Daily Directional Bias Indicator (S&P 500)This indicator is designed to help you be on the right side of the trade.
Most traders who struggle to know which way price may move are only looking at part of the picture. This Directional Bias Indicator uses both the Accumulation/Distribution Line and VIX for directional confirmation.
The Accumulation/Distribution Line
The Accumulation/Distribution (ACC) line helps us gauge market momentum by showing the cumulative flow of money into or out of an asset. When the ACC line is rising, it suggests that buying pressure is dominating, indicating a bullish market. Conversely, when the ACC line is falling, it suggests that selling pressure is stronger, indicating a bearish market. By comparing the ACC line with the VWAP, traders can see if the price is moving in line with the overall market sentiment. If the ACC line is above the VWAP, it suggests the market is in a bullish phase; if it's below, it indicates a bearish phase.
The VIX
The VIX (Volatility Index) is often referred to as the "fear gauge" of the market. When the VIX is rising, it typically signals increased market fear and higher volatility, which can be a sign of bearish market conditions. Conversely, when the VIX is falling, it suggests lower volatility and a more stable, bullish market. Using the VIX with the VWAP helps us confirm market direction, particularly in relation to the S&P 500.
VWAP
For both the ACC Line and VIX, we use a VWAP line to gauge whether the ACC line or the VIX is above or below the average. When the ACC line is above the VWAP, we view it as a sign that price will go up. However, because the VIX has an inverse relationship, when the VIX falls below the VWAP, we take that as a sign to go long.
How to use
The yellow line represents the ACC Line.
The red line represents the VWAP based on the ACC line.
The triangles at the bottom simply show when the ACC line is above or below the VWAP.
The triangles at the top show whether the VIX is bullish or bearish.
If both triangles (top or bottom) are bullish, this confirms that the price of an asset like the S&P 500 will likely go up. If both triangles are pointing down, it suggests that price will fall.
As always, test for yourself.
Happy trading!
Educational
2.5% Risk High Reward Strategy with DebuggingKey Features:
Loosened RSI Conditions: Adjusted to allow trades when RSI is below 50 (long) or above 50 (short).
Buy/Sell Labels: Visual labels added for buy and sell signals.
Stop-Loss (SL) and Take-Profit (TP): Dotted lines displayed for SL and TP levels.
Account Balance: Plots account balance over time for backtesting purposes.
Debugging Visuals: EMA, RSI, and volume threshold plotted to validate entry conditions.
Data extraction to clipboardHow to extract data from indicators/stratagies to clipbaord
///// Educational purpose only /////
This could be useful to store the best parameters for a strategy for instance...
to store and reuse them, to build some code in automatic , to transfer...
using the " log.info() " function ...
Earnings Master (EM) V1.0
Earnings Master (EM)
As an Investor/ Trader, while analysing the tradingview charts, he/she may quickly like to see some of the fundamental data like the financial health of the company which may help to shortlist the list of stocks to pick.
It will be great if he can see the last few quarters or years earnings, to make informed decisions based on detailed financial data.
A person may be interested to see the last few quarters sales data, Profit data, EPS, etc.
Normally he/she has to go to some other fundamental websites to see these data, which will be highly time consuming and a hectic process if he is going through hundreads of charts per day.
Thanks for our new Indicator Earnings Master (EM). This indicator is designed to provide detailed financial insights into a company's performance by displaying key financial metrics such as Profit After Tax (PAT), Operating profit margin (OPM), Earnings Per Share (EPS), Total Revenue etc.
The indicator also calculates and visualizes the percentage changes in these metrics over different quarters, offering a comprehensive view of the company's financial health.
Also it provides sector/Industry details and percentage up from 52-week low and down from 52-week high
Features:
Table Display:
A customisable table that can be viewed in both Dark and light themes
A customisable table that can be positioned in various locations on the chart (e.g., top left, top center, bottom right, etc.).
Color-coded values to indicate positive and negative changes in financial metrics.
Dynamic text size and color for better readability.
Financial Metrics:
PAT (Profit After Tax): Displays the PAT values for the current and previous quarters.
Industry and Sector: Displays the industry and the particular sector of the company
EPS (Earnings Per Share): Displays the EPS values for the current and previous quarters.
Total Revenue: Shows revenue values in crores (Cr) for multiple quarters.
Free Float: Represents the number of freely floating shares.
Quarter-over-Quarter (QoQ) Change: Computes the percentage change in PAT and sales for different quarters.
Sales in Crores: Displays sales values in crores (Cr) and calculates the QoQ changes.
Operating profit margin (OPM): which is a financial ratio that measures how much profit a company makes on sales after paying variable production costs
Inputs
User inputs for table position, Dark mode , and calculation periods for earnings.
- Option to show/hide Borders
Also can customise the indicator to show/hide the following table fields
- Show Sector
- Show Mcap/ Free Float Mcap?
- Show Earnings
- Show 52w High/Low stats
How to Use:
Add the Earnings Master indicator to your TradingView chart.
Customize the table position and color mode as per your preference.
Analyze the displayed financial metrics and percentage changes to gain insights into the company's performance.
Use the color-coded values to quickly identify significant changes and trends in PAT, EPS, revenue, and other key metrics.
Example Output:
In Quarter Ended mode the table will display the following fields
Quarter Ended period values
PAT Quarterly values
PAT YoY in percentage
PAT QoQ in percentage
Quarterly Sales values
Sales YoY in percentage
Sales QoQ in percentage
EPS values
EPS YoY in percentage (Option available to show/hide)
EPS QoQ in percentage (Option available to show/hide)
Price To Earnings (P/E) ratio
Operating profit margin (OPM)
In Year Ended mode the table will display the following fields
Year Ended period values
PAT Quarterly values
PAT YoY in percentage
Yearly Sales values
Sales YoY in percentage
EPS values
Price To Earnings (P/E) ratio
Price To Earnings (P/E) ratio YoY in percentage
Operating profit margin (OPM)
Trading Sessions with Highs and LowsTrading Sessions with Highs and Lows is designed to visually highlight specific trading sessions on the chart, providing traders with key insights into market behavior during these time periods. Here’s a detailed explanation of how the indicator works:
Key Features
1. Session Boxes:
• The indicator plots colored boxes on the chart to represent the price range of defined trading sessions.
• Each box spans the session’s start and end times and encapsulates the high and low prices during that period.
• Two trading sessions are defined by default:
• USA Trading Session: 9:30 AM - 4:00 PM (New York Time).
• UK Trading Session: 8:00 AM - 4:30 PM (London Time).
2. Session Labels:
• The name of the session (e.g., “USA” or “UK”) is displayed above the session box for clear identification.
3. High and Low Markers:
• Markers are added to the chart at the session’s high and low points:
• High Marker: A green label indicating the session high.
• Low Marker: A red label indicating the session low.
4. Dynamic Reset:
• After the session ends, the session high and low values are reset to na to prepare for the next trading day.
