Annualized Spot-Future DifferenceThe "Annualized Spot-Future Difference" indicator (ASFD) compares the closing prices of a futures contract and its underlying spot asset. It calculates the price difference between the two instruments and annualizes this difference to provide a standardized measure for comparison.
The indicator takes inputs for the futures ticker symbol and the spot ticker symbol, allowing flexibility in selecting the specific assets for analysis. Additionally, it allows the user to input the contract date, which represents the expiration date of the futures contract.
The ASFD indicator plots the annualized difference between the futures and spot prices. It calculates the price difference by subtracting the spot price from the futures price. To annualize this difference, it considers the remaining days to the contract expiration and scales the difference accordingly.
The annualized difference can provide insights into market expectations, as it reflects the market's perception of the future price movement of the underlying asset. A positive value indicates that the futures price is higher than the spot price, potentially suggesting bullish sentiment. Conversely, a negative value suggests bearish sentiment, with the futures price lower than the spot price.
Traders and analysts can utilize the ASFD indicator to identify potential opportunities for arbitrage or evaluate market sentiment regarding the underlying asset. By monitoring changes in the annualized difference over time, they can gain insights into market dynamics and make informed trading decisions.
It's important to note that the ASFD indicator relies on accurate and up-to-date pricing data for both the futures and spot assets. Traders should verify that the selected ticker symbols correspond to the desired instruments and ensure that the contract date aligns with the relevant futures contract expiration.
Overall, the ASFD indicator provides a quantitative measure of the annualized price difference between futures and spot assets, enabling traders and analysts to assess market expectations and identify potential trading opportunities.
Cerca negli script per "sentiment"
NSE Bank Nifty - Arms Index (TRIN)
NSE Bank Nifty – Arms Index TRIN).
How it works?
By default, it considers all the constituents of Bank Nifty for calculation on TRIN
Input configuration parameters:
1. Advance/Decline Formula:
a. Based on same day open and close price
b. Based on todays close compared to previous day close
2. Plots:
a. TRIN
b. Simple moving average of TRIN
c. Advance/Decline Price line
d. Advance/Decline Volume line
About Arms Index (TRIN)
The Arms Index , also called the Short-Term Trading Index (TRIN) is a technical analysis indicator that compares the number of advancing and declining stocks (AD Ratio) to advancing and declining volume (AD volume ). It is used to gauge market sentiment. Richard W. Arms, Jr. invented it in 1967, and it measures the relationship between market supply and demand . It serves as a predictor of future price movements in the market, primarily on an intraday basis. It does this by generating overbought and oversold levels, which indicate when the index (and the majority of stocks in it) will change direction.
• If AD Volume creates a higher ratio than the AD Ratio, TRIN will be below one.
• If AD Volume has a lower ratio than AD Ratio, TRIN will be above one.
• A TRIN reading below one typically accompanies a strong price advance, since the strong volume in the rising stocks helps fuel the rally.
• A TRIN reading above one typically accompanies a strong price decline, since the strong volume in the decliners helps fuel the selloff.
• The Arms Index moves opposite the price trajectory of the Index. As discussed above, a strong price rally will see TRIN move to lower levels. A falling index will see TRIN push higher.
The Formula for Arms Index (TRIN) is:
Stock Ratio = Advancing stocks / Declining Stocks
Volume Ratio = Volume of Advancing stocks / Volume Declining Stocks
TRIN = Stock Ratio / Volume Ratio
What Does the Arms Index (TRIN) Tell You?
The Arms index seeks to provide a more dynamic explanation of overall movements in the composite value of stock exchanges, by analyzing the strength and breadth of these movements.
Neutral State: An index value of 1.0 indicates that the ratio of AD Volume is equal to the AD Ratio. The market is said to be in a neutral state when the index equals 1.0, since the up volume is evenly distributed over the advancing issues and the down volume is evenly distributed over the declining issues.
Bullish State: Many analysts believe that the Arms Index provides a bullish signal when it's less than 1.0, since there's greater volume in the average up stock than the average down stock.
Bearish State: On the other hand, a reading of greater than 1.0 is typically seen as a bearish signal, since there's greater volume in the average down stock than the average up stock.
The farther away from 1.00 the Arms Index value is, the greater the contrast between buying and selling on that day. A value that exceeds 3.00 indicates an oversold market and that bearish sentiment is too dramatic. This could mean an upward reversal in prices/index is coming.
Conversely, a TRIN value that dips below 0.50 may indicate an overbought market and that bullish sentiment is overheating.
Traders look not only at the value of the indicator but also at how it changes throughout the day. They look for extremes in the index value for signs that the market may soon change directions.
Limitations of Using the Arms Index (TRIN)
Here are two examples of instances where problems may occur:
• Suppose that a very bullish day occurs where there are twice as many advancing issues as declining issues and twice as much advancing volume as declining volume . Despite the very bullish trading, the Arms Index would yield only a neutral value of (2/1)/(2/1) = 1.0, suggesting that the index's reading may not be entirely accurate.
• Suppose that another bullish scenario occurs where there are three times as many advancing issues as declining issues and twice as much advancing volume than declining volume . In this case, the Arms Index would actually yield a bearish (3/1)/(2/1) = 1.5 reading, again suggesting an inaccuracy.
Source: www.investopedia.com
Essa - Market Structure Crystal Ball SystemEssa - Market Structure Crystal Ball V2.0
Ever wished you had a glimpse into the market's next move? Stop guessing and start anticipating with the Market Structure Crystal Ball!
This isn't just another indicator that tells you what has happened. This is a comprehensive analysis tool that learns from historical price action to forecast the most probable future structure. It combines advanced pattern recognition with essential trading concepts to give you a unique analytical edge.
Key Features
The Predictive Engine (The Crystal Ball)
This is the core of the indicator. It doesn't just identify market structure; it predicts it.
Know the Odds: Get a real-time probability score (%) for the next structural point: Higher High (HH), Higher Low (HL), Lower Low (LL), or Lower High (LH).
Advanced Analysis: The engine considers the pattern sequence, the speed (velocity) of the move, and its size to find the most accurate historical matches.
Dynamic Learning: The indicator constantly updates its analysis as new price data comes in.
The All-in-One Dashboard
Your command center for at-a-glance information. No need to clutter your screen!
Market Phase: Instantly know if the market is in a "🚀 Strong Uptrend," "📉 Steady Downtrend," or "↔️ Consolidation."
Live Probabilities: See the updated forecasts for HH, HL, LL, and LH in a clean, easy-to-read format.
Confidence Level: The dashboard tells you how confident the algorithm is in its current prediction (Low, Medium, or High).
🎯 Dynamic Prediction Zones
Turn probabilities into actionable price areas.
Visual Targets: Based on the highest probability outcome, the indicator draws a target zone on your chart where the next structure point is likely to form.
Context-Aware: These zones are calculated using recent volatility and average swing sizes, making them adaptive to the current market conditions.
🔍 Fair Value Gap (FVG) Detector
Automatically identify and track key price imbalances.
Price Magnets: FVGs are automatically detected and drawn, acting as potential targets for price.
Smart Tracking: The indicator tracks the status of each FVG (Fresh, Partially Filled, or Filled) and uses this data to refine its predictions.
🌍 Trading Session Analysis
Never lose track of key session levels again.
Visualize Sessions: See the Asia, London, and New York sessions highlighted with colored backgrounds.
Key Levels: Automatically plots the high and low of each session, which are often critical support and resistance levels.
Breakout Alerts: Get notified when price breaks a session high or low.
📈 Multi-Timeframe (MTF) Context
Understand the bigger picture by integrating higher timeframe analysis directly onto your chart.
BOS & MSS: Automatically identifies Breaks of Structure (trend continuation) and Market Structure Shifts (potential reversals) from up to two higher timeframes.
Trade with the Trend: Align your intraday trades with the dominant trend for higher probability setups.
⚙️ How It Works in Simple Terms
1️⃣ It Learns: The indicator first identifies all the past swing points (HH, HL, LL, LH) and analyzes their characteristics (speed, size, etc.).
2️⃣ It Finds a Match: It looks at the most recent price action and searches through hundreds of historical bars to find moments that were almost identical.
3️⃣ It Analyzes the Outcome: It checks what happened next in those similar historical scenarios.
4️⃣ It Predicts: Based on that historical data, it calculates the probability of each potential outcome and presents it to you.
🚀 How to Use This Indicator in Your Trading
Confirmation Tool: Use a high probability score (e.g., >60% for a HH) to confirm your own bullish analysis before entering a trade.
Finding High-Probability Zones: Use the Prediction Zones as potential areas to take profit, or as reversal zones to watch for entries in the opposite direction.
Gauging Market Sentiment: Check the "Market Phase" on the dashboard. Avoid forcing trades when the indicator shows "😴 Low Volatility."
Confluence is Key: This indicator is incredibly powerful when combined with your existing strategy. Use it alongside supply/demand zones, moving averages, or RSI for ultimate confirmation.
We hope this tool gives you a powerful new perspective on the market. Dive into the settings to customize it to your liking!
If you find this indicator helpful, please give it a Boost 👍 and leave a comment with your feedback below! Happy trading!
Disclaimer: All predictions are probabilistic and based on historical data. Past performance is not indicative of future results. Always use proper risk management.
Dual Volume Profiles: Session + Rolling (Range Delineation)Dual Volume Profiles: Session + Rolling (Range Delineation)
INTRO
This is a probability-centric take on volume profile. I treat the volume histogram as an empirical PDF over price, updated in real time, which makes multi-modality (multiple acceptance basins) explicit rather than assumed away. The immediate benefit is operational: if we can read the shape of the distribution, we can infer likely reversion levels (POC), acceptance boundaries (VAH/VAL), and low-friction corridors (LVNs).
My working hypothesis is that what traders often label “fat tails” or “power-law behavior” at short horizons is frequently a tail-conditioned view of a higher-level Gaussian regime. In other words, child distributions (shorter periodicities) sit within parent distributions (longer periodicities); when price operates in the parent’s tail, the child regime looks heavy-tailed without being fundamentally non-Gaussian. This is consistent with a hierarchical/mixture view and with the spirit of the central limit theorem—Gaussian structure emerges at aggregate scales, while local scales can look non-Gaussian due to nesting and conditioning.
This indicator operationalizes that view by plotting two nested empirical PDFs: a rolling (local) profile and a session-anchored profile. Their confluence makes ranges explicit and turns “regime” into something you can see. For additional nesting, run multiple instances with different lookbacks. When using the default settings combined with a separate daily VP, you effectively get three nested distributions (local → session → daily) on the chart.
This indicator plots two nested distributions side-by-side:
Rolling (Local) Profile — short-window, prorated histogram that “breathes” with price and maps the immediate auction.
Session Anchored Profile — cumulative distribution since the current session start (Premkt → RTH → AH anchoring), revealing the parent regime.
Use their confluence to identify range floors/ceilings, mean-reversion magnets, and low-volume “air pockets” for fast traverses.
What it shows
POC (dashed): central tendency / “magnet” (highest-volume bin).
VAH & VAL (solid): acceptance boundaries enclosing an exact Value Area % around each profile’s POC.
