Indicator

Relative Strength Regime Meter (SPY/QQQ/Peer Auto)RS Dash v2 is a relative strength (RS) dashboard designed to quickly answer one question:
Is this asset leading or lagging vs (1) the market, (2) Nasdaq/growth, and (3) its peer group?
What it measures
For the current chart symbol, it calculates RS ratios:
RS vs SPY (market baseline)
RS vs QQQ (Nasdaq / growth baseline)
RS vs PEER ETF (sector/industry baseline)
RS ratio is simply:
RS = Symbol Close / Benchmark Close
Then it compares each RS ratio to its moving average (MA):
✅ if RS > RS_MA
Optional stricter rule: ✅ only if RS > RS_MA and RS_MA is rising
Peer ETF: Manual or Auto
You can pick the peer ETF in two ways:
MANUAL mode
Choose from labeled options like:
XLK – TECH, XLE – ENERGY, SMH – SEMIS, etc.
AUTO mode (default)
The script selects the peer ETF whose returns have the highest correlation to the symbol over a lookback window, with guardrails:
Min correlation threshold: if correlation is too low, it falls back to your chosen fallback peer.
Sticky switching: it only changes peer when the new best peer is better by a set margin (reduces “flicker”).
The table shows what AUTO picked, and it also prints the correlation as a trust meter.
Dashboard + Score
A table (bottom-left) shows:
SPY ✅/❌
QQQ ✅/❌
PEER ✅/❌ (with chosen peer name)
Total score 0–3
Interpretation:
3/3 = strong leadership (outperforming market + Nasdaq + peers)
2/3 = mixed leadership
0–1/3 = weak / lagging regime
Plot modes (solves scaling issues)
Because raw RS ratios can be on very different numeric scales, there are three plot modes:
Signal (% vs RS MA) (recommended)
Plots each RS as % above/below its RS MA where 0 = neutral.
Indexed (Base 100)
Normalizes each RS to start at 100 so you can compare “performance curves.”
Raw (single)
Shows only one RS ratio at a time (SPY / QQQ / PEER) for inspection.
Leadership line (Regime meter)
The Leadership line is a step line that visualizes the 0–3 score as a regime meter (it only has 4 states, by design). It helps you spot regime shifts without reading the table.
Divergences (optional)
Optional bullish/bearish divergence markers compare price pivots vs RS pivots on your chosen benchmark (SPY/QQQ/PEER). These are confirmation tools, not signals by themselves.
What this indicator is NOT
It does not predict tops/bottoms.
It does not replace fundamentals or risk management.
“AUTO peer” is correlation-based; in unusual regimes it can pick a peer that’s statistically close but not conceptually perfect — override with MANUAL when needed.
Suggested workflow
Keep plot mode on Signal (% vs RS MA)
Use AUTO peer for speed; flip to MANUAL if the chosen peer doesn’t make sense.
Use score changes + divergences as context, then use your main price/volume system for entries/exits.
Open-source, modify as you like.
Shorter description
RS Dash v2 compares the current symbol’s relative strength vs SPY, QQQ, and a Peer ETF (manual or auto-selected).
Each benchmark gets a ✅/❌ based on whether RS > RS_MA (optional: MA rising). The dashboard shows a 0–3 score and a Leadership step line that visualizes regime shifts.
Includes 3 plot modes to fix scaling: Signal (% vs MA), Indexed Base 100, and Raw single. Optional RS divergences.
Settings explanation
RS MA length: smoothing for RS trend. Higher = slower, fewer flips.
Auto return length / correlation lookback: controls how AUTO chooses the peer. Higher = more stable but slower to adapt.
Min corr / switch delta: guardrails to prevent nonsense picks and rapid switching.
Plot mode: choose Signal for decision clarity, Indexed for comparison curves, Raw for inspection.
Blunt “professional honesty” note
Correlation-based peer selection is a statistical best guess, not a fundamental sector classifier. That’s why the indicator is transparent: it shows the selected peer and correlation so users can override. Indicator

