[killerbee] MTF RetracementKey Features
Multi-Timeframe (MTF) Analysis: Plot the high, low, and open from up to four user-defined higher timeframes. This allows you to see the bigger picture and identify key levels that institutional traders are watching.
Dynamic Support & Resistance: Lines are drawn at these key MTF levels and extend until price breaks through them, providing a clean and dynamic view of support and resistance.
Session Highlighting: Automatically draw boxes and high/low lines for the Asia, London, and RTH (Regular Trading Hours) sessions. This helps you understand the context of price action throughout the trading day.
Customizable Opening Price Lines: Pinpoint significant opening prices with dedicated lines for events like the "Midnight Open," "8:30 Open," and "9:30 Open."
"NQ STATS TABLE": A powerful statistical table that provides real-time insights:
Break/Hit Confirmation: Instantly see when a key MTF high/low has been broken or when an opening price has been retraced to.
9 AM Directional Bias: A bullish or bearish bias based on the close of the 9 AM (New York time) hourly candle.
Historical Probabilities: The table displays historical probabilities for price to either break a previous high/low or retrace to the open, based on the current hour of the trading session.
Extensive Customization: Nearly every visual aspect of the indicator can be customized to your preference, including colors, line styles, visibility of each component, and the position of the stats table.
How to Use
Identify Key Levels: The lines from the higher timeframes (HTF1, HTF2, etc.) represent significant support and resistance. Pay close attention to these levels as price approaches them.
Look for Breaks and Retracements:
When a high or low line is broken, the line will stop extending. This can signal a shift in market structure and a potential continuation in the direction of the break.
The "Open Line" for each timeframe represents the opening price. When the line stops extending, it means price has retraced back to that open, a common occurrence in the market.
Utilize the Sessions:
The Asia, London, and RTH boxes help you frame your trading day. The highs and lows of these sessions are often critical levels of support and resistance.
Breakouts from these session ranges can lead to strong directional moves.
Leverage the STATS TABLE:
Use the "Break" and "Hit" columns to quickly confirm when key levels have been breached or revisited.
The "Direction" row gives you a quick sentiment reading based on the 9 AM candle.
The "Trades Back %" and "High/Low Forms" provide a statistical edge by showing you the historical likelihood of certain price behaviors based on the time of day. This can help you decide whether to play for a breakout or a retracement.
在腳本中搜尋" TABLE "
Mavericks ORBMavericks ORB – Opening Range Breakout Zones
Overview:
Mavericks ORB is a fully customizable Opening Range Breakout (ORB) indicator designed for serious intraday traders. It dynamically plots the ORB range for your chosen session and timeframe (5 min, 15 min, or any custom range), projects powerful price zones above and below the range, and automatically includes key midpoints—giving you actionable levels for breakouts, reversals, and dynamic support/resistance.
How It Works:
Configurable Session & Duration:
Choose any session start time and range length (e.g., 5 or 15 minutes) to define your personal ORB window.
Automatic Range Detection:
The indicator marks the high, low, and midpoint of the ORB range as soon as your defined period completes.
Dynamic Zones & Midpoints:
Three replicated price zones are projected both above and below the initial ORB, each calculated using the original ORB’s range and evenly spaced. Each zone includes its own midpoint for nuanced trade management and target planning.
Pre-Market Levels:
Tracks pre-market high and low (with fully customizable colors), giving you crucial context as the regular session opens.
Session Range Visualization:
Highlights the defined trading session with an adjustable background color for easy visual tracking.
Real-Time Info Table:
Displays a summary of all key levels—ORB range, highs, lows, and pre-market levels—right on your chart.
Full Customization:
Adjust all colors, enable/disable session range shading, show/hide labels, and tweak all session settings to fit your trading style.
Key Features:
Select any ORB start time and duration (fully customizable)
Plots ORB High, Low, and Midpoint in real time
Automatically projects 3 zones above and 3 zones below, each with its own midpoint
Pre-market high/low detection and labeling
Configurable session shading for visual clarity
At-a-glance info table with all major levels
Multiple color customizations for all zones and lines
Ready-to-use alert conditions for session and pre-market events
How to Use:
Set your preferred ORB start time and duration (e.g., 9:30 AM, 5 min for US equities).
Watch as the ORB forms and updates in real time.
Once complete, the high, low, and midpoint are plotted.
Monitor the projected zones above and below.
Use these for breakouts, targets, or support/resistance.
Reference the info table for all levels and pre-market context.
Customize as you go: Adjust colors, shading, and session settings to your needs.
Who is this for?
Intraday traders who trade the opening range breakout strategy (stocks, futures, forex, crypto)
Price action traders who want clean, actionable levels
Anyone looking for a reliable, highly visual ORB framework on TradingView
Short Description (for TradingView):
Mavericks ORB is a customizable Opening Range Breakout indicator that plots your session’s high, low, midpoint, and projects three dynamic zones above and below the range including midpoints for powerful trade planning. Includes pre-market levels, session highlights, and a real-time info table. Perfect for intraday price action traders.
What Makes Mavericks ORB Unique?
Flexible: Works with any timeframe or session.
Visual: Clean, uncluttered, and fully customizable.
Strategic: Automatic zone and midpoint projection, not just lines.
Practical: At-a-glance info table and real pre-market context.
Alert-ready: Triggers for session and pre-market events.
If you want to include any tips or a personal note (some script publishers do), you could add:
Tip: Use the midpoints for partial profit-taking or to gauge momentum strength. Adjust your ORB window for different asset classes or volatility environments.
ZenAlgo - DominatorThis indicator provides a structured multi-ticker overview of market momentum and relative strength by analyzing short-term price behavior across selected assets in comparison with broader crypto dominance and Bitcoin/ETH performance.
Ticker and Market Data Handling
The script accepts up to 9 user-defined symbols (tickers) along with BTCUSD and ETHUSD. For each symbol:
It retrieves the current price.
It also requests the daily opening price from the "D" timeframe to compute intraday percentage change.
For BTC, ETH, and dominance (sum of BTC, USDT, and USDC dominance), daily change is calculated using this same method.
This comparison enables tracking relative performance from the daily open, which provides meaningful insight into intraday strength or weakness among different assets.
Dominance Logic
The indicator aggregates dominance data from BTC , USDT , and USDC using TradingView’s CRYPTOCAP indices. This combined dominance is used as a reference in directional and status calculations. ETH dominance is also analyzed independently.
Changes in dominance are used to infer whether market attention is shifting toward Bitcoin/stablecoins (typically indicating risk-off sentiment) or away from them (typically risk-on behavior, benefiting altcoins).
Price Direction Estimation
The script estimates directional bias using an EMA-based deviation technique:
A short EMA (user-defined lookback , default 4 bars) is calculated.
The current close is compared to the EMA to assess directional bias.
Recent candle changes are also inspected to confirm a consistent short-term trend (e.g., 3 consecutive higher closes for "up").
A small threshold is used to avoid classifying flat movements as trends.
This directionality logic is applied separately to:
The selected ticker's price
BTC price
Combined dominance
This allows the script to contextualize the movement of each asset within broader market conditions.
Market Status Evaluation
A custom function analyzes ETH and BTC dominance trends along with their relative strength to define the overall market regime:
Altseason is identified when BTC dominance is declining, ETH dominance rising, and ETH outperforms BTC.
BTC Season occurs when BTC dominance is rising, ETH dominance falling, and BTC outperforms ETH.
If neither condition is met, the state is Neutral .
This classification is shown alongside each ticker's row in the table and helps traders assess whether market conditions favor Bitcoin, Ethereum, or altcoins in general.
Ticker Status Classification
Each ticker is analyzed independently using the earlier directional logic. Its status is then determined as follows:
Full Bull : Ticker is trending up while dominance is declining or BTC is also rising.
Bullish : Ticker is trending up but not supported by broader bullish context.
Bearish : Ticker is trending down but without broader confirmation.
Full Bear : Ticker is trending down while dominance rises or BTC falls.
Neutral : No strong directional bias or conflicting context.
This classification reflects short-term momentum and macro alignment and is color-coded in the results table.
Table Display and Plotting
A configurable table is shown on the chart, which:
Displays the name and status of each selected ticker.
Optionally includes BTC, ETH, and market state.
Uses color-coding for intuitive interpretation.
Additionally, price changes from the daily open are plotted for each selected ticker, BTC, ETH, and combined dominance. These values are also labeled directly on the chart.
Labeling and UX Enhancements
Labels next to the current candle display price and percent change for each active ticker and for BTC, ETH, and combined dominance.
Labels update each bar, and old labels are deleted to avoid clutter.
Ticker names are dynamically shortened by stripping exchange prefixes.
How to Use This Indicator
This tool helps traders:
Spot early rotations between Bitcoin and altcoins.
Identify intraday momentum leaders or laggards.
Monitor which tickers align with or diverge from broader market trends.
Detect possible sentiment shifts based on dominance trends.
It is best used on lower to mid timeframes (15m–4h) to capture intraday to short-term shifts. Users should cross-reference with longer-term trend tools or structural indicators when making directional decisions.
Interpretation of Values
% Change : Measures intraday move from daily open. Strong positive/negative values may indicate breakouts or reversals.
Status : Describes directional strength relative to market conditions.
Market State : Gives a general bias toward BTC dominance, ETH strength, or altcoin momentum.
Limitations & Considerations
The indicator does not analyze liquidity or volume directly.
All logic is based on short-term movements and may produce false signals in ranging or low-volume environments.
Dominance calculations rely on external CRYPTOCAP indices, which may differ from exchange-specific flows.
Added Value Over Other Free Tools
Unlike basic % change tables or price overlays, this indicator:
Integrates dominance-based macro context into ticker evaluation.
Dynamically classifies market regimes (BTC season / Altseason).
Uses multi-factor logic to determine ticker bias, avoiding single-metric interpretation.
Displays consolidated information in a table and chart overlays for rapid assessment.
Multi-Timeframe Continuity Custom Candle ConfirmationMulti-Timeframe Continuity Custom Candle Confirmation
Overview
The Timeframe Continuity Indicator is a versatile tool designed to help traders identify alignment between their current chart’s candlestick direction and higher timeframes of their choice. By coloring bars on the current chart (e.g., 1-minute) based on the directional alignment with selected higher timeframes (e.g., 10-minute, daily), this indicator provides a visual cue for confirming trends across multiple timeframes—a concept known as Timeframe Continuity. This approach is particularly useful for day traders, swing traders, and scalpers looking to ensure their trades align with broader market trends, reducing the risk of trading against the prevailing momentum.
Originality and Usefulness
This indicator is an original creation, built from scratch to address a common challenge in trading: ensuring that price action on a lower timeframe aligns with the trend on higher timeframes. Unlike many trend-following indicators that rely on moving averages, oscillators, or other lagging metrics, this script directly compares the bullish or bearish direction of candlesticks across timeframes. It introduces the following unique features:
Customizable Timeframes: Users can select from a range of higher timeframes (5m, 10m, 15m, 30m, 1h, 2h, 4h, 1d, 1w, 1M) to check for alignment, making it adaptable to various trading styles.
Neutral Candle Handling: The script accounts for neutral candles (where close == open) on the current timeframe by allowing them to inherit the direction of the higher timeframe, ensuring continuity in trend visualization.