Volume histograms:
Rolling can auto-color by buy/sell dominance over the lookback (green = buying ≥ selling, red = selling > buying).
Session uses a fixed style (blue by default).
Session anchoring (exchange timezone):
Premarket → anchors at 00:00 (midnight).
RTH → anchors at 09:30.
After-hours → anchors at 16:00.
Session display span:
Session Max Span (bars) = 0 → draw from session start → now (anchored).
> 0 → draw a rolling window N bars back → now, while still measuring all volume since session start.
Why it’s useful
Think in terms of nested probability distributions: the rolling node is your local Gaussian; the session node is its parent.
VA↔VA overlap ≈ strong range boundary.
POC↔POC alignment ≈ reliable mean-reversion target.
LVNs (gaps) ≈ low-friction corridors—expect quick moves to the next node.
Quick start
Add to chart (great on 5–10s, 15–60s, 1–5m).
Start with: bins = 240, vaPct = 0.68, barsBack = 60.
Watch for:
First test & rejection at overlapping VALs/VAHs → fade back toward POC.
Acceptance beyond VA (several closes + growing outer-bin mass) → traverse to the next node.
Inputs (detailed)
General
Lookback Bars (Rolling)
Count of most-recent bars for the rolling/local histogram. Larger = smoother node that shifts slower; smaller = more reactive, “breathing” profile.
• Typical: 40–80 on 5–10s charts; 60–120 on 1–5m.
• If you increase this but keep Number of Bins fixed, each bin aggregates more volume (coarser bins).
Number of Bins
Vertical resolution (price buckets) for both rolling and session histograms. Higher = finer detail and crisper LVNs, but more line objects (closer to platform limits).
• Typical: 120–240 on 5–10s; 80–160 on 1–5m.
• If you hit performance or object limits, reduce this first.
Value Area %
Exact central coverage for VAH/VAL around POC. Computed empirically from the histogram (no Gaussian assumption): the algorithm expands from POC outward until the chosen % is enclosed.
• Common: 0.68 (≈“1σ-like”), 0.70 for slightly wider core.
• Smaller = tighter VA (more breakout flags). Larger = wider VA (more reversion bias).
Max Local Profile Width (px)
Horizontal length (in pixels) of the rolling bars/lines and its VA/POC overlays. Visual only (does not affect calculations).
Session Settings
RTH Start/End (exchange tz)
Defines the current session anchor (Premkt=00:00, RTH=your start, AH=your end). The session histogram always measures from the most recent session start and resets at each boundary.
Session Max Span (bars, 0 = full session)
Display window for session drawings (POC/VA/Histogram).
• 0 → draw from session start → now (anchored).
• > 0 → draw N bars back → now (rolling look), while still measuring all volume since session start.
This keeps the “parent” distribution measurable while letting the display track current action.
Local (Rolling) — Visibility
Show Local Profile Bars / POC / VAH & VAL
Toggle each overlay independently. If you approach object limits, disable bars first (POC/VA lines are lighter).
Local (Rolling) — Colors & Widths
Color by Buy/Sell Dominance
Fast uptick/downtick proxy over the rolling window (close vs open):
• Buying ≥ Selling → Bullish Color (default lime).
• Selling > Buying → Bearish Color (default red).
This color drives local bars, local POC, and local VA lines.
• Disable to use fixed Bars Color / POC Color / VA Lines Color.
Bars Transparency (0–100) — alpha for the local histogram (higher = lighter).
Bars Line Width (thickness) — draw thin-line profiles or chunky blocks.
POC Line Width / VA Lines Width — overlay thickness. POC is dashed, VAH/VAL solid by design.
Session — Visibility
Show Session Profile Bars / POC / VAH & VAL
Independent toggles for the session layer.
Session — Colors & Widths
Bars/POC/VA Colors & Line Widths
Fixed palette by design (default blue). These do not change with buy/sell dominance.
• Use transparency and width to make the parent profile prominent or subtle.
• Prefer minimal? Hide session bars; keep only session VA/POC.
Reading the signals (detailed playbook)
Core definitions
POC — highest-volume bin (fair price “magnet”).
VAH/VAL — upper/lower bounds enclosing your Value Area % around POC.
Node — contiguous block of high-volume bins (acceptance).
LVN — low-volume gap between nodes (low friction path).
Rejection vs Acceptance (practical rule)
Rejection at VA edge: 0–1 closes beyond VA and no persistent growth in outer bins.
Acceptance beyond VA: ≥3 closes beyond VA and outer-bin mass grows (e.g., added volume beyond the VA edge ≥ 5–10% of node volume over the last N bars). Treat acceptance as regime change.
Confluence scores (make boundary/target quality objective)
VA overlap strength (range boundary):
C_VA = 1 − |VA_edge_local − VA_edge_session| / ATR(n)
Values near 1.0 = tight overlap (stronger boundary).
Use: if C_VA ≥ 0.6–0.8, treat as high-quality fade zone.
POC alignment (magnet quality):
C_POC = 1 − |POC_local − POC_session| / ATR(n)
Higher C_POC = greater chance a rotation completes to that fair price.
(You can estimate these by eye.)
Setups
1) Range Fade at VA Confluence (mean reversion)
Context: Local VAL/VAH near Session VAL/VAH (tight overlap), clear node, local color not screaming trend (or flips to your side).
Entry: First test & rejection at the overlapped band (wick through ok; prefer close back inside).
Stop: A tick/pip beyond the wider of the two VA edges or beyond the nearest LVN, a small buffer zone can be used to judge whether price is truly rejecting a VAL/VAH or simply probing.
Targets: T1 node mid; T2 POC (size up when C_POC is high).
Flip: If acceptance (rule above) prints, flip bias or stand down.
2) LVN Traverse (continuation)
Context: Price exits VA and enters an LVN with acceptance and growing outer-bin volume.
Entry: Aggressive—first close into LVN; Conservative—retest of the VA edge from the far side (“kiss goodbye”).
Stop: Back inside the prior VA.
Targets: Next node’s VA edge or POC (edge = faster exits; POC = fuller rotations).
Note: Flatter VA edge (shallower curvature) tends to breach more easily.
3) POC→POC Magnet Trade (rotation completion)
Context: Local POC ≈ Session POC (high C_POC).
Entry: Fade a VA touch or pullback inside node, aiming toward the shared POC.
Stop: Past the opposite VA edge or LVN beyond.
Target: The shared POC; optional runner to opposite VA if the node is broad and time-of-day is supportive.
4) Failed Break (Reversion Snap-back)
Context: Push beyond VA fails acceptance (re-enters VA, outer-bin growth stalls/shrinks).
Entry: On the re-entry close, back toward POC.
Stop/Target: Stop just beyond the failed VA; target POC, then opposite VA if momentum persists.
How to read color & shape
Local color = most recent sentiment:
Green = buying ≥ selling; Red = selling > buying (over the rolling window). Treat as context, not a standalone signal. A green local node under a blue session VAH can still be a fade if the parent says “over-valued.”
Shape tells friction:
Fat nodes → rotation-friendly (fade edges).
Sharp LVN gaps → traversal-friendly (momentum continuation).
Time-of-day intuition
Right after session anchor (e.g., RTH 09:30): Session profile is young and moves quickly—treat confluence cautiously.
Mid-session: Cleanest behavior for rotations.
Close / news: Expect more traverses and POC migrations; tighten risk or switch playbooks.
Risk & execution guidance
Use tight, mechanical stops at/just beyond VA or LVN. If you need wide stops to survive noise, your entry is late or the node is unstable.
On micro-timeframes, account for fees & slippage—aim for targets paying ≥2–3× average cost.
If acceptance prints, don’t fight it—flip, reduce size, or stand aside.
Suggested presets
Scalp (5–10s): bins 120–240, barsBack 40–80, vaPct 0.68–0.70, local bars thin (small bar width).
Intraday (1–5m): bins 80–160, barsBack 60–120, vaPct 0.68–0.75, session bars more visible for parent context.
Performance & limits
Reuses line objects to stay under TradingView’s max_lines_count.
Very large bins × multiple overlays can still hit limits—use visibility toggles (hide bars first).
Session drawings use time-based coordinates to avoid “bar index too far” errors.
Known nuances
Rolling buy/sell dominance uses a simple uptick/downtick proxy (close vs open). It’s fast and practical, but it’s not a full tape classifier.
VA boundaries are computed from the empirical histogram—no Gaussian assumption.
This script does not calculate the full daily volume profile. Several other tools already provide that, including TradingView’s built-in Volume Profile indicators. Instead, this indicator focuses on pairing a rolling, short-term volume distribution with a session-wide distribution to make ranges more explicit. It is designed to supplement your use of standard or periodic volume profiles, not replace them. Think of it as a magnifying lens that helps you see where local structure aligns with the broader session.
How to trade it (TL;DR)
Fade overlapping VA bands on first rejection → target POC.
Continue through LVN on acceptance beyond VA → target next node’s VA/POC.
Respect acceptance: ≥3 closes beyond VA + growing outer-bin volume = regime change.
FAQ
Q: Why 68% Value Area?
A: It mirrors the “~1σ” idea, but we compute it exactly from empirical volume, not by assuming a normal distribution.
Q: Why are my profiles thin lines?
A: Increase Bars Line Width for chunkier blocks; reduce for fine, thin-line profiles.
Q: Session bars don’t reach session start—why?
A: Set Session Max Span (bars) = 0 for full anchoring; any positive value draws a rolling window while still measuring from session start.
Changelog (v1.0)
Dual profiles: Rolling + Session with independent POC/VA lines.
Session anchoring (Premkt/RTH/AH) with optional rolling display span.
Dynamic coloring for the rolling profile (buying vs selling).
Fully modular toggles + per-feature colors/widths.
Thin-line rendering via bar line width.
Volume Point of Control with Fib Based Profile🍀Description:
This indicator is a comprehensive volume profile analysis tool designed to identify key price levels based on trading activity within user-defined timeframes. It plots the Point of Control (POC), Value Area High (VAH), and Value Area Low (VAL), along with dynamically calculated Fibonacci levels derived from the developing period's range. It offers extensive customization for both historical and developing levels.
🍀Core Features:
Volume Profiling (POC, VAH, VAL):
Calculates and plots the POC (price level with the highest volume), VAH, and VAL for a selected timeframe (e.g., Daily, Weekly).
The Value Area percentage is configurable. 70% is common on normal volume profiles, but this script allows you to configure multiple % levels via the fib levels. I recommend using 2 versions of this indicator on a chart, one has Value Area at 1 (100% - high and low of lookback) and the second is a specified VA area (i.e. 70%) like in the chart snapshot above. See examples at the bottom.
Historical Levels:
Plots POC, VAH, and VAL from previous completed periods.
Optionally displays only "Unbroken" levels – historical levels that price has not yet revisited, which can act as stronger magnets or resistance/support.
The user can manage the number of historical lines displayed to prevent chart clutter.
Developing Levels:
Shows the POC, VAH, and VAL as they form in real-time during the current, incomplete period. This provides insight into intraday/intra-period value migration.
Dynamic Fibonacci Levels:
Calculates and plots Fibonacci retracement/extension levels based dynamically on the range between the developing POC and the developing VAH/VAL.
