Anchored Probability Cone by TenozenFirst of all, credit to @nasu_is_gaji for the open source code of Log-Normal Price Forecast! He teaches me alot on how to use polylines and inverse normal distribution from his indicator, so check it out!
What is this indicator all about?
This indicator draws a probability cone that visualizes possible future price ranges with varying levels of statistical confidence using Inverse Normal Distribution , anchored to the start of a selected timeframe (4h, W, M, etc.)
Feutures:
Anchored Cone: Forecasts begin at the first bar of each chosen higher timeframe, offering a consistent point for analysis.
Drift & Volatility-Based Forecast: Uses log returns to estimate market volatility (smoothed using VWMA) and incorporates a trend angle that users can set manually.
Probabilistic Price Bands: Displays price ranges with 5 customizable confidence levels (e.g., 30%, 68%, 87%, 99%, 99,9%).
Dynamic Updating: Recalculates and redraws the cone at the start of each new anchor period.
How to use:
Choose the Anchored Timeframe (PineScript only be able to forecast 500 bars in the future, so if it doesn't plot, try adjusting to a lower anchored period).
You can set the Model Length, 100 sample is the default. The higher the sample size, the higher the bias towards the overall volatility. So better set the sample size in a balanced manner.
If the market is inside the 30% conifidence zone (gray color), most likely the market is sideways. If it's outside the 30% confidence zone, that means it would tend to trend and reach the other probability levels.
Always follow the trend, don't ever try to trade mean reversions if you don't know what you're doing, as mean reversion trades are riskier.
That's all guys! I hope this indicator helps! If there's any suggestions, I'm open for it! Thanks and goodluck on your trading journey!
Statistics
AQPRO Block Force
📝 INTRODUCTION
AQPRO Block Force is a powerful trading tool designed to identify and track Orderblocks (OBs) in real-time based on Fair Value Gap (FVG) principles. This indicator employs quite strict yet effective FVG filtering criteria to ensure only significant OBs are displayed, avoiding minor inefficiencies or duplicates within the same impulse or corrective moves. Each OB adapts dynamically to price action and can be categorized as Classic, Strong, or Extreme, based on proprietary conditions and best ideas from SMC (Smart Money Concepts).
In addition to plotting Orderblocks, the indicator offers useful filtering systems like an Age Filter to ensure cleanliness of the OB data on the chart and prevent old, irrelevant OBs from obstructing the chart. Users can also enable MTF (Multi-Timeframe) functionality to view OBs from other timeframes, providing a comprehensive analysis across multiple levels of market structure. With extensive customization options, AQPRO Block Force allows traders to tailor the visuals and behavior to fit their specific trading preferences.
This indicator does not parse any instituotinal data, order books and other fancy financial sources for finding order blocks nor it uses them for confirmation purposes. Calculations algorithms of order blocks are based purely on current asset's price history.
IMPORTANT NOTE: in the sections below term 'quality' will be applied to orderblocks quite a number of times. By 'quality' in the context of orderblocks we mean the reaction of price upon the sweep of orderblock. Basically, if the price reverses after reaching the orderblock, this orderblock is considered to be of high quality. Definition for low -quality orderblock can be deducted by analogy.
🎯 PURPOSE OF USAGE
This indicator serves one and only purpose — help traders identify most lucrative institutional orderblocks on the chart in real time. Even though event of price reaching an orderblock cannot be considered as a sole signal in many trading strategies without proper confirmation, such event nevertheless is quite important in SMC-based trading, because when price sweeps OB it usually means, that a reversal will soon follow, but, of course, this is not the case every time.
Traders should not expect from this indicator detection of perfect orderblocks, which would surely revese the price on encounter, but they can expect is a time-proven algorithm of determing orderblocks that on average produces more high-quality orderblocks than simple similar tools from open-source libraries.
More in-depth advices on the usage will be given in the sections below, but for now let's summarise subgoals of the indicator:
Detecting orderblocks filtered through strict FVG validation rules to improve overall quality of orderblocks;
Classifying orderblocks as Classic, Strong, or Extreme based on wether or not classic orderblocks pass filtering conditions, which are based on crossing critical price levels and SMC principles like ChoCh (Change of Character);
Eliminating clutter and manage chart space with the Age Filter, removing old OBs outside a user-defined age range;
Utilizing MTF functionality to track significant OBs from other timeframes alongside current timeframe analysis;
Providing traders with customization options for indicator's visuals to help them organize information on the chart in a clean way.
⚙️ SETTINGS OVERVIEW
This indicator's customization options allow you to fully control its functionality and visuals. Below is a breakdown of the settings grouped by the exact setting sections and parameters from the indicator:
🔑 Main Settings
Show OBs from current timeframe — toggles the display of OBs from the current timeframe on the chart;
Show classic OBs — enables or disables the display of Classic OBs;
Show strong OBs — enables or disables the display of Strong OBs, which meet the ChoCh-based filter criteria;
Show extreme OBs — enables or disables the display of Extreme OBs, which exceed proprietary price level risk thresholds.
⏳ Filter: Age
Use Age Filter — toggles the Age Filter, which removes old OBs based on their age;
Max Age — sets the maximum age of OBs to be displayed (in bars). OBs older than this value will be hidden;
Min Age — sets the minimum age of OBs to be displayed (in bars). OBs younger than this value will not be shown.
🌋 MTF Settings
Show MTF OBs — toggles the display of OBs from higher timeframes;
Timeframe — select the timeframe to use for MTF OB detection (e.g., 15m, 1h).
⏳ MTF / Filter: Age
Use Age Filter (MTF) — toggles the Age Filter for MTF OBs;
Max Age — sets the maximum age of MTF OBs to be displayed (in bars);
Min Age — sets the minimum age of MTF OBs to be displayed (in bars).
🎨 Visual Settings
Classic OB (Bullish) — sets the color for bullish Classic OBs;
Classic OB (Bearish) — sets the color for bearish Classic OBs;
Strong OB (Bullish) — sets the color for bullish Strong OBs;
Strong OB (Bearish) — sets the color for bearish Strong OBs;
Extreme OB (Bullish) — sets the color for bullish Extreme OBs;
Extreme OB (Bearish) — sets the color for bearish Extreme OBs.
📈 APPLICATION GUIDE
Application methodology of this indicator is pretty much the same as with any other indicator, whose purpose is to find and display orderblocks on the chart. However, before actually diving into the guide on application, we want to make a small step back to remind traders of the history of orderblocks as a concept, its limitations and benefits.
Orderblocks themselves are essentially just zones of potential institutional interest, which if reached are expected to reverse the price in the opposite direction. 'Potential' is a suitable remark for indicator's success probability, because, as was mentioned above, orderblocks don't guarantee price reversal regardless of quality of the indicator. This is the case for the simplest of reasons — orderblocks are based solely on price history and thus are to be considered a mathematical model , degree of success of which is never 100%, because all mathematical models abide by a "golden rule of trading" : past performance doesn't guarantee future results.
However, the extensive history of orderblocks clearly shows that this tool, despite being decades old, can still help traders produce market insights and improve any strategy's performance. Orderblocks can be used both as a primary source of signals and as confirmation tool, but from our experience they are better to be used as confirmation tool. Our indicator is not an exception in this matter and we advice any trader to use it mainly for confirmation purposes, because use-case of orderblocks as confirmation tools have much success stories on average than being used as primary signal source.
This being said, let's return to the application guide and start reviewing the indicator from the most basic step — how it will look like when you first load it on your chart:
This indicator consisis of 3 main logic blocks:
Orderblock evaluation;
MTF Orderblock evaluation;
Orderblock post-filtering.
The principles behind these logic blocks will be easy to understand for truly experiences traders, but we understand the need to explain them to a wider audience, so let's review each of these logic blocks below.
ORDERBLOCK EVALUATION
Principles behind our orderblock detection logic are as follows:
Find FVG (Fair Value Gap) .
Note: this indicator uses only three-candle FVGs and doesn't track FVGs with insidebars after third (farther) candle.
If you don't know what FVG means, we recommend researching this term in the Internet, but the basic explanation is this: FVG is the formation of candles, which are positioned in a way that there are an unclosed price area between 1st and 3rd candle.
Conditions:
bullish FVG = high of 3rd candle < low of 1st candle AND high of 3rd candle < close of 2nd candle AND high of 2nd candle < close of 1st candle AND low of 3rd candle < low of 2nd candle ;
bearish FVG = low of 3rd candle < high of 1st candle AND low of 3rd candle > close of 2nd candle AND low of 2nd candle > close of 1st candle AND high of 3rd candle > high of 2nd candle .
See visual showcase of valid & invalid bullish & bearish FVGs on the screenshot below:
As was shown on the screenshot above, the only correc t formation for FVGs are considered to be just like on pictures 1 and 2 (leftmost column of patterns) . Only these formations will take part in further determenings orderblocks.
Send FVGs through filtering conditions.
