FACTOR MONITORThe Factor Monitor is a comprehensive designed to track relative strength and standard deviation movements across multiple market segments and investment factors. The indicator calculates and displays normalized percentage moves and their statistical significance (measured in standard deviations) across daily, 5-day, and 20-day periods, providing a multi-timeframe view of market dynamics.
Key Features:
Real-time tracking of relative performance between various ETF pairs (e.g., QQQ vs SPY, IWM vs SPY)
Standard deviation scoring system that identifies statistically significant moves
Color-coded visualization (green/red) for quick interpretation of relative strength
Multiple timeframe analysis (1-day, 5-day, and 20-day moves)
Monitoring of key market segments:
Style factors (Value, Growth, Momentum)
Market cap segments (Large, Mid, Small)
Sector relative strength
Risk factors (High Beta vs Low Volatility)
Credit conditions (High Yield vs Investment Grade)
The tool is particularly valuable for:
Identifying significant factor rotations in the market
Assessing market breadth through relative strength comparisons
Spotting potential trend changes through statistical deviation analysis
Monitoring sector leadership and market regime shifts
Quantifying the magnitude of market moves relative to historical norms
在腳本中搜尋"采列VS新圣徒"
Tops & Bottoms by Volume [SS]Hey everyone,
Releasing this indicator that helps you time entries by alerting to potential tops and bottoms in the market.
Background to the indicator:
I was playing around with things that signalled reversals / tops and bottoms in SPSS and R using Pivot Points to mark tops and bottoms. Happened to come across a generally statistically significant relationship between sell to buy volume that was tracked over 10 to 50 candles back and pivot highs and pivot lows.
So I put it into a beta version of an indicator to see how it looked and was a bit surprised.
Since then, I have went back and narrowed down the details of what works/what doesn't work and this is the tentative result!
What it does / How to Use:
It tracks the cumulative buy vs sell volume. Buy volume is cumulated as close > open (or green candles) and sell is open > close (or red candles).
It then cumulates this over a user-defined period (defaulted to 14). It then looks back to see the highest vs lowest areas of sell and buy volume and makes determinations based on this relationship.
The relationship was determined by me using my own analysis and programmed into the indicators algorithm (using highest vs lowest function in pine).
It will plot areas of potential reversal to the upside as green on the histogram or red for a downside reversal. Once this becomes significant enough to signal an actual bottom or top, it will then change the SMA colour from white to green (for bottom) or red (for top).
Your entries generally should be once the SMA turns back to white. So from green to white, you would enter long or inverse for red to white (enter short).
Settings and Customizability:
Here are the key points to keep in mind if you are using this indicator:
Your lookback length should be between 10 to 50. I have left it open for you to modify it below and above this lookback period; however, this is the major periods deemed to be significant in identifying tops and bottoms. Thus, I advise against operating outside of those parameters.
You can toggle between smoothed look or historgram with SMA. The strength in this indicator comes from using the SMA and watching the SMA for signals of reversals, so if you want to filter out the background noise, you can simply look at the plotted SMA. If you want a more responsive indication of impending reversals, leave the smoothed option off and view the histogram in conjunction with the SMA.
The indicator will change the candle colour to red for bearish reversal and green to bullish reversal. This is based on the SMA. You can toggle this off and/or on as desired.
It is recommended to leave ETH (extended trading hours) turned off and RTH turned on.
Please read the instructions carefully.
If you require further assistance, I have posted a tutorial video.
Please be sure you are reading and/or watching carefully.
If you have questions, please feel free to post them below. But bear in mind I likely will not respond if it is already addressed in the description above (this happens often).
Also, feel free to leave your comments or suggestions below as well.
Thanks for checking this out. If you are interested in volume based trading, I suggest also checking out my Buyer to Seller volume indicator which cumulates total buying vs selling volume over a designated lookback period. Both of these used in conjunction are very powerful tools for volume based traders! ( Available here )
NOTE:
The boxes drawn in the chart are my own for demonstration purposes. I unfortunately cannot get the indicator to overlay the boxes on the chart in a separate viewing pane. That is why I opted to use the barcolor function to change the candle color instead :-).
Thanks again everyone and safe trades!
ATRvsDTR + ADR Zone + SSS50%This Script is to be used for intra day as far as the adr zones. The adr zones are used as support and resistance but also can be used to determine whether the stock is breaking out or not. Also being that the adr zones are calculated using a 5 or 10 day period unless you change the settings, and are set when price opens. It does really help you know whether a stock is moving more than it does on average to me it just signifies its directional. So I added the atr vs dtr so you can see what a stock moves on average versus what it has moved today.
The atr period is calculated based on the daily period unless you change the settings. I added to the original script 3 more percentages the atr vs dtr will change as it goes higher so that you can be aware when the stock is getting closer to moving 100% of its atr. Even though a stock breaks above or below the adr that doesn't mean it has moved more than it normally moves.
I also have the weekly open on the script as I trade the strat and I want to know, at what price the the week will change from bearish to bullish and vice versa. So that I can understand the trend when I am trading intraday.
The 50% lines were added for Sara strat snipers 50% rule and you can change the timeframes on them. This is used to know whether a candle will go 3. This also can help with retracements vs reversals, because in traditional technical analysis 50% is around where people start think its a reversal more so than a retracement.
I believe the script will be very help as it can show you price being directional but can also let you know when the stock is getting close to moving more than it normally has or if it has moved more than it normally has. As well as being able to see if something is a retracement vs a reversal. I trade TheStrat strategy so this can be very helpful in that regard
The 50% retracement levels are default 1h and daily. You can change them and whether or not they show
In the example chart you can see we are below weekly open which is bearish and you can also see where price reverses out of the upper adr zone. As well as how much of the atr we have moved on this day in time.
Bitcoin Block Height (Total Blocks)Bitcoin Block Height by RagingRocketBull 2020
Version 1.0
Differences between versions are listed below:
ver 1.0: compare QUANDL Difficulty vs Blockchain Difficulty sources, get total error estimate
ver 2.0: compare QUANDL Hash Rate vs Blockchain Hash Rate sources, get total error estimate
ver 3.0: Total Blocks estimate using different methods
--------------------------------
This indicator estimates Bitcoin Block Height (Total Blocks) using Difficulty and Hash Rate in the most accurate way possible, since
QUANDL doesn't provide a direct source for Bitcoin Block Height (neither QUANDL:BCHAIN, nor QUANDL:BITCOINWATCH/MINING).
Bitcoin Block Height can be used in other calculations, for instance, to estimate the next date of Bitcoin Halving.
Using this indicator I demonstrate:
- that QUANDL data is not accurate and differ from Blockchain source data (industry standard), but still can be used in calculations
- how to plot a series of data points from an external csv source and compare it with another source
- how to accurately estimate Bitcoin Block Height
Features:
- compare QUANDL Difficulty source (EOD, D1) with external Blockchain Difficulty csv source (EOD, D1, embedded)
- show/hide Quandl/Blockchain Difficulty curves
- show/hide Blockchain Difficulty candles
- show/hide differences (aqua vertical lines)
- show/hide time gaps (green vertical lines)
- count source differences within data range only or for the whole history
- multiply both sources by alpha to match before comparing
- floor/round both matched sources when comparing
- Blockchain Difficulty offset to align sequences, bars > 0
- count time gaps and missing bars (as result of time gaps)
WARNING:
- This indicator hits the max 1000 vars limit, adding more plots/vars/data points is not possible
- Both QUANDL/Blockchain provide daily EOD data and must be plotted on a daily D1 chart otherwise results will be incorrect
- current chart must not have any time gaps inside the range (time gaps outside the range don't affect the calculation). Time gaps check is provided.
Otherwise hardcoded Blockchain series will be shifted forward on gaps and the whole sequence become truncated at the end => data comparison/total blocks estimate will be incorrect
Examples of valid charts that can run this indicator: COINBASE:BTCUSD,D1 (has 8 time gaps, 34 missing bars outside the range), QUANDL:BCHAIN/DIFF,D1 (has no gaps)
Usage:
- Description of output plot values from left to right:
- c_shifted - 4x blockchain plotcandles ohlc, green/black (default na)
- diff - QUANDL Difficulty
- c_shifted - Blockchain Difficulty with offset
- QUANDL Difficulty multiplied by alpha and rounded
- Blockchain Difficulty multiplied by alpha and rounded
- is_different, bool - cur bar's source values are different (1) or not (0)
- count, number of differences
- bars, total number of bars/data points in the range
- QUANDL daily blocks
- Blockchain daily blocks
- QUANDL total blocks
- Blockchain total blocks
- total_error - difference between total_blocks estimated using both sources as of cur bar, blocks
- number_of_gaps - number of time gaps on a chart
- missing_bars - number of missing bars as result of time gaps on a chart
- Color coding:
- Blue - QUANDL data
- Red - Blockchain data
- Black - Is Different
- Aqua - number of differences
- Green - number of time gaps
- by default the indicator will show lots of vertical aqua lines, 138 differences, 928 bars, total error -370 blocks
- to compare the best match of the 2 sources shift Blockchain source 1 bar into the future by setting Blockchain Difficulty offset = 1, leave alpha = 0.01 =>
this results in no vertical aqua lines, 0 differences, total_error = 0 blocks
if you move the mouse inside the range some bars will show total_error = 1 blocks => total_error <= 1 blocks
- now uncheck Round Difficulty Values flag => some filled aqua areas, 218 differences.
- now set alpha = 1 (use raw source values) instead of 0.01 => lots of filled aqua areas, 871 differences.
although there are many differences this still doesn't affect the total_blocks estimate provided Difficulty offset = 1
Methodology:
To estimate Bitcoin Block Height we need 3 steps, each step has its own version:
- Step 1: Compare QUANDL Difficulty vs Blockchain Difficulty sources and estimate error based on differences
- Step 2: Compare QUANDL Hash Rate vs Blockchain Hash Rate sources and estimate error based on differences
- Step 3: Estimate Bitcoin Block Height (Total Blocks) using different methods in the most accurate way possible
QUANDL doesn't provide block time data, but we can calculate it using the Hash Rate approximation formula:
estimated Hash rate/sec H = 2^32 * D / T, where D - Difficulty, T - block time, sec
1. block time (T) can be derived from the formula, since we already know Difficulty (D) and Hash Rate (H) from QUANDL
2. using block time (T) we can estimate daily blocks as daily time / block time
3. block height (total blocks) = cumulative sum of daily blocks of all bars on the chart (that's why having no gaps is important)
Notes:
- This code uses Pinescript v3 compatibility framework
- hash rate is in THash/s, although QUANDL falsely states in description GHash/s! THash = 1000 GHash
- you can't read files, can only embed/hardcode raw data in script
- both QUANDL and Blockchain sources have no gaps
- QUANDL and Blockchain series are different in the following ways:
- all QUANDL data is already shifted 1 bar into the future, i.e. prev day's value is shown as cur day's value => Blockchain data must be shifted 1 bar forward to match
- all QUANDL diff data > 1 bn (10^12) are truncated and have last 1-2 digits as zeros, unlike Blockchain data => must multiply both values by 0.01 and floor/round the results
- QUANDL sometimes rounds, other times truncates those 1-2 last zero digits to get the 3rd last digit => must use both floor/round
- you can only shift sequences forward into the future (right), not back into the past (left) using positive offset => only Blockchain source can be shifted
- since total_blocks is already a cumulative sum of all prev values on each bar, total_error must be simple delta, can't be also int(cum()) or incremental
- all Blockchain values and total_error are na outside the range - move you mouse cursor on the last bar/inside the range to see them
TLDR, ver 1.0 Conclusion:
QUANDL/Blockchain Difficulty source differences don't affect total blocks estimate, total error <= 1 block with avg 150 blocks/day is negligible
Both QUANDL/Blockchain Difficulty sources are equally valid and can be used in calculations. QUANDL is a relatively good stand in for Blockchain industry standard data.
