Monthly Drawdowns and Moves UP This script allows users to analyze the performance of a specific month across multiple years, focusing on maximum drawdowns and maximum upward moves within the selected month. The script offers the following features:
Dynamic Month Selection : Choose any month to analyze using an intuitive dropdown menu.
Maximum Drawdown and Upward Move Calculations :
Calculate the largest percentage drop (drawdown) and rise (move up) for the selected month each year.
Visual Highlights :
The selected month is visually highlighted on the chart with a semi-transparent overlay.
Dynamic Labels:
Labels display the maximum drawdown and upward move directly on the chart for better visualization.
Comprehensive Table Summary:
A table provides a year-by-year summary of the maximum drawdowns and upward moves for the selected month, making it easy to spot trends over time.
Customizable Display Options:
Toggle the visibility of drawdown labels, move-up labels, and the summary table for a clutter-free experience.
This tool is perfect for traders and analysts looking to identify seasonal patterns, assess risk and opportunity, and gain deeper insights into monthly performance metrics across years. Customize, explore, and make informed decisions with this powerful Pine Script indicator.
Wyszukaj w skryptach "Cycle"
Weighted Fourier Transform: Spectral Gating & Main Frequency🙏🏻 This drop has 2 purposes:
1) to inform every1 who'd ever see it that Weighted Fourier Tranform does exist, while being available nowhere online, not even in papers, yet there's nothing incredibly complicated about it, and it can/should be used in certain cases;
2) to show TradingView users how they can use it now in dem endevours, to show em what spectral filtering is, and what can they do with all of it in diy mode.
... so we gonna have 2 sections in the description
Section 1: Weighted Fourier Transform
It's quite easy to include weights in Fourier analysis: you just premultiply each datapoint by its corresponding weight -> feed to direct Fourier Transform, and then divide by weights after inverse Fourier transform. Alternatevely, in direct transform you just multiply contributions of each data point to the real and imaginary parts of the Fourier transform by corresponding weights (in accumulation phase), and in inverse transform you divide by weights instead during the accumulation phase. Everything else stays the same just like in non-weighted version.
If you're from the first target group let's say, you prolly know a thing or deux about how to code & about Fourier Transform, so you can just check lines of code to see the implementation of Weighted Discrete version of Fourier Transform, and port it to to any technology you desire. Pine Script is a developing technology that is incredibly comfortable in use for quant-related tasks and anything involving time series in general. While also using Python for research and C++ for development, every time I can do what I want in Pine Script, I reach for it and never touch matlab, python, R, or anything else.
Weighted version allows you to explicetly include order/time information into the operation, which is essential with every time series, although not widely used in mainstream just as many other obvious and right things. If you think deeply, you'll understand that you can apply a usual non-weighted Fourier to any 2d+ data you can (even if none of these dimensions represent time), because this is a geometric tool in essence. By applying linearly decaying weights inside Fourier transform, you're explicetly saying, "one of these dimensions is Time, and weights represent the order". And obviously you can combine multiple weightings, eg time and another characteristic of each datum, allows you to include another non-spatial dimension in your model.
By doing that, on properly processed (not only stationary but Also centered around zero data), you can get some interesting results that you won't be able to recreate without weights:
^^ A sine wave, centered around zero, period of 16. Gray line made by: DWFT (direct weighted Fourier transform) -> spectral gating -> IWFT (inverse weighted Fourier transform) -> plotting the last value of gated reconstructed data, all applied to expanding window. Look how precisely it follows the original data (the sine wave) with no lag at all. This can't be done by using non-weighted version of Fourier transform.
^^ spectral filtering applied to the whole dataset, calculated on the latest data update
And you should never forget about Fast Fourier Transform, tho it needs recursion...
Section 2: About use cases for quant trading, about this particular implementaion in Pine Script 6 (currently the latest version as of Friday 13, December 2k24).
Given the current state of things, we have certain limits on matrix size on TradingView (and we need big dope matrixes to calculate polynomial regression -> detrend & center our data before Fourier), and recursion is not yet available in Pine Script, so the script works on short datasets only, and requires some time.
A note on detrending. For quality results, Fourier Transform should be applied to not only stationary but also centered around zero data. The rightest way to do detrending of time series
is to fit Cumulative Weighted Moving Polynomial Regression (known as WLSMA in some narrow circles xD) and calculate the deltas between datapoint at time t and this wonderful fit at time t. That's exactly what you see on the main chart of script description: notice the distances between chart and WLSMA, now look lower and see how it matches the distances between zero and purple line in WFT study. Using residuals of one regression fit of the whole dataset makes less sense in time series context, we break some 'time' and order rules in a way, tho not many understand/cares abouit it in mainstream quant industry.