This is the truly important part. Without properly filtering FVGs we would get huge clusters of FVGs on the chart and they will not make sense to be reviewed, because there will be just too much of them and their quality will be very questionable .
Even though there is a quite number of ways to filter FVGs, we decided to go with the ones we deem actually useful. For this indicator we chose two methods, that work in tandem — 1) base candle's inside bar condition and 2) single appearance on current impulse/correction line. Let's review these conditions below and start with looking at the examples of them on the screenshot below:
Examples of 1st & 2nd conditions are displayed on the left and right charts respectively.
The filtering logic in 1st and 2nd is quite connected and further explanation should help you understand it just enough to start trading with our indicator.
Let's start with explaining the term 'base candle' and logic behind it. Base candle candle be explained quite shortly: it is the latest candle on the chart, whose high or low broke previous base candle's high or low respectively. The first candle in the time series of price data is by default considered the base candle. If any new candle after base candle doesn't overtake base candle's high or low (meaning, that this candle is inside the range of base candle), such candle is called an "inside bar" .
Inside bar's term is important to understand, because FVGs, which appear inside the inside bars are usually quite useless, because price doesn't react from them, so orderblocks with such FVGs are also of bad quality as well. Clear depiction of inside bar was provided in the screenshot of conditions above on the left chart, so we won't waste time making another example.
However, this is not it. Base candle, inside bars and a few other types of bars are all a part of SMC ideas and in the world of SMC there is a special term, that hold the most important place and is considered the cornerstone of SMC methodology — impulse/correction lines (valid pullbacks) . The average definition of impulse/correction lines is quite hard to understand for an average trader, but we can summarise like this:
Impulse/correction line is a line, that starts at the beginning of the sequence of base candles, each new candle of which consistently updates previous base candle's respective high/low.
We won't go into description of this principle because it is outside of scope of this indicator, but you can research this topic in the Internet by keywords ' impulse correction trading ' or 'valid pullback principles trading '. The general idea of usage of impulse/correction lines in the context of this indicator is that each such lines 'holds' inside at least one FVG and we need to find exactly the first FVG, while leaving all other FVGs behind, because they to be of worse quality on average.
Basically, by using translating these terms into conditions from example above, we have achieved a simple yet powerful filtering system. system for FVGs, which allows us to work with orderblocks of much higher quality than average open-source indicators.
If FVG passed filters, evaluate its OB.
When FVG is confirmed, we can start the evaluation of its orderblock. The evaluation of orderblocks consists of several checkpoints: 1) is orderblock beyond current ChoCh* AND/OR 2) is orderblock from extreme price levels, calculated by our proprietary risk system. Let's review these checkpoints below.
* ChoCh (Change of Character, fundamental SMC idea) — price level, which if broken by close of price can potentially cause a revesal of the trend to direction opposite to the the previous one. To learn more about ChoCh please research the term on the Internet, because this indicator uses its standard definition and explaining of this term goes beyond the scope of this indicator.
To determine if orderblock is beyond current ChoCh levels, we need to first determine where these levels are on the chart. ChoCh levels of this indicator are calculated with a very lite approach, which is based on pivot points.
You can see basic demonstration of ChoCh levels in action on the screenshot below:
IMPORTANT NOTE: pivot period for pivots points inside our indicator is by default equal to 5 and cannot be changed in settings at the moment of publication.
On the screenshot above you can clearly see that ChoCh levels are essentially highest/lowest pivot point levels in between certain range of bars, where price doesn't update its extremum. You can see on there screenshot a new type of line — BoS (Break of Structure). BoS is almost the same thing as ChoCh, but with one change: it is a confirmation of price updating its extremum in the same direction as it was before, while ChoCh updates price extremum in the direction opposite to which it was before .
Why do these levels matter when evaluating the orderblocks? Orderblocks, which are located beyond current BoS/ChoCh levels, are of much higher quality on average than average orderblocks and they are called Strong Orderblocks .
On the chart such orderblocks are marked with 'Strong OB' label inside the body of an orderblock.
You can see the examples of Strong OBs on the screenshot below:
That was the explanation of the 1st orderblock evaluation criteria. Now let's talk about the 2nd one.
Our 2nd evaluation criteria for orderblocks is a test on whether or price is behind specific price level, which is calculated by our proprietary risk system, which is based on fundamental of statistics, such as 'standard deviation' and etc.
This criteria allows us to catch orderblocks, which are located at quite extreme price levels, and mark them on trader's chart explicitly. Orderblocks, which are above our custom price levels, are called Extreme Orderblocks an are marked with 'Extreme OB' label inside orderblock's body.
You can see the example of Extreme OB on the screenshot below:
That was the explanation of the 2nd evaluation criteria of the orderblock.
If an orderblock doesn't pass any of these two criterias, it is considered a classic orderblock. These orderblock are most common ones and have the lowest success rate among other types of orderblocks, listed above. Such orderblocks are marked with 'OB' label inside the orderblock's body.
You can see the examples of classic OB on the screenshot below:
This is it for orderblock evaluation logic. After doing all these steps, all orderblocks that we found are collected and displayed on the chart with their bodies and label marks.
What happens after the detection of the orderblocks?
All active orderblocks are being tracked in real time and their statuses are being updated as well (Strong orderblock can become Extreme orderblock and vice versa) . By an active orderblock we mean an orderblock, which wasn't swept by price's high or low. Bodies of active orderblocks are prolonged to the next candle on each new candle.
If an orderblock was swept, indicator will stop prolonging this orderblock and will mark it as swept on the chart with almost hollow body and dashed border line of the orderblock's body. Also swept orderblocks lose their name label, so you won't see any text in the orderblock after it was swept, but you will see its colour.
You can see the example of an active & swept orderblocks on the screenshot below:
This functionality helps distinguish active orderblocks from swept ones (inactive) and make more informed decisions.
MTF OB EVALUATION
Principles of MTF OBs evaluation are exactly the same as they are for current timeframe's OBs.
MTF OBs are displayed on the chart in same way as other OBs, but with one little change: to the right side of MTF OB's status will be postfix of the timeframe, from which this OB came from. Timeframe for MTF OBs can be chosen by user in the settings of the indicator.
MTF OBs also preserve their statuses (Strong, Extreme and Classic) when displayed on the current timeframe, so you won't stack of mistakenly marked MTF OBs as Extreme just because they are far away from the price.
You can see the example of MTF OBs on the screenshot below:
Also MTF OBs when swept lose only their name label, but the timeframe postfix will still be there, so you could distinguish MTF OBs from OBs of the current timeframe.
See the example of swept MTF OBs below:
Overall MTF orderblocks is a very useful to get a sense of where the higher timeframe liquidity reside and then adjust your strategy accordingly. Taking your trades from the place of high liquidity, like orderblocks, doesn't guarantee certain solid price reaction, but it definitely provides a trader with much a greater change of 1) catching a decent price move 2) not losing money white trading against institutional players.
As was stated above, we recommend using this tool as a confirmation system for your main trading strategy, because its usage as primary source of signals in the long-run is not viable, judging from historical backtest results and general public opinions of traders.
ORDERBLOCK POST-FILTERING
To enhance filtering capabilities of this indicator even further, we decided to add two filters, which would help reduce the amount of bad and untradeable orderblocks. These two filters are 1) age filter and 2) cancellation filter. Let's review both of them below.
Talking about the age filter , this filter was designed to help get rid of old orderblocks, which clutter the chart with visual noise and make it harder to find valueable orderblocks. This filter has to parameters: min age and max age . What does age mean in the context of an orderblock? It is the distance between OB's left border's bar and current bar. If this distance is between min age and max age values, such orderblock is considered valid and age filter passes it for further evaluation, but this distance is too short or too long, age filter deletes this orderblock from the chart.
You can the example of an orderblock which didn't pass age filter requirements and was deleted from the chart on the screenshot below:
It is important to mention that the missing orderblock from the right chart will be appear on the chart right when its age will exceed min age parameter of age filter.
The principle of work for max age parameter can be deducted by analogy: if the orderblock's age in bigger than max age value of age filter, this orderblock will be deleted from the chart .
For MTF OBs we decided to their own age filter, so that it won't abide by current timeframe's restrictions, because MTF OBs are usually much older than OB from current timeframe, so they would deleted a lot of time before they even appear on the chart, if they would abide by the age filter of current timeframe.
Default parameters of age filter are "max age = 500" and "min age = 0" . "Min age = 0" means that there is restrictions on the minimum age of orderblocks and they will appear on the chart as soon as the indicator validates them.
That was the explanation of the age filter.
Talking about the cancellation filter , this filter was intended to spot orderblocks which were extremely untradable and visually alert traders about them on the chart. In this indicator this filter works like this: for each orderblock cancellation filter creates a special price level and checks if it was broken by the close of price.
This special price level consists of the farthest border. of the orderblock ( top border for bearish OBs and bottom border for bullish OBs) and a certain threshold, which is added to the farthest border. This threshold is based on the current ATR value of the asset. This filter helps detect the orderblocks which should not be considered for trading, because price has already went too far beyond the liquidity of this orderblock.