Pair Correlation Master [Macro]The Main Idea
Trading represents a constant battle between Systemic Flows (the whole market moving together) and Idiosyncratic Moves (one specific asset moving on its own).
This tool allows you to monitor a "basket" of 4 assets simultaneously (e.g., the major USD pairs). It answers the most important question in forex and multi-asset trading: "Is this move happening because the Dollar is weak, or because the Euro is strong?"
It separates the "Signal" (the unique move) from the "Noise" (the herd movement).
1. The Chart Lines: The "Race" (Macro Trend)
Think of the lines on your chart as a long-distance race. They visualize the performance of all 4 assets over the last 200 candles (adjustable).
- Bunched Together: If all lines are moving in the same direction, the market is highly correlated. (e.g., "The Dollar is selling off everywhere").
- Fanning Out: If the lines are spreading apart, specific currencies are outperforming others.
- The Zero Line: This is the starting line.
--- Above 0: The pair is in a macro uptrend.
--- Below 0: The pair is in a macro downtrend.
2. The Dashboard: The "Health Check" (Micro Data)
The table in the top right gives you the immediate statistics for right now.
- A. The Z-Score (The Rubber Band)
This measures how "stretched" price is compared to its normal behavior.
- White (< 2.0): Normal trading activity.
- Orange (> 2.0): The price is stretching. Warning sign.
- Red (> 3.0): Critical Stretch. The rubber band is pulled to its limit. Statistically, a pullback or pause is highly likely.
B. The Star (★)
The script automatically calculates the average behavior of your group. If one asset is behaving completely differently from the rest, it marks it with a Star (★).
- Example: EURUSD, GBPUSD, and NZDUSD are flat, but AUDUSD is rallying hard. AUDUSD gets the ★. This is where the unique opportunity lies.
🎯 Best Uses: 4H & Daily Timeframes
This indicator is tuned for "Macro" analysis. It works best on the "4-Hour" and "Daily" charts to filter out intraday noise and capture swing trading moves.
- Strategy 1: The "Rubber Band" Snap (Mean Reversion)
- Setup: Look for a Z-Score in the RED (> 3.0) on the Daily timeframe.
- Action: This indicates an unsustainable move. Look for reversals or exhaustion patterns to trade against the trend back toward the mean.
- Strategy 2: The "Lone Wolf" (Trend Following)
- Setup: Look for the asset with the Star (★).
- Action: If the whole basket is flat (Balanced), but the Star asset is breaking out, that creates a high-quality trend trade because that specific currency has its own catalyst (News/Earnings).
- Strategy 3: Systemic Flows (Basket Trading)
- Setup: The dashboard footer says "⚠️ SYSTEMIC MOVE."
- Action: This means everything is moving together (e.g., a massive USD crash). Don't look for unique setups; just join the trend on the strongest pair.
Dashboard Footer Key
The bottom of the table summarizes the current state of the market for you:
- Balanced / Rangebound: The market is quiet. Good for range trading.
- Focus: : Trade this specific pair. It is moving independently.
- Systemic Move: The whole basket is moving violently. Trade the momentum.
p.s. Suggestion - apply and use on the chart rather than an oscillator. Indicator