Offers 8 configurable % levels above and below POC that can be toggled on/off.
Visual Customization:
Extensive options for colors, line styles, and widths for all plotted levels.
Optional gradient fill for the Value Area that visualizes current price distance from POC - option to invert the colors as well.
Labels for developing levels and Fibonacci levels for easy identification.
🍀Characteristics:
Volume-Driven: Levels are derived from actual trading volume, reflecting areas of high participation and price agreement/disagreement.
Timeframe Specific: The results are entirely dependent on the chosen profile timeframe.
Dynamic & Static Elements: Developing levels and Fibs update live, while historical levels remain fixed once their period closes.
Lagging (Historical) & Potentially Leading: Historical levels are based on the past, but are often respected by future price action. Developing levels show current dynamics.
🍀How to Use It:
Identifying Support & Resistance: Historical and developing POCs, VAHs, and VALs are often key areas where price may react. Unbroken levels are particularly noteworthy.
Market Context & Sentiment: Trading above the POC suggests bullish strength/acceptance of higher prices, while trading below suggests bearishness/acceptance of lower prices.
Entry/Exit Zones: Interactions with these levels (rejections, breakouts, tests) can provide potential entry or exit signals, especially when confirming with other analysis methods.
Dynamic Targets: The Fibonacci levels calculated from the developing POC-VA range offer potential intraday/intra-period price targets or areas of interest.
Understanding Value Migration: Observing the movement of the developing POC/VAH/VAL throughout the period reveals where value is currently being established.
🍀Potential Drawbacks:
Input Sensitivity: The choice of timeframe, Value Area percentage, and volume resolution heavily influences the generated levels. Experimentation is needed for optimal settings per instrument/market. (I've found that Range Charts can provide very accurate volume levels on TV since the time element is removed. This helps to refine the accuracy of price levels with high volume.)
Volume Data Dependency: Requires accurate volume data. May be less reliable on instruments with sparse or questionable volume reporting.
Chart Clutter: Enabling all features simultaneously can make the chart busy. Utilize the line management inputs and toggle features as needed.
Not a Standalone Strategy: This indicator provides context and key levels. It should be used alongside other technical analysis tools and price action reading for robust decision-making.
Developing Level Fluctuation: Developing POC/VA/Fib levels can shift considerably, especially early in a new period, before settling down as more volume accumulates and time passes.
🍀Recommendations/Examples:
I recommend have this indicator on your chart twice, one has the VA set at 1 (100%) and has the fib levels plotted. The second has the VA set to 0.7 (70%) to highlight the defined VA.
Here is an example with 3 on a chart. VA of 100%, VA of 80%, and VA of 20%
Volume Patterns [SS]Hey everyone,
Been a while since doing anything with Pinescript.
Here is my iteration of a Volume Pattern identification, inspired by Bulkowski's work on patterns and volume.
The indicator aims to identify the 4 major types of volume patterns, these are:
Bullish Breakout Volume
Bearish Breakout Volume
Inverted Domes
Domes
Classification
These patterns are all assigned to a classification based on theory. For example, dome volume is usually bearish, inverted dome is usually bullish, etc. etc. However, in order to accommodate changing sentiments and volatility, I have coded logic into the indicator to assess for the actual sentiment associated with these patterns itself.
The indicator calculates the average return associated with each pattern, scaling the data into a percent return. It then has the ability to re-scale the target using the close price associated with the pattern at the time of pattern signaling, to calculate the target price and plot the target on the chart for you.
Additionally, it provides you with the following:
Labels to signal when a pattern has happened
A table that shows you the average returns associated with the 4 major patterns
Target lines with labels that visually show you the target price associated with the pattern, as well as which pattern they are associated with.
All of these things can be toggled on or off depending on your preference.
Customizing the indicator
In addition to being able to toggle the visuals on or off depending on what you want to see or not see, there are some minor customization abilities in terms of training the indicator to recognize the patterns and predict the TP.
The first one is the Training length
In the settings, you will see "Train", and the default is 500. This is the amount the indicator is looking back in history to learn the patterns and returns associated with them. This 500 is appropriate in most cases and on most timeframes.
Lastly, the Lookforward Length
The look forward length represents the number of bars forward you want to determine the returns for. It is defaulted to 10, but you can modify it.
So, if you are on the 1-Minute chart and have the look forward set to 10, then once a signal happens, the target price is calculated based on 10 minutes from the time of signal. You can increase this or decrease this based on your preference.
Longer look forwards can be good for swingers but should be used on the larger timeframes, shorter are good for scalpers but should be used on the shorter timeframes.
The indicator's use is incredibly simple, you'll pick it up in no time!
Hope you enjoy it and as always, safe trades!
Just an FYI for those who may have questions:
The indicator is open source. This means you are free to take it and modify it as you wish. You do not need to ask me.
Please read the description carefully, as 100% of questions I am asked about indicators are covered in the description. ;-)
Have a good one guys and gals! 🚀🚀🚀
Waldo Cloud Bollinger Bands
Waldo Cloud Bollinger Bands Indicator Description for TradingView
Title: Waldo Cloud Bollinger Bands
Short Title: Waldo Cloud BB
Overview:
The Waldo Cloud Bollinger Bands indicator is a sophisticated tool designed for traders looking to combine the volatility analysis of Bollinger Bands with the momentum insights of the Relative Strength Index (RSI) and moving average crossovers. This indicator overlays on your chart, providing a visual representation that helps in identifying potential trading opportunities based on price action, momentum, and trend direction.
Concept:
This indicator merges three key technical analysis concepts:
Bollinger Bands: These are used to measure market volatility. The bands consist of a central moving average (basis) with an upper and lower band that are standard deviations away from this average. In this indicator, you can customize the type of moving average used for the basis (SMA, EMA, SMMA, WMA, VWMA), the length of the period, the source price, and the standard deviation multiplier, offering flexibility to adapt to different market conditions.
Relative Strength Index (RSI): The RSI is incorporated to provide insight into the momentum of price movements. Users can adjust the RSI length and overbought/oversold levels and even choose the price source for RSI calculation, allowing for tailored momentum analysis. The RSI values influence the cloud color between the Bollinger Bands, signaling market conditions.
Moving Average Crossovers: Two moving averages with customizable lengths and types are used to identify trend direction through crossovers. A fast MA (default 20 periods) and a slow MA (default 50 periods) are plotted when enabled, helping to signal potential bullish or bearish market conditions when they cross over each other.
Functionality:
Bollinger Bands Calculation: The basis of the Bollinger Bands is calculated using a user-defined moving average type, with a customizable length, source, and standard deviation multiplier. The upper and lower bands are then plotted around this basis.
RSI Calculation: The RSI is computed using a user-specified source, length, and overbought/oversold levels. This RSI value is used to determine the color of the cloud between the Bollinger Bands, which visually represents market sentiment:
Purple when RSI is overbought.
Blue when RSI is oversold.
Green for bullish conditions (when the fast MA crosses above the slow MA, RSI is bullish, and the price is above the slow MA).
Red for bearish conditions (when the fast MA crosses below the slow MA, RSI is bearish, and the price is below the slow MA).
Gray for neutral conditions.
Trend Analysis: The indicator uses two moving averages to help determine the trend direction.
When the fast MA crosses over the slow MA, it suggests a potential change in trend direction, which, combined with RSI conditions, provides a more comprehensive trading signal.
Customization:
Users can select the type of moving average for all calculations through the "Global MA Type" setting, ensuring consistency in how trends and volatility are interpreted.
The Bollinger Bands settings allow for adjustments in length, source, standard deviation, and offset, giving traders control over how volatility is measured.
RSI settings include the ability to change the RSI source, length, and overbought/oversold thresholds, which can be fine-tuned to match trading strategies.
The option to show or hide moving averages provides clarity on the chart, focusing on either the Bollinger Bands or including the MA crossovers for trend analysis.
Usage:
This indicator is ideal for traders who incorporate both volatility and momentum in their trading decisions.
By observing the color changes in the cloud, along with the position of the price relative to the moving averages, traders can gauge potential entry and exit points.
For instance, a green cloud with a price above the slow MA might suggest a strong buying opportunity, while a red cloud with a price below might indicate selling pressure.
Conclusion:
The Waldo Cloud Bollinger Bands indicator offers a unique blend of volatility, momentum, and trend analysis, providing traders with a multi-faceted view of market conditions. Its customization options make it adaptable to various trading styles and market environments, making it a valuable addition to any trader's toolkit on Trading View.
SW monthly Gann Days**Script Description:**
The script you are looking at is based on the work of W.D. Gann, a famous trader and market analyst in the early 20th century, known for his use of geometry, astrology, and numerology in market analysis. Gann believed that certain days in the market had significant importance, and he observed that markets often exhibited significant price moves around specific dates. These dates were typically associated with cyclical patterns in price movements, and Gann referred to these as "Gann Days."
In this script, we have focused on highlighting certain days of the month that Gann believed to have an influence on market behavior. The specific days in question are the **6th to 7th**, **9th to 10th**, **14th to 15th**, **19th to 20th**, **23rd to 24th**, and **29th to 31st** of each month. These ranges are based on Gann’s theory that there are recurring time cycles in the market that cause turning points or critical price movements to occur around certain days of the month.
### **Why Gann Used These Days:**
1. **Mathematical and Astrological Cycles:**
Gann believed that markets were influenced by natural cycles, and that certain dates (or combinations of dates) played a critical role in the price movements. These specific days are part of his broader theory of "time cycles" where the market would often change direction, reverse, or exhibit significant volatility on particular days. Gann's research was based on both mathematical principles and astrological observations, leading him to assign importance to these days.
2. **Gann's Universal Timing Theory:**
According to Gann, financial markets operate in a universe governed by geometric and astrological principles. These cycles repeat themselves over time, and specific days in a given month correspond to key turning points within these repeating cycles. Gann found that the 6th to 7th, 9th to 10th, 14th to 15th, 19th to 20th, 23rd to 24th, and 29th to 31st often marked significant changes in the market, making them particularly important for traders to watch.
3. **Market Psychology and Sentiment:**
These specific days likely correspond to key moments where market participants tend to react in predictable ways, influenced by past market behavior on similar dates. For example, news events or scheduled economic reports might fall within these time windows, causing the market to respond in a particular way. Gann's method involves using these cyclical patterns to predict turning points in market prices, enabling traders to anticipate when the market might make a reversal or face a significant shift in direction.
4. **Turning Points:**
Gann believed that markets often reversed or encountered critical points around specific dates. This is why he considered certain days more important than others. By identifying and focusing on these days, traders can better anticipate the market’s movement and make more informed trading decisions.
5. **Numerology:**
Gann also utilized numerology in his trading system, believing that numbers, and particularly certain key numbers, had significance in predicting market movements. The days selected in this script may correspond to numerological patterns that Gann identified in his analysis of the markets, such as recurring numbers in his astrological and geometric systems.
### **Purpose of the Script:**
This script highlights these "Gann Days" within a trading chart for 2024 and 2025. The color-coding or background highlighting is intended to draw attention to these dates, so traders can observe the potential for significant market movements during these times. By identifying these specific dates, traders following Gann's theories may gain insights into possible turning points, corrections, or key price movements based on the market's historical behavior around these days.