Orderblocks, which are spotted by this filter, are marked with '❌' emoji on the price history.
You can see the example of an orderblock which was spotted by the cancellation filter in the screenshot below:
This filter is applied to both current timeframe and MTF timeframe and is NOT configurable in the settings.
🔔 ALERTS
This indicator employs alerts for an event when new signal occurs on the current timeframe or on MTF timeframe. While creating the alert below 'Condition' field choose 'any alert() function call'.
When this alert is triggered, it will generate this kind of message:
// Alerts for current timeframe
string msg_template = "EXCHANGE:ASSET, TIMEFRAME: BULLISH_OR_BEARISH OB at SWEPT_OB_BORDER_PRICE was reached."
string msg_example = "BINANCE:BTCUSDT, 15m: bearish OB at 170000.00 was reached."
// Alerts for MTF timeframe
string msg_template_mtf = "EXCHANGE:ASSET, TIMEFRAME: BULLISH_OR_BEARISH MTF OB at SWEPT_OB_BORDER_PRICE was reached."
string msg_example_mtf = "BINANCE:BTCUSDT, 15m: bearish MTF OB at 170000.00 was reached."
📌 NOTES
These OBs work on any timeframe, but we would advise to to use on higher timeframes, starting from at least 15m, because liquidity from higher timeframe tends to be much valuable when deciding which orderblock to take for a trade;
Use these OBs as a confirmation tool for your main strategy and refrain from using them as primary signal source. Traders, which use SMC-based strategies, will benefit from these orderblocks the most;
We recommend trading only with Strong and Extreme orderblocks, because they are proved to be of much greater quality than classic orderblocks and they work quite well in mid-term and long-term trading strategies. Classic orderblocs can be used for short-term trading strategies, but even in this case these OBs cannot be blindly trusted;
We strongly advise against take for a trading orderblocks, which were spotted by cancellation filter, because they are considered to be voided of liquidity;
Don't forget that you can toggle different types of OBs, MTF settings and visual settings in the settings of the indicator and fine-tune them to your liking.
🏁 AFTERWORD
AQPRO Block Force is an indicator which designed with idea of helping trading save time on automatically detecting valuable orderblocks on the chart, evaluate their strength and filter out bad orderblocks. These employ the best principles of SMC, including FVGs, valid pullbacks and etc. FVGs play the key role in validating the existence of a particular orderblock and work in tandem with valid pullback to determine the maximum amount of true FVGs even in the most cluttered impulse/correction moves of the price. Our filters — Age Filter and Cancellation Filter — enhance the quality of the orderblocks by allowing only the newest and liquid orderblocks to appear on the chart. Additional MTF functionality allow trader to see orderblocks from other timeframe, which can be chosen in the settings, and get a sense of where the global liquidity resides. This indicator will be a useful confirmation tool to any trading strategy, but the SMC traders will surely get the most benefits out of it.
ℹ️ If you have questions about this or any other our indicator, please leave it in the comments.
BPCO Z-ScoreBPCO Z-Score with Scaled Z-Value and Table
Description:
This custom indicator calculates the Z-Score of a specified financial instrument (using the closing price as a placeholder for the BPCO value), scales the Z-Score between -2 and +2 based on user-defined thresholds, and displays it in a table for easy reference.
The indicator uses a simple moving average (SMA) and standard deviation to calculate the original Z-Score, and then scales the Z-Score within a specified range (from -2 to +2) based on the upper and lower thresholds set by the user.
Additionally, the scaled Z-Score is displayed in a separate table on the right side of the chart, providing a clear, numerical value for users to track and interpret.
Key Features:
BPCO Z-Score: Calculates the Z-Score using a simple moving average and standard deviation over a user-defined window (default: 365 days). This provides a measure of how far the current price is from its historical average in terms of standard deviations.
Scaled Z-Score: The original Z-Score is then scaled between -2 and +2, based on the user-specified upper and lower thresholds. The thresholds default to 3.5 (upper) and -1.5 (lower), and can be adjusted as needed.
Threshold Bands: Horizontal lines are plotted on the chart to represent the upper and lower thresholds. These help visualize when the Z-Score crosses critical levels, indicating potential market overbought or oversold conditions.
Dynamic Table Display: The scaled Z-Score is shown in a dynamic table at the top-right of the chart, providing a convenient reference for traders. The table updates automatically as the Z-Score fluctuates.
How to Use:
Adjust Time Window: The "Z-Score Period (Days)" input allows you to adjust the time period used for calculating the moving average and standard deviation. By default, this is set to 365 days (1 year), but you can adjust this depending on your analysis needs.
Set Upper and Lower Thresholds: Use the "BPCO Upper Threshold" and "BPCO Lower Threshold" inputs to define the bands for your Z-Score. The default values are 3.5 for the upper band and -1.5 for the lower band, but you can adjust them based on your strategy.
Interpret the Z-Score: The Z-Score provides a standardized measure of how far the current price (or BPCO value) is from its historical mean, relative to the volatility. A value above the upper threshold (e.g., 3.5) may indicate overbought conditions, while a value below the lower threshold (e.g., -1.5) may indicate oversold conditions.
Use the Scaled Z-Score: The scaled Z-Score is calculated based on the original Z-Score, but it is constrained to a range between -2 and +2. When the BPCO value hits the upper threshold (3.5), the scaled Z-Score will be +2, and when it hits the lower threshold (-1.5), the scaled Z-Score will be -2. This gives you a clear, easy-to-read value to interpret the market's condition.
Data Sources:
BPCO Data: In this indicator, the BPCO value is represented by the closing price of the asset. The calculation of the Z-Score and scaled Z-Score is based on this price data, but you can modify it to incorporate other data streams as needed (e.g., specific economic indicators or custom metrics).
Indicator Calculation: The Z-Score is calculated using the following formulas:
Mean (SMA): A simple moving average of the BPCO (close price) over the selected period (365 days by default).
Standard Deviation (Std): The standard deviation of the BPCO (close price) over the same period.
Z-Score: (Current BPCO - Mean) / Standard Deviation
Scaled Z-Score: The Z-Score is normalized to fall within a specified range (from -2 to +2), based on the upper and lower threshold inputs.
Important Notes:
Customization: The indicator allows users to adjust the period (window) for calculating the Z-Score, as well as the upper and lower thresholds to suit different timeframes and trading strategies.
Visual Aids: Horizontal lines are drawn to represent the upper and lower threshold levels, making it easy to visualize when the Z-Score crosses critical levels.
Limitations: This indicator relies on historical price data (or BPCO) and assumes that the standard deviation and mean are representative of future price behavior. It does not account for potential market shifts or extreme events that may fall outside historical norms.
SOPR with Z-Score Table📊 Glassnode SOPR with Dynamic Z-Score Table
ℹ️ Powered by Glassnode On-Chain Metrics
📈 Description:
This indicator visualizes the Spent Output Profit Ratio (SOPR) for major cryptocurrencies — Bitcoin, Ethereum, and Litecoin — along with a dynamically normalized Z-Score. SOPR is a key on-chain metric that reflects whether coins moved on-chain are being sold at a profit or a loss.
🔍 SOPR is calculated using Glassnode’s entity-adjusted SOPR feed, and a custom SMA is applied to smooth the signal. The normalized Z-Score helps identify market sentiment extremes by scaling SOPR relative to its historical context.
📊 Features:
Selectable cryptocurrency: Bitcoin, Ethereum, or Litecoin
SOPR smoothed by user-defined SMA (default: 10 periods)
Upper & lower bounds (±4%) for SOPR, shown as red/green lines
Background highlighting when SOPR moves outside normal range
Normalized Z-Score scaled between –2 and +2
Live Z-Score display in a compact top-right table
🧮 Calculations:
SOPR data is sourced daily from Glassnode:
Bitcoin: XTVCBTC_SOPR
Ethereum: XTVCETH_SOPR
Litecoin: XTVCLTC_SOPR
Z-Score is calculated as:
SMA of SOPR over zscore_length periods
Standard deviation of SOPR
Z-Score = (SOPR – mean) / standard deviation
Z-Score is clamped between –2 and +2 for visual consistency
🎯 Interpretation:
SOPR > 1 implies coins are sold in profit
SOPR < 1 suggests coins are sold at a loss
When SOPR is significantly above or below its recent range (e.g., +4% or –4%), it may signal overheating or capitulation
The Z-Score contextualizes how extreme the current SOPR is relative to history
📌 Notes:
Best viewed on daily charts
Works across selected assets (BTC, ETH, LTC)
MVRVZ BTCMVRVZ BTC (Market Value to Realized Value Z-Score)
Description:
The MVRVZ BTC indicator provides insights into the relationship between the market value and realized value of Bitcoin, using the Market Value to Realized Value (MVRV) ratio, which is then adjusted using a Z-Score. This indicator highlights potential market extremes and helps in identifying overbought or oversold conditions, offering a unique perspective on Bitcoin's valuation.
