OB EmaCross + BBThis is my setup and the way I like to trade.
It is based in an EMA cross ( 9 x 21) and the Bollinger Bands without the central Moving Average.
I prefer to use the EMA cross in the middle of the bands.
It is also possible to activate "Colored Bars" to paint the candles according to the EMA cross: green if the candles are above both EMAs, white when at least one of them are in between EMAs and red if they are both below EMAs.
My operational works like this:
- Buy when price is above EMAs
- Sell when price is belos EMAs
Of course, I use BB to give me the direction of the trend and I only enter in a trade when the price is in the same trend of the BB.
I avoid trades when the bands are getting narrowed.
I hope you enjoy my indicator and let me know if you have any suggestion! ;)
在脚本中搜索"band"
MTF Fair Value Gap Indicator ULTRAFVG Fair Value Gap Indicator
FVG's commonly known as Fair Value Gaps are mostly in use for forex trading, however it’s been widely used in price action trading, even on regular large cap stocks. Think of it as an imbalance area where the price of the stock may actually be under/over valued due to many orders being injected in a short amount of time, ie . a gap caused by an impulse created by the speed of the price movement. In essence, the FVG can become a kind of magnet drawing the price back to that level to attempt to balance out the orders (when? we don't know). Please do research to understand the concept of FVG's.
You can look for an opportunity as price approaches the FVG for entry either long/short because after all, it is an "Area of Interest" so the price will either bounce or blow through the area. No indicator works 100% of the time so take in context as just another indicator. It tends work on larger time frames best.
IMPORTANT TV RELATED LIMITATIONS: You should take the time to understand the following. A MAXIMUM of 500 boxes and labels are allowed, thus if you elect to display many different time frames of FVGs and/or select to not auto delete old Daily FVGs, the oldest FVGs will be deleted and not be seen. Additionally if you are on a smaller chart time frame (1 min), you may not see older FVGs such as Daily ones that occurred and still exist from long ago. This is due to TV limitation of 20,000 candles of history in each chart timeframe. Example: A 1 minute chart supports approximately 14 days worth of data so looking for Daily FVGs would only go back that far, whereas if your chart was set to 5 minutes you'd be able to see 5 times as many, ie . 60 days worth of Daily FVG's. Obviously setting your chart and looking for Daily FVG's would support up to 20,000 days worth.
The Indicator Provides many different features:
*Creation of FVG's for all hours or just during market hours. Currently you can enable FVG’s for the following timeframes: Current chart timeframe, 5Min, 10Min, 15Min, 1Hr, 4Hr, 8Hr, Daily, Weekly, Monthly.
*Text label displays overlaying FVG bands including creation timestamps.
* Bands reflecting FVG's in action (created/deleted) for the current chart time frame, 15min, 1hr, 4hr, 8hr and daily time frames. The FVG's will be overlayed on the chart if enabled.
*Mitigation Action - Normal - When FVG is balanced out by price action, the FVG will disappear. Dynamic - The FVG band will decrease as the price movement eats into it thus only showing the remaining imbalance. None - For those that wish to retain FVG's even if they were mitigated. Half - FVG’s disappear when the price intrudes 50% of the overall FVG band zone.
*Mitigation Type - The elimination or balancing of the FVG is caused by either the candle wick or body passing completely through the FVG.
*Maximum FVGs - A maximum number of FVGs are created for each different enabled time frame (be aware setting a large number could impact system performance).
*All FVG band colors can be customized by the user.
* All FVG bands auto extend to the right.
* Intrusion Alerts - Trading View alerts are supported. You can use the indicator settings to enable an alert if the price intrudes into the FVG zone by a certain percentage. This is not related to mitigation or removal of the FVG, just a warning that price has reached the area of interest.
DB KCBB%D WavesDB KCBB%D Waves
What does the indicator do?
The indicator plots the percent difference between the low and high prices against a combined Kelpler Channel Bollinger Bands for the current timeframe. The low percent difference and the high percent difference each have their own waves plotted. A mirror mode default allows both waves to be visualized in a mirrored plot that clearly shows when outer bands are present and when they swap. Each percent difference band is displayed with a 1 bar lookback to visualize local tops/bottoms.
The overall trend is displayed using two sets of green/red colors on the percent difference waves so that each wave is recognizable, but the overall price trend is visible. A fast 3 SMA is taken of each percent difference wave to obtain the overall trend and then averaged together. The trend is then calculated based on direction from the previous bar period.
How should this indicator be used?
By default, the indicator will display in a mirror mode which will display both the low and high percent change waves mirrored to allow for the most pattern recognition possible. You will notice the percent difference waves swap from inner to outer, showing the overall market direction for that timeframe. When each percent difference wave interacts with the zero line, it indicates either buys or sells opportunities depending on which band is on the inside. When the inner wave crosses zero, special attention should be paid to the outer wave to know if it's a significant move. Likewise, when the outer wave peaks, it can indicate buy or sell opportunities depending on which wave is on the outside.
A zero line and other lines are displayed from the highest of the high percent difference wave over a long period of time. The lines can measure movement and possible oversold/overbought locations or large volatility. You can also use the lines for crossing points for either wave as alerts to know when to buy or sell zones are happening.
When individual percent difference waves are designed to be reviewed without mirroring, the mirror checkbox can be unchecked in the settings. Doing so will display both the high and low percent difference waves separately. Using this display, you can more cleanly review how each wave interacts with various line levels.
For those who desire to only have half of the mirror or one set of waves inverted against each other, check the "mirrored" and the "mirrored flipped" checkboxes in the settings. Doing so will display the top half of the mirror indicator, which is the low percent difference wave with the high percent difference wave inverted.
