Display MB on BarsDescription
The "Display MB on Bars" Pine Script indicator is designed to visually represent Market Breadth values and R4.5 scores on trading charts. This script enables traders to highlight and analyze key market behavior using pre-defined thresholds for MB scores and dynamically calculated R4.5 values. Additionally, it includes a moving average status table to assess price levels relative to the 10-day and 20-day moving averages.
Features:
1. COB Date Matching: Displays data corresponding to specific "COB dates" provided by the user.
2. MB Value Visualization:
o Highlights bars with a background color based on MB values:
Red if MB ≤ MB_Red (default: -1).
Green if MB ≥ MB_Green (default: 3).
3. R4.5 Scores Display:
o Creates a label on the chart with the MB and R4.5 values when conditions are met (e.g., R4.5 > 200 or specific MB thresholds).
4. Index Moving Average Comparison:
o Calculates 10-day and 20-day moving averages for the selected symbol (default: NSE:NIFTYMIDSML400).
o Shows the price position relative to these moving averages in a table.
How to Use:
1. Configure Inputs:
o COB Dates: Enter a comma-separated list of dates in the format DD-MM-YYYY.
o MB Values: Provide the corresponding MB scores for the COB dates.
o R4.5 Values: Provide the R4.5 scores for the COB dates.
o Set the thresholds for MB values (MB Red<= and MB Green>=).
o Toggle features like MB, RS (R4.5), and the moving average status table.
2. Interpret the Output:
o Observe background colors on the bars:
Red: Indicates MB is less than or equal to the lower threshold.
Green: Indicates MB exceeds the upper threshold.
o Check labels above bars for R4.5 and MB values when conditions are met.
o Refer to the status table on the top-right corner to understand price positions relative to 10-day and 20-day moving averages.
This script is especially useful for traders seeking insights into custom metrics like MB and R4.5, enabling quick identification of key patterns and trends in the market.
חפש סקריפטים עבור "averages"
2 MA Simplified Sideways Candle ColorsHow to Use the Indicator: A Simple Guide
This custom indicator colors candlesticks to help you quickly identify market conditions based on two moving averages (9-period and 21-period). Here’s how to get started:
Add the Indicator to Your Chart:
Copy the provided Pine Script code.
Open TradingView and navigate to the Pine Editor.
Paste the code into a new script, save it, and then add the indicator to your chart.
Understand the Candlestick Colors:
Green Candles (Bullish):
Indicates a bullish market when the price is above the 9-period SMA and the 9 SMA is above the 21 SMA.
Red Candles (Bearish):
Indicates a bearish market when the price is below the 21-period SMA and the 9 SMA is below the 21 SMA.
Yellow Candles (Sideways):
Indicates a sideways (neutral) market when:
Condition 1: Price is below the 9 SMA but above the 21 SMA, with the 9 SMA above the 21 SMA, or
Condition 2: The 9 SMA is below the 21 SMA, and the price lies between them.
White Candles (No Clear Signal):
Used when none of the above conditions apply.
Interpreting the Signals:
When you see green candles, the market is showing bullish momentum.
When you see red candles, bearish pressure is dominant.
Yellow candles suggest the market is moving sideways without a strong trend.
White candles mean that none of the specific conditions (bullish, bearish, or sideways) are currently met.
Chart Reference:
The script also plots two moving averages on your chart (a blue line for the 9-period SMA and an orange line for the 21-period SMA). These lines help visualize how price interacts with these averages.
Using the Indicator in Practice:
Once added to your chart, monitor the color of the candlesticks:
Green signals may be opportunities to consider long positions.
Red signals may indicate a good time to consider short positions or tighten stops.
Yellow signals suggest caution as the market isn’t trending strongly.
White candles indicate no strong signal, so it might be a period of consolidation or indecision.
This simple visual cue system allows you to quickly assess market sentiment and make more informed trading decisions based on the relationship between price and the two moving averages.
Volume Weighted Jurik Moving AverageThe Jurik Moving Average (JMA) is a smoothing indicator that is designed to improve upon traditional moving averages by reducing lag while enhancing responsiveness to price movements. It was created by Jurik Research and is often used to track trends with greater accuracy and minimal delay. The JMA is based on a combination of **exponential smoothing** and **phase adjustments**, making it more adaptable to varying market conditions compared to standard moving averages like SMA (Simple Moving Average) or EMA (Exponential Moving Average).
The core advantage of the JMA lies in its ability to adjust to price changes without excessively lagging, which is a common issue with traditional moving averages. It incorporates a **phase parameter** that can be adjusted to smooth out the signal further or make it more responsive to recent price action. This phase adjustment allows traders to fine-tune the JMA's sensitivity to the market, optimizing it for different timeframes and trading strategies.
How JMA Works and Benefits of Adding Volume Weight
The JMA works by applying a **smoothing process** to price data while allowing for adjustments through its phase and power parameters. These parameters help control the degree of smoothness and responsiveness. The result is a curve that follows price trends closely but with less lag than traditional moving averages.
Adding **volume weighting** to the JMA enhances its ability to reflect market activity more accurately. Just like the **Volume-Weighted Moving Average (VWMA)**, volume-weighting adjusts the moving average based on the strength of trading volume, meaning that price movements with higher volume will have a greater influence on the JMA. This can help traders identify trends that are supported by significant market participation, making the moving average more reliable.
The benefit of a volume-weighted JMA is that it responds more effectively to price movements that occur during periods of high trading volume, which are often considered more significant. This can help traders avoid false signals that may occur during low-volume periods when price changes may not reflect true market sentiment. By incorporating volume into the calculation, the JMA becomes more aligned with real market conditions, enhancing its effectiveness for trend identification and decision-making.
Adaptive Fibonacci Trend Ribbon[FibonacciFlux]Adaptive Fibonacci Trend Ribbon (FibonacciFlux)
Overview
The Adaptive Fibonacci Trend Ribbon is a versatile technical analysis tool designed for traders who want to leverage the power of multiple moving averages while integrating Fibonacci numbers. This indicator provides a dynamic visual representation of market trends, enhancing decision-making processes in trading.
Key Features
1. Multi-Moving Averages
- The indicator calculates eight different moving averages based on user-defined periods, including Fibonacci numbers such as 5, 8, 13, 21, 34, 55, 89, and 144.
- Traders can choose from various moving average types, including EMA, HMA, WMA, VWMA, ALMA, SMA, RMA, and TMA , allowing for tailored analysis based on market conditions.
2. Trend Detection
- Each moving average is color-coded based on its trend direction, with green indicating an upward trend and red indicating a downward trend.
- This visual clarity helps traders quickly assess market sentiment and make informed decisions.
3. Fill Areas for Enhanced Insight
- The indicator features fill areas between the moving averages, which dynamically change color according to their relative positions.
- This provides a clear visual cue of trend strength and potential reversal points, allowing traders to identify key areas of interest.
4. Customizable Inputs
- Users can easily adjust the source data, moving average lengths, and ALMA parameters (offset and sigma) to fit their trading strategies.
- This flexibility ensures that traders can adapt the tool to various market conditions and personal preferences.
Insights and Applications
1. Fibonacci Integration
- By incorporating Fibonacci numbers into the moving average periods, this indicator allows traders to align their strategies with key levels of support and resistance.
- This can enhance the accuracy of entry and exit points, particularly in trending markets.
2. Trend Continuation and Reversal Analysis
- The adaptive nature of the moving averages provides insights into potential trend continuations or reversals.
- Traders can use the indicator to identify when to enter or exit positions based on the interaction between the moving averages.
3. Visual Clarity for Quick Decisions
- The color-coded moving averages and fill areas offer immediate visual feedback on market conditions, helping traders react swiftly to changing dynamics.
- This is especially useful in fast-moving markets where timely decisions are critical.
Conclusion
The Adaptive Fibonacci Trend Ribbon is an essential tool for traders looking to enhance their technical analysis capabilities. By combining multiple moving averages with Fibonacci integration and dynamic visual cues, this indicator offers a robust framework for understanding market trends. Its flexibility and clarity make it an invaluable asset for both novice and experienced traders alike.
Open Source Contribution
This indicator is open source, inviting contributions and improvements from the trading community. Feel free to fork, enhance, and share your insights with the world, helping to foster a collaborative environment for traders everywhere.
WPR Volume Candle [Atareum]AWPRVC (Atareum WPR Volume Candles) is clearly an awesome indicator produced by AtareumFX that is based on William’s Percent Range concepts by combination with volume. This is a new approach of volume candles that is combined with R% concepts and creates such a powerful tool to trace the market and assists traders to make better decisions surly and so much accurate. You can find this new indicator more useful because it has all benefits and advantages of William’s R% and cover its disadvantages. Also it is more powerful because of using volume in its calculations and generate a new candles which is more reliable and trustworthy.
Concept:
Using William’s Percent leading periods and calculations on redesigning new candles in combination with volume, that makes unique reform candles, but these new candles with their new cloud system clearly response to any reasonable price movement with so much information.
As you know if use R% there are some misleading fake signals generate by oscillator, also it could not show any sign of price moving trend which is almost confusing for beginners or even a pro trader! And finally this oscillator is so sensitive to price change that is so creepy to use for most of traders.
This new AWPRVC solve the problem and make all of them handy and useful for you.
The cloud system which is designed in AWPRVC shows the price trend moving from Bearish Zone (-100 to -50 percent) to Bullish Zone (-50 to 0 percent). You can trust the lead moving forward of the clouds in two separate Top and Bottom (Bull and Bear) lines which solely determine the trend and power of price moving. When clouds are close to each other means we continue the trend and when they get far away from each other means we will face powerful trend in near future. If they are in Bearish Zone we continue the selling pressure and vice versa. Following picture shows good sample of Long and Short positions in compare with so many fake signals generated on original R%.
Besides the cloud system of AWPRVC which is clearly show the price trend and it is completely enough for being sure about price moving trend, you can use moving average which is designated in it to confirm the price trend, also.
Also you can see this new AWPRVC candle by using volume within its conformation, make reasonable price candles which is no so sensitive and so creepy and make your decisions come true in peace and clear sense of market moves. You can see following picture which is showing although the real price candles are so unclear and nonsense of making decision but the AWPRVC candles lead you to make true and trustable position.
As you see this new combination of Williams R% oscillator with volume and also generating a perfect new cloud system will clearly help traders even pro to trust the signals and understand whole market movement better and all of original problems of R% solved and even make a most powerful, trustworthy and useful new indicator.
Parameters:
Section 1 : Candle colour setting for flourishing just as you desire !
Section 2 : Defining Periods of R% and source of candle data in combination with determining the smoothing type of moving averages and signal period.
Section 3 : Select using Standard candles alongside with redesigned cloud calculation type and three additional moving averages which can plot on each newly generated candles and standard candles on a chart with the type mode defined in the previous section.
Note: if you want to omit any or all of these moving averages, you can use 0 in period, instead of selecting "None" in the plot moving option!
Usage :
Overall:
Regardless of the additional moving averages which will lead to so many situations of market according to their types and designs, that is four different period for new redesign AWPRVC and three period for standard chart. You can easily select periods and type for these moving averages. Also, do not forget that signal moving averages is shown only on AWPRVC chart and have two different colour for upward and downward trends. Other moving averages are plot by just one single colour.
Cloud levels are so important because AWPRVC candles show respect to them and when they break the clouds upward or downward it is surly beginning of a trend. Do not forget we have 5 levels for tracing new AWPRVC candles move as follows : Ready for Short \ Long, Surly Short \ Long and Turn Trend which is in middle range of movement percent. Each level clearly shows what it means by its name.
Support and Resistance:
Any consolidation of AWPRVC candles in Ready for Short or Long Zones means the support or resistance level due to its nature, but important thing is how long the candles lasts in there or how many times repeated in the same level in AWPRVC chart zone in future.
For plotting the support or resistance you should trace range of AWPRVC candles consolidated and plot zone in standard chart candles just like following picture.