Links:
QUANDL difficulty source: www.quandl.com
QUANDL hash rate source: www.quandl.com
Blockchain difficulty source (export data as csv): www.blockchain.com
RedK_Supply/Demand Volume Viewer v1Background
============
VolumeViewer is a volume indicator, that offers a simple way to estimate the movement and balance (or lack of) of supply & demand volume based on the shape of the price bar. i put this together few years ago and i have a version of this published for another platform under different names (Directional Volume, BetterVolume) in case you come across them
what is V.Viewer
=====================
The idea here is to find a "simple proxy" for estimating the demand or supply portions of a volume bar - these 2 forces have the potential to affect the current price trend so we want an easy way to track them - or to understand if a stock is in accumulation or distribution - we want to do this without having access to Level II or bid/ask data, and without having to get into the complexity of exploring the lower timeframe price & volume data
- to achieve that, we depend on a simple assumption, that the volume associated with an up move is "demand" and the volume associated with a down move is "Supply". so we basically extrapolate these supply and demand values based on how the bar looks like - a full "green" price bar / candle will be considered 100% demand, and a full "red" price bar will be considered 100% supply - a bar that opens and closes at the same level will be 50/50 split between supply & demand.
- you may say this is a "too simple" of an assumption to make, but believe me, it works :) at least at the basic scenario we need here: i'm just exploring the volume movement and finding key levels - and it provides a good improvement compared to the classic way we see volume on a chart - which is still available here in VolumeViewer.
in all cases, i consider this to be work in progress, so i'd welcome any ideas to improve (without getting too complicated) - there's already a host of great volume-based indicators that will do the multi timeframe drill down, but that's not my scope here.
Technical Jargon & calculation
===========================
1. first we calculate a score % for the volume portion that is considered demand based on the bar shape
skip this part if it sounds too technical => if you're into coding indicators, you would probably know there are couple of different concepts for that algorithm - for example, the one used in Balance Of Power formula - which i'm a big fan of - but the one i use here is different. (how?) this is my own, ant it simply applies double weight for the "wick" parts of a price bar compared to the "body of the bar" -- i did some side-by-side comparison in past and decided this one works better. you can change it in the code if you like
2. after calculating the Bull vs Bears portion of volume, we take a moving average of both for the length you set, to come up with what we consider to be the Demand vs Supply - as usual, i use a weighted moving average (WMA) here.
3. the balance or net volume between these 2 lines is calculated, then we apply a final smoothing and that's the main plot we will get
4. being a very visual person, i did my best to build up the visuals in the correct order - then also to ensure the "study title" bar is properly organized and is simple and useful (Full Volume, Supply, Demand, Net Volume).
- i wish there was a way in Pine to hide a value that i still need to visually plot but don't want it showing its value on the study title bar, but couldn't find it. so the last plot value is repeated twice.
How to use
===========
- V.Viewer is set up to show the simplified view by default for simplicity. so when you first add it to a chart, you will get only the supply vs demand view you can see in the middle pane in the above chart
- Optional / detailed mode: go into the settings, and expose all other plots, you will be able to add the classic volume histogram, and the Supply / Demand lines - note these 2 lines will be overlay-ed on top of each other - this provides an easy way to see who is in control - especially if you change the display of these 2 lines into "area" style. This is what is showing in the lower pane in the above chart.
** Exploring Key Price Levels
- the premise is, at spots where there's big lack of balance, that's where to expect to find key price levels (support / resistance) and these price levels will come into play in future so can be used to set entry / exit targets for our trades - see the example in the AAPL chart where you can easily locate these "balance or reversal levels" using the tops/bottoms/zero-crossings from the Net Volume line
** Use for longer-term Price Analysis
- we can also use this simple indicator to gain more insights (at a high level) of the price in terms of accumulation vs distribution and if the sellers or buyers are in control - for example, in the above AAPL chart, V.Viewer tells us that buyers have been in control since October 19 - even during the recent drop, demand continued to be in play - compare that to DIS chart below for the same period, where it shows that the market was dumping DIS thru the weakness. DIS was bleeding red most of the time
Final thoughts
=============
- V.Viewer is an attempt to enhance the way we see and use Volume by leveraging the shape of the price bar to estimate volume supply & demand - and the Net between the 2
- it will work for stocks and other instruments as long as there's volume data
- note that V.Viewer does not track trend. each bar is taken in isolation of prior bars - the price may be going down and V.Viewer is showing supply going up (absorption scenario?) - so i suggest you do not use it to make decisions without consulting other trend / momentum indicators - of course this is a possible improvement idea, or can be implemented in another indicator, add in trend somehow, or maybe think of making this a +100 / -100 Oscillator .. feel free to play with these thoughts
- all thoughts welcome - if this is useful to you in your trading, please share with other trades here to learn from each other
- the code is commented - please feel free to use it as you like, or build things on top of it - but please continue to credit the author of this code :)
good luck!
-
Chiki-Poki BFXLS Longs Shorts Abs Normalized Volume Pro by RRBChiki-Poki BFXLS Longs vs Shorts Absolute Normalized Volume Value Pro by RagingRocketBull 2018
Version 1.0
This indicator displays Longs vs Shorts in a side by side graph, shows volume's absolute price value and normalized volume of Longs/Shorts for the current asset. This allows for more accurate L/S comparisons (like a log scale for volume) since volume on spot exchanges (Bitstamp, Bitfinex, Coinbase etc) is measured in coins traded, not USD traded. Similarly, L/S is usually the amount of coins in open L/S positions, not their total USD value. On Bitmex and other futures exchanges volume is measured in USD traded, so you don't need to apply the Volume Absolute Price Value checkbox to compare L/S. You should always check first whether your source is measured in coins or USD.
Chiki-Poki BFXLS primarily uses *SHORTS/LONGS feeds from Bitfinex for the current crypto asset, but you can specify custom L/S source tickers instead.
This 2-in-1 works both in the Main Chart and in the indicator pane below. You can switch between Main/Sub Window panes using RMB on the indicator's name and selecting Move To/Pane Above/Below.
This indicator doesn't use volume of the current asset. It uses L/S ticker's OHLC as a source for SHORTS/LONGS volumes instead. Essentially L/S => L/S Volume == L/S
Features:
- Display Longs vs Shorts side by side graph for the current crypto asset, i.e. for BTCUSD - BTCUSDLONGS/BTCUSDSHORTS, for ETHUSD - ETHUSDLONGS/ETHUSDSHORTS etc.
- Use custom OHLC ticker sources for Longs/Shorts from different exchanges/crypto assets with/without exchange prefix.
- Plot Longs/Shorts as lines or candles
- Show/Hide L/S, Diff, MAs, ATH/ATL
- Use Longs/Shorts Volume Absolute Price Value (Price * L/S Volume) instead of Coins Traded in open L/S positions to compare total L/S value/capitalization
- Normalize L/S Volume using Price / Price MA / L/S Volume MA
- Supports any existing type of MA: SMA, EMA, WMA, HMA etc
- Volume Absolute Price Value / Normalize also works on candles
- Oscillator mode with negative axis (works in both Main Chart/Subwindow panes).
- Highlight L/S Volume spikes above L/S MAs in both lines/oscillator.
- Change L/S MA color based on a number of last rising/falling L/S bars, colorize candles
- Display L/S volume as 1000s, mlns, or blns using alpha multiplier
1. based on BFXLS Longs vs Shorts and Compare Style, uses plot*, security and custom hma functions
2. swma has a fixed length = 4, alma and linreg have additional offset and smoothing params
Notes:
- Make sure that Left Price Scale shows up with Auto Fit Data enabled. You can reattach indicator to a different scale in Style.
- It is not recommended to switch modes multiple times due to TradingView's scale reattachment bugs. You should switch between Main Chart and Sub Window only once.
- When the USD price of an asset is lower you can trade more coins but capitalization value won't be as significant as when there are less coins for a higher price. Same goes for Shorts/Longs.
Current ATH in shorts doesn't trigger a squeeze because its total value is now far less than before and we are in a bear market where it's normal to have a higher number of shorts.
- You should always subtract Hedged L/S from L/S because hedged positions are temporary - used to preserve the value of the main position in the opposite direction and should be disregarded as such.
- Low margin rates increase the probability of a move in an underlying direction because it is cheaper. High margin rates => the market is anticipating a move in this direction, thus a more expensive rate. Sudden 5-10x rate raises imply a possible reversal soon. high - 0.1%, avg - 0.01-0.02%, low - 0.001-0.005%
You can also check out:
- BFXLS Longs/Shorts on BFXData
- Bitfinex L/S margin rates and Hedged L/S on datamish
- Bitmex L/S on Coinfarm.online
4 diffs (CB & IBIT Premium)📊 Script Name: 4 diffs (CB & IBIT Premium)
Version: Pine Script® v6
Overlay: Yes (table displayed on chart)
🧠 What it Does:
This script tracks four important Bitcoin price differentials to monitor spot/perpetual/futures price inefficiencies and ETF premium/discounts, and displays them in a live table on the chart. It helps traders identify arbitrage opportunities or institutional pricing signals.
📈 Displayed Metrics:
Coinbase Premium
→ Difference between Coinbase spot and Binance spot prices.
→ Use case: US vs. offshore spot market divergence.
Coinbase Spot vs Binance Perpetual
→ Difference between Coinbase spot and Binance perpetual price.
→ Use case: Spot-perp basis, often used for funding rate insights or market stress.
Bybit vs Binance Perpetual
→ Difference between Bybit perp and Binance perp price.
→ Use case: Compare derivative pricing across major offshore exchanges.
IBIT Premium (CME vs ETF-implied)
→ Compares CME futures price vs. IBIT’s implied spot BTC value
→ IBIT implied BTC = IBIT ETF price ÷ (BTC held / shares outstanding)
→ Use case: Gauge institutional premium/discount and ETF arbitrage clues.
🛠️ Customization:
Text color of the table is adjustable via the input setting.
📌 Visual Output:
A fixed 2×4 table appears in the top-right corner of the chart.
Each row shows a label and the live price difference in USD.
Volume Data Table (Real-time & Historical Volume Analysis)Volume Data Table (Real-time & Historical Volume Analysis)
Overview:
The Volume Data Table indicator is a powerful tool designed to provide concise, real-time, and historical volume insights directly on your chart. It aggregates critical volume metrics into an organized, customizable table, making it incredibly easy to identify unusual volume activity, sudden surges, or sustained interest in a particular asset.
This indicator is perfect for traders who rely on volume analysis to confirm price movements, spot potential reversals, or gauge market conviction.
Key Features & How It Works:
Real-time Volume Metrics:
The table prominently displays the volume data for the current (last) candle, including:
Time: The precise time of the current candle's close, formatted in IST (Indian Standard Time - UTC+5:30) for your convenience.
Volume: The total volume for the current candle, smartly formatted in K (Thousands) or M (Millions) for readability.
Change % (Chg%): The percentage change in volume compared to the immediately preceding candle. This helps you quickly spot sudden increases or decreases in trading activity.
Vs 4-Avg % (vs4Avg%): The percentage change in volume compared to the average volume of the last 4 preceding candles. This is crucial for identifying volume surges or drops relative to recent historical activity, which can signal significant market events.
