Advance Smc Ict V4 The Advance SMC ICT Indicator is designed to assist traders in mapping market structure and identifying key price zones based on Smart Money Concepts (SMC) such as dz idm , dz ext , hist idm , hist dz ext & tracks major and minor order flow, and marks potential areas of interest, such as the Golden Zone. The indicator aims to simplify complex chart analysis, providing a structured approach to observing market movements across different timeframes.
✦Understanding the Concept of Order Blocks
DZ IDM
Dz idm is the zone just below inducement . it is also know as decisional order block .
This decisional order block plays a crucial role in identifying potential trade entries and is especially effective at highlighting key reversal zones.
This order block contains inducement liquidity above it, which enhances its significance compared to other order blocks.
Chart Illustration
This diagram illustrates the IDM Order Block (OB-IDM), which is the first order block that appears just below the current IDM level.
SETTING
1. Customizable IDM OB BG Color – Demand
Define the fill color for demand-side IDM OBs to highlight buy zones clearly.
2. Customizable IDM OB BG Color – Supply
Define the fill color for supply-side IDM OBs to mark sell zones distinctly.
3. Customizable IDM OB Text Color – Demand
Choose the label color for “Demand” text so it remains legible over the demand zone.
4. *Customizable IDM OB Text Color – Supply
Choose the label color for “Supply” text so it stands out over the supply zone.
DZ EXT
Extreme Order Block (OB-EXT):
The OB-EXT refers to the extreme order block identified between a Major Low and a Major High. Positioned at the edge of a swing range, this zone often reflects the initial point of strong price movement and can serve as a key area where institutional activity may have occurred.
Usage:
The OB-EXT is used to highlight potential high-probability reversal zones. Its location at structural extremes makes it useful for identifying trade entries during deep pullbacks or at the beginning of trend shifts. Traders often monitor this level for reaction when price revisits it, as it can signal renewed interest and possible directional continuation.
Chart Illustration
Setting
1. Customizable EXT OB BG Color – Demand
Define the fill color for demand-side EXT Order Blocks to highlight key buy zones.
2. Customizable EXT OB BG Color – Supply
Define the fill color for supply-side EXT Order Blocks to mark critical sell zones.
3. Customizable EXT OB Text Color – Demand
Choose the “Demand” label color so it remains legible over the demand-zone background.
4. Customizable EXT OB Text Color – Supply
Choose the “Supply” label color so it stands out clearly against the supply-zone fill.
✦HIST IDM OB AND HIST EXT OB
This indicator automatically identifies and highlights key swing zones to enhance market structure analysis.This features help traders to focus on current swing ,
It dynamically marks the current active swing zones as:
DZ IDM: The most recent Inverse Demand Momentum zone, based on current price structure.
DZ EXT: The latest extreme zone between a major swing low and high.
It also tracks unmitigated historical zones as:
Hist DZ IDM: Previous IDM zones that have not yet been mitigated.
Hist DZ EXT: Past extreme zones that remain untested.
Chart Illustration
✦Minor Order flow
This tool is designed to help traders visualize both Smart Money Concepts (SMC) and Minor Order Flow in a structured and effective way. In a bullish market, a Minor Order Flow zone is defined as the last unmitigated selling move before price continues upward after a short pullback. In a bearish market, it marks the last unmitigated buying move before price resumes its downward trend.
The indicator tracks these zones in real-time,
TradingView
OANDA:XAUUSD Chart Image by AlgoHub100
dynamically labeling unmitigated zones in pink for visibility. Once price revisits and mitigates a zone, its color changes to a bluish tone, clearly showing which areas are active versus completed. This visual shift allows traders to focus on relevant swing levels, filtering out old or already-reacted zones.
Chart Illustration
Minor Order Flow Settings
-Control how Minor Order Flow levels appear on your chart:
-Toggle ON/OFF to enable or disable Minor Order Flow for a cleaner chart when needed.
-Max Count limits the number of Minor Order Flow levels shown (default: 10).
-Separate Bullish and Bearish Colors for easy identification of market direction.
-Custom Colors let you choose distinct visual styles for bullish and bearish flows.
✦Major Order flow
Major Order Flow
The Major Order Flow highlights the last unmitigated selling move in a bullish market and the last unmitigated buying move in a bearish market. These levels represent key institutional order blocks where price is likely to react.
Unmitigated Zones are displayed in blue on the chart, indicating potential areas of interest where price may return.
Once the zone is mitigated (touched by price), the color changes to greyish blue, signaling the zone has been tested.
