Gann Support and Resistance LevelsThis indicator plots dynamic Gann Degree Levels as potential support and resistance zones around the current market price. You can fully customize the Gann degree step (e.g., 45°, 30°, 90°), the number of levels above and below the price, and the price movement per degree to fine-tune the levels to your strategy.
Key Features:
✅ Dynamic levels update automatically with the live price
✅ Adjustable degree intervals (Gann steps)
✅ User control over how many levels to display above and below
✅ Fully customizable label size, label color, and text color for mobile-friendly visibility
✅ Clean visual design for easy chart analysis
How to Use:
Gann levels can act as potential support and resistance zones.
Watch for price reactions at major degrees like 0°, 90°, 180°, and 270°.
Can be combined with other technical tools like price action, trendlines, or Gann fans for deeper analysis.
📌 This tool is perfect for traders using Gann theory, grid-based strategies, or those looking to enhance their visual trading setups with structured levels.
Cari dalam skrip untuk "TRENDLINES"
Cumulative Volume Delta📊 Indicator Name:
Cumulative Volume Delta (CVD) + Candle Divergence (Color DIfference)
📌 Purpose:
This indicator visualizes volume delta over a user-defined time anchor and highlights divergence between volume-based momentum and price movement. It's especially useful for identifying potential reversals, fakeouts, or hidden buying/selling pressure.
🔍 How It Works:
1. Volume Delta Calculation (CVD Candles):
The script uses ta.requestVolumeDelta() to approximate volume delta data over a chosen anchor period (e.g., 1D).
Volume delta = Buy Volume – Sell Volume
Each candle on the CVD chart represents changes in cumulative volume delta, with OHLC-style values:
openVolume: cumulative delta at the start of the bar
lastVolume: cumulative delta at the end of the bar
maxVolume, minVolume: intra-bar high and low
2. Visual Representation (CVD Candles):
Green/Teal candle: Delta is increasing (buying pressure dominates)
Red candle: Delta is decreasing (selling pressure dominates)
3. Divergence Detection:
The script compares the direction of the price candle with the direction of the CVD candle:
Price Up + CVD Down → Possible hidden selling (bearish divergence)
Price Down + CVD Up → Possible hidden buying (bullish divergence)
4. Color Highlighting:
Orange candle on the CVD chart signals divergence between price and volume delta.
This color override helps you quickly spot potential discrepancies between price movement and underlying volume pressure.
5. Alerting:
An alertcondition is added so you can receive a notification whenever a divergence occurs.
⚙️ User Inputs:
Anchor period (e.g., 1D): Timeframe over which the CVD is anchored.
Use custom timeframe: Allows you to override and define the internal lower timeframe used for volume estimation (e.g., 1-min).
📈 How to Use It:
✅ Bullish Divergence (Price down, CVD up)
This may indicate:
Buyers absorbing selling pressure.
A potential reversal to the upside.
Hidden accumulation.
🚫 Bearish Divergence (Price up, CVD down)
This may indicate:
Sellers stepping in despite upward price.
A potential reversal to the downside.
Hidden distribution.
🧠 Trading Insights:
CVD is often used by order flow traders or those analyzing market depth and volume imbalances.
This version lets you visually align price action with underlying volume, improving decision-making.
The divergence signal can be combined with other technical tools like support/resistance, candlestick patterns, or trendlines for confirmation.
Demand Index (Hybrid Sibbet) by TradeQUODemand Index (Hybrid Sibbet) by TradeQUO \
\Overview\
The Demand Index (DI) was introduced by James Sibbet in the early 1990s to gauge “real” buying versus selling pressure by combining price‐change information with volume intensity. Unlike pure price‐based oscillators (e.g. RSI or MACD), the DI highlights moves backed by above‐average volume—helping traders distinguish genuine demand/supply from false breakouts or low‐liquidity noise.
\Calculation\
\
\ \Step 1: Weighted Price (P)\
For each bar t, compute a weighted price:
```
Pₜ = Hₜ + Lₜ + 2·Cₜ
```
where Hₜ=High, Lₜ=Low, Cₜ=Close of bar t.
Also compute Pₜ₋₁ for the prior bar.
\ \Step 2: Raw Range (R)\
Calculate the two‐bar range:
```
Rₜ = max(Hₜ, Hₜ₋₁) – min(Lₜ, Lₜ₋₁)
```
This Rₜ is used indirectly in the exponential dampener below.
\ \Step 3: Normalize Volume (VolNorm)\
Compute an EMA of volume over n₁ bars (e.g. n₁=13):
```
EMA_Volₜ = EMA(Volume, n₁)ₜ
```
Then
```
VolNormₜ = Volumeₜ / EMA_Volₜ
```
If EMA\_Volₜ ≈ 0, set VolNormₜ to a small default (e.g. 0.0001) to avoid division‐by‐zero.
\ \Step 4: BuyPower vs. SellPower\
Calculate “raw” BuyPowerₜ and SellPowerₜ depending on whether Pₜ > Pₜ₋₁ (bullish) or Pₜ < Pₜ₋₁ (bearish). Use an exponential dampener factor Dₜ to moderate extreme moves when true range is small. Specifically:
• If Pₜ > Pₜ₋₁,
```
BuyPowerₜ = (VolNormₜ) / exp
```
otherwise
```
BuyPowerₜ = VolNormₜ.
```
• If Pₜ < Pₜ₋₁,
```
SellPowerₜ = (VolNormₜ) / exp
```
otherwise
```
SellPowerₜ = VolNormₜ.
```
Here, H₀ and L₀ are the very first bar’s High/Low—used to calibrate the scale of the dampening. If the denominator of the exponential is near zero, substitute a small epsilon (e.g. 1e-10).
\ \Step 5: Smooth Buy/Sell Power\
Apply a short EMA (n₂ bars, typically n₂=2) to each:
```
EMA_Buyₜ = EMA(BuyPower, n₂)ₜ
EMA_Sellₜ = EMA(SellPower, n₂)ₜ
```
\ \Step 6: Raw Demand Index (DI\_raw)\
```
DI_rawₜ = EMA_Buyₜ – EMA_Sellₜ
```
A positive DI\_raw indicates that buying force (normalized by volume) exceeds selling force; a negative value indicates the opposite.
\ \Step 7: Optional EMA Smoothing on DI (DI)\
To reduce choppiness, compute an EMA over DI\_raw (n₃ bars, e.g. n₃ = 1–5):
```
DIₜ = EMA(DI_raw, n₃)ₜ.
```
If n₃ = 1, DI = DI\_raw (no further smoothing).
\
\Interpretation\
\
\ \Crossing Zero Line\
• DI\_raw (or DI) crossing from below to above zero signals that cumulative buying pressure (over the chosen smoothing window) has overcome selling pressure—potential Long signal.
• Crossing from above to below zero signals dominant selling pressure—potential Short signal.
\ \DI\_raw vs. DI (EMA)\
• When DI\_raw > DI (the EMA of DI\_raw), bullish momentum is accelerating.
• When DI\_raw < DI, bullish momentum is weakening (or bearish acceleration).
\ \Divergences\
• If price makes new highs while DI fails to make higher highs (DI\_raw or DI declining), this hints at weakening buying power (“bearish divergence”), possibly preceding a reversal.
• If price makes new lows while DI fails to make lower lows (“bullish divergence”), this may signal waning selling pressure and a potential bounce.
\ \Volume Confirmation\
• A strong price move without a corresponding rise in DI often indicates low‐volume “fake” moves.
• Conversely, a modest price move with a large DI spike suggests true institutional participation—often a more reliable breakout.
\
\Usage Notes & Warnings\
\
\ \Never Use DI in Isolation\
It is a \filter\ and \confirmation\ tool—combine with price‐action (trendlines, support/resistance, candlestick patterns) and risk management (stop‐losses) before executing trades.
\ \Parameter Selection\
• \Vol EMA length (n₁)\: Commonly 13–20 bars. Shorter → more responsive to volume spikes, but noisier.
• \Buy/Sell EMA length (n₂)\: Typically 2 bars for fast smoothing.
• \DI smoothing (n₃)\: Usually 1 (no smoothing) or 3–5 for moderate smoothing. Long DI\_EMA (e.g. 20–50) gives a slower signal.
\ \Market Adaptation\
Works well in liquid futures, indices, and heavily traded stocks. In thinly traded or highly erratic markets, adjust n₁ upward (e.g., 20–30) to reduce noise.
---
\In Summary\
The Demand Index (James Sibbet) uses a three‐stage smoothing (volume → Buy/Sell Power → DI) to reveal true demand/supply imbalance. By combining normalized volume with price change, Sibbet’s DI helps traders identify momentum backed by real participation—filtering out “empty” moves and spotting early divergences. Always confirm DI signals with price action and sound risk controls before trading.
Adaptive Volume‐Demand‐Index (AVDI)Demand Index (according to James Sibbet) – Short Description
The Demand Index (DI) was developed by James Sibbet to measure real “buying” vs. “selling” strength (Demand vs. Supply) using price and volume data. It is not a standalone trading signal, but rather a filter and trend confirmer that should always be used together with chart structure and additional indicators.
---
\ 1. Calculation Basis\
1. Volume Normalization
$$
\text{normVol}_t
= \frac{\text{Volume}_t}{\mathrm{EMA}(\text{Volume},\,n_{\text{Vol}})_t}
\quad(\text{e.g., }n_{\text{Vol}} = 13)
$$
This smooths out extremely high volume spikes and compares them to the average (≈ 1 means “average volume”).
2. Price Factor
$$
\text{priceFactor}_t
= \frac{\text{Close}_t - \text{Open}_t}{\text{Open}_t}.
$$
Positive values for bullish bars, negative for bearish bars.
3. Component per Bar
$$
\text{component}_t
= \text{normVol}_t \times \text{priceFactor}_t.
$$
If volume is above average (> 1) and the price rises slightly, this yields a noticeably positive value; conversely if the price falls.
4. Raw DI (Rolling Sum)
Over a window of \$w\$ bars (e.g., 20):
$$
\text{RawDI}_t
= \sum_{i=0}^{w-1} \text{component}_{\,t-i}.
$$
Alternatively, recursively for \$t \ge w\$:
$$
\text{RawDI}_t
= \text{RawDI}_{t-1}
+ \text{component}_t
- \text{component}_{\,t-w}.
$$
5. Optional EMA Smoothing
An EMA over RawDI (e.g., \$n\_{\text{DI}} = 50\$) reduces short-term fluctuations and highlights medium-term trends:
$$
\text{EMA\_DI}_t
= \mathrm{EMA}(\text{RawDI},\,n_{\text{DI}})_t.
$$
6.Zero Line
Handy guideline:
RawDI > 0: Accumulated buying power dominates.
RawDI < 0: Accumulated selling power dominates.
