’s price action and provides a visual representation of the market’s current trend strength and exposure.
Important Considerations:
Risk Management: While the exposure score provides valuable insight, it should be combined with other risk management tools and analysis for optimal trading decisions.
Signal Sensitivity: The accuracy and effectiveness of the signals depend on market conditions and may require adjustments based on the user’s trading strategy or timeframe.
Disclaimer:
This script is for educational purposes only. Trading involves significant risk, and users should carefully evaluate all market conditions and apply appropriate risk management strategies before using this tool in live trading environments.
Inversion Fair Value Gap Oscillator | Flux Charts💎 GENERAL OVERVIEW
Introducing the new Inversion Fair Value Gap Oscillator (IFVG Oscillator) indicator! This unique indicator identifies and tracks Inversion Fair Value Gaps (IFVGs) in price action, presenting them in an oscillator format to reveal market momentum based on IFVG strength. It highlights bullish and bearish IFVGs while enabling traders to adjust detection sensitivity and apply volume and ATR-based filters for more precise setups. For more information about the process, check the "📌 HOW DOES IT WORK" section.
Features of the new IFVG Oscillator:
Fully Customizable FVG & IFVG Detection
An Oscillator Approach To IFVGs
Divergence Markers For Potential Reversals
Alerts For Divergence Labels
Customizable Styling
📌 HOW DOES IT WORK?
Fair Value Gaps are price gaps within bars that indicate inefficiencies, often filled as the market retraces. An Inversion Fair Value Gap is created in the opposite direction once a FVG gets invalidated. The IFVG Oscillator scans historical bars to identify these gaps, then filters them based on ATR or volume. Each IFVG is marked as bullish or bearish according to the opposite direction of the original FVG that got invalidated.
An oscillator is calculated using recent IFVGs with this formula :
1. The Oscillator starts as 0.
2. When a new IFVG Appears, it contributes (IFVG Width / ATR) to the oscillator of the corresponding type.
3. Each confirmed bar, the oscillator is recalculated as OSC = OSC * (1 - Decay Coefficient)
The oscillator aggregates and decays past IFVGs, allowing recent IFVG activity to dominate the signal. This approach emphasizes current market momentum, with oscillations moving bullish or bearish based on IFVG intensity. Divergences are marked where IFVG oscillations suggest potential reversals. Bullish Divergence conditions are as follows :
1. The current candlestick low must be the lowest of last 25 bars.
2. Net Oscillator (Shown in gray line by default) must be > 0.
3. The current Bullish IFVG Oscillator value should be no more than 0.1 below the highest value from the last 25 bars.
Traders can use divergence signals to get an idea of potential reversals, and use the Net IFVG Oscillator as a trend following marker.
🚩 UNIQUENESS
The Inversion Fair Value Gap Oscillator stands out by converting IFVG activity into an oscillator format, providing a momentum-based visualization of IFVGs that reveals market sentiment dynamically. Unlike traditional indicators that statically mark IFVG zones, the oscillator decays older IFVGs over time, showing only the most recent, relevant activity. This approach allows for real-time insight into market conditions and potential reversals based on oscillating IFVG strength, making it both intuitive and powerful for momentum trading.
Another unique feature is the combination of customizable ATR and volume filters, letting traders adapt the indicator to match their strategy and market type. You can also set-up alerts for bullish & bearish divergences.
⚙️ SETTINGS
1. General Configuration
Decay Coefficient -> The decay coefficient for oscillators. Increasing this setting will result in oscillators giving the weight to recent IFVGs, while decreasing it will distribute the weight equally to the past and recent IFVGs.
2. Fair Value Gaps
Zone Invalidation -> Select between Wick & Close price for FVG Zone Invalidation.
Zone Filtering -> With "Average Range" selected, algorithm will find FVG zones in comparison with average range of last bars in the chart. With the "Volume Threshold" option, you may select a Volume Threshold % to spot FVGs with a larger total volume than average.
FVG Detection -> With the "Same Type" option, all 3 bars that formed the FVG should be the same type. (Bullish / Bearish). If the "All" option is selected, bar types may vary between Bullish / Bearish.
Detection Sensitivity -> You may select between Low, Normal or High FVG detection sensitivity. This will essentially determine the size of the spotted FVGs, with lower sensitivies resulting in spotting bigger FVGs, and higher sensitivies resulting in spotting all sizes of FVGs.