Divergence:
When standard price candles move downward but we see upward trend in clouds of AWPRVC candles that means we should face Bullish Trend because of the divergence and vice versa. You can see perfect example in following picture.
Signal:
Alert of Long :
Bullish candle cross both cloud down and up level simultaneously.
Confirmed Long :
AWPRVC candles cross up turn trend level and pullback to cloud up level.
Take profit of Long:
Any cross down of the AWPRVC candles from surly short level of chart.
Alert of Short :
Bearish candle cross both cloud up and down level simultaneously.
Confirmed Short :
AWPRVC candles cross down turn trend level and pullback to cloud down level.
Take profit of Short:
Any cross up of the AWPRVC candles from surly long level of chart.
Notes:
Use moving averages cross of standard chart candles as lead to be in positions more as they are good representative of trend.
As long as AWPRVC candles or Cloud levels are in Bullish Zone, you can stay in Long positions.
Cloud level thickness means the power of trend and can be use as confirmation of powerful trend, so when cloud levels tight or going to cross each other it means the trend is going to be reversed.
It is the result of many years of experience in markets and there are so many details about this AWPRVC chart which I am in the experiment phase to publish in the future, so please help me with your ideas and do not hesitate to comment and inform me any suggestions or criticism.
Leading T3Hello Fellas,
Here, I applied a special technique of John F. Ehlers to make lagging indicators leading. The T3 itself is usually not realling the classic lagging indicator, so it is not really needed, but I still publish this indicator to demonstrate this technique of Ehlers applied on a simple indicator.
The indicator does not repaint.
In the following picture you can see a comparison of normal T3 (purple) compared to a 2-bar "leading" T3 (gradient):
The range of the gradient is:
Bottom Value: the lowest slope of the last 100 bars -> green
Top Value: the highest slope of the last 100 bars -> purple
Ehlers Special Technique
John Ehlers did develop methods to make lagging indicators leading or predictive. One of these methods is the Predictive Moving Average, which he introduced in his book “Rocket Science for Traders”. The concept is to take a difference of a lagging line from the original function to produce a leading function.
The idea is to extend this concept to moving averages. If you take a 7-bar Weighted Moving Average (WMA) of prices, that average lags the prices by 2 bars. If you take a 7-bar WMA of the first average, this second average is delayed another 2 bars. If you take the difference between the two averages and add that difference to the first average, the result should be a smoothed line of the original price function with no lag.
T3
To compute the T3 moving average, it involves a triple smoothing process using exponential moving averages. Here's how it works:
Calculate the first exponential moving average (EMA1) of the price data over a specific period 'n.'
Calculate the second exponential moving average (EMA2) of EMA1 using the same period 'n.'
Calculate the third exponential moving average (EMA3) of EMA2 using the same period 'n.'
The formula for the T3 moving average is as follows:
T3 = 3 * (EMA1) - 3 * (EMA2) + (EMA3)
By applying this triple smoothing process, the T3 moving average is intended to offer reduced noise and improved responsiveness to price trends. It achieves this by incorporating multiple time frames of the exponential moving averages, resulting in a more accurate representation of the underlying price action.
Thanks for checking this out and give a boost, if you enjoyed the content.
Best regards,
simwai
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Credits to @loxx
Fib TSIFib TSI = Fibonacci True Strength Index
The Fib TSI indicator uses Fibonacci numbers input for the True Strength Index moving averages. Then it is converted into a stochastic 0-100 scale.
The Fibonacci sequence is the series of numbers where each number is the sum of the two preceding numbers. 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610...
TSI uses moving averages of the underlying momentum of a financial instrument.
Stochastic is calculated by a formula of high and low over a length of time on a scale of 0-100.
How to use Fib TSI:
100 = overbought
0 = oversold
Rising = bullish
Falling = bearish
crossover 50 = bullish
crossunder 50 = bearish
The default input settings are:
2 = Stoch D smoothing
3 = TSI signal
TSI uses 2 moving averages compared with each other.
5 = TSI fastest
TSI uses 2 moving averages compared with each other.
Default value is 3/5.
color = white
8 = TSI fast
TSI uses 2 moving averages compared with each other.
Default value is 5/8.
color = blue
13 = TSI mid
TSI uses 2 moving averages compared with each other.
Default value is 8/13.
color = orange
21 = TSI slow
TSI uses 2 moving averages compared with each other.
Default value is 13/21.
color = purple
34 = TSI slowest
TSI uses 2 moving averages compared with each other.
Default value is 21/34.
color = yellow
55 = Stoch K length
All total / 5 = All TSI
color rising above 50 = bright green
color falling above 50 = mint green
color falling below 50 = bright red
color rising below 50 = pink
Up bullish reversal = green arrow up
bullish trend = green dots
Down bearish reversal = red arrow down
bearish trend = red dots
Horizontal lines:
100
75
50
25
0
2 different visual options example snapshot:
Munich GuppyWELCOME to the Munich Guppy!
This is a simple moving average indicator that will help you determine the trend of your chart using historical moving averages.
The indicator consists of 3 EMA's and one ALMA moving average. Using these 4 moving averages I have programmed the relationship between the moving averages to color the background of your chart.
If your background is red, this means that the alma moving average has fallen below the EMA's (EMA1 and EMA 2) as well as (EMA 1 and EMA 2) are postured in a down trending/up trending fashion
For example, the 21EMA is greater than the 55EMA, this signals that the chart has been outperforming its intermediate averages. Now if the ALMA is below both the 21ema and 55ema, in this instance, your chart background will become green.
The ALMA has color options '+CoC' and '-Coc', this simply means if the candle closes below the alma, it will turn red, if closure above it will turn green.
EMA 3 which is default set to 200, has no affect on the color of the background.
Now I hope I have thoroughly explained the simplicity of this indicator, if you have any questions leave them below or private message me for any other requests,
Good Trading!
-CheatCode1
AMACD - All Moving Average Convergence DivergenceThis indicator displays the Moving Average Convergane and Divergence ( MACD ) of individually configured Fast, Slow and Signal Moving Averages. Buy and sell alerts can be set based on moving average crossovers, consecutive convergence/divergence of the moving averages, and directional changes in the histogram moving averages.
The Fast, Slow and Signal Moving Averages can be set to:
Exponential Moving Average ( EMA )
Volume-Weighted Moving Average ( VWMA )
Simple Moving Average ( SMA )
Weighted Moving Average ( WMA )
Hull Moving Average ( HMA )
Exponentially Weighted Moving Average (RMA) ( SMMA )
Symmetrically Weighted Moving Average ( SWMA )
Arnaud Legoux Moving Average ( ALMA )
Double EMA ( DEMA )
Double SMA (DSMA)
Double WMA (DWMA)
Double RMA ( DRMA )
Triple EMA ( TEMA )
Triple SMA (TSMA)
Triple WMA (TWMA)
Triple RMA (TRMA)
Linear regression curve Moving Average ( LSMA )
Variable Index Dynamic Average ( VIDYA )
Fractal Adaptive Moving Average ( FRAMA )
If you have a strategy that can buy based on External Indicators use 'Backtest Signal' which returns a 1 for a Buy and a 2 for a sell.
'Backtest Signal' is plotted to display.none, so change the Style Settings for the chart if you need to see it for testing.
Price Distance to its MA by DGTPrices high above the moving average (MA) or low below it are likely to be remedied in the future by a reverse price movement as stated in an Article by Denis Alajbeg, Zoran Bubas and Dina Vasic published in International Journal of Economics, Commerce and Management
Here comes a study to indicate the idea of this article, Price Distance to its Moving Averages (P/MA Ratio)
The analysis expressed in the paper indicates that there is a connection between the distance of the prices to moving averages and subsequent returns : portfolios of stocks with lower prices to moving averages generally outperformed portfolios of stocks with higher prices to moving averages. This “overextended” effect is more pronounced when using shorter moving averages of 20 and 50 days, and is especially strong in short-term holding periods like one and two weeks. The highest annual returns are recorded when buying in the range of 0-5% below shorter moving averages of 20/50 days, and 0-10% below longer moving averages of 100/200 days. However, buying very far below almost all moving averages on almost all holding periods produces the lowest returns.
The concept of this study recognizes three different modes of action.
In a clearly established upward trend traders should be buying when prices are near or below the MA line and selling when prices move too far above the MA.
Conversely, in downward trend stocks should be shorted when reaching or going above the moving average and covered when they drop too far below the MA line.
In a sideways movement traders are advised to buy if the price is too low below the moving average and sell when it goes too far above it
Short-term traders can expect to outperform in a one or two week time window if buying stocks with lower prices compared to their 20 and 50 SMA/EMA, one to two-week holding periods is quite high, ranging from 72,09% to 90,61% for the SMA(20, 50) and 85,03% to 87,5% for the EMA(20, 50). The best results for the SMA 20 and 50, on average, are concentrated in the region of 0-5% below the MA for the majority of holding periods. Buying very far below almost all MA in almost all holding periods turns out to be the worst possible option
Candle patterns, momentum could be used in conjunction with this indicator for better results. Try Colored DMI and Ichimoku colored SuperTrend by DGT
Shapeshifting Moving Average - Switching From Low-Lag To SmoothThe term "shapeshifting" is more appropriate when used with something with a shape that isn't supposed to change, this is not the case of a moving average whose shape can be altered by the length setting or even by an external factor in the case of adaptive moving averages, but i'll stick with it since it describe the purpose of the proposed moving average pretty well.
In the case of moving averages based on convolution, their properties are fully described by the moving average kernel ( set of weights ), smooth moving averages tend to have a symmetrical bell shaped kernel, while low lag moving averages have negative weights. One of the few moving averages that would let the user alter the shape of its kernel is the Arnaud Legoux moving average, which convolve the input signal with a parametric gaussian function in which the center and width can be changed by the user, however this moving average is not a low-lagging one, as the weights don't include negative values.
Other moving averages where the user can change the kernel from user settings where already presented, i posted a lot of them, but they only focused on letting the user decrease or increase the lag of the moving average, and didn't included specific parameters controlling its smoothness. This is why the shapeshifting moving average is proposed, this parametric moving average will let the user switch from a smooth moving average to a low-lagging one while controlling the amount of lag of the moving average.
Settings/Kernel Interaction
Note that it could be possible to design a specific kernel function in order to provide a more efficient approach to today goal, but the original indicator was a simple low-lag moving average based on a modification of the second derivative of the arc tangent function and because i judged the indicator a bit boring i decided to include this parametric particularity.
As said the moving average "kernel", who refer to the set of weights used by the moving average, is based on a modification of the second derivative of the arc tangent function, the arc tangent function has a "S" shaped curve, "S" shaped functions are called sigmoid functions, the first derivative of a sigmoid function is bell shaped, which is extremely nice in order to design smooth moving averages, the second derivative of a sigmoid function produce a "sinusoid" like shape ( i don't have english words to describe such shape, let me know if you have an idea ) and is great to design bandpass filters.
We modify this 2nd derivative in order to have a decreasing function with negative values near the end, and we end up with:
The function is parametric, and the user can change it ( thus changing the properties of the moving average ) by using the settings, for example an higher power value would reduce the lag of the moving average while increasing overshoots. When power < 3 the moving average can act as a slow moving average in a moving average crossover system, as weights would not include negative values.
Here power = 0 and length = 50. The shapeshifting moving average can approximate a simple moving average with very low power values, as this would make the kernel approximate a rectangular function, however this is only a curiosity and not something you should do.
As A Smooth Moving Average
“So smooth, and so tranquil. It doesn't get any quieter than this”
A smooth moving average kernel should be : symmetrical, not to width and not to sharp, bell shaped curve are often appropriates, the proposed moving average kernel can be symmetrical and can return extremely smooth results. I will use the Blackman filter as comparison.