Overall, Gann’s use of specific days was based on his deep belief in the cyclical nature of the market and his attempt to tie those cycles to the natural laws of time, geometry, and astrology. By focusing on these dates, Gann aimed to give traders an edge in predicting significant market events and price shifts.
Dominant Smoothed Volume Pro Smoothed Volume Pro provides a useful tool designed to provide traders with a deeper understanding of market dynamics by analyzing buy and sell volume across multiple timeframes. Unlike traditional volume indicators, this script normalizes volume data from lower timeframes to align with the current chart's timeframe, providing an apples-to-apples comparison. The result is a visual histogram representation of the dominant buy or sell activity, smoothed over 5 different periods to reflect momentum shifts and enhance clarity.
Core Methodology
1. Multi-Timeframe Volume Analysis
This indicator leverages data from five different lower timeframes, each chosen dynamically based on the current chart's timeframe. By aggregating and normalizing these granular data points, the indicator captures subtle shifts in buy and sell volume that might otherwise go unnoticed. This multi-timeframe approach allows for a more detailed and accurate representation of market activity.
2. Data Normalization
Normalization is a critical component of this indicator. It ensures that volume data from lower timeframes is scaled appropriately to match the total volume of the current chart's timeframe. This step eliminates discrepancies caused by varying time intervals, providing a more meaningful comparison of volume trends across different periods.
3. Smoothing for Momentum Representation
The indicator employs five customizable smoothing factors to smooth out noisy volume data.
Each smoothing factor is distinctly color-coded in the histogram and table for intuitive analysis, helping traders quickly identify prevailing trends.
Features and Benefits
➖Customizable Smoothing Factors: Choose from five different smoothing factors, each with its unique settings for line styles, colors, and extensions.
➖Normalized Buy and Sell Volume: Displays normalized buy and sell volumes as a percentage of total activity, aiding in quick decision-making.
➖Visual Cues: Color-coded columns and labels help identify dominant trends at a glance, with high-opacity fills for visual clarity.
➖Dynamic Table: A built-in table summarizes smoothed volume data for each smoothing factor, offering a quick overview of bullish and bearish percentages.
➖Momentum Signals: Detect significant shifts in volume momentum with visually distinct alerts for high relative volumes, including special symbols like "⚡" and "🔥."
Practical Applications
➖Identifying Market Sentiment: Quickly determine whether the market is dominated by buyers or sellers at any given moment.
➖Spotting Reversals: Use momentum shifts in smoothed volume to anticipate potential trend reversals.
➖Enhancing Entry and Exit Points: Combine this indicator with other technical tools to refine entry and exit points in your trading strategy.
Why This Indicator Stands Out
Many existing volume indicators focus solely on raw or single-timeframe data, which can be misleading or incomplete. This indicator sets itself apart by:
Utilizing multi-timeframe data to provide a holistic view of market activity.
Applying robust normalization techniques to ensure data consistency.
Offering advanced smoothing options to emphasize actionable momentum signals.
This unique combination of features makes it an indispensable tool for traders seeking to enhance their market analysis and decision-making process.
As always, by combining the Smoothed Volume Pro with other tools, traders ensure that they are not relying on a single indicator. This layered approach can reduce the likelihood of false signals and improve overall trading accuracy.
Here's an additional visual representation using the plot fills:
Wick Detection (1 and 0) - AYNETDetailed Scientific Explanation
1. Wick Detection Logic
Definition of a Wick:
A wick, also known as a shadow, represents the price action outside the range of a candlestick's body (the region between open and close).
Upper Wick: Occurs when the high value exceeds the greater of open and close.
Lower Wick: Occurs when the low value is lower than the smaller of open and close.
Upper Wick Detection:
pinescript
Kodu kopyala
bool has_upper_wick = high > math.max(open, close)
This checks if the high price of the candle is greater than the maximum of the open and close prices. If true, an upper wick exists.
Lower Wick Detection:
pinescript
Kodu kopyala
bool has_lower_wick = low < math.min(open, close)
This checks if the low price of the candle is less than the minimum of the open and close prices. If true, a lower wick exists.
2. Binary Representation
The presence of a wick is encoded as a binary value for simplicity and computational analysis:
Upper Wick: Represented as 1 if present, otherwise 0.
pinescript
Kodu kopyala
float upper_wick_binary = has_upper_wick ? 1 : 0
Lower Wick: Represented as 1 if present, otherwise 0. This value is inverted (-1) for visualization purposes.
pinescript
Kodu kopyala
float lower_wick_binary = has_lower_wick ? 1 : 0
3. Visualization with Histograms
The plot function is used to create histograms for visualizing the binary wick data:
Upper Wicks: Plotted as positive values with green columns:
pinescript
Kodu kopyala
plot(upper_wick_binary, title="Upper Wick", color=color.new(color.green, 0), style=plot.style_columns, linewidth=2)
Lower Wicks: Plotted as negative values with red columns:
pinescript
Kodu kopyala
plot(lower_wick_binary * -1, title="Lower Wick", color=color.new(color.red, 0), style=plot.style_columns, linewidth=2)
Features and Applications
1. Wick Visualization:
Upper wicks are displayed as positive green columns.
Lower wicks are displayed as negative red columns.
This provides a clear visual representation of wick presence in historical data.
2. Technical Analysis:
Wick formations often indicate market sentiment:
Upper Wicks: Sellers pushed the price lower after buyers drove it higher, signaling rejection at the top.
Lower Wicks: Buyers pushed the price higher after sellers drove it lower, signaling rejection at the bottom.
3. Signal Generation:
Traders can use wick detection to build strategies, such as identifying key price levels or market reversals.
Enhancements and Future Improvements
1. Wick Length Measurement
Instead of binary detection, measure the actual length of the wick:
pinescript
Kodu kopyala
float upper_wick_length = high - math.max(open, close)
float lower_wick_length = math.min(open, close) - low
This approach allows for thresholds to identify significant wicks:
pinescript
Kodu kopyala
bool significant_upper_wick = upper_wick_length > 10 // For wicks longer than 10 units.
bool significant_lower_wick = lower_wick_length > 10
2. Alerts for Long Wicks
Trigger alerts when significant wicks are detected:
pinescript
Kodu kopyala
alertcondition(significant_upper_wick, title="Long Upper Wick", message="A significant upper wick has been detected.")
alertcondition(significant_lower_wick, title="Long Lower Wick", message="A significant lower wick has been detected.")
3. Combined Wick Analysis
Analyze both upper and lower wicks to assess volatility:
pinescript
Kodu kopyala
float total_wick_length = upper_wick_length + lower_wick_length
bool high_volatility = total_wick_length > 20 // Combined wick length exceeds 20 units.
Conclusion
This script provides a compact and computationally efficient way to detect candlestick wicks and represent them as binary data. By visualizing the data with histograms, traders can easily identify wick formations and use them for technical analysis, signal generation, and volatility assessment. The approach can be extended further to measure wick length, detect significant wicks, and integrate these insights into automated trading systems.
Iceberg Trade Revealer [CHE]Unveiling Iceberg Trades: A Deep Dive into Low Volatility Market Phases
Introduction
In the dynamic world of trading, hidden forces often influence market movements in ways that aren't immediately apparent. One such force is the phenomenon of iceberg trades—large orders that are concealed to prevent significant market impact. This presentation explores the concept of iceberg trades, explains why they are typically hidden during periods of low volatility, and introduces an indicator designed to reveal these elusive trades.
Agenda
1. Understanding Iceberg Trades
- Definition and Purpose
- Impact on Market Dynamics
2. The Low Volatility Concealment
- Why Low Volatility Phases?
- Strategies Behind Hiding Large Orders
3. Introducing the Iceberg Trade Revealer Indicator
- How the Indicator Works
- Key Components and Calculations
4. Demonstration and Use Cases
- Interpreting the Indicator Signals
- Practical Trading Applications
5. Conclusion
- Summarizing the Insights
- Q&A Session
1. Understanding Iceberg Trades
Definition and Purpose
- Iceberg Trades are large single orders divided into smaller lots to disguise the total order quantity.
- Traders use iceberg orders to minimize market impact and avoid unfavorable price movements.
Impact on Market Dynamics
- Concealed Volume: Iceberg orders hide true supply and demand levels.
- Price Stability: They prevent sudden spikes or drops by releasing orders gradually.
- Market Sentiment: Their presence can influence perceptions of market strength or weakness.
2. The Low Volatility Concealment
Why Low Volatility Phases?
- Less Market Attention: Low volatility periods attract fewer traders, making it easier to conceal large orders.
- Reduced Slippage: Prices are more stable, reducing the risk of executing orders at unfavorable prices.
- Strategic Advantage: Large players can accumulate or distribute positions without tipping off the market.
Strategies Behind Hiding Large Orders
- Order Splitting: Breaking down large orders into smaller pieces.
- Time Slicing: Executing orders over an extended period.
- Algorithmic Trading: Using sophisticated algorithms to optimize order execution.
3. Introducing the Iceberg Trade Revealer Indicator
How the Indicator Works
- Core Thesis: Iceberg trades can be detected by analyzing periods of unusually low volatility.
- Volatility Analysis: Uses the Average True Range (ATR) and Bollinger Bands to identify low volatility phases.
- Signal Generation: Marks periods where iceberg trades are likely occurring.
Key Components and Calculations
1. Average True Range (ATR)
- Measures market volatility over a specified period.
- Lower ATR values indicate less price movement.
2. Bollinger Bands
- Creates a volatility envelope around the ATR.
- Bands tighten during low volatility and widen during high volatility.
3. Timeframe Adjustments
- Utilizes multiple timeframes to enhance signal accuracy.
- Options for auto, multiplier, or manual timeframe selection.
4. Signal Conditions
- Iceberg Trade Detection: ATR falls below the lower Bollinger Band.
- Revealed Volatility: ATR rises above the upper Bollinger Band, indicating potential market moves after iceberg trades.
4. Demonstration and Use Cases
Interpreting the Indicator Signals
- Iceberg Trade Zones: Highlighted areas where large hidden orders are likely.
- Revealed Volatility Zones: Areas indicating the market's response to the execution of iceberg trades.
Practical Trading Applications
- Entry and Exit Points: Use signals to time trades alongside institutional activity.
- Risk Management: Adjust strategies during detected low volatility phases.
- Market Analysis: Gain insights into underlying market mechanics.
5. Conclusion
Summarizing the Insights
- Iceberg Trades play a significant role in market movements, especially when concealed during low volatility phases.
- The Iceberg Trade Revealer Indicator provides a tool to uncover these hidden activities, offering traders a strategic edge.
- Understanding and utilizing this indicator can enhance trading decisions by aligning them with the actions of major market players.
Best regards Chervolino ( Volker )
Q&A Session
- Questions and Discussions: Open the floor for any queries or further explanations.
Thank You!
By delving into the hidden aspects of market activity, traders can better navigate the complexities of financial markets. The Iceberg Trade Revealer Indicator serves as a bridge between observable market data and the concealed strategies of large institutions.
References
- Average True Range (ATR): A technical analysis indicator that measures market volatility.