Two ways of using the script:
Spectral Gating aka Spectral filtering. Frequency domain filtering is quite responsive and for a greater computational cost does not introduce a lag the way it works with time-domain filtering. Works this way: direct Fourier transform your data to get frequency & phase info -> compute power spectrum out of it -> zero out all dem freqs that ain't hit your threshold -> inverse Fourier tranform what's left -> repeat at each datapoint plotting the very first value of reconstructed array*. With this you can watch for zero crossings to make appropriate trading decisions.
^^ plot Freq pass to use the script this way, use Level setting to control the intensity of gating. These 3 only available values: -1, 0 and 1, are the general & natural ones.
* if you turn on labels in script's style settings, you see the gray dots perfectly fitting your data. They get recalculated (for the whole dataset) at each update. You call it repainting, this is for analytical & aesthetic purposes. Included for demonstration only.
Finding main/dominant frequency & period. You can use it to set up Length for your other studies, and for analytical purposes simply to understand the periodicity of your data.
^^ plot main frequency/main period to use the script this way. On the screenshot, you can see the script applied to sine wave of period 16, notice how many datapoints it took the algo to figure out the signal's period quite good in expanding window mode
Now what's the next step? You can try applying signal windowing techniques to make it all less data-driven but your ego-driven, make a weighted periodogram or autocorrelogram (check Wiener-Khinchin Theorem ), and maybe whole shiny spectrogram?
... you decide, choice is yours,
The butterfly reflect the doors ...
∞
Weekly Stacked Daily Changes [LuxAlgo]The Weekly Stacked Daily Changes tool allows traders to compare daily net price changes for each day of the week, stacked by week. It provides a very convenient way to compare daily and weekly volatility at the same time.
🔶 USAGE
The tool requires no configuration and works perfectly out of the box, displaying the net price change for each day of the week as stacked boxes of the appropriate size.
Traders can adjust the width of the columns and the spacing between days and weeks, options to change the color and disable the months and new month lines are also available.
🔹 Bottom Stack Bias
This feature allows traders to compare weekly volatility in two different ways.
With this feature disabled, all weeks use zero as the bottom of the stack, so traders can see at a glance weeks with more volatility and weeks with less volatility.
Enabling this feature will cause the tool to display the stacks with the weekly net price change as the bottom, so if a stack starts below the zero line it means that week has a negative net return, and if it starts above the zero line it means that week has a positive net return.
🔶 SETTINGS
Width: Select the fixed width for each column.
Offset: Choose the fixed width between each column.
Spacing: Select the distance between each day within each column.
🔹 Style
Bottom Stack Bias: Use weekly net price change as the bottom of the stack.
Bullish Change: Color for days with positive net price change
Bearish Change: Color for days with negative net price change
Show Months: Under each week stack, display the month
Show Months Delimiter: Display a line indicating the start of a new month
Fibonacci Time PeriodsThe " Fibonacci Time Periods " indicator uses power exponents of the constant Phi based on your custom time period to generate Fibonacci sequence-based progression on a given chart. This tool can help to anticipate the timing of potential turning points by highlighting Fib time zones where significant price movements may occur.
It is different from other alternatives specifically for the ability to alter the rate of progression .
Most famous regular Fib sequence expands with 1.618^(n+1) rate which produces vast change just after few iterations.
Those ever-expanding big intervals don't allow us to cover the smaller details of the chart which we might find crucial. So, the idea was born to break down the constant Phi to a self-fraction using power exponents. In other words, reducing rate of progression to make the expansion more gradual without losing properties of Fibonacci proportions.
Default settings have a rate of 0.25 which is basically Phi^1/4
That means we expect 4x more lines than in regular sequence to cover missing bits owing to formula: 1.618^(0.25*(n+1))
(Line 0.618 is added to enhance visual orientation and perception of proportions)
How it works:
Exponential rate of progression
First, it works out the difference between your custom start (0) and end (1) period
The result is multiplied by 1.618^rate to get the step
Rest lines are created by iterations. For instance, with default rate of 0.25, the 1st generated line = start + (End-Start)*1.618^0.25* 1 , second line = start + (End-Start)*1.618^0.25* 2 , etc.