3. Inversion Fair Value Gaps
Zone Invalidation -> Select between Wick & Close price for IFVG Zone Invalidation.
4. Style
Divergence Labels On -> You can switch divergence labels to show up on the chart or the oscillator plot.
Arshtiq - Multi-Timeframe Trend StrategyMulti-Timeframe Setup:
The script uses two distinct timeframes: a higher (daily) timeframe for identifying the trend and a lower (hourly) timeframe for making trades. This combination allows the script to follow the larger trend while timing entries and exits with more precision on a shorter timeframe.
Moving Averages Calculation:
higher_ma: The 20-period Simple Moving Average (SMA) calculated based on the daily timeframe. This average gives a sense of the larger trend direction.
lower_ma: The 20-period SMA calculated on the hourly (current) timeframe, providing a dynamic level for detecting entry and exit points within the broader trend.
Trend Identification:
Bullish Trend: The script determines that a bullish trend is present if the current price is above the daily moving average (higher_ma).
Bearish Trend: Similarly, a bearish trend is identified when the current price is below this daily moving average.
Trade Signals:
Buy Signal: A buy signal is generated when the price on the hourly chart crosses above the hourly 20-period MA, but only if the higher (daily) timeframe trend is bullish. This ensures that buy trades align with the larger upward trend.
Sell Signal: A sell signal is generated when the price on the hourly chart crosses below the hourly 20-period MA, but only if the daily trend is bearish. This ensures that sell trades are consistent with the broader downtrend.
Plotting and Visual Cues:
Higher Timeframe MA: The daily 20-period moving average is plotted in red to help visualize the long-term trend.
Buy and Sell Signals: Buy signals appear as green labels below the price bars with the text "BUY," while sell signals appear as red labels above the bars with the text "SELL."
Background Coloring: The background changes color based on the identified trend for easier trend recognition:
Green (with transparency) when the daily trend is bullish.
Red (with transparency) when the daily trend is bearish.
WiseOwl Indicator - 1.0 The WiseOwl Indicator - 1.0 is a technical analysis tool designed to help traders identify potential entry points and market trends based on Exponential Moving Averages (EMAs) across multiple timeframes. It focuses on providing clear visual cues for bullish and bearish market conditions, as well as potential breakout opportunities.
Key Features
Multi-Timeframe EMA Analysis: Calculates EMAs on the current timeframe, Daily timeframe, and 15-minute timeframe to confirm trends.
Bullish and Bearish Market Identification: Determines market conditions based on the 200-period EMA on the Daily timeframe.
Directional Candle Coloring: Highlights candles based on their position relative to EMAs to provide immediate visual feedback.
Entry Signals: Plots buy and sell signals on the chart when specific conditions are met on the 1-hour and 4-hour timeframes.
Breakout Candle Highlighting: Colors candles differently when significant price movements occur, indicating potential breakout opportunities.
How It Works
Market Condition Determination:
Bullish Market: When the close price is above the 200-period EMA on the Daily timeframe.
Bearish Market: When the close price is below the 200-period EMA on the Daily timeframe.
Directional Candle Coloring:
Green Background: Applied when the close is above the 50-period EMA and the market is not bearish.
Red Background: Applied when the close is below the 50-period EMA and the market is not bullish.
Uses the Average True Range (ATR) to define a range threshold.
Suppresses signals when EMAs are within this range, indicating a sideways market.
Plotting Entry Signals:
Plots arrows on the chart for potential long and short entries on the 1-hour and 4-hour timeframes.
Breakout Candle Coloring:
Colors candles blue when a bullish breakout condition is met.
Colors candles orange when a bearish breakout condition is met.
How to Use
Trend Identification: Use the background coloring to quickly identify the overall market trend.
Green Background: Suggests bullish conditions; consider looking for long opportunities.
Red Background: Suggests bearish conditions; consider looking for short opportunities.
Entry Signals: Look for plotted arrows on the chart.
Green Upward Arrow: Indicates a potential long entry signal on the 1-hour or 4-hour timeframe.
Red Downward Arrow: Indicates a potential short entry signal on the 1-hour or 4-hour timeframe.
Breakout Opportunities: Watch for candles colored blue or orange.
Blue Candles: Highlight significant upward price movements.
Orange Candles: Highlight significant downward price movements.
Avoiding Ranging Markets: Be cautious when signals are suppressed due to ranging conditions; the market may not have a clear direction.
Example Usage
Identifying a Bullish Market:
The background turns green.