2. Interpretation & Application
Crossing Zero
RawDI above zero → Indication of increasing buying pressure (potential long signal).
RawDI below zero → Indication of increasing selling pressure (potential short signal).
Not to be used alone for entry—always confirm with price action.
RawDI vs. EMA_DI
RawDI > EMA\_DI → Acceleration of demand.
RawDI < EMA\_DI → Weakening of demand.
Divergences
Price makes a new high, RawDI does not make a higher high → potential weakness in the uptrend.
Price makes a new low, RawDI does not make a lower low → potential exhaustion of the downtrend.
3. Typical Signals (for Beginners)
\ 1. Long Setup\
RawDI crosses zero from below,
RawDI > EMA\_DI (acceleration),
Price closes above a short-term swing high or resistance.
Stop-Loss: just below the last swing low, Take-Profit/Trailing: on reversal signals or fixed R\:R.
2. Short Setup
RawDI crosses zero from above,
RawDI < EMA\_DI (increased selling pressure),
Price closes below a short-term swing low or support.
Stop-Loss: just above the last swing high.
---
4. Notes and Parameters
Recommended Values (Beginners):
Volume EMA (n₍Vol₎) = 13
RawDI window (w) = 20
EMA over DI (n₍DI₎) = 50 (medium-term) or 1 (no smoothing)
Attention:\
NEVER use in isolation. Always in combination with price action analysis (trendlines, support/resistance, candlestick patterns).
Especially during volatile news phases, RawDI can fluctuate strongly → EMA\_DI helps to avoid false signals.
---
Conclusion The Demand Index by James Sibbet is a powerful filter to assess price movements by their volume backing. It shows whether a rally is truly driven by demand or merely a short-term volume anomaly. In combination with classic chart analysis and risk management, it helps to identify robust entry points and potential trend reversals earlier.
Simple Auto Trend LinesOpinionated way of drawing automatic trend lines. It draws automatically trend lines based on specified top/bottom strengths with multiple sets in order to keep track of multiple levels of interest.
Has the ability to hide invalidated trendlines if price moves away from it.
RSI Crossover Signal Companion - Alerts + Visuals🔷 RSI Crossover Signal Companion — Alerts + Visuals
The Relative Strength Index (RSI) is a momentum oscillator that measures the speed and change of recent price movements. It helps traders identify overbought or oversold conditions, possible trend reversals, and momentum strength.
This utility builds on TradingView’s classic Relative Strength Index (RSI) by adding real-time alerts and triangle markers when the RSI crosses its own moving average — a common technique for early momentum detection.
It is designed as a lightweight, visual companion tool for traders using RSI/MA crossover logic in manual or semi-automated strategies.
🔍 Features
✅ Preserves the full original RSI layout, including:
• Gradient fill and overbought/oversold zones
• Standard RSI input settings (length, source, etc.)
• MA smoothing options with user-defined type and length
🔺 Adds visual triangle markers:
🔼 Up triangle when RSI crosses above its MA
🔽 Down triangle when RSI crosses below its MA
📢 Built-in alerts for RSI/MA crosses:
“RSI Crossed Above MA”
“RSI Crossed Below MA”
📈 How to Use
This script is ideal for:
• Spotting early momentum shifts
• Confirming entries or exits in other systems (price action, trendlines, breakouts)
• Building alert-based automation (webhooks, bots, etc.)
Popular use cases:
• Combine with trend indicators like MA200 or MA12
• Use in confluence with price structure and divergence
• Validate breakout moves with momentum confirmation
⚙️ Customization
RSI length, MA length, MA type, and source are fully adjustable
Triangle marker size, shape, and color can be edited under Style
Alerts are pre-built and ready for use
Tight Range Display with Background🌟 Tight Range Transparency Display with Background
What Is This Indicator?
Hey traders! Ever wanted a simple way to spot those quiet, low-volatility moments in the market that often signal a big move is coming? The Tight Range Transparency Display with Background does exactly that! This indicator highlights periods where the price is moving in a tight range—think of it as the calm before the storm. It paints the chart background blue to show these zones, with the shade getting darker the tighter the range becomes. It’s like having a visual cue to say, “Hey, something might be brewing here!”
Why You’ll Love It
Spot Key Moments Easily: The blue background makes it super easy to see when the market is in a tight range, which often happens before breakouts or big trends.
Customizable Settings: You can tweak the range thresholds to match your trading style—whether you’re looking for super tight zones or slightly broader ones.
Visual Clarity: The background gets darker when the range is tighter, giving you a quick sense of how compressed the price action is.
Perfect for Any Market: Works on stocks, forex, crypto, or any chart you trade, across any timeframe.
How to Use It
Add It to Your Chart:
Just copy this script into TradingView’s Pine Editor and hit "Add to Chart." It’ll overlay right on your price chart.
Tweak the Settings:
Open the indicator settings and use the dropdown menus to pick your preferred "Tight Range %" and "Wide Range %." For example, set a Tight Range % of 2.0% to catch smaller ranges, or go higher like 10.0% for broader ones.
You can also adjust the ATR Period (default is 5) to make the indicator more or less sensitive to recent price swings.
Watch for the Blue Background:
When the price enters a tight range, the chart background turns blue. The darker the blue, the tighter the range—meaning a potential breakout could be closer!
Trade Smarter:
Use these tight range zones to prepare for potential breakouts. For example, if you see a dark blue background, it might be a good time to watch for a big price move.
Pair this with other tools like support/resistance levels or volume spikes to confirm your trades.
Who Is This For?
Swing Traders: Perfect for spotting consolidation zones before a big swing.
Breakout Traders: Tight ranges often lead to breakouts—use this to time your entries.
Smart Money Followers: If you’re into smart money concepts, tight ranges can signal accumulation or distribution phases.
Beginners & Pros Alike: It’s easy to use for new traders but powerful enough for seasoned pros.
Real-World Example
Imagine you’re trading a stock on a 1-hour chart. You notice the background turns blue, and it’s getting darker over a few bars. This tells you the price range is tightening—maybe the stock is consolidating after a big move. You check your other indicators, see a volume spike, and spot a breakout above resistance. Boom! You catch the next big trend, all because this indicator helped you focus on the right moment.
Tips for Best Results
Try Different Timeframes: Tight ranges on a 15-minute chart might signal short-term moves, while a daily chart could highlight bigger trends.
Adjust for Your Market: For volatile markets like crypto, you might want a higher Tight Range % (e.g., 10.0%). For calmer markets like forex, try a lower setting (e.g., 2.0%).
Combine with Other Tools: Use this alongside trendlines, moving averages, or volume indicators to confirm your setups.
Why I Made This
I created this indicator because I wanted a simple, visual way to spot those critical low-volatility zones without cluttering my chart. The dynamic background color makes it intuitive to see when the market is “coiling up” for a potential move. I hope it helps you find better trading opportunities just like it does for me!
Let’s Connect
If you find this indicator helpful, I’d love to hear about it! Drop a comment or a rating to let me know how it’s working for you. Got ideas to make it even better? Feel free to message me on TradingView—I’m always open to suggestions.
Published On
Date: May 22, 2025
Happy trading, and may your charts always be in your favor! 🚀
How to Publish on TradingView
Open Pine Editor:
On TradingView, open a chart and go to the Pine Editor tab at the bottom.
Paste the Code:
Copy the script you provided and paste it into the Pine Editor.
Compile:
Click "Add to Chart" to ensure it compiles without errors.
Publish:
Click the "Publish Script" button (paper plane icon) in the Pine Editor.
Select "Publish New Script."
Add the Description:
Title: "Tight Range Transparency Display with Background"
Description: Copy the content above into the description field.
Visibility: Choose "Public" to share with everyone (or "Invite-Only" for restricted access).
Tags: Add tags like "tight range", "breakout", "smart money", "volatility", "swing trading".
Screenshot: Add a screenshot of the indicator on a chart, showing the blue background during a tight range.
Submit:
Click "Publish" to submit. TradingView will review it and make it live if it meets their guidelines.
Additional Notes
Screenshot Tip: Use a chart where the blue background is clearly visible (e.g., during a consolidation period) to make the indicator’s effect stand out.
Engage with Users: After publishing, respond to comments and feedback to build a positive reputation on TradingView.
This content is designed to be approachable and engaging, helping traders understand the value of your indicator and encouraging them to try it out.
(OFPI) Order Flow Polarity Index - Momentum Gauge (DAFE) (OFPI) Order Flow Polarity Index - Momentum Gauge: Decode Market Aggression
The (OFPI) Gauge Bar is your front-row seat to the battle between buyers and sellers. This isn’t just another indicator—it’s a momentum tracker that reveals market aggression through a sleek, centered gauge bar and a smart dashboard. Built for traders who want clarity without clutter, it’s your edge for spotting who’s driving price, bar by bar.
What Makes It Unique?
Order Flow Pressure Index (OFPI): Splits volume into buy vs. sell pressure based on candle body position. It’s not just volume—it’s intent, showing who’s got the upper hand.
T3 Smoothing Magic: Uses a Tilson T3 moving average to keep signals smooth yet responsive. No laggy SMA nonsense here.
Centered Gauge Bar: A 20-segment bar splits bullish (lime) and bearish (red) momentum around a neutral center. Empty segments scream indecision—it’s like a visual heartbeat of the market.
Momentum Shift Alerts: Catches reversals with “Momentum Shift” flags when the OFPI crests, so you’re not caught off guard.
Clean Dashboard: A compact, bottom-left table shows momentum status, the gauge bar, and the OFPI value. Color-coded, transparent, and no chart clutter.
Inputs & Customization
Lookback Length (default 10): Set the window for pressure calculations. Short for scalps, long for trends.
T3 Smoothing Length (default 5): Tune the smoothness. Tight for fast markets, relaxed for chill ones.
T3 Volume Factor (default 0.7): Crank it up for snappy signals or down for silky trends.
Toggle the dashboard for minimalist setups or mobile trading.
How to Use It
Bullish Momentum (Lime, Right-Filled): Buyers are flexing. Look for breakouts or trend continuations. Pair with support levels.
Bearish Momentum (Red, Left-Filled): Sellers are in charge. Scout for breakdowns or shorts. Check resistance zones.
Neutral (Orange, Near Center): Market’s chilling. Avoid big bets—wait for a breakout or play the range.
Momentum Shift: A reversal might be brewing. Confirm with price action before jumping in.
Not a Solo Act: Combine with your strategy—trendlines, RSI, whatever. It’s a momentum lens, not a buy/sell bot.
Why Use the OFPI Gauge?
See the Fight: Most tools just count volume. OFPI shows who’s winning with a visual that slaps.
Works Anywhere: Crypto, stocks, forex, any timeframe. Tune it to your style.