If we change the rate to 1 it will produce the regular fib sequence with 1.618^(n+1) rate
Fixed rate of progression:
In this mode, when rate is 0.25, it grows exactly with exponent step of 0.25 so first, second, third, etc generated lines also have the fixed exponent of 0.25. The distance between lines do not expand.
How to use:
Set the start and end dates
Choose the type of progression
Choose your desired rate of progression
Customize the colors to match your chart preferences.
Observe the generated Fibonacci time intervals and use them to identify potential market movements and reactions.
trend_switch
█ Description
Asset price data was time series data, commonly consisting of trends, seasonality, and noise. Many applicable indicators help traders to determine between trend or momentum to make a better trading decision based on their preferences. In some cases, there is little to no clear market direction, and price range. It feels much more appropriate to use a shorter trend identifier, until clearly defined market trend. The indicator/strategy developed with the notion aims to automatically switch between shorter and longer trend following indicator. There were many methods that can be applied and switched between, however in this indicator/strategy will be limited to the use of predictive moving average and MESA adaptive moving average (Ehlers), by first determining if there is a strong trend identified by calculating the slope, if slope value is between upper and lower threshold assumed there is not much price direction.
█ Formula
// predictive moving average
predict = (2*wma1-wma2)
trigger = (4*predict+3*predict +2*predict *predict)
// MESA adaptive moving average
mama = alpha*src+(1-alpha)*mama
fama = .5*alpha*mama+(1-.5-alpha)*fama
█ Feature
The indicator will have a specified default parameter of:
source = ohlc4
lookback period = 10
threshold = 10
fast limit = 0.5
slow limit = 0.05
Strategy type can be switched between Long/Short only and Long-Short strategy
Strategy backtest period
█ How it works
If slope between the upper (red) and lower (green) threshold line, assume there is little to no clear market direction, thus signal predictive moving average indicator
If slope is above the upper (red) or below the lower (green) threshold line, assume there is a clear trend forming, the signal generated from the MESA adaptive moving average indicator
█ Example 1 - Slope fall between the Threshold - activate shorter trend
█ Example 2 - Slope fall above/below Threshold - activate longer trend
Advanced MACD [CryptoSea]Advanced MACD (AMACD) enhances the traditional MACD indicator, integrating innovative features for traders aiming for deeper insights into market momentum and sentiment. It's crafted for those seeking to explore nuanced behaviors of the MACD histogram, thus offering a refined perspective on market dynamics.
Divergence moves can offer insight into continuation or potential reversals in structure, the example below is a clear continuation signal.
Key Features
Enhanced Histogram Analysis: Precisely tracks movements of the MACD histogram, identifying growth or decline periods, essential for understanding market momentum.
High/Low Markers: Marks the highest and lowest points of the histogram within a user-defined period, signaling potential shifts in the market.
Dynamic Averages Calculation: Computes average durations of histogram phases, providing a benchmark against historical performance.
Color-Coded Histogram: Dynamically adjusts the histogram's color intensity based on the current streak's duration relative to its average, offering a visual cue of momentum strength.
Customisable MACD Settings: Enables adjustments to MACD parameters, aligning with individual trading strategies.
Interactive Dashboard: Showcases an on-chart table with average durations for each phase, aiding swift decision-making.
Settings & Customisation
MACD Settings: Customise fast length, slow length, and signal smoothing to tailor the MACD calculations to your trading needs.
Reset Period: Determine the number of bars to identify the histogram's significant high and low points.
Histogram High/Lows: Option to display critical high and low levels of the histogram for easy referencing.
Candle Colours: Select between neutral or traditional candle colors to match your analytical preferences.
When in strong trends, you can use the average table to determine when to look to get into a position. This example we are in a strong downtrend, we then see the histogram growing above the average in these conditions which is where we should look to get into a shorting position.
Strategic Applications
The AMACD serves not just as an indicator but as a comprehensive analytical tool for spotting market trends, momentum shifts, and potential reversal points. It's particularly useful for traders to:
Spot Momentum Changes Utilise dynamic coloring and streak tracking to alert shifts in momentum, helping anticipate market movements.
Identify Market Extremes Use high and low markers to spot potential market turning points, aiding in risk management and decision-making.
Alert Conditions
Above Average Movement Alerts: Triggered when the duration of the MACD histogram's growth or decline is unusually long, these alerts signal sustained momentum:
Above Zero: Alerts for both growing and declining movements above zero, indicating either continued bullish trends or potential bearish reversals.
Below Zero: Alerts for growth and decline below zero, pointing to potential bullish reversals or confirmed bearish trends.
