Accurate Bollinger Bands mcbw_ [True Volatility Distribution]The Bollinger Bands have become a very important technical tool for discretionary and algorithmic traders alike over the last decades. It was designed to give traders an edge on the markets by setting probabilistic values to different levels of volatility. However, some of the assumptions that go into its calculations make it unusable for traders who want to get a correct understanding of the volatility that the bands are trying to be used for. Let's go through what the Bollinger Bands are said to show, how their calculations work, the problems in the calculations, and how the current indicator I am presenting today fixes these.
--> If you just want to know how the settings work then skip straight to the end or click on the little (i) symbol next to the values in the indicator settings window when its on your chart <--
--------------------------- What Are Bollinger Bands ---------------------------
The Bollinger Bands were formed in the 1980's, a time when many retail traders interacted with their symbols via physically printed charts and computer memory for personal computer memory was measured in Kb (about a factor of 1 million smaller than today). Bollinger Bands are designed to help a trader or algorithm see the likelihood of price expanding outside of its typical range, the further the lines are from the current price implies the less often they will get hit. With a hands on understanding many strategies use these levels for designated levels of breakout trades or to assist in defining price ranges.
--------------------------- How Bollinger Bands Work ---------------------------
The calculations that go into Bollinger Bands are rather simple. There is a moving average that centers the indicator and an equidistant top band and bottom band are drawn at a fixed width away. The moving average is just a typical moving average (or common variant) that tracks the price action, while the distance to the top and bottom bands is a direct function of recent price volatility. The way that the distance to the bands is calculated is inspired by formulas from statistics. The standard deviation is taken from the candles that go into the moving average and then this is multiplied by a user defined value to set the bands position, I will call this value 'the multiple'. When discussing Bollinger Bands, that trading community at large normally discusses 'the multiple' as a multiplier of the standard deviation as it applies to a normal distribution (gaußian probability). On a normal distribution the number of standard deviations away (which trades directly use as 'the multiple') you are directly corresponds to how likely/unlikely something is to happen:
1 standard deviation equals 68.3%, meaning that the price should stay inside the 1 standard deviation 68.3% of the time and be outside of it 31.7% of the time;
2 standard deviation equals 95.5%, meaning that the price should stay inside the 2 standard deviation 95.5% of the time and be outside of it 4.5% of the time;
3 standard deviation equals 99.7%, meaning that the price should stay inside the 3 standard deviation 99.7% of the time and be outside of it 0.3% of the time.
Therefore when traders set 'the multiple' to 2, they interpret this as meaning that price will not reach there 95.5% of the time.
---------------- The Problem With The Math of Bollinger Bands ----------------
In and of themselves the Bollinger Bands are a great tool, but they have become misconstrued with some incorrect sense of statistical meaning, when they should really just be taken at face value without any further interpretation or implication.
In order to explain this it is going to get a bit technical so I will give a little math background and try to simplify things. First let's review some statistics topics (distributions, percentiles, standard deviations) and then with that understanding explore the incorrect logic of how Bollinger Bands have been interpreted/employed.
---------------- Quick Stats Review ----------------
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(If you are comfortable with statistics feel free to skip ahead to the next section)
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-------- I: Probability distributions --------
When you have a lot of data it is helpful to see how many times different results appear in your dataset. To visualize this people use "histograms", which just shows how many times each element appears in the dataset by stacking each of the same elements on top of each other to form a graph. You may be familiar with the bell curve (also called the "normal distribution", which we will be calling it by). The normal distribution histogram looks like a big hump around zero and then drops off super quickly the further you get from it. This shape (the bell curve) is very nice because it has a lot of very nifty mathematical properties and seems to show up in nature all the time. Since it pops up in so many places, society has developed many different shortcuts related to it that speed up all kinds of calculations, including the shortcut that 1 standard deviation = 68.3%, 2 standard deviations = 95.5%, and 3 standard deviations = 99.7% (these only apply to the normal distribution). Despite how handy the normal distribution is and all the shortcuts we have for it are, and how much it shows up in the natural world, there is nothing that forces your specific dataset to look like it. In fact, your data can actually have any possible shape. As we will explore later, economic and financial datasets *rarely* follow the normal distribution.
-------- II: Percentiles --------
After you have made the histogram of your dataset you have built the "probability distribution" of your own dataset that is specific to all the data you have collected. There is a whole complicated framework for how to accurately calculate percentiles but we will dramatically simplify it for our use. The 'percentile' in our case is just the number of data points we are away from the "middle" of the data set (normally just 0). Lets say I took the difference of the daily close of a symbol for the last two weeks, green candles would be positive and red would be negative. In this example my dataset of day by day closing price difference is:
week 1:
week 2:
sorting all of these value into a single dataset I have:
I can separate the positive and negative returns and explore their distributions separately:
negative return distribution =
positive return distribution =
Taking the 25th% percentile of these would just be taking the value that is 25% towards the end of the end of these returns. Or akin the 100%th percentile would just be taking the vale that is 100% at the end of those:
negative return distribution (50%) = -5
positive return distribution (50%) = +4
negative return distribution (100%) = -10
positive return distribution (100%) = +20
Or instead of separating the positive and negative returns we can also look at all of the differences in the daily close as just pure price movement and not account for the direction, in this case we would pool all of the data together by ignoring the negative signs of the negative reruns
combined return distribution =
In this case the 50%th and 100%th percentile of the combined return distribution would be:
combined return distribution (50%) = 4
combined return distribution (100%) = 10
Sometimes taking the positive and negative distributions separately is better than pooling them into a combined distribution for some purposes. Other times the combined distribution is better.
Most financial data has very different distributions for negative returns and positive returns. This is encapsulated in sayings like "Price takes the stairs up and the elevator down".
-------- III: Standard Deviation --------
The formula for the standard deviation (refereed to here by its shorthand 'STDEV') can be intimidating, but going through each of its elements will illuminate what it does. The formula for STDEV is equal to:
square root ( (sum ) / N )
Going back the the dataset that you might have, the variables in the formula above are:
'mean' is the average of your entire dataset
'x' is just representative of a single point in your dataset (one point at a time)
'N' is the total number of things in your dataset.
Going back to the STDEV formula above we can see how each part of it works. Starting with the '(x - mean)' part. What this does is it takes every single point of the dataset and measure how far away it is from the mean of the entire dataset. Taking this value to the power of two: '(x - mean) ^ 2', means that points that are very far away from the dataset mean get 'penalized' twice as much. Points that are very close to the dataset mean are not impacted as much. In practice, this would mean that if your dataset had a bunch of values that were in a wide range but always stayed in that range, this value ('(x - mean) ^ 2') would end up being small. On the other hand, if your dataset was full of the exact same number, but had a couple outliers very far away, this would have a much larger value since the square par of '(x - mean) ^ 2' make them grow massive. Now including the sum part of 'sum ', this just adds up all the of the squared distanced from the dataset mean. Then this is divided by the number of values in the dataset ('N'), and then the square root of that value is taken.
There is nothing inherently special or definitive about the STDEV formula, it is just a tool with extremely widespread use and adoption. As we saw here, all the STDEV formula is really doing is measuring the intensity of the outliers.
--------------------------- Flaws of Bollinger Bands ---------------------------
The largest problem with Bollinger Bands is the assumption that price has a normal distribution. This is assumption is massively incorrect for many reasons that I will try to encapsulate into two points:
Price return do not follow a normal distribution, every single symbol on every single timeframe has is own unique distribution that is specific to only itself. Therefore all the tools, shortcuts, and ideas that we use for normal distributions do not apply to price returns, and since they do not apply here they should not be used. A more general approach is needed that allows each specific symbol on every specific timeframe to be treated uniquely.
The distributions of price returns on the positive and negative side are almost never the same. A more general approach is needed that allows positive and negative returns to be calculated separately.
In addition to the issues of the normal distribution assumption, the standard deviation formula (as shown above in the quick stats review) is essentially just a tame measurement of outliers (a more aggressive form of outlier measurement might be taking the differences to the power of 3 rather than 2). Despite this being a bit of a philosophical question, does the measurement of outlier intensity as defined by the STDEV formula really measure what we want to know as traders when we're experiencing volatility? Or would adjustments to that formula better reflect what we *experience* as volatility when we are actively trading? This is an open ended question that I will leave here, but I wanted to pose this question because it is a key part of what how the Bollinger Bands work that we all assume as a given.
Circling back on the normal distribution assumption, the standard deviation formula used in the calculation of the bands only encompasses the deviation of the candles that go into the moving average and have no knowledge of the historical price action. Therefore the level of the bands may not really reflect how the price action behaves over a longer period of time.
------------ Delivering Factually Accurate Data That Traders Need------------
In light of the problems identified above, this indicator fixes all of these issue and delivers statistically correct information that discretionary and algorithmic traders can use, with truly accurate probabilities. It takes the price action of the last 2,000 candles and builds a huge dataset of distributions that you can directly select your percentiles from. It also allows you to have the positive and negative distributions calculated separately, or if you would like, you can pool all of them together in a combined distribution. In addition to this, there is a wide selection of moving averages directly available in the indicator to choose from.
Hedge funds, quant shops, algo prop firms, and advanced mechanical groups all employ the true return distributions in their work. Now you have access to the same type of data with this indicator, wherein it's doing all the lifting for you.
------------------------------ Indicator Settings ------------------------------
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---- Moving average ----
Select the type of moving average you would like and its length
---- Bands ----
The percentiles that you enter here will be pulled directly from the return distribution of the last 2,000 candles. With the typical Bollinger Bands, traders would select 2 standard deviations and incorrectly think that the levels it highlights are the 95.5% levels. Now, if you want the true 95.5% level, you can just enter 95.5 into the percentile value here. Each of the three available bands takes the true percentile you enter here.
---- Separate Positive & Negative Distributions----
If this box is checked the positive and negative distributions are treated indecently, completely separate from each other. You will see that the width of the top and bottom bands will be different for each of the percentiles you enter.
If this box is unchecked then all the negative and positive distributions are pooled together. You will notice that the width of the top and bottom bands will be the exact same.
---- Distribution Size ----
This is the number of candles that the price return is calculated over. EG: to collect the price return over the last 33 candles, the difference of price from now to 33 candles ago is calculated for the last 2,000 candles, to build a return distribution of 2000 points of price differences over 33 candles.
NEGATIVE NUMBERS(<0) == exact number of candles to include;
EG: setting this value to -20 will always collect volatility distributions of 20 candles
POSITIVE NUMBERS(>0) == number of candles to include as a multiple of the Moving Average Length value set above;
EG: if the Moving Average Length value is set to 22, setting this value to 2 will use the last 22*2 = 44 candles for the collection of volatility distributions
MORE candles being include will generally make the bands WIDER and their size will change SLOWER over time.
I wish you focus, dedication, and earnest success on your journey.
Happy trading :)
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AI InfinityAI Infinity – Multidimensional Market Analysis
Overview
The AI Infinity indicator combines multiple analysis tools into a single solution. Alongside dynamic candle coloring based on MACD and Stochastic signals, it features Alligator lines, several RSI lines (including glow effects), and optionally enabled EMAs (20/50, 100, and 200). Every module is individually configurable, allowing traders to tailor the indicator to their personal style and strategy.
Important Note (Disclaimer)
This indicator is provided for educational and informational purposes only.
It does not constitute financial or investment advice and offers no guarantee of profit.
Each trader is responsible for their own trading decisions.
Past performance does not guarantee future results.
Please review the settings thoroughly and adjust them to your personal risk profile; consider supplementary analyses or professional guidance where appropriate.
Functionality & Components
1. Candle Coloring (MACD & Stochastic)
Objective: Provide an immediate visual snapshot of the market’s condition.
Details:
MACD Signal: Used to identify bullish and bearish momentum.
Stochastic: Detects overbought and oversold zones.
Color Modes: Offers both a simple (two-color) mode and a gradient mode.
2. Alligator Lines
Objective: Assist with trend analysis and determining the market’s current phase.
Details:
Dynamic SMMA Lines (Jaw, Teeth, Lips) that adjust based on volatility and market conditions.
Multiple Lengths: Each element uses a separate smoothing period (13, 8, 5).
Transparency: You can show or hide each line independently.
3. RSI Lines & Glow Effects
Objective: Display the RSI values directly on the price chart so critical levels (e.g., 20, 50, 80) remain visible at a glance.
Details:
RSI Scaling: The RSI is plotted in the chart window, eliminating the need to switch panels.
Dynamic Transparency: A pulse effect indicates when the RSI is near critical thresholds.
Glow Mode: Choose between “Direct Glow” or “Dynamic Transparency” (based on ATR distance).
Custom RSI Length: Freely adjustable (default is 14).
4. Optional EMAs (20/50, 100, 200)
Objective: Utilize moving averages for trend assessment and identifying potential support/resistance areas.
Details:
20/50 EMA: Select which one to display via a dropdown menu.
100 EMA & 200 EMA: Independently enabled.
Color Logic: Automatically green (price > EMA) or red (price < EMA). Each EMA’s up/down color is customizable.