Table: A table displays the direction of each selected timeframe and the current timeframe, helping identify direction in the event you don't want to color bars.
Toggles for Flexibility: Options to disable bar coloring and the debug table allow users to customize the indicator’s visual output for cleaner charts or focused analysis.
This indicator is not a mashup of existing scripts but a purpose-built tool to visualize timeframe alignment directly through candlestick direction, offering traders a straightforward way to confirm trend consistency.
What It Does
The Timeframe Continuity Indicator colors bars on your chart when the direction of the current timeframe’s candlestick (bullish, bearish, or neutral) aligns with the direction of the selected higher timeframes:
Lime: The current bar (e.g., 1m) is bullish or neutral, and all selected higher timeframes (e.g., 10m) are bullish.
Pink: The current bar is bearish or neutral, and all selected higher timeframes are bearish.
Default Color: If the directions don’t align (e.g., 1m bar is bearish but 10m is bullish), the bar remains the default chart color.
The indicator also includes a debug table (toggleable) that shows the direction of each selected timeframe and the current timeframe, helping traders diagnose alignment issues.
How It Works
The script uses the following methodology:
1. Direction Calculation: For each timeframe (current and selected higher timeframes), the script determines the candlestick’s direction:
Bullish (1): close > open / Bearish (-1): close < open / Neutral (0): close == open
Higher timeframe directions are fetched using Pine Script’s request.security function, ensuring accurate data retrieval.
2. Alignment Check: The script checks if all selected higher timeframes are uniformly bullish (full_bullish) or bearish (full_bearish).
o A higher timeframe must have a clear direction (bullish or bearish) to trigger coloring. If any selected timeframe is neutral, alignment fails, and no coloring occurs.
3. Coloring Logic: The current bar is colored only if its direction aligns with the higher timeframes:
Lime if the higher timeframes are bullish and the current bar is bullish or neutral.
Maroon if the higher timeframes are bearish and the current bar is bearish or neutral.
If the current bar’s direction opposes the higher timeframe (e.g., 1m bearish, 10m bullish), the bar remains uncolored.
Users can disable bar coloring entirely via the settings, leaving bars in their default chart color.
4. Direction Table:
A table in the top-right corner (toggleable) displays the direction of each selected timeframe and the current timeframe, using color-coded labels (green for bullish, red for bearish, gray for neutral).
This feature helps traders understand why a bar is or isn’t colored, making the indicator accessible to users unfamiliar with Pine Script.
How to Use
1. Add the Indicator: Add the "Timeframe Continuity Indicator" to your chart in TradingView (e.g., a 1m chart of SPY).
2. Configure Settings:
Timeframe Selection: Check the boxes for the higher timeframes you want to compare against (default: 10m). Options include 5m, 10m, 15m, 30m, 1h, 2h, 4h, 1D, 1W, and 1M. Select multiple timeframes if you want to ensure alignment across all of them (e.g., 10m and 1d).
Enable Bar Coloring: Default: true (bars are colored lime or maroon when aligned). Set to false to disable coloring and keep the default chart colors.
Show Table: Default: true (table is displayed in the top-right corner). Set to false to hide the table for a cleaner chart.
3. Interpret the Output:
Colored Bars: Lime bars indicate the current bar (e.g., 1m) is bullish or neutral, and all selected higher timeframes are bullish. Maroon bars indicate the current bar is bearish or neutral, and all selected higher timeframes are bearish. Uncolored bars (default chart color) indicate a mismatch (e.g., 1m bar is bearish while 10m is bullish) or no coloring if disabled.
Direction Table: Check the table to see the direction of each selected timeframe and the current timeframe.
4. Example Use Case:
On a 1m chart of SPY, select the 10m timeframe.
If the 10m timeframe is bearish, 1m bars that are bearish or neutral will color maroon, confirming you’re trading with the higher timeframe’s trend.
If a 1m bar is bullish while the 10m is bearish, it remains uncolored, signaling a potential misalignment to avoid trading.
Underlying Concepts
The indicator is based on the concept of Timeframe Continuity, a strategy used by traders to ensure that price action on a lower timeframe aligns with the trend on higher timeframes. This reduces the risk of entering trades against the broader market direction. The script directly compares candlestick directions (bullish, bearish, or neutral) rather than relying on lagging indicators like moving averages or RSI, providing a real-time, price-action-based confirmation of trend alignment. The handling of neutral candles ensures that minor indecision on the lower timeframe doesn’t interrupt the visualization of the higher timeframe’s trend.
Why This Indicator?
Simplicity: Directly compares candlestick directions, avoiding complex calculations or lagging indicators.
Flexibility: Customizable timeframes and toggles cater to various trading strategies.
Transparency: The debug table makes the indicator’s logic accessible to all users, not just those who can read Pine Script.
Practicality: Helps traders confirm trend alignment, a key factor in successful trading across timeframes.
Time based Insights [Digit23]Description:
The NSE Trading Time Insights indicator is a powerful tool designed for traders on the National Stock Exchange (NSE) of India. It provides a comprehensive overview of different trading sessions throughout the day, offering valuable insights into market characteristics and potential trading strategies for each time period.
Key Features:
1. Dynamic Session Display: The indicator automatically detects the current trading session and highlights it in the table.
2. Customizable Table: Users can choose to display either a full table showing all sessions or focus on the current session only.
3. User-Editable Content: Time ranges, session characteristics, and trading insights are fully customizable by the user.
4. Visual Customization: Table position and color scheme can be adjusted to suit individual preferences.
5. Market Status Indicator: Clearly shows when the market is closed.
Sessions Covered:
1. Opening Bell
2. Mid-Morning
3. Lunch Hour
4. Early Afternoon
5. Power Hour
For each session, the indicator displays:
- Time Range
- Session Name
- Market Characteristics
- Trading Insights
Customization Options:
- Table Position: Choose from top-left, top-right, bottom-left, or bottom-right of the chart.
- Color Scheme: Customize colors for header, cells, highlighting, and market closed status.
- Session Details: Edit time ranges, characteristics, and trading insights for each session.
Usage:
This indicator is particularly useful for:
1. New traders learning about intraday market dynamics on the NSE.
2. Experienced traders looking for a quick reference of session characteristics.
3. Traders developing or refining time-based trading strategies.
4. Anyone seeking to understand the typical flow of the trading day on the NSE.
Note:
The indicator uses the chart's time to determine the current session. Ensure your chart is set to the correct time zone for accurate results.
Disclaimer:
This indicator is for informational purposes only. The provided insights and characteristics are general in nature and may not reflect current market conditions. Always conduct your own analysis and risk assessment before making trading decisions.
Position Size Calculator for ContractDescription:
Position Size Calculator is a versatile Pine Script tool designed to help traders manage their risk and position sizing effectively. This script calculates essential trading metrics and visualizes them directly on your chart, helping you make informed trading decisions.
Features:
- Account Size & Risk Management:
- Account Size: Input your total account balance to calculate position sizes.
- Maximum Risk: Define how much of your account you are willing to risk per trade in dollars.
- Pip Value: Set the value of a single pip for one contract, which is crucial for calculating risk
and position size.
Trade Setup Visualization:
- Entry Price: Specify the price at which you plan to enter the trade.
- Stop Loss: Define your stop loss level to manage your risk.
- Take Profit: Set your target profit level for the trade.
- Visualize the Entry, Stop Loss, and Take Profit levels on your chart with customizable line
colors and text sizes.
- View the distance in pips between the Entry, Stop Loss, and Take Profit levels.
Position Size Calculation:
- Calculates the number of contracts to open based on your risk tolerance and the pip value.
- Displays the maximum number of contracts you can open given your risk parameters.
Customizable Table Display:
- Table Position: Choose the position of the summary table on the chart (Top-Left, Top-Right,
Bottom-Left, Bottom-Right, etc.).
- Table Text Size: Adjust the text size for the summary table.
- Table Background Color: Set the background color for the summary table.
- Table Border Color: Customize the border color of the summary table.
How to Use:
1- Input your Account Size: Enter your current account balance.
2- Set Maximum Risk and Pip Value: Define how much you're willing to risk per trade and the
pip value for your contract.
3- Define Trade Levels: Input your desired Entry Price, Stop Loss, and Take Profit levels.
4- Customize Visuals: Adjust the line styles and table settings to fit your preferences.
5- View Calculations: The script will display the distance in pips and the calculated position
size directly on your chart.
Example Usage:
Example to calculate the value of 1 pips with 1 contract:
Inputs:
Account Size: Your total trading account balance.
Maximum Risk: Risk amount per trade in dollars.
Pip Value: Value of one pip for a single contract.
Entry Price: The price at which you plan to enter the trade.
Stop Loss: The level at which you will exit the trade to cut losses.
Take Profit: The target price to lock in profits.
Line Text Size: Size of the text for the Entry, Stop Loss, and Take Profit lines.
Line Extend: Option to extend the lines for visual clarity.
Table Position: Position of the summary table on the chart.
Table Text Size: Size of the text in the summary table.
Table Background Color: Background color of the summary table.
Table Border Color: Border color of the summary table.
Visuals:
Entry Price, Stop Loss, and Take Profit levels are clearly marked on the chart.
Summary Table with important trade metrics displayed.
Universal RPPI Indices & Futures [SS Premium]Hello everyone,
For the much-anticipated indicator release, the universal RPPI for Futures and Indices!
If you follow me, chances are you know this indicator by now, since its the basis of all of my analyses and target prices, but if not, let me introduce you!
What is it?
The RPPI for Indices & Futures is essentially a compendium indicator. It contains hundreds of, just over 100 different math models of various futures and indices.
These models are designed to forecast the current targets on multiple timeframes including:
1. The daily
2. The weekly
3. The monthly
4. The Three Month (for SPY and QQQ ONLY)
5. The 6 Month (for DJI, SPX and USOIL/CLI1! ONLY)
6. The annual (for DJI, SPX and USOIL/CLI1! ONLY)
7. The 3 hour
So I will go over the details of the models within the indicators compendium and how they are produced. If you are not interested, just skip to the next section!
What is a model and how is it produced?
Models are math equations and frameworks that attempt to predict future behavior. They are developed in many ways and through many methods. In this particular indicator, each index and future is unique and has been created in various ways, such as using principles of data smoothing, data interpolation, data substitution and data omission.
All this means is, I have manually adjusted model parameters to correct for rare, outlier events. The outcome is having a more accurate model that is better prepared to predict what you want it to predict.
Now let's get into the indicator use.
The first thing we need to talk about is selecting a model type. Different model types are available on a handful of stocks in the indicator, such as SPY, QQQ, DJI and DIA, and so it is important to explain the difference.
Corrected vs Uncorrected Models (i.e. Low Precision vs High Precision Models)
In the settings menu, you will see the second option that reads "Precision". This is where you have the ability to select the model type.
"High Precision" is a corrected model. It is a model that I have used data manipulation for (like the examples above) to enhance its accuracy.
"Low Precision" is a UNCORRECTED model. These models have undergone no data manipulation and are just raw projections.
Which do you use?
There are only a handful of tickers that have both models, like SPY, GLD1! and DJI (among others). Some tickers perform better with low precision models, others perform better with high precision models.