Clean & Pro: No chart spam, just a sharp gauge and a dashboard that delivers.
Unique Edge: No other indicator blends body-based pressure, T3 smoothing, and a centered gauge like this.
The OFPI Gauge catches the market’s pulse so you can trade with confidence. It’s not about predicting the future—it’s about knowing who’s in control right now.
For educational purposes only. Not financial advice. Always use proper risk management.
Use with discipline. Trade your edge.
— Dskyz , for DAFE Trading Systems
Why EMA Isn't What You Think It IsMany new traders adopt the Exponential Moving Average (EMA) believing it's simply a "better Simple Moving Average (SMA)". This common misconception leads to fundamental misunderstandings about how EMA works and when to use it.
EMA and SMA differ at their core. SMA use a window of finite number of data points, giving equal weight to each data point in the calculation period. This makes SMA a Finite Impulse Response (FIR) filter in signal processing terms. Remember that FIR means that "all that we need is the 'period' number of data points" to calculate the filter value. Anything beyond the given period is not relevant to FIR filters – much like how a security camera with 14-day storage automatically overwrites older footage, making last month's activity completely invisible regardless of how important it might have been.
EMA, however, is an Infinite Impulse Response (IIR) filter. It uses ALL historical data, with each past price having a diminishing - but never zero - influence on the calculated value. This creates an EMA response that extends infinitely into the past—not just for the last N periods. IIR filters cannot be precise if we give them only a 'period' number of data to work on - they will be off-target significantly due to lack of context, like trying to understand Game of Thrones by watching only the final season and wondering why everyone's so upset about that dragon lady going full pyromaniac.
If we only consider a number of data points equal to the EMA's period, we are capturing no more than 86.5% of the total weight of the EMA calculation. Relying on he period window alone (the warm-up period) will provide only 1 - (1 / e^2) weights, which is approximately 1−0.1353 = 0.8647 = 86.5%. That's like claiming you've read a book when you've skipped the first few chapters – technically, you got most of it, but you probably miss some crucial early context.
▶️ What is period in EMA used for?
What does a period parameter really mean for EMA? When we select a 15-period EMA, we're not selecting a window of 15 data points as with an SMA. Instead, we are using that number to calculate a decay factor (α) that determines how quickly older data loses influence in EMA result. Every trader knows EMA calculation: α = 1 / (1+period) – or at least every trader claims to know this while secretly checking the formula when they need it.
Thinking in terms of "period" seriously restricts EMA. The α parameter can be - should be! - any value between 0.0 and 1.0, offering infinite tuning possibilities of the indicator. When we limit ourselves to whole-number periods that we use in FIR indicators, we can only access a small subset of possible IIR calculations – it's like having access to the entire RGB color spectrum with 16.7 million possible colors but stubbornly sticking to the 8 basic crayons in a child's first art set because the coloring book only mentioned those by name.
For example:
Period 10 → alpha = 0.1818
Period 11 → alpha = 0.1667
What about wanting an alpha of 0.17, which might yield superior returns in your strategy that uses EMA? No whole-number period can provide this! Direct α parameterization offers more precision, much like how an analog tuner lets you find the perfect radio frequency while digital presets force you to choose only from predetermined stations, potentially missing the clearest signal sitting right between channels.
Sidenote: the choice of α = 1 / (1+period) is just a convention from 1970s, probably started by J. Welles Wilder, who popularized the use of the 14-day EMA. It was designed to create an approximate equivalence between EMA and SMA over the same number of periods, even thought SMA needs a period window (as it is FIR filter) and EMA doesn't. In reality, the decay factor α in EMA should be allowed any valye between 0.0 and 1.0, not just some discrete values derived from an integer-based period! Algorithmic systems should find the best α decay for EMA directly, allowing the system to fine-tune at will and not through conversion of integer period to float α decay – though this might put a few traditionalist traders into early retirement. Well, to prevent that, most traditionalist implementations of EMA only use period and no alpha at all. Heaven forbid we disturb people who print their charts on paper, draw trendlines with rulers, and insist the market "feels different" since computers do algotrading!
▶️ Calculating EMAs Efficiently
The standard textbook formula for EMA is:
EMA = CurrentPrice × alpha + PreviousEMA × (1 - alpha)
But did you know that a more efficient version exists, once you apply a tiny bit of high school algebra:
EMA = alpha × (CurrentPrice - PreviousEMA) + PreviousEMA
The first one requires three operations: 2 multiplications + 1 addition. The second one also requires three ops: 1 multiplication + 1 addition + 1 subtraction.
That's pathetic, you say? Not worth implementing? In most computational models, multiplications cost much more than additions/subtractions – much like how ordering dessert costs more than asking for a water refill at restaurants.
Relative CPU cost of float operations :
Addition/Subtraction: ~1 cycle
Multiplication: ~5 cycles (depending on precision and architecture)
Now you see the difference? 2 * 5 + 1 = 11 against 5 + 1 + 1 = 7. That is ≈ 36.36% efficiency gain just by swapping formulas around! And making your high school math teacher proud enough to finally put your test on the refrigerator.
▶️ The Warmup Problem: how to start the EMA sequence right
How do we calculate the first EMA value when there's no previous EMA available? Let's see some possible options used throughout the history:
Start with zero : EMA(0) = 0. This creates stupidly large distortion until enough bars pass for the horrible effect to diminish – like starting a trading account with zero balance but backdating a year of missed trades, then watching your balance struggle to climb out of a phantom debt for months.
Start with first price : EMA(0) = first price. This is better than starting with zero, but still causes initial distortion that will be extra-bad if the first price is an outlier – like forming your entire opinion of a stock based solely on its IPO day price, then wondering why your model is tanking for weeks afterward.
Use SMA for warmup : This is the tradition from the pencil-and-paper era of technical analysis – when calculators were luxury items and "algorithmic trading" meant your broker had neat handwriting. We first calculate an SMA over the initial period, then kickstart the EMA with this average value. It's widely used due to tradition, not merit, creating a mathematical Frankenstein that uses an FIR filter (SMA) during the initial period before abruptly switching to an IIR filter (EMA). This methodology is so aesthetically offensive (abrupt kink on the transition from SMA to EMA) that charting platforms hide these early values entirely, pretending EMA simply doesn't exist until the warmup period passes – the technical analysis equivalent of sweeping dust under the rug.
Use WMA for warmup : This one was never popular because it is harder to calculate with a pencil - compared to using simple SMA for warmup. Weighted Moving Average provides a much better approximation of a starting value as its linear descending profile is much closer to the EMA's decay profile.
These methods all share one problem: they produce inaccurate initial values that traders often hide or discard, much like how hedge funds conveniently report awesome performance "since strategy inception" only after their disastrous first quarter has been surgically removed from the track record.
▶️ A Better Way to start EMA: Decaying compensation
Think of it this way: An ideal EMA uses an infinite history of prices, but we only have data starting from a specific point. This creates a problem - our EMA starts with an incorrect assumption that all previous prices were all zero, all close, or all average – like trying to write someone's biography but only having information about their life since last Tuesday.
But there is a better way. It requires more than high school math comprehension and is more computationally intensive, but is mathematically correct and numerically stable. This approach involves compensating calculated EMA values for the "phantom data" that would have existed before our first price point.
Here's how phantom data compensation works:
We start our normal EMA calculation:
EMA_today = EMA_yesterday + α × (Price_today - EMA_yesterday)
But we add a correction factor that adjusts for the missing history:
Correction = 1 at the start
Correction = Correction × (1-α) after each calculation
We then apply this correction:
True_EMA = Raw_EMA / (1-Correction)
This correction factor starts at 1 (full compensation effect) and gets exponentially smaller with each new price bar. After enough data points, the correction becomes so small (i.e., below 0.0000000001) that we can stop applying it as it is no longer relevant.
Let's see how this works in practice:
For the first price bar:
Raw_EMA = 0
Correction = 1
True_EMA = Price (since 0 ÷ (1-1) is undefined, we use the first price)
For the second price bar:
Raw_EMA = α × (Price_2 - 0) + 0 = α × Price_2
Correction = 1 × (1-α) = (1-α)
True_EMA = α × Price_2 ÷ (1-(1-α)) = Price_2
For the third price bar:
Raw_EMA updates using the standard formula
Correction = (1-α) × (1-α) = (1-α)²
True_EMA = Raw_EMA ÷ (1-(1-α)²)
With each new price, the correction factor shrinks exponentially. After about -log₁₀(1e-10)/log₁₀(1-α) bars, the correction becomes negligible, and our EMA calculation matches what we would get if we had infinite historical data.
This approach provides accurate EMA values from the very first calculation. There's no need to use SMA for warmup or discard early values before output converges - EMA is mathematically correct from first value, ready to party without the awkward warmup phase.
Here is Pine Script 6 implementation of EMA that can take alpha parameter directly (or period if desired), returns valid values from the start, is resilient to dirty input values, uses decaying compensator instead of SMA, and uses the least amount of computational cycles possible.
// Enhanced EMA function with proper initialization and efficient calculation
ema(series float source, simple int period=0, simple float alpha=0)=>
// Input validation - one of alpha or period must be provided
if alpha<=0 and period<=0
runtime.error("Alpha or period must be provided")
// Calculate alpha from period if alpha not directly specified
float a = alpha > 0 ? alpha : 2.0 / math.max(period, 1)
// Initialize variables for EMA calculation
var float ema = na // Stores raw EMA value
var float result = na // Stores final corrected EMA
var float e = 1.0 // Decay compensation factor
var bool warmup = true // Flag for warmup phase
if not na(source)
if na(ema)
// First value case - initialize EMA to zero
// (we'll correct this immediately with the compensation)
ema := 0
result := source
else
// Standard EMA calculation (optimized formula)
ema := a * (source - ema) + ema
if warmup
// During warmup phase, apply decay compensation
e *= (1-a) // Update decay factor
float c = 1.0 / (1.0 - e) // Calculate correction multiplier
result := c * ema // Apply correction
// Stop warmup phase when correction becomes negligible
if e <= 1e-10
warmup := false
else
// After warmup, EMA operates without correction
result := ema
result // Return the properly compensated EMA value
▶️ CONCLUSION
EMA isn't just a "better SMA"—it is a fundamentally different tool, like how a submarine differs from a sailboat – both float, but the similarities end there. EMA responds to inputs differently, weighs historical data differently, and requires different initialization techniques.
By understanding these differences, traders can make more informed decisions about when and how to use EMA in trading strategies. And as EMA is embedded in so many other complex and compound indicators and strategies, if system uses tainted and inferior EMA calculatiomn, it is doing a disservice to all derivative indicators too – like building a skyscraper on a foundation of Jell-O.
The next time you add an EMA to your chart, remember: you're not just looking at a "faster moving average." You're using an INFINITE IMPULSE RESPONSE filter that carries the echo of all previous price actions, properly weighted to help make better trading decisions.