Configuration Options
Candle Coloring:
Choose between Gradient or Simple mode.
Adjust the color scheme for bullish/bearish candles.
Transparency is dynamically based on candle body size and Stochastic state.
Alligator Lines:
Toggle each line (Jaw/Teeth/Lips) on or off.
Select individual colors for each line.
RSI Section:
RSI Length can be set as desired.
RSI lines (0, 20, 50, 80, 100) with user-defined colors and transparency (pulse effect).
Additional lines (e.g., RSI 40/60) are also available.
Glow Effects:
Switch between “Dynamic Transparency” (ATR-based) and “Direct Glow”.
Independently applied to the RSI 100 and RSI 0 lines.
EMAs (20/50, 100, 200):
Activate each one as needed.
Each EMA’s up/down color can be customized.
Example Use Cases
Trend Identification:
Enable Alligator lines to gauge general trend direction through SMMA signals.
Timing:
Watch the Candle Colors to spot potential overbought or oversold conditions.
Fine-Tuning:
Utilize the RSI lines to closely monitor important thresholds (50 as a trend barometer, 80/20 as possible reversal zones).
Filtering:
Enable a 50 EMA to quickly see if the market is trading above (bullish) or below (bearish) it.
Austin MTF EMA Entry PointsAustin MTF EMA Entry Points
Overview
The Austin MTF EMA Entry Points is a custom TradingView indicator designed to assist traders in identifying high-probability entry points by combining multiple time frame (MTF) analysis. It leverages exponential moving averages (EMAs) from the daily, 1-hour, and 15-minute charts to generate buy and sell signals that align with the overall trend.
This indicator is ideal for traders who:
Want to trade in the direction of the broader daily trend.
Seek precise entry points on lower time frames (1H and 15M).
Prefer using EMAs as their main trend-following tool.
How It Works
Daily Trend Filter:
The indicator calculates the 50 EMA on the daily chart.
The daily EMA acts as the primary trend filter:
If the current price is above the daily 50 EMA, the trend is bullish.
If the current price is below the daily 50 EMA, the trend is bearish.
Lower Time Frame Entry Points:
The indicator calculates the 20 EMA on both the 1-hour (1H) and 15-minute (15M) time frames.
Buy and sell signals are generated when the price aligns with the trend on all three time frames:
Buy Signal: Price is above the daily 50 EMA and also above the 20 EMA on both the 1H and 15M charts.
Sell Signal: Price is below the daily 50 EMA and also below the 20 EMA on both the 1H and 15M charts.
Visual and Alert Features:
Plot Lines:
The daily 50 EMA is plotted in yellow for easy identification of the main trend.
The 20 EMA from the 1H chart is plotted in blue, and the 15M chart's EMA is in purple for comparison.
Buy/Sell Markers:
Green "Up" arrows appear for buy signals.
Red "Down" arrows appear for sell signals.
Alerts:
Alerts notify users when a buy or sell signal is triggered, making it easier to act on trading opportunities in real-time.
How to Use the Indicator
Identify the Main Trend:
Check the relationship between the price and the daily 50 EMA (yellow line):
Only look for buy signals if the price is above the daily 50 EMA.
Only look for sell signals if the price is below the daily 50 EMA.
Wait for Lower Time Frame Alignment:
For a valid signal, ensure that the price is also above or below the 20 EMA (blue and purple lines) on both the 1H and 15M time frames:
This alignment confirms short-term momentum in the same direction as the daily trend.
Act on Signals:
Use the arrows as visual cues for entry points:
Enter long trades on green "Up" arrows.
Enter short trades on red "Down" arrows.
The alerts will notify you of these signals, so you don’t have to monitor the chart constantly.
Exit Strategy:
Use your preferred stop-loss, take-profit, or trailing stop strategy.
You can also exit trades if the price crosses back below/above the daily 50 EMA, signaling a potential reversal.
Use Cases
Swing Traders: Use the daily trend filter to trade in the direction of the dominant trend, while using 1H and 15M signals to fine-tune entries.
Day Traders: Leverage the 1H and 15M time frames to capitalize on short-term momentum while respecting the broader daily trend.
Position Traders: Monitor the indicator to determine potential reversals or significant alignment across time frames.
Customizable Inputs
The indicator includes the following inputs:
Daily EMA Length: Default is 50. Adjust this to change the length of the trend filter EMA.
Lower Time Frame EMA Length: Default is 20. Adjust this to change the short-term EMA for the 1H and 15M charts.
Time Frames: Hardcoded to "D", "60", and "15", but you can modify the script for different time frames if needed.
Example Scenarios
Buy Signal:
Price is above the daily 50 EMA.
Price crosses above the 20 EMA on both the 1H and 15M time frames.
A green "Up" arrow is displayed, and an alert is triggered.
Sell Signal:
Price is below the daily 50 EMA.
Price crosses below the 20 EMA on both the 1H and 15M time frames.
A red "Down" arrow is displayed, and an alert is triggered.
Strengths and Limitations
Strengths:
Aligns trades with the higher time frame trend for increased probability.
Uses multiple time frame analysis to identify precise entry points.
Visual signals and alerts make it easy to use in real-time.
Limitations:
May produce fewer signals in choppy or ranging markets.
Requires discipline to avoid overtrading when conditions are unclear.
Lag in EMAs could result in late entries in fast-moving markets.
Final Notes
The Austin MTF EMA Entry Points indicator is a powerful tool for traders who value multiple time frame alignment and trend-following strategies. While it simplifies decision-making, it is always recommended to backtest and practice proper risk management before using it in live markets.
Try it out and make smarter, trend-aligned trades today! 🚀
3_SMA_Strategy_V-Singhal by ParthibIndicator Name: 3_SMA_Strategy_V-Singhal by Parthib
Description:
The 3_SMA_Strategy_V-Singhal by Parthib is a dynamic trend-following strategy that combines three key simple moving averages (SMA) — SMA 20, SMA 50, and SMA 200 — to generate buy and sell signals. This strategy uses these SMAs to capture and follow market trends, helping traders identify optimal entry (buy) and exit (sell) points. Additionally, the strategy highlights the closing price (CP), which plays a critical role in confirming buy and sell signals.
The strategy also features a Second Buy Signal triggered if the price falls more than 10% after an initial buy signal, providing a re-entry opportunity with a different visual highlight for the second buy signal.
Features:
Three Simple Moving Averages (SMA):
SMA 20: Short-term moving average reflecting immediate market trends.
SMA 50: Medium-term moving average showing the prevailing trend.
SMA 200: Long-term moving average that indicates the overall market trend.
Buy Signal (B1):
Triggered when:
SMA 200 > SMA 50 > SMA 20, indicating a bullish market structure.
The closing price is positioned below all three SMAs, confirming a potential upward reversal.
A green label appears at the low of the bar with the text B1-Price, indicating the price at which the buy signal is generated.
Second Buy Signal (B2):
Triggered if the price falls more than 10% after the first buy signal, providing an opportunity to re-enter the market at a potentially better price.
A blue label appears at the low of the bar with the text B2-Price, showing the price at which the second buy opportunity arises.
Sell Signal (S):
Triggered when:
SMA 20 > SMA 50 > SMA 200, indicating a bearish trend.
The closing price (CP) is positioned above all three SMAs, confirming a potential downward movement.
A red label appears at the high of the bar with the text S-Price, showing the price at which the sell signal is triggered.
How It Works:
Buy Conditions:
SMA 200 > SMA 50 > SMA 20: Indicates a bullish market where the long-term trend (SMA 200) is above the medium-term (SMA 50), and the medium-term trend is above the short-term (SMA 20).
Closing price below all three SMAs: Confirms that the price is in a favorable position for a potential upward reversal.
Sell Conditions:
SMA 20 > SMA 50 > SMA 200: This setup indicates a bearish trend.
Closing price above all three SMAs: Confirms that the price is in a favorable position for a potential downward movement.
Second Buy Signal (B2): If the price falls more than 10% after the first buy signal, the strategy triggers a second buy opportunity (B2) at a potentially better price. This helps traders take advantage of pullbacks or corrections after an initial favorable entry.
Labeling System:
B1-Price: The first buy signal label, appearing when the market is bullish and the closing price is below all three SMAs.
B2-Price: The second buy signal label, triggered if the price falls more than 10% after the initial buy signal.
S-Price: The sell signal label, appearing when the market turns bearish and the closing price is above all three SMAs.
How to Use:
Add the Indicator: Add "3_SMA_Strategy_V-Singhal by Parthib" to your chart on TradingView.
Interpret Buy Signals (B1): Look for green labels with the text "B1-Price" when the closing price (CP) is below all three SMAs and the trend is bullish.
Interpret Second Buy Signals (B2): If the price falls more than 10% after the first buy, look for blue labels with "B2-Price" and a re-entry opportunity.
Interpret Sell Signals (S): Look for red labels with the text "S-Price" when the market turns bearish, and the closing price (CP) is above all three SMAs.
Conclusion:
The 3_SMA_Strategy_V-Singhal by Parthib is an efficient and simple trend-following tool for traders looking to make informed buy and sell decisions. By combining the power of three SMAs and the closing price (CP) confirmation, this strategy helps traders to buy when the market shows a strong bullish setup and sell when the trend turns bearish. Additionally, the second buy signal feature ensures that traders don’t miss out on re-entry opportunities after price corrections, giving them a chance to re-enter the market at a favorable price.
RSI and Bollinger Bands Screener [deepakks444]Indicator Overview
The indicator is designed to help traders identify potential long signals by combining the Relative Strength Index (RSI) and Bollinger Bands across multiple timeframes. This combination allows traders to leverage the strengths of both indicators to make more informed trading decisions.
Understanding RSI
What is RSI?
The Relative Strength Index (RSI) is a momentum oscillator that measures the speed and change of price movements. Developed by J. Welles Wilder Jr. for stocks and forex trading, the RSI is primarily used to identify overbought or oversold conditions in an asset.
How RSI Works:
Calculation: The RSI is calculated using the average gains and losses over a specified period, typically 14 periods.
Range: The RSI oscillates between 0 and 100.
Interpretation:
Key Features of RSI:
Momentum Indicator: RSI helps identify the momentum of price movements.
Divergences: RSI can show divergences, where the price makes a higher high, but the RSI makes a lower high, indicating potential reversals.
Trend Identification: RSI can also help identify trends. In an uptrend, the RSI tends to stay above 50, and in a downtrend, it tends to stay below 50.
Understanding Bollinger Bands
What is Bollinger Bands?
Bollinger Bands are a type of trading band or envelope plotted two standard deviations (positively and negatively) away from a simple moving average (SMA) of a price. Developed by financial analyst John Bollinger, Bollinger Bands consist of three lines:
Upper Band: SMA + (Standard Deviation × Multiplier)
Middle Band (Basis): SMA
Lower Band: SMA - (Standard Deviation × Multiplier)
How Bollinger Bands Work:
Volatility Measure: Bollinger Bands measure the volatility of the market. When the bands are wide, it indicates high volatility, and when the bands are narrow, it indicates low volatility.
Price Movement: The price tends to revert to the mean (middle band) after touching the upper or lower bands.
Support and Resistance: The upper and lower bands can act as dynamic support and resistance levels.
Key Features of Bollinger Bands:
Volatility Indicator: Bollinger Bands help traders understand the volatility of the market.
Mean Reversion: Prices tend to revert to the mean (middle band) after touching the bands.
Squeeze: A Bollinger Band Squeeze occurs when the bands narrow significantly, indicating low volatility and a potential breakout.
Combining RSI and Bollinger Bands
Strategy Overview:
The strategy aims to identify potential long signals by combining RSI and Bollinger Bands across multiple timeframes. The key conditions are:
RSI Crossing Above 60: The RSI should cross above 60 on the 15-minute timeframe.
RSI Above 60 on Higher Timeframes: The RSI should already be above 60 on the hourly and daily timeframes.
Price Above 20MA or Walking on Upper Bollinger Band: The price should be above the 20-period moving average of the Bollinger Bands or walking on the upper Bollinger Band.
Strategy Details:
RSI Calculation:
Calculate the RSI for the 15-minute, 1-hour, and 1-day timeframes.
Check if the RSI crosses above 60 on the 15-minute timeframe.
Ensure the RSI is above 60 on the 1-hour and 1-day timeframes.
Bollinger Bands Calculation:
Calculate the Bollinger Bands using a 20-period moving average and 2 standard deviations.
Check if the price is above the 20-period moving average or walking on the upper Bollinger Band.
Entry and Exit Signals:
Long Signal: When all the above conditions are met, consider a long entry.
Exit: Exit the trade when the price crosses below the 20-period moving average or the stop-loss is hit.
Example Usage
Setup:
Add the indicator to your TradingView chart.
Configure the inputs as per your requirements.
Monitoring:
Look for the long signal on the chart.
Ensure that the RSI is above 60 on the 15-minute, 1-hour, and 1-day timeframes.
Check that the price is above the 20-period moving average or walking on the upper Bollinger Band.