Relative Performance Analyzer [AstrideUnicorn]Relative Performance Analyzer (RPA) is a performance analysis tool inspired by the data comparison features found in professional trading terminals. The RPA replicates the analytical approach used by portfolio managers and institutional analysts who routinely compare multiple securities or other types of data to identify relative strength opportunities, make allocation decisions, choose the most optimal investment from several alternatives, and much more.
Key Features:
Multi-Symbol Comparison: Track up to 5 different symbols simultaneously across any asset class or dataset
Two Performance Calculation Methods: Choose between percentage returns or risk-adjusted returns
Interactive Analysis: Drag the start date line on the chart or manually choose the start date in the settings
Professional Visualization: High-contrast color scheme designed for both dark and light chart themes
Live Performance Table: Real-time display of current return values sorted from the top to the worst performers
Practical Use Cases:
ETF Selection: Compare similar ETFs (e.g., SPY vs IVV vs VOO) to identify the most efficient investment
Sector Rotation: Analyze which sectors are showing relative strength for strategic allocation
Competitive Analysis: Compare companies within the same industry to identify leaders (e.g., APPLE vs SAMSUNG vs XIAOMI)
Cross-Asset Allocation: Evaluate performance across stocks, bonds, commodities, and currencies to guide portfolio rebalancing
Risk-Adjusted Decisions: Use risk-adjusted performance to find investments with the best returns per unit of risk
Example Scenarios:
Analyze whether tech stocks are outperforming the broader market by comparing XLK to SPY
Evaluate which emerging market ETF (EEM vs VWO) has provided better risk-adjusted returns over the past year
HOW DOES IT WORK
The indicator calculates and visualizes performance from a user-defined starting point using two methodologies:
Percentage Returns: Standard total return calculation showing percentage change from the start date
Risk-Adjusted Returns: Cumulative returns divided by the volatility (standard deviation), providing insight into the efficiency of performance. An expanding window is used to calculate the volatility, ensuring accurate risk-adjusted comparisons throughout the analysis period.
HOW TO USE
Setup Your Comparison: Enable up to 5 assets and input their symbols in the settings
Set Analysis Period: When you first launch the indicator, select the start date by clicking on the price chart. The vertical start date line will appear. Drag it on the chart or manually input a specific date to change the start date.
Choose Return Type: Select between percentage or risk-adjusted returns based on your analysis needs
Interpret Results
Use the real-time table for precise current values
SETTINGS
Assets 1-5: Toggle on/off and input symbols for comparison (stocks, ETFs, indices, forex, crypto, fundamental data, etc.)
Start Date: Set the initial point for return calculations (drag on chart or input manually)
Return Type: Choose between "Percentage" or "Risk-Adjusted" performance. Indicator

Weekday Close vs Open — Last N (per weekday)# Weekday Close vs Open - Last N Occurrences
This indicator distills every weekday's historical open-to-close behavior into a compact table so you can see how "typical" the current session is before the day even closes. It runs independently of your chart timeframe by pulling daily OHLCV data under the hood, tracking the last **N** completed occurrences for each weekday, and refreshing only when a daily bar closes. On daily charts you can also shade every past bar that matches today's weekday (excluding the in-progress session) to reinforce the pattern visually while the table remains non-repainting.
## What It Shows
- **Win/Loss/Tie counts** - how many of the last `N` occurrences closed above the open (wins), below (losses), or inside the tie threshold you define as "flat".
- **Win % heatmap** - the win column is color-coded (deep green > deep red) so you immediately recognize strong or weak weekdays.
- **Advanced metrics (optional)** - average daily volume plus the average percentage excursion above/below the open (`AvgUp%`, `AvgDn%`) for that weekday.
- **Totals row** - aggregates every weekday into one row to estimate overall hit rate and average stats across the entire data set.
- **Weekday shading (optional)** - on daily charts you can tint every bar that matches today's weekday (all Mondays, all Fridays, etc.) for instant pattern recognition.
## How It Works
1. The script requests daily OHLCV data (non-repainting) regardless of the chart timeframe.
2. When a new daily bar confirms, it packs that day's data into one of seven arrays (one per weekday). Each day contributes five floats (O/H/L/C/V) so trimming and statistics stay in lockstep.
3. A helper function (`f_dayMetrics`) scans daily history to compute average volume, average excursion above/below the open, and win/loss/tie counts for the requested weekday.
4. The table populates on the last bar of the chart session, respecting your advanced/totals toggles and keeping text at `size.normal`.
## Reading the Table
- **Win/Loss/Tie columns**: raw counts taken from your chosen `N`.
- **Win %***: excludes ties from the denominator so it reflects only decisive closes.
- **AvgUp% / AvgDn%**: typical intraday extension (high vs open, open vs low) in percent.
- **Avg Vol**: arithmetic mean of daily volume for that weekday.
- **TOTAL row**: provides a global win rate plus volume/up/down averages weighted by how many samples each weekday contributed.
## Practical Uses
- Spot weekdays that historically trend higher or lower before entering a trade.
- Compare current price action against the typical intraday range (`AvgUp%` vs today's move).
- Filter mean-reversion vs breakout setups based on the most reliable weekday patterns.
- Quickly gauge whether today is behaving "in character" by referencing the highlighted row or the optional whole-chart weekday shading.
> **Tip:** Use smaller `N` values (e.g., 10-20) for adaptive, recent behavior and larger values (50+) to capture longer-term seasonality. Tighten the tie threshold if you want almost every candle to register as win/loss, or widen it to focus only on meaningful moves. Indicator