- Bollinger Bands: A volatility indicator that creates a band of three lines which are plotted in relation to a security's price.
- Iceberg Orders: Large orders divided into smaller lots to hide the actual order quantity.
Note: Always consider multiple factors when making trading decisions. Indicators provide tools, but they do not guarantee results.
Educational Content Disclaimer:
Disclaimer:
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Enhanced High Volume AbsorptionDescription of the "Enhanced High Volume Absorption" Indicator
The "Enhanced High Volume Absorption" indicator is a specialized trading tool designed for the TradingView platform, optimized for the 15-minute chart timeframe. It offers traders a unique approach to analyzing market momentum and strength by focusing on significant volume movements, which are often precursors to major price shifts.
What the Indicator Does:
High Volume Detection: This indicator identifies periods of high volume trading, which is a key indicator of strong market interest. High volume periods often precede significant price movements, making this an essential tool for anticipating market trends.
Volume Absorption Analysis: It analyzes the absorption of volume in the market. Absorption here refers to situations where the market is able to absorb trading volumes significantly higher than the average without a corresponding substantial change in price. This can be an indication of strong underlying market strength or weakness.
Price Movement Correlation: The script correlates volume spikes with price movements (upward or downward) to provide context to the volume absorption. This correlation helps determine whether the absorption is due to buying pressure (bullish indication) or selling pressure (bearish indication).
How It Does It:
Moving Average Comparisons: The script calculates short-term and long-term Simple Moving Averages (SMAs) of trading volumes. By comparing current volumes to these averages, it determines if the current volume is significantly higher than usual.
Volume Thresholds: It uses user-defined multipliers and minimum volume thresholds to filter significant volume events, ensuring that only notable volume spikes are considered.
Impact Analysis: Alongside volume analysis, the script computes the price change and its impact as a percentage of the current price, providing insights into the magnitude of price movements during these high-volume periods.
How to Use It:
Market Entry and Exit Points: The indicator can be used to spot potential entry and exit points. For example, a high volume absorption event with a minimal price change might indicate a strong support or resistance level.
Confirming Market Sentiment: It can be used in conjunction with other technical indicators to confirm market trends or reversals. High volume absorption aligned with other bullish or bearish indicators can provide a stronger case for a market move.
Scalping and Short-Term Trading: Optimized for the 15-minute timeframe, this indicator is particularly useful for scalpers and short-term traders. It helps in identifying quick market movements and can be a crucial part of a scalping strategy.
Originality and Underlying Concepts:
The originality of this indicator lies in its specific focus on volume absorption and its impact on price, especially tailored for short-term trading scenarios. Unlike many indicators that only analyze price movements or standard volume analysis, this script delves deeper into how the market is reacting to volume spikes, offering a nuanced view of market dynamics
that is often overlooked. The concept of volume absorption, coupled with the analysis of price movement direction, provides a unique perspective on market strength or weakness.
This tool is distinct in its approach as it doesn't just follow trends or provide generic scalping signals. Instead, it offers a methodical analysis of volume dynamics in relation to price action. By focusing on how the market absorbs volume, the indicator gives traders insights into whether current market movements are backed by substantial trading activity or if they are more likely to be short-lived.
Understanding volume absorption is crucial, especially in a 15-minute trading environment where market movements are swift and require quick decision-making. This indicator aids in identifying those moments when the market shows a significant reaction (or lack thereof) to large volumes, indicating potential setup for a strong move or reversal.
In summary, the "Enhanced High Volume Absorption" indicator is a valuable tool for traders who want to incorporate volume analysis into their trading strategy, especially in a fast-paced, short-term trading environment. It provides a deeper understanding of market dynamics, enabling traders to make more informed decisions based on the interplay between volume and price action.
DYNAMIC TRADING DASHBOARDStudy Material for the "Dynamic Trading Dashboard"
This Dynamic Trading Dashboard is designed as an educational tool within the TradingView environment. It compiles commonly used market indicators and analytical methods into one visual interface so that traders and learners can see relationships between indicators and price action. Understanding these indicators, step by step, can help traders develop discipline, improve technical analysis skills, and build strategies. Below is a detailed explanation of each module.
________________________________________
1. Price and Daily Reference Points
The dashboard displays the current price, along with percentage change compared to the day’s opening price. It also highlights whether the price is moving upward or downward using directional symbols. Alongside, it tracks daily high, low, open, and daily range.
For traders, daily levels provide valuable reference points. The daily high and low are considered intraday support and resistance, while the median price of the day often acts as a pivot level for mean reversion traders. Monitoring these helps learners see how price oscillates within daily ranges.
________________________________________
2. VWAP (Volume Weighted Average Price)
VWAP is calculated as a cumulative average price weighted by volume. The dashboard compares the current price with VWAP, showing whether the market is trading above or below it.
For traders, VWAP is often a guide for institutional order flow. Price trading above VWAP suggests bullish sentiment, while trading below VWAP indicates bearish sentiment. Learners can use VWAP as a training tool to recognize trend-following vs. mean reversion setups.
________________________________________
3. Volume Analysis
The system distinguishes between buy volume (when the closing price is higher than the open) and sell volume (when the closing price is lower than the open). A progress bar highlights the ratio of buying vs. selling activity in percentage.
This is useful because volume confirms price action. For instance, if prices rise but sell volume dominates, it can signal weakness. New traders learning with this tool should focus on how volume often precedes price reversals and trends.
________________________________________
4. RSI (Relative Strength Index)
RSI is a momentum oscillator that measures price strength on a scale from 0 to 100. The dashboard classifies RSI readings into overbought (>70), oversold (<30), or neutral zones and adds visual progress bars.
RSI helps learners understand momentum shifts. During training, one should notice how trending markets can keep RSI extended for longer periods (not immediate reversal signals), while range-bound markets react more sharply to RSI extremes. It is an excellent tool for practicing trend vs. range identification.
________________________________________
5. MACD (Moving Average Convergence Divergence)
The MACD indicator involves a fast EMA, slow EMA, and signal line, with focus on crossovers. The dashboard shows whether a “bullish cross” (MACD above signal line) or “bearish cross” (MACD below signal line) has occurred.
MACD teaches traders to identify trend momentum shifts and divergence. During practice, traders can explore how MACD signals align with VWAP trends or RSI levels, which helps in building a structured multi-indicator analysis.
________________________________________
6. Stochastic Oscillator
This indicator compares the current close relative to a range of highs and lows over a period. Displayed values oscillate between 0 and 100, marking zones of overbought (>80) and oversold (<20).
Stochastics are useful for students of trading to recognize short-term momentum changes. Unlike RSI, it reacts faster to price volatility, so false signals are common. Part of the training exercise can be to observe how stochastic “flips” can align with volume surges or daily range endpoints.
________________________________________
7. Trend & Momentum Classification
The dashboard adds simple labels for trend (uptrend, downtrend, neutral) based on RSI thresholds. Additionally, it provides quick momentum classification (“bullish hold”, “bearish hold”, or neutral).
This is beneficial for beginners as it introduces structured thinking: differentiating long-term market bias (trend) from short-term directional momentum. By combining both, traders can practice filtering signals instead of trading randomly.
________________________________________
8. Accumulation / Distribution Bias
Based on RSI levels, the script generates simplified tags such as “Accumulate Long”, “Accumulate Short”, or “Wait”.
This is purely an interpretive guide, helping learners think in terms of accumulation phases (when markets are low) and distribution phases (when markets are high). It reinforces the concept that trading is not only directional but also involves timing.
________________________________________
9. Overall Market Status and Score
Finally, the dashboard compiles multiple indicators (VWAP position, RSI, MACD, Stochastics, and price vs. median levels) into a Market Score expressed as a percentage. It also labels the market as Overbought, Oversold, or Normal.
This scoring system isn’t a recommendation but a learning framework. Students can analyze how combining different indicators improves decision-making. The key training focus here is confluence: not depending on one indicator but observing when several conditions align.
Extended Study Material with Formulas
________________________________________
1. Daily Reference Levels (High, Low, Open, Median, Range)
• Day High (H): Maximum price of the session.
DayHigh=max(Hightoday)DayHigh=max(Hightoday)
• Day Low (L): Minimum price of the session.
DayLow=min(Lowtoday)DayLow=min(Lowtoday)
• Day Open (O): Opening price of the session.
DayOpen=OpentodayDayOpen=Opentoday
• Day Range:
Range=DayHigh−DayLowRange=DayHigh−DayLow
• Median: Mid-point between high and low.
Median=DayHigh+DayLow2Median=2DayHigh+DayLow
These act as intraday guideposts for seeing how far the price has stretched from its key reference levels.
________________________________________
2. VWAP (Volume Weighted Average Price)
VWAP considers both price and volume for a weighted average:
VWAPt=∑i=1t(Pricei×Volumei)∑i=1tVolumeiVWAPt=∑i=1tVolumei∑i=1t(Pricei×Volumei)
Here, Price_i can be the average price (High + Low + Close) ÷ 3, also known as hlc3.
• Interpretation: Price above VWAP = bullish bias; Price below = bearish bias.
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3. Volume Buy/Sell Analysis
The dashboard splits total volume into buy volume and sell volume based on candle type.
• Buy Volume:
BuyVol=Volumeif Close > Open, else 0BuyVol=Volumeif Close > Open, else 0
• Sell Volume:
SellVol=Volumeif Close < Open, else 0SellVol=Volumeif Close < Open, else 0
• Buy Ratio (%):
VolumeRatio=BuyVolBuyVol+SellVol×100VolumeRatio=BuyVol+SellVolBuyVol×100
This helps traders gauge who is in control during a session—buyers or sellers.
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4. RSI (Relative Strength Index)
RSI measures strength of momentum by comparing gains vs. losses.
Step 1: Compute average gains (AG) and losses (AL).
AG=Average of Upward Closes over N periodsAG=Average of Upward Closes over N periodsAL=Average of Downward Closes over N periodsAL=Average of Downward Closes over N periods
Step 2: Calculate relative strength (RS).
RS=AGALRS=ALAG
Step 3: RSI formula.
RSI=100−1001+RSRSI=100−1+RS100
• Used to detect overbought (>70), oversold (<30), or neutral momentum zones.
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5. MACD (Moving Average Convergence Divergence)
• Fast EMA:
EMAfast=EMA(Close,length=fast)EMAfast=EMA(Close,length=fast)
• Slow EMA:
EMAslow=EMA(Close,length=slow)EMAslow=EMA(Close,length=slow)
• MACD Line:
MACD=EMAfast−EMAslowMACD=EMAfast−EMAslow
• Signal Line:
Signal=EMA(MACD,length=signal)Signal=EMA(MACD,length=signal)
• Histogram:
Histogram=MACD−SignalHistogram=MACD−Signal
Crossovers between MACD and Signal are used in studying bullish/bearish phases.
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6. Stochastic Oscillator
Stochastic compares the current close against a range of highs and lows.
%K=Close−LowestLowHighestHigh−LowestLow×100%K=HighestHigh−LowestLowClose−LowestLow×100
Where LowestLow and HighestHigh are the lowest and highest values over N periods.
The %D line is a smooth version of %K (using a moving average).