Trading:
Enter a long position when the criteria are met.
Set a stop-loss below the low of the recent 15-minute candle or based on your risk management rules.
Monitor the trade and exit when the RSI returns below 60 on any of the timeframes or when the price crosses below the 20-period moving average.
House Rules Compliance
No Financial Advice: This strategy is for educational purposes only and should not be construed as financial advice.
Risk Management: Always use proper risk management techniques, including stop-loss orders and position sizing.
Past Performance: Past performance is not indicative of future results. Always conduct your own research and analysis.
TradingView Guidelines: Ensure that any shared scripts or strategies comply with TradingView's terms of service and community guidelines.
Conclusion
This strategy combines RSI and Bollinger Bands across multiple timeframes to identify potential long signals. By ensuring that the RSI is above 60 on higher timeframes and that the price is above the 20-period moving average or walking on the upper Bollinger Band, traders can make more informed decisions. Always remember to conduct thorough research and use proper risk management techniques.
simple swing indicator-KTRNSE:NIFTY
1. Pivot High/Low as Lines:
Purpose: Identifies local peaks (pivot highs) and troughs (pivot lows) in price and draws horizontal lines at these levels.
How it Works:
A pivot high occurs when the price is higher than the surrounding bars (based on the pivotLength parameter).
A pivot low occurs when the price is lower than the surrounding bars.
These pivots are drawn as horizontal lines at the price level of the pivot.
Visualization:
Pivot High: A red horizontal line is drawn at the price level of the pivot high.
Pivot Low: A green horizontal line is drawn at the price level of the pivot low.
Example:
Imagine the price is trending up, and at some point, it forms a peak. The script identifies this peak as a pivot high and draws a red line at the price of that peak. Similarly, if the price forms a trough, the script will draw a green line at the low point.
2. Moving Averages (20-day and 50-day):
Purpose: Plots the 20-day and 50-day simple moving averages (SMA) on the chart.
How it Works:
The 20-day SMA smooths the closing price over the last 20 days.
The 50-day SMA smooths the closing price over the last 50 days.
These lines provide an overview of short-term and long-term price trends.
Visualization:
20-day SMA: A blue line showing the 20-day moving average.
50-day SMA: An orange line showing the 50-day moving average.
Example:
When the price is above both moving averages, it indicates an uptrend. If the price crosses below these averages, it might signal a downtrend.
3. Supertrend:
Purpose: The Supertrend is an indicator based on the Average True Range (ATR) and is used to track the market trend.
How it Works:
When the market is in an uptrend, the Supertrend line will be green.
When the market is in a downtrend, the Supertrend line will be red.
Visualization:
Uptrend: The Supertrend line will be plotted in green.
Downtrend: The Supertrend line will be plotted in red.
Example:
If the price is above the Supertrend, the market is considered to be in an uptrend, and if the price is below the Supertrend, the market is in a downtrend.
4. Momentum (Rate of Change):
Purpose: Measures the rate at which the price changes over a set period, showing if the momentum is positive or negative.
How it Works:
The Rate of Change (ROC) measures how much the price has changed over a certain number of periods (e.g., 14).
Positive ROC indicates upward momentum, and negative ROC indicates downward momentum.
Visualization:
Positive ROC: A purple line is plotted above the zero line.
Negative ROC: A purple line is plotted below the zero line.
Example:
If the ROC line is above zero, it means the price is increasing, suggesting bullish momentum. If the ROC is below zero, it indicates bearish momentum.
5. Volume:
Purpose: Displays the volume of traded assets, giving insight into the strength of price movements.
How it Works:
The script will color the volume bars based on whether the price closed higher or lower than the previous bar.
Green bars indicate bullish volume (closing price higher than the previous bar), and red bars indicate bearish volume (closing price lower than the previous bar).
Visualization:
Bullish Volume: Green volume bars when the price closes higher.
Bearish Volume: Red volume bars when the price closes lower.
Example:
If you see a green volume bar, it suggests that the market is participating in an uptrend, and the price has closed higher than the previous period. Red bars indicate a downtrend or selling pressure.
6. MACD (Moving Average Convergence Divergence):
Purpose: The MACD is a trend-following momentum indicator that shows the relationship between two moving averages of the price.
How it Works:
The MACD Line is the difference between the 12-period EMA (Exponential Moving Average) and the 26-period EMA.
The Signal Line is the 9-period EMA of the MACD Line.
The MACD Histogram shows the difference between the MACD line and the Signal line.
Visualization:
MACD Line: A blue line representing the difference between the 12-period and 26-period EMAs.
Signal Line: An orange line representing the 9-period EMA of the MACD line.
MACD Histogram: A red or green histogram that shows the difference between the MACD line and the Signal line.
Example:
When the MACD line crosses above the Signal line, it’s considered a bullish signal. When the MACD line crosses below the Signal line, it’s considered a bearish signal.
Full Chart Example:
Imagine you're looking at a price chart with all the indicators:
Pivot High/Low Lines are drawn as red and green horizontal lines.
20-day and 50-day SMAs are plotted as blue and orange lines, respectively.
Supertrend shows a green or red line indicating the trend.
Momentum (ROC) is shown as a purple line oscillating around zero.
Volume bars are green or red based on whether the close is higher or lower.
MACD appears as a blue line and orange line, with a red or green histogram showing the MACD vs. Signal line difference.
How the Indicators Work Together:
Trend Confirmation: If the price is above the Supertrend line and both SMAs are trending up, it indicates a strong bullish trend.
Momentum: If the ROC is positive and the MACD line is above the Signal line, it further confirms bullish momentum.
Volume: Increasing volume, especially with green bars, suggests that the trend is being supported by active participation.
By using these combined indicators, you can get a comprehensive view of the market's trend, momentum, and potential reversal points (via pivot highs and lows).
Volume HighlightVolume Highlight
Description:
This script helps users analyze trading volume by:
1. Highlighting the highest volume bars:
• Trading sessions with volume equal to or exceeding the highest value over the last 20 periods are displayed in purple.
• Other sessions are displayed in light gray.
2. Displaying the 20-period SMA (Simple Moving Average):
• A 20-period SMA line of the volume is included to track the general trend of trading volume.
Key Features:
• Color-coded Highlights:
• Quickly identify trading sessions with significant volume spikes.
• 20-Period SMA Line:
• Observe the overall trend of trading volume.
• Intuitive Volume Bars:
• Volume bars are clearly displayed for easy interpretation.
How to Use:
1. Add the script to your chart on TradingView.
2. Look at the color of the volume bars:
• Purple: Sessions with the highest trading volume in the past 20 periods.
• Light gray: Other sessions.
3. Use the 20-period SMA line to analyze volume trends.
Purpose:
• Analyze market momentum through trading volume.
• Support trading decisions by identifying significant volume spikes.
Illustration:
• A chart showing color-coded volume bars and the 20-period SMA line.
Options Series - Explode BB⭐ Bullish Zone:
⭐ Bearish Zone:
⭐ Neutral Zone:
The provided script integrates Bollinger Bands with different lengths (20 and 200 periods) and applies customized candle coloring based on certain conditions. Here's a breakdown of its importance and insights:
⭐ 1. Dual Bollinger Bands (BBs):
Bollinger Bands (BB) with 20-period length:
This is the standard setting for Bollinger Bands, with a 20-period simple moving average (SMA) as the central line and upper/lower bands derived from the standard deviation.
These bands are used to identify volatility. Wider bands indicate higher volatility, while narrower bands indicate low volatility.
200-period BB:
This is a longer-term indicator providing insight into the overall trend and long-term volatility.
The 200-period bands filter out noise and offer a "macro" view of price movements compared to the 20-period bands, which focus on short-term price actions.
⭐ 2. Overlay of Bollinger Bands and SMA:
The script plots the Bollinger Bands along with the SMA (Simple Moving Average) of the 200-period BB. This gives traders both a short-term (20-period) and long-term (200-period) perspective, which is valuable for detecting major trend shifts or key support and resistance zones.
Using multiple time frames (20-period for short-term and 200-period for long-term) can help traders spot both immediate opportunities and overarching trends.
⭐ 3. Candle Coloring Based on Key Conditions:
Bullish Signal (GreenFluroscent): When the price closes above the upper 200-period Bollinger Band, the candle turns green, indicating a potential bullish breakout.
Bearish Signal (RedFluroscent): If the price closes below the lower 200-period Bollinger Band, the candle turns red, suggesting a bearish breakout.
Neutral or Uncertain Market: Candles are gray when the price remains between the upper and lower bands, indicating a lack of a strong directional bias.
This color-coded visualization allows traders to quickly assess market sentiment based on the Bollinger Bands' extremes.
⭐ 4. Strategic Importance of the Setup:
Multi-timeframe Analysis: Combining short-term (20-period) and long-term (200-period) Bollinger Bands enables traders to assess the market's overall volatility and trend strength. The longer-term bands act as a reference for broader trend direction, while the shorter-term bands can signal shorter-term pullbacks or entry/exit points.
Breakout Identification: By color-coding the candles when prices cross either the upper or lower 200-period bands, the script makes it easier to spot potential breakouts. This can be particularly helpful in trading strategies that rely on volatility expansions or trend-following tactics.
⭐ 5. Customization and Flexibility:
Custom Colors: The script uses distinct fluorescent green and red colors to highlight key bullish and bearish conditions, providing clear visual cues.
Simplicity with Flexibility: Despite its simplicity, the script leaves room for customization, allowing traders to adjust the Bollinger Band multipliers or apply different conditions to candle coloring for more nuanced setups.
This script enhances standard Bollinger Band usage by introducing multi-timeframe analysis, breakout signals, and visual cues for trend strength, making it a powerful tool for both trend-following and mean-reversion strategies.
🚀 Conclusion:
This script effectively simplifies volatility analysis by visually marking bullish, bearish, and neutral zones, making it a robust tool for identifying trade opportunities across multiple timeframes. Its dual-band approach ensures both trend-following and mean-reversion strategies are supported.
VWAP and MA Crossover SignalsDescription: The VWAP and 20 MA Crossover Indicator is a powerful trading tool designed to capitalize on trend reversals and momentum shifts. This indicator overlays two key technical analysis tools on the price chart: the Volume Weighted Average Price (VWAP) and the 20-period Moving Average (MA).
Functionality:
VWAP: Represents the average price a security has traded at throughout the day, based on volume and price. It is a measure of the market's trend and trading volume.
20 MA: Offers a smoothed average of the closing prices over the last 20 periods, providing a glimpse of the underlying trend.
Signals:
Buy Signal: Generated when the VWAP crosses above the 20-period MA, suggesting an upward momentum and a potential bullish trend reversal.
Sell Signal: This occurs when the VWAP crosses below the 20-period MA, indicating a downward momentum and a potential bearish trend reversal.
Usage: This indicator is ideal for traders focusing on intraday and swing trading strategies, providing clear visual cues for entry and exit points based on the interaction between VWAP and the 20 MA. By identifying key crossover points, traders can make informed decisions about potential bullish or bearish movements in the market.
Application: To use this indicator, simply add it to your TradingView chart setup. The buy and sell signals will be displayed directly on the chart, allowing for easy interpretation and quick action. Adjust the settings to fit your specific trading strategy or market conditions.
Uptrick: EMA Trend Indicator
### Overview
The goal of this script is to visually indicate on a trading chart whether all three Exponential Moving Averages (EMAs) are trending upwards (i.e., their slopes are positive). If all EMAs are trending upwards, the script will color the bars green. If not, the bars will be colored red.
### Key Concepts
1. **Exponential Moving Average (EMA)**: An EMA is a type of moving average that places more weight on recent data, making it more responsive to price changes compared to a simple moving average (SMA). In this script, we use three different EMAs with different lengths (20, 50, and 200 periods).
2. **Slope of an EMA**: The slope of an EMA refers to the direction in which the EMA is moving. If the current value of the EMA is higher than its value in the previous bar, the slope is positive (upward). Conversely, if the current value is lower than its previous value, the slope is negative (downward).
3. **Bar Color Coding**: The script changes the color of the bars on the chart to provide a visual cue:
- **Green Bars**: Indicate that all three EMAs are trending upwards.
- **Red Bars**: Indicate that one or more EMAs are not trending upwards.
### Detailed Breakdown
#### 1. Input Fields
- **EMA Lengths**: The script starts by allowing the user to input the lengths for the three EMAs. These lengths determine how many periods (e.g., days) are used to calculate each EMA.
- `ema20_length` is set to 20, meaning the first EMA uses the last 20 bars of data.
- `ema50_length` is set to 50, meaning the second EMA uses the last 50 bars of data.
- `ema200_length` is set to 200, meaning the third EMA uses the last 200 bars of data.
#### 2. EMA Calculation
- The script calculates the values of the three EMAs:
- **EMA 20**: This is calculated using the last 20 bars of closing prices.
- **EMA 50**: This is calculated using the last 50 bars of closing prices.
- **EMA 200**: This is calculated using the last 200 bars of closing prices.