To know what model works best with which stock, the indicator will tell you. At the bottom of the settings table, simply select "Show Model Data":
Selecting this, you will get a table that looks like this:
It will tell you the available model types and which one works best. For IWM, the high-precision corrected model is best. This is true for QQQ and NQ1! as well. However, for SPY and ES1!, the uncorrected model is actually better:
Sometimes, different models perform better at various levels of precision, for example, high on the monthly but low on the daily.
This is why I have omitted this option for the majority of stocks. I don't want this to be confusing to use. For 90% of the included tickers, I have selected the model of best fit. However, for a few of the very popular and volatile tickers (ES, NQ specifically), I have included the ability to use both.
Rule of Thumb:
The rule of thumb with selecting high vs low, is essentially this:
a) If the market is hugely volatility with major swings intraday that exceed its normal behaviour, switch to the low precesion model. This will not be skewed by the massive swings.
b) If the market is stable, trendy or range bound, but not trending beyond its normal, general behaviour, keep it at high precision.
With that, you will be good to go!
Using the indicator:
The indicator is intended as a standalone indicator. Of course, you can combine other indicators that you like to help you out, but there is a strategy version of this that will be released within the coming days/weeks, as this is intended to be a full strategy in and of itself.
As with the universal forecaster, you are given threshold levels that are labelled "Bullish Condition" and "Bearish Condition", a break and hold of the "Bullish Condition" and it is a long to the high targets. Inverse for the bearish condition.
In addition to these conditionals, the indicator also provides you with a high probability retracement level. These are available on the weekly, monthly and higher timeframes. A special moving retracement level is available for SPY only, however it moves based on the PA to give you a sort of POC.
Testing Model Performance:
It is possible to see model performance. At the bottom of the settings menu, select the option to "Show Demographic Data". You need to be sure you are on the chart of the selected timeframe.
This is ES1! on the daily timeframe. It shows you the demographics, i.e. the extent targets are hit, the extent that the high prob retracement targets are missed, the extent that ES closes in and out of its daily range.
This is very valuable information. This table is essentially saying there is only a 10% chance that ES will close above its range and a 9% chance ES closes below its range. This means, that the most ideal setups are a move outside of its range!!
You can view it on all timeframes. If your chart isn't aligned with the lookback, you will get a warning sign:
Misc Functions:
Show price accumulation:
There is an option to toggle on price accumulation. It will show you the amount of accumulation in each of the ranges:
This will show where the accumulation of price rests in relation to the targets.
Autoregression Assessment:
You can have the indicator plot an autoregressive trendline of the expected stock trajectory. You can select the forecast length and it will plot the direction it suspects the stock will go:
Show Standard Deviation:
In the menu, you can toggle on the show standard deviation function. This will plot the standard deviation that each price rests at. The default timeframe for standard deviation is the daily. If you are looking at the weekly, please select the weekly timeframe.
This is helpful because you can see which targets are likely based on where the standard deviation rests. In the above example, a move to the low range would be a move to -2 standard deviations and beyond. This is not something that a ticker would normally do in general circumstances.
FAQ Table:
There is also an option to display an FAQ table. This will show you model revisions and pending revision dates. This will allow you to see when each model was last updated and when new updates will be pushed:
Which models does this contain?
The indicator contains models for the following stocks:
SPY
QQQ
DIA
DJI
ES1!
SPX
NQ1!
NDX
SOXX
IWM
RTY
GCL1! (Gold)
CL1! / USOIL (Oil)
XLE
XLF
YM1!
And some more are in the works (like JETS).
NOTE: Feel free to leave a comment of future ones you would like to see!
The indicator will automatically select the model for whichever ticker you are on.
Some models are cross-compatible, such as CL1! and USOIL, but the indicator is programmed to recognize those that are cross-compatible and auto-select those models.
From there, you just need to select the timeframe you wish to view!
And that is the indicator! I know very wordy explanation but wanted to cover all basis on the indicator so you can be well prepared!
As always, leave your questions, and comments below, and safe trades!
Autoregressive CloudHello,
I am releasing this indicator called the Autoregressive Cloud Indicator.
What it does:
The indicator performs an autoregression analysis on 3 price variables of a ticker, those being the High, the Low and the Close. It uses a 1-lag system and looks back at the previous close, high and low’s effect on the proceeding high, low and close. It then plots out the anticipated range for the ticker based on the autoregression analysis, as well as displays the lag-correlation (autocorrelation) in a table.
What is Autoregression analysis?
Autoregression is a modelling technique used to describe a time series based on its own past values. It assumes that the current value of a variable is a linear combination of its previous values and a random error term.
And what is autocorrelation?
Autocorrelation measures the correlation between a time series and its lagged values. It quantifies the degree to which the current value of a series is related to its past values at different lags, indicating any patterns or dependencies in the data over time. Autoregression and autocorrelation are closely related concepts used to analyze and model time series data.
So how does it work?
The indicator calculates autoregressive values for the close, high, and low prices of a security based on the specified lookback length (which is defaulted to 50). It then plots three sets of clouds representing the smoothed autoregressive values for each price component (done using the SMA function). The transparency of the clouds can be adjusted using the "Transparency" input. Additionally, the code includes a correlation table that displays the correlation coefficients between the lagged values of the close, high, and low prices. The table's position can be customized using the "Position" input.
The indicator defaults to the chart timeframe; however, you can manually adjust the indicator to display the range for whatever timeframe you would like. You can view the 30 minute, 15 or even hourly range on the 1 minute or 5 minute chart if you want.
The indicator will show the anticipated “true trading range” of the stock based on the autoregression and autocorrelation of all 3 variables:
Above is SPY on the 5 minute timeframe with 15 minute levels overlayed. Here, you can see the anticipated trading range for that 15 minute time period.
Using the Correlation Table:
The correlation table displays the Pearson Coefficient for all 3 autoregressions.
A positive correlation: A positive autocorrelation indicates a positive relationship between past and current values of a time series variable. It suggests that when the variable has a high value at a certain time, it is more likely to have a high value in the future, and when it has a low value, it is more likely to have a low value in the future. This positive autocorrelation can imply persistence or trend in the data, indicating that past values can provide useful information for predicting future values. The rule of thumb is anything over 0.5 is considered significant.
A positive correlation among all 3 variables also indicates an uptrend. If you see a strong positive (i.e. the values are all greater than 0.8), it indicates an incredibly decisive and strong uptrend.
A negative correlation: A negative autocorrelation indicates an inverse relationship between past and current values of a time series variable. It suggests that when the variable has a high value at a certain time, it is more likely to have a low value in the future, and vice versa. This negative autocorrelation can imply mean reversion or oscillatory behavior in the data, where extreme values tend to be followed by values closer to the average. It indicates that past values can provide useful information for predicting future values by anticipating a reversal in the direction of the variable. The rule of thumb is anything below or equal to -0.5 is considered significant.
A negative correlation among all 3 variables also indicates a downtrend. If you see a strong negative (i.e. the values are all less than or equal to -0.8), it indicates an incredibly decisive and strong downtrend.
Uses of the Indicator:
The indicator can be used for the following functions:
1. Day trading and scalping within an expected range;
2. Determining the strength or weakness of an uptrend or downtrend on various timeframes;
3. Determining the relationship between previous values and past performance and its effect on future performance;
4. Can alert to changes in trend direction in advance (you may see high, low or close turn negative before others, signifying that weakness is beginning to materialize in an uptrend, or inverse in a downtrend (value changes positive)).
Customizability:
SMA: The autoregression data is smoothed by a 3 period lookback. You can change this if you want, but in order for the indicator to present the true trading range, it is recommended to leave it at <= 3.
Lookback Length: This is the length of the lookback period for the autoregression and autocorrelation functions.
Transparency settings: You can adjust the transparency of the clouds manually.
Timeframe: You can adjust the timeframe, as explained above, to display the timeframe of interest. When you adjust the timeframe, the data will all reflect that timeframe and not necessarily the current TF you have open (i.e. you select 30 minutes while viewing it on the 5 minute, it will show the data for the 30 minute TF period).
Video Tutorial:
I have prepared a video outlining the indicator and also explaining the theory of autoregression/correlation. You can find it below:
Let me know any comments, questions or suggestions below.
Thank you for taking the time to read/watch and check out this indicator.
Safe trades everyone!
EMA bridge and dashboard with color coding.
Summary:
This is a custom moving average indicator script that calculates and plots different Exponential Moving Averages (EMAs) based on user-defined input values. The script also displays MACD and RSI, and provides a table that displays the current trend of the market in a color-coded format.
Explanation:
- The script starts by defining the name of the indicator and the different inputs that the user can customize.
- The inputs include bridge values for three different EMAs (high, close, and low), and four other EMAs (5, 50, 100, and 200).
- The script assigns values to these inputs using the `ta.ema()` function.
- Additionally, the script calculates EMAs for higher timeframes (3m, 5m, 15m, and 30m).
- The script then plots the EMAs on the chart using different colors and line widths.
- The script defines conditions for going long or short based on the crossover of two EMAs.
- It plots triangles above or below bars to indicate the crossover events.
- The script also calculates and displays the RSI and MACD of the asset.
- Finally, the script creates a table that displays the current trend of the market in a color-coded format. The table can be positioned on the top, middle, or bottom of the chart and on the left, center, or right side of the chart.
Parameters:
- i_ema_h: Bridge value for high EMA (default=34)
- i_ema_c: Bridge value for close EMA (default=34)
- i_ema_l: Bridge value for low EMA (default=34)
- i_ema_5: Value for 5-period EMA (default=5)
- i_ema_50: Value for 50-period EMA (default=50)
- i_ema_100: Value for 100-period EMA (default=100)
- i_ema_200: Value for 200-period EMA (default=200)
- i_f_ema: Value for fast EMA used in MACD calculation (default=9)
- i_s_ema: Value for slow EMA used in MACD calculation (default=21)
- fastInput: Value for fast length used in MACD calculation (default=7)
- slowInput: Value for slow length used in MACD calculation (default=14)
- tableYposInput: Vertical position of the table (options: top, middle, bottom; default=middle)
- tableXposInput: Horizontal position of the table (options: left, center, right; default=right)
- bullColorInput: Color of the table cell for a bullish trend (default=green)
- bearColorInput: Color of the table cell for a bearish trend (default=red)
- neutColorInput: Color of the table cell for a neutral trend (default=white)
- neutColorLabelInput: Color of the label for neutral trend in the table (default=fuchsia)
Usage:
To use this script, simply copy and paste it into the Pine Editor on TradingView. You can then customize the input values to your liking or leave them at their default values. Once you have added the script to your chart, you can view the EMAs, MACD, RSI, and trend table on the chart. The trend table provides a quick way to assess the current trend of the market at a glance.
Autoback Grid Lab [trade_lexx]Autoback Grid Lab: Your personal laboratory for optimizing grid strategies.
Introduction
First of all, it is important to understand that Autoback Grid Lab is a powerful professional tool for backtesting and optimization, created specifically for traders using both grid strategies and regular take profit with stop loss.
The main purpose of this script is to save you weeks and months of manual testing and parameter selection. Instead of manually testing one combination of settings after another, Autoback Grid Lab automatically tests thousands of unique strategies on historical data, providing you with a comprehensive report on the most profitable and, more importantly, sustainable ones.
If you want to find mathematically sound, most effective settings for your grid strategy on a specific asset and timeframe, then this tool was created for you.