Configurable Historical Data:
Beyond the current candle, you can customize how many previous candles' volume data you wish to display. A simple input setting allows you to choose from 1 to 20 historical rows, giving you flexibility to review recent volume trends. Each historical row also provides its own "Change %" and "Vs 4-Avg %" for detailed analysis of past candle activity.
Intuitive Color-Coding:
Percentage change values are intuitively color-coded for instant visual cues:
Green: Indicates a positive (increase) in volume percentage.
Red: Indicates a negative (decrease) in volume percentage.
Clean & Organized Table Display:
The indicator presents all this data in a neat, easy-to-read table positioned at the top-right of your chart. The table automatically adjusts its height based on the number of historical rows you choose, ensuring a compact and efficient use of screen space.
Ideal Use Cases:
Volume Confirmation: Quickly confirm the conviction behind price movements. A strong price move on high "Vs 4-Avg %" volume often indicates higher reliability.
Spotting Abnormal Volume: Identify candles with unusually high or low volume compared to their recent average, which can precede or accompany significant price action.
Momentum Analysis: Understand if buying/selling pressure is increasing or decreasing over recent periods.
Scalping & Day Trading: The real-time updates and concise format make it highly effective for fast-paced short-term decision-making.
Complements Other Indicators: Use it alongside price action, candlestick patterns, or other technical indicators for a more robust analysis.
Customization Options:
Number of Historical Rows: Adjust Number of Historical Rows from 1 to 20 to tailor the depth of your historical volume review.
Important Disclaimer:
This indicator is a technical analysis tool and should be used as part of a comprehensive trading strategy. It is not financial advice. Trading in financial markets involves substantial risk, and you could lose money. Always perform your own research and risk management.
DCA Investment Tracker Pro [tradeviZion]DCA Investment Tracker Pro: Educational DCA Analysis Tool
An educational indicator that helps analyze Dollar-Cost Averaging strategies by comparing actual performance with historical data calculations.
---
💡 Why I Created This Indicator
As someone who practices Dollar-Cost Averaging, I was frustrated with constantly switching between spreadsheets, calculators, and charts just to understand how my investments were really performing. I wanted to see everything in one place - my actual performance, what I should expect based on historical data, and most importantly, visualize where my strategy could take me over the long term .
What really motivated me was watching friends and family underestimate the incredible power of consistent investing. When Napoleon Bonaparte first learned about compound interest, he reportedly exclaimed "I wonder it has not swallowed the world" - and he was right! Yet most people can't visualize how their $500 monthly contributions today could become substantial wealth decades later.
Traditional DCA tracking tools exist, but they share similar limitations:
Require manual data entry and complex spreadsheets
Use fixed assumptions that don't reflect real market behavior
Can't show future projections overlaid on actual price charts
Lose the visual context of what's happening in the market
Make compound growth feel abstract rather than tangible
I wanted to create something different - a tool that automatically analyzes real market history, detects volatility periods, and shows you both current performance AND educational projections based on historical patterns right on your TradingView charts. As Warren Buffett said: "Someone's sitting in the shade today because someone planted a tree a long time ago." This tool helps you visualize your financial tree growing over time.
This isn't just another calculator - it's a visualization tool that makes the magic of compound growth impossible to ignore.
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🎯 What This Indicator Does
This educational indicator provides DCA analysis tools. Users can input investment scenarios to study:
Theoretical Performance: Educational calculations based on historical return data
Comparative Analysis: Study differences between actual and theoretical scenarios
Historical Projections: Theoretical projections for educational analysis (not predictions)
Performance Metrics: CAGR, ROI, and other analytical metrics for study
Historical Analysis: Calculates historical return data for reference purposes
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🚀 Key Features
Volatility-Adjusted Historical Return Calculation
Analyzes 3-20 years of actual price data for any symbol
Automatically detects high-volatility stocks (meme stocks, growth stocks)
Uses median returns for volatile stocks, standard CAGR for stable stocks
Provides conservative estimates when extreme outlier years are detected
Smart fallback to manual percentages when data insufficient
Customizable Performance Dashboard
Educational DCA performance analysis with compound growth calculations
Customizable table sizing (Tiny to Huge text options)
9 positioning options (Top/Middle/Bottom + Left/Center/Right)
Theme-adaptive colors (automatically adjusts to dark/light mode)
Multiple display layout options
Future Projection System
Visual future growth projections
Timeframe-aware calculations (Daily/Weekly/Monthly charts)
1-30 year projection options
Shows projected portfolio value and total investment amounts
Investment Insights
Performance vs benchmark comparison
ROI from initial investment tracking
Monthly average return analysis
Investment milestone alerts (25%, 50%, 100% gains)
Contribution tracking and next milestone indicators
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📊 Step-by-Step Setup Guide
1. Investment Settings 💰
Initial Investment: Enter your starting lump sum (e.g., $60,000)
Monthly Contribution: Set your regular DCA amount (e.g., $500/month)
Return Calculation: Choose "Auto (Stock History)" for real data or "Manual" for fixed %
Historical Period: Select 3-20 years for auto calculations (default: 10 years)
Start Year: When you began investing (e.g., 2020)
Current Portfolio Value: Your actual portfolio worth today (e.g., $150,000)
2. Display Settings 📊
Table Sizes: Choose from Tiny, Small, Normal, Large, or Huge
Table Positions: 9 options - Top/Middle/Bottom + Left/Center/Right
Visibility Toggles: Show/hide Main Table and Stats Table independently
3. Future Projection 🔮
Enable Projections: Toggle on to see future growth visualization
Projection Years: Set 1-30 years ahead for analysis
Live Example - NASDAQ:META Analysis:
Settings shown: $60K initial + $500/month + Auto calculation + 10-year history + 2020 start + $150K current value
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🔬 Pine Script Code Examples
Core DCA Calculations:
// Calculate total invested over time
months_elapsed = (year - start_year) * 12 + month - 1
total_invested = initial_investment + (monthly_contribution * months_elapsed)
// Compound growth formula for initial investment
theoretical_initial_growth = initial_investment * math.pow(1 + annual_return, years_elapsed)
// Future Value of Annuity for monthly contributions
monthly_rate = annual_return / 12
fv_contributions = monthly_contribution * ((math.pow(1 + monthly_rate, months_elapsed) - 1) / monthly_rate)
// Total expected value
theoretical_total = theoretical_initial_growth + fv_contributions
Volatility Detection Logic:
// Detect extreme years for volatility adjustment
extreme_years = 0
for i = 1 to historical_years
yearly_return = ((price_current / price_i_years_ago) - 1) * 100
if yearly_return > 100 or yearly_return < -50
extreme_years += 1
// Use median approach for high volatility stocks
high_volatility = (extreme_years / historical_years) > 0.2
calculated_return = high_volatility ? median_of_returns : standard_cagr
Performance Metrics:
// Calculate key performance indicators
absolute_gain = actual_value - total_invested
total_return_pct = (absolute_gain / total_invested) * 100
roi_initial = ((actual_value - initial_investment) / initial_investment) * 100
cagr = (math.pow(actual_value / initial_investment, 1 / years_elapsed) - 1) * 100
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📊 Real-World Examples
See the indicator in action across different investment types:
Stable Index Investments:
AMEX:SPY (SPDR S&P 500) - Shows steady compound growth with standard CAGR calculations
Classic DCA success story: $60K initial + $500/month starting 2020. The indicator shows SPY's historical 10%+ returns, demonstrating how consistent broad market investing builds wealth over time. Notice the smooth theoretical growth line vs actual performance tracking.
MIL:VUAA (Vanguard S&P 500 UCITS) - Shows both data limitation and solution approaches
Data limitation example: VUAA shows "Manual (Auto Failed)" and "No Data" when default 10-year historical setting exceeds available data. The indicator gracefully falls back to manual percentage input while maintaining all DCA calculations and projections.
MIL:VUAA (Vanguard S&P 500 UCITS) - European ETF with successful 5-year auto calculation
Solution demonstration: By adjusting historical period to 5 years (matching available data), VUAA auto calculation works perfectly. Shows how users can optimize settings for newer assets. European market exposure with EUR denomination, demonstrating DCA effectiveness across different markets and currencies.
NYSE:BRK.B (Berkshire Hathaway) - Quality value investment with Warren Buffett's proven track record
Value investing approach: Berkshire Hathaway's legendary performance through DCA lens. The indicator demonstrates how quality companies compound wealth over decades. Lower volatility than tech stocks = standard CAGR calculations used.
High-Volatility Growth Stocks:
NASDAQ:NVDA (NVIDIA Corporation) - Demonstrates volatility-adjusted calculations for extreme price swings
High-volatility example: NVIDIA's explosive AI boom creates extreme years that trigger volatility detection. The indicator automatically switches to "Median (High Vol): 50%" calculations for conservative projections, protecting against unrealistic future estimates based on outlier performance periods.
NASDAQ:TSLA (Tesla) - Shows how 10-year analysis can stabilize volatile tech stocks
Stable long-term growth: Despite Tesla's reputation for volatility, the 10-year historical analysis (34.8% CAGR) shows consistent enough performance that volatility detection doesn't trigger. Demonstrates how longer timeframes can smooth out extreme periods for more reliable projections.
NASDAQ:META (Meta Platforms) - Shows stable tech stock analysis using standard CAGR calculations
Tech stock with stable growth: Despite being a tech stock and experiencing the 2022 crash, META's 10-year history shows consistent enough performance (23.98% CAGR) that volatility detection doesn't trigger. The indicator uses standard CAGR calculations, demonstrating how not all tech stocks require conservative median adjustments.
Notice how the indicator automatically detects high-volatility periods and switches to median-based calculations for more conservative projections, while stable investments use standard CAGR methods.
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📈 Performance Metrics Explained
Current Portfolio Value: Your actual investment worth today
Expected Value: What you should have based on historical returns (Auto) or your target return (Manual)
Total Invested: Your actual money invested (initial + all monthly contributions)
Total Gains/Loss: Absolute dollar difference between current value and total invested
Total Return %: Percentage gain/loss on your total invested amount
ROI from Initial Investment: How your starting lump sum has performed
CAGR: Compound Annual Growth Rate of your initial investment (Note: This shows initial investment performance, not full DCA strategy)
vs Benchmark: How you're performing compared to the expected returns
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⚠️ Important Notes & Limitations
Data Requirements: Auto mode requires sufficient historical data (minimum 3 years recommended)
CAGR Limitation: CAGR calculation is based on initial investment growth only, not the complete DCA strategy
Projection Accuracy: Future projections are theoretical and based on historical returns - actual results may vary
Timeframe Support: Works ONLY on Daily (1D), Weekly (1W), and Monthly (1M) charts - no other timeframes supported
Update Frequency: Update "Current Portfolio Value" regularly for accurate tracking
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📚 Educational Use & Disclaimer
This analysis tool can be applied to various stock and ETF charts for educational study of DCA mathematical concepts and historical performance patterns.
Study Examples: Can be used with symbols like AMEX:SPY , NASDAQ:QQQ , AMEX:VTI , NASDAQ:AAPL , NASDAQ:MSFT , NASDAQ:GOOGL , NASDAQ:AMZN , NASDAQ:TSLA , NASDAQ:NVDA for learning purposes.
EDUCATIONAL DISCLAIMER: This indicator is a study tool for analyzing Dollar-Cost Averaging strategies. It does not provide investment advice, trading signals, or guarantees. All calculations are theoretical examples for educational purposes only. Past performance does not predict future results. Users should conduct their own research and consult qualified financial professionals before making any investment decisions.
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© 2025 TradeVizion. All rights reserved.