The indicator will also change the background color of its own pane to indicate possible buy/sell periods (work in progress).
Does the indicator include any alerts?
Yes, they are a work in progress but starting out with this release, we have:
NOTE: This is an initial release version of this indicator. Please do not use these alerts with bots yet, as they will repaint in real-time.
NOTE: A later release may happen that will delay firing the events until 1/2 of the current bar time has passed.
NOTE: As with any indicator watch your upper timeframe waves first before zooming into lower.
DB KCBB%D Buy Zone Alert
DB KCBB%D MEDIUM Buy Alert
DB KCBB%D STRONG Buy Alert
DB KCBB%D Sell Alert
DB KCBB%D STRONG Sell Alert
DB KCBB%D Trend Up Alert
DB KCBB%D Trend Down Alert
Use at your own risk and do your own diligence.
Enjoy!
Range Bound Channel Index (RBCI) w/ Expanded Source Types [Loxx]Range Bound Channel Index (RBCI) w/ Expanded Source Types is a reversal and trend indicator. This version includes Bollinger bands to show trend exhaustion
What is Range Bound Channel Index (RBCI)?
Range Bound Channel Index (RBCI) is calculated by using a channel (bandwidth) filter (CF). Channel filter simultaneously fulfills two functions: removes low frequent trend formed by low frequent components of the spectrum; removes high frequency noise formed by the high frequent components of the spectrum.
When RBCI approaches its local maximum the prices approach upper border of the trading channel and when RBCI approach its local minimum the prices approach the lower border of the trading corridor.
Included:
-Toggle on/off bar coloring
-Loxx's Expanded Source Types
Bollinger CloudsThis indicator plots Bollinger Bands for your current timeframe (e.g 5 minutes) and also plots the Bollinger Bands for a higher timeframe (15 minutes for 5 minute timeframe). Then the gaps between the current and higher timeframe upper and lower bands is filled to create clouds which can be used as entry zones. Like Bollinger Bands, this indicator shouldn't be solely used for entries, use it in conjunction with other indicators.
Bollinger Band Timeframes
Current / Higher
1 minute / 5 minutes
3 minutes / 10 minutes
5 minutes / 15 minutes
10 minutes / 30 minutes
15 minutes / 1 hour
30 minutes / 2 hours
45 minutes / 1.5 hours
1 hour / 4 hours
2 hours / 8 hours
2.5 hours / 10 hours
4 hours / 1 Day
1 Day / 3 Days
3 Days / 9 Days
5 Days / 2 Weeks
1 Week / 1 Month
Waddah Attar Explosion V3 [NHK] -Bollinger - MACDWaddah Attar Explosion Version3 indicator to work in Forex and Crypto, This indicator oscillates above and below zero and the Bollinger band is plotted over the MACD Histogram to take quick decisions, Colors are changed for enhanced look. dead zone is plotted in a background area and option is provided to hide dead zone. One can easily detect sideways market movement using Bollinger band and volume. when volume is in between Bollinger band no trades are to be taken as volume is low and market moving in sideways
credits to: @shayankm and @LazyBear
Read the main description below...
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
This is a port of a famous MT4 indicator. This indicator uses MACD /BB to track trend direction and strength. Author suggests using this indicator on 30mins.
Explanation from the indicator developer:
"Various components of the indicator are:
Dead Zone Line: Works as a filter for weak signals. Do not trade when the up or down histogram is in between Dead Zone.
Histograms:
- Pink histogram shows the current down trend.
- Blue histogram shows the current up trend.
- Sienna line / Bollinger Band shows the explosion in price up or down.
Signal for ENTER_BUY: All the following conditions must be met.
- Blue histogram is raising.
- Blue histogram above Explosion line.
- Explosion line raising.
- Both Blue histogram and Explosion line above DeadZone line.
Signal for EXIT_BUY: Exit when Blue histogram crosses below Explosion line / Bollinger Band.
Signal for ENTER_SELL: All the following conditions must be met.
- Pink histogram is raising.
- Pink histogram above Explosion line.
- Explosion line raising.
- Both Pink histogram and Explosion line above DeadZone line.
Signal for EXIT_SELL: Exit when Pink histogram crosses below Explosion line.
All of the parameters are configurable via options page. You may have to tune it for your instrument.
fi - 5EMA + BB - 5 emas en un mismo indicador junto con las bandas de bollinguer.
- Opcion de timeframe
- Actualizado a version 5
//Indicador adaptado a medida sobre "4EMA lines EMA Cross @Philacone + Bollinger Bands by Alessiof"
//Todos los méritos para Alessiof, muchas gracias!!!
Correlations P/L Range (in percent)This script shows the inefficiency of the markets.
Comparing two (correlated) symbols, the values above 0 means the main symbol (at the top of the graph)
outperforms the other. A value below 0 means the main symbol underperforms the other.
The band displays different entries until the last candle. Any P/L (of the band range)
is visible in the band. Example: given a band range length of 5, then all last 5 values
are compares with the current value for both symbols. Or in other words:
If symbol A, lets say ETHUSD outperforms, lets say BITCOIN (the main symbol), in the last
5 candles, then we would see all values of the band are negative.
Any question, comment or improvements are welcome.
Trading Toolkit - Comprehensive AnalysisTrading Toolkit – Comprehensive Analysis
A unified trading analysis toolkit with four sections:
📊 Company Info
Fundamentals, market cap, sector, and earnings countdown.
📅 Performance
Date‑range analysis with key metrics.