How It Works:
MVRVZ is calculated by taking the difference between Bitcoin's Market Capitalization (MC) and Realized Capitalization (MCR), then dividing that by the Standard Deviation (Stdev) of the price over a specified period (usually 104 weeks).
The resulting value is plotted as the MVRVZ line, representing how far the market price deviates from its realized value.
Z-Score is then applied to the MVRVZ line, with the Z-Score bounded between +2 and -2, which allows it to be used within a consistent evaluation framework, regardless of how high or low the MVRVZ line goes. The Z-Score will reflect overbought or oversold conditions:
A Z-Score above +2 indicates the market is likely overbought (possible market top).
A Z-Score below -2 indicates the market is likely oversold (possible market bottom).
Values between -2 and +2 indicate more neutral market conditions.
How to Read the Indicator:
MVRVZ Line:
The MVRVZ line shows the relationship between market cap and realized cap. A higher value indicates the market is overvalued relative to the actual capital realized by holders.
The MVRVZ line can move above or below the top and bottom lines you define, which are adjustable according to your preferences. These lines act as trigger levels.
Top and Bottom Trigger Lines:
You can customize the Top Line and Bottom Line values to your preference.
When the MVRVZ line crosses the Top Line, the market might be considered overbought.
When the MVRVZ line crosses the Bottom Line, the market might be considered oversold.
SCDA Z-Score:
The Z-Score is displayed alongside the MVRVZ line and is bounded between -2 and +2. It scales proportionally based on the MVRVZ line's position relative to the top and bottom trigger lines.
The Z-Score ensures that even if the MVRVZ line moves beyond the trigger lines, the Z-Score will stay within the limits of -2 to +2, making it ideal for your custom evaluation system (SCDA).
Background Highlighting:
The background color changes when the MVRVZ line crosses key levels:
When the MVRVZ line exceeds the Top Trigger, the background turns red, indicating overbought conditions.
When the MVRVZ line falls below the Bottom Trigger, the background turns green, indicating oversold conditions.
Data Sources:
The data for the MVRVZ indicator is sourced from Glassnode and Coinmetrics, which provide the necessary values for:
BTC Market Cap (MC) – The total market capitalization of Bitcoin.
BTC Realized Market Cap (MCR) – The capitalization based on the price at which Bitcoin was last moved on the blockchain (realized value).
How to Use the Indicator:
Market Extremes:
Use the MVRVZ and Z-Score to spot potential market tops or bottoms.
A high Z-Score (above +2) suggests the market is overbought, while a low Z-Score (below -2) suggests the market is oversold.
Adjusting the Triggers:
Customize the Top and Bottom Trigger Lines to suit your trading strategy. These lines can act as dynamic reference points for when to take action based on the Z-Score or MVRVZ line crossing these levels.
Market Evaluation (SCDA Framework):
The bounded Z-Score (from -2 to +2) is tailored for your SCDA evaluation system, allowing you to assess market conditions based on consistent criteria, no matter how volatile the MVRVZ line becomes.
Conclusion:
The MVRVZ BTC indicator is a powerful tool for assessing the relative valuation of Bitcoin based on its market and realized capitalization. By combining it with the Z-Score, you get an easy-to-read, bounded evaluation system that highlights potential market extremes and helps you make informed decisions about Bitcoin's price behavior.
ETI IndicatorThe Ensemble Technical Indicator (ETI) is a script that combines multiple established indicators into one single powerful indicator. Specifically, it takes a number of technical indicators and then converts them into +1 to represent a bullish trend, or a -1 to represent a bearish trend. It then adds these values together and takes the running sum over the past 20 days.
The ETI is composed of the following indicators and converted to +1 or -1 using the following criteria:
Simple Moving Average (10 days) : When the price is above the 10-day simple moving averaging, +1, when below -1
Weighted Moving Average (10 days) : Similar to the SMA 10, when the the price is above the 10-day weighted moving average, +1, when below -1
Stochastic K% : If the current Stochastic K% is greater than the previous value, then +1, else -1.
Stochastic D% : Similar to the Stochastic K%, when the current Stochastic D% is greater than the previous value, +1, else -1.
MACD Difference : First subtract the MACD signal (i.e. the moving average) from the MACD value and if the current value is higher than the previous value, then +1, else -1.
William's R% : If the current William's R% is greater than the previous one, then +1, else -1.
William's Accumulation/Distribution : If the current William's AD value is greater than the previous value, then +1, else -1.
Commodity Channel Index : If the Commodity Channel Index is greater than 200 (overbought), then -1, if it is less than -200 (oversold) then +1. When it is between those values, if the current value is greater than the previous value then +1, else -1.
Relative Strength Index : If the Relative Strength Index is over 70 (overbought) then -1 and if under 30 (oversold) then +1. If the Relative Strength Indicator is between those values then if the current value is higher than the previous value +1, else -1.
Momentum (9 days) : If the momentum value is greater than 0, then +1, else -1.
Again, once these values have been calculated and converted, they are added up to produce a single value. This single value is then summed across the previous 20 candles to produce a running sum.
By coalescing multiple technical indicators into a single value across time, traders can better understand how multiple inter-related indicators are behaving at once; high scores indicate that numerous indicators are showing bullish signals indicating a potential or ongoing uptrend (and vice-versa with low scores).
Additional Features
Numerous smoothing transformations have also been added (e.g. gaussian smoothing) to remove some of the noise might exist.
Suggested Use
It is recommended that stocks are shorted when the cross below 0, and are bought when the ETI crosses above -40. Arrows can be shown on the indicator to show these points. However feel free to use levels that work best for you.
Traditionally, I have treated values above +50 as overbought and below -40 as undersold (with -80 indicating extremely oversold); however these levels could also indicate either upwards and downwards momentum so taking a position based on where the ETI is (rather than crossing levels) should be done with caution.
Capital Flow StrengthCapital Flow Strength Indicator Guide
This is a comprehensive technical indicator that measures capital flow into or out of an asset, combined with volume analysis. Here's how to use it effectively:
Basic Understanding
The indicator shows capital flow strength on a scale from -100 to +100
Positive values (green) indicate money flowing into the asset
Negative values (red) indicate money flowing out
The blue/gray volume bars show relative volume compared to recent average
Key Components
Capital Flow Line
Green line above zero: Buying pressure dominates
Red line below zero: Selling pressure dominates
Crossing zero: Potential shift in market sentiment
Reference Lines
0 line: Neutral balance between buyers and sellers
+50 line: Strong buying pressure
-50 line: Strong selling pressure
Volume Strength Bars
Blue bars: Volume exceeding threshold (currently 1.5x average)
Gray bars: Normal volume levels
Taller bars: Higher relative volume
Trading Applications
Entry Signals
Strong buying setup: Capital flow above +50 with blue volume bars
Strong selling setup: Capital flow below -50 with blue volume bars
Confirmation Tool
Use with price action and other indicators for confirmation
Strong readings are more reliable when volume is higher than average
Divergence Analysis
Bullish divergence: Price making lower lows but capital flow making higher lows
Bearish divergence: Price making higher highs but capital flow making lower highs
Customization Options
Length (14): Adjust the calculation period
Volume Threshold (1.5): Modify sensitivity to volume spikes
Alert Conditions
The indicator has two built-in alerts:
"Strong Capital Inflow" - triggers when flow > 50 with high volume
"Strong Capital Outflow" - triggers when flow < -50 with high volume
These alerts can help you identify significant buying or selling pressure as it emerges.
Correlation Drift📈 Correlation Drift
The Correlation Drift indicator is designed to detect shifts in market momentum by analyzing the relationship between correlation and price lag. It combines the principles of correlation analysis and lag factor measurement to provide a unique perspective on trend alignment and momentum shifts.
🔍 Core Concept:
The indicator calculates the Correlation vs PLF Ratio, which measures the alignment between an asset’s price movement and a chosen benchmark (e.g., BTCUSD). This ratio reflects how well the asset’s momentum matches the market trend while accounting for price lag.
📊 How It Works:
Correlation Calculation:
The script calculates the correlation between the asset and the selected benchmark over a specified period.
A higher correlation indicates that the asset’s price movements are in sync with the benchmark.
Price Lag Factor (PLF) Calculation:
The PLF measures the difference between long-term and short-term price momentum, dynamically scaled by recent volatility.
It highlights potential overextensions or lags in the asset’s price movements.
Combining Correlation and PLF:
The Correlation vs PLF Ratio combines these metrics to detect momentum shifts relative to the trend.
The result is a dynamic, smoothed histogram that visualizes whether the asset is leading or lagging behind the trend.
💡 How to Interpret:
Positive Values (Green/Aqua Bars):
Indicates bullish alignment with the trend.
Aqua: Rising bullish momentum, suggesting continuation.
Teal: Decreasing bullish momentum, signaling caution.