Chart Illustration
MAJOR ORDER FLOW VS MINOR ORDER FLOW
Major Order Flow identifies the last unmitigated selling move in a bullish market (or buying move in a bearish market). These zones are shown in blue and change to greyish blue once mitigated. Minor Order Flow tracks the last unmitigated move within a larger structure, helping refine entries.
TradingView
OANDA:XAUUSD Chart Image by AlgoHub100
Breaker Block Indicator Overview
This indicator automatically identifies and confirms two special order block levels (breaker blocks) to highlight key supply and demand zones. It pre-marks these zones and then confirms them when price breaks through with a single candle. By focusing solely on these validated zones, the indicator helps traders concentrate on only the most significant supply and demand zones.
OB IDM Breaker Block
An OB IDM Breaker Block is an order block located just below an Inducement (IDM) level, which is a liquidity trap designed to lure traders. The indicator flags this block in advance. When price breaks the block with a single candle, it becomes a confirmed breaker block. This break indicates the inducement has failed and highlights a strong supply or demand zone.
OB EXT Breaker Block
An OB EXT Breaker Block is the extreme order block that lies between a Break of Structure (BOS) and a Change of Character (CHoCH). A BOS occurs when price clears a prior swing high or low, and a CHoCH is an early sign of reversal. The OB EXT is the first (outermost) order block in that swing, and it is marked by the indicator ahead of time. When price breaks this block with a single candle, it becomes a confirmed breaker block, signaling a major shift and highlighting a key supply or demand zone.
Breaker Block identifies a former order block that was invalidated by a break of structure and later retested. These levels often act as support or resistance zones, reflecting a potential shift in market sentiment. Traders may use Breaker Blocks to spot areas where price could react, helping with trade entries or exits.
Chart Illustration
TradingView
OANDA:XAUUSD Chart Image by AlgoHub100
✦Golden zone
The Golden Zone is the critical retracement band between the 61.8% and 78.6% Fibonacci levels of a significant market swing. This indicator automatically recognizes when price breaks a prior swing (Break of Structure, or BOS) and then shifts momentum (Change of Character, or CHoCH). As soon as these two events occur, it anchors a Fibonacci retracement between the BOS high/low and the CHoCH point, shading the area between the 0.618 and 0.786 levels (default: yellow fill).
Although TradingView’s built-in Fibonacci tool is free, it requires you to click two swing points every time—leaving you to guess whether those swings truly represent a valid BOS or CHoCH. In contrast, this indicator’s built-in logic ensures that the 61.8%–78.6% band is always drawn on the most relevant portion of price action without any extra effort. Whenever price completes a new BOS → CHoCH sequence, the Golden Zone instantly redraws, so you never have delayed or outdated retracements.
All aspects of the Golden Zone are fully customizable. You can replace the default 0.618/0.786 boundaries with any retracement values—such as 0.65/0.85 or 0.50/0.75—by entering your preferred ratios in the settings. Once set, those custom levels apply to every future swing, eliminating manual redraws. Likewise, the fill color, opacity, and boundary-line colors can be changed to match your chart’s theme. Select your color choices once, and each new Golden Zone appears consistently across multiple charts and timeframes.
By combining automatic structure alignment with one-click strategy adaptation (custom Fibonacci levels) and flexible styling (color, opacity, line thickness), this indicator saves you countless clicks and removes human error from swing selection. It provides a reliable, always-on highlight of where institutional orders commonly accumulate or distribute, making it easier to spot high-probability pullback entries or reversal areas.
Chart Illustration
This image shows our indicator automatically detecting major SMC swings and shading the Fibonacci 0.618–0.786 “Golden Zone” between each Break of Structure (BOS) and its subsequent Change of Character (CHoCH). By instantly plotting this band, you trade at a discounted price within the swing without manually identifying or drawing Fib lines. All retracement levels (e.g., 0.65/0.85, 0.50/0.75) and zone colors (fill, opacity, and boundary lines) are fully customizable—set your preferred ratios and styling once, and the indicator applies them on every new swing. This automation removes guesswork, saves clicks, and ensures you always see the most relevant pullback area in real time.
Minor Pullback
A minor pullback appears as a shallow retracement within an ongoing trend, without breaking the larger market structure. It represents a brief pause before price resumes its primary direction.
Traders can view minor pullbacks as opportunities to enter at slightly improved prices while the trend remains intact.
Observing how price recovers from a minor pullback helps confirm whether momentum continues in the same direction.
These pullbacks allow users to assess existing positions, consider small adjustments, and check nearby support or resistance levels.
Settings: Enabling “Show Internal Structure” highlights all minor pullbacks on the chart.
Example:
Major Pullback
A major pullback occurs when price retraces more deeply, often testing significant swing points or support/resistance zones. It can temporarily approach or break a key structure level before resuming the trend.