🎯 Market Sentiment
CNN‑style Fear & Greed Index (7 components) + 150‑SMA positioning.
🛡️ Risk Levels
ATR/MAD‑based stop‑loss and take‑profit calculations.
Key Features
CNN‑style Fear & Greed approximation using:
Momentum: S&P 500 vs 125‑DMA
Price Strength: NYSE 52‑week highs vs lows
Market Breadth: McClellan Volume Summation (Up/Down volume)
Put/Call Ratio: 5‑day average (inverted)
Volatility: VIX vs 50‑DMA (inverted)
Safe‑Haven Demand: 20‑day SPY–IEF return spread
Junk‑Bond Demand: HY vs IG credit spread (inverted)
Normalization: z‑score → percentile (0–100) with ±3 clipping.
CNN‑aligned thresholds:
Extreme Fear: 0–24 | Fear: 25–44 | Neutral: 45–54 | Greed: 55–74 | Extreme Greed: 75+.
Risk tools: ATR & MAD volatility measures with configurable multipliers.
Flexible layout: vertical or side‑by‑side columns.
Data Sources
S&P 500: CBOE:SPX or AMEX:SPY
NYSE: INDEX:HIGN, INDEX:LOWN, USI:UVOL, USI:DVOL
Options: USI:PCC (Total PCR), fallback INDEX:CPCS (Equity PCR)
Volatility: CBOE:VIX
Treasuries: NASDAQ:IEF
Credit Spreads: FRED:BAMLH0A0HYM2, FRED:BAMLC0A0CM
Risk Management
ATR risk bands: 🟢 ≤3%, 🟡 3–6%, ⚪ 6–10%, 🟠 10–15%, 🔴 >15%
MAD‑based stop‑loss and take‑profit calculations.
Author: Daniel Dahan
(AI Generated, Merged & enhanced version with CNN‑style Fear & Greed)
The Vishnu Zone Ver 2 by Dr. Sudhir Khollam## 📜 **The Vishnu Zone — Trade When the Brahma Zone Ends**
**Author:** Dr. Sudhir Khollam (SALSA© Method of Astrology & Market Psychology)
**Category:** Volatility Phase Detection / Bollinger Band Expansion Analysis
---
### 🔶 **Concept Overview**
In the **SALSA© Market Philosophy**, every market phase follows a cosmic rhythm —
* **Brahma Phase** represents *creation and expansion* (high volatility and strong directional movement).
* **Vishnu Phase** represents *maintenance and stability* (where expansion cools down and balanced opportunities appear).
**“The Vishnu Zone”** indicator identifies the exact moments when the **Brahma Phase ends** — signaling that the expansion has completed and the market is likely to enter a more stable, tradable state.
This is a **precision-timing indicator** that helps traders avoid entering at the end of impulsive phases and instead prepare for equilibrium-based trades (mean reversion, range setups, or steady trends).
---
### ⚙️ **How It Works**
The indicator measures **Bollinger Band Width (BBW)** to quantify expansion and contraction in volatility.
1. It calculates the **adaptive expansion threshold** using the average BBW over a rolling lookback period.
2. When the current BBW **drops below** this adaptive threshold **after being above it**, the script marks it as the **end of the Brahma Phase**.
3. This moment is shown visually as:
* 🕉 **“Vishnu” label** above the candle
* A **horizontal dotted line** extending for several bars
Together, these mark a **Vishnu Zone**, where the market transitions from expansion to consolidation — an ideal time for stabilization or entry planning.
---
### 📊 **Inputs & Settings**
| Parameter | Description |
| ---------------------------------- | ------------------------------------------------------------------------------ |
| **Bollinger Band Length** | The number of bars used for SMA and standard deviation (default 20). |
| **Bollinger Multiplier** | Determines the width of Bollinger Bands (default 2.0). |
| **Adaptive Lookback Period** | Rolling window to calculate the mean BBW for dynamic adjustment (default 150). |
| **Expansion Multiplier** | Multiplies the mean BBW to define the expansion threshold (default 1.35). |
| **Horizontal Line Extension Bars** | Number of bars to extend the Vishnu Zone line into the future (default 40). |
| **Show End-of-Brahma Labels?** | Toggle 🕉 labels on/off. |
| **Show Horizontal Lines?** | Toggle Vishnu Zone lines on/off. |
---
### 🔔 **Alerts**
When the **Brahma Phase ends**, the indicator triggers an alert:
> *“Brahma Phase Ends, Vishnu has taken over.”*
This helps traders receive real-time notification of volatility contraction and possible entry zones.
---
### 🧠 **Best Practices**
* Works effectively on **5-minute to 1-hour timeframes** for intraday trading.
* Best paired with **momentum or volume filters** to confirm trend exhaustion.
* Avoid entering during rapid expansion (Brahma phase). Wait for a Vishnu signal to ensure market stabilization.
---
### 🌌 **Philosophical Interpretation (SALSA© Principle)**
Just as Vishnu sustains the universe after Brahma’s creation, the market too enters a **maintenance phase** after every burst of expansion.
Recognizing this shift allows traders to align with **cosmic rhythm and price psychology**, not just technical metrics.
---
### 🧩 **Summary**
✅ Detects when expansion volatility ends
✅ Marks transition zones between impulsive and stable phases
✅ Sends real-time alerts
✅ Adaptive and self-adjusting across markets and assets
✅ Simple, clean visualization — ideal for disciplined trading
---
### ⚡ **Use Case**
Perfect for traders who:
* Prefer **low-risk entries** after volatility spikes
* Trade **mean reversion**, **range breakouts**, or **volatility collapses**
* Believe in the **cyclic nature of market energy**
---
Squeeze Momentum MACDSqueeze Momentum MACD
🧠 Description
Squeeze Momentum MACD combines the concept of market volatility compression (the “squeeze”) from Bollinger Bands (BB) and Keltner Channels (KC) with a MACD-style momentum oscillator to reveal potential breakout phases.