EMA done right might significantly improve the quality of all signals, strategies, and trades that rely on EMA somewhere deep in its algorithmic bowels – proving once again that math skills are indeed useful after high school, no matter what your guidance counselor told you.
Precision LevelsThis open-source Support and Resistance Indicator helps traders plot key price levels where the market may reverse or consolidate. By plotting support and resistance zones based on historical price action, it provides clear visual cues for potential entry and exit points across various timeframes.
Customizable Settings: Adjust visual styles to suit your trading strategy.
Multi-Timeframe Support: View and plot levels from higher timeframes using the monthly and weekly levels.
User-Friendly: Lightweight design with clear plotting for easy integration into any setup.
How It Works:
The indicator plots simple Support and resistance. Zones are labeled monthly, weekly, and daily
Usage:
Apply the indicator to your chart.
Enter a value for each support and resistance level. Drag and Adjust on the chart to your liking.
Use the plotted levels to identify potential reversals, breakouts, or stop-loss placements.
Combine with other tools (e.g., trendlines or oscillators) for confirmation.
Note: This is the open-source version of my previously protected Support and Resistance Indicator. The protected version is flagged and hidden from community and no longer maintained. Feel free to explore and modify the code to fit your needs! For feedback or suggestions, leave a comment below or message me direct.
SuperTrend: Silent Shadow 🕶️ SuperTrend: Silent Shadow — Operate in trend. Vanish in noise.
Overview
SuperTrend: Silent Shadow is an enhanced trend-following system designed for traders who demand clarity in volatile markets and silence during indecision.
It combines classic Supertrend logic with a proprietary ShadowTrail engine and an adaptive Silence Protocol to filter noise and highlight only the cleanest signals.
Key Features
✅ Core Supertrend Logic
Built on Average True Range (ATR), this trend engine identifies directional bias with visual clarity. Lines adjust dynamically with price action and flip when meaningful reversals occur.
✅ ShadowTrail: Stepped Counter-Barrier
ShadowTrail doesn’t predict reversals — it reinforces structure.
When price is trending, ShadowTrail forms a stepped ceiling in downtrends and a stepped floor in uptrends. This visual containment zone helps define the edges of price behavior and offers a clear visual anchor for stop-loss placement and trade containment.
✅ Silence Protocol: Adaptive Noise Filtering
During low-volatility zones, the system enters “stealth mode”:
• Trend lines turn white to indicate reduced signal quality
• Fill disappears to reduce distraction
This helps avoid choppy entries and keeps your focus sharp when the market isn’t.
✅ Visual Support & Stop-Loss Utility
When trendlines flatten or pause, they naturally highlight price memory zones. These flat sections often align with:
• Logical stop-loss levels
• Prior support/resistance areas
• Zones of reduced volatility where price recharges or rejects
✅ Custom Styling
Full control over line colors, width, transparency, fill visibility, and silence behavior. Tailor it to your strategy and visual preferences.
How to Use
• Use Supertrend color to determine bias — flips mark momentum shifts
• ShadowTrail mirrors the primary trend as a structural ceiling/floor
• Use flat segments of both lines to identify consolidation zones or place stops
• White lines = low-quality signal → stand by
• Combine with RSI, volume, divergence, or your favorite tools for confirmation
Recommended For:
• Traders seeking clearer trend signals
• Avoiding false entries in sideways or silent markets
• Identifying key support/resistance visually
• Structuring stops around real market containment levels
• Scalping, swing, or position trading with adaptive clarity
Built by Sherlock Macgyver
Forged for precision. Designed for silence.
When the market speaks, you listen.
When it doesn’t — you wait in the shadows.
BK AK-47 Divergence🚨 Introducing BK AK-47 Divergence — Multi-Timeframe Precision Firepower for True Traders 🚨
After months of development, I’m proud to release my fifth weapon in the arsenal — BK AK-47 Divergence.
💥 Why “AK-47”? The Meaning Behind the Name
The AK-47 isn’t just a rifle. It’s the symbol of reliability, versatility, and raw stopping power. It performs in every environment — from the mud to the mountains — just like this indicator cuts through noise on any timeframe, any asset, any condition.
🔸 “AK” honors the same legacy as before — my mentor, A.K., whose discipline and vision forged my trading edge.
🔸 “47” signifies layered precision: 4 = structure, 7 = spiritual completion. Together, it’s the weapon of divine order that adapts, reacts, and strikes with purpose.
🔍 What Is BK AK-47 Divergence?
It’s a next-generation divergence detector — a smart hybrid of MACD, Bollinger Bands, and multi-timeframe divergence logic wrapped in a custom volatility engine and real-time flash alerts.
Designed for snipers in the market — those who only take the highest-probability shots.
⚙️ Core Weapon Systems
✅ MACD + BB Precision Overlay → MACD plotted inside dynamic Bollinger Bands — reveals hidden pressure zones where most indicators fail.
✅ Smart Histogram Scaling → Adaptive amplification based on volatility. No more weak histograms in strong markets.
✅ Full Multi-Timeframe Divergence Detection:
🔻 Current TF Divergence
🕐 Higher TF Divergence
⏱️ Lower TF Divergence
Each plotted with clean visual alerts, color-coded by direction and timeframe. You get instant divergence recognition across dimensions.
✅ Background Flash Alerts → When MACD hits BB extremes, the background lights up in red or green. Eyes instantly lock in on key moments.
✅ Advanced Pivot Lookback Control → New lookback system compares multiple pivot layers, not just the last swing. This gives true structural divergence, not just noise.
✅ Dynamic Fill Zones:
🔴 Oversold
🟢 Overbought
🔵 Neutral
Built to filter false signals and highlight hidden edge.
🛡️ Why This Indicator Changes the Game
🔹 Built for divergence snipers — not lagging MACD watchers.
🔹 Perfect for traders who sync with:
• Elliott Waves
• Fibonacci Time/Price Clusters
• Harmonic Patterns
• Gann Angles or Squares
• Price Action & Trendlines
🔹 Lets you visually map:
• Converging divergences (multi-TF confirmation)
• High-volatility histograms in low-volatility price zones (entry sweet spots)
• Flash-momentum warnings at BB pressure zones
🎯 How to Use BK AK-47 Divergence
🔹 Breakout Confirmation → MACD breaches upper BB with bullish divergence = signal to ride momentum.
🔹 Mean Reversion Reversals → MACD breaks lower BB + bullish div = setup for sniper long.
🔹 Top/Bottom Detection → Bearish divergence + MACD failure at upper BB = early reversal signal.
🔹 TF Sync Strategy → Align current TF with higher or lower divergences for laser-confirmed entries.
🧠 Final Thoughts
This isn’t just a divergence tool. It’s a battlefield reconnaissance system — one that lets you see when, where, and why the next pivot is forming.
🔹 Built in honor of the AK-legacy — reliability, discipline, and firepower.
🔹 Designed to cut through noise, expose structure, and alert you to what really matters.
🔹 Crafted for those who trade with intent, vision, and respect for the craft.
🙏 And most importantly: All glory to Gd — the One who gives wisdom, clarity, and purpose.
Without Him, the markets are chaos. With Him, we move in structure, order, and divine timing.
—
⚡ Stay dangerous. Stay precise. Stay aligned.
🔥 BK AK-47 Divergence — Locked. Loaded. Laser-focused. 🔥
May the markets bend to your discipline.
Gd bless. 🙏
Rocky's Dynamic DikFat Supply & Demand ZonesDynamic Supply & Demand Zones
Overview
The Dynamic Supply & Demand Zones indicator identifies key supply and demand levels on your chart by detecting pivot highs and lows. It draws customizable boxes around these zones, helping traders visualize areas where price may react. With flexible display options and dynamic box behavior, this tool is designed to assist in identifying potential support and resistance levels for various trading strategies.
Key Features
Pivot-Based Zones: Automatically detects supply (resistance) and demand (support) zones using pivot highs and lows on the chart’s timeframe.
Dynamic Box Sizing: Boxes shrink when price enters them, reflecting reduced zone strength, and stop adjusting once price fully crosses through.
Customizable Display: Choose to show current-day boxes, historical boxes, or all boxes, with an option to update past box colors dynamically.
Session-Based Extension: Boxes can extend to the current bar or stop at 4:00 PM of the creation day’s 9:30 AM–4:00 PM trading session (ideal for stock markets).
Color Coding: Borders change color based on price position:
Green for demand zones (price above the box).
Red for supply zones (price below the box).
White for neutral zones (price inside the box).
User-Friendly Inputs: Adjust pivot lookback periods, box visibility, extension behavior, and colors via intuitive input settings.
How It Works
Zone Detection: The indicator uses pivot highs and lows to define supply and demand zones, plotting boxes between these levels.
Box Behavior:
Boxes are created when pivot highs and lows are confirmed, with no overlap with the previous box.
When price enters a box, it shrinks to reflect interaction, stopping once price exits completely.
Boxes can extend to the current bar or end at 4:00 PM of the creation day (or next trading day if created after 4:00 PM or on weekends).
Display Options:
Current Only: Shows boxes created on the current day.
Historical Only: Shows boxes from previous days, with optional color updates.
All Boxes: Shows all boxes, with an option to hide historical box color updates.
Performance: Limits the number of boxes to 200 to ensure smooth performance, removing older boxes as needed.
Inputs
Pivot Look Right/Left: Set the number of bars (default: 2) to confirm pivot highs and lows.
What Boxes to Show: Select Current Only, Historical Only, or All Boxes (default: Current Only).
Boxes On/Off: Toggle box visibility (default: on).
Extend Boxes to Current Bar: Choose whether boxes extend to the current bar or stop at 4:00 PM (default: off, stops at 4:00 PM).
Update Past Box Colors: Enable/disable color updates for historical boxes (default: on).
Demand/Supply/Neutral Box Color: Customize border colors (default: green, red, white).
How to Use
Add the indicator to your chart.
Adjust inputs to match your trading style (e.g., pivot lookback, box extension, colors).
Use the boxes to identify potential support (demand) and resistance (supply) zones:
Green-bordered boxes (price above) may act as support.
Red-bordered boxes (price below) may act as resistance.
White-bordered boxes (price inside) indicate active price interaction.
Combine with other analysis tools (e.g., trendlines, indicators) to confirm trade setups.
Monitor box shrinking to gauge zone strength and watch for breakouts when price fully crosses a box.
Understanding Supply and Demand in Stock Trading
In stock trading, supply and demand are fundamental forces driving price movements. Demand refers to the willingness of buyers to purchase a stock at a given price, often creating support levels where buying interest prevents further price declines. Supply represents the willingness of sellers to offload a stock, forming resistance levels where selling pressure halts price increases. These zones are critical because they highlight areas where significant buying or selling activity has occurred, influencing future price behavior.