[blackcat] L2 Trend Guard OscillatorOVERVIEW
📊 The L2 Trend Guard Oscillator is a comprehensive technical analysis framework designed specifically to identify market trend reversals using adaptive filtering algorithms that combine price action dynamics with statistical measures of volatility and momentum.
Key Purpose:
Generate reliable early warning signals before major trend changes occur
Provide clear directional bias indicators aligned with institutional investor behavior patterns
Offer risk-managed entry/exit opportunities suitable for various timeframes
TECHNICAL FOUNDATION EXPLAINED
🎓 Core Mechanism Breakdown:
→ Advanced smoothing technique emphasizing recent data points more heavily than older ones
↓ Reduces lag while maintaining signal integrity compared to traditional MA approaches
• Short-term Momentum Assessment:
🔶 Relative strength between closing prices vs lower bounds
• Long-term Directional Bias Analysis:
📈 Extended timeframe comparison generating structural context
• Defense Level Generation:
➜ Protective boundary calculation incorporating EMAs for stability enhancement
PARAMETER CONFIGURATION GUIDE
🔧 Adjustable Settings Explained In Detail:
Timeframe Selection:**
↔ Controls lookback period sensitivity affecting responsiveness
↕ Adjusts reaction speed vs accuracy trade-off dynamically
Weight Factor Specification:**
⚡ Influences emphasis on newer versus historical observations
🎯 Defines key decision-making thresholds clearly
ALGORITHM EXECUTION FLOW
💻 Processing Sequence Overview:
:
→ Gather raw pricing inputs across required periods
↓ Normalize values preparing them for subsequent processing stages
:
✔ Calculate relative strength positions against established ranges
❌ Filter outliers maintaining signal integrity consistently
⟶ Apply dual-pass filtering reducing false signals effectively
➡ Generate actionable trading opportunities systematically
VISUALIZATION ARCHITECTURE
🎨 Display Elements Designated Purpose:
🔵 Primary Indicator Traces:
→ Aqua Trace: Buy/Sell Signal Progression
↑ Red Line: Opposing Force Boundary
🟥 Gray Dashed: Zero Reference Point
🏷️ Label System For Critical Events:
✅ BUY: Bullish Opportunity Markers
❌ SELL: Bearish Setup Validations
STRATEGIC IMPLEMENTATION FRAMEWORK
📋 Practical Deployment Steps:
Initial Integration Protocol:
• Select appropriate timeframe matching strategy objectives
• Configure input parameters aligning with target asset behavior traits
• Conduct thorough backtesting under simulated environments initially
Active Monitoring Procedures:
→ Regular observation of labeled event placements versus actual movements
↓ Track confirmation patterns leading up to signaled opportunities carefully
↑ Evaluate overall framework reliability across different regime types regularly
Execution Guidelines Formulation:
✔ Enter positions only after achieving minimum number of confirming inputs
❌ Avoid isolated occurrences lacking adequate supporting evidence always
➞ Look for convergent factors strengthening conviction before acting decisively
PERFORMANCE OPTIMIZATION TECHNIQUES
🚀 Continuous Improvement Strategies:
Parameter Calibration Approach:
✓ Start testing default suggested configurations thoroughly
↕ Gradually adjust individual components observing outcome changes methodically
✨ Document findings building personalized version profile incrementally
Context Adaptability Methods:
🔄 Add supplementary indicators enhancing overall reliability when needed
🔧 Remove unnecessary complexity layers avoiding confusion/distracted decisions
💫 Incorporate custom rules adapting specific security behaviors effectively
Efficiency Improvement Tactics:
⚙️ Streamline redundant computational routines wherever possible efficiently
♻️ Leverage shared data streams minimizing resource utilization significantly
⏳ Optimize refresh frequencies balancing update speed vs overhead properly
Multi Scanner Plot & Table V1Here's how to interpret each column in the table:
Price vs MAs:
What it shows: Where the current price is relative to the short-term (e.g., 20-period) and long-term (e.g., 50-period) Simple Moving Averages (SMAs) calculated on your current chart's timeframe.
Interpretation:
Above Both (Green background): Price is above both the short and long MAs. Generally considered a bullish sign for the current trend.
Below Both (Red background): Price is below both MAs. Generally considered a bearish sign.
Mixed (Gray background): Price is between the two MAs (e.g., above the short but below the long, or vice-versa). Indicates indecision or a potential trend change.
RSI Value:
What it shows: The actual numerical value of the Relative Strength Index (RSI) calculated on your current chart's timeframe.
Interpretation: Just the raw RSI number (e.g., 65.32). The background is always gray. You compare this value to standard overbought/oversold levels (like 70/30) or the levels defined in the script's inputs.
RSI Status:
What it shows: Interprets the RSI Value based on the Overbought/Oversold levels set in the script's inputs (default 70/30). Calculated on your current chart's timeframe.
Interpretation:
Overbought (Red background): RSI is above the overbought level (e.g., > 70). Suggests the asset might be due for a pullback or reversal downwards. Red indicates a potentially bearish condition.
Oversold (Green background): RSI is below the oversold level (e.g., < 30). Suggests the asset might be due for a bounce or reversal upwards. Green indicates a potentially bullish condition.
Neutral (Gray background): RSI is between the oversold and overbought levels.
Last Sig Price:
What it shows: The price level where the last "SIG NOW" Buy or Sell signal occurred on your current chart's timeframe.
Interpretation: Helps you see the entry price of the most recent short-term signal generated by this script. The background color matches the signal type: Green for the last Buy signal, Red for the last Sell signal. N/A if no signal has occurred yet.
SIG NOW:
What it shows: This is the main short-term signal generated by the script based on conditions on your current chart's timeframe. It combines the "Price vs MAs" status and specific RSI conditions (price must be above/below both MAs and RSI must be within a certain range defined in the inputs).
Interpretation:
BUY (Green background): The specific buy conditions are met right now. (Price above both MAs AND RSI is strong but not necessarily overbought).
SELL (Red background): The specific sell conditions are met right now. (Price below both MAs AND RSI is weak but not necessarily oversold).
NEUTRAL (Gray background): Neither the Buy nor the Sell conditions are currently met.
ALERT:
What it shows: Flags unusual volume activity on the current bar compared to the recent average volume (calculated on your current chart's timeframe).
Interpretation:
SPIKE (Yellow background, black text): Current volume is significantly higher than the recent average (defined by the Volume Spike Multiplier). Can indicate strong interest or a potential climax.
DUMP (Purple background): Current volume is significantly lower than the recent average (defined by the Volume Dump Multiplier). Can indicate fading interest.
NONE (Gray background): Volume is within the normal range for the lookback period.
SD$:
What it shows: The price level where the last Volume Spike or Dump occurred on your current chart's timeframe.
Interpretation: Shows the price associated with the most recent significant volume event. The background color indicates the type of the last event: Green if the last event was a Spike, Red if the last event was a Dump. N/A if no Spike/Dump has occurred yet.
BB Value (%B):
What it shows: This relates to Bollinger Bands, but specifically calculated on a Higher Timeframe (HTF) that you can set in the inputs (e.g., Daily BBs while viewing an Hourly chart). It shows the Bollinger Band Percent B (%B) value for that HTF. %B measures where the HTF closing price is relative to the HTF upper and lower bands.
Interpretation:
Value > 1: HTF price closed above the HTF upper Bollinger Band.
Value < 0: HTF price closed below the HTF lower Bollinger Band.
Value between 0 and 1: HTF price closed within the HTF Bollinger Bands (e.g., 0.5 is exactly on the middle band).
The background is always gray.
LTS (Long Term Signal):
What it shows: A signal derived only from the Higher Timeframe (HTF) Bollinger Bands.
Interpretation:
BUY (Green background): The HTF price closed above the HTF upper Bollinger Band (see BB Value > 1). Considered a strong bullish signal from the higher timeframe perspective.
SELL (Red background): The HTF price closed below the HTF lower Bollinger Band (see BB Value < 0). Considered a strong bearish signal from the higher timeframe perspective.
NEUTRAL (Gray background): The HTF price closed within the HTF Bollinger Bands.
How to Understand Bollinger Bands and Signals in this Context:
Bollinger Bands are primarily used for the Long Term Signal (LTS) column. This script calculates BBs on a higher timeframe (you choose which one, or it defaults to the chart's timeframe if left blank).
The "LTS" signal triggers:
A BUY when the price on that higher timeframe closes above its upper Bollinger Band. This often indicates strong momentum or a potential breakout.
A SELL when the price on that higher timeframe closes below its lower Bollinger Band. This often indicates strong negative momentum or a potential breakdown.
The "BB Value" column gives you the raw %B number from that same higher timeframe, showing you exactly where the price is relative to the bands (is it just barely above/below, or way outside?).
The script does not directly use Bollinger Bands from the current chart timeframe for the "SIG NOW" or other table signals. The main short-term signals ("SIG NOW") rely on Moving Averages and RSI on the current timeframe. The LTS provides a longer-term perspective using HTF Bollinger Bands.
In summary: Look at the table to quickly gauge:
Short-term trend (Price vs MAs).
Short-term momentum (RSI Status, SIG NOW).
Recent short-term entry points (Last Sig Price).
Current volume anomalies (ALERT).
Long-term strength/weakness based on HTF Bollinger Bands (LTS, BB Value).
Combine these pieces of information to get a more rounded view of the current market conditions according to this specific script's logic.
Easy MA SignalsEasy MA Signals
Overview
Easy MA Signals is a versatile Pine Script indicator designed to help traders visualize moving average (MA) trends, generate buy/sell signals based on crossovers or custom price levels, and enhance chart analysis with volume-based candlestick coloring. Built with flexibility in mind, it supports multiple MA types, crossover options, and customizable signal appearances, making it suitable for traders of all levels. Whether you're a day trader, swing trader, or long-term investor, this indicator provides actionable insights while keeping your charts clean and intuitive.
Configure the Settings
The indicator is divided into three input groups for ease of use:
General Settings:
Candlestick Color Scheme: Choose from 10 volume-based color schemes (e.g., Sapphire Pulse, Emerald Spark) to highlight high/low volume candles. Select “None” for TradingView’s default colors.
Moving Average Length: Set the MA period (default: 20). Adjust for faster (lower values) or slower (higher values) signals.
Moving Average Type: Choose between SMA, EMA, or WMA (default: EMA).
Show Buy/Sell Signals: Enable/disable signal plotting (default: enabled).
Moving Average Crossover: Select a crossover type (e.g., MA vs VWAP, MA vs SMA50) for signals or “None” to disable.
Volume Influence: Adjust how volume impacts candlestick colors (default: 1.2). Higher values make thresholds stricter.
Signal Appearance Settings:
Buy/Sell Signal Shape: Choose shapes like triangles, arrows, or labels for signals.
Buy/Sell Signal Position: Place signals above or below bars.
Buy/Sell Signal Color: Customize colors for better visibility (default: green for buy, red for sell).
Custom Price Alerts:
Custom Buy/Sell Alert Price: Set specific price levels for alerts (default: 0, disabled). Enter a non-zero value to enable.
Set Up Alerts
To receive notifications (e.g., sound, popup, email) when signals or custom price levels are hit:
Click the Alert button (alarm clock icon) in TradingView.
Select Easy MA Signals as the condition and choose one of the four alert types:
MA Crossover Buy Alert: Triggers on MA crossover buy signals.
MA Crossover Sell Alert: Triggers on MA crossover sell signals.
Custom Buy Alert: Triggers when price crosses above the custom buy price.
Custom Sell Alert: Triggers when price crosses below the custom sell price.