The indicator first calculates:
BB Width = Upper Band − Lower Band
KC Width = Upper Band − Lower Band
Then it computes their difference:
Δ = BB Width − KC Width
When Δ > 0 → BB width is greater than KC width → volatility is expanding → potential momentum breakout.
When Δ < 0 → BB is inside KC → volatility is compressing → potential squeeze phase before expansion.
This Δ value is then processed through a MACD-style calculation:
MACD Line = EMA(fast) − EMA(slow)
Signal Line = EMA(MACD, signal length)
Histogram = MACD − Signal
The result is a visual momentum oscillator that behaves like MACD but measures volatility expansion instead of price direction.
🔹 Features:
Dynamic 4-color MACD & Signal lines (positive/negative + rising/falling)
Optional display of raw BB & KC widths
Fully adjustable parameters for BB, KC, and MACD
Works on all timeframes and instruments
🔹 Ideal For:
Detecting market squeezes and breakout momentum
Timing entries before volatility expansion
Integrating volatility and momentum into a single framework
Market Pressure Differential (MPD) [SharpStrat]Market Pressure Differential (MPD)
Concept & Purpose
The Market Pressure Differential (MPD) is a proprietary indicator designed to measure the internal balance of buying and selling pressure directly on the price chart.
Unlike standard momentum or trend indicators, MPD analyzes the structural behavior of each candle—its body, wicks, and overall range—to determine whether the market is dominated by expansion (buying aggression) or contraction (selling absorption).
This indicator provides a visual overlay of market pressure that adapts dynamically to volatility, helping traders see real-time shifts in participation intensity without using oscillators.
In simple terms:
When MPD expands upward → buyer pressure dominates.
When MPD contracts downward → seller pressure dominates.
Calculation Overview
MPD uses a structural candle formula to compute directional pressure:
Body Ratio = (Close − Open) / (High − Low)
Wick Differential = (Lower Wick − Upper Wick) / (High − Low)
Raw Pressure = (Body Ratio × Body Weight) + (Wick Differential × Wick Weight)
Then it applies:
EMA smoothing (to stabilize short-term noise)
Standard deviation normalization (to maintain consistent scaling)
ATR projection (to adapt the signal visually to volatility)
This produces the MPD projection line and the pressure ribbon, drawn directly on the main chart.
Customizable Inputs
Users can adjust color schemes, EMA smoothing length, ATR parameters, normalization length, and body/wick weighting to adapt the indicator’s sensitivity and aesthetic to different markets or chart themes.
How to Use
The Market Pressure Differential (MPD) visualizes the real-time balance between buying and selling pressure. It should be used as a contextual bias tool, not a standalone signal generator.
The white line represents the MPD projection, showing how market pressure evolves in real time based on candle structure and volatility.
The red line represents the ATR envelope, which defines the market’s expected volatility range.
MPD reacts quickly to candle structure, so trend bias is based on how its projection behaves relative to the ATR envelope:
Above the ATR band → positive pressure and bullish bias.
Below the ATR band → negative pressure and bearish bias.
Hovering near the ATR band → neutral or indecisive conditions.
The MPD percentage in the label represents the normalized strength of pressure relative to recent volatility.
Positive % = buying dominance.
Negative % = selling dominance.
Higher absolute values = stronger momentum compared to volatility.
To trade with MPD:
Watch candle colors and the projection line — green or positive % shows buyer control, red or negative % shows seller control.
Note transitions above or below the ATR level for early signs of momentum shifts.
Combine MPD signals with price structure, key levels, or volume for confirmation.
This helps reveal which side controls the market and whether that pressure is strong enough to overcome typical volatility.
Disclaimer
It introduces a novel structural–pressure approach to visualizing market dynamics.
For educational and analytical purposes only; this does not constitute financial advice.
Fisher Transform Trend Navigator [QuantAlgo]🟢 Overview
The Fisher Transform Trend Navigator applies a logarithmic transformation to normalize price data into a Gaussian distribution, then combines this with volatility-adaptive thresholds to create a trend detection system. This mathematical approach helps traders identify high-probability trend changes and reversal points while filtering market noise in the ever-changing volatility conditions.