These calculations result in three values for each bar on the chart, each representing the EMA value at that point in time.
#### 3. Determining EMA Slopes
- **EMA Slopes**: To understand the trend of each EMA, the script compares the current value of each EMA to its value in the previous bar:
- For the 20-period EMA, the script checks if today’s EMA value is higher than yesterday’s EMA value.
- This process is repeated for the 50-period and 200-period EMAs.
- If today’s EMA value is greater than yesterday’s value, the slope is positive (upward).
- If today’s EMA value is not greater (it is either equal to or less than yesterday’s value), the slope is not positive.
#### 4. Evaluating All Slopes
- **All Slopes Positive Condition**: The script combines the results of the individual slope checks into a single condition. It uses a logical "AND" operation:
- The condition will be `true` only if all three EMAs (20, 50, and 200) have positive slopes.
- If any one of the EMAs does not have a positive slope, the condition will be `false`.
#### 5. Coloring the Bars
- **Bar Coloring Logic**: Based on the above condition, the script decides the color of each bar on the chart:
- If all slopes are positive (condition is `true`), the bar is colored green.
- If any slope is not positive (condition is `false`), the bar is colored red.
- **Visual Cue**: This provides a quick, visual indication to traders:
- Green bars suggest that the market is in an upward trend across all three EMAs, which might indicate a strong bullish trend.
- Red bars suggest that the trend is not uniformly upward, which could be a sign of weakening momentum or a potential reversal.
#### 6. Alerts
- **Alert Conditions**: The script also allows for alert conditions to be set based on the slope analysis:
- An alert can be triggered when all EMA slopes are positive. This might be useful for traders who want to be notified when the market shows strong upward momentum.
### Summary
- The script essentially takes the market data and applies three different EMAs to it, each with a different time frame.
- It then checks the direction (slope) of each of these EMAs to determine if they are all trending upwards.
- If they are, the script colors the bar green, signaling a potentially strong bullish trend.
- If any of the EMAs is not trending upwards, it colors the bar red, indicating a potential issue with the strength of the trend.
This approach helps traders quickly assess market conditions based on multiple EMAs, providing a clearer picture of the overall trend across different time frames.
Trading Made Easy ATR BandsAs always, this is not financial advice and use at your own risk. Trading is risky and can cost you significant sums of money if you are not careful. Make sure you always have a proper entry and exit plan that includes defining your risk before you enter a trade.
Background:
This is my take on two relatively famous indicators that paint the colour of your candles in order to help identify trend direction and smooth out market noise. The Elder Impulse System was designed by Dr . Alexander Elder in his book Come Into My Trading Room and attempts to identify the change of trends and when these trends speed up and slow down (school.stockcharts.com). The system used a 13 period EMA and a MACD histogram, and compared each of these indicators to the previous period. In short, when both the histogram and the EMA were rising, the trend was accelerating to the upside and when both were falling, accelerating to the downside. Conversely, when the indicators were not in alignment, say the MACD falling but the EMA rising, it signaled a slowing down of momentum. The downside of this indicator is that it be can rather jumpy, focusing on a short period EMA for 50% of its calculation, leaving a trader to potentially sit on the sidelines during opportune pull backs to enter winning positions, or exit early when there is still a lot of gas left in the tank.
A similar concept has been employed by John Carter and his organization, SimplerTrading, with the 10X bars indicator. However, here they use the famous Directional Movement Index (DMI) created by J. Welles Wilder as the basis for their bars (www.simplertrading.com). John Carter states that the use of this indicator can lead to getting in earlier on more, bigger, and faster setups. The downside of this indicator is the reliance on the ADX calculations to keep you out of rangebound trades. Anyone who is familiar with the DMI system understands it has unparalleled ability to identify longer term trends, but it is also quite slow, leaving the trader to miss a good portion of the initial runup due to this ADX portion that is very slow to get moving and also slow to signal exits.
In short, both of these systems are designed with one thing in mind: keeping the trader on the right side of the move --- but both suffer from the same issue but on opposite sides of the spectrum. One is too fast and the other is too slow. Ultimately, leaving profits on the table for the trader when such a situation could be avoided.
Here I present my own take on these and have made the “Trading Made Easy ATR Bands”. I name it this because trading is much easier when you trade with the prevailing trend, and this system identifies these periods quite effectively while doing a better job of handling the speed flux of most markets. The base formula uses the DMI as its main calculation and the relationship between the DMI+ and DMI- lines, respectively, like the 10X bars. While the trader can investigate these on their own to understand these more intimately, essentially the DMI+ and DMI- lines are calculating the highs and lows respectively of each bar compared to a period in the past and smoothed with the true range, a measurement of volatility . What this ultimately presents is a picture of uptrends and downtrends, where price is making consistently more highs or more lows over a period of time. Where I have modified this relative to the 10X bars is I have ignored the ADX calculations. Further, values over 25 have been discussed as “strong” momentum, in my calculations, I have sped this up to 20 to get a trader into the move earlier. Second, I have added an additional calculation based around the 21-period exponential moving average calculated against its previous output. This then, like the Elder Impulse System, has two forms of market momentum as its calculation to smooth out noise, but has the benefit of being less jumpy, like the original 10X bar system. I have added a series of exponential moving averages following the Fibonacci sequence from 8-144 as a system of dynamic support and resistance showing the sentiment of both the shorter and longer term market participants. Last, I have added a series of Keltner Channels , from 1X-4X, that encompass the 21 period EMA as a base line. The 21 EMA is a stable in all of John Carter’s work and I do believe he is correct that the market is mostly structured around this line, since it roughly approximates one month of trading data. It is not uncommon to see price expand and contract back to this line over and over again.
Trade Signals:
Strong Bullish Momentum – The system will generate a green bar when the DMI+ line is over the DMI- line, the DMI+ line is equal or greater than 20 and the 21 EMA has increased relative to its last close.
Weak Bullish Momentum – The system will generate a blue bar in several scenarios. First, when the DMI+ line is over the DMI- line but the DMI+ line is not over 20 and the EMA is equal or less than the previous close. It will also print a blue bar if either the DMI or the EMA are not aligned, such as the DMI+ is over the DMI- but not over 20 but the EMA has risen compared to the last bar. Last, it will also print a blue bar if the DMI- is over the DMI+ but the EMA is rising.
Strong Bearish Momentum – The system will generate a red bar when the DMI- line is over the DMI+ line, the DMI- line is equal or greater than 20, and the 21 EMA has fallen relative to its last close.
Weak Bearish Momentum – The system will generate an orange bar in several scenarios. First when the DMI- line is over the DMI+ line but the DMI- line is not over 20 and the EMA is equal or greater than the last bar. It will also print an orange bar if either the DMI or the EMA are not aligned, such as the DMI- is over the DMI+ but not over 20 but the EMA has fallen. Lastly, it will also print an orange bar if the DMI+ line is over the DMI- and the EMA has fallen relative to the last bar.
Uses:
1) Like the Elder Impulse System and 10X Bar systems, these should be used as trade filters only.. It is in the trader’s best interest to trade with the trends and these bars identify these periods but may not always generate the most opportune time to enter a market. For instance, trying to short a market when the market is in a phase of Strong Bullish Momentum would not be wise, and vice versa with trying to open long positions when the market is exhibiting Strong Bearish Momentum. Use multiple forms of evidence to confirm the signals shown before entering any trade and to not take these signals on their without confluence of ideas. A viable system could use the Elder Triple Screen System (for reference, see this decent write up --- www.dailyforex.com) with the Trading Made Easy Bands as your “Tide” or longer term filter, and a further trading plan to establish an entry on a short time frame pull back.
2) Interim Trend Exhaustion – Keltner channels work as moving standard deviations from the 21 EMA . 3X multipliers will encompass 99.7% of price and 4X will encompass 99.9% of price away from the 21 EMA . During a trend it would be a good idea to lock in partial profits when price reaches these outer extrema as it is very highly probable that a retracement back to the mean is approaching. While not part of the system, and not recommended to be used by this system, a mean reversion trader could in theory look for reversals at these extrema points and trade a mean reversion strategy back to the 21EMA, but is a much riskier trade with lower probability of success. A trend trader should look to enter trades when a signal is given within the 1ATR or 2ATR zone as this is when price has not really started accelerating yet and is likely to see continued momentum in that direction.
FARAZ.MATI20vA personal indicator.
This indicator has the following features :
Thanks to the managers and administrators of TradingView site for the appropriate space with wide facilities for optimal use. All (indicators) were available on the site and I only defined certain settings for them.
FARAZ.MATI20v
EMA: 5
SMA : 20
SMA : 50
Collision and interruption of Moving 20 by Moving 5 can be the beginning of an upward trend. Provided that the Moving 5 is placed under the candles. (The best signal for the Moving 5 is to collide with the Moving 20 under the candles). Also, the collision of the Moing 5 with the Moing 20 on top of the candles can be a sign of falling. Especially if this collision occurs above the candles.The cut of the Moving 20 and the Moving 50 indicate the intensity of the wave. If Moving 20 is above Moving 50 in this collision, it shows the intensity of the uptrend and if it is below Moving 50, it shows the intensity of the downtrend.
SMA : 100
SMA : 200
Both (resistance and support) are very strong, which is very effective in larger timeframes (such as 1 day).
HMA : 20
To determine the entry point. In such a way that whenever the seeds (HMA) are below the candlesticks. 3 seeds are in ascending position. The body of the candle and the shadow should not touch them. It can be a good signal to enter. Also if the seeds are placed on top of the candlesticks. Show the descending direction of 3 seeds. Provided that the body of the candle and the shadow have not hit them. It is a signal for the short position.
SAR : With the applied settings, it is a kind (trending view) that can evaluate the volume of input to any currency much sooner and determine the probability of rising or falling. If our wave lines (stairs) are at the bottom of the candles, it means an upward trend, and if they are at the top of the candles, it means a downward trend. As the volume of inputs increases, the trend increases, and as the volume of inputs decreases, the trend will also decrease.
Ichimoku Cloud : To determine the lines (support and resistance) the peaks formed by the cloud can represent a resistance area. Price To cross the area marked by the Ichimoku cloud must have a strong candle. This can be very effective in determining the point of entry and purchase.
zig zag : For better diagnosis of the process. Using it to determine areas of support and resistance can be useful. Determining the points of the Fibonacci table is also very effective.
SNL Popular Moving Averages MTFSNL△ Popular Moving Averages MTF
Short title: PopMAs
These are popular moving averages used by various traders and they are multi-timeframe, i.e. you can see
the 200 day SMA on a 15 minute chart.
Four moving averages are also included for the current timeframe (20, 50, 100 and 200 EMA).
Not all moving averages are enabled by default. You can turn individual moving averges on or off in the
"Style" tab of the indicator's settings.
The way I see moving averages is that they do not represent a magic mathematical truth, but are simply the
result of many people agreeing on the same parameters. I guess the origin were five working days in a week
and therefore a month would be four times five, i.e. a 20 day SMA. 200 days are probably an estimate of
the work days in a year and the 50 day SMA represents a quarter year.
There are many indicators on TradingView that offer various adjustable moving averages, including
combinations and multi-timeframe. But my interest was to have an indicator with the most popular moving
averages and it should be multi-timeframe capable. By design I did not want to make the periods adjustable,
but you could add this easily if you like.
Here are some examples of poplular moving averages:
20 unit EMA : support on 4h BTC chart, Carl the Moon
20, 50, 100, 200 day SMA : classic trading all charts, Benjamin Cowen, Tone Vays
20, 50, 100, 200 week SMA: Benjamin Cowen
21 week EMA: well known BTC support, Benjamin Cowen
800 hour EMA: Traders Reality -> not possible in TradingView, represented as 33 day EMA
Known problems:
- I have not found a way to turn off floating labels according to a plot's state chosen in the "Style"
tab. So you will still see the label floating around even if you have turned off the moving average's
line. But you can always turn of all the floating labels in the settings.
- I have observed unexpected differences on multi-timeframe values: For example, looking at the true 20
week SMA on a weekly BTC chart showed a present time value of 43821 USD, but the value was 43908 USD
for the result of this call used in this script: security(syminfo.tickerid, "W", sma(close, 20))
The difference went away when switching my chart to weekly and back to 15 minutes.
Please comment if you know of other moving averages that are often and successfully used or if you find
that one of the included moving averages is irrelevant and should be removed from this script.
And I would very much appreciate any input regarding the mentioned known problems.
MrMi 3 in 1 MAThis 3 in 1 moving average script can help all of you to save your indicator use especially for free user. this script icluded 20 MA, 50 MA, and 200 MA which is important to all trader. I hope this script can assist all of you to maximize the important indicators in your trading plan.
Skrip purata bergerak 3 dalam 1 ini dapat membantu anda semua untuk menjimatkan penggunaan penunjuk anda terutama untuk pengguna percuma. skrip ini merangkumi 20 MA, 50 MA, dan 200 MA yang penting bagi semua peniaga. Saya harap skrip ini dapat membantu anda semua untuk memaksimumkan petunjuk penting dalam rancangan perdagangan anda.