Price crosses above the 50 EMA.
A green upward arrow appears below a candle on the 1-hour or 4-hour chart.
Identifying a Bearish Market:
The background turns red.
Price crosses below the 50 EMA.
A red downward arrow appears above a candle on the 1-hour or 4-hour chart.
Notes
Open-Source Code: The script is open-source, allowing users to review and understand the logic behind the indicator.
Educational Purpose: This indicator is intended to aid in technical analysis and should not be used as the sole basis for trading decisions.
Disclaimer
This indicator is for educational purposes only and does not constitute financial advice. Trading involves risk, and you should consult with a qualified financial advisor before making any investment decisions.
Half Trend Regression [AlgoAlpha]Introducing the Half Trend Regression indicator by AlgoAlpha, a cutting-edge tool designed to provide traders with precise trend detection and reversal signals. This indicator uniquely combines linear regression analysis with ATR-based channel offsets to deliver a dynamic view of market trends. Ideal for traders looking to integrate statistical methods into their analysis to improve trade timing and decision-making.
Key Features
🎨 Customizable Appearance : Adjust colors for bullish (green) and bearish (red) trends to match your charting preferences.
🔧 Flexible Parameters : Configure amplitude, channel deviation, and linear regression length to tailor the indicator to different time frames and trading styles.
📈 Dynamic Trend Line : Utilizes linear regression of high, low, and close prices to calculate a trend line that adapts to market movements.
🚀 Trend Direction Signals : Provides clear visual signals for potential trend reversals with plotted arrows on the chart.
📊 Adaptive Channels : Incorporates ATR-based channel offsets to account for market volatility and highlight potential support and resistance zones.
🔔 Alerts : Set up alerts for bullish or bearish trend changes to stay informed of market shifts in real-time.
How to Use
🛠 Add the Indicator : Add the Half Trend Regression indicator to your chart from the TradingView library. Access the settings to customize parameters such as amplitude, channel deviation, and linear regression length to suit your trading strategy.
📊 Analyze the Trend : Observe the plotted trend line and the filled areas under it. A green fill indicates a bullish trend, while a red fill indicates a bearish trend.
🔔 Set Alerts : Use the built-in alert conditions to receive notifications when a trend reversal is detected, allowing you to react promptly to market changes.
How It Works
The Half Trend Regression indicator calculates linear regression lines for the high, low, and close prices over a specified period to determine the general direction of the market. It then computes moving averages and identifies the highest and lowest points within these regression lines to establish a dynamic trend line. The trend direction is determined by comparing the moving averages and previous price levels, updating as new data becomes available. To account for market volatility, the indicator calculates channels above and below the trend line, offset by a multiple of half the Average True Range (ATR). These channels help visualize potential support and resistance zones. The area under the trend line is filled with color corresponding to the current trend direction—green for bullish and red for bearish. When the trend direction changes, the indicator plots arrows on the chart to signal a potential reversal, and alerts can be set up to notify you. By integrating linear regression and ATR-based channels, the indicator provides a comprehensive view of market trends and potential reversal points, aiding traders in making informed decisions.
Enhance your trading strategy with the Half Trend Regression indicator by AlgoAlpha and gain a statistical edge in the markets! 🌟📊
Custom Volume for scalping### **Indicator Summary: Custom Volume with Arrow Highlight**
#### **Purpose:**
This indicator visualizes volume bars in a chart, highlighting specific conditions based on volume trends. It displays arrows above the volume bars to indicate potential bullish or bearish market conditions.
#### **Key Features:**
1. **Volume Bars**:
- The indicator plots volume as columns on the chart.
- Volume bars are colored:
- **White** for bullish volume (when the closing price is higher than the opening price).
- **Blue** for bearish volume (when the closing price is lower than the opening price).
2. **Highlight Conditions**:
- The indicator identifies a sequence of three consecutive volume bars:
- The first two bars must be of the same direction (either both bullish or both bearish).
- The third bar must be of the opposite direction.
- Additionally, the third bar's volume must be greater than the previous bar's volume.
3. **Arrow Indicators**:
- When the highlight conditions are met:
- An **upward arrow** ("▲") is placed above the third volume bar for bullish conditions (when the third bar is bullish).
- A **downward arrow** ("▼") is placed above the third volume bar for bearish conditions (when the third bar is bearish).
- The arrows are colored to match the respective volume bar: white for bullish and blue for bearish.