Key Features
My tool has functionality that transforms the process of finding the perfect strategy from a routine into an exciting exploration.
🧪 Mass testing of thousands of combinations
The script is able to systematically generate and run a huge number of unique combinations of parameters through the built-in simulator. You set the ranges, and the indicator does all the work, testing all possible options for the following grid settings:
* Number of safety orders (SO Count)
* Grid step (SO Step)
* Step Multiplier (SO Multiplier) for building nonlinear grids
* Martingale for controlling the volume of subsequent orders
* Take Profit (%)
* Stop Loss (%), with the possibility of calculating both from the entry point and from the dynamic breakeven line
* The volume of the base order (Volume BO) as a percentage of the deposit
🏆 Unique `FinalScore` rating system
Sorting strategies by net profit alone is a direct path to self—deception and choosing strategies that are "tailored" to history and will inevitably fail in real trading. To solve this problem, we have developed FinalScore, a comprehensive assessment of the sustainability and quality of the strategy.
How does it work?
FinalScore analyzes each combination not one by one, but by nine key performance metrics at once, including Net Profit, Drawdown, Profit Factor, WinRate, Sharpe coefficients, Sortino, Squid and Omega. Each of these indicators is normalized, that is, reduced to a single scale. Then, to test the strategy for strength, the system performs 30 iterations, each time assigning random weights to these 9 metrics. A strategy gets a high FinalScore only if it shows consistently high results under different evaluation criteria. This proves her reliability and reduces the likelihood that her success was an accident.
📈 Realistic backtesting engine
The test results are meaningless if they do not take into account the actual trading conditions. Our simulator simulates real trading as accurately as possible, taking into account:
* Leverage: Calculation of the required margin to open and hold positions.
* Commission: A percentage commission is charged each time an order is opened and closed.
* Slippage: The order execution price is adjusted by a set percentage to simulate real market conditions.
* Liquidation model: This is one of the most important functions. The script continuously monitors the equity of the account (capital + unrealized P&L). If equity falls below the level of the supporting margin (calculated from the current value of the position), the simulator forcibly closes the position, as it would happen on a real exchange. This eliminates unrealistic scenarios where the strategy survives after a huge drawdown.
🔌 Integration with external signals
The indicator operates in two modes:
1. `No Signal': Standard mode. The trading cycle starts immediately as soon as the previous one has been closed. Ideal for testing the "pure" mechanics of the grid.
2. `External Signal`: In this mode, a new trading cycle will start only when a signal is received from an external source. You can connect any other indicator (such as the RSI, MACD, or your own strategy) to the script and use it as a trigger to log in. This allows you to combine the power of a grid strategy with your own entry points.
📊 Interactive and informative results panel
Upon completion of the calculations, a detailed table with the TOP N best strategies appears on the screen, sorted according to your chosen criterion. For each strategy in the rating, you will see not only the key metrics (Profit, Drawdown, duration of transactions), but also all the parameters that led to this result. You can immediately take these settings and apply them in your trading.
Application Options: How To Solve Your Problems
Autoback Grid Lab is a flexible tool that can be adapted to solve various tasks, from complete grid optimization to fine—tuning existing strategies. Here are some key scenarios for its use:
1. Complete Optimization Of The Grid Strategy
This is the basic and most powerful mode of use. You can find the most efficient grid configuration for any asset from scratch.
* How to use: Set wide ranges for all key grid parameters ('SO Count`, SO Step, SO Multiplier, Martingale, TP, etc.).
* In the `No Signal` mode: You will find the most stable grid configuration that works as an independent, constantly active strategy, regardless of which-or entrance indicators.
* In the `External Signal` mode: You can connect your favorite indicator for input (for example, RSI, MACD or a complex author's script) and find the optimal grid parameters that best complement your input signals. This allows you to turn a simple signaling strategy into a full-fledged grid system.
2. Selecting the Optimal Take Profit and Stop Loss for Your Strategy
Do you already have an entry strategy, but you are not sure where it is best to put Take Profit and Stop Loss? Autoback Grid Lab can solve this problem as well.
* How to use:
1. Disable optimization of all grid parameters (uncheck SO Count, SO Step, Martingale, etc.). Set the Min value for SO Count to 0.
2. Set the ranges for iteration only for 'Take Profit` and `Stop Loss'.
3. Turn on the External Signal mode and connect your indicator with input signals.
* Result: The script will run your historical entry signals with hundreds of different TP and SL combinations and show you which stop order levels bring maximum profit with minimal risk specifically for your entry points.
3. Building a Secure Network with Risk Management
Many traders are afraid of grid strategies because of the risk of large drawdowns. With the help of the optimizer, you can purposefully find the parameters for such a grid, which includes mandatory risk management through Stop Loss.
* How to use: Enable and set the range for Stop Loss, along with other grid parameters. Don't forget to test both types of SL calculations (`From entry point` and `From breakeven line`) to determine which one works more efficiently.
* Result: You will find balanced strategies in which the grid parameters (number of orders, martingale) and the Stop Loss level are selected in such a way as to maximize profits without going beyond the acceptable risk level for you.
How To Use The Indicator (Step-By-Step Guide)
Working with the Autoback Grid Lab is a sequential process consisting of four main steps: from initial setup to analysis of the finished results. Follow this guide to get the most out of the tool.
Step 1: Initial Setup
1. Add the indicator to the chart of your chosen asset and timeframe.
2. Open the script settings. The first thing you should pay attention to is the ⚙️ Optimization Settings ⚙️ group.
3. Set the `Bars Count'. This parameter determines how much historical data will be used for testing.
* Important: The more bars you specify, the more statistically reliable the backtest results will be. We recommend using the maximum available value (25,000) to test strategies at different market phases.
* Consider: The indicator performs all calculations on the last historical bar. After applying the TradingView settings, it will take some time to load all the specified bars. The results table will appear only after the data is fully loaded. Don't worry if it doesn't appear instantly. And if an error occurs, simply switch the number of combinations to 990 and back to 1000 until the table appears.
Step 2: Optimization Configuration
At this stage, you define the "universe" of parameters that our algorithm will explore.
1. Set the search ranges (🛠 Optimization Parameters 🛠 group).
For each grid parameter that you want to optimize (for example, SO Count or `Take Profit'), you must specify three values:
* Min: The minimum value of the range.
* Max: The maximum value of the range.
* Step: The step with which the values from Min to Max will be traversed.
*Example:* If you set Min=5, Max=10, and Step=1 for SO Count, the script will test strategies with 5, 6, 7, 8, 9, and 10 safety orders.
* Tip for users: To get the first results quickly, start with a larger step (for example, TP from 0.5% to 2.5% in 0.5 increments instead of 0.1). After you identify the most promising areas, you can perform a deeper analysis by expanding the ranges around these values.
2. Set Up Money Management (Group `💰 Money Management Settings 💰`).
Fill in these fields with the values that best match your actual trading conditions. This is critically important for obtaining reliable results.
* Capital: Your initial deposit.
* Leverage: Leverage.
* Commission (%): Your trading commission as a percentage.
* Slippage (%): Expected slippage.
* Liquidation Level (%): The level of the supporting margin (MMR in %). For example, for Binance Futures, this value is usually between 0.4% and 2.5%, depending on the asset and position size. Specify this value for your exchange.
3. Select the Sorting Criterion and the Direction (Group `⚙️ Optimization Settings ⚙️').
* `Sort by': Specify the main criteria by which the best strategies will be selected and sorted. I strongly recommend using finalScore to find the most balanced and sustainable strategies.
* `Direction': Choose which trades to test: Long, Short or Both.
Step 3: Start Testing and Work with "Parts"
The total number of unique combinations generated based on your ranges can reach tens of millions. TradingView has technical limitations on the number of calculations that the script can perform at a time. To get around this, I implemented a "Parts" system.
1. What are `Part` and `Combinations in Part'?
* `Combinations in Part': This is the number of backtests that the script performs in one run (1000 by default).
* `Part`: This is the number of the "portion" of combinations that you want to test.
2. How does it work in practice?
* After you have everything set up, leave Part:1 and wait for the results table to appear. You will see the TOP N best strategies from the first thousand tested.
* Analyze them. Then, to check the next thousand combinations, just change the Part to 2 in the settings and click OK. The script will run a test for the next batch.
* Repeat this process by increasing the Part number (`3`, 4, 5...), until you reach the last available part.
* Where can I see the total number of parts? In the information row below the results table, you will find Total parts. This will help you figure out how many more tests are left to run.
Step 4: Analyze the Results in the Table
The results table is your main decision—making tool. It displays the best strategies found, sorted by the criteria you have chosen.
1. Study the performance metrics:
* Rating: Position in the rating.
* Profit %: Net profit as a percentage of the initial capital.
* Drawdown%: The maximum drawdown of the deposit for the entire test period.
* Max Length: The maximum duration of one transaction in days, hours and minutes.
* Trades: The total number of completed trades.
2. Examine the winning parameters:
* To the right of the performance metrics are columns showing the exact settings that led to this result ('SO Count`, SO Step, TP (%), etc.).
3. How to choose the best strategy?
* Don't chase after the maximum profit! The strategy with the highest profit often has the highest drawdown, which makes it extremely risky.
* Seek a balance. The ideal strategy is a compromise between high profitability, low drawdown (Drawdown) and the maximum length of trades acceptable to you (Max Length).
* finalScore was created to find this balance. Trust him — he often highlights not the most profitable, but the most stable and reliable options.
Detailed Description Of The Settings
This section serves as a complete reference for each parameter available in the script settings. The parameters are grouped in the same way as in the indicator interface for your convenience.
Group: ⚙️ Optimization Settings ⚙️
The main parameters governing the testing process are collected here.
* `Enable Optimizer': The main switch. Activates or deactivates all backtesting functionality.
* `Direction': Determines which way trades will be opened during the simulation.
* Long: Shopping only.
* Short: Sales only.
* Both: Testing in both directions. Important: This mode only works in conjunction with an External Signal, as the script needs an external signal to determine the direction for each specific transaction.
* `Signal Mode`: Controls the conditions for starting a new trading cycle (opening a base order).
* No Signal: A new cycle starts immediately after the previous one is completed. This mode is used to test "pure" grid mechanics without reference to market conditions.
* External Signal: A new cycle begins only when a signal is received from an external indicator connected via the Signal field.
* `Signal': A field for connecting an external signal source (works only in the `External Signal` mode). You can select any other indicator on the chart.
* For Long** trades, the signal is considered received if the value of the external indicator ** is greater than 0.
* For Short** trades, the signal is considered received if the value of the external indicator ** is less than 0.
* `Bars Count': Sets the depth of the history in the bars for the backtest. The maximum value (25000) provides the most reliable results.
* `Sort by`: A key criterion for selecting and ranking the best strategies in the final table.
* FinalScore: Recommended mode. A comprehensive assessment that takes into account 9 metrics to find the most balanced and sustainable strategies.
* Profit: Sort by net profit.
* Drawdown: Sort by minimum drawdown.
* Max Length: Sort by the minimum length of the longest transaction.
* `Combinations Count': Indicates how many of the best strategies (from 1 to 50) will be displayed in the results table.
* `Close last trade`: If this option is enabled, any active trade will be forcibly closed at the closing price of the last historical bar. For grid strategies, it is recommended to always enable this option in order to get the correct calculation of the final profit and eliminate grid strategies that have been stuck for a long time.