%D=SMA(%K,smooth)%D=SMA(%K,smooth)
• Values above 80 = overbought; below 20 = oversold.
________________________________________
7. Trend and Momentum Classification
This dashboard generates simplified trend/momentum logic using RSI.
• Trend:
• RSI < 40 → Downtrend
• RSI > 60 → Uptrend
• In Between → Neutral
• Momentum Bias:
• RSI > 70 → Bullish Hold
• RSI < 30 → Bearish Hold
• Otherwise Neutral
This is not predictive, only a classification framework for educational use.
________________________________________
8. Accumulation/Distribution Bias
Based on extreme RSI values:
• RSI < 25 → Accumulate Long Bias
• RSI > 80 → Accumulate Short Bias
• Else → Wait/No Action
This helps learners understand the idea of accumulation at lows (strength building) and distribution at highs (profit booking).
________________________________________
9. Overall Market Status and Score
The tool adds up 5 bullish conditions:
1. Price above VWAP
2. RSI > 50
3. MACD > Signal
4. Stochastic > 50
5. Price above Daily Median
BullishScore=ConditionsMet5×100BullishScore=5ConditionsMet×100
Then it categorizes the market:
• RSI > 70 or Stoch > 80 → Overbought
• RSI < 30 or Stoch < 20 → Oversold
• Else → Normal
This encourages learners to think in terms of probabilistic conditions instead of single-indicator signals.
________________________________________
⚠️ Warning:
• Trading financial markets involves substantial risk.
• You can lose more money than you invest.
• Past performance of indicators does not guarantee future results.
• This script must not be copied, resold, or republished without authorization from aiTrendview.
By using this material or the code, you agree to take full responsibility for your trading decisions and acknowledge that this is not financial advice.
________________________________________
⚠️ Disclaimer and Warning (From aiTrendview)
This Dynamic Trading Dashboard is created strictly for educational and research purposes on the TradingView platform. It does not provide financial advice, buy/sell recommendations, or guaranteed returns. Any use of this tool in live trading is completely at the user’s own risk. Markets are inherently risky; losses can exceed initial investment.
The intellectual property of this script and its methodology belongs to aiTrendview. Unauthorized reproduction, modification, or redistribution of this code is strictly prohibited. By using this study material or the script, you acknowledge personal responsibility for any trading outcomes. Always consult professional financial advisors before making investment decisions.
Bitcoin cme gap indicators, BINANCE vs CME exchanges premium gap
# CME BTC Premium Indicator Documentation CME:BTC1!
## 1. Overview
Indicator Name: CME BTC Premium
Platform: TradingView (Pine Script v6)
Type: Premium / Gap Analysis
Purpose:
* Visualize the CME BTC futures premium/discount relative to Binance BTCUSDT spot price.
* Detect gap-up or gap-down events on the daily chart.
* Assess short-term market sentiment and potential volatility through price discrepancies.
## 2. Key Features
1. CME Premium Calculation
* Formula:
CME Premium(%) = ((CME Price - Binance Price) / Binance Price) X 100
* Positive premium: CME futures are higher than spot → Color: Blue
* Negative premium: CME futures are lower than spot → Color: Purple
2. Premium Visualization Options
* `Column` (default)
* `Line`
3. Daily Gap Detection (Daily Chart Only)
* Gap Up: CME open > previous high × 1.0001 (≥ 0.01%)
* Gap Down: CME open < previous low × 0.9999 (≤ 0.01%)
* Visualization:
* Bar Color:
* Gap Up → Yellow (semi-transparent)
* Gap Down → Blue (semi-transparent)
* Background Color:
* Gap Up → Yellow (semi-transparent)
* Gap Down → Blue (semi-transparent)
4. Label Display
* If `Show CME Label` is enabled, the last bar displays a premium percentage label.
* Label color matches premium color; text color: Black.
* Style: `style_label_upper_left`, Size: `small`.
## 3. User Inputs
| Option Name | Description | Type / Default |
| -------------- | ------------------------- | --------------------------------------- |
| Show CME Label | Display CME premium label | Boolean / true |
| CME Plot Type | CME premium chart style | String / Column (Options: Column, Line) |
## 4. Data Sources
| Data Item | Symbol | Description |
| ------------- | ---------------- | ----------------------------- |
| Binance Price | BINANCE\:BTCUSDT | Spot BTC price |
| CME Price | CME\:BTC1! | CME BTC futures closing price |
| CME Open | CME\:BTC1! | CME BTC futures open price |
| CME Low | CME\:BTC1! | CME BTC futures low price |
| CME High | CME\:BTC1! | CME BTC futures high price |
## 5. Chart Display
1. Premium Column/Line
* Displays the CME premium percentage in real-time.
* Color: Premium ≥ 0 → Blue, Premium < 0 → Purple
2. Zero Line
* Indicates CME futures are at parity with spot for quick visual reference.
3. Gap Highlight
* Applied only on daily charts.
* Gap-up or gap-down is highlighted using bar and background colors.
4. Label
* Shows the latest CME premium percentage for quick monitoring.
## 6. Use Cases
* Analyze spot-futures premium to gauge CME market sentiment.
* Identify short-term volatility and potential trend reversals through daily gaps.
* Combine premium and gap analysis to support altcoin trend analysis and position strategy.
## 7. Limitations
* This indicator does not provide investment advice or trading recommendations; it is for informational purposes only.
* Data delays, API restrictions, or exchange differences may result in calculation discrepancies.
* Gap detection is meaningful only on daily charts; other timeframes may not provide valid signals.
Latent Regime Informed Monte Carlo ForecastThis script uses a Monte Carlo simulation to forecast where price might be a set number of bars into the future (default 6 bars ahead). It generates hundreds of possible future price paths based on an average move (drift) and random shocks (volatility). The result is a distribution of outcomes, displayed as probability zones: the median (most likely), inner bands (50% confidence), and wider bands (80% and 95% confidence). Due to the randomness assumption in Monte Carlo simulations, the paths are not very important so to minimize cluttering on the graphs we only plot bands. These zones help you visualize uncertainty, set stops and targets based on probabilities, and spot when market behavior changes.
The accuracy of any Monte Carlo forecast depends heavily on how well you estimate trend and volatility. By default and no prior information the Monte Carlo simulation gives you a parabolic forecast that assumes absolute randomness. This is where the Kalman filter comes in. The filter (derived from control theory) aims to detect latent (unobservable) traits about the system by continuously updating its transition probabilities to better understand how the latent traits affect the observable measurement (price). With each new observable state we get better and better transition probabilities and enhances our understanding about the latent and unobservable market characteristics like trend and volatility. Both crucial measurements for short term market sentiment.
Extracting these measurements for market sentiment informs us how to better parametrize the Monte Carlo simulation for a better forecast. Each bar, the KF updates its estimates based on how close its last prediction was to reality. In calm periods, it holds estimates steady; in volatile periods, it adapts quickly. This gives you real-time, low-lag measurements of both trend and volatility.
By feeding these adaptive estimates into the Monte Carlo simulation, the forecast becomes much more responsive to current market conditions. In trends, the predicted paths tilt toward the direction of movement; in choppy markets, they spread wider but stay centered; when volatility spikes, the probability zones expand immediately. The result is a dynamic forecast tool that adjusts on every bar, giving you a clearer, probability-based picture of where the market could go next.
This is my very first script and I would love feedback/ideas for different topics.
My background is in economics/mathematics and interests lie in time series analysis/exploring financial features for DS
Ultimate Scalping Strategy v2Strategy Overview
This is a versatile scalping strategy designed primarily for low timeframes (like 1-min, 3-min, or 5-min charts). Its core logic is based on a classic EMA (Exponential Moving Average) crossover system, which is then filtered by the VWAP (Volume-Weighted Average Price) to confirm the trade's direction in alignment with the market's current intraday sentiment.
The strategy is highly customizable, allowing traders to add layers of confirmation, control trade direction, and manage exits with precision.
Core Strategy Logic
The strategy's entry signals are generated when two primary conditions are met simultaneously:
Momentum Shift (EMA Crossover): It looks for a crossover between a fast EMA (default length 9) and a slow EMA (default length 21).
Buy Signal: The fast EMA crosses above the slow EMA, indicating a potential shift to bullish momentum.
Sell Signal: The fast EMA crosses below the slow EMA, indicating a potential shift to bearish momentum.
Trend/Sentiment Filter (VWAP): The crossover signal is only considered valid if the price is on the "correct" side of the VWAP.
For a Buy Signal: The price must be trading above the VWAP. This confirms that, on average, buyers are in control for the day.
For a Sell Signal: The price must be trading below the VWAP. This confirms that sellers are generally in control.
Confirmation Filters (Optional)
To increase the reliability of the signals and reduce false entries, the strategy includes two optional confirmation filters:
Price Action Filter (Engulfing Candle): If enabled (Use Price Action), the entry signal is only valid if the crossover candle is also an "engulfing" candle.
A Bullish Engulfing candle is a large green candle that completely "engulfs" the body of the previous smaller red candle, signaling strong buying pressure.
A Bearish Engulfing candle is a large red candle that engulfs the previous smaller green candle, signaling strong selling pressure.
Volume Filter (Volume Spike): If enabled (Use Volume Confirmation), the entry signal must be accompanied by a surge in volume. This is confirmed if the volume of the entry candle is greater than its recent moving average (default 20 periods). This ensures the move has strong participation behind it.
Exit Strategy
A position can be closed in one of three ways, creating a comprehensive exit plan:
Stop Loss (SL): A fixed stop loss is set at a level determined by a multiple of the Average True Range (ATR). For example, a 1.5 multiplier places the stop 1.5 times the current ATR value away from the entry price. This makes the stop dynamic, adapting to market volatility.
Take Profit (TP): A fixed take profit is also set using an ATR multiplier. By setting the TP multiplier higher than the SL multiplier (e.g., 2.0 for TP vs. 1.5 for SL), the strategy aims for a positive risk-to-reward ratio on each trade.
Exit on Opposite Signal (Reversal): If enabled, an open position will be closed automatically if a valid entry signal in the opposite direction appears. For example, if you are in a long trade and a valid short signal occurs, the strategy will exit the long position immediately. This feature turns the strategy into more of a reversal system.
Key Features & Customization
Trade Direction Control: You can enable or disable long and short trades independently using the Allow Longs and Allow Shorts toggles. This is useful for trading in harmony with a higher-timeframe trend (e.g., only allowing longs in a bull market).
Visual Plots: The strategy plots the Fast EMA, Slow EMA, and VWAP on the chart for easy visualization of the setup. It also plots up/down arrows to mark where valid buy and sell signals occurred.
Dynamic SL/TP Line Plotting: A standout feature is that the strategy automatically draws the exact Stop Loss and Take Profit price lines on the chart for every active trade. These lines appear when a trade is entered and disappear as soon as it is closed, providing a clear visual of your risk and reward targets.
Alerts: The script includes built-in alertcondition calls. This allows you to create alerts in TradingView that can notify you on your phone or execute trades automatically via a webhook when a long or short signal is generated.