4. **Adjustable Size**:
- The arrows are sized appropriately to ensure visibility without cluttering the chart.
#### **Use Cases:**
- This indicator can help traders identify potential reversals or continuation patterns based on volume behavior.
- It is particularly useful for traders focusing on volume analysis to confirm market trends and make informed trading decisions.
#### **Customization:**
- Users can modify the conditions and visual attributes according to their preferences, such as changing colors, sizes, and label positions.
### **Conclusion:**
The "Custom Volume with Arrow Highlight" indicator provides a straightforward and effective way to visualize volume trends and identify key market conditions, aiding traders in their decision-making processes. It combines the power of volume analysis with clear visual cues, making it a valuable tool for technical analysis in trading.
If you need any further modifications or details, let me know!
Fair Value Gap Oscillator | Flux Charts💎 GENERAL OVERVIEW
Introducing the new Fair Value Gap Oscillator (FVG Oscillator) indicator! This unique indicator identifies and tracks Fair Value Gaps (FVGs) in price action, presenting them in an oscillator format to reveal market momentum based on FVG strength. It highlights bullish and bearish FVGs while enabling traders to adjust detection sensitivity and apply volume and ATR-based filters for more precise setups. For more information about the process, check the "📌 HOW DOES IT WORK" section.
Features of the new FVG Oscillator:
Fully Customizable FVG Detection
An Oscillator Approach To FVGs
Divergence Markers For Potential Reversals
Alerts For Divergence Labels
Customizable Styling
📌 HOW DOES IT WORK?
Fair Value Gaps are price gaps within bars that indicate inefficiencies, often filled as the market retraces. The FVG Oscillator scans historical bars to identify these gaps, then filters them based on ATR or volume. Each FVG is marked as bullish or bearish according to the trend direction that preceded its formation.
An oscillator is calculated using recent FVGs with this formula :
1. The Oscillator starts as 0.
2. When a new FVG Appears, it contributes (FVG Width / ATR) to the oscillator of the corresponding type.
3. Each confirmed bar, the oscillator is recalculated as OSC = OSC * (1 - Decay Coefficient)
The oscillator aggregates and decays past FVGs, allowing recent FVG activity to dominate the signal. This approach emphasizes current market momentum, with oscillations moving bullish or bearish based on FVG intensity. Divergences are marked where FVG oscillations suggest potential reversals. Bullish Divergence conditions are as follows :
1. The current candlestick low must be the lowest of last 25 bars.
2. Net Oscillator (Shown in gray line by default) must be > 0.
3. The current Bullish FVG Oscillator value should be no more than 0.1 below the highest value from the last 25 bars.
Traders can use divergence signals to get an idea of potential reversals, and use the Net FVG Oscillator as a trend following marker.
🚩 UNIQUENESS
The Fair Value Gap Oscillator stands out by converting FVG activity into an oscillator format, providing a momentum-based visualization of FVGs that reveals market sentiment dynamically. Unlike traditional indicators that statically mark FVG zones, the oscillator decays older FVGs over time, showing only the most recent, relevant activity. This approach allows for real-time insight into market conditions and potential reversals based on oscillating FVG strength, making it both intuitive and powerful for momentum trading.
Another unique feature is the combination of customizable ATR and volume filters, letting traders adapt the indicator to match their strategy and market type. You can also set-up alerts for bullish & bearish divergences.
⚙️ SETTINGS
1. General Configuration
Decay Coefficient -> The decay coefficient for oscillators. Increasing this setting will result in oscillators giving the weight to recent FVGs, while decreasing it will distribute the weight equally to the past and recent FVGs.
2. Fair Value Gaps
Zone Invalidation -> Select between Wick & Close price for FVG Zone Invalidation.
Zone Filtering -> With "Average Range" selected, algorithm will find FVG zones in comparison with average range of last bars in the chart. With the "Volume Threshold" option, you may select a Volume Threshold % to spot FVGs with a larger total volume than average.
FVG Detection -> With the "Same Type" option, all 3 bars that formed the FVG should be the same type. (Bullish / Bearish). If the "All" option is selected, bar types may vary between Bullish / Bearish.
Detection Sensitivity -> You may select between Low, Normal or High FVG detection sensitivity. This will essentially determine the size of the spotted FVGs, with lower sensitivies resulting in spotting bigger FVGs, and higher sensitivies resulting in spotting all sizes of FVGs.