High/Low Break Alerts: Activated when the histogram reaches new highs or falls to new lows beyond the set thresholds, these alerts are crucial for identifying shifts in market dynamics:
Break Above Last High: Indicates a potential upward trend as the histogram surpasses recent highs.
Break Below Last Low: Warns of a possible downward trend as the histogram drops below recent lows.
These alert conditions enable traders to automate part of their market monitoring or potential to automate the signals to take action elsewhere.
Global Net Liquidity (TG fork)Worldwide net liquidity, with trend coloring.
Global Net Liquidity attempts to represent worldwide net liquidity, and is defined as: Fed + Japan + China + UK + ECB - RRP - TGA , Where the first five components are central bank assets.
On TradingView, the indicator can be reproduced with the following equations: Global Net Liquidity = FRED:WALCL + FRED:JPNASSETS * FX_IDC:JPYUSD + CNCBBS * FX_IDC:CNYUSD + GBCBBS * FX:GBPUSD + ECBASSETSW * FX:EURUSD + RRPONTSYD + WTREGEN
However, this indicator adds a moving average cloud, and margin coloring, which eases historical trend assessment at a glance.
This indicator can be seen as an alternative representation of the accumulation/distribution indicator (and hence the same terms can be used in this description).
The Moving Average Cloud is simply the filling between the moving average (by default an EMA) and the current value. This feature was inspired by D7R ACC/DIST closed-source indicator, kudos to D7R for making such neat visual indicators.
Usage instructions:
Blue is more likely a phase of accumulation because the current value is above its historical price as defined by the moving average,
red is when this is more likely a phase of distribution.
Yellow is when the difference is below the margin, so we consider it is insignificant and that the trend is undecided. This can be disabled by setting the margin to 0.
While the color indicates if it's more likely an accumulation (blue) or distribution (red) phase or undecided (yellow), the cloud's vertical size allows to assess the strength of this tendency and the horizontal size the momentum, so that the bigger the cloud, the stronger the accumulation (if cloud is blue) or distribution (if cloud is red).
Why is that so? This is because the cloud represents the difference between the current tendency and the moving averaged past one, so a bigger cloud represents a bigger departure from recently observed tendencies. In practice, when there is accumulation, a pump in price can be expected soon, or if it already happened then it means it is indeed supported by volume, whereas if distribution, either a dump is to be expected soon, or if it already happened it means it's supported by volume.
Or maybe not necessarily a dump, but if there is a move upward in price, but the indicator indicates a strong distribution, then it means that the price movement is not supported and may not be sustainable (reversal may happen at anytime), whereas if price is going upward AND there is an accumulation (blue coloring) then it is more sustainable. This can be used to adapt strategies accordingly (risk on/risk off depending on whether there is concordance of both price and accumulation/distribution).
This indicator also includes sentiment signals that can be used to trigger alarms.
This indicator is a remix of Dharmatech's, who authored the first this Global Net Liquidity equation, kudos to them! Please show them some love if you like this indicator!
MVRV Z-ScoreThe MVRV ratio was created by Murad Mahmudov & David Puell. It simply compares Market Cap to Realised Cap, presenting a ratio (MVRV = Market Cap / Realised Cap). The MVRV Z-Score is a later version, refining the metric by normalising the peaks and troughs of the data.
Fierytrading: Volatility DepthDear Tradingview community,
I'd like to share one of my staple indicators with you. The volatility depth indicator calculates the volatility over a 7-day period and plots it on your chart.
This indicator only works for the DAILY chart on BTC/USD.
Colors
I've color coded the indicator as follows:
- Red: Extreme Volatility
- Orange: High Volatility
- Yellow: Normal Volatility
- Green: Low Volatility
Red: extreme changes in price. Often during local tops and bottoms.
Orange: higher than average moves in price. Often before or after a "red" period. Often seen in the middle of bear or bull markets.
Yellow: normal price action. Often seen during early stage bull-markets and late stage bear-markets.
Green: very low price movement. Often during times of indecision. Once this indicator becomes green, you can expect a big move in either direction. Low volatility is always followed by high volatility.
In a long-term uptrend, a green period often signals a bullish break out. In a long-term downtrend it often signals a bearish break out.
How to use
Save the indicator and apply it to your chart. You can change the length in the settings, but it's optimized for 7 days, so no need to change it.
I've build in alerts for all 4 different volatility periods. In most cases, the low volatility alert is enough.