Enable Play Sound and select a sound (e.g., “Bell”).
Set the frequency (e.g., Once Per Bar Close for confirmed signals) and create the alert.
Analyze the Chart
Moving Average Line: Displays the selected MA with color changes (green for bullish, red for bearish, gray for neutral) based on price position relative to the MA.
Buy/Sell Signals: Appear as shapes or labels when crossovers or custom price levels are hit.
Candlestick Colors: If a color scheme is selected, candles change color based on volume strength (high, low, or neutral), aiding in trend confirmation.
Why Use Easy MA Signals?
Easy MA Signals is designed to simplify technical analysis while offering advanced customization. It’s ideal for traders who want:
A clear visualization of MA trends and crossovers.
Flexible signal generation based on MA crossovers or custom price levels.
Volume-enhanced candlestick coloring to identify market strength.
Easy-to-use settings with tooltips for beginners and pros alike.
This script is particularly valuable because it combines multiple features into one indicator, reducing chart clutter and providing actionable insights without overwhelming the user.
Benefits of Easy MA Signals
Highly Customizable: Supports SMA, EMA, and WMA with adjustable lengths.
Offers multiple crossover options (VWAP, SMA10, SMA20, etc.) for tailored strategies.
Custom price alerts allow precise targeting of key levels.
Volume-Based Candlestick Coloring: 10 unique color schemes highlight volume strength, helping traders confirm trends.
Adjustable volume influence ensures adaptability to different markets.
Flexible Signal Visualization: Choose from various signal shapes (triangles, arrows, labels) and positions (above/below bars).
Customizable colors improve visibility on any chart background.
Alert Integration: Built-in alert conditions for crossovers and custom prices support sound, email, and app notifications.
Easy setup for real-time trading decisions.
User-Friendly Design: Organized input groups with clear tooltips make configuration intuitive.
Suitable for beginners and advanced traders alike.
Example Use Cases
Swing Trading with MA Crossovers:
Scenario: A trader wants to trade Bitcoin (BTC/USD) on a 4-hour chart using an EMA crossover strategy.
Setup:
Set Moving Average Type to EMA, Length to 20.
Set Moving Average Crossover to “MA vs SMA50”.
Enable Show Buy/Sell Signals and choose “arrowup” for buy, “arrowdown” for sell.
Select “Emerald Spark” for candlestick colors to highlight volume surges.
Usage: Buy when the EMA20 crosses above the SMA50 (green arrow appears) and volume is high (dark green candles). Sell when the EMA20 crosses below the SMA50 (red arrow). Set alerts for real-time notifications.
Scalping with Custom Price Alerts:
Scenario: A day trader monitors Tesla (TSLA) on a 5-minute chart and wants alerts at specific support/resistance levels.
Setup:
Set Custom Buy Alert Price to 150.00 (support) and Custom Sell Alert Price to 160.00 (resistance).
Use “labelup” for buy signals and “labeldown” for sell signals.
Keep Moving Average Crossover as “None” to focus on price alerts.
Usage: Receive a sound alert and label when TSLA crosses 150.00 (buy) or 160.00 (sell). Use volume-colored candles to confirm momentum before entering trades.
When NOT to Use Easy MA Signals
High-Frequency Trading: Reason: The indicator relies on moving averages and volume, which may lag in ultra-fast markets (e.g., sub-second trades). High-frequency traders may need specialized tools with real-time tick data.
Alternative: Use order book or market depth indicators for faster execution.
Low-Volatility or Sideways Markets:
Reason: MA crossovers and custom price alerts can generate false signals in choppy, range-bound markets, leading to whipsaws.
Alternative: Use oscillators like RSI or Bollinger Bands to trade within ranges.
This indicator is tailored more towards less experienced traders. And as always, paper trade until you are comfortable with how this works if you're unfamiliar with trading! We hope you enjoy this and have great success. Thanks for your interested in Easy MA Signals!
Stochastic Overlay - Regression Channel (Zeiierman)█ Overview
The Stochastic Overlay – Regression Channel (Zeiierman) is a next-generation visualization tool that transforms the traditional Stochastic Oscillator into a dynamic price-based overlay.
Instead of leaving momentum trapped in a lower subwindow, this indicator projects the Stochastic oscialltor directly onto price itself — allowing traders to visually interpret momentum, overbought/oversold conditions, and market strength without ever taking their eyes off price action.
⚪ In simple terms:
▸ The Bands = The Stochastic Oscillator — but on price.
▸ The Midline = Stochastic 50 level
▸ Upper Band = Stochastic Overbought Threshold
▸ Lower Band = Stochastic Oversold Threshold
When the price moves above the midline → it’s the same as the oscillator moving above 50
When the price breaks above the upper band → it’s the same as Stochastic entering overbought.
When the price reaches the lower band →, think of it like Stochastic being oversold.
This makes market conditions visually intuitive. You’re literally watching the oscillator live on the price chart.
█ How It Works
The indicator layers 3 distinct technical elements into one clean view:
⚪ Stochastic Momentum Engine
Tracks overbought/oversold conditions and directional strength using:
%K Line → Momentum of price
%D Line → Smoothing filter of %K
Overbought/Oversold Bands → Highlight potential reversal zones
⚪ Volatility Adaptive Bands
Dynamic bands plotted above and below price using:
ATR * Stochastic Scaling → Creates wider bands during volatile periods & tighter bands in calm conditions
Basis → Moving average centerline (EMA, SMA, WMA, HMA, RMA selectable)
This means:
→ In strong trends: Bands expand
→ In consolidations: Bands contract
⚪ Regression Channel
Projects trend direction with different models:
Logarithmic → Captures non-linear growth (perfect for crypto or exponential stocks)
Linear → Classic regression fit
Adaptive → Dynamically adjusts sensitivity
Leading → Projects trend further ahead (aggressive mode)
Channels include:
Midline → Fair value trend
Upper/Lower Bounds → Deviation-based support/resistance
⚪ Heatmap - Bull & Bear Power Strength
Visual heatmeter showing:
% dominance of bulls vs bears (based on close > or < Band Basis)
Automatic normalization regardless of timeframe
Table display on-chart for quick visual insight
Dynamic highlighting when extreme levels are reached
⚪ Trend Candlestick Coloring
Bars auto-color based on trend filter:
Above Basis → Bullish Color
Below Basis → Bearish Color
█ How to Use
⚪ Trend Trading
→ Use Band direction + Regression Channel to identify trend alignment
→ Longs favored when price holds above the Basis
→ Shorts favored when price stays below the Basis
→ Use the Bull & Bear heatmap to asses if the bulls or the bears are in control.
⚪ Mean Reversion
→ Look for price to interact with Upper or Lower Band extremes
→ Stochastic reaching OB/OS zones further supports reversals
⚪ Momentum Confirmation
→ Crossovers between %K and %D can confirm continuation or divergence signals
→ Especially powerful when happening at band boundaries
⚪ Strength Heatmap
→ Quickly visualize current buyer vs seller control
→ Sharp spikes in Bull Power = Aggressive buying
→ Sharp spikes in Bear Power = Heavy selling pressure
█ Why It Useful
This is not a typical Stochastic or regression tool. The tool is designed for traders who want to:
React dynamically to price volatility
Map momentum into volatility context
Use adaptive regression channels across trend styles
Visualize bull vs bear power in real-time
Follow trends with built-in reversal logic
█ Settings
Stochastic Settings
Stochastic Length → Period of calculation. Higher = smoother, Lower = faster signals.
%K Smoothing → Smooths the Stochastic line itself.
%D Smoothing → Smooths the moving average of %K for slower signals.
Stochastic Band
Band Length → Length of the Moving Average Basis.
Volatility Multiplier → Controls band width via ATR scaling.
Band Type → Choose MA type (EMA, SMA, WMA, HMA, RMA).
Regression Channel
Regression Type → Logarithmic / Linear / Adaptive / Leading.
Regression Length → Number of bars for regression calculation.
Heatmap Settings
Heatmap Length → Number of bars to calculate bull/bear dominance.
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Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Multi-Timeframe EMAsMulti Timeframe EMA's
The 'Multi-Timeframe EMA Band Comparison' indicator is a tool designed to analyze trend direction across multiple timeframes using Exponential Moving Averages. it calculates the 50, 100, and 200 period EMAs for fiver user defined timeframes and compares their relationships to provide a visual snapshot of bullish or bearish momentum.
How it Works:
EMA Calculations: For each selected timeframe, the indicator computes the 50, 100, and 200 period EMAs based on the closing price.
Band Comparisons: Three key relationships are evaluated:
50 EMA vs 100 EMA
100 EMA vs 200 EMA
50 EMA vs 200 EMA
Scoring System: Each comparison is assigned a score:
🟢 (Green Circle): The shorter EMA is above the longer EMA, signaling bullish momentum.
🔴 (Red Circle): The shorter EMA is below the longer EMA, signaling bearish momentum.
⚪️ (White Circle): The EMAs are equal or data is unavailable (rare).
Average Score:
An overall average score is calculated across all 15 comparisons ranging from 1 to -1, displayed with two decimal places and color coded.
Customization:
This indicator is fully customizable from the timeframe setting to the color of the table. The only specific part that is not changeable is the EMA bands.
Econometrica by [SS]This is Econometrica, an indicator that aims to bridge a big gap between the resources available for analysis of fundamental data and its impact on tickers and price action.
I have noticed a general dearth of available indicators that offer insight into how fundamentals impact a ticker and provide guidance on how they these economic factors influence ticker behaviour.
Enter Econometrica. Econometrica is a math based indicator that aims to co-integrate and model indicator price action in relation to critical economic metrics.
Econometrica supports the following US based economic data:
CPI
Non-Farm Payroll
Core Inflation
US Money Supply
US Central Bank Balance Sheet
GDP
PCE
Let's go over the functions of Econometrica.
Creating a Regression Cointegrated Model
The first thing Econometrica does is creates a co-integrated regression, as you see in the main chart, predicting ticker value ranges from fundamental economic data.
You can visualize this in the main chart above, but here are some other examples:
SPY vs Core Inflation:
BA vs PCE:
QQQ vs US Balance Sheet:
The band represents the anticipated range the ticker should theoretically fall in based on the underlying economic value. The indicator will breakdown the relationship between the economic indicator and the ticker more precisely. In the images above, you can see how there are some metrics provided, including Stationairty, lagged correlation, Integrated Correlation and R2. Let's discuss these very briefly:
Stationarity: checks to ensure that the relationship between the economic indicator and ticker is stationary. Stationary data is important for making unbiased inferences and projections, so having data that is stationary is valuable.
Lagged Correlation: This is a very interesting metric. Lagged correlation means whether there is a delay in the economic indicator and the response of the ticker. Typically, you will observed a lagged correlation between an economic indicator and price of a ticker, as it can take some time for economic changes to reach the market. This lagged correlation will provide you with how long it takes for the economic indicator to catch up with the ticker in months.
Integrated Correlation: This metric tells you how good of a fit the regression bands are in relation to the ticker price. A higher correlation, means the model is better at consistent and accurate information about the anticipated range for the ticker in relation to the economic indicator.
R2: Provides information on the variance and degree of model fit. A high R2 value means that the model is capable of explaining a large amount of variance between the economic indicator and the ticker price action.
Explaining the Relationship
Owning to the fact that the indicator is a bit on the mathy side (it has to be to do this kind of task), I have included ability for the indicator to explain and make suggestions based on the underlying data. It can assess the model's fit and make suggestions for tweaking. It can also explain the implications of the data being presented in the model.