5. Customizable Background Colors:
• Each session’s box has a distinct, semi-transparent background color for better visual separation.
How It Works
1. Core Functionality:
• A function, plot_box, takes the session name, start time, end time, and background color as input.
• It calculates whether the current time is within the session.
• During the session:
• It tracks the session’s highest and lowest prices.
• It identifies the bars where the high and low occurred.
• At the session’s end:
• It plots a box on the chart covering the session’s time and price range.
• Labels are created for the session name and its high/low points.
2. Session Timing:
• Timestamps for the USA and UK trading sessions are calculated using the timestamp function with respective time zones.
3. Visual Elements:
• The box.new function draws the session boxes on the chart.
• The label.new function creates session name and high/low labels.
Usage
• Overlay Mode: The indicator is applied directly on the price chart (overlay=true), making it easy to visualize session-specific price behavior.
• Trading Strategy:
• Identify session-specific support and resistance levels.
• Observe price action trends during key trading periods.
• Align trading decisions with session dynamics.
Customization
While the indicator is preset for the USA and UK trading sessions, it can be easily modified:
1. Add/Remove Sessions: Define additional sessions by providing their start and end times.
2. Change Colors: Update the background_color in the plot_box calls to use different colors for sessions.
3. Adjust Time Zones: Replace the current time zones with others relevant to your trading style.
Visualization Example
• USA Session:
• Time: 9:30 AM - 4:00 PM (New York Time).
• Box Color: Semi-transparent orange.
• UK Session:
• Time: 8:00 AM - 4:30 PM (London Time).
• Box Color: Semi-transparent green.
Why Use This Indicator?
1. Market Awareness: Easily spot price behavior during high-liquidity trading periods.
2. Trend Analysis: Analyze how sessions overlap or affect each other.
3. Session Boundaries: Use session high/low levels as dynamic support and resistance zones.
This indicator is an essential tool for intraday and swing traders who want to align their strategies with key market timings.
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!
Moment-Based Adaptive DetectionMBAD (Moment-Based Adaptive Detection) : a method applicable to a wide range of purposes, like outlier or novelty detection, that requires building a sensible interval/set of thresholds. Unlike other methods that are static and rely on optimizations that inevitably lead to underfitting/overfitting, it dynamically adapts to your data distribution without any optimizations, MLE, or stuff, and provides a set of data-driven adaptive thresholds, based on closed-form solution with O(n) algo complexity.
1.5 years ago, when I was still living in Versailles at my friend's house not knowing what was gonna happen in my life tomorrow, I made a damn right decision not to give up on one idea and to actually R&D it and see what’s up. It allowed me to create this one.
The Method Explained
I’ve been wandering about z-values, why exactly 6 sigmas, why 95%? Who decided that? Why would you supersede your opinion on data? Based on what? Your ego?
Then I consciously noticed a couple of things:
1) In control theory & anomaly detection, the popular threshold is 3 sigmas (yet nobody can firmly say why xD). If your data is Laplace, 3 sigmas is not enough; you’re gonna catch too many values, so it needs a higher sigma.
2) Yet strangely, the normal distribution has kurtosis of 3, and 6 for Laplace.
3) Kurtosis is a standardized moment, a moment scaled by stdev, so it means "X amount of something measured in stdevs."
4) You generate synthetic data, you check on real data (market data in my case, I am a quant after all), and you see on both that:
lower extension = mean - standard deviation * kurtosis ≈ data minimum
upper extension = mean + standard deviation * kurtosis ≈ data maximum
Why not simply use max/min?
- Lower info gain: We're not using all info available in all data points to estimate max/min; we just pick the current higher and lower values. Lol, it’s the same as dropping exponential smoothing with alpha = 0 on stationary data & calling it a day.
You can’t update the estimates of min and max when new data arrives containing info about the matter. All you can do is just extend min and max horizontally, so you're not using new info arriving inside new data.
- Mixing order and non-order statistics is a bad idea; we're losing integrity and coherence. That's why I don't like the Hurst exponent btw (and yes, I came up with better metrics of my own).
- Max & min are not even true order statistics, unlike a percentile (finding which requires sorting, which requires multiple passes over your data). To find min or max, you just need to do one traversal over your data. Then with or without any weighting, 100th percentile will equal max. So unlike a weighted percentile, you can’t do weighted max. Then while you can always check max and min of a geometric shape, now try to calculate the 56th percentile of a pentagram hehe.
TL;DR max & min are rather topological characteristics of data, just as the difference between starting and ending points. Not much to do with statistics.
Now the second part of the ballet is to work with data asymmetry:
1) Skewness is also scaled by stdev -> so it must represent a shift from the data midrange measured in stdevs -> given asymmetric data, we can include this info in our models. Unlike kurtosis, skewness has a sign, so we add it to both thresholds:
lower extension = mean - standard deviation * kurtosis + standard deviation * skewness
upper extension = mean + standard deviation * kurtosis + standard deviation * skewness
2) Now our method will work with skewed data as well, omg, ain’t it cool?
3) Hold up, but what about 5th and 6th moments (hyperskewness & hyperkurtosis)? They should represent something meaningful as well.
4) Perhaps if extensions represent current estimated extremums, what goes beyond? Limits, beyond which we expect data not to be able to pass given the current underlying process generating the data?
When you extend this logic to higher-order moments, i.e., hyperskewness & hyperkurtosis (5th and 6th moments), they measure asymmetry and shape of distribution tails, not its core as previous moments -> makes no sense to mix 4th and 3rd moments (skewness and kurtosis) with 5th & 6th, so we get:
lower limit = mean - standard deviation * hyperkurtosis + standard deviation * hyperskewness
upper limit = mean + standard deviation * hyperkurtosis + standard deviation * hyperskewness
While extensions model your data’s natural extremums based on current info residing in the data without relying on order statistics, limits model your data's maximum possible and minimum possible values based on current info residing in your data. If a new data point trespasses limits, it means that a significant change in the data-generating process has happened, for sure, not probably—a confirmed structural break.
And finally we use time and volume weighting to include order & process intensity information in our model.
I can't stress it enough: despite the popularity of these non-weighted methods applied in mainstream open-access time series modeling, it doesn’t make ANY sense to use non-weighted calculations on time series data . Time = sequence, it matters. If you reverse your time series horizontally, your means, percentiles, whatever, will stay the same. Basically, your calculations will give the same results on different data. When you do it, you disregard the order of data that does have order naturally. Does it make any sense to you? It also concerns regressions applied on time series as well, because even despite the slope being opposite on your reversed data, the centroid (through which your regression line always comes through) will be the same. It also might concern Fourier (yes, you can do weighted Fourier) and even MA and AR models—might, because I ain’t researched it extensively yet.
I still can’t believe it’s nowhere online in open access. No chance I’m the first one who got it. It’s literally in front of everyone’s eyes for centuries—why no one tells about it?