The smooth version of the moving average can be used when the "smooth" setting is selected. Here power can only be an even number, if power is odd, power will be equal to the nearest lowest even number. When power = 0, the kernel is simply a parabola:
More smoothness can be achieved by using power = 2
In red the shapeshifting moving average, in green a Blackman filter of both length = 100. Higher values of power will create lower negative values near the border of the kernel shape, this often allow to retain information about the peaks and valleys in the input signal. Power = 6 approximate the Blackman filter pretty well.
Conclusion
A moving average using a modification of the 2nd derivative of the arc tangent function as kernel has been presented, the kernel is parametric and allow the user to switch from a low-lag moving average where the lag can be increased/decreased to a really smooth moving average.
As you can see once you get familiar with a function shape, you can know what would be the characteristics of a moving average using it as kernel, this is where you start getting intimate with moving averages.
On a side note, have you noticed that the views counter in posted ideas/indicators has been removed ? This is truly a marvelous idea don't you think ?
Thanks for reading !
Trend is your friendThis indicator evaluates the trend based on crosses of two McGinley moving averages. It paints candles accordingly (it does not repaint), so you can see what the indicator is saying more clearly and stay in your trade until you see a period of consolidation or a reversal. You can control how far away those moving averages need to be for you to consider it a trend. If this distance is not met candles color is not changed and it shows you that the market is in a period of consolidation. I also added visualization of RSI, so you can have an easier time finding appropriate profit targets. For stop loss I would recommend placing it a couple points above or below the previous high / low that is located above / below you final target for entry. You can also use a certain percentage that works for you. I tried adding a stop loss based on ATR, but I did not like the results. Using market structure is a better choice in my opinion.
Here is a basic trading strategy for the default settings:
Wait for the indicator to start printing a series of green or red candles. After that you can enter a long or a short around moving averages. Another valid place to entry is the specific RSI zone. If we are in an uptrend buying when RSI is oversold can be beneficial as you expect market to recover. I do not recommend changing RSI from 14. Vice versa for the downtrend. It gives you an edge as you know at what price RSI will be oversold and allows you to place trades in advance. Pretty neat! You need to realize that no indicator or strategy can give you an exact entry. There will always be some margin of error. What I wanted to say is that if there is a strong trend up and you buy around your key moving averages and when RSI is oversold you entered in good places and there is a pretty good chance you will make money.
Time frame settings:
If you want to use tighter stop losses I would recommend sticking to 15m. Do not go lower. It is not worth the stress. 1h and 4h seems to be very good as well, but expect your stop losses to be wider. What I personally tend to do is display 15m, 30m and 1h and compare it. Think of it as a short, mid and long term. That way you can see things little bit better.
Examples:
1H chart BTC
4h chart EUR / USD
1D chart NASDAQ
15m chart BTC (Daytrading)
That last chart shows that even if you were longing while the trend was about to change you still had a good chance to close it with a little profit and switch to short easily. The default settings is what has worked the best for me. Feel free to change them as you see fit and do not forget to let me know if you find something that works better :)
Notes:
Either disable wick display or change it to a neutral color like gray for both green and red candles. Unfortunately pine script does not allow wick painting, so if you have red / green wicks it will look terrible. If RSI visualization makes your candles look too small you can go to settings and disable the display of individual RSI levels. You will still be able to see the zones, but the scale won't be affected.
Percentage Price Oscillator (PPO)The Percentage Price Oscillator (PPO) is a momentum oscillator that measures the difference between two moving averages as a percentage of the larger moving average. As with its cousin, MACD, the Percentage Price Oscillator is shown with a signal line, a histogram and a centerline. Signals are generated with signal line crossovers, centerline crossovers, and divergences. First, PPO readings are not subject to the price level of the security. Second, PPO readings for different securities can be compared, even when there are large differences in the price.
Calculations
PPO: {(12-day EMA - 26-day EMA)/26-day EMA} x 100
Signal Line: 9-day EMA of PPO
PPO Histogram: PPO - Signal Line
While MACD measures the absolute difference between two moving averages, PPO makes this a relative value by dividing the difference by the slower moving average (26-day EMA). PPO is simply the MACD value divided by the longer moving average. The result is multiplied by 100 to move the decimal place two spots.
Interpretation
As with MACD, the PPO reflects the convergence and divergence of two moving averages. PPO is positive when the shorter moving average is above the longer moving average. The indicator moves further into positive territory as the shorter moving average distances itself from the longer moving average. This reflects strong upside momentum. The PPO is negative when the shorter moving average is below the longer moving average. Negative readings grow when the shorter moving average distances itself from the longer moving average (goes further negative). This reflects strong downside momentum. The histogram represents the difference between PPO and its 9-day EMA, the signal line. The histogram is positive when PPO is above its 9-day EMA and negative when PPO is below its 9-day EMA. The PPO-Histogram can be used to anticipate signal line crossovers in the PPO.
MACD, PPO and Price
MACD levels are affected by the price of a security. A high-priced security will have higher or lower MACD values than a low-priced security, even if volatility is basically equal. This is because MACD is based on the absolute difference in the two moving averages. Because MACD is based on absolute levels, large price changes can affect MACD levels over an extended period of time. If a stock advances from 20 to 100, its MACD levels will be considerably smaller around 20 than around 100. The PPO solves this problem by showing MACD values in percentage terms.
Conclusions
The Percentage Price Oscillator (PPO) generates the same signals as the MACD, but provides an added dimension as a percentage version of MACD. The PPO levels of the Dow Industrials (price > 20K) can be compared against the PPO levels of IBM (price < 200) because the PPO “levels” the playing field. In addition, PPO levels in one security can be compared over extended periods of time, even if the price has doubled or tripled. This is not the case for the MACD.
Limitations
Despite its advantages, the PPO is still not the best oscillator to identify overbought or oversold conditions because movements are unlimited (in theory). Levels for RSI and the Stochastic Oscillator are limited and this makes them better suited to identify overbought and oversold levels.
Source: Stockcharts
ATAI Volume analysis with price action V 1.00ATAI Volume Analysis with Price Action
1. Introduction
1.1 Overview
ATAI Volume Analysis with Price Action is a composite indicator designed for TradingView. It combines per‑side volume data —that is, how much buying and selling occurs during each bar—with standard price‑structure elements such as swings, trend lines and support/resistance. By blending these elements the script aims to help a trader understand which side is in control, whether a breakout is genuine, when markets are potentially exhausted and where liquidity providers might be active.
The indicator is built around TradingView’s up/down volume feed accessed via the TradingView/ta/10 library. The following excerpt from the script illustrates how this feed is configured:
import TradingView/ta/10 as tvta
// Determine lower timeframe string based on user choice and chart resolution
string lower_tf_breakout = use_custom_tf_input ? custom_tf_input :
timeframe.isseconds ? "1S" :
timeframe.isintraday ? "1" :
timeframe.isdaily ? "5" : "60"
// Request up/down volume (both positive)
= tvta.requestUpAndDownVolume(lower_tf_breakout)
Lower‑timeframe selection. If you do not specify a custom lower timeframe, the script chooses a default based on your chart resolution: 1 second for second charts, 1 minute for intraday charts, 5 minutes for daily charts and 60 minutes for anything longer. Smaller intervals provide a more precise view of buyer and seller flow but cover fewer bars. Larger intervals cover more history at the cost of granularity.
Tick vs. time bars. Many trading platforms offer a tick / intrabar calculation mode that updates an indicator on every trade rather than only on bar close. Turning on one‑tick calculation will give the most accurate split between buy and sell volume on the current bar, but it typically reduces the amount of historical data available. For the highest fidelity in live trading you can enable this mode; for studying longer histories you might prefer to disable it. When volume data is completely unavailable (some instruments and crypto pairs), all modules that rely on it will remain silent and only the price‑structure backbone will operate.
Figure caption, Each panel shows the indicator’s info table for a different volume sampling interval. In the left chart, the parentheses “(5)” beside the buy‑volume figure denote that the script is aggregating volume over five‑minute bars; the center chart uses “(1)” for one‑minute bars; and the right chart uses “(1T)” for a one‑tick interval. These notations tell you which lower timeframe is driving the volume calculations. Shorter intervals such as 1 minute or 1 tick provide finer detail on buyer and seller flow, but they cover fewer bars; longer intervals like five‑minute bars smooth the data and give more history.
Figure caption, The values in parentheses inside the info table come directly from the Breakout — Settings. The first row shows the custom lower-timeframe used for volume calculations (e.g., “(1)”, “(5)”, or “(1T)”)
2. Price‑Structure Backbone
Even without volume, the indicator draws structural features that underpin all other modules. These features are always on and serve as the reference levels for subsequent calculations.
2.1 What it draws
• Pivots: Swing highs and lows are detected using the pivot_left_input and pivot_right_input settings. A pivot high is identified when the high recorded pivot_right_input bars ago exceeds the highs of the preceding pivot_left_input bars and is also higher than (or equal to) the highs of the subsequent pivot_right_input bars; pivot lows follow the inverse logic. The indicator retains only a fixed number of such pivot points per side, as defined by point_count_input, discarding the oldest ones when the limit is exceeded.
• Trend lines: For each side, the indicator connects the earliest stored pivot and the most recent pivot (oldest high to newest high, and oldest low to newest low). When a new pivot is added or an old one drops out of the lookback window, the line’s endpoints—and therefore its slope—are recalculated accordingly.
• Horizontal support/resistance: The highest high and lowest low within the lookback window defined by length_input are plotted as horizontal dashed lines. These serve as short‑term support and resistance levels.
• Ranked labels: If showPivotLabels is enabled the indicator prints labels such as “HH1”, “HH2”, “LL1” and “LL2” near each pivot. The ranking is determined by comparing the price of each stored pivot: HH1 is the highest high, HH2 is the second highest, and so on; LL1 is the lowest low, LL2 is the second lowest. In the case of equal prices the newer pivot gets the better rank. Labels are offset from price using ½ × ATR × label_atr_multiplier, with the ATR length defined by label_atr_len_input. A dotted connector links each label to the candle’s wick.
2.2 Key settings
• length_input: Window length for finding the highest and lowest values and for determining trend line endpoints. A larger value considers more history and will generate longer trend lines and S/R levels.
• pivot_left_input, pivot_right_input: Strictness of swing confirmation. Higher values require more bars on either side to form a pivot; lower values create more pivots but may include minor swings.
• point_count_input: How many pivots are kept in memory on each side. When new pivots exceed this number the oldest ones are discarded.
• label_atr_len_input and label_atr_multiplier: Determine how far pivot labels are offset from the bar using ATR. Increasing the multiplier moves labels further away from price.
• Styling inputs for trend lines, horizontal lines and labels (color, width and line style).
Figure caption, The chart illustrates how the indicator’s price‑structure backbone operates. In this daily example, the script scans for bars where the high (or low) pivot_right_input bars back is higher (or lower) than the preceding pivot_left_input bars and higher or lower than the subsequent pivot_right_input bars; only those bars are marked as pivots.
These pivot points are stored and ranked: the highest high is labelled “HH1”, the second‑highest “HH2”, and so on, while lows are marked “LL1”, “LL2”, etc. Each label is offset from the price by half of an ATR‑based distance to keep the chart clear, and a dotted connector links the label to the actual candle.
The red diagonal line connects the earliest and latest stored high pivots, and the green line does the same for low pivots; when a new pivot is added or an old one drops out of the lookback window, the end‑points and slopes adjust accordingly. Dashed horizontal lines mark the highest high and lowest low within the current lookback window, providing visual support and resistance levels. Together, these elements form the structural backbone that other modules reference, even when volume data is unavailable.
3. Breakout Module
3.1 Concept
This module confirms that a price break beyond a recent high or low is supported by a genuine shift in buying or selling pressure. It requires price to clear the highest high (“HH1”) or lowest low (“LL1”) and, simultaneously, that the winning side shows a significant volume spike, dominance and ranking. Only when all volume and price conditions pass is a breakout labelled.
3.2 Inputs
• lookback_break_input : This controls the number of bars used to compute moving averages and percentiles for volume. A larger value smooths the averages and percentiles but makes the indicator respond more slowly.