Good luck!
Fed Projected Interest RatesThis script shows you the current interest rates by the FED (see ZQ symbol nearest expiration)
and the next expirations (see ZQ further expiration dates).
It is important to keep your expiration and descriptions up to date, to do that to the indicator inputs and change as you please.
RS Stage AnalysisThis script trying to detect different lifecycle of stock / Stages.
There is mainly 4 stages of stocks.
1) stage 1 - Accumulation = color = aqua
2) stage 2 - Advancing = color = green
3) stage 3 - Distribution = color = yellow
4) stage 4 - Declining = color = red
At some point the condition i wrote wont detect any stage.
Stan Weinstein Trend IndicatorThis indicator is a trend indicator for trading charts based on the method of Stan Weinstein. It uses various technical methods to identify four trend phases on an asset: consolidation, advancement, plateauing, and decline. Users can customize the indicator by modifying parameters such as the periods for various calculations, such as the exponential moving average (EMA), the relative strength index (RSI), and support and resistance levels. The results of these calculations are then used to determine if an asset is in a phase of consolidation, advancement, plateauing, or decline.
The results are displayed as markers on the chart, with the following colors:
White: Consolidation
Green: Advancement
Blue: Plateauing
Red: Decline
According to the method of Stan Weinstein, it is recommended to buy an asset during an advancement phase and sell it during a plateauing phase. Similarly, it is recommended to sell an asset during a decline phase and cut this sale when the consolidation phase starts. It is important to note that this indicator is for informational purposes only and should not be used as investment advice. It is important to conduct fundamental and technical analysis before making an investment decision. It is also recommended to combine this analysis with other methods for optimal results and to consider the risks associated with any investment.
All default parameters of this indicator have been carefully chosen to provide the best possible results, however, it is possible to modify them according to personal preferences. It is important to note that modifying certain parameters may make the indicator less relevant and it is therefore recommended not to deviate too much from default values, unless you have a good understanding of the Stan Weinstein method and the technical indicators used.
It is important to note that this indicator is optimized for 1-week charts. It can be used to look at charts at other timeframes but calculations will always be based on weekly data.
Also, it is noteworthy that this indicator is optimized for cryptocurrencies, except Bitcoin, as it is used to calculate the relative strength of a token. However, you can choose the asset or index you want in the menu to calculate the relative strength. Furthermore, all the default settings are carefully chosen, but users are free to modify them, but doing so may result in less relevant results.
AlexD Market annual seasonalityThe indicator displays the percentage of bullish days with a given date over several years.
This allows you to determine the days of the year when the price usually goes up or down.
Indicator has a built-in "simple moving average" shifted back by half a period, due to which the delay of this smoothing is removed.
ciclo e velocita cicloCycle analisys made by MA builted usisng the difference between 2 MA , one with lenght double then the other one. Cycle speed indicator is the moment of the Cycle MA and give us the up or down of the Cycle MA
7:00-9:30 ET High/LowThis indicator is designed to identify and plot the highest and lowest price levels within the 7:00 AM to 9:30 AM Eastern Time (ET) trading window. These levels are then extended throughout the trading day, providing clear visual references for potential support and resistance derived from the early morning price action.
Core Functionality
The script defines a specific trading session (7:00-9:30 ET) and tracks the highest high and lowest low price reached during that time. Once the session is over, these high and low lines remain on the chart for the rest of the day, acting as key levels for traders to watch. At the start of each new trading day, the indicator resets, clearing the previous day's lines and drawing new ones based on the current day's morning session.
Features and Customization
This indicator is fully customizable through the settings menu, allowing you to tailor the appearance to perfectly suit your chart layout.
Session High Line:
Customize the color, width, and line style (Solid, Dashed, Dotted).
Session High Label:
Set your own custom label text (e.g., "Morning High").
Customize the label's background color.
Customize the label's text color.
Adjust the text size.
Session Low Line:
Customize the color, width, and line style (Solid, Dashed, Dotted).
Session Low Label:
Set your own custom label text (e.g., "Morning Low").
Customize the label's background color.
Customize the label's text color.
Adjust the text size.
ORB + SMA 20/50 Crossover BUY/SELL by Yuvaraj Veppampattu Plots ORB High & Low lines for the first X minutes.
Adds SMA 20 & SMA 50 lines on chart.
Shows BUY arrow when SMA20 crosses ABOVE SMA50.
Shows SELL arrow when SMA20 crosses BELOW SMA50.
Adds alerts for both ORB breakouts & SMA crossovers.