Smarter Money Flow Divergence Detector [PhenLabs]📊 Smarter Money Flow Divergence Detector
Version: PineScript™ v6
📌 Description
SMFD was developed to help give you guys a better ability to “read” what is going on behind the scenes without directly having access to that level of data. SMFD is an enhanced divergence detection indicator that identifies money flow patterns from advanced volume analysis and price action correspondence. The detection portion of this indicator combines intelligent money flow calculations with multi timeframe volume analysis to help you see hidden accumulation and distribution phases before major price movements occur.
The indicator measures institutional trading activity by looking at volume surges, price volume dynamics, and the factors of momentum to construct an overall picture of market sentiment. It’s built to assist traders in identifying high probability entries by identifying if smart money is positioning against price action.
🚀 Points of Innovation
● Advanced Smart Money Flow algorithm with volume spike detection and large trade weighting
● Multi timeframe volume analysis for enhanced institutional activity detection
● Dynamic overbought/oversold zones that adapt to current market conditions
● Enhanced divergence detection with pivot confirmation and strength validation
● Color themes with customizable visual styling options
● Real time institutional bias tracking through accumulation/distribution analysis
🔧 Core Components
● Smart Money Flow Calculation: Combines price momentum, volume expansion, and VWAP analysis
● Institutional Bias Oscillator: Tracks accumulation/distribution patterns with volume pressure analysis
● Enhanced Divergence Engine: Detects bullish/bearish divergences with multiple confirmation factors
● Dynamic Zone Detection: Automatically adjusts overbought/oversold levels based on market volatility
● Volume Pressure Analysis: Measures buying vs selling pressure over configurable periods
● Multi factor Signal System: Generates entries with trend alignment and strength validation
🔥 Key Features
● Smart Money Flow Period: Configurable calculation period for institutional activity detection
● Volume Spike Threshold: Adjustable multiplier for detecting unusual institutional volume
● Large Trade Weight: Emphasis factor for high volume periods in flow calculations
● Pivot Detection: Customizable lookback period for accurate divergence identification
● Signal Sensitivity: Three tier system (Conservative/Medium/Aggressive) for signal generation
● Themes: Four color schemes optimized for different chart backgrounds
🎨 Visualization
● Main Oscillator: Line, Area, or Histogram display styles with dynamic color coding
● Institutional Bias Line: Real time tracking of accumulation/distribution phases
● Dynamic Zones: Adaptive overbought/oversold boundaries with gradient fills
● Divergence Lines: Automatic drawing of bullish/bearish divergence connections
● Entry Signals: Clear BUY/SELL labels with signal strength indicators
● Information Panel: Real time statistics and status updates in customizable positions
📖 Usage Guidelines
Algorithm Settings
● Smart Money Flow Period
○ Default: 20
○ Range: 5-100
○ Description: Controls the calculation period for institutional flow analysis.
Higher values provide smoother signals but reduce responsiveness to recent activity
● Volume Spike Threshold
○ Default: 1.8
○ Range: 1.0-5.0
○ Description: Multiplier for detecting unusual volume activity indicating institutional participation. Higher values require more extreme volume for detection
● Large Trade Weight
○ Default: 2.5
○ Range: 1.5-5.0
○ Description: Weight applied to high volume periods in smart money calculations. Increases emphasis on institutional sized transactions
Divergence Detection
● Pivot Detection Period
○ Default: 12
○ Range: 5-50
○ Description: Bars to analyze for pivot high/low identification.
Affects divergence accuracy and signal frequency
● Minimum Divergence Strength
○ Default: 0.25
○ Range: 0.1-1.0
○ Description: Required price change percentage for valid divergence patterns.
Higher values filter out weaker signals
✅ Best Use Cases
● Trading with intraday to daily timeframes for institutional position identification
● Confirming trend reversals when divergences align with support/resistance levels
● Entry timing in trending markets when institutional bias supports the direction
● Risk management by avoiding trades against strong institutional positioning
● Multi timeframe analysis combining short term signals with longer term bias
⚠️ Limitations
● Requires sufficient volume for accurate institutional detection in low volume markets
● Divergence signals may have false positives during highly volatile news events
● Best performance on liquid markets with consistent institutional participation
● Lagging nature of volume based calculations may delay signal generation
● Effectiveness reduced during low participation holiday periods
💡 What Makes This Unique
● Multi Factor Analysis: Combines volume, price, and momentum for comprehensive institutional detection
● Adaptive Zones: Dynamic overbought/oversold levels that adjust to market conditions
● Volume Intelligence: Advanced algorithms identify institutional sized transactions
● Professional Visualization: Multiple display styles with customizable themes
● Confirmation System: Multiple validation layers reduce false signal generation
🔬 How It Works
1. Volume Analysis Phase:
● Analyzes current volume against historical averages to identify institutional activity
● Applies multi timeframe analysis for enhanced detection accuracy
● Calculates volume pressure through buying vs selling momentum
2. Smart Money Flow Calculation:
● Combines typical price with volume weighted analysis
● Applies institutional trade weighting for high volume periods
● Generates directional flow based on price momentum and volume expansion
3. Divergence Detection Process:
● Identifies pivot highs/lows in both price and indicator values
● Validates divergence strength against minimum threshold requirements
● Confirms signals through multiple technical factors before generation
💡 Note: This indicator works best when combined with proper risk management and position sizing. The institutional bias component helps identify market sentiment shifts, while divergence signals provide specific entry opportunities. For optimal results, use on liquid markets with consistent institutional participation and combine with additional technical analysis methods.
Long-Leg Doji Breakout StrategyThe Long-Leg Doji Breakout Strategy is a sophisticated technical analysis approach that capitalizes on market psychology and price action patterns.
Core Concept: The strategy identifies Long-Leg Doji candlestick patterns, which represent periods of extreme market indecision where buyers and sellers are in equilibrium. These patterns often precede significant price movements as the market resolves this indecision.
Pattern Recognition: The algorithm uses strict mathematical criteria to identify authentic Long-Leg Doji patterns. It requires the candle body to be extremely small (≤0.1% of the total range) while having long wicks on both sides (at least 2x the body size). An ATR filter ensures the pattern is significant relative to recent volatility.
Trading Logic: Once a Long-Leg Doji is identified, the strategy enters a "waiting mode," monitoring for a breakout above the doji's high (long signal) or below its low (short signal). This confirmation approach reduces false signals by ensuring the market has chosen a direction.
Risk Management: The strategy allocates 10% of equity per trade and uses a simple moving average crossover for exits. Visual indicators help traders understand the pattern identification and trade execution process.
Psychological Foundation: The strategy exploits the natural market cycle where uncertainty (represented by the doji) gives way to conviction (the breakout), creating high-probability trading opportunities.
The strength of this approach lies in its ability to identify moments when market sentiment shifts from confusion to clarity, providing traders with well-defined entry and exit points while maintaining proper risk management protocols.
How It Works
The strategy operates on a simple yet powerful principle: identify periods of market indecision, then trade the subsequent breakout when the market chooses direction.
Step 1: Pattern Detection
The algorithm scans for Long-Leg Doji candles, which have three key characteristics:
Tiny body (open and close prices nearly equal)
Long upper wick (significant rejection of higher prices)
Long lower wick (significant rejection of lower prices)
Step 2: Confirmation Wait
Once a doji is detected, the strategy doesn't immediately trade. Instead, it marks the high and low of that candle and waits for a definitive breakout.
Step 3: Trade Execution
Long Entry: When price closes above the doji's high
Short Entry: When price closes below the doji's low
Step 4: Exit Strategy
Positions are closed when price crosses back through a 20-period moving average, indicating potential trend reversal.
Market Psychology Behind It
A Long-Leg Doji represents a battlefield between bulls and bears that ends in a stalemate. The long wicks show that both sides tried to push price in their favor but failed. This creates a coiled spring effect - when one side finally gains control, the move can be explosive as trapped traders rush to exit and momentum traders jump aboard.
Key Parameters
Doji Body Threshold (0.1%): Ensures the body is truly small relative to the candle's range
Wick Ratio (2.0): Both wicks must be at least twice the body size
ATR Filter: Uses Average True Range to ensure the pattern is significant in current market conditions
Position Size: 10% of equity per trade for balanced risk management
Pros:
High Probability Setups: Doji patterns at key levels often lead to significant moves as they represent genuine shifts in market sentiment.
Clear Rules: Objective criteria for entry and exit eliminate emotional decision-making and provide consistent execution.
Risk Management: Built-in position sizing and exit rules help protect capital during losing trades.
Market Neutral: Works equally well for long and short positions, adapting to market direction rather than fighting it.
Visual Confirmation: The strategy provides clear visual cues, making it easy to understand when patterns are forming and trades are triggered.
Cons:
False Breakouts: In choppy or ranging markets, price may break the doji levels only to quickly reverse, creating whipsaws.
Patience Required: Traders must wait for both pattern formation and breakout confirmation, which can test discipline during active market periods.
Simple Exit Logic: The moving average exit may be too simplistic, potentially cutting profits short during strong trends or holding losers too long during reversals.
Volatility Dependent: The strategy relies on sufficient volatility to create meaningful doji patterns - it may underperform in extremely quiet markets.
Lagging Entries: Waiting for breakout confirmation means missing the very beginning of moves, reducing potential profit margins.
Best Market Conditions
The strategy performs optimally during periods of moderate volatility when markets are making genuine directional decisions rather than just random noise. It works particularly well around key support/resistance levels where the market's indecision is most meaningful.
Optimization Considerations
Consider combining with additional confluence factors like volume analysis, support/resistance levels, or other technical indicators to improve signal quality. The exit strategy could also be enhanced with trailing stops or multiple profit targets to better capture extended moves while protecting gains.
Best for Index option,
Enjoy !!
OA - SMESSmart Money Entry Signals (SMES)
The SMES indicator is developed to identify potential turning points in market behavior by analyzing internal price dynamics, rather than relying on external volume or sentiment data. It leverages normalized price movement, directional volatility, and smoothing algorithms to detect potential areas of accumulation or distribution by market participants.
Core Concepts
Smart Money Flow calculation based on normalized price positioning
Directional VHF (Vertical Horizontal Filter) used to enhance signal directionality
Overbought and Oversold regions defined with optional glow visualization
Entry and Exit signals based on dynamic crossovers
Highly customizable input parameters for precision control
Key Inputs
Smart Money Flow Period
Smoothing Period
Price Analysis Length
Fibonacci Lookback Length
Visual toggle options (zones, glow effects, signal display)
Usage
This tool plots the smoothed smart money flow as a standalone oscillator, designed to help traders identify potential momentum shifts or extremes in market sentiment. Entry signals are generated through crossover logic, while optional filters based on price behavior can refine those signals. Exit signals are shown when the smart money line exits extreme regions.
Important Notes
This indicator does not repaint
Works on all timeframes and instruments
Best used as a confirmation tool with other technical frameworks
All calculations are based strictly on price data
Disclaimer
This script is intended for educational purposes only. It does not provide financial advice or guarantee performance. Please do your own research and apply appropriate risk management before making any trading decisions.
BVB dominance bars
Hello everyone, this is my first indicator. these candles shows you who's in control. I like to think its some what close to heikin ashi candles as it shows you the Trend but doesn't average it out. also shows you when there is indecision. please read the instructions on how it works. its not a stand alone strategy. but adds value to your own strategy.