Group: 💰 Money Management Settings 💰
The parameters in this group determine the financial conditions of the simulation. Specify values that are as close as possible to your actual values in order to get reliable results.
* `Capital': The initial deposit amount for the simulation.
* `Leverage`: The leverage used to calculate the margin.
* `Slippage` (%): Simulates the difference between the expected and actual order execution price. The specified percentage will be applied to each transaction.
* `Commission` (%): The trading commission of your exchange as a percentage. It is charged at the execution of each order (both at opening and closing).
* `Liquidation Level' (%): Maintenance Margin Ratio. This is a critical parameter for a realistic test. Liquidation in the simulator occurs if the Equity of the account (Capital + Unrealized P&L) falls below the level of the supporting margin.
Group: 🛠 Optimization Parameters 🛠
This is the "heart" of the optimizer, where you set ranges for iterating through the grid parameters.
* `Part`: The portion number of the combinations to be tested. Start with 1, and then increment (`2`, 3, ...) sequentially to check all generated strategies.
* `Combinations in Part': The number of backtests performed at a time (in one "Part"). Increasing the value may speed up the process, but it may cause the script to error due to platform limitations. If an error occurs, it is recommended to switch to the step below and back.
Three fields are available for each of the following parameters (`SO Count`, SO Step, SO Multiplier, etc.):
* `Min`: Minimum value for testing.
* `Max': The maximum value for testing.
* `Step`: The step with which the values in the range from Min to Max will be iterated over.
There is also a checkbox for each parameter. If it is enabled, the parameter will be optimized in the specified range. If disabled, only one value specified in the Min field will be used for all tests.
* 'Stop Loss': In addition to the standard settings Min, Max, Step, it has an additional parameter:
* `Type`: Defines how the stop loss price is calculated.
* From entry point: The SL level is calculated once from the entry price (base order price).
* From breakeven line: The SL level is dynamically recalculated from the average position price after each new safety order is executed.
Group: ⚡️Filters⚡️
Filters allow you to filter out those results from the final table that do not meet your minimum requirements.
For each filter (`Max Profit`, Min Drawdown, `Min Trade Length`), you can:
1. Turn it on or off using the checkbox.
2. Select the comparison condition: Greater (More) or Less (Less).
3. Set a threshold value.
*Example:* If you set Less and 20 for the Min Drawdown filter, only those strategies with a maximum drawdown of less than 20% will be included in the final table.
Group: 🎨 Visual Settings 🎨
Here you can customize the appearance of the results table.
* `Position': Selects the position of the table on the screen (for example, Bottom Left — bottom left).
* `Font Size': The size of the text in the table.
* `Header Background / Data Background`: Background colors for the header and data cells.
* `Header Font Color / Data Font Color`: Text colors for the header and data cells.
Important Notes and Limitations
So that you can use the Autoback Grid Lab as efficiently and consciously as possible, please familiarize yourself with the following key features of its work.
1. It is a Tool for Analysis, not for Signals
It is extremely important to understand that this script does not generate trading signals in real time. Its sole purpose is to conduct in—depth research (**backtesting**) on historical data.
* The results you see in the table are a report on how a particular strategy would have worked in the past.
* The script does not provide alerts and does not draw entry/exit points on the chart for the current market situation.
* Your task is to take the best sets of parameters found during optimization and use them in your real trading, for example, when setting up a trading bot or in a manual trading system.
2. Features Of Calculations (This is not a "Repainting")
You will notice that the results table appears and is updated only once — when all historical bars on the chart are loaded. It does not change in real time with each tick of the price.
This is correct and intentional behavior.:
* To test thousands, and sometimes millions of combinations, the script needs to perform a huge amount of calculations. In the Pine Script™ environment, it is technically possible to do this only once, at the very last bar in history.
* The script does not show false historical signals, which then disappear or change. It provides a static report on the results of the simulation, which remains unchanged for a specific historical period.
3. Past Results do not Guarantee Future Results.
This is the golden rule of trading, and it fully applies to the results of backtesting. Successful strategy performance in the past is not a guarantee that it will be as profitable in the future. Market conditions, volatility and trends are constantly changing.
My tool, especially when sorting by finalScore, is aimed at finding statistically stable and reliable strategies to increase the likelihood of their success in the future. However, it is a tool for managing probabilities, not a crystal ball for predicting the future. Always use proper risk management.
4. Dependence on the Quality and Depth of the Story
The reliability of the results directly depends on the quantity and quality of the historical data on which the test was conducted.
* Always strive to use the maximum number of bars available (`Bars Count: 25,000`) so that your strategy is tested on different market cycles (rise, fall, flat).
* The results obtained on data for one month may differ dramatically from the results obtained on data for two years. The longer the testing period, the higher the confidence in the parameters found.
Conclusion
The Autoback Grid Lab is your personal research laboratory, designed to replace intuitive guesses and endless manual selection of settings with a systematic, data—driven approach. Experiment with different assets, timeframes, and settings ranges to find the unique combinations that best suit your trading style.
Sniper-2025 Sniper-2025 Indicator Explanation
Overview
The Sniper-2025 indicator is a versatile technical analysis tool designed for TradingView, combining a Hyper Wave oscillator, Smart Money Flow analysis, divergence detection, reversal signals, confluence visualization, and a machine learning-based k-Nearest Neighbors (k-NN) prediction model. It provides traders with actionable buy and sell signals, trend insights, and confluence indicators to enhance decision-making across various trading strategies. The indicator is highly customizable, allowing users to adjust sensitivity, colors, and display options to suit their preferences.
Key Features
1. Hyper Wave Oscillator: A normalized oscillator based on price data, smoothed with either a Simple Moving Average (SMA) or Exponential Moving Average (EMA), highlighting momentum and potential reversal points.
2. Smart Money Flow: Tracks bullish and bearish money flow using a smoothed Money Flow Index (MFI), providing insights into market strength and direction.
3. Divergence Detection: Identifies bullish and bearish divergences between price and the oscillator, with optional labels displaying price levels.
4. Reversal Signals: Detects major and minor reversal conditions based on volume, oscillator values, and RSI, visualized as triangles and circles on the chart.
5. Confluence Meter and Areas: Visualizes alignment between the oscillator and MFI, indicating bullish or bearish confluence with customizable colors and shaded areas.
6. Signal and Divergence Labels: Displays labels for key oscillator levels (e.g., Z-Buy, Z-V-Sell) and money flow conditions (e.g., C-Buy, T-Sell) with customizable visibility and sizes.
7. Trend and Control Table: Shows the current trend (Bullish/Bearish) and control (Bull/Bear) in a customizable table positioned on the chart.
8. k-NN Prediction: Uses a k-Nearest Neighbors algorithm to predict price movement direction based on RSI indicators, with adjustable prediction sensitivity.
9. Gradient Fills and Alerts: Visualizes overbought and oversold zones with gradient fills and provides alert conditions for key crossovers and crossunders.
How It Works
- Hyper Wave Oscillator: The oscillator is calculated by normalizing the close price relative to the highest, lowest, and average prices over a user-defined length (default: 15). It is smoothed using SMA or EMA (default: SMA, length 3) to generate a signal line. Crossovers and crossunders of the oscillator and signal line are plotted as circles, indicating potential buy or sell signals.
- Smart Money Flow: The MFI is calculated over a user-defined length (default: 10) and smoothed (default: 6). It tracks bullish (positive) or bearish (negative) money flow, with colors changing based on direction (blue for bullish, red for bearish). The indicator compares current MFI to its historical average to identify strong trends.
- Divergence Detection: The script identifies divergences by comparing oscillator peaks/troughs with price highs/lows. Bullish divergences (price makes lower lows, oscillator does not) and bearish divergences (price makes higher highs, oscillator does not) are plotted as lines, with optional labels showing the divergence type and price.
- Reversal Signals: Major reversals are detected when volume exceeds a threshold (based on a 7-period SMA and reversal factor, default: 4) and the oscillator exceeds ±4. Minor reversals consider RSI (±20) and oscillator crossovers. Signals are plotted as triangles (major) or circles (minor), with blue for bullish and red for bearish.
- Confluence Meter and Areas: The confluence meter, displayed on the right, shows alignment between the oscillator and MFI using a gradient from red (bearish) to blue (bullish). Shaded areas at ±55 highlight strong bullish or bearish confluence when both indicators align.
- Signal and Divergence Labels: Labels are plotted on the candlestick chart when the oscillator crosses key levels (±20, ±40) or when money flow conditions are met (e.g., MFI crossing 0 or ±20/±40). Users can toggle label visibility and adjust sizes (Small, Normal, Large, Huge).
- Trend and Control Table: A table displays the trend (based on oscillator SMA) and control (based on MFI direction), with customizable position (default: Top Right), text color, and background color. Sensitivity for trend and control calculations can be adjusted.
- k-NN Prediction: The k-NN algorithm predicts price movement direction by comparing current RSI values (5-period and 20-period WMAs) to historical data. The number of neighbors (default: 200) and trend length (default: 20) control prediction sensitivity. A green line shows the prediction, with gradient fills indicating overbought (lime) and oversold (red) zones.
- Gradient Fills and Alerts: Gradient fills highlight the prediction's position relative to overbought/oversold zones, calculated using a 2000-period lookback and standard deviation. Alerts are triggered for crossovers/crossunders of the prediction line with its WMA, overbought/oversold levels, or the zero line.
Usage Instructions
1. Add the Sniper-2025 indicator to your TradingView chart.
2. Interpret signals:
- Z-Buy/Z-V-Buy (green labels): Potential buy signals when the oscillator crosses below -20/-40.
- Z-Sell/Z-V-Sell (red labels): Potential sell signals when the oscillator crosses above 20/40.
- C-Buy/C-Sell (green/red labels): Money flow shifts to bullish/bearish when MFI crosses 0.
- T-Buy/T-Sell (green/red labels): Money flow crosses ±20, indicating stronger trends.
- T-V-Buy/T-V-Sell (green/red labels): Money flow crosses ±40, indicating very strong trends.
- Divergence Labels: Green (D-Bullish) or red (D-Bearish) labels indicate potential reversals.
- Reversal Signals: Blue triangles/circles for bullish reversals, red for bearish.
- Confluence Meter: Blue (bullish) or red (bearish) gradient indicates alignment strength.
- Table: Check "Trend" and "Control" for market direction (🟩/🟥 for trend, 🟢/🔴 for control).
- k-NN Prediction: Green line above 0 suggests bullish momentum; below 0 suggests bearish. Watch for crossovers with the WMA or overbought/oversold zones.
3. Set alerts for crossovers/crossunders of the prediction line, oscillator, or MFI to automate trading signals.
Customization Options
- Hyper Wave: Adjust Main Length (mL, default: 15) for oscillator sensitivity, Signal Type (sT, SMA/EMA), and Signal Length (sLHW, default: 3). Customize colors and transparency.
- Smart Money Flow: Set Money Flow Length (mfL, default: 10) and Smooth (mfS, default: 6) for MFI sensitivity. Choose bullish/bearish colors.
- Divergence: Modify Divergence Sensibility (dvT, default: 20) for short-term (lower) or long-term (higher) divergences. Toggle visibility and price display on labels.