Multi-Strategy Trading Screener SummaryI only combined famous scripts, all thanks to wonderful scripts and community out there .
ThankYou !
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Core Architecture
Multi-Symbol Analysis: Tracks up to 5 configurable tickers simultaneously
Multi-Timeframe Support: Each symbol can use different timeframes
Real-Time Dashboard: Color-coded table displaying all signals and analysis
Trend Validation: All signals include trend alignment confirmation
Integrated Trading Strategies
1. Breaker Blocks (Order Blocks)
Detects institutional order blocks using swing analysis
Tracks when blocks are broken and become "breaker blocks"
Monitors retests of broken levels
Shows trend alignment (✓ aligned, ⚠️ misaligned)
2. Chandelier Exit
ATR-based trend-following exit system
Provides BUY/SELL signals based on dynamic stop levels
Uses configurable ATR multiplier and lookback period
3. Smart Money Breakout
Channel breakout detection with volatility normalization
Identifies accumulation/distribution phases
Generates persistent BUY/SELL signals on breakouts
4. Trendline Breakout
Dynamic trendline detection using pivot highs/lows
Calculates trendline slopes and breakout points
Provides BUY signals on upward breaks, SELL on downward breaks
Dashboard Columns Explained
Symbol: Ticker being analyzed
Trend: Overall SuperTrend direction (🟢 UP / 🔴 DOWN / ⚪ FLAT)
Timeframe: Analysis timeframe with clock icon
Breaker Block: Type (Bullish/Bearish) with trend alignment indicator
Status: Price position relative to breaker block (Inside/Approaching/Far)
Retests: Number of times the broken level was retested (indicates level strength)
Volume: Volume associated with the order block formation
Chandelier: BUY/SELL signals from Chandelier Exit strategy
Smart Money: BUY/SELL signals from breakout detection
Trendline: BUY/SELL signals from trendline breakouts
Key Features
No HOLD States: All signals show definitive BUY (🟢) or SELL (🔴) only
Persistent Signals: Signals remain active until opposite conditions trigger
Color Coding: Visual distinction between bullish (green) and bearish (red) signals
Trend Alignment: Enhanced accuracy through trend confirmation logic
This screener provides a comprehensive view of market conditions across multiple strategies, helping identify high-probability trading opportunities when signals align.
HIFI Altcoin Season Index (Total3 vs BTC)This indicator helps you determine whether the crypto market is in an "altcoin season" or a "bitcoin season." It doesn't compare every single altcoin to Bitcoin individually; instead, it uses a more efficient approach.
Methodology
The index calculates the difference in price performance over a selected period (default 90 days) between the total market capitalization of altcoins without Ethereum (TOTAL3) and Bitcoin (BTC).
Interpretation
Value above 75: TOTAL3 is showing significantly stronger growth than BTC, indicating an ALTCOIN SEASON. 🚀
Value below 25: BTC is outperforming TOTAL3, indicating a BITCOIN SEASON. 👑
Value between 25 and 75: The market is in a mixed or neutral phase. 🤷
Benefits
This method avoids the technical limitations of Pine Script when requesting data for a large number of symbols, making the indicator stable and reliable.
Disclaimer: This indicator is a tool for market analysis and should not be considered financial advice.
ICT 00:00, 08:30, 09:30 & 13:30 Opens (NY) — Prior-Day HistoryICT 00:00, 08:30, 09:30 & 13:30 Opens (NY)
This is a derivative of ALPHAICTRADER’s open-source script, republished under the MPL-2.0 with clear attribution and documented changes. It plots four New-York–anchored intraday reference levels—0000, 0830, 0930, 1330—as short, right-padded stubs with clean side labels. Use these time anchors (ICT-style midnight + key US windows) to frame bias, volatility pockets, and intraday trade locations.
What’s original in this version (changes)
Right-padded stubs instead of chart-wide rays — each level ends N bars past the latest candle (configurable).
Side labels at the line tip — text-only labels (0000, 0830, 0930, 1330) that sit at the right end of each stub and update every bar.
Optional prior-day history — show Today only or Today + Prior Day; older lines/labels auto-pruned.
Per-anchor controls — Display, Style, Color, Width, and Show Label for each time.
What it plots (and why)
0000 (NY Midnight): daily session anchor for bias/liquidity context.
0830 (NY): macro data window (CPI/NFP/claims) where volatility often concentrates.
0930 (NY): US cash equity market open; opening-drive structure/acceptance tests.