🟢 How It Works
The indicator's foundation begins with price normalization, where recent price action is scaled to a bounded range between -1 and +1:
highestHigh = ta.highest(priceSource, fisherPeriod)
lowestLow = ta.lowest(priceSource, fisherPeriod)
value1 = highestHigh != lowestLow ? 2 * (priceSource - lowestLow) / (highestHigh - lowestLow) - 1 : 0
value1 := math.max(-0.999, math.min(0.999, value1))
This normalized value then passes through the Fisher Transform calculation, which applies a logarithmic function to convert the data into a Gaussian normal distribution that naturally amplifies price extremes and turning points:
fisherTransform = 0.5 * math.log((1 + value1) / (1 - value1))
smoothedFisher = ta.ema(fisherTransform, fisherSmoothing)
The smoothed Fisher signal is then integrated with an exponential moving average to create a hybrid trend line that balances statistical precision with price-following behavior:
baseTrend = ta.ema(close, basePeriod)
fisherAdjustment = smoothedFisher * fisherSensitivity * close
fisherTrend = baseTrend + fisherAdjustment
To filter out false signals and adapt to market conditions, the system calculates dynamic threshold bands using volatility measurements:
dynamicRange = ta.atr(volatilityPeriod)
threshold = dynamicRange * volatilityMultiplier
upperThreshold = fisherTrend + threshold
lowerThreshold = fisherTrend - threshold
When price momentum pushes through these thresholds, the trend line locks onto the new level and maintains direction until the opposite threshold is breached:
if upperThreshold < trendLine
trendLine := upperThreshold
if lowerThreshold > trendLine
trendLine := lowerThreshold
🟢 Signal Interpretation
Bullish Candles (Green): indicate normalized price distribution favoring bulls with sustained buying momentum = Long/Buy opportunities
Bearish Candles (Red): indicate normalized price distribution favoring bears with sustained selling pressure = Short/Sell opportunities
Upper Band Zone: Area above middle level indicating statistically elevated trend strength with potential overbought conditions approaching mean reversion zones
Lower Band Zone: Area below middle level indicating statistically depressed trend strength with potential oversold conditions approaching mean reversion zones
Built-in Alert System: Automated notifications trigger when bullish or bearish states change, allowing you to act on significant developments without constantly monitoring the charts
Candle Coloring: Optional feature applies trend colors to price bars for visual consistency and clarity
Configuration Presets: Three parameter sets available - Default (balanced settings), Scalping (faster response with higher sensitivity), and Swing Trading (slower response with enhanced smoothing)
Color Customization: Four color schemes including Classic, Aqua, Cosmic, and Custom options for personalized chart aesthetics
Regression Channel (ShareScope-style, parallel)What it does
Replicates ShareScope’s Trend of displayed data look: a single straight linear-regression line (dashed) across a chosen window with parallel, constant-width bands above and below, plus optional shading.
Use it to see the overall trend gradient for a period and a statistically sized channel based on the fit’s residual error.
How it works (math, short)
Computes an OLS regression once over the analysis window.
Residual standard error s is derived from SSE and degrees of freedom (n−2).
Band half-width is constant across the window:
Mean CI (narrower): half = z * s / √n
Prediction (wider): half = z * s * √(1 + 1/n)
Three straight, parallel lines are drawn from the regression endpoints; midline is dashed.
This is intentionally not a tapered CI (which widens at the ends). It matches the visual behaviour of ShareScope’s shaded trend line channel.
Inputs
Source – Price series (Close, High, Low, HL2, etc.).
Use last N bars / N (bars) – Rolling window length.
From / To (date mode) – Alternative fixed date window.
Confidence (%) – 90 / 95 / 99 / Custom (uses z≈t).
Custom Z (t) – Override the quantile if desired.
Prediction bands – Use wider prediction envelope instead of mean CI.
Shade region + colors / opacity / line width.
Usage
To mimic ShareScope exactly, pick the same date span (use date mode) and set Confidence 99%.
Choose Prediction OFF for a tighter “confidence” look; ON for a wider, more permissive channel.
If ShareScope used High as source, set Source = High here as well.
Notes & limitations
TradingView does not expose the visible viewport to Pine. The script cannot auto-read “displayed data.” Use last N bars or date range.
Bands are parallel by design. Prices may close outside; the channel does not bend.
Window capped at 5,000 bars for performance. No alerts are emitted.
Differences vs TV’s native tools
Linear Regression (drawing) – manual object; no statistical sizing or shading.
Linear Regression Channel (indicator) – uses price standard deviations around the regression; width is a user stdev multiple.
This script – uses residual error of the OLS fit and a z/t quantile to size a statistically meaningful parallel channel.
Changelog
r3.1 – Guard fix (no return at top level), minor refactor, stable line updates.
r3 – Switched to single-fit OLS with parallel constant-width bands (ShareScope look).
(Earlier experimental builds r1–r2.2 implemented rolling/tapered CI; superseded.)
Disclaimer: Educational use only. Not investment advice.
PSAR+EMA+Hull+BBDescription
This all-in-one indicator combines four proven tools:
Parabolic SAR (Everget) — trend direction and potential reversals.
Exponential Moving Averages (20/50/100/200) — customizable lengths, colors, and offsets.
Hull Suite (InSilico) — smooth trend detection with multiple variations (HMA, THMA, EHMA).
Bollinger Bands — volatility and dynamic support/resistance.
Features
Toggle each module on/off in settings.
Fully configurable inputs (lengths, colors, offsets, multipliers).
Optional PSAR labels, highlights, and state fill.
Hull can color candles, draw band fills, and pull from higher timeframes.
Bollinger Bands include multiple basis types, stdev multipliers, and fill transparency.
Built-in alerts: PSAR direction change, Hull trending up/down.
Category
Trend Analysis (with Volatility as secondary).
Bollinger Adaptive Trend Navigator [QuantAlgo]🟢 Overview
The Bollinger Adaptive Trend Navigator synthesizes volatility channel analysis with variable smoothing mechanics to generate trend identification signals. It uses price positioning within Bollinger Band structures to modify moving average responsiveness, while incorporating ATR calculations to establish trend line boundaries that constrain movement during volatile periods. The adaptive nature makes this indicator particularly valuable for traders and investors working across various asset classes including stocks, forex, commodities, and cryptocurrencies, with effectiveness spanning multiple timeframes from intraday scalping to longer-term position analysis.