Here is an example with QQQ and the US Balance Sheet:
This helps to simplify and interpret the results you are looking at.
Forecasting the Economic Indicator
In addition to assessing the economic indicator's impact on the ticker, the indicator is also capable of forecasting out the economic indicator over the next 25 releases.
Here is an example of the CPI forecast:
Overall use of the indicator
The indicator is meant to bridge the gap between Technical Analysis and Fundamental Analysis.
Any trader who is attune to fundamentals would benefit from this, as this provides you with objective data on how and to what extent fundamental and economic data impacts tickers.
It can help affirm hypothesis and dispel myths objectively.
It also omits the need from having to perform these types of analyses outside of Tradingview (i.e. in excel, R or Python), as you can get the data in just a few licks of enabling the indicator.
Conclusion
I have tried to make this indicator as user friendly as possible. Though it uses a lot of math, it is fairly straight forward to interpret.
The band plotted can be considered the fair market value or FMV of the ticker based on the underlying economic data, provided the indicator tells you that the relationship is significant (and it will blatantly give you this information verbatim, you don't have to interpret the math stuff).
This is US economic data only. It does not pull economic data from other countries. You can absolutely see how US economic data impacts other markets like the TSX, BANKNIFTY, NIFTY, DAX etc. but the indicator is only pulling US economic data.
That is it!
I hope you enjoy it and find this helpful!
Thanks everyone and safe trades as always 🚀🚀🚀
STRX - Correlation DominationThis indicator displays the correlation among three selected assets (for example, Gold, Dollar Index, and Nasdaq) on a custom timeframe. A table positioned at the top-right corner of the chart lets you quickly see the correlation between:
Asset 1 vs Asset 2
Asset 1 vs Asset 3
Asset 2 vs Asset 3
Correlations are calculated using the Pearson correlation function (ta.correlation). If the correlation is greater than or equal to 0.4, the value appears in green (strong positive correlation). If it is less than or equal to -0.4, it appears in red (strong negative correlation). Otherwise, it is displayed in yellow (weak correlation).
Multi-asset and multi-timeframe: Compare up to three instruments at once on your chosen timeframe.
Customizable period: Use the “Correlation Period” setting to adjust the correlation calculation window.
Clear table format: The results are immediately visible in an easy-to-read table.
Disclaimer: This script is provided solely for educational and informational purposes. It does not constitute a recommendation or an invitation to invest. Use it as an additional resource and always conduct thorough market analysis before opening any trading positions. Past performance does not guarantee future results.
ICT Professional Accumulation DistributionICT Professional Accumulation Distribution (ICT AD) provides a x-ray view into market accumulation and distribution. You can literally see the institutions at work.
The indicator consists of two cumulative lines derived from:
Cumulative change from open to close
Cumulative change from previous close to new open
By overlaying these two cumulative lines, you can detect real meaningful divergence that is narrative based not mathematically derived. You're seeing the real works of algorithms in play working in this area.
These divergences are only useful at extremes (topping or bottoming formations), not while trending. It will probably confirm your suspicion about making a important high or low.
This works on all timeframes but is most impactful on the daily.
How to use:
Method 1:
Enable the option for "Show Open vs Close."
Calculate the shift by subtracting the "Open vs Close" line value from the ICT Accumulation/Distribution (AD) line value.
Look for divergences between the two cumulative lines.
Method 2:
Switch the chart's display mode to "Line View" (representing the Open vs Close).
look for divergences between the line chart and the ICT AD line.
BTC x M2 Divergence (Weekly)### Why the "M2 Money Supply vs BTC Divergence with Normalized RSI" Indicator Should Work
IMPORTANT
- Weekly only indicator
- Combine it with BTC Halving Cycle Profit for better results
The "M2 Money Supply vs BTC Divergence with Normalized RSI" indicator leverages the relationship between macroeconomic factors (M2 money supply) and Bitcoin price movements, combined with technical analysis tools like RSI, to provide actionable trading signals. Here's a detailed rationale on why this indicator should be effective:
1. **Macroeconomic Influence**:
- **M2 Money Supply**: Represents the total money supply, including cash, checking deposits, and easily convertible near money. Changes in M2 reflect liquidity in the economy, which can influence asset prices, including Bitcoin.
- **Bitcoin Sensitivity to Liquidity**: Bitcoin, being a digital asset, often reacts to changes in liquidity conditions. An increase in money supply can lead to higher asset prices as more money chases fewer assets, while a decrease can signal tightening conditions and lower prices.
2. **Divergence Analysis**:
- **Economic Divergence**: The indicator calculates the divergence between the percentage changes in M2 and Bitcoin prices. This divergence can highlight discrepancies between Bitcoin's price movements and broader economic conditions.
- **Market Inefficiencies**: Large divergences may indicate inefficiencies or imbalances that could lead to price corrections or trends. For example, if M2 is increasing (indicating more liquidity) but Bitcoin is not rising proportionately, it might suggest a potential upward correction in Bitcoin's price.
3. **Normalization and Smoothing**:
- **Normalized Divergence**: Normalizing the divergence to a consistent scale (-100 to 100) allows for easier comparison and interpretation over time, making the signals more robust.
- **Smoothing with EMA**: Applying Exponential Moving Averages (EMAs) to the normalized divergence helps to reduce noise and identify the underlying trend more clearly. This double-smoothed divergence provides a clearer signal by filtering out short-term volatility.
4. **RSI Integration**:
- **RSI as a Momentum Indicator**: RSI measures the speed and change of price movements, indicating overbought or oversold conditions. Normalizing the RSI and incorporating it into the divergence analysis helps to confirm the strength of the signals.
- **Combining Divergence with RSI**: By using RSI in conjunction with divergence, the indicator gains an additional layer of confirmation. For instance, a bullish divergence combined with an oversold RSI can be a strong buy signal.
5. **Dynamic Zones and Sensitivity**:
- **Good DCA Zones**: Highlighting zones where the divergence is significantly positive (good DCA zones) indicates periods where Bitcoin might be undervalued relative to economic conditions, suggesting good buying opportunities.
- **Red Zones**: Marking zones with extremely negative divergence, combined with RSI confirmation, identifies potential market tops or bearish conditions. This helps traders avoid buying into overbought markets or consider selling.
- **Peak Detection**: The sensitivity setting for detecting upside down peaks allows for early identification of potential market bottoms, providing timely entry points for traders.
6. **Visual Cues and Alerts**:
- **Clear Visualization**: The plots and background colors provide immediate visual feedback, making it easier for traders to spot significant conditions without deep analysis.
- **Alerts**: Built-in alerts for key conditions (good DCA zones, red zones, sell signals) ensure traders can act promptly based on the indicator's signals, enhancing the practicality of the tool.
### Conclusion
The "M2 Money Supply vs BTC Divergence with Normalized RSI" indicator integrates macroeconomic data with technical analysis to offer a comprehensive view of Bitcoin's market conditions. By analyzing the divergence between M2 money supply and Bitcoin prices, normalizing and smoothing the data, and incorporating RSI for momentum confirmation, the indicator provides robust signals for identifying potential buying and selling opportunities. This holistic approach increases the likelihood of capturing significant market movements and making informed trading decisions.
Divergence Indicator [Trendoscope®]🎲 New Divergence Indicator by Trendoscope
Our latest Divergence Indicator revolutionizes the way traders identify market trends and potential reversals. Built upon the robust foundation of the Zigzag Trend Divergence Detector and inline with our recent implementation of the Divergence Goggles indicator, this tool is designed to be intuitive yet powerful, making it an essential addition to any trader's toolkit.
We received several queries on extending the Divergence Goggles to last N bars instead of using an interactive widget. Though it is possible, we thought the better approach is to enable the indicator to use any oscillator and trend indicator in order to define the divergence.
🎯 Key Features
Flexible Oscillator Integration : Choose from a wide range of built-in oscillators or import your own, including options like the innovative Multiband Oscillator. This versatility extends to using volume indicators like OBV for divergence calculations, broadening the scope of analysis.
Trend Identification Versatility : Utilize built-in methods like Zigzag and MA Difference, or integrate external trend indicators. Our system adapts to various methods, ensuring you have the right tools for precise trend identification.
Customizable Zigzag Sensitivity : Adjust the Zigzag based on your chosen oscillator's sensitivity to ensure divergence lines are accurate and visually coherent.
Repainting vs. Delayed Signals : Tailor the indicator to your strategy by choosing between immediate repainting signals and slightly delayed but more stable signals.
🎯 Understanding Divergence: Key Rules
Bullish Divergence
Happens only in downtrend
Observed on Pivot Lows
Price makes lower low whereas oscillator makes higher low, indicating weakness and possible reversal
Bearish Divergence
Happens only in uptrend
Observed on Pivot Highs
Price makes higher high whereas oscillator makes lower high, indicating weakness and possible reversal
Bullish Hidden Divergence
Happens only in uptrend
Observed on Pivot Lows
Price makes higher low, whereas indicator makes lower low due to price consolidation. In bullish trend, this is considered as bullish as the price gets a breather and get ready to surge further.
Bearish Hidden Divergence
Happens only in downtrend
Observed on Pivot Highs
Price makes lower high whereas oscillator makes higher high due to price consolidation. In bearish trend, this is considered as bearish as the price gets a breather and get ready to fall further.
🎯 Visual Insights: Divergence and Hidden Divergence
For a clearer understanding, refer to our visual guides:
🎲 Using the Divergence Indicator: A Step-by-Step Guide
🎯 Step 1 - Selecting the Oscillator
Customize your analysis by choosing from a variety of oscillators or importing your preferred one. Options are available to select a range of built-in oscillators and the loopback length. However, if the oscillator that user want to use is not in the list, they can simply load the oscillator from the indicator library and use it as an external signal.
In our current example, we are using a custom oscillator called - Multiband Oscillator
This also means, the indicator option is not limited to oscillators. Users can even make use of volume indicators such as OBV for the calculation of divergence.
🎯 Step 2 - Choosing the Trend Identification Method
Select from our built-in methods or integrate an external indicator to accurately identify market trends. Trend is one of the key parameters of divergence type identification. Trend can be identified mathematically by various methods. Some of them are as simple as above or below 200 moving average and some can follow trend based indicators such as supertrend and others can be very complex.
To cater for a wider audience, here too we have provided the option to use an external trend indicator. The simple condition for the external trend indicator is that it should return positive value for uptrend and negative value for downtrend.
Other than that, we also have 2 built in trend identification methods.
Zigzag - The trend is defined by the starting pivot of divergence line. If the starting pivot is Higher High or Higher Low, then it is considered uptrend. And if the starting pivot is either Lower Low or Lower High, then we consider it as downtrend.
MA Difference - In this case, the difference between the moving average of pivots joining the divergence line will determine the trend. It is considered uptrend if the moving average increased from starting pivot to ending pivot of the divergence line, and it is considered downtrend if the moving average decreased from starting pivot to the ending pivot of the divergence line.
🎯 Step 3 - Adjusting Zigzag Sensitivity
Fine-tune the Zigzag to match the oscillator's sensitivity, ensuring divergence lines are accurate and visually coherent.
🎯 Step 4 - Managing Repainting
Understand the implications of repainting in the last pivot of the Zigzag and choose between immediate or delayed signals based on your trading strategy. The last pivot of the zigzag repaint by design. This is not necessarily a bad thing. Users can just choose not to use the last pivot, but instead use the last but one for all the calculations. But, this also means, the signals will be delayed.
Indicator provides option to use repainting signal vs delayed signal. If you select the repaint option, the signals are shown immediately as and when they occur. But, there is a possibility that these signals change when the new price candles change zigzag pivot.