يمكن أن يساعدك هذا البرنامج النصي 3 في 1 في المتوسط المتحرك جميعًا على حفظ استخدام المؤشر الخاص بك بشكل خاص للمستخدم المجاني. يتضمن هذا البرنامج النصي 20 MA و 50 MA و 200 MA وهو أمر مهم لجميع المتداولين. آمل أن يساعدك هذا البرنامج النصي جميعًا على تعظيم المؤشرات المهمة في خطة التداول الخاصة بك.
这种三合一移动平均值脚本可以帮助所有人节省指标使用量，尤其是对于免费用户而言。该脚本包括20 MA，50 MA和200 MA，这对所有交易者都很重要。我希望该脚本可以帮助大家最大化您的交易计划中的重要指标。
यह 3 इन 1 मूविंग एवरेज स्क्रिप्ट विशेष रूप से मुफ्त उपयोगकर्ता के लिए आपके संकेतक उपयोग को बचाने में आप सभी की मदद कर सकती है। इस स्क्रिप्ट में 20 एमए, 50 एमए और 200 एमए शामिल हैं जो सभी व्यापारी के लिए महत्वपूर्ण है। मुझे उम्मीद है कि यह स्क्रिप्ट आपकी ट्रेडिंग योजना में महत्वपूर्ण संकेतकों को अधिकतम करने के लिए आप सभी की सहायता कर सकती है।
이 3 in 1 이동 평균 스크립트는 특히 무료 사용자를 위해 지표 사용을 절약하는 데 도움이 될 수 있습니다. 이 스크립트에는 모든 상인에게 중요한 20 MA, 50 MA 및 200 MA가 포함되었습니다. 이 스크립트가 거래 계획의 중요한 지표를 극대화하는 데 도움이되기를 바랍니다.
この3in 1移動平均スクリプトは、特に無料ユーザーの場合、インジケーターの使用を節約するのに役立ちます。このスクリプトには、すべてのトレーダーにとって重要な20 MA、50 MA、および200MAが含まれていました。このスクリプトが、取引計画の重要な指標を最大化するのに役立つことを願っています。
VWAP forex Yesterday Hi/Low update fix This script is an updte fix of an earlier script that stopped functioning when TradingView updated Pine script. This script plots Forex (24 hour session) VWAP, yesterday's high, low, open and close (HLOC),
the day before's HLOC -
Also plots higher timeframe 20 emas
1 minute 5, 15, 60 period 20 ema
5 minute 15, 60 period 20 ema
15 minute 60, 120 , 240 period 20 ema
60 minute 120, 240 period 20 ema
120 minute 240, D period 20 ema
240 minute D period 20 ema
Also signals inside bars (high is less than or equal to the previous bar's high and the low is greater than or equal to the previous low) the : true inside bars have a maroon triangle below the bar as well as a ">" above the bar.
If subsequest bars are inside the last bar before the last true inside bar they also are marked with an ">"
This is probably a slight variation from the way Leaf_West plots the inside bars.
It appears that he marks all bars that are inside the original bar until one a bar has a high or low
outside the original bar. But I would need to see an example on his charts.
The Time Session Glitch and the Fix FX_IDC, COINBASE and BITSTAMP:
The script will correctly default to 1700 hrs to 1700hrs EDT/EST session for FXCM.
Strangely some securities appear to erroneously start their session at 1200 hrs ie. My guess is that they are somehow tied to GMT+0 instead of New York time (GMT+5). See this for yourself by selecting EURUSD using the FXCM exchange (FX:EURUSD) and then EURUSD from the IDC exchange (FX_IDC:EURUSD). The FX-IDC session opening range starts 5 hours before it actually should at 1700 hrs EDT/EST. To correct for this I have implemented an automatic fix (default) and a user selected "5 hour time shift adjust. ment needed on some securities".
There is also a 4 hour time shift button which might be necessary when New York reverts from Eastern Standard Time to Eastern Daylight Time (1 hour difference) in March (and then back again in November). In the default auto adjust mode you will need to select the 1 hour time shift. That is if this glitch still exists at that time.
I have looked at other scripts, other than my own and where the script is available, that need to use information about the opening bar and all have the same time shift issue
COINBASE and BITSTAMP open at 0000 hours GMT. Since I use lines instead of circles or crosses I had to make a small adjustment to plot the lines correctly.
If it needs work let me know.
Jayy
VWAP forex Yesterday Hi/Low switchThis script plots VWAP, yesterday's high, low, open and close (HLOC), the day before's HLOC -
Also plots higher timeframe 20 emas including:
1 minute 5, 15, 60 period 20 ema
5 minute 15, 60 period 20 ema
15 minute 60, 120 , 240 period 20 ema
60 minute 120, 240 period 20 ema
120 minute 240, D period 20 ema
240 minute D period 20 ema
Also signals inside bars (high is less than or equal to the previous
bar's high and the low is greater than or equal to the previous low) the : true inside bars have a maroon triangle below the bar as well as a ">" above the bar.
If subsequent bars are inside the last bar before the last true inside bar they also are marked with an ">"
If you have suggestions let me know.
Jayy
Smart Money Precision Structure [BullByte]Smart Money Precision Structure
Advanced Market Structure Analysis Using Institutional Order Flow Concepts
---
OVERVIEW
Smart Money Precision Structure (SMPS) is a comprehensive market analysis indicator that combines six analytical frameworks to identify high-probability market structure patterns. The indicator uses multi-dimensional scoring algorithms to evaluate market conditions through institutional order flow concepts, providing traders with professional-grade market analysis.
---
PURPOSE AND ORIGINALITY
Why This Indicator Was Developed
• Addresses the gap between retail and institutional analysis methods
• Consolidates multiple analysis techniques that professionals use separately
• Automates complex market structure evaluation into actionable insights
• Eliminates the need for multiple indicators by providing comprehensive analysis
What Makes SMPS Original
• Six-Layer Confluence System - Unique combination of market regime, structure, volume flow, momentum, price action, and adaptive filtering
• Institutional Pattern Recognition - Identifies smart money accumulation and distribution patterns
• Adaptive Intelligence - Parameters automatically adjust based on detected market conditions
• Real-Time Market Scoring - Proprietary algorithm rates market quality from 0-100%
• Structure Break Detection - Advanced pivot analysis identifies trend reversals early
---
HOW IT WORKS - TECHNICAL METHODOLOGY
1. Market Regime Analysis Engine
The indicator evaluates five core market dimensions:
• Volatility Score - Measures current volatility against 50-period historical baseline
• Trend Score - Analyzes alignment between 8, 21, and 50-period EMAs
• Momentum Score - Combines RSI divergence with MACD signal alignment
• Structure Score - Evaluates pivot point formation clarity
• Efficiency Score - Calculates directional movement efficiency ratio
These scores combine to classify markets into five regimes:
• TRENDING - Strong directional movement with aligned indicators
• RANGING - Sideways movement with mixed directional signals
• VOLATILE - Elevated volatility with unpredictable price swings
• QUIET - Low volatility consolidation periods
• TRANSITIONAL - Market shifting between different regimes
2. Market Structure Analysis
Advanced pivot point analysis identifies:
• Higher Highs and Higher Lows for bullish structure
• Lower Highs and Lower Lows for bearish structure
• Structure breaks when established patterns fail
• Dynamic support and resistance from recent pivot points
• Key level proximity detection using ATR-based buffers
3. Volume Flow Decoding
Institutional activity detection through:
• Volume surge identification when volume exceeds 2x average
• Buy versus sell pressure analysis using price-volume correlation
• Flow strength measurement through directional volume consistency
• Divergence detection between volume and price movements
• Institutional threshold alerts when unusual volume patterns emerge
4. Multi-Period Momentum Synthesis
Weighted momentum calculation across four timeframes:
• 1-period momentum weighted at 40%
• 3-period momentum weighted at 30%
• 5-period momentum weighted at 20%
• 8-period momentum weighted at 10%
Result smoothed with 6-period EMA for noise reduction.
5. Price Action Quality Assessment
Each bar evaluated for:
• Range quality relative to 20-period average
• Body-to-range ratio for directional conviction
• Wick analysis for rejection pattern identification
• Pattern recognition including engulfing and hammer formations
• Sequential price movement analysis
6. Adaptive Parameter System
Parameters automatically adjust based on detected regime:
• Trending markets reduce sensitivity and confirmation requirements
• Volatile markets increase filtering and require additional confirmations
• Ranging markets maintain neutral settings
• Transitional markets use moderate adjustments
---
COMPLETE SETTINGS GUIDE
Section 1: Core Analysis Settings
Analysis Sensitivity (0.3-2.0)
• Default: 1.0
• Lower values require stronger price movements
• Higher values detect more subtle patterns
• Scalpers use 0.8-1.2, swing traders use 1.5-2.0
Noise Reduction Level (2-7)
• Default: 4
• Controls filtering of false patterns
• Higher values reduce pattern frequency
• Increase in volatile markets
Minimum Move % (0.05-0.50)
• Default: 0.15%
• Sets minimum price movement threshold
• Adjust based on instrument volatility
• Forex: 0.05-0.10%, Stocks: 0.15-0.25%, Crypto: 0.20-0.50%
High Confirmation Mode
• Default: True (Enabled)
• Requires all technical conditions to align
• Reduces frequency but increases reliability
• Disable for more aggressive pattern detection
Section 2: Market Regime Detection
Enable Regime Analysis
• Default: True (Enabled)
• Activates market environment evaluation
• Essential for adaptive features
• Keep enabled for best results
Regime Analysis Period (20-100)
• Default: 50 bars
• Determines regime calculation lookback
• Shorter for responsive, longer for stable
• Scalping: 20-30, Swing: 75-100
Minimum Market Clarity (0.2-0.8)
• Default: 0.4
• Quality threshold for pattern generation
• Higher values require clearer conditions
• Lower for more patterns, higher for quality
Adaptive Parameter Adjustment
• Default: True (Enabled)
• Enables automatic parameter optimization
• Adjusts based on market regime
• Highly recommended to keep enabled
Section 3: Market Structure Analysis
Enable Structure Validation
• Default: True (Enabled)
• Validates patterns against support/resistance
• Confirms trend structure alignment
• Essential for reliability
Structure Analysis Period (15-50)
• Default: 30 bars
• Period for structure pattern analysis
• Affects support/resistance calculation
• Match to your trading timeframe
Minimum Structure Alignment (0.3-0.8)
• Default: 0.5
• Required structure score for valid patterns
• Higher values need stronger structure
• Balance with desired frequency
Section 4: Analysis Configuration
Minimum Strength Level (3-5)
• Default: 4
• Minimum confirmations for pattern display
• 5 = Maximum reliability, 3 = More patterns
• Beginners should use 4-5
Required Technical Confirmations (4-6)
• Default: 5
• Number of aligned technical factors
• Higher = fewer but better patterns
• Works with High Confirmation Mode
Pattern Separation (3-20 bars)
• Default: 8 bars
• Minimum bars between patterns
• Prevents clustering and overtrading
• Increase for cleaner charts
Section 5: Technical Filters
Momentum Validation
• Default: True (Enabled)
• Requires momentum alignment
• Filters counter-trend patterns
• Essential for trend following
Volume Confluence Analysis
• Default: True (Enabled)
• Requires volume confirmation
• Identifies institutional participation
• Critical for reliability
Trend Direction Filter
• Default: True (Enabled)
• Only shows patterns with trend
• Reduces counter-trend signals
• Disable for reversal hunting
Section 6: Volume Flow Analysis
Institutional Activity Threshold (1.2-3.5)
• Default: 2.0
• Multiplier for unusual volume detection
• Lower finds more institutional activity
• Stock: 2.0-2.5, Forex: 1.5-2.0, Crypto: 2.5-3.5
Volume Surge Multiplier (1.8-4.5)
• Default: 2.5
• Defines significant volume increases
• Adjust per instrument characteristics
• Higher for stocks, lower for forex
Volume Flow Period (12-35)
• Default: 18 bars
• Smoothing for volume analysis
• Shorter = responsive, longer = smooth
• Match to timeframe used
Section 7: Analysis Frequency Control
Maximum Analysis Points Per Hour (1-5)
• Default: 3
• Limits pattern frequency
• Prevents overtrading
• Scalpers: 4-5, Swing traders: 1-2
Section 8: Target Level Configuration
Target Calculation Method