📖 How It Works
The BvB Dominance Bars indicator is a visual tool that colors candles based on market control—whether bulls or bears are in charge. It uses a custom metric comparing the price's relationship to a smoothed moving average (EMA), then normalizes that difference over time to express relative bullish or bearish pressure.
Here’s the breakdown:
Bulls vs Bears Logic:
A short-term EMA (default: 14-period) is used to establish a midpoint reference.
Bull Pressure is calculated as how far the high is above this EMA.
Bear Pressure is how far the low is below this EMA.
These are normalized over a lookback period (default: 120 bars) to produce percentile scores (0–100) for both bulls and bears.
Dominance & Color Coding:
The indicator compares normalized bull and bear scores.
Candles are color-coded based on:
Bright Lime: Strong Bull Dominance (with high confidence)
Soft Lime/Yellow: Moderate Bull Control
Bright Red: Strong Bear Dominance
Soft Red/Yellow: Moderate Bear Control
Gray: Neutral/Low conviction
Optional Live Label:
A small floating label shows who has control: “Bull Control,” “Bear Control,” or “Neutral.”
🧠 How to Use It (Example Strategy)
The BvB Dominance Bars indicator is not a standalone buy/sell signal but a market sentiment overlay. It’s most effective when combined with your own strategy, like price action or trend-following tools.
Here’s an example use case:
🧪 Reversal Confirmation Strategy
Objective: Catch high-probability reversals during key kill zones or supply/demand levels.
Setup:
Mark your key support/resistance zones using your standard method (e.g., FVGs, liquidity sweeps, or ICT PD arrays).
Wait for price to reach one of these zones.
Watch candle colors from the BvB Dominance Bars:
If you expect a bullish reversal, wait for a transition from red/gray candles to lime green or bright lime (bullish dominance taking over).
If you expect a bearish reversal, look for a change from green/gray to red or bright red.
Entry Filter:
Only enter if the dominant color holds for 2+ candles.
Avoid trades when candles are gray or yellow (indecision/neutral).
Exit Option:
Exit if dominance shifts against you (e.g., from lime to red), or use structure-based stops.
⚙️ Settings You Can Adjust:
BvB Period: Controls how fast EMA responds.
Bars Back: Determines how long the normalization looks back.
Thresholds: Influence how strong the dominance must be to change candle color.
✅ Best Used When:
You already have a bias and just want a confirmation of sentiment.
You're trading intraday and want a feel for shifting momentum without relying on noisy indicators.
You want a clean, color-coded overlay to help filter out fakeouts and indecision.
Full Day Midpoint Line with Dynamic StdDev Bands (ETH & RTH)A Pine Script indicator designed to plot a midpoint line based on the high and low prices of a user-defined trading session (typically Extended Trading Hours, ETH) and to add dynamic standard deviation (StdDev) bands around this midpoint.
Session Midpoint Line:
The midpoint is calculated as the average of the session's highest high and lowest low during the defined ETH period (e.g., 4:00 AM to 8:00 PM).
This line represents a central tendency or "fair value" for the session, similar to a pivot point or volume-weighted average price (VWAP) anchor.
Interpretation:
Prices above the midpoint suggest bullish sentiment, while prices below indicate bearish sentiment.
The midpoint can act as a dynamic support/resistance level, where price may revert to or react at this level during the session.
Dynamic StdDev Bands:
The bands are calculated by adding/subtracting a multiple of the standard deviation of the midpoint values (tracked in an array) from the midpoint.
The standard deviation is dynamically computed based on the historical midpoint values within the session, making the bands adaptive to volatility.
Interpretation:
The upper and lower bands represent potential overbought (upper) and oversold (lower) zones.
Prices approaching or crossing the bands may indicate stretched conditions, potentially signaling reversals or breakouts.
Trend Identification:
Use the midpoint as a reference for the session’s trend. Persistent price action above the midpoint suggests bullishness, while below indicates bearishness.
Combine with other indicators (e.g., moving averages, RSI) to confirm trend direction.
Support/Resistance Trading:
Treat the midpoint as a dynamic pivot point. Price rejections or consolidations near the midpoint can be entry points for mean-reversion trades.
The StdDev bands can act as secondary support/resistance levels. For example, price reaching the upper band may signal a potential short entry if accompanied by reversal signals.
Breakout/Breakdown Strategies:
A strong move beyond the upper or lower band may indicate a breakout (bullish above upper, bearish below lower). Confirm with volume or momentum indicators to avoid false breakouts.
The dynamic nature of the bands makes them useful for identifying significant price extensions.
Volatility Assessment:
Wider bands indicate higher volatility, suggesting larger price swings and potentially riskier trades.
Narrow bands suggest consolidation, which may precede a breakout. Traders can prepare for volatility expansions in such scenarios.
The "Full Day Midpoint Line with Dynamic StdDev Bands" is a versatile and visually intuitive indicator well-suited for day traders focusing on session-specific price action. Its dynamic midpoint and volatility-adjusted bands provide valuable insights into support, resistance, and potential reversals or breakouts.
Guppy Multiple Moving Average (GMMA)The GMMA Momentum Indicator plots 12 EMAs on your chart, divided into two groups:
Short-term EMAs (6 lines, default periods: 3, 5, 8, 10, 12, 15): Represent short-term trader sentiment and momentum.
Long-term EMAs (6 lines, default periods: 30, 35, 40, 45, 50, 60): Reflect long-term investor behavior and broader market trends.
By analyzing the interaction between these two groups, the indicator identifies:
Bullish and bearish trends based on the relative positions of the short- and long-term EMAs.
Momentum strength through the spread or convergence of the EMAs.
Potential reversals or breakouts via compression signals.
This PineScript version enhances the traditional GMMA by adding visual cues like background colors, bearish signals, and compression detection, making it ideal for swing traders seeking clear, actionable insights.
The GMMA Momentum Indicator provides several key features:
1. Trend Identification
Bullish Trend: When the short-term EMAs (green lines) are above the long-term EMAs (blue lines) and spreading apart, it signals strong upward momentum. The chart background turns light green to highlight this condition.
Bearish Trend: When the short-term EMAs cross below the long-term EMAs and converge, it indicates downward momentum. The background turns light red, and an orange downward triangle appears above the bar to mark a new bearish signal.
2. Momentum Analysis
The spread between the short-term EMAs reflects the strength of short-term momentum. A wide spread suggests strong momentum, while a tight grouping indicates weakening momentum or consolidation. Similarly, the long-term EMAs act as dynamic support or resistance, guiding traders on the broader trend.
3. Compression Detection
Compression occurs when both the short-term and long-term EMAs converge, signaling low volatility and a potential breakout or reversal. A yellow upward triangle appears below the bar when compression is detected, alerting traders to watch for price action.
4. Visual Cues
Green short-term EMAs: Show short-term trader activity.
Blue long-term EMAs: Represent long-term investor sentiment.
Background colors: Light green for bullish trends, light red for bearish trends, and transparent for neutral conditions.
Orange downward triangles: Mark new bearish trends.
Yellow upward triangles: Indicate compression, hinting at potential breakouts.
How to Use the GMMA Momentum Indicator for Swing Trading
Swing trading involves capturing price moves over days to weeks, and the GMMA Momentum Indicator is an excellent tool for this strategy. Here’s how to use it effectively:
1. Identifying Trade Entries
Buy Opportunities:
Look for a bullish trend (green background) where the short-term EMAs are above the long-term EMAs and spreading apart, indicating strong momentum.
A compression signal (yellow triangle) followed by a breakout above resistance or a bullish candlestick pattern can confirm an entry.
Example: On a daily chart, if the short-term EMAs cross above the long-term EMAs and the background turns green, consider entering a long position, especially if volume supports the move.
Sell Opportunities:
Watch for a bearish signal (orange downward triangle) or a bearish trend (red background) where the short-term EMAs cross below the long-term EMAs.
Example: If the short-term EMAs collapse below the long-term EMAs and an orange triangle appears, it may signal a shorting opportunity or a time to exit longs.
2. Managing Trades
Use the long-term EMAs as dynamic support (in uptrends) or resistance (in downtrends) to set stop-loss levels or trail stops.
Monitor the spread of the short-term EMAs. A widening spread suggests the trend is strong, while convergence may indicate it’s time to take profits or tighten stops.
3. Anticipating Reversals
Compression signals (yellow triangles) highlight periods of low volatility, often preceding significant price moves. Combine these with price action (e.g., breakouts or reversals) or other indicators (e.g., RSI or volume) for confirmation.
Example: If a compression signal appears near a key support level and the price breaks upward, it could signal the start of a new bullish swing.
4. Best Practices
Timeframes: The indicator works well on daily or 4-hour charts for swing trading, but you can adjust the EMA periods for shorter (e.g., 1-hour) or longer (e.g., weekly) timeframes.
Confirmation: Combine the GMMA with other tools like support/resistance levels, candlestick patterns, or oscillators (e.g., MACD) to reduce false signals.
Risk Management: Always use proper position sizing and stop-losses, as EMAs are lagging indicators and may produce delayed signals in choppy markets.
Professional MSTI+ Trading Indicator"Professional MSTI+ Trading Indicator" is a comprehensive technical analysis tool that combines over 20 indicators to generate high-quality trading signals and assess market sentiment. The script integrates standard indicators (MACD, RSI, Bollinger Bands, Stochastic, Simple Moving Averages, and Volume Analysis) with advanced components (Squeeze Momentum, Fisher Transform, True Strength Index, Heikin-Ashi, Laguerre RSI, Hull MA) and further includes metrics such as ADX, Chaikin Money Flow, Williams %R, VWAP, and EMA for in-depth market analysis.
Key Features:
Multiple Presets for Different Trading Styles:
Choose from optimal configurations like Professional, Swing Trading, Day Trading, Scalping, or Reversal Hunter. Note that the presets may not work perfectly on all pairs, and manual calibration might be required. This flexibility allows you to fine-tune the settings to align with your unique strategies and signals.
Multi-Layered Signal Filtering:
Filters based on trend, volume, and volatility help eliminate false signals, enhancing the accuracy of market entries.
Comprehensive Fear & Greed Index:
The indicator aggregates data from RSI, volatility, momentum, trend, and volume to gauge overall market sentiment, providing an additional layer of market context.
Dynamic Information Panel:
Displays detailed status updates for each component (e.g., MACD, RSI, Laguerre RSI, TSI, Fisher Transform, Squeeze, Hull MA, etc.) along with a visual strength bar that represents the intensity of the trading signal.
Signal Generation:
Buy and sell signals are generated when a predefined number of conditions are met and confirmed over multiple bars. These signals are clearly displayed on the chart with arrows, making it easier to spot potential entry and exit points.
Alert Setup:
Built-in alert conditions allow you to receive real-time notifications when trading signals are generated, helping you stay on top of market movements.
"Professional MSTI+ Trading Indicator" is designed to enhance your trading strategy by providing a multi-faceted market analysis and an intuitive visual interface. While the presets offer a robust starting point, they may require manual calibration on certain pairs, giving you the flexibility to configure your own unique strategies and signals.