How to use
That’s easy: can be applied to any, even non-stationary and/or heteroscedastic time series to automatically detect novelties, outliers, anomalies, structural breaks, etc. In terms of quant trading, you can try using extensions for mean reversion trades and limits for emergency exits, for example. The market-making application is kinda obvious as well.
The only parameter the model has is length, and it should NOT be optimized but picked consciously based on the process/system you’re applying it to and based on the task. However, this part is not about sharing info & an open-access instrument with the world. This is about using dem instruments to do actual business, and we can’t talk about it.
∞
IU Price Density(Market Noise)This Price density Indicator will help you understand what and how market noise is calculated and treated.
Market noise = when the market is moving up and down without any clear direction
The Price Density Indicator is a technical analysis tool used to measure the concentration or "density" of price movements within a specific range. It helps traders differentiate between noisy, choppy markets and trending ones.
I’ve developed a custom Pine Script indicator, "IU Price Density," designed to help traders distinguish between noisy, indecisive markets and clear trading opportunities. It can be applied across multiple markets.
How this work:
Formula = (Σ (High𝑖 - Low𝑖)) / (Max(High) - Min(Low))
Where,
High𝑖 = the high price at the 𝑖 data point.
Low𝑖 = the low price at the 𝑖 data point.
Max(High) = highest price over the data set.
Max(Low) = Lowest price over the data set.
How to use it :
This indicator ranges from 0 to 10
Green(0-3) = Trending Market
Orange(3-6) = Market is normal
Red(6-10) = Noise market
💡 Key Features:
Dynamic Visuals: The indicator uses color-coded signals—green for trending markets and red for noisy, volatile conditions—making it easy to identify optimal trading periods at a glance.
Background Shading: With background colors highlighting significant market conditions, traders can quickly assess when to engage or avoid certain trades.
Customizable Parameters: The length and smoothing factors allow for flexibility in adapting the indicator to various assets and timeframes.
Whether you're a swing trader or an intraday strategist, this tool provides valuable insights to improve your market analysis. I’m excited to bring this indicator to the community!
Altcoin Season Index - AdamThe "Altcoin Season Index" is a powerful tool for understanding market dynamics between Bitcoin and altcoins. This indicator helps traders identify whether the market is favoring Bitcoin or if it has shifted to favor altcoins. Understanding this can be crucial for making informed decisions about allocating your investments within the crypto market.
Overview of the Altcoin Season Index
The Altcoin Season Index calculates how well the top 10 altcoins are performing compared to Bitcoin over a given period. It helps traders determine if they are currently in an "Altcoin Season" or a "Bitcoin Season." The indicator gives a score from 0 to 100, representing the percentage of altcoins outperforming Bitcoin over a specific time window. When many altcoins are performing better than Bitcoin, it suggests a possible "Altcoin Season," whereas the opposite may indicate a period of Bitcoin dominance.
Key Features:
1. Top 10 Altcoin Performance Comparison: The indicator evaluates the performance of the top 10 altcoins compared to Bitcoin. It provides a clear view of how well altcoins are doing relative to the market leader, Bitcoin.
2. Customizable Performance Period: The period of analysis is adjustable, allowing users to set a specific timeframe, typically in days, to evaluate the relative performance of altcoins versus Bitcoin.
3. Dynamic Replacement of Altcoins: The indicator includes a feature to replace the last coin in the list, ensuring that the data stays relevant as market conditions change. For example, when a new altcoin enters the top 10 in terms of market cap, the indicator can replace an older coin that is falling out of the top ranks.
4. Threshold Indicators: The indicator uses predefined thresholds to determine and visualize whether it is an "Altcoin Season" or a "Bitcoin Season":
- A value above 75 indicates an Altcoin Season, suggesting that altcoins are outperforming Bitcoin.
- A value below 25 suggests Bitcoin dominance, where Bitcoin is outperforming the majority of altcoins.
How the Indicator Works:
1. Performance Calculation: The indicator calculates the percentage change in price for each of the top 10 altcoins and Bitcoin over a given number of days. The comparison is made by looking at how much each asset's price has changed over the specified period.
2. Altcoin Season Calculation: The indicator counts the number of altcoins that have outperformed Bitcoin during the given period. The result is then expressed as a percentage, known as the Altcoin Season Index. If 8 out of 10 altcoins are outperforming Bitcoin, the index will be 80%, signaling a strong altcoin season.
3. Visual Representation: The indicator is visualized on a separate panel within TradingView, showing the Altcoin Season Index over time. Additionally, thresholds are marked on the chart, and background colors are applied to provide visual cues:
- Red Background: When the Altcoin Season Index is above 75, indicating a strong altcoin season.
- Blue Background: When the Altcoin Season Index is below 25, indicating Bitcoin dominance.
Practical Use:
- Identify Market Cycles: Traders can use this indicator to identify when the market is moving into or out of an altcoin season. This can help traders decide whether to rotate capital into altcoins or Bitcoin.
- Investment Strategy Adjustment: During altcoin seasons, altcoins tend to outperform Bitcoin. Traders might allocate more of their portfolio to promising altcoins. Conversely, during Bitcoin-dominant periods, shifting investments towards Bitcoin could provide more stability.
- Support Technical Analysis: This indicator complements other forms of technical analysis by providing macro-level insights about market direction and which asset classes might be favored.
Example Usage:
Imagine that the Altcoin Season Index is currently at 80%. This means that 8 of the top 10 altcoins have performed better than Bitcoin over the selected period. This strong altcoin performance suggests that the market has entered an "Altcoin Season." A trader observing this might consider reallocating funds towards altcoins to capitalize on the positive momentum.
Alternatively, if the index is at 20%, only 2 out of the top 10 altcoins are outperforming Bitcoin, indicating that Bitcoin is currently the stronger player. In this scenario, traders may choose to prioritize Bitcoin or maintain a more conservative portfolio allocation.
Note:
This indicator includes a feature to replace the bottom-ranked altcoin (typically a coin that falls out of the top 10) with a new altcoin when market conditions change. This ensures that the analysis remains relevant by focusing on the top-performing assets by market capitalization.
Conclusion:
The Altcoin Season Index is a helpful tool for understanding broader trends in the cryptocurrency market and making strategic investment decisions. By monitoring which assets are performing better, traders can adapt their strategies and make more informed choices, particularly during shifts in market sentiment.
Please leave your feedback or contributions if there are any inaccuracies in my indicator. Thank you!
Risk Indicator# Risk Indicator
A dynamic risk analysis tool that helps traders identify optimal entry and exit points using a normalized risk scale from 0 to 1. The indicator combines price action, moving averages, and logarithmic scaling to provide clear visual signals for different risk zones.