- Reversal: Adjust Reversal Factor (rsF, default: 4) for signal strength (higher = fewer, stronger signals). Set colors for bullish/bearish signals.
- Confluence: Toggle Confluence Meter (sCNF) and Areas (sCNB), and customize colors.
- Labels: Enable/disable specific signal labels (e.g., showZBuy, showHSell) and adjust Label Size (default: Normal).
- Table: Toggle Trend and Control display, adjust sensitivities, and set position and colors.
- k-NN Prediction: Adjust Prediction Data (numNeighbors, default: 200) for sensitivity and Trend Length (momentumWindow, default: 20) for responsiveness.
Conclusion
The Sniper-2025 indicator is a powerful tool for traders seeking a comprehensive analysis of price momentum, money flow, divergences, reversals, and predictive signals. Its customizable settings and clear visualizations make it suitable for both novice and experienced traders. Use the indicator to identify high-probability trading opportunities, monitor market trends, and refine strategies with its machine learning-driven predictions.
ICT HTF Candles + CISD + FVG, by AlephxxiiICT HTF Candles + CISD + FVG
A practical, friendly overlay for ICT-style trading
This indicator gives you three things at once—right on your chart:
HTF Candles Panel (context):
Compact candles from higher timeframes (e.g., 5m, 15m, 1H, 4H, 1D, 1W) appear to the right of price so you always see the higher-timeframe story without switching charts. It includes labels, remaining time for the current HTF candle, and optional open/high/low/close reference lines.
CISD Levels (bias flips):
Automatically plots +CISD and -CISD lines. When price closes above +CISD, the indicator considers bullish delivery. When price closes below -CISD, it considers bearish delivery. An on-chart table (optional) shows the current bias at a glance.
FVG (Fair Value Gaps):
Highlights inefficiency zones (gaps) on your current timeframe and/or a selected higher timeframe. You can choose to mark a gap “filled” when price hits the midpoint (optional).
Quick start (2 minutes)
Add to chart and keep your normal trading timeframe (e.g., 1–5m).
In settings → HTF 1..6, pick the higher timeframes you want to see (e.g., 5m, 15m, 1H, 4H, 1D, 1W).
Turn on FVG (current, HTF or both).
Watch +CISD / -CISD lines and the Current State table.
Close above +CISD → Bullish bias
Close below -CISD → Bearish bias
Trade with the bias and use FVGs as areas to refine entries or targets.
How to read it (the simple way)
Bias (CISD):
Bullish once price closes above the active +CISD level.
Bearish once price closes below the active -CISD level.
The small table (if enabled) says Bullish or Bearish right now.
HTF panel:
Shows higher-timeframe candles next to your current chart.
Labels show the timeframe (e.g., 1H) and a countdown for the current candle.
Optional traces draw HTF Open/High/Low/Close levels—great “magnets” for price.
FVGs:
Shaded boxes = potential inefficiency areas.
If Midpoint Fill is on, a touch of the midline counts as filled.
You can display current TF, HTF, or both.
Suggested workflow (popular ICT-style intraday)
Define bias with CISD
Only look for longs if Bullish, shorts if Bearish.
Check HTF context
Are you trading into a large HTF FVG or key HTF O/H/L/C level? That can be a target or a headwind.
Refine entries with FVGs
On your entry TF (1–5m), use fresh FVGs in the direction of the bias. Avoid fading straight into big HTF imbalances.
Key settings you’ll actually use
HTF 1..6: toggle each strip, select timeframe, and how many candles to show.
Style & layout: adjust offset, spacing, and width of the right-side panels.
Labels & timers: show/hide HTF name and remaining time; place labels at Top/Bottom/Both.
Custom daily open (NY): set the 1D candle to start at Midnight, 08:30, or 09:30 (America/New_York).
Trace lines: optional HTF O/H/L/C lines (style, width, anchor TF).
FVG module (extra): choose Current TF / HTF / Both, enable Midpoint Fill, auto-delete on fill, and show timeframe labels.
CISD lines: customize color, style (solid/dotted/dashed), thickness, and forward extension.
Table: enable/disable and choose its position.
Alerts
When a CISD completes, the script fires an alert (e.g., “Bullish CISD Formed” or “Bearish CISD Formed”).
Tip: Set your TradingView alert once on the indicator, then choose the alert message you want to receive.
Notes & limitations (read me)
“VI” label: The “Volume Imbalance” option marks price imbalances (body non-overlap). It does not read volume data.
Timezone: Daily logic and timers use America/New_York, which aligns with US indices/equities and common ICT practice.
Performance: This tool draws many boxes/lines/labels. If your chart feels heavy, reduce the number of HTFs or candles shown, or narrow panel width.
Repainting: HTF panels are designed to avoid future leakage; FVG logic follows standard 3-bar checks. As usual, wait for candle closes for confirmations.
Level cleanup: If Keep old CISD levels is OFF (default), the script keeps only the current active CISD to reduce clutter.
Daily 50‑ & 200‑SMA Ceiling Radar — EnhancedDescription:
This custom TradingView indicator, developed by Trader Malik and licensed under Trades Per Minute, is a powerful visual tool for identifying how price behaves relative to major daily moving averages — the 50-SMA and 200-SMA. It helps traders quickly understand key technical dynamics such as trend alignment, MA proximity, and short-term momentum sentiment — all displayed on a clean, minimal overlay with visual alerts and an adjustable data table.
FEATURES
1. Daily 50 & 200 Simple Moving Averages (SMA):**
- Displayed directly on the chart using distinct blue and orange lines.
- These serve as primary trend filters and support/resistance zones.
2. Price Highlighting:
- A red background flashes momentarily when the price crosses either the 50-SMA or 200-SMA.
- A green background fills the chart when price is above both MAs (bullish zone).
- A red background persists if price is below both MAs (bearish zone).
3. MA Gap Analysis Table:
- 50-SMA Row**: Shows % gap between 50-SMA and 200-SMA.
- 200-SMA Row**: Shows % gap between 200-SMA and 50-SMA.
- Sentiment Row**: Displays short-term trend bias based on the slope of the past 7 daily closes — Bullish, Neutral, or Bearish.
USER SETTINGS
Table Location: Choose between **Top Right** or **Bottom Right** of the chart.
Table Size: Select **Small**, **Medium**, or **Large** to suit screen preferences and layout aesthetics.
This script is **intellectual property of Trades Per Minute** and distributed by **Trader Malik** for use under licensing terms. Redistribution or repurposing without authorization is strictly prohibited.
Fractal Adaptive Moving Average (FRAMA)Core Concept
Unlike traditional moving averages that use fixed smoothing factors, FRAMA adapts its responsiveness based on how "fractal" or chaotic the price movement is:
In trending markets (low fractal dimension), it becomes more responsive
In choppy/sideways markets (high fractal dimension), it becomes smoother
How It Works
1. Fractal Dimension Calculation:
Splits the lookback period into two halves
Calculates price ranges for each half and the total period
Uses logarithmic ratios to determine the fractal dimension (bounded between 1.0 and 2.0)
2. Dynamic Alpha Calculation:
Converts fractal dimension to a smoothing factor (alpha)
Higher fractal dimension = lower alpha = smoother average
Lower fractal dimension = higher alpha = more responsive average
3. Adaptive Smoothing:
Applies the calculated alpha to create the moving average
FRAMA = alpha × current_price + (1 - alpha) × previous_FRAMA
Key Parameters
Length (16): Lookback period for calculations
Fast Constant (4.0): Maximum responsiveness limit
Slow Constant (300.0): Minimum responsiveness limit
Visual Features
Line Color: Green when rising, red when falling
Background: Light green above FRAMA (bullish), light red below (bearish)
Information Table: Shows current FRAMA value, price, trend direction, and efficiency ratio
Close Price: Plotted as a semi-transparent white line for comparison
Trading Applications
FRAMA is particularly useful for:
Trend Following: More responsive in strong trends, less noisy in consolidations
Support/Resistance: Acts as dynamic support in uptrends, resistance in downtrends
Market Regime Detection: The efficiency ratio helps identify trending vs. ranging markets
Entry/Exit Signals: Crossovers and price position relative to FRAMA
The indicator automatically balances between being fast enough to catch trends early while being smooth enough to avoid false signals in choppy markets.
In this FRAMA script, fractal refers to measuring the complexity or "roughness" of price movements over time, not the self-similar geometric patterns we typically think of.
What the Script Measures
The script calculates a fractal dimension that quantifies how chaotic or smooth the price action is:
Low fractal dimension (closer to 1.0): Price moves in a relatively straight, trending manner
High fractal dimension (closer to 2.0): Price moves in a jagged, choppy, sideways manner.
The Logic
If the market is trending smoothly:
The sum of the two half-period ranges will be close to the total range
This gives a fractal dimension closer to 1.0
The indicator becomes more responsive (faster)
If the market is choppy/sideways:
The sum of the two half-period ranges will be much larger than the total range
This gives a fractal dimension closer to 2.0
The indicator becomes less responsive (smoother)
Practical Example
Imagine a 16-period lookback:
Trending market: Price goes from 100 → 116 steadily
Choppy market: Price bounces 100→108→102→114→106→116
The choppy market has a higher fractal dimension because there's more "path length" relative to the actual distance traveled.
Why This Matters
The fractal dimension becomes the adaptive mechanism that automatically adjusts the moving average's sensitivity based on current market conditions - making it faster in trends and smoother in consolidations.
what is efficiency that is shown in tables
The efficiency shown in the table measures how "efficient" or smooth the FRAMA line is compared to the actual price movement.
What It Means
Efficiency = FRAMA Movement ÷ Price Movement
Values close to 0: FRAMA is very smooth/stable while price is moving significantly
Values close to 1: FRAMA is moving almost as much as the price
Values > 1: FRAMA is moving more than the raw price (rare, usually in very short periods)
Practical Interpretation
Low Efficiency (0.1 - 0.3):
FRAMA is doing a good job of smoothing out noise
Market is likely choppy/sideways
The adaptive mechanism is working - keeping the average stable during consolidation
High Efficiency (0.7 - 1.0):
FRAMA is closely following price movements
Market is likely trending strongly
The adaptive mechanism is making the average more responsive
Medium Efficiency (0.3 - 0.7):
Balanced market conditions
FRAMA is providing moderate smoothing
Trading Context
This efficiency ratio helps you understand:
Market regime: Is this a trending or ranging market?
Signal quality: Low efficiency periods might produce fewer but higher-quality signals
Adaptive performance: How well the FRAMA is adapting to current conditions
For example, if you see efficiency at 0.15, it means the FRAMA moved only 15% as much as the price did in the last bar, indicating it's successfully filtering out noise in a choppy market. If efficiency is 0.85, the FRAMA is closely tracking price, suggesting a trending environment where you want the average to be responsive.
OBV Strength Relative to Volume (Lakhs View)OBV Strength Relative to Volume (Lakhs View)
Description:
to provide a compact yet powerful insight into volume momentum and price conviction. It's tailored for traders and analysts in markets like India, where high-volume stocks are often better interpreted in lakhs.
💡 Key Features:
OBV Calculation: Cumulative OBV is computed based on price movement direction and volume contribution.
OBV Strength (%): Measures the percentage strength of OBV relative to total volume over a user-defined period. It reflects how strongly volume is contributing to price movements.