3. Style
Divergence Labels On -> You can switch divergence labels to show up on the chart or the oscillator plot.
Trend Strength Momentum Indicator (TSMI)Introducing the Trend Strength Momentum Indicator (TSMI)
With over two decades of experience, I've found that no single indicator can consistently predict market movements. The key lies in combining multiple indicators to capture different market dimensions—trend, momentum, and volume. With this in mind, I present the Trend Strength Momentum Indicator (TSMI), a comprehensive tool designed to spot emerging uptrends and downtrends in cryptocurrency and other asset markets.
1. Overview of TSMI
The TSMI amalgamates three critical market aspects:
Trend Direction and Strength: Utilizing Moving Averages (MA) and the Average Directional Index (ADX).
Momentum: Incorporating the Moving Average Convergence Divergence (MACD) and the Relative Strength Index (RSI).
Volume Confirmation: Employing the On-Balance Volume (OBV) indicator.
By combining these elements, TSMI aims to provide a robust signal that not only indicates the direction of the trend but also confirms its strength and sustainability through momentum and volume analysis.
2. Components and Calculations
A. Trend Component
Exponential Moving Averages (EMA):
50-day EMA: Captures the short to medium-term trend.
200-day EMA: Reflects the long-term trend.
Average Directional Index (ADX):
Measures the strength of the trend regardless of its direction.
A value above 25 indicates a strong trend, while below 20 suggests a weak or non-trending market.
B. Momentum Component
Moving Average Convergence Divergence (MACD):
Calculated by subtracting the 26-day EMA from the 12-day EMA.
The MACD line crossing above the signal line (9-day EMA of MACD) indicates bullish momentum; crossing below suggests bearish momentum.
Relative Strength Index (RSI):
Oscillates between 0 and 100.
Readings above 70 indicate overbought conditions; below 30 suggest oversold conditions.
C. Volume Component
On-Balance Volume (OBV):
Cumulatively adds volume on up days and subtracts volume on down days.
A rising OBV alongside rising prices confirms an uptrend; divergence may signal a reversal.
3. TSMI Calculation Steps
Step 1: Trend Analysis
EMA Crossover:
Identify if the 50-day EMA crosses above the 200-day EMA (Golden Cross), indicating a potential uptrend.
Conversely, if the 50-day EMA crosses below the 200-day EMA (Death Cross), it may signal a downtrend.
ADX Confirmation:
Confirm the strength of the trend. An ADX value above 25 supports the EMA crossover signal.
Step 2: Momentum Assessment
MACD Evaluation:
Look for MACD crossing above its signal line for bullish momentum or below for bearish momentum.
RSI Check:
Ensure RSI is not in overbought (>70) or oversold (<30) territory to avoid potential reversals against the trend.
Step 3: Volume Verification
OBV Direction:
Confirm that OBV is moving in the same direction as the price trend.
Rising OBV with rising prices strengthens the bullish signal; falling OBV with falling prices strengthens the bearish signal.
Step 4: Composite Signal Generation
Bullish Signal:
50-day EMA crosses above 200-day EMA (Golden Cross).
ADX above 25, indicating a strong trend.
MACD crosses above its signal line.
RSI is between 30 and 70, avoiding overbought conditions.
OBV is rising.
Bearish Signal:
50-day EMA crosses below 200-day EMA (Death Cross).
ADX above 25.
MACD crosses below its signal line.
RSI is between 30 and 70, avoiding oversold conditions.
OBV is falling.
4. How to Use the TSMI
A. Entry Points
Buying into an Uptrend:
Wait for the bullish signal criteria to align.
Enter the position after the 50-day EMA crosses above the 200-day EMA, supported by positive momentum (MACD and RSI) and volume (OBV).
Selling or Shorting into a Downtrend:
Look for the bearish signal criteria.
Initiate the position after the 50-day EMA crosses below the 200-day EMA, with confirming momentum and volume indicators.
B. Exit Strategies
Protecting Profits:
Monitor RSI for overbought or oversold conditions, which may indicate potential reversals.
Watch for MACD divergences or crossovers against your position.
Use trailing stops based on the ATR (Average True Range) to allow profits to run while protecting against sharp reversals.
C. Risk Management
Position Sizing:
Use the ADX value to adjust position sizes. A stronger trend (higher ADX) may justify a larger position, whereas a weaker trend suggests caution.
Avoiding False Signals:
Be cautious during sideways markets where EMAs may whipsaw.