If you chose not to select the repaint option, then the divergence signals may lag by a few bars.
RVol LabelThis Code is update version of Code Provided by @ssbukam, Here is Link to his original Code and review the Description
Below is Original Description
1. When chart resolution is Daily or Intraday (D, 4H, 1H, 5min, etc), Relative Volume shows value based on DAILY. RVol is measured on daily basis to compare past N number of days.
2. When resolution is changed to Weekly or Monthly, then Relative Volume shows corresponding value. i.e. Weekly shows weekly relative volume of this week compared to past 'N' weeks. Likewise for Monthly. You would see change in label name. Like, Weekly chart shows W_RVol (Weekly Relative Volume). Likewise, Daily & Intraday shows D_RVol. Monthly shows M_RVol (Monthly Relative Volume).
3. Added a plot (by default hidden) for this specific reason: When you move the cursor to focus specific candle, then Indicator Value displays relative volume of that specific candle. This applies to Intraday as well. So if you're in 1HR chart and move the cursor to a specific candle, Indicator Value shows relative volume for that specific candlestick bar.
4. Updating the script so that text size and location can be customized.
Changes to Updated Label by me
1. Added Today's Volume to the Label
2. Added Total Average Volume to the Label
3. Comparison vs Both in Single Line and showing how much volume has traded vs the average volume for that time of the day
4. Aesthetic Look of the Label
How to Use Relative Volume for Trading
Using Relative Volume (RVol) in trading can be a valuable tool to help you identify potential trading opportunities and gain insight into market behavior. Here are some ways to use RVol in your trading strategy:
Identifying High-Volume Breakouts: RVol can help you spot potential breakouts when the volume surges significantly above its average. High RVol during a breakout suggests strong market interest, increasing the probability of a sustained move in the direction of the breakout.
Confirming Trends and Reversals: RVol can act as a confirmation tool for trends and reversals. A trend accompanied by rising RVol indicates a strong and sustainable move. Conversely, a trend with declining RVol might suggest a weakening trend or potential reversal.
Spotting Volume Divergence: When the price is moving in one direction, but RVol is declining or not confirming the move, it may indicate a divergence. This discrepancy could suggest a potential reversal or trend change.
Support and Resistance Confirmation: High RVol near key support or resistance levels can indicate potential price reactions at those levels. This confirmation can be valuable in determining whether a level is likely to hold or break.
Filtering Trade Signals: Incorporate RVol into your existing trading strategy as a filter. For example, you might consider taking trades only if RVol is above a certain threshold, ensuring that you focus on high-impact trading opportunities.
Avoiding Low-Volume Traps: Low RVol can indicate a lack of interest or participation in the market. In such situations, price movements may be erratic and less reliable, so it's often wise to avoid trading during low RVol periods.
Monitoring News Events: Around significant news events or earnings releases, RVol can help you gauge the market's reaction to the information. High RVol during such events can present trading opportunities but be cautious of increased volatility and potential gaps.
Adjusting Trade Size: During periods of extremely high RVol, it might be prudent to adjust your position size to account for higher risk.
Using Relative Volume in Morning Session
If the Volume traded in first 15 minute to 30 Minutes is already at 50% or 100% depending upon the ticker, it means that it is going to have very high Volume vs average by end of the day.
This gives me conviction for Long or Short Trades
Remember that RVol is not a standalone indicator; it works best when used in conjunction with other technical and fundamental analysis tools. Additionally, RVol's effectiveness may vary across different markets and trading strategies. Therefore, backtesting and validating the use of RVol in your trading approach is essential.
Lastly, risk management is crucial in trading. While RVol can provide valuable insights, it cannot guarantee profitable trades. Always use appropriate risk management strategies, such as setting stop-loss levels, and avoid overexposing yourself to the market based solely on RVol readings.
Market Structure & Liquidity: CHoCHs+Nested Pivots+FVGs+Sweeps//Purpose:
This indicator combines several tools to help traders track and interpret price action/market structure; It can be divided into 4 parts;
1. CHoCHs, 2. Nested Pivot highs & lows, 3. Grade sweeps, 4. FVGs.
This gives the trader a toolkit for determining market structure and shifts in market structure to help determine a bull or bear bias, whether it be short-term, med-term or long-term.
This indicator also helps traders in determining liquidity targets: wether they be voids/gaps (FVGS) or old highs/lows+ typical sweep distances.
Finally, the incorporation of HTF CHoCH levels printing on your LTF chart helps keep the bigger picture in mind and tells traders at a glance if they're above of below Custom HTF CHoCH up or CHoCH down (these HTF CHoCHs can be anything from Hourly up to Monthly).
//Nomenclature:
CHoCH = Change of Character
STH/STL = short-term high or low
MTH/MTL = medium-term high or low
LTH/LTL = long-term high or low
FVG = Fair value gap
CE = consequent encroachement (the midline of a FVG)
~~~ The Four components of this indicator ~~~
1. CHoCHs:
•Best demonstrated in the below charts. This was a method taught to me by @Icecold_crypto. Once a 3 bar fractal pivot gets broken, we count backwards the consecutive higher lows or lower highs, then identify the CHoCH as the opposite end of the candle which ended the consecutive backwards count. This CHoCH (UP or DOWN) then becomes a level to watch, if price passes through it in earnest a trader would consider shifting their bias as market structure is deemed to have shifted.
•HTF CHoCHs: Option to print Higher time frame chochs (default on) of user input HTF. This prints only the last UP choch and only the last DOWN choch from the input HTF. Solid line by default so as to distinguish from local/chart-time CHoCHs. Can be any Higher timeframe you like.
•Show on table: toggle on show table(above/below) option to show in table cells (top right): is price above the latest HTF UP choch, or is price below HTF DOWN choch (or is it sat between the two, in a state of 'uncertainty').
•Most recent CHoCHs which have not been met by price will extend 10 bars into the future.
• USER INPUTS: overall setting: SHOW CHOCHS | Set bars lookback number to limit historical Chochs. Set Live CHoCHs number to control the number of active recent chochs unmet by price. Toggle shrink chochs once hit to declutter chart and minimize old chochs to their origin bars. Set Multi-timeframe color override : to make Color choices auto-set to your preference color for each of 1m, 5m, 15m, H, 4H, D, W, M (where up and down are same color, but 'up' icon for up chochs and down icon for down chochs remain printing as normal)
2. Nested Pivot Highs & Lows; aka 'Pivot Highs & Lows (ST/MT/LT)'
•Based on a seperate, longer lookback/lookforward pivot calculation. Identifies Pivot highs and lows with a 'spikeyness' filter (filtering out weak/rounded/unimpressive Pivot highs/lows)
•by 'nested' I mean that the pivot highs are graded based on whether a pivot high sits between two lower pivot highs or vice versa.
--for example: STH = normal pivot. MTH is pivot high with a lower STH on either side. LTH is a pivot high with a lower MTH on either side. Same applies to pivot lows (STL/MTL/LTL)
•This is a useful way to measure the significance of a high or low. Both in terms of how much it might be typically swept by (see later) and what it would imply for HTF bias were we to break through it in earnest (more than just a sweep).
• USER INPUTS: overall setting: show pivot highs & lows | Bars lookback (historical pivots to show) | Pivots: lookback/lookforward length (determines the scale of your pivot highs/lows) | toggle on/off Apply 'Spikeyness' filter (filters out smooth/unimpressive pivot highs/lows). Set Spikeyness index (determines the strength of this filter if turned on) | Individually toggle on each of STH, MTH, LTH, STL, MTL, LTL along with their label text type , and size . Toggle on/off line for each of these Pivot highs/lows. | Set label spacer (atr multiples above / below) | set line style and line width
3. Grade Sweeps:
•These are directly related to the nested pivots described above. Most assets will have a typical sweep distance. I've added some of my expected sweeps for various assets in the indicator tooltips.
--i.e. Eur/Usd 10-20-30 pips is a typical 'grade' sweep. S&P HKEX:5 - HKEX:10 is a typical grade sweep.
•Each of the ST/MT/LT pivot highs and lows have optional user defined grade sweep boxes which paint above until filled (or user option for historical filled boxes to remain).
•Numbers entered into sweep input boxes are auto converted into appropriate units (i.e. pips for FX, $ or 'handles' for indices, $ for Crypto. Very low $ units can be input for low unit value crypto altcoins.
• USER INPUTS: overall setting: Show sweep boxes | individually select colors of each of STH, MTH, LTH, STL, MTL, LTL sweep boxes. | Set Grade sweep ($/pips) number for each of ST, MT, LT. This auto converts between pips and $ (i.e. FX vs Indices/Crypto). Can be a float as small or large as you like ($0.000001 to HKEX:1000 ). | Set box text position (horizontal & vertical) and size , and color . | Set Box width (bars) (for non extended/ non-auto-terminating at price boxes). | toggle on/off Extend boxes/lines right . | Toggle on/off Shrink Grade sweeps on fill (they will disappear in realtime when filled/passed through)
4. FVGs:
•Fair Value gaps. Represent 'naked' candle bodies where the wicks to either side do not meet, forming a 'gap' of sorts which has a tendency to fill, or at least to fill to midline (CE).
•These are ICT concepts. 'UP' FVGS are known as BISIs (Buyside imbalance, sellside inefficiency); 'DOWN' FVGs are known as SIBIs (Sellside imbalance, buyside inefficiency).
• USER INPUTS: overall setting: show FVGs | Bars lookback (history). | Choose to display: 'UP' FVGs (BISI) and/or 'DOWN FVGs (SIBI) . Choose to display the midline: CE , the color and the line style . Choose threshold: use CE (as opposed to Full Fill) |toggle on/off Shrink FVG on fill (CE hit or Full fill) (declutter chart/see backtesting history)
////••Alerts (general notes & cautionary notes)::
•Alerts are optional for most of the levels printed by this indicator. Set them via the three dots on indicator status line.
•Due to dynamic repainting of levels, alerts should be used with caution. Best use these alerts either for Higher time frame levels, or when closely monitoring price.
--E.g. You may set an alert for down-fill of the latest FVG below; but price will keep marching up; form a newer/higher FVG, and the alert will trigger on THAT FVG being down-filled (not the original)
•Available Alerts:
-FVG(BISI) cross above threshold(CE or full-fill; user choice). Same with FVG(SIBI).
-HTF last CHoCH down, cross below | HTF last CHoCH up, cross above.
-last CHoCH down, cross below | last CHoCH up, cross above.
-LTH cross above, MTH cross above, STH cross above | LTL cross below, MTL cross below, STL cross below.
////••Formatting (general)::
•all table text color is set from the 'Pivot highs & Lows (ST, MT, LT)' section (for those of you who prefer black backgrounds).
•User choice of Line-style, line color, line width. Same with Boxes. Icon choice for chochs. Char or label text choices for ST/MT/LT pivot highs & lows.
////••User Inputs (general):
•Each of the 4 components of this indicator can be easily toggled on/off independently.
•Quite a lot of options and toggle boxes, as described in full above. Please take your time and read through all the tooltips (hover over '!' icon) to get an idea of formatting options.
•Several Lookback periods defined in bars to control how much history is shown for each of the 4 components of this indicator.
•'Shrink on fill' settings on FVGs and CHoCHs: Basically a way to declutter chart; toggle on/off depending on if you're backtesting or reading live price action.
•Table Display: applies to ST/MT/LT pivot highs and to HTF CHoCHs; Toggle table on or off (in part or in full)
////••Credits:
•Credit to ICT (Inner Circle Trader) for some of the concepts used in this indicator (FVGS & CEs; Grade sweeps).