Traders might view a major pullback as a deeper buying opportunity in an uptrend or a validation of support.
Major pullbacks sometimes act as liquidity pools where stop-hunters target orders before a reversal.
The indicator flags major pullbacks distinctly, helping users recognize when caution is advised and when to adjust risk management.
Settings: Enabling “Mark High/Low” automatically labels major swing highs and lows.
Example:
SMC Market Structure
Smart Money Concepts focus on how institutions move price. This indicator highlights core structure components:
Break of Structure (BOS)
Indicates trend continuation when price breaks a previous swing high in an uptrend or swing low in a downtrend.
The indicator marks BOS events so users can verify that the prevailing direction remains intact.
Change of Character (CHOCH)
Signals a possible trend shift when price fails to make a new high in an uptrend and instead breaks the previous low, or vice versa.
CHOCH events are labeled to warn that momentum may be shifting.
Inducement (Trap Zones)
Marks areas where price briefly fakes a breakout to capture liquidity (stop-hunts) before reversing.
Identifying inducement moves helps avoid entries during false breakouts and encourages waiting for clearer confirmation.
The indicator labels induced swings, assisting in recognizing when a breakout may be a trap rather than a sustained move.
Example:
Order Blocks & Point of Interest (POI)
Order blocks represent price areas where institutional buying or selling created a significant move. This indicator distinguishes several types:
Point of Interest (POI)
A collective name for zones where price reactions often occur: Order Block, Breaker Block, and Mitigation Block.
Demand Zone (Bullish Order Block)
A price region where buy orders have overwhelmed sell orders, often forming a base before an upward move.
Traders may consider these zones when seeking long entries.
Supply Zone (Bearish Order Block)
Where sell orders exceed buy orders, frequently causing a downward reversal.
Traders might watch these zones for short entries or to set profit targets.
Breaker Block & Mitigation Block
Breaker Block appears after price breaks through a prior order block and then returns to test it from the opposite side, acting as flipped support or resistance.
Mitigation Block represents areas where institutions address unfilled orders created by previous moves, helping identify unbalanced liquidity.
Single Candle Order Block (SCOB)
A specific order block defined by one candlestick that initiates a notable price imbalance.
SCOBs often signal precise institutional interest and are flagged to show potential reversal or continuation levels.
Settings:
Enabling “Show POI” displays all Order Blocks, Breaker Blocks, and Mitigation Blocks.
Enabling “Institutional Order Block” toggles Demand/Supply Zones.
CONCLUSION
The Advance SMC ICT Indicator stands out by translating Smart Money Concepts into clear, actionable visuals—mapping inducement zones alongside four specialized order block types, including IDM and Extreme Order Blocks, to highlight where institutional activity is most likely concentrated. By combining precise structure analysis (BOS, CHOCH, inducements) with liquidity and fair value gap identification, it gives traders a nuanced view of where supply and demand pressures intersect. In practice, this means users can more easily spot where stop-runs may occur, recognize high-probability entry areas, and avoid common traps created by large-scale order flows.
While the Advance SMC ICT Indicator provides valuable insights into how professional participants interact with price, it is not a standalone trading system. Traders should always confirm its signals with their own analysis, apply sound risk management techniques, and consider broader market context before executing any trade.
Orderflow
Demand Index (Hybrid Sibbet) by TradeQUO\ Demand Index (Hybrid Sibbet) by TradeQUO \
\ Overview\
The Demand Index (DI) was introduced by James Sibbet in the early 1990s to gauge “real” buying versus selling pressure by combining price‐change information with volume intensity. Unlike pure price‐based oscillators (e.g. RSI or MACD), the DI highlights moves backed by above‐average volume—helping traders distinguish genuine demand/supply from false breakouts or low‐liquidity noise.
\ Calculation\
\
\ \ Step 1: Weighted Price (P)\
For each bar t, compute a weighted price:
```
Pₜ = Hₜ + Lₜ + 2·Cₜ
```
where Hₜ=High, Lₜ=Low, Cₜ=Close of bar t.
Also compute Pₜ₋₁ for the prior bar.
\ \ Step 2: Raw Range (R)\
Calculate the two‐bar range:
```
Rₜ = max(Hₜ, Hₜ₋₁) – min(Lₜ, Lₜ₋₁)
```
This Rₜ is used indirectly in the exponential dampener below.