### Key Features
• Displays risk levels on a scale of 0-1 with intuitive color gradients (blue → cyan → green → yellow → orange → red)
• Shows predicted price levels for different risk values
• Divides the chart into 5 DCA (Dollar Cost Average) zones
• Includes customizable alerts for rapid risk changes and zone transitions
• Automatically adjusts to market conditions using dynamic ATH/ATL calculations
### Customizable Parameters
• SMA Period: Adjust the smoothing period for the baseline moving average
• Power Factor: Fine-tune the sensitivity of risk calculations
• Initial ATL Value: Set the starting point for ATL calculations
• Label Offset: Adjust the position of price level labels
• Visual Options: Toggle price levels and zone labels
• Alert Settings: Customize alert thresholds and enable/disable notifications
### Risk Zones Explained
The indicator divides the chart into five distinct zones:
- 0.0-0.2: DCA 5x (Deep Blue) - Strongest buy zone
- 0.2-0.4: DCA 4x (Cyan) - Strong buy zone
- 0.4-0.6: DCA 3x (Green) - Neutral zone
- 0.6-0.8: DCA 2x (Yellow/Orange) - Take profit zone
- 0.8-1.0: DCA 1x (Red) - Strong take profit / potential sell zone
### Alerts
Built-in alerts for:
• Rapid increases in risk level
• Rapid decreases in risk level
• Entry into buy zones
• Entry into sell zones
### How to Use
1. Add the indicator to your chart
2. Adjust the SMA period and power factor to match your trading timeframe
3. Monitor the risk level and corresponding price predictions
4. Use the DCA zones to guide your position sizing
5. Set up alerts for your preferred risk thresholds
### Tips
- Lower risk values (blue/cyan) suggest potentially good entry points
- Higher risk values (orange/red) suggest taking profits or reducing position size
- Use in conjunction with other technical analysis tools for best results
- Adjust the power factor to fine-tune sensitivity to price movements
### Notes
- Past performance is not indicative of future results
- This indicator is meant to be used as part of a complete trading strategy
- Always manage your risk and position size according to your trading plan
Version 1.0
LRSI-TTM Squeeze - AynetThis Pine Script code creates an indicator called LRSI-TTM Squeeze , which combines two key concepts to analyze momentum, squeeze conditions, and price movements in the market:
Laguerre RSI (LaRSI): A modified version of RSI used to identify trend reversals in price movements.
TTM Squeeze: Identifies market compressions (low volatility) and potential breakouts from these squeezes.
Functionality and Workflow of the Code
1. Laguerre RSI (LaRSI)
Purpose:
Provides a smoother and less noisy version of RSI to track price movements.
Calculation:
The script uses a filtering coefficient (alpha) to process price data through four levels (L0, L1, L2, L3).
Movement differences between these levels calculate buying pressure (cu) and selling pressure (cd).
The ratio of these pressures forms the Laguerre RSI:
bash
Kodu kopyala
LaRSI = cu / (cu + cd)
The LaRSI value indicates:
Below 20: Oversold condition (potential buy signal).
Above 80: Overbought condition (potential sell signal).
2. TTM Squeeze
Purpose:
Analyzes the relationship between Bollinger Bands (BB) and Keltner Channels (KC) to determine whether the market is compressed (low volatility) or expanded (high volatility).
Calculation:
Bollinger Bands:
Calculated based on the moving average (SMA) of the price, with an upper and lower band.
Keltner Channels:
Created using the Average True Range (ATR) to calculate an upper and lower band.
Squeeze States:
Squeeze On: BB is within KC.
Squeeze Off: BB is outside KC.
Other States (No Squeeze): Neither of the above applies.
3. Momentum Calculation
Momentum is computed using the linear regression of the difference between the price and its SMA. This helps anticipate the direction and strength of price movements when the squeeze ends.
Visuals on the Chart
Laguerre RSI Line:
An RSI indicator scaled to 0-100 is plotted.
The line's color changes based on its movement:
Green line: RSI is rising.
Red line: RSI is falling.
Key levels:
20 level: Oversold condition (buy signal can be triggered).
80 level: Overbought condition (sell signal can be triggered).
Momentum Histogram:
Displays momentum as histogram bars with colors based on its direction and strength:
Lime (light green): Positive momentum increasing.
Green: Positive momentum decreasing.
Red: Negative momentum decreasing.
Maroon (dark red): Negative momentum increasing.
Squeeze Status Indicator:
A marker is plotted on the zero line to indicate the squeeze state:
Yellow: Squeeze On (compression active).
Blue: Squeeze Off (compression ended, movement expected).
Gray: No Squeeze.
Information Table
A table is displayed in the top-right corner of the chart, showing closing prices for different timeframes (e.g., 1 minute, 5 minutes, 1 hour, etc.). Each timeframe is color-coded.
Alerts
LaRSI Alerts:
Crosses above 20: Exiting oversold condition (buy signal).
Crosses below 80: Exiting overbought condition (sell signal).
Squeeze Alerts:
When the squeeze ends: Indicates a potential price move.
When the squeeze starts: Indicates volatility is decreasing.
Summary
This indicator is a powerful tool for determining market trends, momentum, and squeeze conditions. It helps users identify periods when the market is likely to move or remain stagnant, providing alerts based on these analyses to support trading strategies.
PIVOTBOSS ADR The PivotBoss ADR Method offers a complete approach to analyzing the volatility for a
given market in multiple timeframes by simply using average daily range. The ADR Breakout
helps us identify markets that are extremely compressed and due for significant expansion.
The PivotBoss ADR Targets Indicator is a simple, yet powerful, tool that helps you forecast extremely accurate targets based on the volatility of a given instrument. This indicator self-adjusts to a market's current volatility in order to plot reliable targets in multiple timeframes, including daily, weekly, and monthly targets.
1. Compression/Expansion: The development of trading ranges (Compression) builds the energy that will lead to the next
phase of price discovery (Expansion). ADR helps us quantify when a range is significantly compressed and due for expansion.
2. Volatility: Measures the SPEED of a market in order to forecast future volatility and price behavior. Markets rotate between
LOW and HIGH volatility states. Low ADR readings (<65% ADR) suggest significant compression, implying expansion ahead.
3. The ADR Breakout (Expansion Day): A true breakout from a narrow ADR range includes an Expansion Day, which is a
Trend Day on Day 1, wherein the session’s midpoint exceeds the breakout point and sees a Close beyond the range.
4. The ADR Breakout (Rejection Day): A failed breakout from a narrow ADR range includes a Rejection Day, which may take
the form of a long tail on Day 1, wherein the market attempted range expansion, but failed and closes back within the range.
This signature oftentimes leads to major expansion on the OPPOSITE side of the range.
5. A Variety of Trade Opportunities: Once TRUE expansion occurs from a narrow ADR range, a variety of trade opportunities
present themselves over the course of the next several days, or even weeks. These opportunities include swing trades, day
trades, and even scalps. Understanding when and where to look for these opportunities is key
Crypto Arbitrage Scanner [CryptoSea]Crypto Arbitrage Scanner
The Crypto Arbitrage Scanner is an advanced tool designed to help traders identify arbitrage opportunities across multiple cryptocurrency exchanges. With the ability to compare prices, volumes, and differences in price, this indicator is a must-have for any trader seeking to exploit cross-exchange inefficiencies in real time.