The importance of supply and demand lies in their ability to reveal where institutional traders, with large orders, have entered or exited the market. Demand zones, often seen at pivot lows, indicate strong buying interest and potential areas for price reversals or bounces. Supply zones, typically at pivot highs, signal heavy selling and possible reversal points for downward moves. By identifying these zones, traders can anticipate where price is likely to stall, reverse, or break out, enabling better entry and exit decisions. This indicator visualizes these zones as dynamic boxes, making it easier to spot high-probability trading opportunities while emphasizing the core market dynamics of supply and demand.
Feedback
This indicator is designed to help traders visualize supply and demand zones effectively. If you have suggestions for improvements, please share your feedback in the comments!
Internal Market Structure + Order BlocksInternal Market Structure + Order Blocks
This indicator combines internal market structure shifts with order block detection to help traders identify key zones of institutional interest and potential trend reversals. It highlights bullish and bearish engulfing conditions that mark the formation of valid order blocks, and it plots internal structure shifts—early signals that may precede a larger move.
Key Features:
-Bullish & Bearish Order Blocks: Highlighted with shaded boxes (green for bullish, red for bearish) following engulfing price action.
-Internal Structure Shifts: Small black triangles show early signs of a potential reversal, offering a unique perspective beyond standard structure analysis.
-Engulfing Breakouts: Marks when price breaks previous opposing structure, confirming new directional intent.
-Alerts Included: Get notified on key structure breaks and internal shifts to stay ahead of potential setups.
This tool is designed to support price action trading by visually mapping key structural changes and zones of interest directly on your chart. It is not intended to function as a standalone trading strategy , but rather as a supplementary tool to inform your own analysis and discretion.
Note: The arrows, polylines, and colored trendlines shown in the chart example are not generated by the indicator. They have been added manually for illustration purposes to demonstrate how the indicator can be used to trace market structure. Likewise, the order blocks in the example are manually drawn and may differ slightly from the indicator's automatic calculations, serving only to enhance visual clarity.
Chart Patterns [ActiveQuants]The Chart Patterns indicator is a comprehensive tool designed to automatically identify a variety of common chart patterns directly on your price chart. By detecting sequences of pivot highs and lows , this indicator helps traders spot potential trend continuations , reversals , and key market structures such as Double Tops and Double Bottoms . Enhance your technical analysis by quickly recognizing these formations as they emerge.
How It Works
The indicator operates in a two-stage process:
Pivot Point Detection: It first identifies significant swing highs and swing lows (pivot points) based on a user-defined Period . These pivots form the fundamental building blocks for pattern recognition.
Pattern Recognition: Using the sequence of these detected pivot points, the script then applies logical rules to identify the following patterns:
Lower Low (LL)
Lower Low & Lower High (LL & LH)
Higher High (HH)
Higher High & Higher Low (HH & HL)
Double Tops
Double Bottoms
Patterns are drawn on the chart with connecting lines and labeled for easy identification. Double Tops and Double Bottoms also feature a status system: " Active " while forming, " Confirmed " upon neckline breakout, or " Invalid " if specific conditions negate the pattern before confirmation.
█ KEY FEATURES
Comprehensive Pattern Detection: Identifies six distinct types of chart patterns, offering insights into both trend continuation and potential reversals.
Pivot-Based Analysis: Uses a robust method of identifying pivot highs and lows as the foundation for pattern formation.
Pattern Status for Double Tops/Bottoms:
- Active: A Double Top or Double Bottom pattern has formed its two peaks/troughs and the intervening neckline point, but the price has not yet broken beyond the neckline. The pattern is developing .
- Confirmed: The price has decisively closed beyond the neckline (below for Double Top, above for Double Bottom), signaling a potential entry or validation of the pattern.
- Invalid: An " Active " Double Top or Double Bottom pattern can be invalidated if, before a neckline breakout occurs, a new pivot point forms that negates the pattern’s structural integrity. For example, if a new pivot low forms above or at the neckline of an Active Double Top, the pattern is considered invalid because the market failed to break down and instead showed relative strength.
Customizable Visuals: Allows users to define colors for bullish and bearish patterns, line widths, and the visibility of pivot points.
Selective Pattern Display: Users can choose to display all patterns or filter by status (Active, Confirmed, Invalid) for Double Tops/Bottoms. Individual pattern types can also be toggled on or off.
Historical Analysis Control: The Show Last History (Bars) input allows users to specify how far back the indicator should plot patterns, optimizing performance and chart readability.
Clear Labeling: Patterns are clearly labeled on the chart, with Double Tops/Bottoms also showing " Top 1 ," " Top 2 ," or " Bottom 1 ," " Bottom 2 " labels.
█ PATTERNS DETECTED
Lower Low (LL): Indicates a potential bearish continuation or the start of a downtrend. Forms when price makes a lower low during an uptrend.
Lower Low & Lower High (LL & LH): A stronger confirmation of a bearish trend, where the market forms a lower low followed by a lower high .
Higher High (HH): Signals a potential bullish continuation or the start of an uptrend. Forms when price makes a higher high during a downtrend.
Higher High & Higher Low (HH & HL): A stronger confirmation of a bullish trend, where the market forms a higher high followed by a higher low .
Double Top: A bearish reversal pattern characterized by two distinct peaks at roughly the same price level, separated by a trough (neckline). Confirmation occurs when price breaks below the neckline.
Double Bottom: A bullish reversal pattern featuring two distinct troughs at roughly the same price level, separated by a peak (neckline). Confirmation occurs when price breaks above the neckline.
█ EXAMPLE: DOUBLE TOP INVALIDATION
Understanding how a Double Top or Double Bottom can be invalidated is crucial. Here's an example for a Double Top:
Formation: The indicator identifies two peaks (Top 1, Top 2) at a similar price level, with a corrective trough (Neckline Pivot P5) in between. The pattern is labeled " Double Top " and is in an " Active " state. ( Imagine points P4 and P6 are the two tops, and P5 is the low point of the neckline between them ).
Pre-Breakout Condition: The price action continues, but before it breaks decisively below the P5 neckline level, a new significant swing low (a new pivot low) forms.
Invalidation Check: The indicator checks the price level of this new pivot low. If this new pivot low occurs at a price equal to or higher than the P5 neckline level, the " Active " Double Top pattern is re-labeled as " Invalid Double Top ". ( See image below for a visual representation of this scenario )
In this example, the Double Top formed with Top 1 (P4) and Top 2 (P6). The neckline is at P5. Before price broke below P5, a new pivot low formed at the red circle. Since this new pivot low is above the P5 neckline, the Double Top is marked " Invalid ".
The logic is that the market failed to break the neckline support and instead established a higher low (or a low at the support level), suggesting that the immediate bearish pressure has waned, thus invalidating the bearish reversal implication of the Double Top before it could confirm. A similar logic applies to Double Bottoms (a new pivot high forming below or at the neckline before an upside breakout).
█ USER INPUTS
Visibility and Common Styling
- Show Last History (Bars):
Specifies the number of recent bars the indicator will analyze and plot patterns on.
Default: 3000 bars. Min: 10.
- Patterns:
Filters which patterns are displayed based on their status.
Options: All, Active, Confirmed, Invalid.
Default: All.
- Pattern Line Width:
Sets the thickness of the lines used to draw the patterns.
Default: 1. Min: 1, Max: 10.
- Bearish Color:
Color for bearish patterns (LL, LL & LH, Double Tops).
Default: Red.
- Bullish Color:
Color for bullish patterns (HH, HH & HL, Double Bottoms).
Default: Green.
Pivot Points
- Period:
The lookback period on either side of a bar to qualify it as a pivot high or low. Higher values detect more significant pivots.
Default: 10 bars. Min: 2.
- Show Pivot Highs:
Toggles the visibility of detected pivot high markers.
Default: Enabled.
- Show Pivot Lows:
Toggles the visibility of detected pivot low markers.
Default: Enabled.
- Pivot Highs Color:
Color for the pivot high markers.
Default: #ff5252 (Reddish).
- Pivot Lows Color:
Color for the pivot low markers.
Default: #089981 (Greenish).
Patterns (Toggles)
- Lower Low:
Enable/disable detection and display of Lower Low patterns.
Default: Enabled.
- Lower Low & Lower High:
Enable/disable detection and display of Lower Low & Lower High patterns.
Default: Enabled.
- Higher High:
Enable/disable detection and display of Higher High patterns.
Default: Enabled.
- Higher High & Higher Low:
Enable/disable detection and display of Higher High & Higher Low patterns.
Default: Enabled.
- Double Tops:
Enable/disable detection and display of Double Top patterns.
Default: Enabled.
- Double Bottoms:
Enable/disable detection and display of Double Bottom patterns.
Default: Enabled.
█ CONCLUSION
The Chart Patterns indicator is a versatile and powerful assistant for traders who utilize classical chart pattern analysis. By automating the detection of key formations and providing clear visual cues along with status updates for patterns like Double Tops and Bottoms, it allows traders to focus on strategy development and execution. With its customizable settings, it can be adapted to various instruments and timeframes, making it a valuable addition to any technical trader's toolkit.
█ IMPORTANT NOTES
⚠ Pivot Period Sensitivity: The Period setting for pivot detection is crucial. A shorter period will identify more frequent, smaller swings, while a longer period will focus on more significant turning points. Adjust this setting based on the asset's volatility, the timeframe you are trading and your trading style.
⚠ Confirmation is Key: While the indicator identifies patterns, always wait for pattern confirmation (e.g., neckline breaks for Double Tops/Bottoms) and consider other factors like volume and market context before making trading decisions.
⚠ Confirmed Bars for Detection: Patterns are identified based on confirmed pivot points, which means a pivot is recognized period bars after it has formed. Status updates for Double Tops/Bottoms (Active, Confirmed, Invalid) also occur on confirmed bars. This approach enhances reliability and reduces the likelihood of repainting based on intra-bar price fluctuations.
⚠ Not a Standalone System: Chart patterns provide valuable insights, but they should be used in conjunction with other technical analysis tools (e.g., trendlines, moving averages, oscillators) and a sound risk management plan.
⚠ Lagging Nature: By their very definition, chart patterns are lagging indicators as they require a sequence of price action and several pivot points to complete their formation.
█ RISK DISCLAIMER
Trading involves a substantial risk of loss and is not suitable for every investor. The information provided by the Chart Patterns indicator is for educational and informational purposes only. It should not be considered as financial advice or a recommendation to buy or sell any security. Chart patterns indicate potential price movements but do not guarantee future results. Always perform your own due diligence and consult with a qualified financial advisor before making any investment decisions. Past performance is not indicative of future results.