Confirm signals with multiple indicators before acting.
5. Examples
Example 1: Spotting an Emerging Uptrend in Bitcoin
Date: Let's assume on March 1st.
Observations:
EMA Crossover: The 50-day EMA crosses above the 200-day EMA.
ADX: Reading is 28, indicating a strong trend.
MACD: Crosses above the signal line and moves into positive territory.
RSI: Reading is 55, comfortably away from overbought levels.
OBV: Shows a rising trend, confirming increasing buying pressure.
Action:
Enter a long position in Bitcoin.
Set a stop-loss below recent swing lows.
Outcome:
Over the next few weeks, Bitcoin's price continues to rise, validating the TSMI signal.
Example 2: Identifying a Downtrend in Ethereum
Date: Let's assume on July 15th.
Observations:
EMA Crossover: The 50-day EMA crosses below the 200-day EMA.
ADX: Reading is 30, confirming a strong trend.
MACD: Crosses below the signal line into negative territory.
RSI: Reading is 45, not yet oversold.
OBV: Declining, indicating selling pressure.
Action:
Initiate a short position or exit long positions in Ethereum.
Place a stop-loss above recent resistance levels.
Outcome:
Ethereum's price declines over the following weeks, confirming the downtrend.
6. When to Use the TSMI
Trending Markets: TSMI is most effective in markets exhibiting clear trends, whether bullish or bearish.
Avoiding Sideways Markets: In range-bound markets, EMAs and momentum indicators may provide false signals. ADX readings below 20 suggest it's best to stay on the sidelines.
Volatile Assets: Particularly useful in cryptocurrency markets, which are known for their volatility and extended trends.
7. Limitations and Considerations
Lagging Indicators: Moving averages and ADX are lagging by nature. Rapid reversals may not be immediately captured.
False Signals: No indicator is foolproof. Always confirm signals with multiple components of TSMI.
Market Conditions: External factors like news events can significantly impact prices. Consider combining TSMI with fundamental analysis.
8. Enhancing TSMI
Customization: Adjust EMA periods (e.g., 20-day and 100-day) based on the asset's volatility and your trading timeframe.
Additional Indicators: Incorporate Bollinger Bands to gauge volatility or Fibonacci retracement levels to identify potential support and resistance.
Conclusion
The Trend Strength Momentum Indicator (TSMI) offers a holistic approach to spotting emerging trends by combining trend direction, momentum, and volume. By synthesizing the strengths of various traditional indicators while mitigating their individual limitations, TSMI provides traders with a powerful tool to navigate the complex landscape of cryptocurrency and other asset markets.
Key Benefits of TSMI:
Comprehensive Analysis: Integrates multiple market dimensions for well-rounded insights.
Early Trend Identification: Aims to spot trends early for optimal entry points.
Risk Management: Helps in making informed decisions, thereby reducing exposure to false signals.
By applying TSMI diligently and complementing it with sound risk management practices, traders can enhance their ability to capitalize on market trends and improve their overall trading performance.
Daily Engulfing Pattern DetectorThis indicator identifies bullish and bearish engulfing patterns on daily timeframes.
A bullish engulfing pattern occurs when a green candle completely engulfs the previous red candle,
taking out its low and closing above both its open and close prices. This suggests a potential trend reversal from bearish to bullish.
A bearish engulfing pattern occurs when a red candle completely engulfs the previous green candle,
taking out its high and closing below both its open and close prices. This suggests a potential trend reversal from bullish to bearish.
Features:
- Works on daily timeframe by default (customizable)
- Displays visual markers: green triangles for bullish patterns, red triangles for bearish patterns
- Includes built-in alerts for both pattern types
Set up alerts by right-clicking the indicator and selecting "Create Alert"
[EmreKb] Combined CandlesThis script combines multiple candlestick patterns into a single, unified candle when they are of the same type (bullish or bearish). Instead of displaying every individual candle on the chart, it merges consecutive candles based on their direction to simplify the visual analysis of price movements.
What It Does:
Combines Candles: If two or more consecutive candles are bullish (close price higher than open price) or bearish (close price lower than open price), the script merges them into a single candle, adjusting the high, low, and close values accordingly.
Displays Merged Candles: The merged candles are drawn on the chart. A green bar represents a bullish period, while a red bar represents a bearish period.
How It Works:
The script tracks whether each candle is bullish or bearish.
If a candle is the same type as the previous one, it updates the combined candle (adjusting the high, low, and close values).