• Default: Market Adaptive
• Three modes available:
- Fixed: Uses set point distances
- Dynamic: ATR-based calculations
- Market Adaptive: Structure-based levels
Minimum Target/Risk Ratio (1.0-3.0)
• Default: 1.5
• Minimum acceptable reward vs risk
• Higher filters lower probability setups
• Professional standard: 1.5-2.0
Fixed Mode Settings:
• Fixed Target Distance: 50 points default
• Fixed Invalidation Distance: 30 points default
• Use for consistent instruments
Dynamic Mode Settings:
• Dynamic Target Multiplier: 1.8x ATR default
• Dynamic Invalidation Multiplier: 1.0x ATR default
• Adapts to volatility automatically
Market Adaptive Settings:
• Use Structure Levels: True (default)
• Structure Level Buffer: 0.1% default
• Places levels at actual support/resistance
Section 9: Visual Display Settings
Color Theme Options
• Professional (Teal/Red)
- Bullish: Teal (#26a69a)
- Bearish: Red (#ef5350)
- Neutral: Gray (#78909c)
- Best for: Traditional traders, clean appearance
• Dark (Neon Green/Pink)
- Bullish: Neon Green (#00ff88)
- Bearish: Hot Pink (#ff0044)
- Neutral: Dark Gray (#333333)
- Best for: Dark theme users, high contrast
• Light (Green/Red Classic)
- Bullish: Green (#4caf50)
- Bearish: Red (#f44336)
- Neutral: Light Gray (#9e9e9e)
- Best for: Light backgrounds, traditional colors
• Vibrant (Cyan/Magenta)
- Bullish: Cyan (#00ffff)
- Bearish: Magenta (#ff00ff)
- Neutral: Medium Gray (#888888)
- Best for: High visibility, modern appearance
Dashboard Position
• Options: Top Left, Top Right, Bottom Left, Bottom Right, Middle Left, Middle Right
• Default: Top Right
• Choose based on chart layout preference
Dashboard Size
• Full: Complete information display (desktop)
• Mobile: Compact view for small screens
• Default: Full
Analysis Display Style
• Arrows : Simple directional markers
• Labels : Detailed text information
• Zones : Colored areas showing pattern regions
• Default: Labels (most informative)
Display Options:
• Display Analysis Strength: Shows star rating
• Display Target Levels: Shows target/invalidation lines
• Display Market Regime: Shows regime in pattern labels
---
HOW TO USE SMPS - DETAILED GUIDE
Understanding the Dashboard
Top Row - Header
• SMPS Dashboard title
• VALUE column: Current readings
• STATUS column: Condition assessments
Market Regime Row
• Shows: TRENDING, RANGING, VOLATILE, QUIET, or TRANSITIONAL
• Color coding: Green = Favorable, Red = Caution
• Status: FAVORABLE or CAUTION trading conditions
Market Score Row
• Percentage from 0-100%
• Above 60% = Strong conditions
• 40-60% = Moderate conditions
• Below 40% = Weak conditions
Structure Row
• Direction: BULLISH, BEARISH, or NEUTRAL
• Status: INTACT or BREAK
• Orange BREAK indicates structure failure
Volume Flow Row
• Direction: BUYING or SELLING
• Intensity: STRONG or WEAK
• Color indicates dominant pressure
Momentum Row
• Numerical momentum value
• Positive = Upward pressure
• Negative = Downward pressure
Volume Status Row
• INST = Institutional activity detected
• HIGH = Above average volume
• NORM = Normal volume levels
Adaptive Mode Row
• ACTIVE = Parameters adjusting
• STATIC = Fixed parameters
• Shows required confirmations
Analysis Level Row
• Minimum strength level setting
• Pattern separation in bars
Market State Row
• Current analysis: BULLISH, BEARISH, NEUTRAL
• Shows analysis price level when active
T:R Ratio Row
• Current target to risk ratio
• GOOD = Meets minimum requirement
• LOW = Below minimum threshold
Strength Row
• BULL or BEAR dominance
• Numerical strength value 0-100
Price Row
• Current price
• Percentage change
Last Analysis Row
• Previous pattern direction
• Bars since last pattern
Reading Pattern Signals
Bullish Structure Pattern
• Upward triangle or "Bullish Structure" label
• Star rating shows strength (★★★★★ = strongest)
• Green line = potential target level
• Red dashed line = invalidation level
• Appears below price bars
Bearish Structure Pattern
• Downward triangle or "Bearish Structure" label
• Star rating indicates reliability
• Green line = potential target level
• Red dashed line = invalidation level
• Appears above price bars
Pattern Strength Interpretation
• ★★★★★ = 6 confirmations (exceptional)
• ★★★★☆ = 5 confirmations (strong)
• ★★★☆☆ = 4 confirmations (moderate)
• ★★☆☆☆ = 3 confirmations (minimum)
• Below minimum = filtered out
Visual Elements on Chart
Lines and Levels:
• Gray Line = 21 EMA trend reference
• Green Stepline = Dynamic support level
• Red Stepline = Dynamic resistance level
• Green Solid Line = Active target level
• Red Dashed Line = Active invalidation level
Pattern Markers:
• Triangles = Arrow display mode
• Text Labels = Label display mode
• Colored Boxes = Zone display mode
Target Completion Labels:
• "Target" = Price reached target level
• "Invalid" = Pattern invalidated by price
---
RECOMMENDED USAGE BY TIMEFRAME
1-Minute Charts (Scalping)
• Sensitivity: 0.8-1.2
• Noise Reduction: 3-4
• Pattern Separation: 3-5 bars
• High Confirmation: Optional
• Best for: Quick intraday moves
5-Minute Charts (Precision Intraday)
• Sensitivity: 1.0 (default)
• Noise Reduction: 4 (default)
• Pattern Separation: 8 bars
• High Confirmation: Enabled
• Best for: Day trading
15-Minute Charts (Short Swing)
• Sensitivity: 1.0-1.5
• Noise Reduction: 4-5
• Pattern Separation: 10-12 bars
• High Confirmation: Enabled
• Best for: Intraday swings
30-Minute to 1-Hour (Position Trading)
• Sensitivity: 1.5-2.0
• Noise Reduction: 5-7
• Pattern Separation: 15-20 bars
• Regime Period: 75-100
• Best for: Multi-day positions
Daily Charts (Swing Trading)
• Sensitivity: 1.8-2.0
• Noise Reduction: 6-7
• Pattern Separation: 20 bars
• All filters enabled
• Best for: Long-term analysis
---
MARKET-SPECIFIC SETTINGS
Forex Pairs
• Minimum Move: 0.05-0.10%
• Institutional Threshold: 1.5-2.0
• Volume Surge: 1.8-2.2
• Target Mode: Dynamic or Market Adaptive
Stock Indices (ES, NQ, YM)
• Minimum Move: 0.10-0.15%
• Institutional Threshold: 2.0-2.5
• Volume Surge: 2.5-3.0
• Target Mode: Market Adaptive
Individual Stocks
• Minimum Move: 0.15-0.25%
• Institutional Threshold: 2.0-2.5
• Volume Surge: 2.5-3.5
• Target Mode: Dynamic
Cryptocurrency
• Minimum Move: 0.20-0.50%
• Institutional Threshold: 2.5-3.5
• Volume Surge: 3.0-4.5
• Target Mode: Dynamic
• Increase noise reduction
---
PRACTICAL APPLICATION EXAMPLES
Example 1: Strong Trending Market
Dashboard Reading:
• Market Regime: TRENDING
• Market Score: 75%
• Structure: BULLISH, INTACT
• Volume Flow: BUYING, STRONG
• Momentum: +0.45
Interpretation:
• Strong uptrend environment
• Institutional buying present
• Look for bullish patterns as continuation
• Higher probability of success
• Consider using lower sensitivity
Example 2: Range-Bound Conditions
Dashboard Reading:
• Market Regime: RANGING
• Market Score: 35%
• Structure: NEUTRAL
• Volume Flow: SELLING, WEAK
• Momentum: -0.05
Interpretation:
• No clear direction
• Low opportunity environment
• Patterns are less reliable
• Consider waiting for regime change
• Or switch to a range-trading approach
Example 3: Structure Break Alert
Dashboard Reading:
• Previous: BULLISH structure
• Current: Structure BREAK
• Volume: INST flag active
• Momentum: Shifting negative
Interpretation:
• Trend reversal potentially beginning
• Institutional participation detected
• Watch for bearish pattern confirmation
• Adjust bias accordingly
• Increase caution on long positions
Example 4: Volatile Market
Dashboard Reading:
• Market Regime: VOLATILE
• Market Score: 45%
• Adaptive Mode: ACTIVE
• Confirmations: Increased to 6
Interpretation:
• Choppy conditions
• Parameters auto-adjusted
• Fewer but higher quality patterns
• Wider stops may be needed
• Consider reducing position size
Below are a few chart examples of the Smart Money Precision Structure (SMPS) indicator in action.
• Example 1 – Bullish Structure Detection on SOLUSD 5m
• Example 2 – Bearish Structure Detected with Strong Confluence on SOLUSD 5m
---
TROUBLESHOOTING GUIDE
No Patterns Appearing
Check these settings:
• High Confirmation Mode may be too restrictive
• Minimum Strength Level may be too high
• Market Clarity threshold may be too high
• Regime filter may be blocking patterns
• Try increasing sensitivity
Too Many Patterns
Adjust these settings:
• Enable High Confirmation Mode
• Increase Minimum Strength Level to 5
• Increase Pattern Separation
• Reduce Sensitivity below 1.0
• Enable all technical filters
Dashboard Shows "CAUTION"
This indicates:
• Market conditions are unfavorable
• Regime is RANGING or QUIET
• Market score is low
• Consider waiting for better conditions
• Or adjust expectations accordingly
Patterns Not Reaching Targets
Consider:
• Market may be choppy
• Volatility may have changed
• Try Dynamic target mode
• Reduce target/risk ratio requirement
• Check if regime is VOLATILE
---
ALERTS CONFIGURATION
Alert Message Format
Alerts include:
• Pattern type (Bullish/Bearish)
• Strength rating
• Market regime
• Analysis price level
• Target and invalidation levels
• Strength percentage
• Target/Risk ratio
• Educational disclaimer
Setting Up Alerts
• Click Alert button on TradingView
• Select SMPS indicator
• Choose alert frequency
• Customize message if desired
• Alerts fire on pattern detection
---
DATA WINDOW INFORMATION
The Data Window displays:
• Market Regime Score (0-100)
• Market Structure Bias (-1 to +1)
• Bullish Strength (0-100)
• Bearish Strength (0-100)
• Bull Target/Risk Ratio
• Bear Target/Risk Ratio
• Relative Volume
• Momentum Value
• Volume Flow Strength
• Bull Confirmations Count
• Bear Confirmations Count
---
BEST PRACTICES AND TIPS
For Beginners
• Start with default settings
• Use High Confirmation Mode
• Focus on TRENDING regime only
• Paper trade first
• Learn one timeframe thoroughly
For Intermediate Users
• Experiment with sensitivity settings
• Try different target modes
• Use multiple timeframes
• Combine with price action analysis
• Track pattern success rate
For Advanced Users
• Customize per instrument
• Create setting templates
• Use regime information for bias
• Combine with other indicators
• Develop systematic rules
---
IMPORTANT DISCLAIMERS
• This indicator is for educational and informational purposes only
• Not financial advice or a trading system
• Past performance does not guarantee future results
• Trading involves substantial risk of loss
• Always use appropriate risk management
• Verify patterns with additional analysis
• The author is not a registered investment advisor
• No liability accepted for trading losses
---
VERSION NOTES
Version 1.0.0 - Initial Release
• Six-layer confluence system
• Adaptive parameter technology
• Institutional volume detection
• Market regime classification
• Structure break identification
• Real-time dashboard
• Multiple display modes
• Comprehensive settings
## My Final Thoughts
Smart Money Precision Structure represents an advanced approach to market analysis, bringing institutional-grade techniques to retail traders through intelligent automation and multi-dimensional evaluation. By combining six analytical frameworks with adaptive parameter adjustment, SMPS provides comprehensive market intelligence that single indicators cannot achieve.
The indicator serves as an educational tool for understanding how professional traders analyze markets, while providing practical pattern detection for those seeking to improve their technical analysis. Remember that all trading involves risk, and this tool should be used as part of a complete analysis approach, not as a standalone trading system.
- BullByte
Donchian Squeeze Oscillator# Donchian Squeeze Oscillator (DSO) - User Guide
## Overview
The Donchian Squeeze Oscillator is a technical indicator designed to identify periods of low volatility (squeeze) and high volatility (expansion) in financial markets by measuring the distance between Donchian Channel bands. The indicator normalizes this measurement to a 0-100 scale, making it easy to interpret across different timeframes and instruments.