📈 Happy trading! 🚀
Atlas BBTlevelsAtlas BBTlevels is a custom Bollinger Bands-based indicator that measures the momentum and strength of price trends using the difference between short- and long-period Bollinger Bands. Inspired by John Bollinger’s official tools like BBTrend, %b, and Bandwidth, this script adds adjustable horizontal threshold levels so traders can mark important reaction zones on their charts.
It visualizes when markets may be entering overheated or exhausted conditions — either for trend continuation or potential reversals — and works across crypto, stocks, forex, spot, or perpetual charts.
How I personally use it:
I apply Atlas BBTlevels across three timeframes:
Low timeframe (LTF): 5m–15m
Mid timeframe (MTF): 1h–6h
High timeframe (HTF): 1d–2d
I review where the indicator historically spiked during major moves. For example, if the 4-hour chart shows repeated spikes to +10 or −10, I’ll set my positive and negative thresholds near those levels. This lets me anticipate zones where the market may reverse, cool off, or break out. I then compare LTF, MTF, and HTF levels to look for confluence. When multiple timeframes align near key levels, it gives me higher confidence to prepare for a trade — but I always combine this with price action and other confirmation tools.
How others can use it:
Identify overbought/oversold zones by adjusting the thresholds to match historical extremes on your chosen asset.
Use it as a trend strength gauge: when the histogram is near or above the top threshold, the trend is likely strong; when it fades back toward zero, momentum is weakening.
Watch for volatility expansions or contractions as the indicator accelerates away from or returns toward zero.
Combine it with price action (support/resistance, trendlines, chart patterns) or other momentum tools to reduce false signals.
Apply it across multiple timeframes to look for confluence — this increases reliability compared to using it on just one chart.
Important tips:
Positive spikes (above zero) usually indicate strength or overextension upward; negative spikes (below zero) show weakness or downward exhaustion.
You can reverse the color logic if you want (for example, highlight negative spikes as green for buy interest and positive spikes as red for sell interest) — this is just a visual preference.
This is not a standalone buy/sell system. Always combine it with other tools, market context, and risk management.
Triangle Breakout Strategy with TP/SL, EMA Filter📌 Triangle Breakout Strategy with TP/SL, EMA Filters, and Backtest – Explained.
✅ 1. Pattern Detection – Triangle Breakout
The script scans for triangle patterns by detecting local pivot highs and pivot lows.
It uses two recent highs and two recent lows to draw converging trendlines (upper and lower boundaries of the triangle).
If the price breaks above the upper trendline, a bullish breakout signal is generated.
🎯 2. TP (Take Profit) & SL (Stop Loss)
When a bullish breakout is detected:
A buy order is placed using strategy.entry.
TP and SL levels are calculated relative to the current close price:
TP = 3% above the entry price
SL = 1.5% below the entry price
These are defined using strategy.exit.
📊 3. EMA Filter
An optional filter checks if:
Price is above both EMA 20 and EMA 50
Only if this condition is met, the strategy allows a long entry.
You can toggle the filter on or off with useEMAFilter.
📈 4. Backtesting with Strategy Tester
This script uses strategy() instead of indicator() to enable TradingView’s built-in backtest engine.
Every buy entry and exit (based on TP or SL) is recorded.
📌 5. Visuals
EMA 20 and EMA 50 lines are plotted on the chart.
A label is shown when a breakout is detected: "Breakout Up"
Results (profit, win rate, drawdown, etc.) can be viewed in the Strategy Tester panel.
[blackcat] L3 Ichimoku FusionCOMPREHENSIVE ANALYSIS OF THE L3 ICHIMOKU FUSION INDICATOR
🌐 Overview:
The L3 Ichimoku Fusion is a sophisticated multi-layered technical analysis tool integrating classic Japanese market forecasting techniques with enhanced dynamic elements designed specifically for identifying potential turning points in financial instruments' pricing action.
Key Purpose:
To provide traders with an intuitive yet powerful framework combining established ichimoku principles while incorporating additional validation checkpoints derived from cross-timeframe convergence studies.
THEORETICAL FOUNDATION EXPLAINED
🎓 Conceptual Background:
:
• Conversion & Base Lines tracking intermediate term averages
• Lagging Span providing delayed feedback mechanism
• Lead Spans projecting future equilibrium states
:
• Adaptive parameter scaling options
• Automated labeling system for critical junctures
• Real-time alert infrastructure enabling immediate response capability
PARAMETER CONFIGURATION GUIDE
⚙️ Input Parameters Explained In Detail:
Regional Setting Selection:**
→ Oriental Configuration: Standardized approach emphasizing slower oscillation cycles
→ Occidental Variation: Optimized settings reducing lag characteristics typical of original methodology
Multiplier Adjustment Functionality:**
↔ Allows fine-graining oscillator responsiveness without altering core relationship dynamics
↕ Enables adaptation to various instrument volatility profiles efficiently
Displacement Value Control:**
↓ Controls lead/lag offset positioning relative to current prices
↑ Provides flexibility in adjusting visual representation alignment preferences
DYNAMIC CALCULATION PROCESSES
💻 Algorithmic Foundation:
:
Utilizes highest/lowest extremes over specified lookback windows
Produces more responsive conversions compared to simple MAs
:
→ Confirms directional bias across multiple independent criteria
← Ensures higher probability outcomes reduce random noise influence
:
♾ Creates persistent annotations documenting significant events
🔄 Handles complex state transitions maintaining historical record integrity
VISUALIZATION COMPONENTS OVERVIEW
🎨 Display Architecture Details:
:
→ Solid colored trendlines representing conversion/base relationships
↑ Fill effect overlay differentiating expansion/compression phases
↔ Offset spans positioned according to calculated displacement values
:
→ Green shading indicates positive configuration scenarios
↘ Red filling highlights negative arrangement situations
⟳ Orange transition areas mark transitional periods requiring caution
:
✔️ LE: Long Entry opportunity confirmed
❌ SE: Short Setup validated
☑ XL/XS: Position closure triggers active
✓ RL/RS: Potential re-entry chances emerging
STRATEGIC APPLICATION FRAMEWORK
📋 Practical Deployment Guidelines:
Initial Integration Phase:
Select appropriate timeframe matching trading horizon preference
Configure input parameters aligning with target asset behavior traits
Test thoroughly under simulated conditions prior to live usage
Active Monitoring Procedures:
• Regular observation of cloud formation evolution
• Tracking label placements against actual price movements
• Noting pattern development leading up to signaled entry/exit moments
Decision Making Process Flowchart:
→ Identify clear breakout/crossover events exceeding confirmation thresholds
← Evaluate contextual factors supporting/rejecting indicated direction
↑ Execute trades only after achieving required number of confirming inputs
PERFORMANCE OPTIMIZATION TECHNIQUES
🚀 Refinement Strategies:
Calibration Optimization Approach:
→ Start testing with default suggested configurations
↓ Gradually adjust individual components observing outcome changes
↑ Document findings systematically building personalized version profile
Context Adaptability Methods:
➕ Add supplementary indicators enhancing overall reliability
➖ Remove unnecessary complexity layers if causing confusion
✨ Incorporate custom rules adapting to specific security behaviors
Efficiency Improvement Tactics:
🔧 Streamline redundant processing routines where possible
♻️ Leverage shared data streams whenever feasible
⚡ Optimize refresh frequencies balancing update speed vs computational load
RISK MITIGATION PROTOCOLS
🛡️ Safety Measures Implementation Guide:
Position Sizing Principles:
∅ Never exceed preset maximum exposure limits defined by risk tolerance
± Scale positions proportionally per account size/market capitalization
× Include slippage allowances within planning stages accounting for liquidity variations
Validation Requirements Hierarchy:
☐ Verify signals meet minimum number of concurrent validations
⛔ Ignore isolated occurrences lacking adequate evidence backing
▶ Look for convergent evidence strengthening conviction level
Emergency Response Planning:
↩ Establish predefined exit strategies including trailing stops mechanisms
🌀 Plan worst-case scenario responses ahead avoiding panic reactions
⇄ Maintain contingency plans addressing unexpected adverse developments
USER EXPERIENCE ENHANCEMENT FEATURES
🌟 Additional Utility Functions:
Alert System Infrastructure:
→ Automatic notifications delivered directly to user devices
↑ Message content customized explaining triggered condition specifics
↔ Timing optimization ensuring minimal missed opportunities due to latency issues
Historical Review Capability:
→ Ability to analyze past performance retrospectively
↓ Assess effectiveness across varying market regimes objectively
↗ Generate statistics measuring success/failure rates quantitatively
Community Collaboration Support:
↪ Share personal optimizations benefiting wider trader community
↔ Exchange experiences improving collective understanding base
✍️ Provide constructive feedback aiding ongoing refinement process
CONCLUSION AND NEXT STEPS
This comprehensive guide serves as your roadmap toward mastering the capabilities offered by the L3 Ichimoku Fusion indicator effectively. Success relies heavily on disciplined application combined with continuous learning and adjustment processes throughout implementation journey.
Wishing you prosperous trading endeavors! 👋💰
Volume-Price Momentum IndicatorVolume-Price Momentum Indicator (VPMI)
Overview
The Volume-Price Momentum Indicator (VPMI), developed by Kevin Svenson , is a powerful technical analysis tool designed to identify strong bullish and bearish momentum in price movements, driven by volume dynamics. By analyzing price changes and volume surges over a user-defined lookback period, VPMI highlights potential trend shifts and continuation patterns through a smoothed histogram, optional labels, and background highlights. Ideal for traders seeking to capture momentum-driven opportunities, VPMI is suitable for various markets, including stocks, forex, and cryptocurrencies.
How It Works
VPMI calculates the difference between volume-weighted buying and selling pressure based on price changes over a specified lookback period. It amplifies signals during high-volume periods, applies smoothing to reduce noise, and uses momentum checks to detect sustained trends.
Indicator display:
A histogram that oscillates above (bullish) or below (bearish) a zero line, with brighter colors indicating stronger momentum and faded colors for weaker signals.
Optional labels ("Bullish" or "Bearish") to mark significant momentum shifts.
Optional background highlights to visually emphasize strong trend conditions.
Alerts to notify users when strong bullish or bearish momentum is detected.
Key Features
Customizable Settings:
Adjust the lookback period, volume threshold, momentum length, and smoothing to suit your trading style.
Volume Sensitivity:
Emphasizes price movements during high-volume surges, enhancing signal reliability.
Momentum Detection: Uses linear regression and momentum change to confirm sustained trends, reducing false signals.
Visual Clarity:
Offers a clear histogram with color-coded signals, plus optional labels and backgrounds for enhanced chart readability.
Alerts:
Configurable alerts for strong momentum signals, enabling timely trade decisions.
Inputs and Customization
Lookback Period (Default: 9):
Sets the number of bars to analyze price changes. Higher values smooth signals but may lag.