Key Features
Multi-Exchange Price and Volume Comparison: Tracks data from multiple major cryptocurrency exchanges, including BINANCE, COINBASE, KUCOIN, and others, allowing traders to easily compare prices and volume across platforms.
Customizable Difference Metrics: Allows users to toggle between displaying price differences in percentages or absolute dollar values, depending on the preferred metric for arbitrage analysis.
Sorting and Filtering Options: Includes user-defined sorting options to order the data by Price, Volume, or Difference, helping to prioritize potential arbitrage opportunities based on the trader's chosen criteria.
Difference and Volume Thresholds: Users can specify the minimum volume and price difference thresholds, ensuring that only significant arbitrage opportunities are highlighted.
Real-Time Alerts: Built-in alert conditions notify users when arbitrage opportunities exceed their defined price difference thresholds, helping traders respond instantly to market movements.
The Crypto Arb Scanner displays a table of prices, volumes, and price differences across selected exchanges. Each exchange is listed along with the current close price, volume, and the difference in price compared to the average price across all exchanges. Highlighting is used to indicate significant differences that may present arbitrage opportunities.
In the example below, we can see a highlighted opportunity in green showing that the price is below the user inputed thresold.
How it Works
Data Collection: Gathers real-time volume and price data from various exchanges using a streamlined process, allowing for a detailed comparison.
Average Price Calculation: Computes the average price across all valid exchanges to identify where price discrepancies occur, providing a clear picture of arbitrage potential.
Sorting Mechanism: Utilizes custom sorting based on user preferences, making it easy to quickly analyze and identify key opportunities.
Dynamic Highlighting and Alerts: Price differences that exceed user-defined thresholds are highlighted, and alerts can be triggered for these arbitrage opportunities, allowing for a timely response.
Application
Arbitrage Trading: The Crypto Arb Scanner is ideal for traders looking to exploit price differences across exchanges, enabling efficient arbitrage opportunities.
Market Efficiency Analysis: Offers insights into the consistency of prices across exchanges, which can help gauge the efficiency and liquidity of the markets being traded.
Customizable Alerts: Set alerts based on price differences or volume, allowing traders to stay informed about changes without constantly monitoring the markets.
The Crypto Arbitrage Scanner is a powerful addition to any trader's toolkit, offering comprehensive features to detect arbitrage opportunities with confidence. With real-time monitoring, customizable metrics, and a user-friendly interface, this tool allows traders to make informed decisions and capitalize on inefficiencies across exchanges.
RamanVol with Bull Snort Candles and Power Volumes1. Volume Analysis and Conditions:
Pocket Pivot Volume (PPV): A condition where a bar's volume on an up day is greater than the highest down-day volume in the last lookbackPeriod (e.g., 10 days). This indicates strong buying interest and is highlighted with blue bars.
High Down-Bar Volume: Identifies high volume on down days, with the volume greater than the 50-period moving average. This is represented by red bars.
High Up-Bar Volume: Identifies high volume on up days, with the volume greater than the 50-period moving average, represented by green bars.
Low Volume: When the volume is below 20% of the moving average volume (lowVolumeFraction), the bar is colored orange, indicating a "dry" or low volume day.
HVE (Highest Volume Ever): Marks the highest volume ever observed, indicated by a purple label above the bar.
HVQ (Highest Volume in Quarter): Marks the highest volume in the last quarter (63 days), indicated by an orange label (Q).
LVQ (Lowest Volume in Quarter): Marks the lowest volume in the last quarter, indicated by a Q label above the bar.
LVY (Lowest Volume in Year): Marks the lowest volume in the last year, indicated by a Y label.
2. Bull Snort Candles:
A Bull Snort candle is a specific type of candle that meets the following criteria:
Volume is more than 3 times the 50-period volume moving average.
The price closes within the top 35% of the day's range.
The close is higher than the previous bar's close.
When a Bull Snort is detected, the background color of the chart turns purple, and a small dot is plotted below the bar (if enabled).
3. Power Volume:
Power Volume occurs when the volume exceeds a certain threshold (e.g., 500,000) and the price moves at least 5% on that bar.
When these conditions are met, the background of the chart is highlighted with a yellow headlight effect, indicating a significant volume and price movement.
4. Relative Volume (RVol):
Relative Volume compares the current volume to the moving average of volume (50-period), showing how much higher or lower the volume is relative to the average. This is expressed as a percentage (e.g., 200% if today's volume is twice the average volume).
5. Table Display:
The indicator updates a table on the right side of the chart with the following metrics:
RVol: Displays the relative volume as a percentage.
Avg Dollar Volume: Shows the average dollar volume (average volume * average price).
Volume RR (Run Rate): Displays the percentage by which today's volume is higher or lower than the moving average.
Up/Down Volume Ratio: A measure of the ratio of total volume on up days to down days. If this ratio is greater than 1, it's considered bullish.
6. Background Highlights:
Bull Snort Candles: The background turns purple when Bull Snort candles are detected.
Power Volumes: The background turns yellow when Power Volume conditions are met.
Low Volume: Days with very low volume are marked with orange bars.
CREDITS: @finallynitin, Mark Minervini, Gill Morales, Dr Chris, Oliver Kell
Double Purge Theory (DPT)The purpose of this script is to identify the Double Purge Theory-MMXM i.e. the run on liquidity on both the sell-side and the buy-side liquidity.
The simple use case behind this script is to provide additional entry confluence for your trade setups and more efficient stop loss placement on any given timeframe.
DPT in itself is a price signature that generally occurs before price makes impulsive move in the direction of the higher time frame narrative. It is not to be used as a standalone indicator for building narrative/framing bias.
How to use this script ?
1) Wait for the indicator to display the BLUE CANDLE highlight (DPT candle) that indicates the double purge has occurred.
2) The DPT should occur at/after price has tapped into a key level and is within the ICT killzones.
3) Position to frame your trade setup once you get a candle with a body close below / above the DPT candle , depending on your bias and stop loss placement at DPT candle high/low or after the body closure as mentioned in step 2.
For example :
Quantum Transform - AynetQuantum Transform Trading Indicator: Explanation
This script is called a "Quantum Transform Trading Indicator" and aims to enhance market analysis by applying complex mathematical models. Written in Pine Script, the indicator includes the following elements:
1. General Structure
Quantum Parameters: Inspired by physical and mathematical concepts (Planck constant ℏ, wave function Ψ, time τ, etc.), it uses specific parameters.
Transformation Functions: Applies various mathematical operations to transform price data in different ways.
Signal Generation: Produces signals for long and short positions.
Visualization: Displays different price transformations and signals on the chart.
2. Core Parameters
The parameters allow users to control various transformations:
Planck Constant (ℏ): A scaling factor for wave modulation.
Wave (Ψ): Controls oscillation in price data.
Time (τ): The length of the lookback period for calculations.
Relativity (γ): Power factor in the Lorentz transformation.
Phase Shift (β): Manages phase shift in transformations.
Frequency (ω): Represents the frequency of price movements.