Lakhs View: Both OBV and Volume are scaled to lakhs for cleaner readability and practical analysis in high-volume securities.
Historical Table Display:
Displays date-wise OBV, Volume, and OBV Strength for the last N candles (customizable).
Automatically updates every 5 bars or on each bar for real-time analysis.
Color-coded cells for quick visual recognition.
⚙️ Inputs:
OBV Strength Period: Number of bars used to calculate OBV strength (default = 5).
Number of Days in Table: Number of recent bars shown in the on-chart table (default = 5).
📈 Plots:
OBV (Lakhs) – Aqua line.
Volume (Lakhs) – Orange columns.
OBV Strength (%) – Green line indicating momentum strength based on volume.
📍 Ideal Use:
Use this indicator to:
Spot divergences between OBV and price.
Assess the strength of volume behind a trend.
Track consistency and spikes in volume-backed price moves.
Quickly scan recent trends with a clear numerical and visual table.
SignalWatcherThis script provides real-time monitoring of multiple technical indicators and generates visual alerts and configurable alarms:
Inputs & Mini-GUI
MACD Settings: Activation, fast, slow and signal line lengths.
RSI Settings: Activation, period length, overbought and oversold thresholds.
ADX Settings: Activation, period length, smoothing and trend strength thresholds.
Volume Settings: Activation, length of the volume MA, factor for detecting volume peaks.
Global Alert: A single composite alert for all signals.
Plot Settings: Activation and deactivation of the plot displays for RSI, MACD (lines) and ADX. Color and width selection for each line.
Display Table: Activation of the status table.
Calculations
MACD: Generates macdLine and signalLine, detects crossovers (bullish) and crossunders (bearish).
RSI: Calculates rsi_val, compares with rsi_ob and rsi_os to determine overbought/oversold.
ADX: Uses ta.dmi() to determine adx_val and checks against adx_thresh for trend strength.
Volume Spike: Exceptional trading activity detected by moving average (vol_ma) and factor (vol_factor).
Alert conditions
Six individual alertcondition() calls: MACD ↑/↓, RSI Overbought/Oversold, ADX Strong Trend, Volume Spike.
Optional composite alert (enable_global): A single notification when one of the indicator signals strikes.
Visual overlays
Alarm overlay (bottom right): Red table with text lines for currently triggered signals.
Status Table (bottom left): Overview of all indicators with current status (On/Off, Values, Thresholds).
Plots in the chart
RSI, MACD Line & Signal Line, ADX: Are displayed as lines if activated in the GUI; configurable colors & line thicknesses.
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.
CANDLE SCRUTINY | GSK-VIZAG-AP-INDIAIndicator: CANDLE SCRUTINY | GSK-VIZAG-AP-INDIA
1. Overview
The CANDLE SCRUTINY indicator is a candle-by-candle analytical tool designed to dissect and visually represent the behavior of recent candles on a chart. It presents a concise table overlay that summarizes critical candlestick data including price movement, directional trend, volume dynamics, and strength of price sequences — all updated in real time.
2. Purpose / Trading Use Case
This tool is ideal for:
Scalpers and intraday traders needing quick real-time candle insights.
Trend analyzers who want to observe evolving price momentum.
Volume-based decision makers monitoring buyer-seller imbalance.
Traders who scrutinize candles for confirmations before entries or exits.
3. Key Features & Logic Breakdown
Candle Classification: Each candle is categorized as Bullish, Bearish, or Doji based on open-close comparison.
Move Calculation: Calculates and displays net candle move (Close - Open) for each bar.
Trend Count: Tracks the number of consecutive candles of the same type (bullish or bearish).
Sequential Move (Total SM): Aggregates move values when candles of the same type form a sequence.
Volume Breakdown: Approximates buy/sell volume ratio using candle type logic.
Delta Volume: Measures buy-sell imbalance to gauge intrabar strength.
Time Localization: Candle timestamps are shown in the user-selected timezone.
4. User Inputs / Settings
Number of Candles (numCandles): Choose how many recent candles to analyze (1–10).
Table Position (tablePos): Set to top_right by default.
Timezone Selector (tzOption): Choose from multiple global timezones (e.g., IST, UTC, NY, London) to view local candle times.
These settings let traders customize the scope and perspective of candle analysis to fit their trading region and strategy focus.
5. Visual & Plotting Elements
A floating data table appears on the chart (top-right by default), showing:
Time of candle (localized)
Type (Bullish/Bearish/Doji)
Move value with green/red background
Total SM (sequential movement) with trend-based color shading
Trend Count
Buy Volume, Sell Volume, Total Volume
Delta (volume imbalance) with color-coded strength indicator
Color coding makes it visually intuitive to quickly assess strength, direction, and sequence.
6. Effective Usage Tips
Use in 1-minute to 15-minute timeframes for scalping or momentum breakout confirmation.
Monitor Delta and Sequential Move (SM) to confirm strength behind price action.
Trend Count helps gauge sustained direction—useful for short-term trend continuation strategies.
Combine with support/resistance zones or volume profile for stronger confluence.
Great for detecting early signs of exhaustion or continuation.
7. What Makes It Unique
Combines price action + volume behavior + trend memory into one compact visual table.
Allows user-defined timezone adjustment, a rare feature in similar indicators.
Designed to give a story of the last N candles from a momentum and participation viewpoint.
Fully non-intrusive overlay—doesn't clutter chart space.
8. Alerts / Additional Features
Currently no alerts, but future versions may include:
Alert when trend count exceeds a threshold
Alert on strong delta volume shifts
Alert on back-to-back Dojis (sign of indecision)
9. Technical Concepts Used
Candlestick Logic: Bullish, Bearish, Doji classification
Volume Analysis: Approximate buy/sell split based on candle type
Color Coding: For intuitive interpretation of move, trend, and delta
Arrays & Looping Logic: Efficient tracking of trends and sequences
Timezone Handling: Uses hour(time, timezone) and minute(time, timezone) for local display
10. Disclaimer
This script is provided for educational and informational purposes only. It does not constitute financial advice. Always backtest thoroughly and use appropriate risk management when applying this or any indicator in live markets. The author is not responsible for any financial losses incurred.
Tetris with Auto-PlayThis indicator is implemented in Pine Script™ v6 and serves as a demonstration of TradingView's capabilities. The core concept is to simulate a classic Tetris game by creating a grid-based environment and managing game state entirely within Pine Script.
Key Technical Aspects:
Grid Representation:
The script defines a custom grid structure using a user-defined type that holds the grid’s dimensions and a one-dimensional array to simulate a two-dimensional board. This structure is used to track occupied cells, clear full rows, and determine stack height.
Piece Management:
A second custom type is used to represent the state of a tetromino piece, including its type, rotation, and position. The code includes functions to calculate the block offsets for each tetromino based on its rotation state.
Collision Detection and Piece Locking:
Dedicated functions check for collisions against the grid borders and existing blocks. When a collision is detected during a downward move, the piece is locked into the grid, and any complete lines are cleared.
AIgo-Driven Placement:
The script incorporates a simple heuristic to determine the best placement for the next tetromino. It simulates different rotations and horizontal positions, evaluating each based on aggregated column height, cleared lines, holes, and bumpiness. This decision-making process is encapsulated in an AI-like function that returns the optimal rotation and placement.
Rendering Using Tables:
The visual representation is managed via TradingView’s table objects. The game board is rendered with a bordered layout, while a separate preview table displays the next piece and the current score. Each cell is updated with text and background colors that correspond to the state of the game.
Execution Flow and Timing:
The main execution loop handles real-time updates by dropping pieces at set intervals and checking for game-over conditions. The code leverages persistent variables and time comparisons to control game speed and manage transitions between piece drops.
Executing:
Add the indicator to the chart
It starts playing itself till game over
There are no parameters to change in this version but the grid in the code directly
p.s. Sadly we have no interactive buttons in the current pinescript versions to play ourself, but its about the possibilitys what we could do ;-)
Maybe in a future version there is more possible, if i find time to enhance and expand the idea
Have fun :-)
Volumen trend indicator 5MVOLUMEN TREND INDICATOR
Introduction
This indicator on TradingView provides a combination of technical analysis through a data table and visual elements on the chart. Its purpose is to provide a comprehensive view of the analyzed asset, facilitating decision-making.
How It Works
The indicator operates on two levels:
Data Table:
Displays key information about the asset's trend.
Includes metrics such as the current price, percentage change, volatility, and other relevant variables.
Can be customized to include additional indicators as needed.
Provides a quick analysis without the need to interpret complex charts.
Technical Elements on the Chart:
Incorporates dynamic support and resistance lines.
Can include moving averages, Bollinger Bands, RSI, or other custom indicators.
Offers visual alerts for significant changes in the asset's trend.
Facilitates detailed technical analysis through direct observation of patterns and signals.
Default Technical Indicators
The indicator comes with the following default pre-configured technical indicators:
Exponential Moving Average (EMA) 9:
This EMA responds more quickly to price movements, making it ideal for identifying short-term trends. It is generally used to detect crossovers with other EMAs or prices and is considered an entry or exit signal.
Exponential Moving Average (EMA) 21:
The 21-period EMA is used to identify medium-term trends. Its interaction with the 9 EMA is key to confirming buy or sell signals when both cross.
RSI (Relative Strength Index):
It is used to measure the magnitude of recent gains and losses of an asset, helping to identify overbought or oversold conditions.
Bollinger Bands:
These bands help identify volatility levels and potential reversal points. Price touching the upper or lower bands can be an important signal of trend change or continuation.
Customization
The user can modify several aspects of the indicator, such as:
Colors and styles of visual elements on the chart.
Types of indicators to include in the table.
Configuration of alerts and notifications.
Time interval for calculations and data updates.
EMA values (the periods can be changed if other configurations are desired).
Recommended Usage
To make the most of the indicator:
Use the data table to get an overview of the asset.
Analyze the technical elements on the chart to confirm trends.
Set alerts to avoid missing key opportunities.
Compare the information with other indicators and data sources before making decisions.
Precautions and Best Practices
Avoid relying solely on the indicator: Complement it with other technical and fundamental analysis.
Adjust the settings according to the asset's volatility: Not all strategies work the same across different markets.
Don’t overload the chart with too many elements: This can create visual noise and confusion in interpretation.
Test it on a demo account before trading live: To familiarize yourself with the indicator's functionality and adjustments.
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Remember that no system is perfect, keep these considerations in mind for this indicator:
Do not trade when a signal appears during an opposite trend:
Do not trade when the market is uncertain in its direction or within a parallel channel:
ROC + SMI Auto Adjust
This indicator combines the Rate of Change (ROC) and the Stochastic Momentum Index (SMI) with automatically adjusted parameters for different time frames (short, medium, long). It normalizes the ROC to match the SMI levels, displays the ROC as a histogram and the SMI as lines, highlights overbought/oversold zones and includes a settings table. Ideal for analyzing momentum on different time frames.
Key Features:
Automatic Parameter Adjustment:
The script detects the current chart time frame (e.g. 1-minute, 1-hour, daily) and adjusts the parameters for the ROC and SMI accordingly.
Parameters such as ROC length, SMI length and smoothing periods are optimized for short, medium and long term time frames.
Rate of Change (ROC):
ROC measures the percentage change in price over a specified period.
The script normalizes the ROC values to match the SMI range, making it easier to compare the two indicators on the same scale.