\ \ Step 3: Normalize Volume (VolNorm)\
Compute an EMA of volume over n₁ bars (e.g. n₁=13):
```
EMA_Volₜ = EMA(Volume, n₁)ₜ
```
Then
```
VolNormₜ = Volumeₜ / EMA_Volₜ
```
If EMA\_Volₜ ≈ 0, set VolNormₜ to a small default (e.g. 0.0001) to avoid division‐by‐zero.
\ \ Step 4: BuyPower vs. SellPower\
Calculate “raw” BuyPowerₜ and SellPowerₜ depending on whether Pₜ > Pₜ₋₁ (bullish) or Pₜ < Pₜ₋₁ (bearish). Use an exponential dampener factor Dₜ to moderate extreme moves when true range is small. Specifically:
• If Pₜ > Pₜ₋₁,
```
BuyPowerₜ = (VolNormₜ) / exp
```
otherwise
```
BuyPowerₜ = VolNormₜ.
```
• If Pₜ < Pₜ₋₁,
```
SellPowerₜ = (VolNormₜ) / exp
```
otherwise
```
SellPowerₜ = VolNormₜ.
```
Here, H₀ and L₀ are the very first bar’s High/Low—used to calibrate the scale of the dampening. If the denominator of the exponential is near zero, substitute a small epsilon (e.g. 1e-10).
\ \ Step 5: Smooth Buy/Sell Power\
Apply a short EMA (n₂ bars, typically n₂=2) to each:
```
EMA_Buyₜ = EMA(BuyPower, n₂)ₜ
EMA_Sellₜ = EMA(SellPower, n₂)ₜ
```
\ \ Step 6: Raw Demand Index (DI\_raw)\
```
DI_rawₜ = EMA_Buyₜ – EMA_Sellₜ
```
A positive DI\_raw indicates that buying force (normalized by volume) exceeds selling force; a negative value indicates the opposite.
\ \ Step 7: Optional EMA Smoothing on DI (DI)\
To reduce choppiness, compute an EMA over DI\_raw (n₃ bars, e.g. n₃ = 1–5):
```
DIₜ = EMA(DI_raw, n₃)ₜ.
```
If n₃ = 1, DI = DI\_raw (no further smoothing).
\
\ Interpretation\
\
\ \ Crossing Zero Line\
• DI\_raw (or DI) crossing from below to above zero signals that cumulative buying pressure (over the chosen smoothing window) has overcome selling pressure—potential Long signal.
• Crossing from above to below zero signals dominant selling pressure—potential Short signal.
\ \ DI\_raw vs. DI (EMA)\
• When DI\_raw > DI (the EMA of DI\_raw), bullish momentum is accelerating.
• When DI\_raw < DI, bullish momentum is weakening (or bearish acceleration).
\ \ Divergences\
• If price makes new highs while DI fails to make higher highs (DI\_raw or DI declining), this hints at weakening buying power (“bearish divergence”), possibly preceding a reversal.
• If price makes new lows while DI fails to make lower lows (“bullish divergence”), this may signal waning selling pressure and a potential bounce.
\ \ Volume Confirmation\
• A strong price move without a corresponding rise in DI often indicates low‐volume “fake” moves.
• Conversely, a modest price move with a large DI spike suggests true institutional participation—often a more reliable breakout.
\
\ Usage Notes & Warnings\
\
\ \ Never Use DI in Isolation\
It is a \ filter\ and \ confirmation\ tool—combine with price‐action (trendlines, support/resistance, candlestick patterns) and risk management (stop‐losses) before executing trades.
\ \ Parameter Selection\
• \ Vol EMA length (n₁)\ : Commonly 13–20 bars. Shorter → more responsive to volume spikes, but noisier.
• \ Buy/Sell EMA length (n₂)\ : Typically 2 bars for fast smoothing.
• \ DI smoothing (n₃)\ : Usually 1 (no smoothing) or 3–5 for moderate smoothing. Long DI\_EMA (e.g. 20–50) gives a slower signal.
\ \ Market Adaptation\
Works well in liquid futures, indices, and heavily traded stocks. In thinly traded or highly erratic markets, adjust n₁ upward (e.g., 20–30) to reduce noise.
---
\ In Summary\
The Demand Index (James Sibbet) uses a three‐stage smoothing (volume → Buy/Sell Power → DI) to reveal true demand/supply imbalance. By combining normalized volume with price change, Sibbet’s DI helps traders identify momentum backed by real participation—filtering out “empty” moves and spotting early divergences. Always confirm DI signals with price action and sound risk controls before trading.
Project SynthIntroducing Project Synth !
Inspired by Pace of Tape and Cumulative Delta I created Project Synth in order to aggregate volume flow data across multiple marketsfor two primary reasions:
Traditional orderflow tools are not available on Tradingview. My script attempts to bring an original; calculus-based approach to creating not only an alternative for traditional orderflow tools, but also a more accurate one.