🟢 How It Works
The core mechanism calculates price position within Bollinger Bands and uses this positioning to create an adaptive smoothing factor:
bbPosition = bbUpper != bbLower ? (source - bbLower) / (bbUpper - bbLower) : 0.5
adaptiveFactor = (bbPosition - 0.5) * 2 * adaptiveMultiplier * bandWidthRatio
alpha = math.max(0.01, math.min(0.5, 2.0 / (bbPeriod + 1) * (1 + math.abs(adaptiveFactor))))
This adaptive coefficient drives an exponential moving average that responds more aggressively when price approaches Bollinger Band extremes:
var float adaptiveTrend = source
adaptiveTrend := alpha * source + (1 - alpha) * nz(adaptiveTrend , source)
finalTrend = 0.7 * adaptiveTrend + 0.3 * smoothedCenter
ATR-based volatility boundaries constrain the final trend line to prevent excessive movement during volatile periods:
volatility = ta.atr(volatilityPeriod)
upperBound = bollingerTrendValue + (volatility * volatilityMultiplier)
lowerBound = bollingerTrendValue - (volatility * volatilityMultiplier)
The trend line direction determines bullish or bearish states through simple slope comparison, with the final output displaying color-coded signals based on the synthesis of Bollinger positioning, adaptive smoothing, and volatility constraints (green = long/buy, red = short/sell).
🟢 Signal Interpretation
Rising Trend Line (Green): Indicates upward direction based on Bollinger positioning and adaptive smoothing = Potential long/buy opportunity
Falling Trend Line (Red): Indicates downward direction based on Bollinger positioning and adaptive smoothing = Potential short/sell opportunity
Built-in Alert System: Automated notifications trigger when bullish or bearish states change, allowing you to act on significant development without constantly monitoring the charts
Candle Coloring: Optional feature applies trend colors to price bars for visual consistency
Configuration Presets: Three parameter sets available - Default (standard settings), Scalping (faster response), and Swing Trading (slower response)
RSI Crossover AlertRSI Crossover Alert Indicator - User Guide
The RSI Crossover Alert Indicator is a comprehensive technical analysis tool that detects multiple types of RSI crossovers and generates real-time alerts. It combines traditional RSI analysis with signal lines, divergence detection, and multi-level crossing alerts.
1. Multiple Crossover Detection
- RSI/Signal Line Cross: Signals a primary trend change.
- RSI/Second Signal Cross: Confirmation signals for stronger trends.
- Level Crossings: Crosses of Overbought 70, Oversold 30, and Midline 50.
- Divergence Detection: Hidden and regular divergences for reversal signals.
2. Alert Types
- Alert: RSI > Signal
Description: Bullish momentum is building.
Signal: Consider long positions.
- Alert: RSI < Signal
Description: Bearish momentum is building.
Signal: Consider short positions.
- Alert: RSI > 70
Description: Entering the overbought zone.
Signal: Prepare for a potential reversal.
- Alert: RSI < 30
Description: Entering the oversold zone.
Signal: Watch for a bounce opportunity.
- Alert: RSI crosses 50
Description: A shift in momentum.
Signal: Trend confirmation.
3. Visual Components
- Lines: RSI blue, Signal orange, Second Signal purple
- Histogram: Visualizes momentum by showing the difference between RSI and the Signal line.
- Background Zones: Red overbought, Green oversold
- Markers: Up/down triangles to indicate crossovers.
- Info Table: Real-time RSI values and status.
Strategy 1: Classic Crossover
- Entry Long: RSI crosses above the Signal Line AND RSI is below 50.
- Entry Short: RSI crosses below the Signal Line AND RSI is above 50.
- Take Profit: On the opposite signal.
- Stop Loss: At the recent swing high/low.
Strategy 2: Extreme Zone Reversal
- Entry Long: RSI is below 30 and crosses above the Signal Line.
- Entry Short: RSI is above 70 and crosses below the Signal Line.
- Risk Management: Higher win rate but fewer signals. Use a minimum 2:1 risk-reward ratio.
Strategy 3: Divergence Trading
- Setup: Enable divergence alerts and look for price/RSI divergence. Wait for an RSI crossover for confirmation.
- Entry: Enter on the crossover after the divergence appears. Place the stop loss beyond the starting point of the divergence.
Strategy 4: Multi-Timeframe Confirmation
1. Check the higher timeframe e.g. Daily to identify the main trend.
2. Use the current timeframe e.g. 4H/1H for your entry.
3. Only enter in the direction of the main trend.
4. Use the RSI crossover as the entry trigger.
Optimal Settings by Market
- Forex Major Pairs
RSI Length: 14, Signal Length: 9, Overbought/Oversold: 70/30
- Crypto High Volatility
RSI Length: 10-12, Signal Length: 6-8, Overbought/Oversold: 75/25
- Stocks Trending
RSI Length: 14-21, Signal Length: 9-12, Overbought/Oversold: 70/30
- Commodities
RSI Length: 14, Signal Length: 9, Overbought/Oversold: 80/20
Risk Management Rules
1. Position Sizing: Never risk more than 1-2% on a single trade. Reduce size in ranging markets.
2. Stop Loss Placement: Place stops beyond the recent swing high/low for crossovers. Using an ATR-based stop is also effective.
3. Profit Taking: Take partial profits at a 1:1 risk-reward ratio. Switch to a trailing stop after reaching 2:1.
1. Filtering Signals
- Combine with volume indicators.
- Confirm the trend on a higher timeframe.
- Wait for candlestick pattern confirmation.
2. Avoid Common Mistakes
- Don't trade every single crossover.
- Avoid taking signals against a strong trend.
- Do not ignore risk management.
3. Market Conditions
- Trending Market: Focus on midline 50 crosses.