When the type changes (from bullish to bearish or vice versa), it finalizes the current combined candle and starts a new one.
The merged candles are displayed on the chart at the end of the data series.
Use Case:
This script simplifies price action by grouping similar candles together, making it easier to identify trends and spot periods of sustained buying or selling pressure. It can help traders focus on the overall direction of the market rather than being distracted by small fluctuations between individual candles.
CoffeeShopCrytpo Dynamic PPIIn the financial world, the Producer Price Index (PPI) is often used to measure how domestic products are performing over time, indicating the health of the market. Domestic products refer to goods and services that are produced within a specific country’s borders. However, in this indicator, we’ve taken that idea and applied it directly to financial assets, allowing traders to see how an asset is performing relative to its own base value over a given period of time.
Here, the asset’s base value is represented as 100%. When the asset performs above 100%, it's considered to be in a buyer's market—indicating strength and demand. Conversely, if the value dips below 100%, it's operating below its base value, signaling a potential seller's market.
Why This Matters:
This indicator not only converts an asset’s performance into a PPI-style calculation, but it also visualizes price movements as price candles. This dual perspective is crucial, because even if the asset’s performance is over 100%, the closing price might still fall below that threshold—adding nuance to your understanding of market conditions.
Key Features of the Indicator:
Bullish and Bearish Convergence Levels: These levels show whether the market leans bullish or bearish. If the Bullish Convergence level is higher than the Bearish one, the market is bullish, and vice versa. Importantly, these levels can signal shifts in market strength, regardless of where the PPI candles are positioned.
If Bullish Convergence is rising below Bearish, the bearish market is weakening and bullish pressure is growing. Conversely, if Bearish Convergence is falling above Bullish, the bearish side is losing ground.
Market Strength Visualizations:
Strong Bullish Market: Bullish Convergence is higher than Bearish, and it’s still rising.
Strong Bearish Market: Bearish Convergence is above Bullish, and it's climbing.
Weak Bullish Market: Bullish Convergence is above Bearish, but the PPI closes below Bullish Convergence.
Weak Bearish Market: Bearish Convergence is above Bullish, but the PPI closes above Bullish Convergence
Pullbacks:
Bullish Pullback: In a strong bullish market, the PPI shows lower closes below the Bullish Convergence.
Bearish Pullback: In a strong bearish market, the PPI shows higher closes above the Bullish Convergence.
Divergences:
Higher Price, Lower or Flat PPI: This indicates that while the asset’s price is rising, its underlying performance (relative to the PPI’s 100% base level) is not keeping up. Essentially, the asset is reaching new price highs, but its strength or "efficiency" of growth is weakening.
The PPI is designed to show the "return" of an asset's performance relative to its historical movement, so when it lags behind price, it suggests that the price rise may not be sustainable.
When you observe the first high of the PPI level above the bullish convergence level, followed by a second high of the PPI below the bullish convergence level in a bullish market, this creates a divergence.
Example of Divergence in image:
1. First High of PPI Above the Bullish Convergence Level:
This suggests strong bullish momentum. The asset’s performance, as measured by the PPI, is in line with or even outperforming price expectations, indicating the market is experiencing a robust bullish trend. The fact that the PPI level is above the bullish convergence line means that the asset is operating well above its base performance (above 100%) and bullish momentum is clearly dominant.
2. Second High of PPI Below the Bullish Convergence Level:
This marks a potential weakening of the bullish momentum. Although the market is still in a bullish state (since bullish convergence remains above bearish), the PPI failing to reach the bullish convergence level suggests that the asset’s performance is not keeping pace with price action or is underperforming relative to its earlier high.
The fact that this occurs while the market is still bullish (bullish convergence is greater than bearish) can signal a possible pullback or a temporary consolidation phase within the larger bullish trend.
What does a divergence mean:
Momentum Weakening: The second high of the PPI being below the bullish convergence line suggests that while prices may still be increasing, the strength behind the move is fading. The asset is not performing as strongly as it did during the first high, and the market’s confidence or momentum might be softening.
Potential Bullish Pullback: This could indicate that a pullback or correction within the larger bullish trend is underway. Traders might be taking profits, or buyers could be losing enthusiasm, causing the asset to stall temporarily. However, because the overall market remains bullish, this doesn’t necessarily mean a full reversal—just a cooling off period.