Dimensions (∇): Enables multi-dimensional field analysis.
3. Functions
a) Relativistic Transform
Inspired by the theory of relativity.
Calculates the Lorentz factor using the rate of price change.
Transforms price data to amplify the relativity effect.
b) Phase Transform
Calculates the phase of price data and applies wave modulation.
Creates phase and amplitude modulation based on the bar index.
c) Resonance Transform
Calculates resonance effects using natural frequency and oscillations.
Highlights periodic behaviors of price movements.
d) Field Transform
Applies multi-dimensional field calculations.
Combines strength, wave, and coherence aspects of price data.
e) Chaos Transform
Implements a chaos effect based on sensitivity analysis.
Simulates chaotic behaviors of price movements.
4. Main Calculations
Quantum Price: The average of all transformation functions.
Bands:
Upper Band: The highest level of quantum price.
Lower Band: The lowest level of quantum price.
Mid Band: The average of upper and lower bands.
Momentum: Calculates the rate of change in quantum price.
5. Signal Generation
Long Signal:
Triggered when the phase price crosses above the field price.
Momentum must be positive, and the price above the mid-band.
Short Signal:
Triggered when the phase price crosses below the field price.
Momentum must be negative, and the price below the mid-band.
Signal strength is calculated relative to the momentum moving average.
6. Visualization
Each transformation is displayed in a unique color.
Bands and Momentum: Visualize price behavior.
Signal Icons: Show buy/sell signals using up/down arrows on the chart.
7. Information Panel
A table in the top-right corner of the chart displays:
The current values of each transformation.
Signal strength (as a percentage).
The type of signal (⬆: Long, ⬇: Short).
Applications
Trend Following: Analyze trends with complex transformations.
Resonance and Chaos Analysis: Understand dynamic behaviors of price.
Signal Strategies: Create strong and reliable buy/sell signals.
If you have any additional questions or customization requests regarding this indicator, feel free to ask!
Azlan MA Silang PLUS++Overview
Azlan MA Silang PLUS++ is an advanced moving average crossover trading indicator designed for traders who want to jump back into the market when they missed their first opportunity to take a trade. It implements a sophisticated dual moving average system with customizable settings and re-entry signals, making it suitable for both trend following and swing trading strategies.
Key Features
• Dual Moving Average System with multiple MA types (EMA, SMA, WMA, LWMA)
• Customizable price sources for each moving average
• Smart re-entry system with configurable maximum re-entries
• Visual signals with background coloring and shape markers
• Comprehensive alert system for both initial and re-entry signals
• Flexible parameter customization through input options
Input Parameters
Moving Average Configuration
• MA1 Type: Choice between SMA, EMA, WMA, LWMA (default: EMA)
• MA2 Type: Choice between SMA, EMA, WMA, LWMA (default: EMA)
• MA1 Length: Minimum value 1 (default: 8)
• MA2 Length: Minimum value 1 (default: 15)
• MA1 & MA2 Shift: Offset values for moving averages
• Price Sources: Configurable for each MA (Open, High, Low, Close, HL/2, HLC/3, HLCC/4)
Re-entry System
• Enable/Disable re-entry signals
• Maximum re-entries allowed (default: 3)
Technical Implementation
Price Source Calculation
The script implements a flexible price source system through the price_source() function:
• Supports standard OHLC values
• Includes compound calculations (HL/2, HLC/3, HLCC/4)
• Defaults to close price if invalid source specified
Moving Average Types
Implements four MA calculations:
1. SMA (Simple Moving Average)
2. EMA (Exponential Moving Average)
3. WMA (Weighted Moving Average)
4. LWMA (Linear Weighted Moving Average)
Signal Generation Logic
Initial Signals
• Buy Signal: MA1 crosses above MA2 with price above both MAs
• Sell Signal: MA1 crosses below MA2 with price below both MAs
Re-entry Signals
Re-entry system activates when:
1. Price crosses under MA1 in buy mode (or over in sell mode)
2. Price returns to cross back over MA1 (or under for sells)
3. Position relative to MA2 confirms trend direction
4. Number of re-entries hasn't exceeded maximum allowed
Visual Components
• MA1: Blue line (width: 2)
• MA2: Red line (width: 2)
• Background Colors:
o Green (60% opacity): Bullish conditions
o Red (60% opacity): Bearish conditions
• Signal Markers:
o Initial Buy/Sell: Up/Down arrows with "BUY"/"SELL" labels
o Re-entry Buy/Sell: Up/Down arrows with "RE-BUY"/"RE-SELL" labels
Alert System
Generates alerts for:
• Initial buy/sell signals
• Re-entry opportunities
• Alerts include ticker and timeframe information
• Configured for once-per-bar-close frequency
Usage Tips
1. Moving Average Selection
o Shorter periods (MA1) capture faster moves
o Longer periods (MA2) identify overall trend
o EMA responds faster to price changes than SMA
2. Re-entry System
o Best used in strong trending markets
o Limit maximum re-entries based on market volatility
o Monitor price action around MA1 for potential re-entry points
3. Risk Management
o Use additional confirmation indicators
o Set appropriate stop-loss levels
o Consider market conditions when using re-entry signals
Code Structure
The script follows a modular design with distinct sections:
1. Input parameter definitions
2. Helper functions for price and MA calculations
3. Main signal generation logic
4. Visual elements and plotting
5. Alert system implementation
This organization makes the code maintainable and easy to modify for custom needs.
Relative Momentum StrengthThe Relative Momentum Strength (RMS) indicator is designed to help traders and investors identify tokens with the strongest momentum over two customizable timeframes. It calculates and plots the percentage price change over 30-day and 90-day periods (or user-defined periods) to evaluate a token's relative performance.
30-Day Momentum (Green Line): Short-term price momentum, highlighting recent trends and movements.
90-Day Momentum (Blue Line): Medium-term price momentum, providing insights into broader trends.
This tool is ideal for comparing multiple tokens or assets to identify those showing consistent strength or weakness. Use it to spot outperformers and potential reversals in a competitive universe of assets.
How to Use:
Apply this indicator to your TradingView chart for any token or asset.
Look for tokens with consistently high positive momentum for potential strength.
Use the plotted values to compare relative performance across your watchlist.
Customization:
Adjust the momentum periods to suit your trading strategy.
Overlay it with other indicators like RSI or volume for deeper analysis.
3 Drive Harmonic Pattern [TradingFinder] Three Drive Reversal🔵 Introduction
The Three Drive harmonic pattern closely resembles other price structures such as Wedge Pattern and Three Push Pattern, yet it stands out due to its precise use of Fibonacci ratios and symmetrical price movements.
This pattern comprises three consecutive and symmetrical price drives, each validated by key Fibonacci ratios (1.27 and 1.618), which help identify critical Potential Reversal Zones (PRZ).
Unlike the Wedge, which relies on converging trend lines and can indicate either continuation or reversal, and the Three Push, which lacks defined Fibonacci ratios and symmetry, the Three Drive pattern defines PRZ with greater accuracy, providing traders with high-probability trading opportunities.