• vol_mult_input : The “spike” multiplier; the current buy or sell volume must be at least this multiple of its moving average over the lookback window to qualify as a breakout.
• rank_threshold_input (0–100) : Defines a volume percentile cutoff: the current buyer/seller volume must be in the top (100−threshold)%(100−threshold)% of all volumes within the lookback window. For example, if set to 80, the current volume must be in the top 20 % of the lookback distribution.
• ratio_threshold_input (0–1) : Specifies the minimum share of total volume that the buyer (for a bullish breakout) or seller (for bearish) must hold on the current bar; the code also requires that the cumulative buyer volume over the lookback window exceeds the seller volume (and vice versa for bearish cases).
• use_custom_tf_input / custom_tf_input : When enabled, these inputs override the automatic choice of lower timeframe for up/down volume; otherwise the script selects a sensible default based on the chart’s timeframe.
• Label appearance settings : Separate options control the ATR-based offset length, offset multiplier, label size and colors for bullish and bearish breakout labels, as well as the connector style and width.
3.3 Detection logic
1. Data preparation : Retrieve per‑side volume from the lower timeframe and take absolute values. Build rolling arrays of the last lookback_break_input values to compute simple moving averages (SMAs), cumulative sums and percentile ranks for buy and sell volume.
2. Volume spike: A spike is flagged when the current buy (or, in the bearish case, sell) volume is at least vol_mult_input times its SMA over the lookback window.
3. Dominance test: The buyer’s (or seller’s) share of total volume on the current bar must meet or exceed ratio_threshold_input. In addition, the cumulative sum of buyer volume over the window must exceed the cumulative sum of seller volume for a bullish breakout (and vice versa for bearish). A separate requirement checks the sign of delta: for bullish breakouts delta_breakout must be non‑negative; for bearish breakouts it must be non‑positive.
4. Percentile rank: The current volume must fall within the top (100 – rank_threshold_input) percent of the lookback distribution—ensuring that the spike is unusually large relative to recent history.
5. Price test: For a bullish signal, the closing price must close above the highest pivot (HH1); for a bearish signal, the close must be below the lowest pivot (LL1).
6. Labeling: When all conditions above are satisfied, the indicator prints “Breakout ↑” above the bar (bullish) or “Breakout ↓” below the bar (bearish). Labels are offset using half of an ATR‑based distance and linked to the candle with a dotted connector.
Figure caption, (Breakout ↑ example) , On this daily chart, price pushes above the red trendline and the highest prior pivot (HH1). The indicator recognizes this as a valid breakout because the buyer‑side volume on the lower timeframe spikes above its recent moving average and buyers dominate the volume statistics over the lookback period; when combined with a close above HH1, this satisfies the breakout conditions. The “Breakout ↑” label appears above the candle, and the info table highlights that up‑volume is elevated relative to its 11‑bar average, buyer share exceeds the dominance threshold and money‑flow metrics support the move.
Figure caption, In this daily example, price breaks below the lowest pivot (LL1) and the lower green trendline. The indicator identifies this as a bearish breakout because sell‑side volume is sharply elevated—about twice its 11‑bar average—and sellers dominate both the bar and the lookback window. With the close falling below LL1, the script triggers a Breakout ↓ label and marks the corresponding row in the info table, which shows strong down volume, negative delta and a seller share comfortably above the dominance threshold.
4. Market Phase Module (Volume Only)
4.1 Concept
Not all markets trend; many cycle between periods of accumulation (buying pressure building up), distribution (selling pressure dominating) and neutral behavior. This module classifies the current bar into one of these phases without using ATR , relying solely on buyer and seller volume statistics. It looks at net flows, ratio changes and an OBV‑like cumulative line with dual‑reference (1‑ and 2‑bar) trends. The result is displayed both as on‑chart labels and in a dedicated row of the info table.
4.2 Inputs
• phase_period_len: Number of bars over which to compute sums and ratios for phase detection.
• phase_ratio_thresh : Minimum buyer share (for accumulation) or minimum seller share (for distribution, derived as 1 − phase_ratio_thresh) of the total volume.
• strict_mode: When enabled, both the 1‑bar and 2‑bar changes in each statistic must agree on the direction (strict confirmation); when disabled, only one of the two references needs to agree (looser confirmation).
• Color customisation for info table cells and label styling for accumulation and distribution phases, including ATR length, multiplier, label size, colors and connector styles.
• show_phase_module: Toggles the entire phase detection subsystem.
• show_phase_labels: Controls whether on‑chart labels are drawn when accumulation or distribution is detected.
4.3 Detection logic
The module computes three families of statistics over the volume window defined by phase_period_len:
1. Net sum (buyers minus sellers): net_sum_phase = Σ(buy) − Σ(sell). A positive value indicates a predominance of buyers. The code also computes the differences between the current value and the values 1 and 2 bars ago (d_net_1, d_net_2) to derive up/down trends.
2. Buyer ratio: The instantaneous ratio TF_buy_breakout / TF_tot_breakout and the window ratio Σ(buy) / Σ(total). The current ratio must exceed phase_ratio_thresh for accumulation or fall below 1 − phase_ratio_thresh for distribution. The first and second differences of the window ratio (d_ratio_1, d_ratio_2) determine trend direction.
3. OBV‑like cumulative net flow: An on‑balance volume analogue obv_net_phase increments by TF_buy_breakout − TF_sell_breakout each bar. Its differences over the last 1 and 2 bars (d_obv_1, d_obv_2) provide trend clues.
The algorithm then combines these signals:
• For strict mode , accumulation requires: (a) current ratio ≥ threshold, (b) cumulative ratio ≥ threshold, (c) both ratio differences ≥ 0, (d) net sum differences ≥ 0, and (e) OBV differences ≥ 0. Distribution is the mirror case.
• For loose mode , it relaxes the directional tests: either the 1‑ or the 2‑bar difference needs to agree in each category.
If all conditions for accumulation are satisfied, the phase is labelled “Accumulation” ; if all conditions for distribution are satisfied, it’s labelled “Distribution” ; otherwise the phase is “Neutral” .
4.4 Outputs
• Info table row : Row 8 displays “Market Phase (Vol)” on the left and the detected phase (Accumulation, Distribution or Neutral) on the right. The text colour of both cells matches a user‑selectable palette (typically green for accumulation, red for distribution and grey for neutral).
• On‑chart labels : When show_phase_labels is enabled and a phase persists for at least one bar, the module prints a label above the bar ( “Accum” ) or below the bar ( “Dist” ) with a dashed or dotted connector. The label is offset using ATR based on phase_label_atr_len_input and phase_label_multiplier and is styled according to user preferences.
Figure caption, The chart displays a red “Dist” label above a particular bar, indicating that the accumulation/distribution module identified a distribution phase at that point. The detection is based on seller dominance: during that bar, the net buyer-minus-seller flow and the OBV‑style cumulative flow were trending down, and the buyer ratio had dropped below the preset threshold. These conditions satisfy the distribution criteria in strict mode. The label is placed above the bar using an ATR‑based offset and a dashed connector. By the time of the current bar in the screenshot, the phase indicator shows “Neutral” in the info table—signaling that neither accumulation nor distribution conditions are currently met—yet the historical “Dist” label remains to mark where the prior distribution phase began.
Figure caption, In this example the market phase module has signaled an Accumulation phase. Three bars before the current candle, the algorithm detected a shift toward buyers: up‑volume exceeded its moving average, down‑volume was below average, and the buyer share of total volume climbed above the threshold while the on‑balance net flow and cumulative ratios were trending upwards. The blue “Accum” label anchored below that bar marks the start of the phase; it remains on the chart because successive bars continue to satisfy the accumulation conditions. The info table confirms this: the “Market Phase (Vol)” row still reads Accumulation, and the ratio and sum rows show buyers dominating both on the current bar and across the lookback window.
5. OB/OS Spike Module
5.1 What overbought/oversold means here
In many markets, a rapid extension up or down is often followed by a period of consolidation or reversal. The indicator interprets overbought (OB) conditions as abnormally strong selling risk at or after a price rally and oversold (OS) conditions as unusually strong buying risk after a decline. Importantly, these are not direct trade signals; rather they flag areas where caution or contrarian setups may be appropriate.
5.2 Inputs
• minHits_obos (1–7): Minimum number of oscillators that must agree on an overbought or oversold condition for a label to print.
• syncWin_obos: Length of a small sliding window over which oscillator votes are smoothed by taking the maximum count observed. This helps filter out choppy signals.
• Volume spike criteria: kVolRatio_obos (ratio of current volume to its SMA) and zVolThr_obos (Z‑score threshold) across volLen_obos. Either threshold can trigger a spike.
• Oscillator toggles and periods: Each of RSI, Stochastic (K and D), Williams %R, CCI, MFI, DeMarker and Stochastic RSI can be independently enabled; their periods are adjustable.
• Label appearance: ATR‑based offset, size, colors for OB and OS labels, plus connector style and width.
5.3 Detection logic
1. Directional volume spikes: Volume spikes are computed separately for buyer and seller volumes. A sell volume spike (sellVolSpike) flags a potential OverBought bar, while a buy volume spike (buyVolSpike) flags a potential OverSold bar. A spike occurs when the respective volume exceeds kVolRatio_obos times its simple moving average over the window or when its Z‑score exceeds zVolThr_obos.
2. Oscillator votes: For each enabled oscillator, calculate its overbought and oversold state using standard thresholds (e.g., RSI ≥ 70 for OB and ≤ 30 for OS; Stochastic %K/%D ≥ 80 for OB and ≤ 20 for OS; etc.). Count how many oscillators vote for OB and how many vote for OS.
3. Minimum hits: Apply the smoothing window syncWin_obos to the vote counts using a maximum‑of‑last‑N approach. A candidate bar is only considered if the smoothed OB hit count ≥ minHits_obos (for OverBought) or the smoothed OS hit count ≥ minHits_obos (for OverSold).
4. Tie‑breaking: If both OverBought and OverSold spike conditions are present on the same bar, compare the smoothed hit counts: the side with the higher count is selected; ties default to OverBought.
5. Label printing: When conditions are met, the bar is labelled as “OverBought X/7” above the candle or “OverSold X/7” below it. “X” is the number of oscillators confirming, and the bracket lists the abbreviations of contributing oscillators. Labels are offset from price using half of an ATR‑scaled distance and can optionally include a dotted or dashed connector line.
Figure caption, In this chart the overbought/oversold module has flagged an OverSold signal. A sell‑off from the prior highs brought price down to the lower trend‑line, where the bar marked “OverSold 3/7 DeM” appears. This label indicates that on that bar the module detected a buy‑side volume spike and that at least three of the seven enabled oscillators—in this case including the DeMarker—were in oversold territory. The label is printed below the candle with a dotted connector, signaling that the market may be temporarily exhausted on the downside. After this oversold print, price begins to rebound towards the upper red trend‑line and higher pivot levels.
Figure caption, This example shows the overbought/oversold module in action. In the left‑hand panel you can see the OB/OS settings where each oscillator (RSI, Stochastic, Williams %R, CCI, MFI, DeMarker and Stochastic RSI) can be enabled or disabled, and the ATR length and label offset multiplier adjusted. On the chart itself, price has pushed up to the descending red trendline and triggered an “OverBought 3/7” label. That means the sell‑side volume spiked relative to its average and three out of the seven enabled oscillators were in overbought territory. The label is offset above the candle by half of an ATR and connected with a dashed line, signaling that upside momentum may be overextended and a pause or pullback could follow.
6. Buyer/Seller Trap Module
6.1 Concept
A bull trap occurs when price appears to break above resistance, attracting buyers, but fails to sustain the move and quickly reverses, leaving a long upper wick and trapping late entrants. A bear trap is the opposite: price breaks below support, lures in sellers, then snaps back, leaving a long lower wick and trapping shorts. This module detects such traps by looking for price structure sweeps, order‑flow mismatches and dominance reversals. It uses a scoring system to differentiate risk from confirmed traps.