Negative Values (Purple/Fuchsia Bars):
Indicates bearish divergence from the trend.
Fuchsia: Falling bearish momentum, indicating increasing pressure.
Purple: Rising bearish momentum, suggesting potential reversal.
Clipping for Readability:
Values are clipped between -3 and +3 to prevent outliers from compressing the histogram.
This ensures clear visualization of typical momentum shifts while still marking extreme cases.
🚀 Best Practices:
Use Correlation Drift as a confirmation tool in conjunction with trend indicators (e.g., moving averages) to identify momentum alignment or divergence.
Look for transitions from positive to negative (or vice versa) as signals of potential trend shifts.
Combine with volume analysis to strengthen confidence in breakout or breakdown signals.
⚠️ Key Features:
Customizable Settings: Adjust the correlation length, PLF length, and smoothing factor to fine-tune the indicator for different market conditions.
Visual Gradient: The histogram changes color based on the strength and direction of the ratio, making it easy to identify shifts at a glance.
Zero Line Reference: Clearly distinguishes between bullish and bearish momentum zones.
🔧 Recommended Settings:
Correlation Length: 14 (for short to medium-term analysis)
PLF Length: 50 (to smooth out noise while capturing trend shifts)
Smoothing Factor: 3 (for enhanced clarity without excessive lag)
Benchmark Symbol: BTCUSD (or another relevant market indicator)
By providing a quantitative measure of trend alignment while accounting for price lag, the Correlation Drift indicator helps traders make more informed decisions during periods of momentum change. Whether you are trading crypto, forex, or equities, this tool can be a powerful addition to your momentum-based trading strategies.
⚠️ Disclaimer:
The Correlation Drift indicator is a technical analysis tool designed to aid in identifying potential shifts in market momentum and trend alignment. It is intended for informational and educational purposes only and should not be considered as financial advice or a recommendation to buy, sell, or hold any financial instrument.
Trading financial instruments, including cryptocurrencies, involves significant risk and may result in the loss of your capital. Past performance is not indicative of future results. Always conduct thorough research and seek advice from a certified financial professional before making any trading decisions.
The developer (RWCS_LTD) is not responsible for any trading losses or adverse outcomes resulting from the use of this indicator. Users are encouraged to test and validate the indicator in a simulated environment before applying it to live trading. Use at your own risk.
Session Stats + (dc_77)The "Session Stats + (dc_77)" indicator is a Pine Script tool designed to analyze trading sessions by plotting key price levels and statistical metrics. It displays a session's open price, manipulation levels (mean and median price movements), and distribution levels based on historical session data, with customizable time zones and session times. Users can toggle projections for 1-hour, 4-hour, daily, weekly, and monthly timeframes, showing average manipulation and distribution distances from the session open. Visual elements like shaded areas, labeled lines, and a vertical anchor line enhance readability, with options to filter data by day of the week. Alert conditions are included to notify users when the price crosses significant levels, such as the session open or manipulation/distribution thresholds.
Hurst Exponent Oscillator [PhenLabs]📊 Hurst Exponent Oscillator -
Version: PineScript™ v5
📌 Description
The Hurst Exponent Oscillator (HEO) by PhenLabs is a powerful tool developed for traders who want to distinguish between trending, mean-reverting, and random market behaviors with clarity and precision. By estimating the Hurst Exponent—a statistical measure of long-term memory in financial time series—this indicator helps users make sense of underlying market dynamics that are often not visible through traditional moving averages or oscillators.
Traders can quickly know if the market is likely to continue its current direction (trending), revert to the mean, or behave randomly, allowing for more strategic timing of entries and exits. With customizable smoothing and clear visual cues, the HEO enhances decision-making in a wide range of trading environments.
🚀 Points of Innovation
Integrates advanced Hurst Exponent calculation via Rescaled Range (R/S) analysis, providing unique market character insights.
Offers real-time visual cues for trending, mean-reverting, or random price action zones.
User-controllable EMA smoothing reduces noise for clearer interpretation.
Dynamic coloring and fill for immediate visual categorization of market regime.
Configurable visual thresholds for critical Hurst levels (e.g., 0.4, 0.5, 0.6).
Fully customizable appearance settings to fit different charting preferences.
🔧 Core Components
Log Returns Calculation: Computes log returns of the selected price source to feed into the Hurst calculation, ensuring robust and scale-independent analysis.
Rescaled Range (R/S) Analysis: Assesses the dispersion and cumulative deviation over a rolling window, forming the core statistical basis for the Hurst exponent estimate.
Smoothing Engine: Applies Exponential Moving Average (EMA) smoothing to the raw Hurst value for enhanced clarity.
Dynamic Rolling Windows: Utilizes arrays to maintain efficient, real-time calculations over user-defined lengths.
Adaptive Color Logic: Assigns different highlight and fill colors based on the current Hurst value zone.
🔥 Key Features
Visually differentiates between trending, mean-reverting, and random market modes.
User-adjustable lookback and smoothing periods for tailored sensitivity.
Distinct fill and line styles for each regime to avoid ambiguity.
On-chart reference lines for strong trending and mean-reverting thresholds.
Works with any price series (close, open, HL2, etc.) for versatile application.
🎨 Visualization
Hurst Exponent Curve: Primary plotted line (smoothed if EMA is used) reflects the ongoing estimate of the Hurst exponent.
Colored Zone Filling: The area between the Hurst line and the 0.5 reference line is filled, with color and opacity dynamically indicating the current market regime.
Reference Lines: Dash/dot lines mark standard Hurst thresholds (0.4, 0.5, 0.6) to contextualize the current regime.
All visual elements can be customized for thickness, color intensity, and opacity for user preference.
📖 Usage Guidelines
Data Settings
Hurst Calculation Length
Default: 100
Range: 10-300
Description: Number of bars used in Hurst calculation; higher values mean longer-term analysis, lower values for quicker reaction.
Data Source
Default: close
Description: Select which data series to analyze (e.g., Close, Open, HL2).
Smoothing Length (EMA)
Default: 5
Range: 1-50
Description: Length for smoothing the Hurst value; higher settings yield smoother but less responsive results.
Style Settings
Trending Color (Hurst > 0.5)
Default: Blue tone
Description: Color used when trending regime is detected.
Mean-Reverting Color (Hurst < 0.5)
Default: Orange tone
Description: Color used when mean-reverting regime is detected.
Neutral/Random Color
Default: Soft blue
Description: Color when market behavior is indeterminate or shifting.
Fill Opacity
Default: 70-80
Range: 0-100
Description: Transparency of area fills—higher opacity for stronger visual effect.
Line Width
Default: 2
Range: 1-5
Description: Thickness of the main indicator curve.
✅ Best Use Cases
Identifying if a market is regime-shifting from trending to mean-reverting (or vice versa).
Filtering signals in automated or systematic trading strategies.
Spotting periods of randomness where trading signals should be deprioritized.
Enhancing mean-reversion or trend-following models with regime-awareness.
⚠️ Limitations
Not predictive: Reflects current and recent market state, not future direction.
Sensitive to input parameters—overfitting may occur if settings are changed too frequently.
Smoothing can introduce lag in regime recognition.
May not work optimally in markets with structural breaks or extreme volatility.
💡 What Makes This Unique
Employs advanced statistical market analysis (Hurst exponent) rarely found in standard toolkits.
Offers immediate regime visualization through smart dynamic coloring and zone fills.
🔬 How It Works
Rolling Log Return Calculation:
Each new price creates a log return, forming the basis for robust, non-linear analysis. This ensures all price differences are treated proportionally.
Rescaled Range Analysis:
A rolling window maintains cumulative deviations and computes the statistical “range” (max-min of deviations). This is compared against the standard deviation to estimate “memory”.
Exponent Calculation & Smoothing:
The raw Hurst value is translated from the log of the rescaled range ratio, and then optionally smoothed via EMA to dampen noise and false signals.
Regime Detection Logic:
The smoothed value is checked against 0.5. Values above = trending; below = mean-reverting; near 0.5 = random. These control plot/fill color and zone display.
💡 Note:
Use longer calculation lengths for major market character study, and shorter ones for tactical, short-term adaptation. Smoothing balances noise vs. lag—find a best fit for your trading style. Always combine regime awareness with broader technical/fundamental context for best results.
Risk Calculator Manual Only### Indicator Name: Risk Calculator Manual Only
Description:
This indicator is designed for manual risk and position size calculation. It helps traders manage risk per trade by clearly displaying key trade parameters on the chart in an easy-to-read table format. The indicator does not auto-calculate entry, stop, or target prices—all values must be entered manually, giving full control to the trader.
Key Features:
- Manual input only: Users manually enter the entry price, stop-loss, and take-profit levels.
- On-chart data table: Displays all calculated metrics in a compact, color-coded table:
- Trade Type: Long or Short, selectable in settings.
- Entry Price, Stop-Loss, Take-Profit: Entered by the user.