Volume Threshold (Default: 1.4):
Defines the volume level (relative to a 20-period SMA) that qualifies as a surge, amplifying signals.
High Volume Multiplier (Default: 1.5):
Boosts histogram values during high-volume periods for stronger signals.
Histogram Smoothing Length (Default: 4):
Controls the EMA smoothing applied to the histogram, reducing noise.
Momentum Check Length (Default: 4):
Sets the period for momentum trend analysis (recommended to be less than Lookback Period).
Momentum Threshold (Default: 6):
Defines the minimum momentum change required for strong signals.
Show Labels (Default: Off):
Toggle to display "Bullish" or "Bearish" labels on significant momentum shifts.
Show Backgrounds (Default: Off):
Toggle to highlight chart backgrounds during strong momentum periods.
Bullish/Bearish Colors:
Customize colors for bullish (default: green) and bearish (default: red) signals.
Faded Transparency (Default: 40):
Adjusts the transparency of weaker signals for visual distinction.
How to Use
Interpret Signals:
Above Zero (Green):
Indicates bullish momentum. Bright green suggests strong, sustained buying pressure.
Below Zero (Red):
Indicates bearish momentum. Bright red suggests strong, sustained selling pressure.
Faded Colors:
Weaker momentum, potentially signaling consolidation or trend exhaustion.
Enable Visuals:
Turn on "Show Labels" and "Show Backgrounds" in the settings for additional context on strong momentum signals.
Set Alerts:
Use the built-in alert conditions ("Strong Bullish Momentum" or "Strong Bearish Momentum") to receive notifications when significant trends emerge.
Combine with Other Tools:
Pair VPMI with support/resistance levels, trendlines, or other indicators (e.g., RSI, MACD) for confirmation.
Best Practices
Timeframe:
VPMI works on all timeframes, but shorter timeframes (e.g., 5m, 15m) may produce more signals, while longer timeframes (e.g., 1h, 4h, 1D) offer higher reliability.
Market Conditions:
Most effective in trending markets. In choppy or sideways markets, consider increasing the smoothing length or momentum threshold to filter noise.
Risk Management:
Always use VPMI signals in conjunction with a robust trading plan, including stop-losses and position sizing.
Limitations
Lagging Nature:
As a momentum indicator, VPMI may lag in fast-moving markets due to smoothing and lookback calculations.
False Signals:
In low-volume or ranging markets, signals may be less reliable. Adjust the volume threshold or momentum settings to improve accuracy.
Customization Required:
Optimal settings vary by asset and timeframe. Experiment with inputs to align with your trading strategy.
Why Use VPMI?
VPMI offers a unique blend of volume and price momentum analysis, making it a versatile tool for traders seeking to identify high-probability trend opportunities. Its customizable inputs, clear visuals, and alert capabilities empower users to tailor the indicator to their needs, whether for day trading, swing trading, or long-term analysis.
Get Started
Apply VPMI to your chart, tweak the settings to match your trading style, and start exploring momentum-driven opportunities. For questions or feedback, consult TradingView’s community forums or documentation. Happy trading!
Filtered Swing Pivot S&R )Pivot support and resis🔍 Filtered Swing Pivot S&R - Overview
This indicator identifies and plots tested support and resistance levels using a filtered swing pivot strategy. It focuses on high-probability zones where price has reacted before, helping traders better anticipate future price behavior.
It filters out noise using:
Customizable pivot detection logic
Minimum price level difference
ATR (Average True Range) volatility filter
Confirmation by price retesting the level before plotting
⚙️ Core Logic Explained
✅ 1. Pivot Detection
The script uses Pine Script's built-in ta.pivothigh() and ta.pivotlow() functions to find local highs (potential resistance) and lows (potential support).
Pivot Lookback/Lookahead (pivotLen):
A pivot is confirmed if it's the highest (or lowest) point within a lookback and lookahead range of pivotLen bars.
Higher values = fewer, stronger pivots.
Lower values = more, but potentially noisier levels.
✅ 2. Pending Pivot Confirmation
Once a pivot is detected:
It is not drawn immediately.
The script waits until price re-tests that pivot level. This retest confirms the market "respects" the level.
For example: if price hits a previous high again, it's treated as a valid resistance.
✅ 3. Dual-Level Filtering System
To reduce chart clutter and ignore insignificant levels, two filters are applied:
Fixed Threshold (Minimum Level Difference):
Ensures a new pivot level is not too close to the last one.
ATR-Based Filter:
Dynamically adjusts sensitivity based on current volatility using the formula:
java
Copy
Edit
Minimum distance = ATR × ATR Multiplier
Only pivots that pass both filters are plotted.
✅ 4. Line Drawing
Once a pivot is:
Detected
Retested
Filtered
…a horizontal dashed line is drawn at that level to highlight support or resistance.
Resistance: Red (default)
Support: Green (default)
These lines are:
Dashed for clarity
Extended for X bars into the future (user-defined) for forward visibility
🎛️ Customizable Inputs
Parameter Description
Pivot Lookback/Lookahead Bars to the left and right of a pivot to confirm it
Minimum Level Difference Minimum price difference required between plotted levels
ATR Length Number of bars used in ATR volatility calculation
ATR Multiplier for Pivot Multiplies ATR to determine volatility-based pivot separation
Line Extension (bars) How many future bars the level line will extend for better visibility
Resistance Line Color Color for resistance lines (default: red)
Support Line Color Color for support lines (default: green)
📈 How to Use It
This indicator is ideal for:
Identifying dynamic support & resistance zones that adapt to volatility.
Avoiding false levels by waiting for pivot confirmation.
Visual guidance for entries, exits, stop placements, or take-profits.
🔑 Trade Ideas:
Use support/resistance retests for entry confirmations.
Combine with candlestick patterns or volume spikes near drawn levels.
Use in confluence with trendlines or moving averages.
🚫 What It Does Not Do (By Design)
Does not repaint or remove past levels once confirmed.
Does not include labels or alerts (but can be added).
Does not auto-scale based on timeframes (manual tuning recommended).
🛠️ Possible Enhancements (Optional)
If desired, you could extend the functionality to include:
Labels with “S” / “R”
Alert when a new level is tested or broken
Toggle for support/resistance visibility
Adjustable line width or style
tance indicator
Smarter Money Concepts - OBs [PhenLabs]📊 Smarter Money Concepts - OBs
Version: PineScript™ v6
📌 Description
Smarter Money Concepts - OBs (Order Blocks) is an advanced technical analysis tool designed to identify and visualize institutional order zones on your charts. Order blocks represent significant areas of liquidity where smart money has entered positions before major moves. By tracking these zones, traders can anticipate potential reversals, continuations, and key reaction points in price action.
This indicator incorporates volume filtering technology to identify only the most significant order blocks, eliminating low-quality signals and focusing on areas where institutional participation is likely present. The combination of price structure analysis and volume confirmation provides traders with high-probability zones that may attract future price action for tests, rejections, or breakouts.
🚀 Points of Innovation
Volume-Filtered Block Detection : Identifies only order blocks formed with significant volume, focusing on areas with institutional participation
Advanced Break of Structure Logic : Uses sophisticated price action analysis to detect legitimate market structure breaks preceding order blocks
Dynamic Block Management : Intelligently tracks, extends, and removes order blocks based on price interaction and time-based expiration
Structure Recognition System : Employs technical analysis algorithms to find significant swing points for accurate order block identification
Dual Directional Tracking : Simultaneously monitors both bullish and bearish order blocks for comprehensive market structure analysis
🔧 Core Components
Order Block Detection : Identifies institutional entry zones by analyzing price action before significant breaks of structure, capturing where smart money has likely positioned before moves.
Volume Filtering Algorithm : Calculates relative volume compared to a moving average to qualify only order blocks formed with significant market participation, eliminating noise.
Structure Break Recognition : Uses price action analysis to detect legitimate breaks of market structure, ensuring order blocks are identified only at significant market turning points.
Dynamic Block Management : Continuously monitors price interaction with existing blocks, extending, maintaining, or removing them based on current market behavior.
🔥 Key Features
Volume-Based Filtering : Filter out insignificant blocks by requiring a minimum volume threshold, focusing only on zones with likely institutional activity
Visual Block Highlighting : Color-coded boxes clearly mark bullish and bearish order blocks with customizable appearance
Flexible Mitigation Options : Choose between “Wick” or “Close” methods for determining when a block has been tested or mitigated
Scan Range Adjustment : Customize how far back the indicator looks for structure points to adapt to different market conditions and timeframes
Break Source Selection : Configure which price component (close, open, high, low) is used to determine structure breaks for precise block identification
🎨 Visualization
Bullish Order Blocks : Blue-colored rectangles highlighting zones where bullish institutional orders were likely placed before upward moves, representing potential support areas.
Bearish Order Blocks : Red-colored rectangles highlighting zones where bearish institutional orders were likely placed before downward moves, representing potential resistance areas.
Block Extension : Order blocks extend to the right of the chart, providing clear visualization of these significant zones as price continues to develop.
📖 Usage Guidelines
Order Block Settings
Scan Range : Default: 25. Defines how many bars the indicator scans to determine significant structure points for order block identification.
Bull Break Price Source : Default: Close. Determines which price component is used to detect bullish breaks of structure.
Bear Break Price Source : Default: Close. Determines which price component is used to detect bearish breaks of structure.
Visual Settings
Bullish Blocks Color : Default: Blue with 85% transparency. Controls the appearance of bullish order blocks.
Bearish Blocks Color : Default: Red with 85% transparency. Controls the appearance of bearish order blocks.
General Options
Block Mitigation Method : Default: Wick, Options: Wick, Close. Determines how block mitigation is calculated - “Wick” uses high/low values while “Close” uses close values for more conservative mitigation criteria.
Remove Filled Blocks : Default: Disabled. When enabled, order blocks are removed once they’ve been mitigated by price action.
Volume Filter
Volume Filter Enabled : Default: Enabled. When activated, only shows order blocks formed with significant volume relative to recent average.
Volume SMA Period : Default: 15, Range: 1-50. Number of periods used to calculate the average volume baseline.
Min. Volume Ratio : Default: 1.5, Range: 0.5-10.0. Minimum volume ratio compared to average required to display an order block; higher values filter out more blocks.
✅ Best Use Cases
Identifying high-probability support and resistance zones for trade entries and exits
Finding optimal stop-loss placement behind significant order blocks
Detecting potential reversal areas where price may react after extended moves
Confirming breakout trades when price clears major order blocks
Building a comprehensive market structure map for medium to long-term trading decisions
Pinpointing areas where smart money may have positioned before major market moves
⚠️ Limitations
Most effective on higher timeframes (1H and above) where institutional activity is more clearly defined
Can generate multiple signals in choppy market conditions, requiring additional filtering
Volume filtering relies on accurate volume data, which may be less reliable for some securities
Recent market structure changes may invalidate older order blocks not yet automatically removed
Block identification is based on historical price action and may not predict future behavior with certainty
💡 What Makes This Unique
Volume Intelligence : Unlike basic order block indicators, this script incorporates volume analysis to identify only the most significant institutional zones, focusing on quality over quantity.