6.2 Inputs
• trap_lookback_len: Window length used to rank extremes and detect sweeps.
• trap_wick_threshold: Minimum proportion of a bar’s range that must be wick (upper for bull traps, lower for bear traps) to qualify as a sweep.
• trap_score_risk: Minimum aggregated score required to flag a trap risk. (The code defines a trap_score_confirm input, but confirmation is actually based on price reversal rather than a separate score threshold.)
• trap_confirm_bars: Maximum number of bars allowed for price to reverse and confirm the trap. If price does not reverse in this window, the risk label will expire or remain unconfirmed.
• Label settings: ATR length and multiplier for offsetting, size, colours for risk and confirmed labels, and connector style and width. Separate settings exist for bull and bear traps.
• Toggle inputs: show_trap_module and show_trap_labels enable the module and control whether labels are drawn on the chart.
6.3 Scoring logic
The module assigns points to several conditions and sums them to determine whether a trap risk is present. For bull traps, the score is built from the following (bear traps mirror the logic with highs and lows swapped):
1. Sweep (2 points): Price trades above the high pivot (HH1) but fails to close above it and leaves a long upper wick at least trap_wick_threshold × range. For bear traps, price dips below the low pivot (LL1), fails to close below and leaves a long lower wick.
2. Close break (1 point): Price closes beyond HH1 or LL1 without leaving a long wick.
3. Candle/delta mismatch (2 points): The candle closes bullish yet the order flow delta is negative or the seller ratio exceeds 50%, indicating hidden supply. Conversely, a bearish close with positive delta or buyer dominance suggests hidden demand.
4. Dominance inversion (2 points): The current bar’s buyer volume has the highest rank in the lookback window while cumulative sums favor sellers, or vice versa.
5. Low‑volume break (1 point): Price crosses the pivot but total volume is below its moving average.
The total score for each side is compared to trap_score_risk. If the score is high enough, a “Bull Trap Risk” or “Bear Trap Risk” label is drawn, offset from the candle by half of an ATR‑scaled distance using a dashed outline. If, within trap_confirm_bars, price reverses beyond the opposite level—drops back below the high pivot for bull traps or rises above the low pivot for bear traps—the label is upgraded to a solid “Bull Trap” or “Bear Trap” . In this version of the code, there is no separate score threshold for confirmation: the variable trap_score_confirm is unused; confirmation depends solely on a successful price reversal within the specified number of bars.
Figure caption, In this example the trap module has flagged a Bear Trap Risk. Price initially breaks below the most recent low pivot (LL1), but the bar closes back above that level and leaves a long lower wick, suggesting a failed push lower. Combined with a mismatch between the candle direction and the order flow (buyers regain control) and a reversal in volume dominance, the aggregate score exceeds the risk threshold, so a dashed “Bear Trap Risk” label prints beneath the bar. The green and red trend lines mark the current low and high pivot trajectories, while the horizontal dashed lines show the highest and lowest values in the lookback window. If, within the next few bars, price closes decisively above the support, the risk label would upgrade to a solid “Bear Trap” label.
Figure caption, In this example the trap module has identified both ends of a price range. Near the highs, price briefly pushes above the descending red trendline and the recent pivot high, but fails to close there and leaves a noticeable upper wick. That combination of a sweep above resistance and order‑flow mismatch generates a Bull Trap Risk label with a dashed outline, warning that the upside break may not hold. At the opposite extreme, price later dips below the green trendline and the labelled low pivot, then quickly snaps back and closes higher. The long lower wick and subsequent price reversal upgrade the previous bear‑trap risk into a confirmed Bear Trap (solid label), indicating that sellers were caught on a false breakdown. Horizontal dashed lines mark the highest high and lowest low of the lookback window, while the red and green diagonals connect the earliest and latest pivot highs and lows to visualize the range.
7. Sharp Move Module
7.1 Concept
Markets sometimes display absorption or climax behavior—periods when one side steadily gains the upper hand before price breaks out with a sharp move. This module evaluates several order‑flow and volume conditions to anticipate such moves. Users can choose how many conditions must be met to flag a risk and how many (plus a price break) are required for confirmation.
7.2 Inputs
• sharp Lookback: Number of bars in the window used to compute moving averages, sums, percentile ranks and reference levels.
• sharpPercentile: Minimum percentile rank for the current side’s volume; the current buy (or sell) volume must be greater than or equal to this percentile of historical volumes over the lookback window.
• sharpVolMult: Multiplier used in the volume climax check. The current side’s volume must exceed this multiple of its average to count as a climax.
• sharpRatioThr: Minimum dominance ratio (current side’s volume relative to the opposite side) used in both the instant and cumulative dominance checks.
• sharpChurnThr: Maximum ratio of a bar’s range to its ATR for absorption/churn detection; lower values indicate more absorption (large volume in a small range).
• sharpScoreRisk: Minimum number of conditions that must be true to print a risk label.
• sharpScoreConfirm: Minimum number of conditions plus a price break required for confirmation.
• sharpCvdThr: Threshold for cumulative delta divergence versus price change (positive for bullish accumulation, negative for bearish distribution).
• Label settings: ATR length (sharpATRlen) and multiplier (sharpLabelMult) for positioning labels, label size, colors and connector styles for bullish and bearish sharp moves.
• Toggles: enableSharp activates the module; show_sharp_labels controls whether labels are drawn.
7.3 Conditions (six per side)
For each side, the indicator computes six boolean conditions and sums them to form a score:
1. Dominance (instant and cumulative):
– Instant dominance: current buy volume ≥ sharpRatioThr × current sell volume.
– Cumulative dominance: sum of buy volumes over the window ≥ sharpRatioThr × sum of sell volumes (and vice versa for bearish checks).
2. Accumulation/Distribution divergence: Over the lookback window, cumulative delta rises by at least sharpCvdThr while price fails to rise (bullish), or cumulative delta falls by at least sharpCvdThr while price fails to fall (bearish).
3. Volume climax: The current side’s volume is ≥ sharpVolMult × its average and the product of volume and bar range is the highest in the lookback window.
4. Absorption/Churn: The current side’s volume divided by the bar’s range equals the highest value in the window and the bar’s range divided by ATR ≤ sharpChurnThr (indicating large volume within a small range).
5. Percentile rank: The current side’s volume percentile rank is ≥ sharp Percentile.
6. Mirror logic for sellers: The above checks are repeated with buyer and seller roles swapped and the price break levels reversed.
Each condition that passes contributes one point to the corresponding side’s score (0 or 1). Risk and confirmation thresholds are then applied to these scores.
7.4 Scoring and labels
• Risk: If scoreBull ≥ sharpScoreRisk, a “Sharp ↑ Risk” label is drawn above the bar. If scoreBear ≥ sharpScoreRisk, a “Sharp ↓ Risk” label is drawn below the bar.
• Confirmation: A risk label is upgraded to “Sharp ↑” when scoreBull ≥ sharpScoreConfirm and the bar closes above the highest recent pivot (HH1); for bearish cases, confirmation requires scoreBear ≥ sharpScoreConfirm and a close below the lowest pivot (LL1).
• Label positioning: Labels are offset from the candle by ATR × sharpLabelMult (full ATR times multiplier), not half, and may include a dashed or dotted connector line if enabled.
Figure caption, In this chart both bullish and bearish sharp‑move setups have been flagged. Earlier in the range, a “Sharp ↓ Risk” label appears beneath a candle: the sell‑side score met the risk threshold, signaling that the combination of strong sell volume, dominance and absorption within a narrow range suggested a potential sharp decline. The price did not close below the lower pivot, so this label remains a “risk” and no confirmation occurred. Later, as the market recovered and volume shifted back to the buy side, a “Sharp ↑ Risk” label prints above a candle near the top of the channel. Here, buy‑side dominance, cumulative delta divergence and a volume climax aligned, but price has not yet closed above the upper pivot (HH1), so the alert is still a risk rather than a confirmed sharp‑up move.
Figure caption, In this chart a Sharp ↑ label is displayed above a candle, indicating that the sharp move module has confirmed a bullish breakout. Prior bars satisfied the risk threshold — showing buy‑side dominance, positive cumulative delta divergence, a volume climax and strong absorption in a narrow range — and this candle closes above the highest recent pivot, upgrading the earlier “Sharp ↑ Risk” alert to a full Sharp ↑ signal. The green label is offset from the candle with a dashed connector, while the red and green trend lines trace the high and low pivot trajectories and the dashed horizontals mark the highest and lowest values of the lookback window.
8. Market‑Maker / Spread‑Capture Module
8.1 Concept
Liquidity providers often “capture the spread” by buying and selling in almost equal amounts within a very narrow price range. These bars can signal temporary congestion before a move or reflect algorithmic activity. This module flags bars where both buyer and seller volumes are high, the price range is only a few ticks and the buy/sell split remains close to 50%. It helps traders spot potential liquidity pockets.
8.2 Inputs
• scalpLookback: Window length used to compute volume averages.
• scalpVolMult: Multiplier applied to each side’s average volume; both buy and sell volumes must exceed this multiple.
• scalpTickCount: Maximum allowed number of ticks in a bar’s range (calculated as (high − low) / minTick). A value of 1 or 2 captures ultra‑small bars; increasing it relaxes the range requirement.
• scalpDeltaRatio: Maximum deviation from a perfect 50/50 split. For example, 0.05 means the buyer share must be between 45% and 55%.
• Label settings: ATR length, multiplier, size, colors, connector style and width.
• Toggles : show_scalp_module and show_scalp_labels to enable the module and its labels.
8.3 Signal
When, on the current bar, both TF_buy_breakout and TF_sell_breakout exceed scalpVolMult times their respective averages and (high − low)/minTick ≤ scalpTickCount and the buyer share is within scalpDeltaRatio of 50%, the module prints a “Spread ↔” label above the bar. The label uses the same ATR offset logic as other modules and draws a connector if enabled.
Figure caption, In this chart the spread‑capture module has identified a potential liquidity pocket. Buyer and seller volumes both spiked above their recent averages, yet the candle’s range measured only a couple of ticks and the buy/sell split stayed close to 50 %. This combination met the module’s criteria, so it printed a grey “Spread ↔” label above the bar. The red and green trend lines link the earliest and latest high and low pivots, and the dashed horizontals mark the highest high and lowest low within the current lookback window.
9. Money Flow Module
9.1 Concept
To translate volume into a monetary measure, this module multiplies each side’s volume by the closing price. It tracks buying and selling system money default currency on a per-bar basis and sums them over a chosen period. The difference between buy and sell currencies (Δ$) shows net inflow or outflow.
9.2 Inputs
• mf_period_len_mf: Number of bars used for summing buy and sell dollars.
• Label appearance settings: ATR length, multiplier, size, colors for up/down labels, and connector style and width.
• Toggles: Use enableMoneyFlowLabel_mf and showMFLabels to control whether the module and its labels are displayed.
9.3 Calculations
• Per-bar money: Buy $ = TF_buy_breakout × close; Sell $ = TF_sell_breakout × close. Their difference is Δ$ = Buy $ − Sell $.
• Summations: Over mf_period_len_mf bars, compute Σ Buy $, Σ Sell $ and ΣΔ$ using math.sum().
• Info table entries: Rows 9–13 display these values as texts like “↑ USD 1234 (1M)” or “ΣΔ USD −5678 (14)”, with colors reflecting whether buyers or sellers dominate.
• Money flow status: If Δ$ is positive the bar is marked “Money flow in” ; if negative, “Money flow out” ; if zero, “Neutral”. The cumulative status is similarly derived from ΣΔ.Labels print at the bar that changes the sign of ΣΔ, offset using ATR × label multiplier and styled per user preferences.