•Credit to @Icecold_crypto for the specific and novel concept of identifying CHoCHs in a simple, objective and effective manner (as demonstrated in the 1st chart below).
CHoCH demo page 1: shifting tweak; arrow diagrams to demonstrate how CHoCHs are defined:
CHoCH demo page 2: Simplified view; short lookback history; few CHoCHs, demo of 'latest' choch being extended into the future by 10 bars:
USAGE: Bitcoin Hourly using HTF daily CHoCHs:
USAGE-2: Cotton Futures (CT1!) 2hr. Painting a rather bullish picture. Above HTF UP CHoCH, Local CHoCHs show bullish order flow, Nice targets above (MTH/LTH + grade sweeps):
Full Demo; 5min chart; CHoCHs, Short term pivot highs/lows, grade sweeps, FVGs:
Full Demo, Eur/Usd 15m: STH, MTH, LTH grade sweeps, CHoCHs, Usage for finding bias (part A):
Full Demo, Eur/Usd 15m: STH, MTH, LTH grade sweeps, CHoCHs, Usage for finding bias, 3hrs later (part B):
Realtime Vs Backtesting(A): btc/usd 15m; FVGs and CHoCHs: shrink on fill, once filled they repaint discreetly on their origin bar only. Realtime (Shrink on fill, declutter chart):
Realtime Vs Backtesting(B): btc/usd 15m; FVGs and CHoCHs: DON'T shrink on fill; they extend to the point where price crosses them, and fix/paint there. Backtesting (seeing historical behaviour):
Support Bands indicatorSupport Band to follow Trends.
We can see clear where price is Trading. Observe how moving averages are developing or aligning to change trend or continuation.
Green up trend vs Red Down Trend
Band 1
8EMA Green Line vs 10SMA Light blue Line
Band 2
21EMA Orange Line vs 30 SMA Brown Line
Also includes
1 SMA Gray line for closing when you're looking at weakly charts.
40 SMA darker Gray
50 SMA Blue
100 SMA White
150 SMA Pink
200 SMA Yellow
300 SMA Dark Red
I hope it helps you to see when price is trending up and a set correctly your stop.
CVD - Cumulative Volume Delta Candles█ OVERVIEW
This indicator displays cumulative volume delta in candle form. It uses intrabar information to obtain more precise volume delta information than methods using only the chart's timeframe.
█ CONCEPTS
Bar polarity
By bar polarity , we mean the direction of a bar, which is determined by looking at the bar's close vs its open .
Intrabars
Intrabars are chart bars at a lower timeframe than the chart's. Each 1H chart bar of a 24x7 market will, for example, usually contain 60 bars at the lower timeframe of 1min, provided there was market activity during each minute of the hour. Mining information from intrabars can be useful in that it offers traders visibility on the activity inside a chart bar.
Lower timeframes (LTFs)
A lower timeframe is a timeframe that is smaller than the chart's timeframe. This script uses a LTF to access intrabars. The lower the LTF, the more intrabars are analyzed, but the less chart bars can display CVD information because there is a limit to the total number of intrabars that can be analyzed.
Volume delta
The volume delta concept divides a bar's volume in "up" and "down" volumes. The delta is calculated by subtracting down volume from up volume. Many calculation techniques exist to isolate up and down volume within a bar. The simplest techniques use the polarity of interbar price changes to assign their volume to up or down slots, e.g., On Balance Volume or the Klinger Oscillator . Others such as Chaikin Money Flow use assumptions based on a bar's OHLC values. The most precise calculation method uses tick data and assigns the volume of each tick to the up or down slot depending on whether the transaction occurs at the bid or ask price. While this technique is ideal, it requires huge amounts of data on historical bars, which usually limits the historical depth of charts and the number of symbols for which tick data is available.
This indicator uses intrabar analysis to achieve a compromise between the simplest and most precise methods of calculating volume delta. In the context where historical tick data is not yet available on TradingView, intrabar analysis is the most precise technique to calculate volume delta on historical bars on our charts. Our Volume Profile indicators use it. Other volume delta indicators in our Community Scripts such as the Realtime 5D Profile use realtime chart updates to achieve more precise volume delta calculations, but that method cannot be used on historical bars, so those indicators only work in real time.
This is the logic we use to assign intrabar volume to up or down slots:
• If the intrabar's open and close values are different, their relative position is used.
• If the intrabar's open and close values are the same, the difference between the intrabar's close and the previous intrabar's close is used.
• As a last resort, when there is no movement during an intrabar and it closes at the same price as the previous intrabar, the last known polarity is used.
Once all intrabars making up a chart bar have been analyzed and the up or down property of each intrabar's volume determined, the up volumes are added and the down volumes subtracted. The resulting value is volume delta for that chart bar.
█ FEATURES
CVD Candles
Cumulative Volume Delta Candles present volume delta information as it evolves during a period of time.
This is how each candle's levels are calculated:
• open : Each candle's' open level is the cumulative volume delta for the current period at the start of the bar.
This value becomes zero on the first candle following a CVD reset.
The candles after the first one always open where the previous candle closed.
The candle's high, low and close levels are then calculated by adding or subtracting a volume value to the open.
• high : The highest volume delta value found in intrabars. If it is not higher than the volume delta for the bar, then that candle will have no upper wick.
• low : The lowest volume delta value found in intrabars. If it is not lower than the volume delta for the bar, then that candle will have no lower wick.
• close : The aggregated volume delta for all intrabars. If volume delta is positive for the chart bar, then the candle's close will be higher than its open, and vice versa.
The candles are plotted in one of two configurable colors, depending on the polarity of volume delta for the bar.
CVD resets
The "cumulative" part of the indicator's name stems from the fact that calculations accumulate during a period of time. This allows you to analyze the progression of volume delta across manageable chunks, which is often more useful than looking at volume delta cumulated from the beginning of a chart's history.
You can configure the reset period using the "CVD Resets" input, which offers the following selections:
• None : Calculations do not reset.
• On a fixed higher timeframe : Calculations reset on the higher timeframe you select in the "Fixed higher timeframe" field.
• At a fixed time that you specify.
• At the beginning of the regular session .
• On a stepped higher timeframe : Calculations reset on a higher timeframe automatically stepped using the chart's timeframe and following these rules:
Chart TF HTF
< 1min 1H
< 3H 1D
<= 12H 1W
< 1W 1M
>= 1W 1Y
The indicator's background shows where resets occur.
Intrabar precision
The precision of calculations increases with the number of intrabars analyzed for each chart bar. It is controlled through the script's "Intrabar precision" input, which offers the following selections:
• Least precise, covering many chart bars
• Less precise, covering some chart bars
• More precise, covering less chart bars
• Most precise, 1min intrabars
As there is a limit to the number of intrabars that can be analyzed by a script, a tradeoff occurs between the number of intrabars analyzed per chart bar and the chart bars for which calculations are possible.
Total volume candles
You can choose to display candles showing the total intrabar volume for the chart bar. This provides you with more context to evaluate a bar's volume delta by showing it relative to the sum of intrabar volume. Note that because of the reasons explained in the "NOTES" section further down, the total volume is the sum of all intrabar volume rather than the volume of the bar at the chart's timeframe.
Total volume candles can be configured with their own up and down colors. You can also control the opacity of their bodies to make them more or less prominent. This publication's chart shows the indicator with total volume candles. They are turned off by default, so you will need to choose to display them in the script's inputs for them to plot.
Divergences
Divergences occur when the polarity of volume delta does not match that of the chart bar. You can identify divergences by coloring the CVD candles differently for them, or by coloring the indicator's background.
Information box
An information box in the lower-left corner of the indicator displays the HTF used for resets, the LTF used for intrabars, and the average quantity of intrabars per chart bar. You can hide the box using the script's inputs.
█ INTERPRETATION
The first thing to look at when analyzing CVD candles is the side of the zero line they are on, as this tells you if CVD is generally bullish or bearish. Next, one should consider the relative position of successive candles, just as you would with a price chart. Are successive candles trending up, down, or stagnating? Keep in mind that whatever trend you identify must be considered in the context of where it appears with regards to the zero line; an uptrend in a negative CVD (below the zero line) may not be as powerful as one taking place in positive CVD values, but it may also predate a movement into positive CVD territory. The same goes with stagnation; a trader in a long position will find stagnation in positive CVD territory less worrisome than stagnation under the zero line.
After consideration of the bigger picture, one can drill down into the details. Exactly what you are looking for in markets will, of course, depend on your trading methodology, but you may find it useful to:
• Evaluate volume delta for the bar in relation to price movement for that bar.
• Evaluate the proportion that volume delta represents of total volume.
• Notice divergences and if the chart's candle shape confirms a hesitation point, as a Doji would.
• Evaluate if the progress of CVD candles correlates with that of chart bars.
• Analyze the wicks. As with price candles, long wicks tend to indicate weakness.
Always keep in mind that unless you have chosen not to reset it, your CVD resets for each period, whether it is fixed or automatically stepped. Consequently, any trend from the preceding period must re-establish itself in the next.
█ NOTES
Know your volume
Traders using volume information should understand the volume data they are using: where it originates and what transactions it includes, as this can vary with instruments, sectors, exchanges, timeframes, and between historical and realtime bars. The information used to build a chart's bars and display volume comes from data providers (exchanges, brokers, etc.) who often maintain distinct feeds for intraday and end-of-day (EOD) timeframes. How volume data is assembled for the two feeds depends on how instruments are traded in that sector and/or the volume reporting policy for each feed. Instruments from crypto and forex markets, for example, will often display similar volume on both feeds. Stocks will often display variations because block trades or other types of trades may not be included in their intraday volume data. Futures will also typically display variations.
Note that as intraday vs EOD variations exist for historical bars on some instruments, differences may also exist between the realtime feeds used on intraday vs 1D or greater timeframes for those same assets. Realtime reporting rules will often be different from historical feed reporting rules, so variations between realtime feeds will often be different from the variations between historical feeds for the same instrument. The Volume X-ray indicator can help you analyze differences between intraday and EOD volumes for the instruments you trade.
If every unit of volume is both bought by a buyer and sold by a seller, how can volume delta make sense?
Traders who do not understand the mechanics of matching engines (the exchange software that matches orders from buyers and sellers) sometimes argue that the concept of volume delta is flawed, as every unit of volume is both bought and sold. While they are rigorously correct in stating that every unit of volume is both bought and sold, they overlook the fact that information can be mined by analyzing variations in the price of successive ticks, or in our case, intrabars.
Our calculations model the situation where, in fully automated order handling, market orders are generally matched to limit orders sitting in the order book. Buy market orders are matched to quotes at the ask level and sell market orders are matched to quotes at the bid level. As explained earlier, we use the same logic when comparing intrabar prices. While using intrabar analysis does not produce results as precise as when individual transactions — or ticks — are analyzed, results are much more precise than those of methods using only chart prices.
Not only does the concept underlying volume delta make sense, it provides a window on an oft-overlooked variable which, with price and time, is the only basic information representing market activity. Furthermore, because the calculation of volume delta also uses price and time variations, one could conceivably surmise that it can provide a more complete model than ones using price and time only. Whether or not volume delta can be useful in your trading practice, as usual, is for you to decide, as each trader's methodology is different.
For Pine Script™ coders
As our latest Polarity Divergences publication, this script uses the recently released request.security_lower_tf() Pine Script™ function discussed in this blog post . It works differently from the usual request.security() in that it can only be used at LTFs, and it returns an array containing one value per intrabar. This makes it much easier for programmers to access intrabar information.
Look first. Then leap.