Symbol vs Benchmark Performance & Volatility TableThis tool puts the current symbol’s performance and volatility side-by-side with any benchmark —NASDAQ, S&P 500, NIFTY or a custom index of your choice.
A quick glance shows whether the stock is outperforming, lagging, or just moving with the market.
⸻
Features
• ✅ Returns over 1W, 1M, 3M, 6M, 12M
• 🔄 Benchmark comparison with optional difference row
• ⚡ Volatility snapshot (20D, 60D, or 252D)
• 🎛️ Fully customizable:
• Show/hide rows and timeframes
• Switch between default or custom benchmarks
• Pick position, size, and colors
Built to answer a simple, everyday question — “How’s this really doing compared to the broader market?”
Thanks to @BeeHolder, whose performance table originally inspired this.
Hope it makes your analysis a little easier and quicker. Indicator

Sector Relative StrengthDescription
This script compares sector performance relative to the S&P 500. Sector price levels or charts alone can mislead, because they tend to move with the broader market. An increase in a sector’s price does not necessarily indicate strength, as it may simply be following the index.
For more a more reliable picture, the script calculates a ratio between each sector ETF and SPY. If the ratio has increased, the sector has outperformed the index. In case it has declined, the sector has underperformed. If the value is near zero, the sector has moved in line with the index. The sectors are presented in a table and sorted on relative performance.
Calculation Method
The performance is expressed as a percentage change in the ratio over a user-defined lookback period. The default lookback is set to 21 bars, which corresponds to one month on a daily chart. This value can be adopted in the settings to match preferred time period.
Z-Score
In addition to the percentage change, the script calculates a Z-score of the ratio, which measures how far the current value deviates from its recent mean. A high positive Z-score indicates that the ratio is significantly above its average, while a negative value indicates it is below. This normalization allows for comparison between sectors with different price levels or volatility profiles.
Table Columns
- Relative %: The sector's performance relative to SPY over the selected lookback period
- Z-Score: Standardized measure of current performance ratio is relative to its average
- Trend Arrow: Indicates the direction of relative performance up down or flat
Example Interpretation
For example, if XLK shows a 3.7% change, it has outperformed SPY over the selected period. Another sector might show a -2.1% change, which indicates underperformance. While both values shows relative strength or weakness, the Z-score is optional and can provide additional context based on how unusual that performance is compared to the sector's own recent behavior.
Use Case
This approach helps evaluate overall market conditions and supports a top-down method. By starting with sector performance, it becomes easier to identify where the market is showing leadership or weakness. This allows the stock selection process to be more deliberate and can help refine or customize screeners based on certain sectors. Indicator

aivance_Multi-Index Performance Comparison# Multi-Index Performance Comparison
This indicator allows traders and investors to easily compare the performance of multiple global market and sector indexes from a user-defined start date. All indexes are normalized to 100% at the specified start date, making relative performance comparisons straightforward.
## Features:
- Customizable start date for performance comparison
- Toggleable global market indexes (S&P 500, MSCI World, DAX, Nasdaq 100, EURO STOXX 50, Japan, Hong Kong)
- Toggleable sector indexes (Materials, Health Care, Financial, Technology, AI & Robotics)
- Clear visualization with distinct colors for each index
- Reference line at 100% for easy benchmark comparison
## How to Use:
1. Set your desired start date for normalizing performance
2. Toggle indexes on/off under the "Inputs" tab
3. Compare relative performance across different markets and sectors
Perfect for identifying relative strength, sector rotation, or global market correlations over your specific timeframe of interest. Indicator