Figure caption, The chart illustrates a steady rise toward the highest recent pivot (HH1) with price riding between a rising green trend‑line and a red trend‑line drawn through earlier pivot highs. A green Money flow in label appears above the bar near the top of the channel, signaling that net dollar flow turned positive on this bar: buy‑side dollar volume exceeded sell‑side dollar volume, pushing the cumulative sum ΣΔ$ above zero. In the info table, the “Money flow (bar)” and “Money flow Σ” rows both read In, confirming that the indicator’s money‑flow module has detected an inflow at both bar and aggregate levels, while other modules (pivots, trend lines and support/resistance) remain active to provide structural context.
In this example the Money Flow module signals a net outflow. Price has been trending downward: successive high pivots form a falling red trend‑line and the low pivots form a descending green support line. When the latest bar broke below the previous low pivot (LL1), both the bar‑level and cumulative net dollar flow turned negative—selling volume at the close exceeded buying volume and pushed the cumulative Δ$ below zero. The module reacts by printing a red “Money flow out” label beneath the candle; the info table confirms that the “Money flow (bar)” and “Money flow Σ” rows both show Out, indicating sustained dominance of sellers in this period.
10. Info Table
10.1 Purpose
When enabled, the Info Table appears in the lower right of your chart. It summarises key values computed by the indicator—such as buy and sell volume, delta, total volume, breakout status, market phase, and money flow—so you can see at a glance which side is dominant and which signals are active.
10.2 Symbols
• ↑ / ↓ — Up (↑) denotes buy volume or money; down (↓) denotes sell volume or money.
• MA — Moving average. In the table it shows the average value of a series over the lookback period.
• Σ (Sigma) — Cumulative sum over the chosen lookback period.
• Δ (Delta) — Difference between buy and sell values.
• B / S — Buyer and seller share of total volume, expressed as percentages.
• Ref. Price — Reference price for breakout calculations, based on the latest pivot.
• Status — Indicates whether a breakout condition is currently active (True) or has failed.
10.3 Row definitions
1. Up volume / MA up volume – Displays current buy volume on the lower timeframe and its moving average over the lookback period.
2. Down volume / MA down volume – Shows current sell volume and its moving average; sell values are formatted in red for clarity.
3. Δ / ΣΔ – Lists the difference between buy and sell volume for the current bar and the cumulative delta volume over the lookback period.
4. Σ / MA Σ (Vol/MA) – Total volume (buy + sell) for the bar, with the ratio of this volume to its moving average; the right cell shows the average total volume.
5. B/S ratio – Buy and sell share of the total volume: current bar percentages and the average percentages across the lookback period.
6. Buyer Rank / Seller Rank – Ranks the bar’s buy and sell volumes among the last (n) bars; lower rank numbers indicate higher relative volume.
7. Σ Buy / Σ Sell – Sum of buy and sell volumes over the lookback window, indicating which side has traded more.
8. Breakout UP / DOWN – Shows the breakout thresholds (Ref. Price) and whether the breakout condition is active (True) or has failed.
9. Market Phase (Vol) – Reports the current volume‑only phase: Accumulation, Distribution or Neutral.
10. Money Flow – The final rows display dollar amounts and status:
– ↑ USD / Σ↑ USD – Buy dollars for the current bar and the cumulative sum over the money‑flow period.
– ↓ USD / Σ↓ USD – Sell dollars and their cumulative sum.
– Δ USD / ΣΔ USD – Net dollar difference (buy minus sell) for the bar and cumulatively.
– Money flow (bar) – Indicates whether the bar’s net dollar flow is positive (In), negative (Out) or neutral.
– Money flow Σ – Shows whether the cumulative net dollar flow across the chosen period is positive, negative or neutral.
The chart above shows a sequence of different signals from the indicator. A Bull Trap Risk appears after price briefly pushes above resistance but fails to hold, then a green Accum label identifies an accumulation phase. An upward breakout follows, confirmed by a Money flow in print. Later, a Sharp ↓ Risk warns of a possible sharp downturn; after price dips below support but quickly recovers, a Bear Trap label marks a false breakdown. The highlighted info table in the center summarizes key metrics at that moment, including current and average buy/sell volumes, net delta, total volume versus its moving average, breakout status (up and down), market phase (volume), and bar‑level and cumulative money flow (In/Out).
11. Conclusion & Final Remarks
This indicator was developed as a holistic study of market structure and order flow. It brings together several well‑known concepts from technical analysis—breakouts, accumulation and distribution phases, overbought and oversold extremes, bull and bear traps, sharp directional moves, market‑maker spread bars and money flow—into a single Pine Script tool. Each module is based on widely recognized trading ideas and was implemented after consulting reference materials and example strategies, so you can see in real time how these concepts interact on your chart.
A distinctive feature of this indicator is its reliance on per‑side volume: instead of tallying only total volume, it separately measures buy and sell transactions on a lower time frame. This approach gives a clearer view of who is in control—buyers or sellers—and helps filter breakouts, detect phases of accumulation or distribution, recognize potential traps, anticipate sharp moves and gauge whether liquidity providers are active. The money‑flow module extends this analysis by converting volume into currency values and tracking net inflow or outflow across a chosen window.
Although comprehensive, this indicator is intended solely as a guide. It highlights conditions and statistics that many traders find useful, but it does not generate trading signals or guarantee results. Ultimately, you remain responsible for your positions. Use the information presented here to inform your analysis, combine it with other tools and risk‑management techniques, and always make your own decisions when trading.
Script_Algo - High Low Range MA Crossover Strategy🎯 Core Concept
This strategy uses modified moving averages crossover, built on maximum and minimum prices, to determine entry and exit points in the market. A key advantage of this strategy is that it avoids most false signals in trendless conditions, which is characteristic of traditional moving average crossover strategies. This makes it possible to improve the risk/reward ratio and, consequently, the strategy's profitability.
📊 How the Strategy Works
Main Mechanism
The strategy builds 4 moving averages:
Two senior MAs (on high and low) with a longer period
Two junior MAs (on high and low) with a shorter period
Buy signal 🟢: when the junior MA of lows crosses above the senior MA of highs
Sell signal 🔴: when the junior MA of highs crosses below the senior MA of lows
As seen on the chart, it was potentially possible to make 9X on the WIFUSDT cryptocurrency pair in just a year and a half. However, be careful—such results may not necessarily be repeated in the future.
Special Feature
Position closing priority ❗: if an opposite signal arrives while a position is open, the strategy first closes the current position and only then opens a new one
⚙️ Indicator Settings
Available Moving Average Types
EMA - Exponential MA
SMA - Simple MA
SSMA - Smoothed MA
WMA - Weighted MA
VWMA - Volume Weighted MA
RMA - Adaptive MA
DEMA - Double EMA
TEMA - Triple EMA
Adjustable Parameters
Senior MA Length - period for long-term moving averages
Junior MA Length - period for short-term moving averages
✅ Advantages of the Strategy
🛡️ False Signal Protection - using two pairs of modified MAs reduces the number of false entries
🔄 Configuration Flexibility - ability to choose MA type and calculation periods
⚡ Automatic Switching - the strategy automatically closes the current position when receiving an opposite signal
📈 Visual Clarity - all MAs are displayed on the chart in different colors
⚠️ Disadvantages and Risks
📉 Signal Lag - like all MA-based strategies, it may provide delayed signals during sharp movements
🔁 Frequent Switching - in sideways markets, it may lead to multiple consecutive position openings/closings
📊 Requires Optimization - optimal parameters need to be selected for different instruments and timeframes
💡 Usage Recommendations
Backtest - test the strategy's performance on historical data
Optimize Parameters - select MA periods suitable for the specific trading instrument
Use Filters - add additional filters to confirm signals
Manage Risks - always use stop-loss and take-profit orders.
You can safely connect to the exchange via webhook and enjoy trading.
Good luck and profits to everyone!!
Volume MAs Oscillator | Lyro RSVolume MAs Oscillator | Lyro RS
Overview
The Volume MAs Oscillator is a powerful volume‑adjusted momentum tool that combines custom‑weighted moving averages on volume‑weighted price with smoothed deviation bands. It offers dynamic insights into trend direction, overbought/oversold conditions, and relative valuation — all within a single indicator
Key Features
Volume‑Adjusted Moving Averages: Moving averages can be volume‑weighted using the following formula: a moving average of (Price × Volume) divided by a moving average of Volume. This formula is applied across more than 14 different moving averages; however, it is not used with the VWMA, as VWMA is inherently a volume-weighted moving average.
Percentage Oscillator: Displays the normalized difference: (source – MA) / MA * 100, centered around zero for easy interpretation of strength and direction.
Deviation Bands: Builds upper and lower bands from standard deviation of the oscillator over a selected lookback, with distinct positive/negative multipliers and optional smoothing to reduce noise.
Inputs: Band Length, Band Smoothing, Positive Band Multiplier, Negative Band Multiplier.
Multi‑Mode Signal System:
1. Trend Mode – Colors oscillator according to breaks above (bullish) or below (bearish) respective bands.
2. Reversion Mode – Inverses color logic: signals overextensions beyond bands as reversion opportunities, greys inside the bands.
3. Valuation Mode – Applies a gradient color scale (UpC ⇄ DnC) to reflect relative valuation strength.
Customizable Visuals: Select from 5 pre‑set palettes—Classic, Mystic, Major Themes, Accented, Royal—or define your own custom bullish/bearish colors.
Chart enhancements include color‑coded oscillator line, deviation bands, glow‑effect midline at zero, background shading and candlestick/bar coloring aligned to signal mode.
Built‑In Signals: Automatically plots ▲ oversold and ▼ overbought markers upon crosses of lower/upper bands (in trend or reversion modes), enhancing signal clarity.
How It Works
MA Calculation – Applies the selected MA type to price × volume (normalized by MA of volume) or direct VWMA.
Oscillator Output – Calculates the % difference of source vs. derived MA.
Band Construction – Computes rolling standard deviation; applies user‑defined multipliers; smooths bands with exponential blending.
Mode-Dependent Coloring & Signals –
• Trend: Highlights strength trends via band cross coloring.
• Reversion: Flags extremes beyond bands as potential pullbacks.
• Valuation: Uses gradient to reflect oscillator’s position relative to recent range.
Signal Markers – Deploys arrows and color rules to flag overbought (▼) or oversold (▲) conditions when bands are breached.
Practical Use
Trend Confirmation – In Trend Mode, use upward price_diff cross above upper band as bullish; downward cross below lower band as bearish.
Mean Reversion – In Reversion Mode, fading extremes beyond bands may precede a retracement.
Relative Valuation – Valuation Mode shines when assessing how extended price_diff is, with gradient colors indicating valuation zones.
Bars/candles color‑coded to oscillator state boosts clarity of market tone and allows for rapid visual scanning.
Customization
Adjust MA type/length to tune responsiveness vs. smoothing.
Configure band settings for volatility sensitivity.
Toggle between signal modes for trend-following or reversion strategies.
Stylish visuals: pick or customize color schemes to match your chart setup.
⚠️Disclaimer
This indicator is a tool for technical analysis and does not provide guaranteed results. It should be used in conjunction with other analysis methods and proper risk management practices. The creators of this indicator are not responsible for any financial decisions made based on its signals.
Heikinisi Candle (With MA + Smoothing + Buy/Sell with Cooldown)This custom Heikinisi Candle (With MA + Smoothing + Buy/Sell with Cooldown) indicator combines the advantages of Heikin-Ashi candles with the flexibility of multiple moving averages and smoothing options. The built-in buy/sell signals with cooldown functionality help traders avoid overtrading while capturing trend reversals and momentum shifts. Whether you're a day trader, swing trader, or long-term investor, this indicator offers powerful tools for analyzing price action and making informed trading decisions.
Note: Disable the regular candle to get better visualization.
Key Features:
Custom Heikin-Ashi Candles:
The core feature of this script is the Heikin-Ashi candles, which are known for smoothing price action and helping traders identify market trends more clearly.
Unlike traditional Heikin-Ashi, this version adjusts the Heikin-Ashi close based on specific price action patterns, including rejection signals and engulfing patterns.
The custom Heikin-Ashi open also incorporates momentum, adjusting dynamically based on recent price changes.
Price Action Measurements:
The indicator measures key price action components, including:
Body: The absolute difference between the open and close.