This pattern appears in both bullish and bearish trends. After the completion of the third drive (Drive 3), it signals the market's readiness to reverse direction. The PRZ in this pattern serves as a crucial zone where price is highly likely to reverse, offering a strategic point for entering or exiting trades. Professional traders utilize the Three Drive pattern and PRZ as essential tools for analyzing and capitalizing on potential market reversals.
Bullish Pattern :
Bearish Pattern :
🔵 How to Use
The Three Drive harmonic pattern is an effective tool for identifying potential reversal points in the market. By utilizing Fibonacci extension levels (1.27 and 1.618) and focusing on the pattern’s symmetry, traders can pinpoint Potential Reversal Zones (PRZ) where the price is likely to change direction. This pattern works in both bearish and bullish scenarios, each with distinct characteristics and trading opportunities.
🟣 Bullish Three Drive Pattern
The bullish Three Drive pattern develops during a downtrend, indicating a potential reversal to the upside. Similar to its bearish counterpart, this pattern features three consecutive downward price movements (drives) with retracements in between. The third drive concludes within the PRZ, which serves as a strong support zone where the price is expected to reverse upwards.
The first drive begins with a downward movement, followed by a retracement to the 0.618 Fibonacci level. The second drive continues downward to reach a 1.27 or 1.618 Fibonacci extension of the retracement. Finally, the third drive aligns with the PRZ, where a confluence of Fibonacci levels creates a high-probability support zone.
In the PRZ, traders look for bullish confirmation signals such as bullish candlestick patterns (e.g., bullish engulfing or pin bars) or increasing trading volume. Once confirmation is observed, the PRZ becomes an ideal entry point for a buy position. Stop-loss orders are placed slightly below the PRZ to minimize risk, while take-profit targets are set at key resistance levels or Fibonacci retracement levels.
🟣 Bearish Three Drive Pattern
The bearish Three Drive pattern forms during an uptrend, signaling a potential reversal to the downside. This pattern consists of three consecutive upward price movements (drives) and intermediate retracements. Each drive aligns with Fibonacci extension levels, and the third drive ends within the PRZ, indicating a high probability of a bearish reversal.
In the first drive, the price moves upward and then retraces to approximately the 0.618 Fibonacci retracement level, forming the base for the second drive. The second drive then extends upward to the 1.27 or 1.618 Fibonacci extension of the preceding retracement. This process repeats for the third drive, which reaches the PRZ, typically defined by the convergence of Fibonacci levels from previous drives.
Once the PRZ is identified, traders look for confirmation signals such as bearish candlestick patterns (e.g., bearish engulfing or pin bars) or declining trading volume. If confirmation is present, the PRZ becomes an optimal zone for entering a sell position. Stop-loss levels are typically placed slightly above the PRZ to protect against pattern failure, and take-profit targets are set at key support levels or Fibonacci retracement levels of the overall structure.
🟣 Three Drive Vs Wedge Pattern Vs 3 Push pattern
The Three Drive, Wedge, and Three Push patterns are all used to identify potential price reversal points, but they differ significantly in structure and application. The Three Drive pattern is based on three consecutive and symmetrical price movements, validated by precise Fibonacci ratios (1.27 and 1.618), to define Potential Reversal Zones (PRZ).
In contrast, the Wedge pattern relies on converging trend lines and does not require Fibonacci ratios; it can act as either a reversal or continuation pattern. Meanwhile, the Three Push pattern shares similarities with Three Drive but lacks precise symmetry and Fibonacci-based validation.
Instead of a PRZ, Three Push focuses on identifying areas of support and resistance, often signaling weakening momentum in the current trend. Among these, the Three Drive pattern is more reliable for pinpointing high-probability reversal zones due to its strict Fibonacci-based and symmetrical structure.
🔵 Setting
🟣 Logical Setting
ZigZag Pivot Period : You can adjust the period so that the harmonic patterns are adjusted according to the pivot period you want. This factor is the most important parameter in pattern recognition.
Show Valid Format : If this parameter is on "On" mode, only patterns will be displayed that they have exact format and no noise can be seen in them. If "Off" is, the patterns displayed that maybe are noisy and do not exactly correspond to the original pattern.
Show Formation Last Pivot Confirm : if Turned on, you can see this ability of patterns when their last pivot is formed. If this feature is off, it will see the patterns as soon as they are formed. The advantage of this option being clear is less formation of fielded patterns, and it is accompanied by the latest pattern seeing and a sharp reduction in reward to risk.
Period of Formation Last Pivot : Using this parameter you can determine that the last pivot is based on Pivot period.
🟣 Genaral Setting
Show : Enter "On" to display the template and "Off" to not display the template.
Color : Enter the desired color to draw the pattern in this parameter.
LineWidth : You can enter the number 1 or numbers higher than one to adjust the thickness of the drawing lines. This number must be an integer and increases with increasing thickness.
LabelSize : You can adjust the size of the labels by using the "size.auto", "size.tiny", "size.smal", "size.normal", "size.large" or "size.huge" entries.
🟣 Alert Setting
Alert : On / Off
Message Frequency : This string parameter defines the announcement frequency. Choices include: "All" (activates the alert every time the function is called), "Once Per Bar" (activates the alert only on the first call within the bar), and "Once Per Bar Close" (the alert is activated only by a call at the last script execution of the real-time bar upon closing). The default setting is "Once per Bar".
Show Alert Time by Time Zone : The date, hour, and minute you receive in alert messages can be based on any time zone you choose. For example, if you want New York time, you should enter "UTC-4". This input is set to the time zone "UTC" by default.
🔵 Conclusion
The Three Drive pattern is a highly effective harmonic tool for identifying potential reversal points in the market. By leveraging its symmetrical structure and precise Fibonacci ratios (1.27 and 1.618), this pattern provides traders with clear entry and exit signals, enhancing the accuracy of their trades.
Whether in bullish or bearish scenarios, the identification of the Potential Reversal Zone (PRZ) serves as a critical aspect of this pattern, enabling traders to anticipate price movements with greater confidence.
Compared to similar patterns like Wedge and Three Push, the Three Drive pattern stands out for its stringent reliance on Fibonacci levels and symmetrical price movements, making it a more robust choice for forecasting reversals. However, as with any technical analysis tool, its effectiveness increases when combined with confirmation signals, such as candlestick patterns, volume analysis, and broader market context.
Mastering the Three Drive pattern requires practice and attention to detail, especially in accurately defining the PRZ and ensuring the pattern adheres to its criteria. Traders who consistently apply this pattern as part of a comprehensive trading strategy can capitalize on high-probability opportunities and improve their overall performance in the market.
Crypto Index Creator (MEMES & AI Supercycle Dominance, etc)This indicator aims to help to create any INDEX desired including but not limited to its Market Cap and Dominance on the crypto market.