- Ranging Market: Look for reversals from overbought/oversold levels.
- Volatile Market: Widen the overbought/oversold levels.
- If you get too many false signals:
Increase the signal line period, add other confirmation indicators, or use a higher timeframe.
- If you are missing major moves:
Decrease the RSI length, shorten the signal line period, or check your alert settings.
Recommended Combinations
1. RSI + MACD: For dual momentum confirmation.
2. RSI + Bollinger Bands: For volatility-adjusted signals.
3. RSI + Volume: To confirm the strength of a signal.
4. RSI + Moving Averages: To use as a trend filter.
This indicator provides a comprehensive RSI analysis. Success depends on proper configuration, risk management, and combining signals with the overall market context. Start with the default settings, then optimize based on your trading style and market conditions.
4H Bollinger Breakout StrategyThis strategy leverages Bollinger Bands on the 4-hour timeframe for long and short trades in trending or ranging markets. Entries trigger on BB breakouts with optional filters for volume, trend, and RSI. Exits occur on opposite BB crosses. Customizable for long-only, short-only, or indicator mode via code comments. Supports forex, stocks, or crypto with full equity allocation and 0.1% commission.
Length (Default: 20): Period for BB basis and std dev; shorter for sensitivity, longer for smoothing.
Basis MA Type (Default: SMA): Selects MA for middle band (SMA, EMA, etc.); EMA for faster response.
Source (Default: Close): Price input for calculations; use close for standard accuracy.
StdDev Multiplier (Default: 1.8): Band width control; higher for fewer signals, lower for more.
Offset (Default: 0): Shifts BB plots; typically unchanged.
Use Filters (Default: True): Applies volume, trend, RSI checks to filter signals.
Volume MA Length (Default: 20): For volume filter (long: >105% avg, short: >120%).
Trend MA Length (Default: 80): SMA for trend filter (long: above MA, short: below).
RSI Length (Default: 14): For short filter (entry if RSI <85).
Use Long/Short Signals (Defaults: True): Toggles directions; long entry on lower BB crossover, short on upper crossunder.
Visuals: BB plots (blue basis, red upper, green lower), orange trend MA, filled background.
Labels/Alerts: Green/red for long entry/exit, yellow/purple for short; alert conditions included.
Volatility-Adjusted Momentum Score (VAMS) [QuantAlgo]🟢 Overview
The Volatility-Adjusted Momentum Score (VAMS) measures price momentum relative to current volatility conditions, creating a normalized indicator that identifies significant directional moves while filtering out market noise. It divides annualized momentum by annualized volatility to produce scores that remain comparable across different market environments and asset classes.
The indicator displays a smoothed VAMS Z-Score line with adaptive standard deviation bands and an information table showing real-time metrics. This dual-purpose design enables traders and investors to identify strong trend continuation signals when momentum persistently exceeds normal levels, while also spotting potential mean reversion opportunities when readings reach statistical extremes.
🟢 How It Works
The indicator calculates annualized momentum using a simple moving average of logarithmic returns over a specified period, then measures annualized volatility through the standard deviation of those same returns over a longer timeframe. The raw VAMS score divides momentum by volatility, creating a risk-adjusted measure where high volatility reduces scores and low volatility amplifies them.
This raw VAMS value undergoes Z-Score normalization using rolling statistical parameters, converting absolute readings into standardized deviations that show how current conditions compare to recent history. The normalized Z-Score receives exponential moving average smoothing to create the final VAMS line, reducing false signals while preserving sensitivity to meaningful momentum changes.
The visualization includes dynamically calculated standard deviation bands that adjust to recent VAMS behavior, creating statistical reference zones. The information table provides real-time numerical values for VAMS Z-Score, underlying momentum percentages, and current volatility readings with trend indicators.
🟢 How to Use
1. VAMS Z-Score Bands and Signal Interpretation
Above Mean Line: Momentum exceeds historical averages adjusted for volatility, indicating bullish conditions suitable for trend following
Below Mean Line: Momentum falls below statistical norms, suggesting bearish conditions or downward pressure
Mean Line Crossovers: Primary transition signals between bullish and bearish momentum regimes
1 Standard Deviation Breaks: Strong momentum conditions indicating statistically significant directional moves worth following
2 Standard Deviation Extremes: Rare momentum readings that often signal either powerful breakouts or exhaustion points
2. Information Table and Market Context
Z-Score Values: Current VAMS reading displayed in standard deviations (σ), showing how far momentum deviates from its statistical norm
Momentum Percentage: Underlying annualized momentum displayed as percentage return, quantifying the directional strength
Volatility Context: Current annualized volatility levels help interpret whether VAMS readings occur in high or low volatility environments
Trend Indicators: Directional arrows and change values provide immediate feedback on momentum shifts and market transitions
3. Strategy Applications and Alert System
Trend Following: Use sustained readings beyond the mean line and 1σ band penetrations for directional trades, especially when VAMS maintains position in upper or lower statistical zones
Mean Reversion: Focus on 2σ extreme readings for contrarian opportunities, particularly effective in sideways markets where momentum tends to revert to statistical norms
Alert Notifications: Built-in alerts for mean crossovers (regime changes), 1σ breaks (strong signals), and 2σ touches (extreme conditions) help monitor multiple instruments for both continuation and reversal setups
Euclidean Range [InvestorUnknown]The Euclidean Range indicator visualizes price deviation from a moving average using a geometric concept Euclidean distance. It helps traders identify trend strength, volatility shifts, and potential overextensions in price behavior.