## How It Works
The DSO calculates the width of Donchian Channels as a percentage of the middle line, smooths this data, and then normalizes it using historical highs and lows over a specified lookback period. The result is inverted so that:
- **High values (80+)** = Narrow channels = Low volatility = Squeeze
- **Low values (20-)** = Wide channels = High volatility = Expansion
## Key Parameters
### Core Settings
- **Donchian Channel Period (20)**: The number of bars used to calculate the highest high and lowest low for the Donchian Channels
- **Smoothing Period (5)**: Applies moving average smoothing to reduce noise in the oscillator
- **Normalization Lookback (200)**: Historical period used to normalize the oscillator between 0-100
### Threshold Levels
- **Over Squeeze (80)**: Values above this level indicate strong squeeze conditions
- **Over Expansion (20)**: Values below this level indicate strong expansion conditions
## Reading the Indicator
### Color Coding
- **Red Line**: Squeeze condition (above 80 threshold) - Markets are consolidating
- **Orange Line**: Neutral/trending condition with upward momentum
- **Green Line**: Expansion condition or downward momentum
### Visual Elements
- **Red Dashed Line (80)**: Squeeze threshold - potential breakout zone
- **Gray Dotted Line (50)**: Middle line - neutral zone
- **Green Dashed Line (20)**: Expansion threshold - high volatility zone
- **Red Background**: Highlights active squeeze periods
## Trading Applications
### 1. Breakout Trading
- **Setup**: Wait for DSO to reach 80+ (squeeze zone)
- **Entry**: Look for breakouts when DSO starts declining from squeeze levels
- **Logic**: Prolonged low volatility often precedes significant price movements
### 2. Volatility Cycle Trading
- **Squeeze Phase**: DSO > 80 - Prepare for potential breakout
- **Breakout Phase**: DSO declining from 80 - Trade the direction of breakout
- **Expansion Phase**: DSO < 20 - Expect trend continuation or reversal
### 3. Trend Confirmation
- **Orange Color**: Suggests bullish momentum during expansion
- **Green Color**: Suggests bearish momentum or consolidation
- Use in conjunction with price action for trend confirmation
## Best Practices
### Timeframe Selection
- **Higher Timeframes (Daily, 4H)**: More reliable signals, fewer false breakouts
- **Lower Timeframes (1H, 15M)**: More frequent signals but higher noise
- **Multi-timeframe Analysis**: Confirm squeeze on higher TF, enter on lower TF
### Parameter Optimization
- **Volatile Markets**: Increase Donchian period (25-30) and smoothing (7-10)
- **Range-bound Markets**: Decrease Donchian period (15-20) for more sensitivity
- **Trending Markets**: Use longer normalization lookback (300-400)
### Signal Confirmation
Always combine DSO signals with:
- **Price Action**: Support/resistance levels, chart patterns
- **Volume**: Confirm breakouts with increasing volume
- **Other Indicators**: RSI, MACD, or momentum oscillators
## Alert System
The indicator includes built-in alerts for:
- **Squeeze Started**: When DSO crosses above the squeeze threshold
- **Expansion Started**: When DSO crosses below the expansion threshold
## Common Pitfalls to Avoid
1. **False Breakouts**: Don't trade every squeeze - wait for confirmation
2. **Parameter Over-optimization**: Stick to default settings initially
3. **Ignoring Market Context**: Consider overall market conditions and news
4. **Single Indicator Reliance**: Always use additional confirmation tools
## Advanced Tips
- Monitor squeeze duration - longer squeezes often lead to bigger moves
- Look for squeeze patterns at key support/resistance levels
- Use DSO divergences with price for potential reversal signals
- Combine with Bollinger Band squeezes for enhanced accuracy
## Conclusion
The Donchian Squeeze Oscillator is a powerful tool for identifying volatility cycles and potential breakout opportunities. Like all technical indicators, it should be used as part of a comprehensive trading strategy rather than as a standalone signal generator. Practice with the indicator on historical data before implementing it in live trading to understand its behavior in different market conditions.
FUMO 200 MagnetWhat it does
FUMO Magnet measures how far price has stretched away from its long-term “magnet” — a blended EMA/SMA moving average (200 by default).
It plots a logarithmic deviation (optionally normalized) as an oscillator around zero.
Above 0** → price is above the magnet (stretched up)
Below 0** → price is below the magnet (stretched down)
Guide levels** highlight potential overbought/oversold zones
---
Why log deviation?
Log returns make extremes comparable across cycles and compress exponential trends — especially useful for BTC and other crypto assets.
Normalization modes further adjust the scale, keeping the oscillator readable on any chart.
---
Inputs
**Base**
* Source (default: Close)
* Base Length (default: 200 EMA/SMA)
* EMA vs SMA weight (%) — 0% = pure SMA, 100% = pure EMA, 50% = blended
* EMA smoothing of deviation — acts as a noise filter
**Normalization**
* None (Log Deviation) — raw log stretch in % terms
* Z-score — deviation in standard deviations (σ)
* Robust Z (MAD) — deviation vs median absolute deviation, resistant to outliers
* Tanh squash — smooth nonlinear squash of extremes for compact scale
* Normalization window (for Z / MAD)
* Tanh scale (lower = stronger squash)
* Clamp after normalization — hard cap at ±X
**Levels**
* Guide levels (Upper / Lower) — visual thresholds (default ±12)
* Zero line toggle
---
### How to read it
* **Trend bias**: sustained time above 0 = uptrend, below 0 = downtrend
* **Stretch / mean reversion**: the farther from 0, the higher the reversion risk
* **Cross-checks**: combine with structure (HH/HL, LH/LL), volume, or momentum (RSI, MACD)
---
### Recommended settings by timeframe
**Long-term (1D / 1W)**
* Normalization: None (Log Deviation)
* Base Length: 200
* EMA vs SMA weight: 50% (adjust 35–65% for faster/slower magnet)
* Deviation smoothing: 20 (10–30 range)
* Guide levels: ±12 to ±20
* Use case: cycle extremes, portfolio rebalancing, trim/add logic
**Swing (4H – 1D)**
* Normalization: Z-score
* Window: 200 (100–250)
* Smoothing: 14–20
* Guide levels: ±2σ to ±3σ
* Use case: stretched conditions across regimes; ±3σ is rare, often mean-reverts
**Intraday / Active swing (1H – 4H)**
* Normalization: Robust Z (MAD)
* Window: 200 (150 for faster response)
* Smoothing: 10–16
* Guide levels: ±3 to ±4 (robust units)
* Use case: handles spikes better than σ, fewer false overbought/oversold signals
**Scalping / Universal readability (15m – 1H)**
* Normalization: Tanh squash
* Tanh scale: 6–10 (start with 8)
* Smoothing: 8–12
* Guide levels: ±8 to ±12
* Use case: compact panel across assets and timeframes; not % or σ, but visually consistent
---
### Optional
* Clamp: enable ±20 (or ±25) for strict bounded range (useful for public charts)
---
### Quick setups
**BTC Daily (“cycle view”)**
* Normalization: None
* Blend: 50%
* Smooth: 20
* Levels: ±12–15
**BTC 4H (“swing”)**
* Normalization: Z-score
* Window: 200
* Smooth: 16
* Levels: ±2.5σ to ±3σ
**Alts 1H (“volatile”)**
* Normalization: Robust Z (MAD)
* Window: 200
* Smooth: 12
* Levels: ±3.5 to ±4.5
**Mixed assets 15m (“compact panel”)**
* Normalization: Tanh squash
* Scale: 8
* Smooth: 10
* Levels: ±8–12
* Clamp: ±20
VWAP For Loop [BackQuant]VWAP For Loop
What this tool does—in one sentence
A volume-weighted trend gauge that anchors VWAP to a calendar period (day/week/month/quarter/year) and then scores the persistence of that VWAP trend with a simple for-loop “breadth” count; the result is a clean, threshold-driven oscillator plus an optional VWAP overlay and alerts.
Plain-English overview
Instead of judging raw price alone, this indicator focuses on anchored VWAP —the market’s average price paid during your chosen institutional period. It then asks a simple question across a configurable set of lookback steps: “Is the current anchored VWAP higher than it was i bars ago—or lower?” Each “yes” adds +1, each “no” adds −1. Summing those answers creates a score that reflects how consistently the volume-weighted trend has been rising or falling. Extreme positive scores imply persistent, broad strength; deeply negative scores imply persistent weakness. Crossing predefined thresholds produces objective long/short events and color-coded context.
Under the hood
• Anchoring — VWAP using hlc3 × volume resets exactly when the selected period rolls:
Day → session change, Week → new week, Month → new month, Quarter/Year → calendar quarter/year.
• For-loop scoring — For lag steps i = , compare today’s VWAP to VWAP .
– If VWAP > VWAP , add +1.
– Else, add −1.
The final score ∈ , where N = (end − start + 1). With defaults (1→45), N = 45.
• Signal logic (stateful)
– Long when score > upper (e.g., > 40 with N = 45 → VWAP higher than ~89% of checked lags).
– Short on crossunder of lower (e.g., dropping below −10).
– A compact state variable ( out ) holds the current regime: +1 (long), −1 (short), otherwise unchanged. This “stickiness” avoids constant flipping between bars without sufficient evidence.
Why VWAP + a breadth score?
• VWAP aggregates both price and volume—where participants actually traded.
• The breadth-style count rewards consistency of the anchored trend, not one-off spikes.
• Thresholds give you binary structure when you need it (alerts, automation), without complex math.
What you’ll see on the chart
• Sub-pane oscillator — The for-loop score line, colored by regime (long/short/neutral).
• Main-pane VWAP (optional) — Even though the indicator runs off-chart, the anchored VWAP can be overlaid on price (toggle visibility and whether it inherits trend colors).
• Threshold guides — Horizontal lines for the long/short bands (toggle).
• Cosmetics — Optional candle painting and background shading by regime; adjustable line width and colors.
Input map (quick reference)
• VWAP Anchor Period — Day, Week, Month, Quarter, Year.
• Calculation Start/End — The for-loop lag window . With 1→45, you evaluate 45 comparisons.
• Long/Short Thresholds — Default upper=40, lower=−10 (asymmetric by design; see below).
• UI/Style — Show thresholds, paint candles, background color, line width, VWAP visibility and coloring, custom long/short colors.
Interpreting the score
• Near +N — Current anchored VWAP is above most historical VWAP checkpoints in the window → entrenched strength.
• Near −N — Current anchored VWAP is below most checkpoints → entrenched weakness.
• Between — Mixed, choppy, or transitioning regimes; use thresholds to avoid reacting to noise.
Why the asymmetric default thresholds?
• Long = score > upper (40) — Demands unusually broad upside persistence before declaring “long regime.”
• Short = crossunder lower (−10) — Triggers only on downward momentum events (a fresh breach), not merely being below −10. This combination tends to:
– Capture sustained uptrends only when they’re very strong.
– Flag downside turns as they occur, rather than waiting for an extreme negative breadth.
Tuning guide
Choose an anchor that matches your horizon
– Intraday scalps : Day anchor on intraday charts.
– Swing/position : Month or Quarter anchor on 1h/4h/D charts to capture institutional cycles.
Pick the for-loop window
– Larger N (bigger end) = stronger evidence requirement, smoother oscillator.
– Smaller N = faster, more reactive score.
Set achievable thresholds
– Ensure upper ≤ N and lower ≥ −N ; if N=30, an upper of 40 can never trigger.
– Symmetric setups (e.g., +20/−20) are fine if you want balanced behavior.
Match visuals to intent
– Enabling VWAP coloring lets you see regime directly on price.
– Background shading is useful for discretionary reading; turn it off for cleaner automation displays.
Playbook examples
• Trend confirmation with disciplined entries — On Month anchor, N=45, upper=38–42: when the long regime engages, use pullbacks toward anchored VWAP on the main pane for entries, with stops just beyond VWAP or a recent swing.
• Downside transition detection — Keep lower around −8…−12 and watch for crossunders; combine with price losing anchored VWAP to validate risk-off.
• Intraday bias filter — Day anchor on a 5–15m chart, N=20–30, upper ~ 16–20, lower ~ −6…−10. Only take longs while score is positive and above a midline you define (e.g., 0), and shorts only after a genuine crossunder.
Behavior around resets (important)
Anchored VWAP is hard-reset each period. Immediately after a reset, the series can be young and comparisons to pre-reset values may span two periods. If you prefer within-period evaluation only, choose end small enough not to bridge typical period length on your timeframe, or accept that the breadth test intentionally spans regimes.
Alerts included
• VWAP FL Long — Fires when the long condition is true (score > upper and not in short).
• VWAP FL Short — Fires on crossunder of the lower threshold (event-driven).
Messages include {{ticker}} and {{interval}} placeholders for routing.
Strengths
• Simple, transparent math — Easy to reason about and validate.
• Volume-aware by construction — Decisions reference VWAP, not just price.
• Robust to single-bar noise — Needs many lags to agree before flipping state (by design, via thresholds and the stateful output).
Limitations & cautions
• Threshold feasibility — If N < upper or |lower| > N, signals will never trigger; always cross-check N.
• Path dependence — The state variable persists until a new event; if you want frequent re-evaluation, lower thresholds or reduce N.
• Regime changes — Calendar resets can produce early ambiguity; expect a few bars for the breadth to mature.
• VWAP sensitivity to volume spikes — Large prints can tilt VWAP abruptly; that behavior is intentional in VWAP-based logic.
Suggested starting profiles
• Intraday trend bias : Anchor=Day, N=25 (1→25), upper=18–20, lower=−8, paint candles ON.
• Swing bias : Anchor=Month, N=45 (1→45), upper=38–42, lower=−10, VWAP coloring ON, background OFF.
• Balanced reactivity : Anchor=Week, N=30 (1→30), upper=20–22, lower=−10…−12, symmetric if desired.