Candle Range: The total range from high to low.
Upper Wick: The distance from the highest price to the maximum of open or close.
Lower Wick: The distance from the lowest price to the minimum of open or close.
These measurements help detect bullish and bearish conditions, as well as price rejection signals.
Buy/Sell Signal Logic:
Buy Signal: Triggered when the Heikin-Ashi close is above the chosen moving average (MA1), with a cooldown period to avoid too frequent signals.
Sell Signal: Triggered when the Heikin-Ashi close falls below the MA1 after a buy signal has already been issued.
The cooldown period ensures that buy and sell signals are spaced apart by a specific number of bars, preventing excessive signal generation during periods of price consolidation.
Multiple Moving Averages (MA):
This script supports up to three customizable moving averages (MA1, MA2, MA3), each of which can be set to different types and lengths, including:
Simple Moving Average (SMA)
Exponential Moving Average (EMA)
Weighted Moving Average (WMA)
Volume Weighted Moving Average (VWMA)
Volume Weighted Moving Price (VWMP)
Least Squares Moving Average (LSMA)
Hull Moving Average (HMA)
Double Exponential Moving Average (DEMA)
Triple Exponential Moving Average (TEMA)
Users can adjust the length and type of each MA for tailored analysis.
Smoothing Options for MAs:
Users can smooth the output of MAs using various types of smoothing algorithms (SMA, EMA, LSMA, WMA, Gaussian) and a customizable length. This helps to reduce noise in the moving average lines and provides clearer signals.
Gaussian Filter (Advanced Smoothing):
A Gaussian Filter is available as a smoothing option for MAs. This filter reduces noise and makes the moving averages smoother, which can be particularly helpful in volatile or choppy markets.
Alerts and Visualization:
The script allows users to plot buy and sell signals on the chart with distinctive markers. A Buy Signal is shown below the bar with a lime green marker and text "Buy," while a Sell Signal is shown above the bar with a red marker and text "Sell."
Traders can also set up alerts based on the buy/sell signals to get notified in real time.
Indicator Configuration:
Heikin-Ashi Candle Configuration:
Automatically adjusts Heikin-Ashi candles based on rejection signals, engulfing patterns, and momentum. It uses custom formulas for the Heikin-Ashi open and close, making it more sensitive to price action than standard Heikin-Ashi candles.
Moving Averages (MA) Configuration:
You can select from multiple moving average types and lengths (MA1, MA2, MA3) for trend-following analysis.
Choose between SMA, EMA, WMA, VWMA, VWMP, LSMA, HMA, DEMA, and TEMA.
Smoothing Options:
Enable or disable smoothing for the moving averages.
Select from different smoothing types, including SMA, EMA, RMA, WMA, LSMA, and Gaussian.
Cooldown Period:
Control the number of bars that must pass before a new buy/sell signal is triggered. This cooldown period helps prevent excessive trading signals in quick succession.
How to Use:
Analyze Price Action with Heikin-Ashi Candles:
The custom Heikin-Ashi candles are ideal for spotting market trends, reversals, and price rejection. Use the candle patterns to gauge the market sentiment.
Use MAs for Trend Confirmation:
The moving averages (MA1, MA2, MA3) can help identify the prevailing trend. A price above a rising MA indicates an uptrend, while a price below a falling MA suggests a downtrend.
Trigger Buy and Sell Signals:
When the Heikin-Ashi close crosses above MA1, a buy signal is triggered.
When the Heikin-Ashi close crosses below MA1 after a buy signal, a sell signal is triggered.
The cooldown period ensures that signals are spaced out, preventing overtrading.
Use Smoothing for Clearer Signals:
If you are trading in a volatile market, you can use the smoothing options to make the MAs smoother and reduce noise.
Kaito Box with RSI Div(Dynamic Adjustment + MA + Long)The script implements a dynamic trading strategy that combines box range detection, RSI divergence signals, and moving average trend analysis. It is designed for use on OKX Signal Bots and includes features for dynamic position scaling and partial position closing. Below is a summary of its key functionalities:
Key Features:
Box Range Detection:
The script identifies price ranges using the highest high and lowest low of a configurable boxLength period.
These levels are plotted on the chart to visualize the price range.
RSI Divergence Detection:
The script calculates RSI using a configurable rsiLength.
Detects bullish divergence when price makes a lower low, but RSI makes a higher low.
Detects bearish divergence when price makes a higher high, but RSI makes a lower high.
Includes separate left and right lookback periods (leftLookback, rightLookback) for precise local extrema detection.
Customizable Moving Averages:
Supports multiple types of Moving Averages (SMA, EMA, SMMA, WMA, VWMA).
Calculates and plots MA20, MA50, MA100, and MA200 on a user-defined timeframe (custom_timeframe).
Identifies uptrends and downtrends based on the alignment of the moving averages and price levels.
Dynamic Position Scaling:
Implements dynamic position sizing for long entries and partial position closing for exits.
The percentage of position size added or closed is based on the difference between the current price and the average position price (avgPrice), with configurable minimum thresholds (minEnterPercent, minExitPercent).
Signal Integration for OKX Bots:
Sends buy/sell signals to OKX Signal Bots using the configured signalToken.
Supports market or limit orders with configurable price offsets and investment types.
Trend-Based Signal Filtering:
Only triggers long signals during downtrends and short signals during uptrends, ensuring trades align with the overall market context.
Visual Annotations:
Plots bullish and bearish divergence signals on the chart.
Displays labels showing dynamic position size adjustments and current average price during trades.
How It Works:
Long Signals:
Triggered when the price breaches the lower box range, and a bullish RSI divergence is detected.
Additional filtering ensures long trades are executed only during downtrend conditions.
Dynamically adjusts the position size based on the price difference from the average entry price.
Short Signals:
Triggered when the price breaches the upper box range, and a bearish RSI divergence is detected.
Additional filtering ensures short trades are executed only during uptrend conditions.
Dynamically closes portions of the position based on price movement relative to the average entry price.
Alerts:
Generates actionable alerts formatted for OKX bots, including order type, signal token, and dynamically calculated position sizes.
Use Case:
This strategy is well-suited for automated trading on platforms like OKX, where it can:
Exploit price ranges and RSI divergences for precise entries and exits.
Dynamically manage position sizes to optimize risk-reward.
Adapt to different market conditions using configurable parameters like moving averages, divergence lookbacks, and trend filters.
This script provides a robust foundation for traders looking to automate their strategies while maintaining flexibility and control over their trading logic.
SL - 4 EMAs, 2 SMAs & Crossover SignalsThis TradingView Pine Script code is built for day traders, especially those trading crypto on a 1‑hour chart. In simple words, the script does the following:
Calculates Moving Averages:
It computes four exponential moving averages (EMAs) and two simple moving averages (SMAs) based on the closing price (or any price you select). Each moving average uses a different time period that you can adjust.
Plots Them on Your Chart:
The EMAs and SMAs are drawn on your chart in different colors and line thicknesses. This helps you quickly see the short-term and long-term trends.
Generates Buy and Sell Signals:
Buy Signal: When the fastest EMA (for example, a 10-period EMA) crosses above a slightly slower EMA (like a 21-period EMA) and the four EMAs are in a bullish order (meaning the fastest is above the next ones), the script will show a "BUY" label on the chart.
Sell Signal: When the fastest EMA crosses below the second fastest EMA and the four EMAs are lined up in a bearish order (the fastest is below the others), it displays a "SELL" label.
In essence, the code is designed to help you spot potential entry and exit points based on the relationships between multiple moving averages, which work as trend indicators. This makes it easier to decide when to trade on your 1‑hour crypto chart.
SASDv2rSensitive Altcoin Season Detector V2
This Pine Script™ code, titled "SASDv2r" (Sensitive Altcoin Season Detector version 2 revised), is designed for cryptocurrency trading analysis on the TradingView platform and tailored for those interested in tracking when altcoins might be outperforming Bitcoin, potentially indicating a market shift towards altcoins.
Feel free to use and modify. If you made it better, please let me know. Intention was to help the community with a tool for retail traders have no access to advanced, MV indicators. Solution uses classic TA only.
Use it witl TOTAL3/BTC indicator.
Please check: it gave signal just before last alt season % rose more than 250%.
Market Cap Data Fetching: The script fetches market capitalization data for Bitcoin, Ethereum, and all other altcoins (excluding Bitcoin and Ethereum) using request.security function.
Altcoin to Bitcoin Ratio: It calculates the ratio of total market cap of altcoins to Bitcoin's market cap (altToBtcRatio), which is central to identifying an "altcoin season."
Moving Averages: Several moving averages are computed for different time frames (50-day SMA, 200-day SMA, 20-day SMA, and 10-day EMA) to analyze trends in the altcoin to Bitcoin ratio.
Momentum Indicators: The script uses RSI (Relative Strength Index) and MACD (Moving Average Convergence Divergence) to gauge momentum and potential reversal points in the market.
Custom Indicators: It includes Volume Weighted Moving Average (VWMA) and a custom momentum indicator (altMomentum and altMomentumAvg) to provide additional insights into market movements.
Volatility Measurement: Bollinger Bands are calculated to assess volatility in the altcoin to Bitcoin ratio, which helps identify periods of high or low market activity.
Visual Analysis: Various plots are added to the chart for visual interpretation, including the altcoin to Bitcoin ratio, different moving averages, and Bollinger Bands.
Alt Season Detection: The script defines conditions for detecting when an "altcoin season" might be starting, based on crossovers of moving averages, RSI levels, MACD signals, and other custom criteria.
Performance Tracking: After signaling an alt season, the script evaluates the performance over the next 30 days by checking if there's been an increase in the altcoin to Bitcoin ratio, adding labels for positive or negative trends.(this one is in progress). Logic still gives false signals and aim is to identify failed signals.
Visual Signals: Labels are placed on the chart to visually indicate the beginning of a potential alt season or the performance outcome after a signal, aiding traders in making informed decisions.
Waldo RSI Overlay :oWaldo RSI Overlay :o Indicator Guide
Welcome to the guide for the Waldo RSI Overlay :o indicator on TradingView. This tool enhances your trading analysis through RSI-based overlays for trend analysis, divergence detection, and breakout/breakdown signals when used with its companion indicator, Waldo RSI :o.
Key Features:
RSI Overlay:
• RSI Source: Choose from:
o ON RSI: Uses the RSI values directly to detect pivots, focusing on RSI highs and lows for trend analysis.
o ON HIGH, ON CLOSE, ON LOW, ON OPEN:
These options base pivot detection on price action at those specific points, offering an alternative market structure view.
• RSI Settings:
o Source: Default is (H+L)/2, but you can select any price for RSI calculation.
o Length: Default RSI length is 7, which you can adjust for sensitivity.
Trend Lines:
• Show Trend Lines: Toggle to display trend lines based on pivot points.
• Zigzag Length: Sets the sensitivity of pivot point detection.
• Confirm Length: Ensures the validity of pivot points (default is 3).
• Colors: Customize colors for Higher Highs (HH), Lower Highs (LH), Higher Lows (HL), and Lower Lows (LL).
• Transparency and Line Width: Control how trend lines and fills appear.
• Label Size: Adjust the size of labels identifying pivot points.
Divergences:
• Classic Divergences:
o Show Classic Div: Enable to highlight regular divergences where price and RSI move in opposite directions.
o Colors: Define colors for bullish and bearish divergence lines and labels.
o Transparency and Line Width: Adjust the visual impact of divergence signals.
• Hidden Divergences:
o Similar settings as classic, but these highlight divergences indicating trend continuation.
Breakout/Breakdown:
• Show Breakout/Breakdown: When activated, this feature signals when the price breaks through previous highs or lows. To activate these breakouts, you need the companion indicator Waldo RSI :o, select the SRC in the External section, and select the crossovers for each one.
This combination provides RSI confirmation for breakout/breakdown events.