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Automatic comparison of symbols depending on custom listIn the indicator settings, specify a list of tickers and the corresponding symbol for comparison (e.g. TVC:DXY). Each new list must be on a separate line. The line must begin with the symbol for comparison, then an equal sign (=), and then a list of tickers separated by commas (e.g. OANDA:XAUUSD, OANDA:XAGUSD). If the ticker selected in the chart window is not found in any of the lists, then the symbol from the first list, which is specified before the equal sign, will be used as the symbol for comparison. For example:
TVC:DXY = OANDA:XAUUSD, OANDA:XAGUSD
OANDA:BCOUSD = OANDA:SPX500USD
OANDA:SPX500USD = BINANCE:BTCUSDT
***
Автоматическое сравнение символов в зависимости от настраиваемого списка
В настройках индикатора укажите список тикеров и соответствующий символ для сравнения. Каждый новый список должен быть на отдельной строке. В начале строки должен быть указан символ для сравнения (например, TVC:DXY), затем знак равенства (=) и после него список тикеров, разделенных запятыми (например, OANDA:XAUUSD, OANDA:XAGUSD). Если выбранный в окне графика тикер не будет найден ни в одном из списков, то в качестве символа для сравнения ему будет соответствовать символ из первого списка, который указан перед знаком равенства. Например:
TVC:DXY = OANDA:XAUUSD, OANDA:XAGUSD
OANDA:BCOUSD = OANDA:SPX500USD
OANDA:SPX500USD = BINANCE:BTCUSDT Indicator

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Time Based Comparison Tool [TFO]The goal of this indicator is to show how multiple assets are trading relative to their Previous Highs and Lows. Many traders have probably seen charts resembling this that may plot how asset prices are trading as a percent change over time, or something similar.
The key difference with this indicator is that all prices are normalized to reflect how they are trading with respect to the previous range of a user-defined timeframe. Without the normalization process, we would simply be observing some percent change from a given point in time; but this does not provide enough information to describe where price is trading relative to our desired frame of reference.
For example, if the timeframe setting was chosen to be 1 day, the indicator would plot the Previous High (PH) and Previous Low (PL) of the current symbol on the daily timeframe, denoted here by the black lines and labels. Then, the adjusted price of all selected symbols would be shown to visualize how each one is moving with respect its own PH and PL, using the current symbol's PH and PL as reference points.
In the above chart, we can see that CL was trading below its PDL from about 10:00-11:00 am EST, then broke above and retested it at around 11:20 am EST, before trading higher. To verify that this comparison works as intended, we can check to see that CL did in fact retest its PDL at this time before trading higher. Note that we are using the close price for this evaluation.
Since limiting the output to close prices can leave out some vital information, we can change the Plot Type setting from "Close" to "High to Low," which will instead show the range of prices from high to low instead of just the close.
We can expand on this by detecting when PH's and PL's have been raided (traded through), by displaying the text PHR (Previous High Raid) or PLR (Previous Low Raid) next to the symbol's label on the right. In this case below, where we're using the 1 week timeframe, we can observe that NQ1! (purple) traded through the PL level and thus its label (right) is updated to indicate a PLR.
Similarly, YM1! traded through its PH level and was updated to indicate a PHR; and ES1! raided both levels, with its label reflecting just that.
Due to the native limitation of output series in a single pine script, alerts have been consolidated to "Any PHR" or "Any PLR," meaning these alerts would fire if any of the selected symbols raided a PH or PL, respectively. If one wanted to be alerted for just a specific symbol, this could be achieved by deselecting all symbols except that which is desired, then setting an alert and adjusting its title for easier user recognition. Indicator