1330 (NY): early-afternoon anchor for continuation vs. fade.
How it works (under the hood)
Session detection: time("1", session, "America/New_York"); first bar flagged via not na(ts) and na(ts ).
Anchor price: open of that first bar per session/day.
Rendering: lines drawn with xloc=bar_index from start bar to bar_index + Right Pad; x2 updates every bar (no extend.right).
Labels: placed at line.get_x2(line) + Label Pad, soft color variant; updated per bar to stay on the tip.
History: arrays keep either today only or today + yesterday and delete anything older immediately.
How to use
Add to any intraday chart (futures/FX/indices). Anchors are always NY-time; TradingView handles DST.
Inputs
00:00 / 08:30 / 09:30 / 13:30 (NY): Display, Line Style, Color, Width, Show Label
Right Edge: Right Pad (bars) · Label Pad (bars)
History: Show Prior Day (History) — off = today only; on = today + yesterday
Suggested pads: Right Pad 2–5 bars; Label Pad 0–2.
These are context anchors, not signals. Combine with your execution model (market structure, liquidity, FVG/OBs, etc.).
Attribution & License (MPL-2.0)
Original work: “ICT NEW YORK MIDNIGHT OPEN AND 8.30 AM OPEN” by ALPHAICTRADER (MPL-2.0).
This derivative: modifications listed above; source published and kept under MPL-2.0 per license terms.
If you distribute a modified version of this Pine file, you must keep MPL-2.0, retain the copyright/licensing header, publish your modified source, and document your changes.
Notes: Pine v5. Minimalist (no day dividers). Educational tool; not financial advice.
Copyright: © ALPHAICTRADER 2022 · © Funk 2025
License: MPL-2.0
Contract Interest Turnover T3 [T69]Overview
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Contract Interest Turnover (CIT) estimates how “churny” a crypto derivatives market is by comparing the amount traded in a bar to the base stock of outstanding contracts (open interest). It normalizes both Volume and Open Interest (OI) by Price (Close), then plots a Turnover Rate = (Volume/Close) ÷ (OI/Close) as colored columns. Higher values = faster contract recycling (strong momentum / hype potential).
Features
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- Auto-fetch OI: Pulls OI via request.security(_OI, …) when the exchange/symbol exposes an OI stream on TradingView.
- Price-normalized comparison: Converts both Volume and OI into comparable notional terms by dividing each by Close.
- Turnover columns with threshold: Color the columns green once Turnover ≥ your set threshold; gray otherwise.
- Status-line readouts: Displays normalized Volume and OI values for quick sanity checks.
- Crypto-aware timeframe: Uses chart TF for crypto; forces daily OI when not crypto to avoid noisy intraday pulls.
How to Use
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1. Add the script on a perpetual/futures symbol that has OI on TradingView (e.g., BTC perps where an _OI feed exists).
2. Watch the Turnover Rate bars: spikes above your threshold flag sessions where contracts are actively flipping.
3. Interpret spikes as a signal of movement or activity — it does not specify price direction, only that the market is engaged and contracts are being traded more intensely than usual.
Configuration
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- Interest Turnover Threshold (default 1.0): colors columns green when Turnover ≥ threshold. Tune per market’s typical churn profile.
Under the Hood (Formulas & Logic)
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- Fetch OI
oiClose ← request.security(ticker.standard(syminfo.tickerid) + "_OI", timeframe, close) with ignore_invalid_symbol = true.
If none is found, the script throws a clear runtime error.
- Normalize to price
vol_norm = volume / close
oi_norm = oiClose / close
This converts both to a common notional basis so their ratio is meaningful even as price changes.
- Turnover Rate
turnover = vol_norm / oi_norm
Interpretation: fraction/multiples of the outstanding contract base traded in the bar. Color = green if turnover ≥ threshold.
Why Open Interest ≈ “Float” Proxy
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In stocks, float ≈ shares the public can trade. In derivatives, there are no “shares,” so Open Interest acts as the live stock of active contracts. It’s the best proxy for “what’s available in play” because it counts open positions that persist across bars. Using Volume ÷ OI mirrors stock float-turnover logic: how fast the tradable base is being recycled each period.
Why Normalize by Price
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Derivatives volume and OI may be reported in contracts, not notional value. One contract’s economic weight changes with price (especially on inverse contracts). Dividing both Volume and OI by Close:
- Puts them on a comparable notional footing.
- Prevents false spikes purely from price moves.
- Makes Turnover comparable across time even as price trends.