- Position Size ($): Automatically calculated based on your risk amount and stop-loss distance.
- Profit ($): Potential profit based on take-profit level.
- Loss ($): Potential loss based on stop-loss level.
- Color coding:
- Profit row is highlighted in green.
- Loss row is highlighted in red.
- Alerts: Optional alerts when price hits the stop-loss or take-profit levels.
How to Use:
1. Enter your planned entry price, stop-loss, and take-profit in the indicator settings.
2. Set your risk amount per trade (in USD).
3. The indicator will calculate the appropriate position size, potential profit, and loss, and display them in a visual table.
4. Enable alerts if you want to be notified when price reaches your stop-loss or take-profit.
Benefits:
- Helps enforce disciplined risk management.
- Visual feedback on key trade metrics, directly on the chart.
- Fast, manual trade planning with no automation—ideal for discretionary traders.
- Supports both long and short trade types.
Notes:
- This tool assumes accurate manual input. It does not auto-detect price levels.
- Best used by traders who prefer full control over their risk setup and calculations.
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Statistical Reliability Index (SRI)Statistical Reliability Index (SRI)
The Statistical Reliability Index (SRI) is a professional financial analysis tool designed to assess the statistical stability and reliability of market conditions. It combines advanced statistical methods to gauge whether current market trends are statistically consistent or prone to erratic behavior. This allows traders to make more informed decisions when navigating trending and choppy markets.
Key Concepts:
1. Extrapolation of Cumulative Distribution Functions (CDF)
What is CDF?
A Cumulative Distribution Function (CDF) is a statistical tool that models the probability of a random variable falling below a certain value.
How it’s used in SRI:
The SRI utilizes the 95th percentile CDF of recent returns to estimate the likelihood of extreme price movements. This helps identify when a market is experiencing statistically significant changes, crucial for forecasting potential breakouts or breakdowns.
Weight in SRI:
The weight of the CDF extrapolation can be adjusted to emphasize its impact on the overall reliability index, allowing customization based on the trader's preference for tail risk analysis.
2. Bias Factor (BF)
What is the Bias Factor?
The Bias Factor measures the ratio of the current market price to the expected mean price calculated over a defined period. It represents the deviation from the typical price level.
How it’s used in SRI:
A higher bias factor indicates that the current price significantly deviates from the historical average, suggesting a potential mean reversion or trend exhaustion.
Weight in SRI:
Adjusting the Bias Factor weight lets users control how much this deviation influences the SRI, balancing between momentum trading and mean reversion strategies.
3. Coefficient of Variation (CV)
What is CV?
The Coefficient of Variation (CV) is a statistical measure that expresses the ratio of the standard deviation to the mean. It indicates the relative variability of asset returns, helping gauge the risk-to-return consistency.
How it’s used in SRI:
A lower CV indicates more stable and predictable price behavior, while a higher CV signals increased volatility. The SRI incorporates the inverse of the normalized CV to reflect price stability positively.
Weight in SRI:
By adjusting the CV weight, users can prioritize consistent price movements over erratic volatility, aligning the indicator with risk tolerance and strategy preferences.
Interpreting the SRI:
1. SRI Plot:
The SRI plot dynamically changes color to reflect market conditions:
Aqua Line: Indicates uptrend stability, signaling statistically consistent upward movements.
Fuchsia Line: Indicates downtrend stability, where statistically reliable downward movements are present.
The overlay background shifts between colors:
Aqua Background: Signifies statistical stability, where trends are historically consistent.
Fuchsia Background: Indicates statistical instability, often associated with trend uncertainty.
Yellow Background: Marks choppy periods, where statistical data suggests that market conditions are not conducive to reliable trading.
2. SRI Volatility Plot:
Displays the volatility of the SRI itself to detect when the indicator is stable or unstable:
Blue Area Fill: Signifies that the SRI is stable, indicating trending conditions.
Yellow Area Fill: Represents choppy or unstable SRI movements, suggesting sideways or unreliable market conditions.
A Chop Threshold Line (dotted yellow) highlights the maximum acceptable SRI volatility before the market is considered too unpredictable.
3. Stability Assessment:
Stable Trend (No Chop):
The SRI is smooth and consistent, often accompanied by aqua or fuchsia lines.
Volatility remains below the chop threshold, indicating a low-risk, trend-following environment.
Chop Mode:
The SRI becomes erratic, and the volatility plot spikes above the threshold.
Marked by a yellow shaded background, indicating uncertain and non-trending conditions.
[Trend Identification:
Use the color-coded SRI line and background to determine uptrend or downtrend reliability.
Be cautious when the SRI volatility plot shows yellow, as this signals trading conditions may not be reliable.
Practical Use Cases:
Trend Confirmation:
Utilize the SRI plot color and background to confirm whether a detected trend is statistically reliable.
Chop Mode Filtering:
During yellow chop periods, it is advisable to reduce trading activity or adopt range-bound strategies.
Strategy Filter:
Combine the SRI with trend-following indicators (like moving averages) to enhance entry and exit accuracy.
Volatility Monitoring:
Pay attention to the SRI volatility plot, as spikes often precede erratic price movements or trend reversals.
Disclaimer:
The Statistical Reliability Index (SRI) is a technical analysis tool designed to aid in market stability assessment and trend validation. It is not intended as a standalone trading signal generator. While the SRI can help identify statistically reliable trends, it is essential to incorporate additional technical and fundamental analysis to make well-informed trading decisions.
Trading and investing involve substantial risk, and past performance does not guarantee future results. Always use risk management practices and consult with a financial advisor to tailor strategies to your individual risk profile and objectives.
h1 net change [keypoems]Hourly Net Change Standard Deviation Projections
What it actually does: it shows statistical hourly levels based on the average net change of each specific hour candle.
For every hourly candle the script:
- Shows the hourly open
- Calculates two volatility sets:
- Overall Stdev (which is fixed calculated over 10 years of data)
- Per-hour Stdev levels, it draws ±0.5σ / ±1σ / ±1.5σ / ±2σ bands in both sets.
Why it matters: Those rails are statistical “speed limits”. Price hugging a +1σ per-hour line? Momentum could shift.
The overlay lets you eyeball mean-reversion vs breakout conditions without a single calculation.
cc AJGB Candle Range Finder with TableOverview:
The "cc AJGB Candle Range Finder with Table" is a versatile Pine Script indicator designed to identify and visualize price ranges within the 1 minute charts based on UTC+2 Time Zone. Unlike traditional range indicators, it offers three unique calculation methods to define ranges based on minute and hour interactions, displays ranges as boxes with labeled point values, and summarizes average range sizes in a customizable table. This tool is ideal for analyzing price ranges of specific time based ranges.
Features:
Customizable Time Range: Users specify a start and end minute (0-59) to define the range period (e.g., 29th to 35th minute).
Three Calculation Methods:
Minute Only: Uses the minute of each bar to identify ranges (e.g., matches user-specified minutes).
Minute - Hour: Adjusts the minute by subtracting the hour, allowing for dynamic range detection across hourly cycles.
Minute + Hour: Combines minute and hour values for a unique range calculation, useful for specific intraday patterns.
Visual Output: Draws boxes around detected ranges, with labels showing the start/end minutes and range size in points.
Summary Table: Displays the average range size (in points) for each method, with customizable position, colors, and text size.
How It Works:
The indicator evaluates each bar’s timestamp in (UTC+2 ONLY) to match user-specified minutes using one or more selected methods. When a start minute is detected, it tracks the high and low prices until the end minute, drawing a box to highlight the range and labeling it with the range size in points. A table summarizes the average range size for each method, helping traders assess typical price movements during the specified period.
Market Analysis: Compare range sizes across different methods to understand intraday volatility patterns.
Settings Customization: Adjust colors, table position, and label sizes to suit your chart preferences.
Settings:
Range to Find: Set start and end minutes.
Range Selection: Enable/disable each method and customize colors.
Range Label Size: Choose label size (Tiny to Huge).
Table Settings: Configure table position (Top, Bottom, Left, Right), sub-position, text size, and colors.
Notes:
Only works on 1 minute charts
The indicator works best using Start Times that are lower than the End Times.
Ensure the chart is set to UTC+2 Time Zone for accurate range detection.
Why It’s Unique:
Unlike standard range indicators that focus on sessions or fixed periods, this tool allows precise minute-based range detection with three distinct calculation methods, offering flexibility for data gathering. The interactive table provides quick insights into average range sizes.
Linear Regression Volume | Lyro RSLinear Regression Volume | Lyro RS
⚠️Disclaimer⚠️
Always combine this indicator with other forms of analysis and risk management. Please do your own research before making any trading decisions.
The LR Volume | 𝓛𝔂𝓻𝓸 𝓡𝓢 indicator blends linear regression with volume-adjusted moving average s to dynamically outline price equilibrium and trend intensity. By integrating volume into its regression model, it highlights meaningful price movement relative to trading activity.