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Sector relative strength and correlation by KaschkoThis script provides a quick overview of the relative strength and correlation of the symbols in a sector by showing a line chart of the close prices on a percent scale with all symbols starting at zero at the left side of the chart. It allows a great deal of flexibility in the configuration of the sectors and symbols in it. The standard preset sectors cover the most important futures markets and their symbols.
However, up to ten sectors with up to ten symbols each can be freely configured. Each sector is defined by a single line that has the following format:
Sector name:Symbol suffix:List of comma separated symbols
For example, the first predefined sector is defined as follows.
Energies:1!:CL,HO,NG,RB
1. The name of the sector is "Energies"
2. The suffix is "1!", i.e., to each symbol in the list "1!" is appended to get the continous future for the given symbol root. When using stock, forex or other symbols, simply leave the suffix empty.
3. The list of comma separated symbols is "CL,HO,NG,RB", i.e. crude oil, heating oil, natural gas and gasoline. As the suffix is "1!", the actual symbols whose prices are shown are "CL1!","HO1!","NG1!" and "RB1!"
You can choose to use settlement-as-close and back-adjusted contracts. The sector can also be determined automatically ("Auto-select"). In this case, it is determined to which sector the symbol currently displayed in the main chart belongs and the script displays it in the context of the other symbols in the sector.
By selecting a suitable chart time frame and time range, you can quickly determine which symbols in the sector are stronger or weaker and which are more or less strongly correlated.
The following symbols are best suited for a quick trial, as the sectors are preset for these:
CL1!,ES1!,6A1!,6B1!,6c1!,6E1!,6J1!,6M1!,6N1!,6S1!,GC1!,GF1!,HE1!,HG1!,HO1!,LBR1!,LE1!,NG1!,NQ1!,PA1!,PL1!,RB1!,SI1!,YM1!,ZB1!,ZC1!,ZF1!,ZL1!,ZM1!,ZN1!,ZO1!,ZR1!,ZS1!,ZT1!,ZW1!,CC1!,CT1!,DX1!,KC1!,OJ1!,SB1!,RTY1!
You can also use the script to compare any symbols (e.g. different shares) with each other. Preferably use the "Custom" sector for this. Indicator

Easy To Trade indicatorAbstract
This script evaluates how easy for traders to trade.
This script computes the level that the gains were distributed in many trading days.
We can use this indicator to decide the instruments and the time we trade.
Introduction
Why we think the trading markets are boring?
It is because most of the gains were concentrated in a few trading days.
We look for instruments we can buy at support and sell at resistance frequently and repeatedly.
However, it does not happen usually because it is difficult to find sellers sell at support and buyers buy at resistance.
This script is a method to measure if an instrument is difficult to trade.
If most of the gains were concentrated in a few trading days, this script says it is difficult to trade.
If gains were distributed in many trading days and we can buy low and sell high repeatedly, this script says it is easy to trade.
Therefore, this script measure how difficult for us to trade by the ratio between the area of value and the total gain.
How it works
1. Determine the instruments and time frames we are interested in.
2. Determine how many days this script evaluate the result. This number may depend on how many days from you buy in to you sell out.
3. If the instrument you choose is easy to trade, this script reports higher values.
4. If the instrument is long term bullish, the number "easy to invest" is usually higher than the number "easy to short" .
5. We can consider trade instruments which are easier to trade than others.
6. We can consider wait until the period that it is difficult to trade has past or keep believing that some instruments are easier to trade than others.
Parameters
x_src = The price for each trading day this script use. It may be open , high , low , close or their combination.
x_is_exp = Whether this script evaluate the price movement in exponential or logarithm. You are advised to answer yes if the price changes drastically.
x_period = How many days this script evaluate the result.
Conclusion
With this indicator , we have data to explain how easy or difficult an instrument is for traders . In other words , if we hear some people say the trading markets are boring or difficult for traders , we can use this indicator to verify how accurate their comments are.
With this explainable analysis , we have more knowledge about which instruments and which sessions are relative easy for us to buy low and sell high repeatedly and frequently , we can have better proceeding than buy and hold simply. Indicator

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Strength Comparison @joshuuuexample:
if you want to find the stronger/weaker pair between eurusd and gbpusd, what you can do is check the eurgbp charts. if eurgbp is bullish, that means, that longs longs on eurusd are better than on gbpusd.
Unfortunately, there is no such thing to compare for example usoil with ukoil, or us100 with us500.
That's where this indicator comes in handy. You can choose whatever two symbols you want, that are supported by pulsewire and you will get a chart, which shows symbol1/symbol2.
Now you can use normal market structure, or the ema option, to find out the stronger symbol.
This can also help predicting the so called SMT Divergences, taught by ICT.
⚠️ Open Source ⚠️
Coders and TV users are authorized to copy this code base, but a paid distribution is prohibited. A mention to the original author is expected, and appreciated.
⚠️ Terms and Conditions ⚠️
This financial tool is for educational purposes only and not financial advice. Users assume responsibility for decisions made based on the tool's information. Past performance doesn't guarantee future results. By using this tool, users agree to these terms. Indicator