This script was inspired originally by Murad's "Memecoins Dominance" but then I extended it to AI and can be extended to anything in fact, so you can create any index!
I made each token entry editable so that the script can survive the evolution of time as likely projects and INDEXES are going to change a lot, so that you can add/modify your own indices of preference if not listed by default and in order to make it future proof.
You can play with the settings, can compare to BTC, ETC, SOL, etc. for helping in your studies
You also have the option to check the info of each symbol on a table available on the settings, in order to help you figure out if there are any errors and also help you to easily check how the symbols are performing individually
Notes:
- Many projects are not like MEMECOINS that have fixed supply, normally VC projects have a very variable circulating supply, so you might want to update the info of the circulating supply for your projects to make it more accurate if you desire.
- For this script there is a limit of 32 Symbols, due to tradingview own limits, yet you can always "add" multiple projects per line as long as their circulating supply is the same.
- You might want to edit/sort the tickers of the top3, top5 and top10 if they follow bellow those top ranks, but this is not necessary if you don't care about Top 3-10 specific calculations.
- My default "indices" were made of token selections of mine as of November 2024, those defaults indices/tickers I might or might not update them eventually but you are free to adapt/modify the tickers in the settings as history evolves, and you can leave your own indexes on the comment section of this post for others to use
- As you might not be able to create/store multiple different indexes at the same time, you might want to add this indicator multiple times on your screen and then modify the tickers of each instance of this indicator, by that you can have multiple indexes.
Daily PlayDaily Play Indicator
The Daily Play Indicator is a clean and versatile tool designed to help traders organize and execute their daily trading plan directly on their charts. This indicator simplifies your workflow by visually displaying key inputs like market trend, directional bias, and key levels, making it easier to focus on your trading strategy.
Features
Dropdown Selection for Trend and Bias:
• Set the overall market trend (Bullish, Bearish, or Neutral) and your directional bias (Long, Short, or Neutral) using intuitive dropdown menus. No more manual typing or guesswork!
Key Levels:
Quickly input and display the Previous Day High and Previous Day Low. These levels are essential for many trading strategies, such as breakouts.
Real-Time News Notes:
Add a quick note about impactful news or market events (e.g., “Fed meeting today” or “Earnings season”) to keep contextual awareness while trading.
Simple On-Chart Display:
The indicator creates a “table-like” structure on the chart, aligning your inputs in an easy-to-read format. The data is positioned dynamically so it doesn’t obstruct the price action.
Customisable Visual Style:
Simple labels with clear text to ensure that your chart remains neat and tidy.
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Use Case
The Daily Play Indicator is ideal for:
• Day traders and scalpers who rely on precise planning and real-time execution.
• Swing traders looking to mark critical levels and develop a trade plan before the session begins.
• Anyone who needs a structured way to stay focused and disciplined during volatile market conditions.
By integrating this tool into your workflow, you can easily align your daily preparation with live market action.
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How to Use
Open the indicator settings to configure your inputs:
• Trend: Use the dropdown to choose between Bullish, Bearish, or Neutral.
• Bias: Select Long, Short, or Neutral to align your personal bias with the market.
• Previous Day Levels: Enter the High and Low of the previous trading session for key reference points.
• News: Add a short description of any relevant market-moving events.
TCSE24TCSE24 or Trendband Cycle Special Edition is designed to help create a simple trading plan by identifying potential Entry, Exit, Target Price, and Stop Loss. I use TCSE24 as a guide for short-term swing trading!
Please note, TCSE24 is not a directional indicator but fits better in Trend Following Strategy.
Only work with chart that have volume by default
Signals for Bullish Trade
1. Trendband Below Candlestick
Filled Red with a Purple Line.
2. Cycle Begin
Bar Color: Vivid Green.
Green Circle Above Candlestick: Target Price.
Green Circle Below Candlestick: Pullback Entry.
Red Circle Below Candlestick: Stop Loss.
3. Breakout
Bar Color: Lemon Green.
Green Circle Below Candlestick: Pullback Entry.
Red Circle Below Candlestick: Stop Loss.
4. Broken Minor Support
Bar Color: Yellow.
Price closes below the lowest low of the last 4 candles.
5. Volume Test
Green Triangle-Up below Candlestick.
Current bar shows 3 consecutive falling volumes.
6. Inside Bar
Orange Triangle-Up below Candlestick.
High and low are within the high and low of the previous candlestick.
7. Box Trading
Purple Diamond
8. Cycle End
Bar Color: Red.
Red Triangle-Up below Candlestick.
9. Info Panel
Background Green, turning Yellow after 20 bars from Cycle Begin.
Background Red when Cycle Ends.
Displays info such as Current Price, Target Price, Pullback Price, Stop Loss.
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Signals for Bearish Trade
1. Trendband Above Candlestick
Filled with Blue.
2.Short Selling Begin
Bar Color: Blue.
Blue Circle Above Candlestick: Stop Loss.
Blue Circle Below Candlestick: Target Price.
3. Breakdown
Blue Circle Above Candlestick: Stop Loss.
4. Short Selling End
Bar Color: White.
Blue Triangle-Down above Candlestick.
5. Info Panel
Background Blue throughout the trade.
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Bullish Trade Entry Suggestions
1. Ensure Cycle Begin is confirmed:
Buy near the closing price.
Use a Buy Stop 2 ticks higher than Cycle Begin's highest price.
Use a Buy Limit at the pullback price.
Wait for a signal candlestick, then Buy the next day if the price rises above the signal candlestick’s high.
2. Ensure Breakout is confirmed:
Buy near the closing price.
Use a Buy Stop 2 ticks higher than Breakout’s highest price.
Use a Buy Limit at the pullback price.
3. Box Trading:
Buy on the third day (T3).
Buy above the Box Trading line.
4. Candlestick Signal:
Ensure the signal candlestick is confirmed:
Look for Doji, Spinning Top, or Hammer patterns.
Buy the next day if the price rises above the signal candle's high.
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Bullish Trade Exit Suggestions
1. Target Sell
Sell when the Target Price (TP) is reached or hold as long as Stop Loss isn’t hit.
Sell if the price doesn’t move, doesn’t reach the target, or doesn’t hit the Stop Loss after 20 candles from Cycle Begin.
Sell if the price closes below the Stop Loss.
2. Candlestick Signal
Look for Doji, Spinning Top, or Hammer patterns.
Sell the next day if the price drops below the signal candle's low.
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Bearish Trade Suggestions
Ensure Short Selling Signal or Breakdown is confirmed:
Sell near the closing price.
Close the position at Target 1, Target 2, Target 3.
Close the position if Stop Loss is hit or when Short Selling End appears.
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Any alert() function call freq
Once_per_bar_close
Cycle Begin, Inside Bar, Doji, Hammer, Spinning Top, Box Trading, Volume Test, Short Selling
Once_per_bar
Breakout, Cycle End
For educational purposes only and should not be taken as advice on how to invest your capital. Always speak with a professional financial planner or advisor before making any investment decisions.