The ROC is displayed as a histogram, where positive values are colored green and negative values are colored red.
Stochastic Momentum Index (SMI):
SMI is a momentum oscillator that identifies overbought and oversold conditions.
The script calculates the SMI and its signal line, plotting them on the chart.
Overbought and oversold levels are displayed as dotted lines for convenience.
SMI and SMI Signal Crossover:
When the main SMI crosses the signal line from below upwards, it may be a buy signal (bullish signal).
When the SMI crosses the signal line from above downwards, it may be a sell signal (bearish signal).
Configurable Inputs:
Users can use the automatically adjusted settings or manually override the parameters (e.g. ROC length, SMI length, smoothing periods).
Overbought and oversold levels for SMI are also configurable.
Parameter Table:
A table is displayed on the chart showing the current parameters (e.g. timeframe, ROC length, SMI length) for transparency and debugging.
The position of the table is configurable (e.g. top left, bottom right).
How it works:
The script first detects the chart timeframe and classifies it as short-term (e.g. 1M, 5M), medium-term (e.g. 1H, 4H) or long-term (e.g. D1, W1).
Based on the timeframe, it sets default values for the ROC and SMI parameters.
ROC and SMI are calculated and normalized so that they can be compared on the same scale.
ROC is displayed as a histogram, while SMI and its signal line are displayed as lines.
Overbought and oversold levels are displayed as horizontal lines.
Use cases:
Trend identification: ROC helps to identify the strength of the trend, while SMI indicates overbought/oversold conditions.
Momentum analysis: The combination of ROC and SMI provides insight into both price momentum and potential reversals.
Time frame flexibility: The auto-adjustment feature makes the script suitable for scalping (short-term), swing trading (medium-term) and long-term investing.
BUY & SELL Dynamic DCA StrategyOverview
The BUY & SELL Dynamic DCA Strategy is a versatile Pine Script indicator designed for traders seeking a robust Dollar Cost Averaging (DCA) approach to manage both long and short positions across various market conditions and timeframes. This innovative tool combines breakout-based level initiation with a dynamic volatility adjustment, enabling traders to enter positions at optimal DCA points, average them strategically, and manage risk with adjustable stop-loss and take-profit levels. Ideal for scalping on short timeframes (1-minute, 5-minute) or swing trading on longer ones (15-minute, 1-hour, 4-hour).
Purpose and Originality
The "BUY & SELL Dynamic DCA Strategy" stands out by integrating several trading concepts into a cohesive, trader-friendly system. While it leverages familiar elements like breakout points and ATR (Average True Range), its originality lies in:
Dynamic Volatility Adjustment: A custom volatility factor, derived from a capped ATR calculation, dynamically scales DCA entry, averaging, and stop-loss levels. This ensures the strategy adapts to market conditions, tightening in low volatility for scalping and widening in high volatility for swing trading.
Dual-Direction DCA: Supports both buy (long) entries on pullbacks and sell (short) entries on rallies, with tailored averaging and exit strategies for each.
Timeframe Versatility: Adjusts its sensitivity based on the chart timeframe, making it suitable for rapid scalping or longer-term trend riding without requiring manual recalibration.
This unique synthesis justifies its publication as a invite-only script, offering a practical tool that enhances traditional DCA methods with adaptive precision.
How It Works
The indicator operates through a multi-step process designed to optimize entry, averaging, and exit points:
1. Initial Level Setting:
Utilizes high and low threshold (calculated over a user-defined period) to establish initial DCA entry levels. If no threshold is detected, it defaults to the previous bar’s price, ensuring immediate applicability.
2. Dynamic DCA Entry:
Entry levels are adjusted using a proprietary volatility factor, which scales the distance from the current price. Long entries trigger when the price falls below this level, while short entries trigger when the price rises above it, with a volume confirmation filter to reduce noise.
3. Averaging Mechanism:
A secondary level (Averaging Level) allows traders to add to their position when the price moves further against the trade (down for longs, up for shorts). This level is also volatility-adjusted, providing a structured cost-reduction strategy.
4. Risk and Reward Management:
A Final Stop-Loss (Final SL) is set farther out, calculated as a multiple of the volatility-adjusted risk distance, offering protection after averaging.
Take-Profit (TP) levels are determined using a user-defined risk-to-reward ratio, ensuring a balanced exit strategy tailored to market movement.
5. Performance Tracking:
A real-time win/loss table in the top-right corner records trade outcomes, with wins and losses color-coded based on the trade direction (green/red for long, red/green for short), aiding performance evaluation.
Features
1. Dual-Mode Operation : Facilitates both long entries on price dips and short entries on price surges, adaptable to bullish and bearish markets.
2. Volatility-Adaptive Levels: Employs a custom ATR-based adjustment to scale entry, averaging, and stop-loss levels, enhancing responsiveness across timeframes.
3. Visual Tools: Features dashed lines and labels for DCA Entry (green for long, red for short), Final SL (red), and TP (cyan), with debug labels for entries and averages.
4. Timeframe Flexibility: Automatically adjusts threshold periods and volatility factors based on the chart timeframe (1m, 5m, 15m, 1h, 4h), optimizing for scalping or swing trading.
5. Customizable Parameters: Allows fine-tuning of period, DCA factors, and visibility options.
Settings
Base Length (default: 10): Base period for pivot calculations, scaled by timeframe (e.g., 10 becomes 20 on 5m).
Type: 'Wicks' (high/low) or 'Body' (open/close) for price-based levels.
RR Ratio (default: 1.2): Risk-to-reward ratio for TP calculation.
DCA Entry Factor (default: 1.0): Multiplier for volatility-adjusted DCA entry distance.
Avg Level Factor (default: 2.0): Multiplier for averaging level distance.
Final SL Factor (default: 3.0): Multiplier for final stop-loss distance.
SL Type: 'Close' or 'High/Low' for stop-loss evaluation.
Show DCA Entry, Show Avg Level, Show Final SL: Toggle visibility of respective lines.
Show Win/Loss Table: Enable/disable performance tracking.
Line Style: Select 'Solid', 'Dashed', or 'Dotted'.
Usage Instructions
1. Application:
Add the "BUY & SELL Dynamic DCA Strategy - JOAT" via the Pine Editor or community scripts on TradingView.
2. Configuration:
Scalping (1m, 5m): Set Base Length to 5-10, use a low DCA Entry Factor (0.5-1.0) for tight entries, and a Final SL Factor of 2.0-3.0.
Swing Trading (15m, 1h, 4h): Increase Base Length to 15-20, use a higher DCA Entry Factor (1.0-2.0), and set Final SL Factor to 3.0-4.0 for wider stops.
Enable visual elements and adjust Line Style as preferred.
3. Signal Interpretation:
Long Trade: A green dashed "DCA Entry" line below the price triggers a "Long Entry" label on crossover down.
Short Trade: A red dashed "DCA Entry" line above the price triggers a "Short Entry" label on crossover up.
Averaging: A yellow "Avg" label (long) or magenta "Avg" label (short) appears at the respective averaging level.
Exits: TP (cyan) for wins, Final SL (red) for losses, tracked in the win/loss table.
Trade Management:
Scalping: Use 1m/5m for quick trades, averaging as price moves against you.
Swing Trading: Use 15m/1h/4h to capture trends, averaging for cost adjustment.
Manually adjust position size for averaging based on risk tolerance.
5. Performance Monitoring:
The top-right table updates with wins (green/red) and losses (red/green) per trade type, helping assess strategy effectiveness.
Limitations
Manual Averaging: Requires manual position size adjustment at the Averaging Level; automation is not included.
Timeframe Sensitivity: May require parameter tuning for optimal performance across 1m to 4h.
No Trend Filter: Sideways markets may generate noise; adding a trend indicator could enhance accuracy (future development).
Initialization Delay: First trade may be delayed until a pivot is detected, using the current price as a fallback.
Originality Justification
The custom volAdj method, which caps ATR at a percentage of price and scales it by timeframe, offering a unique volatility adjustment not found in standard indicators.
The dual-direction DCA with averaging, combining long and short strategies with volatility-modulated levels, providing a comprehensive trading framework.
The timeframe-adaptive design, automatically adjusting pivot periods and volatility factors, making it a versatile tool across scalping and swing trading.
MEMEQUANTMEMEQUANT
This script is a comprehensive and specialized tool designed for tracking trends and money flow within meme coins and DEX tokens. By combining various features such as trend lines, Fibonacci levels, and category-based indices, it helps traders make informed decisions in highly volatile markets.
Key Features:
1. Category-Based Indices:
• Tracks the performance of token categories like:
• AI Agent Tokens
• AI Tokens
• Animal Tokens
• Murad Picks
• Each category consists of leader tokens, which are selected based on their higher market cap and trading volume. These tokens act as benchmarks for their respective categories.
• Visualizes category indices in a line chart to identify trends and compare money flow between categories.
2. Fibonacci Correction Zones:
• Highlights key retracement levels (e.g., 60%, 70%, 80%).
• These levels are crucial for identifying potential reversal zones, commonly observed in meme coin trading patterns.
• Fully customizable to match individual trading strategies.
3. Trend Lines:
• Automatically detects major support and resistance levels.
• Separates long-term and short-term trend lines, allowing traders to focus on significant price movements.
4. Enhanced Info Table:
• Provides real-time insights, including:
• % Distance from All-Time High (ATH)
• Current Trading Volume
• 50-bar Average Volume
• Volume Change Percentage
• Displays information in an easy-to-read table on the chart.
5. Customizable Settings:
• Users can adjust transparency, colors, and ranges for Fibonacci zones, trend lines, and the table.
• Enables or disables individual features (e.g., Fibonacci, trend lines, table) based on preferences.
How It Works:
1. Tracking Money Flow Across Categories:
• The script calculates the market cap to volume ratio for each category of tokens to help identify the dominant trend.
• A higher ratio indicates greater liquidity and stability, while a lower ratio suggests higher volatility or price manipulation.
2. Identifying Retracement Patterns:
• Leverages common retracement behaviors (e.g., 70% correction levels) observed in meme coins to detect potential reversal zones.
• Combines this with trend line analysis for additional confirmation.
3. Leader Tokens as Indicators:
• Each category is represented by its leader tokens, which have historically higher liquidity and market cap. This allows the script to accurately reflect the overall trend in each category.
When to Use:
• Trend Analysis: To identify which category (e.g., AI Tokens or Animal Tokens) is leading the market.
• Reversal Zones: To spot potential support or resistance levels using Fibonacci zones.
• Money Flow: To understand how capital is moving across different token categories in real time.
Who Is This For?
This script is tailored for:
• Traders specializing in meme coins and DEX tokens.
• Those looking for an edge in trend-based trading by analyzing market cap, volume, and retracement levels.
• Anyone aiming to track money flow dynamics between different token categories.
Future Updates:
This is the initial version of the script. Future updates may include:
• Support for additional token categories and DEX data.
• More advanced pattern recognition and alerts for volume and price anomalies.
• Enhanced visualization for historical data trends.
With this tool, traders can combine money flow analysis with the 60-70% retracement strategy, turning it into a powerful assistant for navigating the fast-paced world of meme coins and DEX tokens.
This script is designed to provide meaningful insights and practical utility for traders, adhering to TradingView’s standards for originality, clarity, and user value.