📌 How It Works:
Volume-Weighted Regression Baseline
Price is filtered through one of four volume-adjusted moving averages (SMA, RMA, HMA, ALMA) before being passed through a linear regression model, forming a dynamic fair value line.
Deviation Bands
The indicator plots 1x, 2x, and 3x standard deviation zones above and below the baseline, helping identify potential extremes, volatility spikes, and mean reversion areas.
Slope-Based Color Logic
The baseline and fill areas are dynamically colored:
- 🟢 Green for positive slope (uptrend)
- 🔴 Red for negative slope (downtrend)
- ⚪ Gray for neutral movement
⚙️ Inputs & Options:
Regression Length – Controls how many bars are used in the moving average and regression calculation.
Deviation Multiplier – Adjusts the width of the bands surrounding the regression baseline.
MA Type – Choose from 4 types:
SMA (Simple Moving Average)
RMA (Relative Moving Average)
HMA (Hull Moving Average)
ALMA (Arnaud Legoux Moving Average)
Band Colors – Customizable upper/lower band colors to match your visual style.
🔔 Alerts:
Long Signal – Triggers when the regression slope turns positive.
Short Signal – Triggers when the regression slope turns negative.
Money Flow: In & Out Detector[THANHCONG]Indicator Name:
Money Flow: In & Out Detector
Indicator Description:
The Money Flow: In & Out Detector indicator uses technical indicators such as RSI (Relative Strength Index), MFI (Money Flow Index), and volume analysis to determine money inflow and outflow in the market.
This indicator helps traders identify changes in money flow, allowing them to detect buy and sell signals based on the combination of the following factors:
RSI > 50 and MFI > 50: Money inflow, indicating a buy signal.
RSI < 50 and MFI < 50: Money outflow, indicating a sell signal.
Volume increase/decrease relative to the average: Identifies strong market behavior changes.
Adjustable Parameters:
RSI Length: The number of periods to calculate the RSI (default is 14).
MFI Length: The number of periods to calculate the MFI (default is 14).
Volume MA Length: The number of periods to calculate the moving average of volume (default is 20).
Volume Increase/Decrease (%): The percentage threshold for volume change compared to the moving average (default is 20%).
Look Back Period: The number of periods used to identify peaks and troughs (default is 20).
How to Use the Indicator:
Money Inflow: When both RSI and MFI are above 50, and volume increases significantly relative to the moving average, the indicator shows a Buy signal.
Money Outflow: When both RSI and MFI are below 50, and volume decreases significantly relative to the moving average, the indicator shows a Sell signal.
Identifying Peaks and Troughs: The indicator also helps identify market peaks and troughs based on technical conditions.
Note:
This indicator assists in decision-making, but does not replace comprehensive market analysis.
Use this indicator in conjunction with other technical analysis methods to increase the accuracy of trade signals.
Steps for Publishing the Indicator on TradingView:
Log in to TradingView:
Go to TradingView and log into your account.
Access Pine Script Editor:
Click on Pine Editor from the menu under the chart.
Paste your Pine Script® code into the editor window.
Check the Source Code:
Ensure your code is error-free and running correctly.
Review the entire source code and add the MPL-2.0 license notice if necessary.
Save and Publish:
After testing and confirming the code works correctly, click Add to Chart to try the indicator on your chart.
If satisfied with the result, click Publish Script at the top right of the Pine Editor.
Provide a name for the indicator and then enter the detailed description you’ve prepared.
Ensure you specify the MPL-2.0 license in the description if required.
Choose the Access Type:
You can choose either Public or Private access for your indicator depending on your intention.
Submit for Publication:
Wait for TradingView to review and approve your indicator. Typically, this process takes a few working days for verification and approval.
User Guide:
You can share detailed instructions for users on how to use the indicator on TradingView, including how to adjust the parameters and interpret the signals. For example:
Set RSI Length: Experiment with different RSI Length values to find the sensitivity that suits your strategy.
Interpreting In/Out Signals: When there is strong money inflow (In), consider entering a buy order. When there is strong money outflow (Out), consider selling.
CorrelationMulti-Timeframe Correlation Indicator
This Pine Script indicator measures the correlation between the current symbol and a reference symbol (default: GLD) across three different timeframes. It provides traders with valuable insights into how assets move in relation to each other over short, medium, and long-term periods.
Key Features
Multiple Timeframe Analysis: Calculates correlation coefficients over three customizable periods (default: 20, 50, and 200 bars)
Visual Reference Lines: Displays horizontal lines at +1, 0, and -1 to indicate perfect positive correlation, no correlation, and perfect negative correlation
Color-Coded Outputs: Shows short-term correlation in green, medium-term in yellow, and long-term in red for easy visual interpretation
Understanding Correlation
The correlation coefficient measures the statistical relationship between two data series, ranging from -1 to +1:
+1: Perfect positive correlation (both assets move together in the same direction)
0: No correlation (movements are random and independent)
-1: Perfect negative correlation (assets move in opposite directions)
How To Use This Indicator
Market Relationships: Identify how strongly your current asset correlates with the reference symbol
Diversification Analysis: Find assets with negative correlations to build a diversified portfolio
Divergence Opportunities: Watch for changes in correlation patterns that might signal trading opportunities
Trend Confirmation: Use correlation with benchmark assets to confirm broader market trends
Customization Options
Reference Symbol: Change the default GLD to any other symbol you want to compare against
Period Lengths: Adjust the short, medium, and long timeframes to match your trading strategy and timeframe
This indicator helps traders make more informed decisions by understanding the interrelationships between different assets across various timeframes, potentially improving portfolio construction and risk management strategies.
Daily Average 5m Candle SizeThis indicator measures the average size of each 5 min candle then works out the end of day average for you. Very important for profit targets and stops
Daily Price RangeThe indicator is designed to analyze an instrument’s volatility based on daily extremes (High-Low) and to compare the current day’s range with the typical (median) range over a selected period. This helps traders assess how much of the "usual" daily movement has already occurred and how much may still be possible during the trading day.
Ceres Trader Inv DXY % OverlayIntroducing the “Inverse DXY % Overlay” for TradingView
What it does:
• Plots the U.S. Dollar Index (DXY) as an inverted %-change line directly over your primary chart (e.g. XAUUSD).
• Dollar strength shows as a downward line; dollar weakness shows as an upward line—instantly highlighting negative correlation.
Why it helps:
• Trend confirmation – Ride Gold breakouts only when the dollar is actually weakening.
• Divergence signals – Spot early turn setups when Gold and DXY % don’t move in sync.
• Risk management – Trim or tighten stops when the dollar pivots against your position.
Key features:
Overlay on any symbol (Gold, Silver, Oil, Crypto, equities)
Auto-scaled to left-axis %, so your price chart stays on the right
Lightweight & transparent—1 px grey line, minimal clutter
Now you’ll have a real-time, inverted DXY % line beneath your candles—perfect for gauging USD flow before you pull the trigger on any trade.
Happy trading! 🚀
—Michael (Ceres Trader)
Price Lag Factor (PLF)📊 Price Lag Factor (PLF) for Crypto Traders: A Comprehensive Breakdown
The Price Lag Factor (PLF) is a momentum indicator designed to identify overextended price movements and gauge market momentum. It is particularly optimized for the crypto market, which is known for its high volatility and rapid trend shifts.
🔎 What is the Price Lag Factor (PLF)?
The PLF measures the difference between long-term and short-term price momentum and scales it dynamically based on recent volatility. This helps traders identify when the market might be overbought or oversold while filtering out noise.
The formula used in the PLF calculation is:
PLF = (Z-Long - Z-Short) / Stdev(PLF)
Where:
Z-long: Z-score of the long-term moving average (50-period by default).
Z-short: Z-score of the short-term moving average (14-period by default).
Stdev(PLF): Standard deviation of the PLF over a longer period (50-period by default).
🧠 How to Interpret the PLF:
1. Trend Direction:
Positive PLF (Green Bars): Indicates bullish momentum. The long-term trend is up, and short-term movements are confirming it.
Negative PLF (Red Bars): Indicates bearish momentum. The long-term trend is down, and short-term movements are consistent with it.
2. Momentum Strength:
PLF near Zero (±0.5): Low momentum; trend direction is not strong.
PLF between ±1 and ±2: Moderate momentum, indicating that the market is moving with strength but not in an overextended state.
PLF beyond ±2: High momentum (overbought/oversold), indicating potential trend exhaustion and a possible reversal.
📈 Trading Strategies:
1. Trend Following:
Bullish Signal:
Enter long when PLF crosses above 0 and remains green.
Confirm with other indicators like RSI or MACD to reduce false signals.
Bearish Signal:
Enter short when PLF crosses below 0 and remains red.
Use trend confirmation (e.g., moving average crossover) for better accuracy.
2. Reversal Trading:
Overbought Signal:
If PLF rises above +2, look for signs of bearish divergence or a reversal pattern to consider a short entry.
Oversold Signal:
If PLF falls below -2, watch for bullish divergence or a support bounce to consider a long entry.