Implementation notes
• The indicator runs in a separate pane (oscillator), but VWAP itself is drawn on price using forced overlay so you can see interactions (touches, reclaim/loss).
• HLC3 is used for VWAP price; that’s a common choice to dampen wick noise while still reflecting intrabar range.
• For-loop cap is kept modest (≤50) for performance and clarity.
How to use this responsibly
Treat the oscillator as a bias and persistence meter . Combine it with your entry framework (structure breaks, liquidity zones, higher-timeframe context) and risk controls. The design emphasizes clarity over complexity—its edge is in how strictly it demands agreement before declaring a regime, not in predicting specific turns.
Summary
VWAP For Loop distills the question “How broadly is the anchored, volume-weighted trend advancing or retreating?” into a single, thresholded score you can read at a glance, alert on, and color through your chart. With careful anchoring and thresholds sized to your window length, it becomes a pragmatic bias filter for both systematic and discretionary workflows.
The Barking Rat LiteMomentum & FVG Reversion Strategy
The Barking Rat Lite is a disciplined, short-term mean-reversion strategy that combines RSI momentum filtering, EMA bands, and Fair Value Gap (FVG) detection to identify short-term reversal points. Designed for practical use on volatile markets, it focuses on precise entries and ATR-based take profit management to balance opportunity and risk.
Core Concept
This strategy seeks potential reversals when short-term price action shows exhaustion outside an EMA band, confirmed by momentum and FVG signals:
EMA Bands:
Parameters used: A 20-period EMA (fast) and 100-period EMA (slow).
Why chosen:
- The 20 EMA is sensitive to short-term moves and reflects immediate momentum.
- The 100 EMA provides a slower, structural anchor.
When price trades outside both bands, it often signals overextension relative to both short-term and medium-term trends.
Application in strategy:
- Long entries are only considered when price dips below both EMAs, identifying potential undervaluation.
- Short entries are only considered when price rises above both EMAs, identifying potential overvaluation.
This dual-band filter avoids counter-trend signals that would occur if only a single EMA was used, making entries more selective..
Fair Value Gap Detection (FVG):
Parameters used: The script checks for dislocations using a 12-bar lookback (i.e. comparing current highs/lows with values 12 candles back).
Why chosen:
- A 12-bar displacement highlights significant inefficiencies in price structure while filtering out micro-gaps that appear every few bars in high-volatility markets.
- By aligning FVG signals with candle direction (bullish = close > open, bearish = close < open), the strategy avoids random gaps and instead targets ones that suggest exhaustion.
Application in strategy:
- Bullish FVGs form when earlier lows sit above current highs, hinting at downward over-extension.
- Bearish FVGs form when earlier highs sit below current lows, hinting at upward over-extension.
This gives the strategy a structural filter beyond simple oscillators, ensuring signals have price-dislocation context.
RSI Momentum Filter:
Parameters used: 14-period RSI with thresholds of 80 (overbought) and 20 (oversold).
Why chosen:
- RSI(14) is a widely recognized momentum measure that balances responsiveness with stability.
- The thresholds are intentionally extreme (80/20 vs. the more common 70/30), so the strategy only engages at genuine exhaustion points rather than frequent minor corrections.
Application in strategy:
- Longs trigger when RSI < 20, suggesting oversold exhaustion.
- Shorts trigger when RSI > 80, suggesting overbought exhaustion.
This ensures entries are not just technically valid but also backed by momentum extremes, raising conviction.
ATR-Based Take Profit:
Parameters used: 14-period ATR, with a default multiplier of 4.
Why chosen:
- ATR(14) reflects the prevailing volatility environment without reacting too much to outliers.
- A multiplier of 4 is a pragmatic compromise: wide enough to let trades breathe in volatile conditions, but tight enough to enforce disciplined exits before mean reversion fades.
Application in strategy:
- At entry, a fixed target is set = Entry Price ± (ATR × 4).
- This target scales automatically with volatility: narrower in calm periods, wider in explosive markets.
By avoiding discretionary exits, the system maintains rule-based discipline.
Visual Signals on Chart
Blue “▲” below candle: Potential long entry
Orange/Yellow “▼” above candle: Potential short entry
Green “✔️”: Trade closed at ATR take profit
Blue (20 EMA) & Orange (100 EMA) lines: Dynamic channel reference
⚙️Strategy report properties
Position size: 25% equity per trade
Initial capital: 10,000.00 USDT
Pyramiding: 10 entries per direction
Slippage: 2 ticks
Commission: 0.055% per side
Backtest timeframe: 1-minute
Backtest instrument: HYPEUSDT
Backtesting range: Jul 28, 2025 — Aug 17, 2025
Note on Sample Size:
You’ll notice the report displays fewer than the ideal 100 trades in the strategy report above. This is intentional. The goal of the script is to isolate high-quality, short-term reversal opportunities while filtering out low-conviction setups. This means that the Barking Rat Lite strategy is very selective, filtering out over 90% of market noise. The brief timeframe shown in the strategy report here illustrates its filtering logic over a short window — not its full capabilities. As a result, even on lower timeframes like the 1-minute chart, signals are deliberately sparse — each one must pass all criteria before triggering.
For a larger dataset:
Once the strategy is applied to your chart, users are encouraged to expand the lookback range or apply the strategy to other volatile pairs to view a full sample.
💡Why 25% Equity Per Trade?
While it's always best to size positions based on personal risk tolerance, we defaulted to 25% equity per trade in the backtesting data — and here’s why:
Backtests using this sizing show manageable drawdowns even under volatile periods.
The strategy generates a sizeable number of trades, reducing reliance on a single outcome.
Combined with conservative filters, the 25% setting offers a balance between aggression and control.
Users are strongly encouraged to customize this to suit their risk profile.
What makes Barking Rat Lite valuable
Combines multiple layers of confirmation: EMA bands + FVG + RSI
Adaptive to volatility: ATR-based exits scale with market conditions
Clear, actionable visuals: Easy to monitor and manage trades
Coin Jin Multi SMA+ BB+ SMA forecast Ver 2.0Coin Jin Multi SMA + BB + SMA Forecast 2.0
개요
여러 개의 단순이동평균(SMA: 5/20/60/112/224/448/896 + 사용자 정의 X1/X2), 볼린저 밴드(BB), 그리고 접선 기반 곡선 예측선을 한 번에 표시합니다. 예측선은 선형회귀 기울기와 그 변화율(가속도)을 EMA로 스무딩해 곡선 외삽으로 앞으로 그려지며, 어떤 줌에서도 깔끔하게 보이도록 점선(dotted) 스타일을 강제할 수 있습니다.
스택 마커(정배열/역배열) 안내
조건: 이동평균이 정배열(5>20>60>112>224>448>(896)) 또는 역배열(5<20<60<112<224<448<(896))로 새로 전환되는 순간 삼각형 마커가 생성됩니다.
896일선 포함(with 896): SOLID 마커로 표시, Bull = 초록색, Bear = 빨간색.
896일선 미포함(no 896): HOLLOW(윤곽) 마커로 표시, 시선을 덜 끌도록 투명도 70 적용(Bull = 연두, Bear = 빨강 동일색).
방향: Bull = ▼(위, abovebar) / Bear = ▲(아래, belowbar) 로 배치됩니다.
주요 기능
SMA 7종 기본 + 사용자 정의 SMA 2개(X1/X2) 추가(기본 꺼짐, 길이/색/두께/타입 자유).
BB: 길이/배수/선두께/밴드 채움(기본 90% 투명) 지원.
예측선: Forward bars(1–100, 기본 30), 기울기 산출 길이, 스무딩 강도, 세그먼트 개수, 점/대시 스타일 선택 및 도트 강제.
스택(정/역배열) 전환 마커: with 896=SOLID, no 896=HOLLOW(투명도 70).
처음 사용하는 분들을 위한 팁 (중요)
가격 스케일을 ‘우측’으로 고정하세요.
방법 ① 차트 우측 축을 사용(기본).
방법 ② 지표 레전드의 ‘⋯’ 메뉴 → Move to → Right scale.
예측선이 본선과 어긋나 보이면 스케일이 좌측/양측으로 되어 있거나 자동 합침된 경우이니 Right scale로 맞춰주세요.
입력 요약
MA Source, 각 SMA on/off·길이·색·두께·타입
BB length/mult/width/fill/opacity(기본 90)
Forecast bars ahead(1–100), slope lookback, smoothing, segments, style/opacity, 적용 대상 선택(SMA별)
주의/면책
예측선은 가격 예언 도구가 아니라 시각적 외삽 보조지표입니다. 단독 매매 판단에 사용하지 마세요.
공개 스크린샷은 본 지표만 보이도록 깔끔하게 캡처해 주세요(다른 지표/드로잉 혼합 금지).
변경사항(v2.0)
곡선 예측선 안정화 및 도트 강제 개선.
스택 마커 no 896 상태 HOLLOW 투명도 70 적용(가독성 향상).
사용자 정의 SMA X1/X2 추가(기본 OFF).
Coin Jin Multi SMA + BB + SMA Forecast 2.0 (English)
Overview
This indicator plots multiple Simple Moving Averages (SMA: 5/20/60/112/224/448/896 + two user-defined X1/X2), Bollinger Bands, and a tangent-based curved forecast in one overlay. The forecast extrapolates forward using the linear-regression slope and its rate of change (acceleration) smoothed by EMA, and you can force a dotted look so it stays clean at any zoom level.
Stack Markers (Bullish/Bearish alignment)
Markers appear only when a full bullish stack (5>20>60>112>224>448>(896)) or bearish stack (5<20<60<112<224<448<(896)) is newly formed.
With 896 included: shown as SOLID triangles — Bull = green, Bear = red.
Without 896: shown as HOLLOW (outline) with 70 transparency to reduce visual weight — Bull = lime, Bear = red (same hue).
Orientation: Bull = ▼ abovebar, Bear = ▲ belowbar.
Features
7 standard SMAs + two custom SMAs (X1/X2) (default OFF; fully configurable length/color/width/style).
BB with length/multiplier/width/fill (default fill opacity 90%).
Forecast controls: forward bars (1–100, default 30), slope window, smoothing, segment count, style/opacity, force dotted option.
Stack markers: with 896 = SOLID, without 896 = HOLLOW (70 transparency).
First-time setup (Important)
Pin the indicator to the Right price scale.
Option A: Use the right price axis.
Option B: Indicator legend “⋯” → Move to → Right scale.
If the forecast appears detached from the MA, your series is likely on the left/both scales; switch to Right scale.
Inputs
MA source; per-SMA on/off, length, color, width, style
BB length/multiplier/width/fill/opacity (default 90)
Forecast bars ahead (1–100), slope lookback, smoothing, segments, style/opacity, per-SMA apply switches
Disclaimer
The forecast is a visual extrapolation, not a price prediction. Do not use it alone to make trading decisions.
For publication, please use a clean screenshot that shows only this indicator (no mixed overlays).
What’s new in v2.0
More robust curved forecast with improved “force dotted” rendering.
HOLLOW (no 896) markers now use 70 transparency for better readability.
Added two user-defined SMAs (X1/X2), OFF by default.
VWAP CALENDARThe VWAP CALENDAR indicator plots up to 20 anchored Volume-Weighted Average Price (VWAP) lines on your chart, each starting from a user-defined date and time (e.g., April 20, 2024). Designed for simplicity, it helps traders visualize VWAPs for key events or dates, with customizable labels and colors. The indicator is optimized for crypto markets (e.g., BTC/USD) but works with any symbol providing volume data.
Features: Multiple VWAPs: Configure up to 20
independent VWAPs, each with a custom anchor date and time.
Dynamic Labels: Labels update in real-time, aligning precisely with each VWAP line’s price level, positioned to the right of the chart for clarity.
Customizable Settings: Adjust label text (e.g., “Event A”), line colors, line widths (1–5 pixels), text colors, and text sizes (8–40 points, default 22).
Bubble or No-Background Labels: Choose between bubble-style labels (with colored backgrounds) or plain text labels without backgrounds.
Timeframe Support: Accurate on daily, 4-hour, 1-hour, and 30-minute charts for anchors within ~1.5 years (e.g., April 20, 2024, from August 2025).
Limitations: VWAP accuracy for anchors like April 20, 2024 (~477 days back) is reliable on 1-hour and larger timeframes. Below 30-minute (e.g., 15-minute, 24-minute), VWAPs may start later or be unavailable due to TradingView’s 5,000-bar historical data limit. For distant anchors, use 4-hour or daily charts to ensure accuracy.
Requires sufficient chart history (e.g., premium account or deep exchange data) for older anchors on 1-hour or 30-minute charts.
Usage Notes: Set anchor dates via the indicator settings (e.g., “2024-04-20 00:00”).
Enable/disable individual VWAPs as needed.
Zoom out to load maximum chart history for best results, especially on 1-hour or 30-minute timeframes.
Ideal for crypto symbols with continuous trading data, but verify data availability for other markets.
Disclaimer:
This is a free indicator provided as-is