Structural Precision : Uses sophisticated break of structure algorithms to identify true market turning points, going beyond simple price pattern recognition.
Dynamic Block Management : Implements automatic block tracking, extension, and cleanup to maintain a clean and relevant chart display without manual intervention.
Institutional Focus : Designed specifically to highlight areas where smart money has likely positioned, helping retail traders align with institutional perspectives rather than retail noise.
🔬 How It Works
1. Structure Identification Process :
The indicator continuously scans price action to identify significant swing points and structure levels within the specified range, establishing a foundation for order block recognition.
2. Break Detection :
When price breaks an established structure level (crossing below a significant low for bearish breaks or above a significant high for bullish breaks), the indicator marks this as a potential zone for order block formation.
3. Volume Qualification :
For each potential order block, the algorithm calculates the relative volume compared to the configured period average. Only blocks formed with volume exceeding the minimum ratio threshold are displayed.
4. Block Creation and Management :
Valid order blocks are created, tracked, and managed as price continues to develop. Blocks extend to the right of the chart until they are either mitigated by price action or expire after the designated timeframe.
5. Continuous Monitoring :
The indicator constantly evaluates price interaction with existing blocks, determining when blocks have been tested, mitigated, or invalidated, and updates the visual representation accordingly.
💡 Note:
Order Blocks represent areas where institutional traders have likely established positions and may defend these zones during future price visits. For optimal results, use this indicator in conjunction with other confluent factors such as key support/resistance levels, trendlines, or additional confirmation indicators. The most reliable signals typically occur on higher timeframes where institutional activity is most prominent. Start with the default settings and adjust parameters gradually to match your specific trading instrument and style.
Rolling ATR Momentum - EnhancedATR Rolling Momentum Indicator – User Manual
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🔍 Overview
The ATR Rolling Momentum Indicator is a dynamic volatility tool built on the Average True Range (ATR). It not only tracks increasing or decreasing momentum but also provides early warnings and confirmation signals for potential breakout moves. It’s especially powerful for futures and options traders looking to align with expanding price action.
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📊 Core Components
✅ ATR Delta (Rolling ATR)
- Definition: Difference between current ATR and past ATR (user-defined lookback).
- Use: Tells whether volatility is expanding (positive delta) or contracting (negative delta).
- Visual: Green line for rising momentum, red for declining.
🟣 ATR Delta Slope
- Definition: Measures acceleration in momentum.
- Use: Helps identify early signs of breakout buildup.
- Visual: Purple line. Watch for slope turning up from below.
🟡 Volatility Squeeze (Yellow Dot)
- Definition: Current ATR is significantly lower than its 20-period average.
- Use: Indicates the market is coiling—possible breakout ahead.
🔼 Momentum Start (Green Triangle)
- Definition: ATR Delta slope turns from negative to positive.
- Use: Early warning to prepare for volatility expansion.
🔷 Breakout Confirmation (Blue Label Up)
- Definition: ATR Delta exceeds its high of the last 10 candles.
- Use: Confirms volatility breakout—trade opportunity if direction aligns.
🟩/🟥 Background Color
- Green Background: Momentum rising (positive ATR delta)
- Red Background: Momentum falling (negative ATR delta)
- Yellow Tint: Active squeeze zone
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✅ How to Use It (Futures/Options Focus)
Step-by-Step:
1. Squeeze Detected (Yellow Dot) → Stay alert. Market is coiling.
2. Green Triangle Appears → Momentum is starting to rise.
3. Background Turns Green → Confirmed rising momentum.
4. Blue Label Appears → Confirmed breakout (enter trade if trend aligns).
Directional Bias:
- Use your main chart setup (price action, EMAs, trendlines, etc.) to decide direction (Call or Put, Long or Short).
- ATR Momentum only tells you how strong the move is—not which way.
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⚙️ Inputs & Settings
- ATR Period: Default 14 (core volatility measure)
- Rolling Lookback: Used to calculate delta (default 5)
- Slope Length: Used to measure acceleration (default 3)
- Squeeze Factor: Default 0.8 — lower = more sensitive squeeze detection
- Breakout Lookback: Checks ATR delta against last X bars (default 10)
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🧠 Pro Tips
- Works great when paired with EMA stacks, price structure, or breakout patterns.
- Avoid taking trades based only on squeeze or momentum—combine with chart confirmation.
- If background turns red after a breakout, it may be losing momentum—book partials or tighten stops.
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🧭 Ideal For:
- Nifty/BankNifty Futures
- Option directional trades (call/put buying)
- Index scalping and momentum swing setups
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Use this tool as your volatility compass—it won't tell you where to go, but it'll tell you when the wind is strong enough to move fast.
End of Manual
Liquidity Heatmap SwiftEdgeDescription
Liquidity Heatmap with Buy/Sell Side (Blue/Red) is a technical analysis tool designed to help traders identify potential liquidity zones in the market by combining swing high/low detection with volume analysis, visualized as a heatmap overlay on the chart. This script highlights areas where significant buying or selling pressure may exist, often acting as support or resistance levels, and provides a clear visual representation of these zones using color-coded heatmap boxes and labeled bubbles.
What It Does
The script identifies key price levels (swing highs and lows) where liquidity is likely to be concentrated, such as stop-loss clusters or pending orders. These levels are then grouped into a heatmap, with blue zones representing potential buy-side liquidity (below the current price) and red zones indicating sell-side liquidity (above the current price). Each zone is marked with a bubble showing the estimated liquidity amount, derived from volume data, to help traders gauge the strength of the level.
How It Works
The script combines three main components to create a comprehensive liquidity visualization:
Swing Highs and Lows Detection:
The script uses the ta.pivothigh and ta.pivotlow functions to identify swing highs and lows over a user-defined lookback period (Swing Length). These levels often represent areas where price has reversed, indicating potential liquidity zones where stop-losses or pending orders may be placed.
Volume Analysis:
Volume data at each swing high/low is captured and averaged over a specified period (Volume Average Length). This volume is then scaled using a multiplier (Volume Multiplier for Liquidity) to estimate the liquidity amount at each level, displayed in thousands (e.g., "10K") on the chart via labeled bubbles.
Heatmap Visualization:
The identified levels are grouped into price bins to form a heatmap. The price range is divided into a user-defined number of bins (Number of Heatmap Bins), and each bin is drawn as a colored box (blue for buy-side, red for sell-side). The transparency of the heatmap boxes can be adjusted (Heatmap Transparency) to ensure they do not obscure the price action.
Why Combine These Components?
The combination of swing highs/lows, volume analysis, and a heatmap provides a powerful way to visualize liquidity in the market. Swing highs and lows are natural points where liquidity tends to accumulate, as they often coincide with areas where traders place stop-losses or pending orders. By incorporating volume data, the script quantifies the potential strength of these levels, giving traders insight into the magnitude of liquidity present. The heatmap visualization then aggregates these levels into a clear, color-coded overlay, making it easy to see where buy-side and sell-side liquidity is concentrated without cluttering the chart.
This mashup is particularly useful because it bridges price action (swing levels), market activity (volume), and visual clarity (heatmap), offering a holistic view of potential support and resistance zones that might influence price movements.
How to Use It
Add the Indicator to Your Chart:
Apply the script to your chart by adding it from the Pine Script library. It will overlay directly on your price chart.
Interpret the Heatmap:
Blue Zones (Buy-Side Liquidity): These appear below the current price and indicate levels where buying pressure or stop-losses from short positions may be located.
Red Zones (Sell-Side Liquidity): These appear above the current price and indicate levels where selling pressure or stop-losses from long positions may be located.
The intensity of the color is controlled by the Heatmap Transparency setting—lower values make the zones more opaque, while higher values make them more transparent.
Analyze the Bubbles:
Each liquidity zone is marked with a bubble showing the estimated liquidity amount in thousands (e.g., "10K"). The size of the bubble is scaled by the Bubble Size Multiplier, with larger bubbles indicating higher liquidity.
Adjust Settings for Your Needs:
Liquidity Settings:
Swing Length: Controls the lookback period for detecting swing highs and lows. A smaller value (e.g., 10) is better for shorter timeframes like 1-minute charts, while a larger value (e.g., 50) suits higher timeframes.
Liquidity Threshold: Defines how close two levels must be to be considered the same, preventing duplicate zones.
Volume Average Length: Sets the period for averaging volume data at swing points.
Volume Multiplier for Liquidity: Scales the volume to estimate liquidity amounts shown in the bubbles.
Lookback Period (Hours): Limits how far back the script looks for liquidity zones.
Use Price Window Filter: If enabled, only shows zones within a price range defined by Liquidity Window (Points per Side).
Heatmap Settings:
Number of Heatmap Bins: Determines how many price bins the heatmap is divided into. More bins create a finer resolution but may clutter the chart.
Heatmap Bin Height (Points): Sets the vertical height of each heatmap box in price points.
Heatmap Transparency: Adjusts the transparency of the heatmap boxes (0 = fully opaque, 100 = fully transparent).
Display Settings:
Bubble Size Multiplier: Scales the size of the bubbles showing liquidity amounts.
Trading Application:
Use the heatmap to identify potential support (blue zones) and resistance (red zones) levels where price may react.
Pay attention to zones with larger bubbles, as they indicate higher liquidity and may have a stronger impact on price.
Combine with other analysis tools (e.g., trendlines, indicators) to confirm trade setups.
What Makes It Original?
This script stands out by integrating swing high/low detection with volume-based liquidity estimation and a heatmap visualization in a single tool. Unlike traditional support/resistance indicators that only plot static lines, this script dynamically aggregates liquidity zones into a heatmap, making it easier to see clusters of potential buying or selling pressure. The addition of volume-derived liquidity amounts in labeled bubbles provides a unique quantitative measure of each zone's strength, helping traders prioritize key levels. The color-coded buy/sell distinction further enhances its utility by visually separating zones based on their likely market impact.
Example Use Case
On a 1-minute chart of EUR/USD, you might set Swing Length to 10 to capture short-term pivots, Lookback Period (Hours) to 4 to focus on recent data, and Liquidity Window to 200 points (20 pips) to show only nearby zones. The heatmap will then display blue zones below the current price where buy-side liquidity may act as support, and red zones above where sell-side liquidity may act as resistance. A bubble showing "50K" at a blue zone indicates significant buy-side liquidity, suggesting a potential bounce if the price approaches that level.