Euclidean Distance
Euclidean distance is a fundamental concept in geometry and machine learning. It measures the "straight-line distance" between two points in space. In time series analysis, it can be used to measure how far one sequence deviates from another over a fixed window.
euclidean_distance(src, ref, len) =>
var float sum_sq_diff = na
sum_sq_diff := 0.0
for i = 0 to len - 1
diff = src - ref
sum_sq_diff += diff * diff
math.sqrt(sum_sq_diff)
In this script, we calculate the Euclidean distance between the price (source) and a smoothed average (reference) over a user-defined window. This gives us a single scalar that reflects the overall divergence between price and trend.
How It Works
Moving Average Calculation: You can choose between SMA, EMA, or HMA as your reference line. This becomes the "baseline" against which the actual price is compared.
Distance Band Construction: The Euclidean distance between the price and the reference is calculated over the Window Length. This value is then added to and subtracted from the average to form dynamic upper and lower bands, visually framing the range of deviation.
Distance Ratios and Z-Scores: Two distance ratios are computed: dist_r = distance / price (sensitivity to volatility); dist_v = price / distance (sensitivity to compression or low-volatility states)
Both ratios are normalized using a Z-score to standardize their behavior and allow for easier interpretation across different assets and timeframes.
Z-Score Plots: Z_r (white line) highlights instances of high volatility or strong price deviation; Z_v (red line) highlights low volatility or compressed price ranges.
Background Highlighting (Optional): When Z_v is dominant and increasing, the background is colored using a gradient. This signals a possible build-up in low volatility, which may precede a breakout.
Use Cases
Detect volatile expansions and calm compression zones.
Identify mean reversion setups when price returns to the average.
Anticipate breakout conditions by observing rising Z_v values.
Use dynamic distance bands as adaptive support/resistance zones.
Notes
The indicator is best used with liquid assets and medium-to-long windows.
Background coloring helps visually filter for squeeze setups.
Disclaimer
This indicator is provided for speculative analysis and educational purposes only. It is not financial advice. Always backtest and evaluate in a simulated environment before live trading.
Commodity Trend Reactor [BigBeluga]
🔵 OVERVIEW
A dynamic trend-following oscillator built around the classic CCI, enhanced with intelligent price tracking and reversal signals.
Commodity Trend Reactor extends the traditional Commodity Channel Index (CCI) by integrating trend-trailing logic and reactive reversal markers. It visualizes trend direction using a trailing stop system and highlights potential exhaustion zones when CCI exceeds extreme thresholds. This dual-level system makes it ideal for both trend confirmation and mean-reversion alerts.
🔵 CONCEPTS
Based on the CCI (Commodity Channel Index) oscillator, which measures deviation from the average price.
Trend bias is determined by whether CCI is above or below user-defined thresholds.
Trailing price bands are used to lock in trend direction visually on the main chart.
Extreme values beyond ±200 are treated as potential reversal zones.
🔵 FEATURES\
CCI-Based Trend Shifts:
Triggers a bullish bias when CCI crosses above the upper threshold, and bearish when it crosses below the lower threshold.
Adaptive Trailing Stops:
In bullish mode, a trailing stop tracks the lowest price; in bearish mode, it tracks the highest.
Top & Bottom Markers:
When CCI surpasses +200 or drops below -200, it plots colored squares both on the oscillator and on price, marking potential reversal zones.
Background Highlights:
Each time a trend shift occurs, the background is softly colored (lime for bullish, orange for bearish) to highlight the change.
🔵 HOW TO USE
Use the oscillator to monitor when CCI crosses above or below threshold values to detect trend activation.
Enter trades in the direction of the trailing band once the trend bias is confirmed.
Watch for +200 and -200 square markers as warnings of potential mean reversals.
Use trailing stop areas as dynamic support/resistance to manage stop loss and exit strategies.
The background color changes offer clean confirmation of trend transitions on chart.
🔵 CONCLUSION
Commodity Trend Reactor transforms the simple CCI into a complete trend-reactive framework. With real-time trailing logic and clear reversal alerts, it serves both momentum traders and contrarian scalpers alike. Whether you’re trading breakouts or anticipating mean reversions, this indicator provides clarity and structure to your decision-making.
2-Day Volume Weighted Average Price (VWAP)This indicator extends TradingView’s built-in VWAP by calculating a volume-weighted average price over a continuous two-day window (yesterday + today), anchoring VWAP at the start of yesterday’s session and carrying it through to today’s close, but only plotting the segment that falls within the current trading session—yesterday’s data feeds into the calculation to ensure today’s VWAP reflects the prior session’s volume and price action, while the line drawn on your chart always begins at today’s session open.
Standard Deviation Bands: Optional ±1σ, ±2σ, and ±3σ envelopes, exactly as in the default VWAP, but based on the rolling two-day data.
Range Filter Strategy with ATR TP/SLHow This Strategy Works:
Range Filter:
Calculates a smoothed average (SMA) of price
Creates upper and lower bands based on standard deviation
When price crosses above upper band, it signals a potential uptrend
When price crosses below lower band, it signals a potential downtrend
ATR-Based Risk Management:
Uses Average True Range (ATR) to set dynamic take profit and stop loss levels
Take profit is set at entry price + (ATR × multiplier) for long positions
Stop loss is set at entry price - (ATR × multiplier) for long positions
The opposite applies for short positions
Input Parameters:
Adjustable range filter length and multiplier
Customizable ATR length and TP/SL multipliers
All parameters can be optimized in TradingView's strategy tester
You can adjust the input parameters to fit your trading style and the specific market you're trading. The ATR-based exits help adapt to current market volatility.