Caution in New Long Positions: If you see this divergence, it could be a sign to be more cautious about opening new long positions. It suggests that the asset may need to consolidate or correct before resuming its upward trend, and it’s worth waiting for confirmation of renewed momentum before jumping back in.
ATR Settings
Youll notice there are two ATR settings. One for short term and one for long term.
These values are based on your preferential strategy for what you consider to be long and short term.
The final ATR values are calculated against eachother and applied to the Volatility Label at the end of price.
This label shows you the current ATR as well as the previous candle ATR.
Why this is important:
If the short term ATR is greater than the long term ATR, then volatility is rising in the short term greater than the long term.
This gives your label a value greater than 1.0. This means the short term trend is about to move.
If the long term ATR is greater than the short term ATR, there is no volatility in the short term and only long term exists.
This gives you a value of less than 1.0. This means no volatility or ranging market in the short term.
Directional Targets & POC TableThe "Directional Targets & POC Table" Pine Script™ is a comprehensive tool designed to help traders identify directional bias, potential price targets, and important levels like the Point of Control (POC). Additionally, it detects fair value gaps (FVGs) and order blocks, which are crucial concepts in Smart Money Concepts (SMC) trading. Here's an overview of its functionality:
1. Indicator Overview:
The script combines multiple technical tools into a single visual aid:
Directional Targets: Fibonacci-based upper and lower targets that provide a forecast of where the price might move.
Point of Control (POC): Midpoint of the daily range, displayed visually on the chart.
Fair Value Gaps (FVGs): Areas of imbalance in the market, potentially leading to price reversals.
Order Blocks: Areas where institutional traders might have entered large positions, potentially serving as support or resistance.
2. Key Features:
Directional Targets & POC Table:
A table is displayed in the top-right corner of the chart, showing:
Direction: Based on whether the price is above or below the POC.
Target ↑: The upper target, calculated using Fibonacci's 0.618 level, which acts as a potential resistance.
POC: The midpoint between the daily high and low, serving as the central level of interest.
Target ↓: The lower target, also calculated using the 0.618 Fibonacci level, which serves as potential support.
The table uses colors to make each level easily distinguishable, with green for bullish targets, red for bearish, and yellow for the POC.
POC Visualization:
The Point of Control (POC) is drawn on the chart as a box that stretches horizontally. It highlights the central price range where the highest volume or interest may have occurred, providing a key level for traders to watch.
The POC can act as a support or resistance area, with price frequently reacting at or near this level.
FVG Detection:
Fair Value Gaps are identified when there’s a price imbalance between two bars. These gaps occur when the high of one bar is lower than the low of a bar two periods earlier, or vice versa.
The script draws lines at the boundaries of these gaps, helping traders spot potential areas where the price may return to fill the gap.
If the price revisits and fills the gap, the FVG lines are automatically deleted, signaling the gap is no longer relevant.
Order Blocks Detection:
Bullish Order Blocks are detected when a strong bullish candle forms, where the close equals the high, and it’s higher than the previous bar’s low. This represents potential institutional buying interest.
Bearish Order Blocks are detected when a strong bearish candle forms, where the close equals the low, and it’s lower than the previous bar’s high, representing potential selling interest.
The order blocks are drawn as rectangles on the chart, marking significant price zones that may act as future support (bullish) or resistance (bearish).
3. Direction Determination:
The script calculates the daily high, low, and mid-point (POC). If the current price is above the POC, the market is deemed bullish; if it’s below, the market is bearish. If it’s near the POC, the market is considered neutral.
This directional bias is then displayed in the table, giving traders an easy way to assess whether they should be looking for long or short opportunities.
4. Use Case:
This script is particularly useful for traders who:
Want to identify key levels like the POC and potential price targets based on Fibonacci retracement.
Follow Smart Money Concepts (SMC) and need tools to detect FVGs and order blocks, which can signal areas of market imbalance or institutional involvement.
Need a simple visual aid to determine market direction and structure, helping them make informed trading decisions.
5. Additional Features:
The script is highly visual, providing both numeric information in a table and plotted elements (lines, boxes) directly on the chart.
The automatic detection and clearing of FVGs and order blocks make this tool dynamic and easy to follow.
The script helps identify areas where price might react, giving traders a roadmap to follow for potential entries, exits, or take-profit levels.
This indicator is designed for traders looking to incorporate both conventional and advanced concepts like Fibonacci targets, POC, and SMC principles (FVGs and Order Blocks) into their strategy.