Overbought/Oversold Zones:
• Show Overbought and Oversold Zones: Bars are colored when RSI exceeds 70 (purple) or falls below 30 (blue), indicating potential market extremes.
Moving Averages (Optional):
• Show Moving Averages: Option to overlay two moving averages for trend confirmation.
• Source, Type, Length: Customize each MA's configuration.
Ghost Lines (Optional):
• Ghost Lines: When enabled, trend lines extend for only a specified period (Ghost Length) instead of indefinitely.
How to Use the Indicator:
1. Setup:
o Configure RSI settings by choosing the RSI Source and adjusting the RSI Length to suit your trading style.
o Set the Zigzag Length and Confirm Length for trend line sensitivity based on market volatility.
2. Trend Analysis:
o Look at the colored horizontal lines and fills for HH, LH, HL, LL to discern market structure and potential reversal points.
3. Divergence Detection:
o Identify divergences where price and RSI diverge. Regular divergences might signal trend exhaustion, while hidden ones could indicate trend persistence.
4. Breakout/Breakdown Signals:
o Ensure you have both the Waldo RSI Overlay :o and Waldo RSI :o indicators applied. Green triangles below bars signal breakouts; red ones above indicate breakdowns, based on price movement with RSI confirmation from the companion indicator.
5. Overbought/Oversold:
o Use these colored zones to spot potential momentum shifts or reversal areas.
6. Moving Averages on RSI:
o If used, these can help confirm trends or identify crossover signals for additional trade confirmation.
7. Ghost Lines:
o For a less cluttered chart, enable this to limit how far trend lines extend.
Tips for Usage:
• Always combine this indicator with other analytical tools for better confirmation. No single indicator should guide all decisions.
• Adjust settings according to the asset's behavior and your trading timeframe.
• Regularly review your settings as market dynamics change.
Remember, trading involves risk, and past performance doesn't predict future outcomes. Use this indicator within a comprehensive trading strategy.
Arrow-SimplyTrade vol1.5-FinalTitle: Arrow-SimplyTrade vol1.5-Final
Description:
This advanced trading indicator is designed to assist traders in analyzing market trends and identifying optimal entry signals. It combines several popular technical analysis tools and strategies, including EMA (Exponential Moving Average), MA (Simple Moving Averages), Bollinger Bands, and candlestick patterns. This indicator provides both trend-following and counter-trend signals, making it suitable for various trading styles, such as scalping and swing trading.
Main Features:
EMA (Exponential Moving Average):
EMA200 is the main trend line that helps determine the overall market direction. When the price is above EMA200, the trend is considered bullish, and when the price is below EMA200, the trend is considered bearish.
It helps filter out signals that go against the prevailing market trend.
Simple Moving Averages (MA5 and MA15):
This indicator uses two Simple Moving Averages: MA5 (Fast) and MA15 (Slow). Their crossovers create buy or sell signals:
Buy Signal: When MA5 crosses above MA15, signaling a potential upward trend.
Sell Signal: When MA5 crosses below MA15, signaling a potential downward trend.
Bollinger Bands:
Bollinger Bands measure market volatility and can identify periods of overbought or oversold conditions. The Upper and Lower Bands help detect potential breakout points, while the Middle Line (Basis) serves as dynamic support or resistance.
This tool is particularly useful for identifying volatile conditions and potential reversals.
Arrows:
The indicator plots arrows on the chart to signal entry opportunities:
Green Arrows signal buy opportunities (when MA5 crosses above MA15 and price is above EMA200).
Red Arrows signal sell opportunities (when MA5 crosses below MA15 and price is below EMA200).
Opposite Arrows: Optionally, the indicator can also display arrows for counter-trend signals, triggered by MA5 and MA15 crossovers, regardless of the price's position relative to EMA200.
Candlestick Patterns:
The indicator detects popular candlestick patterns such as Bullish Engulfing, Bearish Engulfing, Hammer, and Doji.
These patterns are important for confirming entry points or anticipating trend reversals.
How to Use:
EMA200: The main trend line. If the price is above EMA200, consider long positions. If the price is below EMA200, consider short positions.
MA5 and MA15: Short-term trend indicators. The crossover of these averages generates buy or sell signals.
Bollinger Bands: Use these bands to spot overbought/oversold conditions. Breakouts from the bands may signal potential entry points.
Arrows: Green arrows represent buy signals, and red arrows represent sell signals. Opposite direction arrows can be used for counter-trend strategies.
Candlestick Patterns: Patterns like Bullish Engulfing or Doji can help confirm the signals.
Customizable Settings:
Fully customizable colors, line styles, and display settings for EMA, MAs, Bollinger Bands, and arrows.
The Candlestick Patterns feature can be toggled on or off based on user preference.
Important Notes:
This indicator is intended to be used in conjunction with other analysis tools.
Past performance does not guarantee future results.
Polish:
Tytuł: Arrow-SimplyTrade vol1.5-Final
Opis:
Ten zaawansowany wskaźnik handlowy jest zaprojektowany, aby pomóc traderom w analizie trendów rynkowych oraz identyfikowaniu optymalnych sygnałów wejścia. Łączy w sobie kilka popularnych narzędzi analizy technicznej i strategii, w tym EMA (Wykładnicza Średnia Ruchoma), MA (Prosta Średnia Ruchoma), Bollinger Bands oraz formacje świecowe. Wskaźnik generuje zarówno sygnały podążające za trendem, jak i przeciwnym trendowi, co sprawia, że jest odpowiedni do różnych stylów handlu, takich jak scalping oraz swing trading.
Główne Funkcje:
EMA (Wykładnicza Średnia Ruchoma):
EMA200 to główna linia trendu, która pomaga określić ogólny kierunek rynku. Gdy cena znajduje się powyżej EMA200, trend jest uznawany za wzrostowy, a gdy poniżej EMA200, za spadkowy.
Pomaga to filtrować sygnały, które są niezgodne z głównym trendem rynkowym.
Proste Średnie Ruchome (MA5 i MA15):
Wskaźnik używa dwóch Prostych Średnich Ruchomych: MA5 (szybka) oraz MA15 (wolna). Ich przecięcia generują sygnały kupna lub sprzedaży:
Sygnał Kupna: Kiedy MA5 przecina MA15 od dołu, sygnalizując potencjalny wzrost.
Sygnał Sprzedaży: Kiedy MA5 przecina MA15 od góry, sygnalizując potencjalny spadek.
Bollinger Bands:
Bollinger Bands mierzą zmienność rynku i mogą pomóc w identyfikowaniu okresów wykupienia lub wyprzedania rynku. Górna i dolna linia pomagają wykrywać punkty wybicia, a Środkowa Linia (Basis) działa jako dynamiczny poziom wsparcia lub oporu.
Narzędzie to jest szczególnie przydatne w wykrywaniu warunków zmienności i potencjalnych odwróceń trendu.
Strzałki:
Wskaźnik wyświetla strzałki na wykresie, które wskazują sygnały kupna i sprzedaży:
Zielona strzałka wskazuje sygnał kupna (gdy MA5 przecina MA15 i cena jest powyżej EMA200).
Czerwona strzałka wskazuje sygnał sprzedaży (gdy MA5 przecina MA15 i cena jest poniżej EMA200).
Strzałki w przeciwnym kierunku: Opcjonalna funkcja, która pokazuje strzałki w przeciwnym kierunku, uruchamiane przez przecięcia MA5 i MA15, niezależnie od pozycji ceny względem EMA200.
Formacje Świecowe:
Wskaźnik wykrywa popularne formacje świecowe, takie jak Bullish Engulfing, Bearish Engulfing, Hammer oraz Doji.
Formacje te pomagają traderom potwierdzić punkty wejścia i przewidzieć możliwe odwrócenia trendu.
Jak Używać:
EMA200: Główna linia trendu. Jeśli cena jest powyżej EMA200, rozważaj pozycje długie. Jeśli cena jest poniżej EMA200, rozważaj pozycje krótkie.
MA5 i MA15: Śledzą krótkoterminowe zmiany trendu. Przecięcia tych średnich generują sygnały kupna lub sprzedaży.
Bollinger Bands: Używaj tych pasm do wykrywania wykupionych lub wyprzedanych warunków. Wybicia z pasm mogą wskazywać potencjalne punkty wejścia.
Strzałki: Zielona strzałka wskazuje sygnał kupna, a czerwona strzałka sygnał sprzedaży. Strzałki w przeciwnym kierunku mogą być używane do strategii przeciwtrendowych.
Formacje Świecowe: Formacje takie jak Bullish Engulfing czy Doji mogą pomóc w potwierdzaniu sygnałów.
Ustawienia Personalizacji:
W pełni personalizowalne kolory, style linii i ustawienia wyświetlania dla EMA, MAs, Bollinger Bands oraz strzałek.
Funkcja Formacji Świecowych może być włączana lub wyłączana według preferencji użytkownika.
Ważne Uwagi:
Ten wskaźnik powinien być używany w połączeniu z innymi narzędziami analizy rynku.
Wyniki z przeszłości nie gwarantują wyników w przyszłości.
Magnificent 7 Overall Percentage Change with MA and Angle LabelsMagnificent 7 Overall Percentage Change with MA and Angle Labels
Overview:
The "Magnificent 7 Overall Percentage Change with MA and Angle Labels" indicator tracks the percentage change of seven key tech stocks (Apple, Microsoft, Amazon, NVIDIA, Tesla, Meta, and Alphabet) and displays their overall average percentage change on the chart. It also provides a moving average of this overall change and calculates the angle of the moving average to help traders gauge the momentum and direction of the overall trend.
How it works:
Real-Time Percentage Change: The indicator calculates the percentage change of each of the "Magnificent 7" stocks compared to their previous day's closing price, giving a snapshot of the market's performance.
Overall Average: It then computes the average of the seven stocks' percentage changes to reflect the broader movement of these major tech companies.
Moving Average: The indicator offers a choice of four types of moving averages (SMA, EMA, WMA, or VWMA) to smooth the overall percentage change, allowing traders to focus on the trend rather than short-term fluctuations.
Slope and Angle Calculation: To provide additional insights, the indicator calculates the slope of the moving average and converts it into an angle (in degrees). This can help traders determine the strength of the trend—steeper angles often indicate stronger momentum.
Key Features:
Percentage Change of the "Magnificent 7":
Tracks the percentage change of Apple (AAPL), Microsoft (MSFT), Amazon (AMZN), NVIDIA (NVDA), Tesla (TSLA), Meta (META), and Alphabet (GOOGL) on the current chart's timeframe.
Overall Average Change:
Computes the average percentage change across all seven stocks, giving a combined view of how the most influential tech stocks are performing.
Customizable Moving Averages:
Offers four types of moving averages (SMA, EMA, WMA, VWMA) to provide flexibility in tracking the trend of the overall percentage change.
Angle Calculation:
Measures the angle of the moving average in degrees, which helps assess the strength of the market’s momentum. Alerts and visual cues can be triggered based on the angle's steepness.
Visual Cues:
The percentage change is plotted in green when positive and red when negative, with a background color that changes accordingly. A zero line is plotted for reference.
Use Case:
This indicator is ideal for traders and investors looking to track the collective performance of the most dominant tech companies in the market. It provides real-time insights into how the "Magnificent 7" stocks are moving together and offers clues about potential market momentum based on the direction and angle of their average percentage change.
Customization:
Moving Average Type and Length: Choose between different types of moving averages (SMA, EMA, WMA, VWMA) and adjust the length to suit your preferred timeframe.
Angle Threshold: Set an angle threshold to trigger alerts when the moving average slope becomes too steep, indicating strong momentum.
Alerts:
Alerts can be created based on the crossing of the moving average or when the angle of the moving average exceeds a specified threshold. This ensures traders are notified when the trend is accelerating or decelerating significantly.
Conclusion:
The "Magnificent 7 Overall Percentage Change with MA and Angle Labels" indicator is a powerful tool for those wanting to monitor the performance of the most influential tech stocks, analyze their overall trend, and receive timely alerts when market conditions shift.