3. Momentum Divergence:
Bullish Divergence:
Price makes a lower low while PLF makes a higher low.
Indicates weakening bearish momentum and a potential bullish reversal.
Bearish Divergence:
Price makes a higher high while PLF makes a lower high.
Signals weakening bullish momentum and a potential bearish reversal.
💡 Best Practices:
Combine with Volume:
Volume spikes during high PLF readings can confirm trend continuation.
Low volume during PLF extremes may hint at false breakouts.
Watch for Extreme Levels:
PLF beyond ±2 suggests overextended price action. Use caution when entering new positions.
Confirm with Other Indicators:
Use with Relative Strength Index (RSI) or Bollinger Bands to get a better sense of overbought/oversold conditions.
Overlay with a moving average to gauge trend consistency.
🚀 Why the PLF Works for Crypto:
Crypto markets are highly volatile and prone to rapid trend changes. The PLF's adaptive scaling ensures it remains relevant regardless of market conditions.
It highlights momentum shifts more accurately than static indicators because it accounts for changing volatility in its calculation.
🚨 Disclaimer for Traders Using the Price Lag Factor (PLF) Indicator:
The Price Lag Factor (PLF) indicator is designed as a technical analysis tool to gauge momentum and identify potential overbought or oversold conditions. However, it should not be relied upon as a sole decision-making factor for trading or investing.
Important Points to Consider:
Market Risk: Trading cryptocurrencies and other financial assets involves significant risk. The PLF may not accurately predict future price movements, especially during unexpected market events.
Indicator Limitations: No technical indicator, including the PLF, is infallible. False signals can occur, particularly in low-volume or highly volatile conditions.
Supplementary Analysis: Always combine PLF insights with other technical indicators, fundamental analysis, and risk management strategies to make informed decisions.
Personal Judgment: Traders should use their own discretion when interpreting PLF signals and never trade based solely on this indicator.
No Guarantees: The PLF is designed for educational and informational purposes only. Past performance is not indicative of future results.
Always perform thorough research and consider consulting with a professional financial advisor before making any trading decisions.
Vietnamese Stock Market FTD (Follow Through Day) AlertA Pine Script implementing William O'Neil’s Follow Through Day (FTD) strategy for the Vietnamese stock market. It scans 7 predefined sector groups (Banks, Real Estate, Retail, etc.) to detect momentum breakouts.
Key Features :
Triggers an FTD signal when ≥X groups (default: 3) have ≥Y stocks (default: 2) rising above a Z% threshold (default: 5%) daily.
Highlights qualifying stocks by group in a dynamic label during alerts.
Visualizes strength via histograms and background shading.
Open-source under Mozilla Public License 2.0 .
Purpose : Identify institutional buying and potential market reversals.
Ultimate NATR█ | Overview
This N-ATR (Normalized Average True Range) volatility indicator illustrates the trend of percentage-based candle volatility over a self-defined number of bars (period). The primary objective of the indicator is to highlight periods of high or low volatility, which can be exploited within the cyclical logic of volatility contraction and expansion. If market behavior is inherently cyclical, it naturally follows that candle volatility itself also exhibits cyclical characteristics.
It can therefore be defined as a recurring pattern:
Low Volatility --> High Volatility --> Low Volatility -->
Here is a concrete example of the cyclical phases of volatility, which compresses during Accumulation or Distribution phases, and then explodes with a mark-up or mark-down in price.
█ | Features
🔵 Plots on Overlay false
Smoothed NATR Line
NATR's Fixed Levels
NATR's Standard Deviation Levels (Dynamic)
🔵 Elements, overlapped to the chart
Analytical and Statistical Tables
NATR Information Label
🔵 Customization
Button to calculate fixed or dynamic (auto-calculated) levels
Dark / light mode based on the layout background
Setting of the initial date for the calculation of N-ATR dependent functions
ATR period
Moving Average of the N-ATR
Data sample (number) on which to calculate the standard deviation of the N-ATR
Adjustment of the multiplicative coefficients of the standard deviation σ
Setting of static values L1, L2, L3, and L4 of the N-ATR
Adjustment of the table zoom factor
█ | N-ATR Calculation
The N-ATR function is built upon the ATR (Average True Range), the quintessential volatility indicator.
Once the ATR_period is defined, the N-ATR is calculated using the following formula:
N-ATR = 100 * ATR / close
A moving average of the N-ATR completes the main indicator curve (yellow), making the function smoother and less sensitive to the instantaneous fluctuations of individual candles.
SMA_natr = sum(natr_i) / ATR_period
natr = 100 * ta.atr(periodo_ATR) / close
media_natr = ta.sma(natr, media_len)
█ | Settings
Show selected calc period : allows you to display or hide a background color that extends from the initial calculation date to the current bar, or from the first available bar if the selected date is earlier.
Set data range for ST.DEV : this setting defines the number of bars over which the standard deviation is calculated—an essential foundational element for plotting the upper and lower curves relative to the N-ATR, as well as for defining the statistical ranges in the tables overlaid on the price chart.
Static Levels : these are user-defined input values representing N-ATR value thresholds, used to classify table values within the ranges L1–L2 / L2–L3 / L3–L4 / >L4. To be meaningful, the user is expected to conduct separate statistical analysis using a spreadsheet or external data analysis tools or languages.
Coefficients x, w, y : these are input values used in the code to calculate statistical ranges and the bands above and below the N-ATR. For example, when expressing the statistical range as μ ± nσ, n can take the value of x, w, or y. By default, the values are x=1, w=2, y=3. However, as explained, they can be customized to represent wider or narrower statistical clusters, depending on the user's analytical preference.
█ | Tables
Static Levels : when the boolean button "Fixed Levels" is active, the table counts and distributes the data across five ranges, defined by the custom input values L1, L2, L3, and L4. Studying the table immediately answers the question: "Have I set appropriate values for the L_x levels?"
If the majority of data points fall within the lowest range, it indicates that the levels are spaced too far apart; conversely, if most values are in the "> L4" range, the levels are likely too narrow.
From left to right, the table also displays the probability that the current candle might move from its current range to the next one (Update Prob.); the absolute frequency of each range and the relative frequency are shown in the rightmost column.
Dynamic Levels : alternatively, you can deselect "Fixed Levels" to obtain an auto-calculated / self-adjusting representation of the N-ATR and its bands, based on the standard deviation input settings. In this case, the table takes on a more statistical form, useful for analyzing the frequency of outliers beyond a certain standard deviation, as defined by the largest multiplicative coefficient "y".
This visualization may also be preferred when aiming to study the standard deviation of the N-ATR in greater depth for a given asset, timeframe, and configuration more broadly.
█ | Next-to-Price Label
Information in the label next to the live price: if the first settings button in the indicator, "Fixed levels", is enabled (true), a label appears next to the price showing information about the relative position of the N-ATR associated with the current candle.
Specifically, if:
natr ≤ L1, ⇨ "Minimum-"
natr > L1 and natr ≤ L2, ⇨ "Minimum+"
natr > L2 and natr ≤ L3, ⇨ "Neutral L3"
natr > L3 and natr ≤ L4, ⇨ "Topping L4"
natr > L4, ⇨ "Excess L4: natr > V4"
Additionally, the corresponding N-ATR range is displayed to the right of the evaluated category for the individual candle.
1-Please note: this allows you to avoid constantly checking the N-ATR curve, especially when working in full-screen mode and focusing solely on the price chart for a cleaner view.
2-Please note : unfortunately, the informational label is not available in Dynamic display mode.
█ | Conclusion
• This indicator captures a snapshot of market turbulence. Whether currently unfolding or approaching, the combination of volatility breakout forecasting with price structure analysis—further evaluated based on periods of compression or high turbulence—offers traders a powerful tool for identifying trend-aligned trade opportunities.
• The accompanying analytical tables enhance the indicator by enabling a statistical interpretation of the likelihood that certain excess thresholds will be reached. Based on this data, traders can gain deeper insight into the nature of the asset, identify outlier volatility levels, and strengthen the hedging of their trades. Used as a filter, this indicator significantly improves win rate potential.
Please note : the indicator is shown here on a black background. I suggest you trying it on a white layout as well, so you can decide which visualization best suits your preferences.
Position size Margin & Lot Calculator [Algo Star]Position Size Margin & Lot Calculator is a lightweight Pine v5 indicator that helps you scale into a trade with five incremental “steps.”
What it does:
Takes your total capital and leverage settings
Splits your risk into five proportioned entries
Shows both the USD margin required and the corresponding MT4/MT5 lot size for each entry
Why you’ll love it:
No manual calculations—everything is displayed in a neat on-chart table
Fully configurable: set your account size, leverage, contract size and price source
Ideal for pyramiding or averaging in with controlled risk at each step
Just add it to any chart, tweak your inputs, and immediately see exactly how much margin and how many lots to allocate at each of the five pre-defined steps—perfect for systematic position sizing without the headache.