Smoothing R-Squared ComparisonIntroduction
Heyo guys, here I made a comparison between my favorised smoothing algorithms.
I chose the R-Squared value as rating factor to accomplish the comparison.
The indicator is non-repainting.
Description
In technical analysis, traders often use moving averages to smooth out the noise in price data and identify trends. While moving averages are a useful tool, they can also obscure important information about the underlying relationship between the price and the smoothed price.
One way to evaluate this relationship is by calculating the R-squared value, which represents the proportion of the variance in the price that can be explained by the smoothed price in a linear regression model.
This PineScript code implements a smoothing R-squared comparison indicator.
It provides a comparison of different smoothing techniques such as Kalman filter, T3, JMA, EMA, SMA, Super Smoother and some special combinations of them.
The Kalman filter is a mathematical algorithm that uses a series of measurements observed over time, containing statistical noise and other inaccuracies, and produces estimates of unknown variables that tend to be more accurate than those based on a single measurement.
The input parameters for the Kalman filter include the process noise covariance and the measurement noise covariance, which help to adjust the sensitivity of the filter to changes in the input data.
The T3 smoothing technique is a popular method used in technical analysis to remove noise from a signal.
The input parameters for the T3 smoothing method include the length of the window used for smoothing, the type of smoothing used (Normal or New), and the smoothing factor used to adjust the sensitivity to changes in the input data.
The JMA smoothing technique is another popular method used in technical analysis to remove noise from a signal.
The input parameters for the JMA smoothing method include the length of the window used for smoothing, the phase used to shift the input data before applying the smoothing algorithm, and the power used to adjust the sensitivity of the JMA to changes in the input data.
The EMA and SMA techniques are also popular methods used in technical analysis to remove noise from a signal.
The input parameters for the EMA and SMA techniques include the length of the window used for smoothing.
The indicator displays a comparison of the R-squared values for each smoothing technique, which provides an indication of how well the technique is fitting the data.
Higher R-squared values indicate a better fit. By adjusting the input parameters for each smoothing technique, the user can compare the effectiveness of different techniques in removing noise from the input data.
Usage
You can use it to find the best fitting smoothing method for the timeframe you usually use.
Just apply it on your preferred timeframe and look for the highlighted table cell.
Conclusion
It seems like the T3 works best on timeframes under 4H.
There's where I am active, so I will use this one more in the future.
Thank you for checking this out. Enjoy your day and leave me a like or comment. 🧙♂️
---
Credits to:
▪@loxx – T3
▪@balipour – Super Smoother
▪ChatGPT – Wrote 80 % of this article and helped with the research Indicator

Quad RSRelative Strength (RS) is an Indicator which measures a Stock's performance as compared to a Benchmark Index or another Stock.
For example: RS will tell you whether “A” is increasing more or less than “B” in any market condition. It is one of the tools which is best suited for Momentum Investing.
How RS can be used as a Momentum Indicator:
RS is used in identifying both the strongest and the weakest stock, or any asset class, within the market. Usually, the stocks which display strong or weak RS over a given time period tend to continue to move in the same direction.
How to calculate Relative Strength:
Divide change of "A" over some time period by the change of a particular index/stock "B" over the same time period.
This indicator oscillates around zero. If the value is greater than zero, "A" has been relatively strong compared to "B", during the selected period; if the value is less than zero, "A" has been relatively weak.
Configuration & Default settings:
The Relative symbol can be Input, default is Nifty50.
Time frame can be set, I recommend setting to Day. Default time frame is set to same as chart.
Four different periods can be set. Default values are 500, 250, 125 & 63. If time frame is set as 'Day', these numbers correspond to 2 years, 1 year, 1/2 year & 1 quarter.
Example chart: NiftyMidCap100 with Quad RS indicator with Nifty50 used as Relative Symbol, Four periods: 500, 250, 125 & 63
Indicator