Advanced Tips
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- Calibrate threshold: Start from the 80th–90th percentile of the last 60–90 bars of Turnover; set the threshold a touch below that to surface early heat.
- Add OI-delta: Layer an OI change histogram (current − prior) to separate new positioning from pure churn.
- Linear vs inverse: For linear (USDT-margined) contracts, the normalization still works and keeps visuals consistent; for inverse, it’s essential.
Limitations
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- Data availability: Works only if your symbol exposes an _OI feed on TradingView; otherwise it errors out.
- Exchange conventions: Volume units differ by venue (contracts, coin, notional). Normalization mitigates, but cross-symbol comparisons still need caution.
- Intrabar gaps: OI is typically end-of-bar; rapid intrabar shifts won’t appear until the bar closes.
Notes
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- Designed primarily for crypto derivatives. For non-crypto, the script blanks OI to avoid misleading plots and uses a daily TF when needed.
Credit
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- Concept & data: Built for TradingView data feeds.
- Acknowledgment: Credit to TradingView default indicator as requested.
- Source: This write-up reflects the logic present in your uploaded script.
Disclaimer
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Markets move; indicators simplify. Use with position sizing, hard stops, and catalyst awareness. The Turnover Rate flags activity, not direction.
KRQ Sessions Asia, Frankfurt, London, NY Open, NY Trap, MM1, MM2Every important timeframe.
1. Asia
2. Frankfurt
3. London
4. NY Open
5. NY Trap
6. MM1
7. MM2
Custom Time Range HighlightThis indicator highlights specific time ranges on your TradingView chart with customizable background colors and labels, making it easier to identify key trading sessions and ICT (Inner Circle Trader) Killzones. It is designed for traders who want to mark important market hours, such as major sessions (Asia, New York, London) or high-volatility Killzones, with full control over activation, timing, colors, and transparency.
Features
Customizable Time Ranges: Define up to 9 different time ranges, including one custom range, three major market sessions (Asia, New York, London), and five ICT Killzones (Asia, NY Open, NY Close, London Open, London Close).
Individual Activation: Enable or disable each time range independently via checkboxes in the settings. By default, only the ICT Killzones are active.
Custom Colors and Transparency: Set unique background and label colors for each range, with adjustable transparency for both.
Labeled Time Ranges: Each active range is marked with a customizable label at the start of the period, displayed above the chart for easy identification.
Priority Handling: If multiple ranges overlap, the range with the higher number (e.g., Asia Killzone over Custom Range) determines the background color.
CET Time Zone: Time ranges are based on Central European Time (CET, Europe/Vienna). Adjust the hours and minutes to match your trading needs.
Settings
The indicator settings are organized into three groups for clarity:
Custom Range: A flexible range (default: 15:30–18:00 CET) for user-defined periods.
Session - Asia, NY, London: Major market sessions (Asia: 01:00–10:00, New York: 14:00–23:00, London: 09:00–18:00 CET).
ICT Killzones - Asia, NY, London: High-volatility periods (NY Open: 13:00–16:00, NY Close: 20:00–23:00, London Open: 08:00–11:00, London Close: 16:00–18:00, Asia: 02:00–05:00 CET).
For each range, you can:
Toggle activation (default: only ICT Killzones enabled).
Adjust start and end times (hours and minutes).
Customize the label text.
Choose background and label colors with transparency levels (0–100).
How to Use
Add the indicator to your chart.
Open the settings to enable/disable specific ranges, adjust their times, or customize colors and labels.
The chart will highlight active time ranges with the selected background colors and display labels at the start of each range.
Use it to focus on key trading periods, such as ICT Killzones for high-probability setups or major sessions for market analysis.
Notes
Ensure your time ranges align with your trading instrument’s session times.
Overlapping ranges prioritize higher-numbered ranges (e.g., Asia Killzone overrides London Session).
Ideal for day traders, scalpers, or ICT strategy followers who need clear visual cues for specific market hours.
Feedback
If you have suggestions for improvements or need help with customization, feel free to leave a comment or contact the author!
Highlight Specific Time CandleThis is a simple Pine Script tool that marks candles occurring at a chosen time of the day. You can set the hour and minute (in 24-hour format) from the inputs, and whenever a candle’s timestamp matches that time, the indicator highlights it with a symbol above the bar and an optional background colour.
This is useful for:
Identifying key intraday times (e.g., market open, midday, closing).
Spotting how price reacts at scheduled events (economic data releases, news times).