In order to detect genuine buying and selling pressure that cannot be easily manipulated. I did this because while I've always enjoyed concept behind both of those tools, I did not think they captured enough data to be useful. By analyzing assets that move together (positive correlation) and assets that move inversely (negative correlation), my system aims to fix the fundamental problems with those indicators and create an objective view of market sentiment based on aggregate orderflow.
Some more detailed explanations (using QQQ and SQQQ as an example):
Inverse Market Dynamics (QQQ vs SQQQ):
In an inverse market like SQQQ, aggressive buyers hit the ask when they expect the underlying (QQQ) to fall, while passive buyers wait on the bid hoping for cheaper inverse exposure. When QQQ rallies, SQQQ sees aggressive selling (people dumping their bearish bets) hitting bids, while passive sellers sit on the ask hoping to exit at better prices. The aggression flows opposite to the underlying market direction.
Why Utilizing Both Markets Provides A More Accurate Delta:
Watching both QQQ and SQQQ gives cross-validation - real buying pressure in QQQ should coincide with selling pressure in SQQQ. If you see buying in QQQ but also buying in SQQQ, that's a conflicting signal suggesting the move might be artificial or driven by other factors. The inverse relationship acts as a confirmation filter, making false signals much harder to generate.
Multiple Markets = Authentic Pressure:
The more unique, important markets you track, the harder it becomes to create fake delta moves. Real institutional buying/selling pressure affects multiple correlated assets simultaneously in predictable patterns - you can't easily manipulate tech stocks, treasury bonds, VIX, and currency pairs all at once to create a false signal. Each additional market acts as a fraud detection layer, ensuring the delta measurement reflects genuine ecosystem-wide buying and selling pressure rather than isolated manipulation or noise.
My Suggestions For Usage:
In order to keep the explanation simple and short for now, I suggest using it just like a cumulative delta indicator. For example: let's say you were watching CME_MINI:ES1! , and you had a resistance level at 6000. When the price reaches your resistance level, you would be looking for a significant divergence between price and Delta. Price : rising, Delta : falling. This means that even though the price was going up, strong and aggressive sellers are jumping in more and more, this can be used as a confirmation tool for a resistance level.
Notes For Moderators, Authors and Users:
Firstly, to the best of my knowledge, I have not been able to find many tools built around the concept of cumulative delta or pace of tape. While I know there are a couple projects, none to the magnitude of synthetically recreating these tools via an algorithm designed around basic calculus principles. While tools like Volume Delta are built in, they do not attempt to capture an accurate picture of aggregated orderflow from what I understand.
Secondly, it needs to be noted that tool aims to create an approximation of buying and selling pressure. To my knowledge it is not possible to create an accurate full picture, at least not within the limitations of Tradingview.
LEGIntroduction
The LEG indicator is an advanced technical analysis tool designed for traders to identify key levels and trading opportunities in the market. By combining Fair Value Gap (FVG) and Swing Point (SP) analysis, the indicator draws important "leg" lines that represent critical areas of market structure change. The LEG indicator helps traders identify potential support and resistance levels, enabling them to make more informed entry and exit decisions.
Use Cases
Trend Identification: Determine market trend direction through multiple unmitigated LEG lines in the same direction
Support/Resistance Areas: LEG lines often become temporary support or resistance levels
Pullback Trading: Look for entry opportunities when price pulls back to unmitigated LEG lines
Stop Loss Placement: Use LEG lines as reference points for stop loss placement
Market Structure Analysis: Understand market structure changes through the creation and mitigation of LEG lines
Configuration Options
Enable LEG Drawing: Turn the LEG indicator on or off
Bullish/Bearish LEG Color: Customize colors for different direction LEG lines
LEG Line Width: Adjust the width of LEG lines (1-5)
LEG Line Style: Choose between solid, dashed, or dotted lines
LEG Line Length: Adjust the horizontal extension length of LEG lines (10-500)
Maximum LEG Display Count: Control the maximum number of LEG lines shown on the chart (1-100)
LEG Offset: Horizontally adjust the position of LEG lines, can offset left or right
Hide Mitigated LEGs: Choose whether to hide LEG lines after price crosses them
使用场景
趋势识别: 通过多个未缓解的同向LEG线判断市场趋势方向
支撑/阻力区域: LEG线通常成为市场的临时支撑或阻力位
回撤交易: 当价格回撤到未缓解的LEG线附近时寻找入场机会
止损设置: 使用LEG线作为止损位的参考点
市场结构分析: 通过LEG线的生成和缓解理解市场结构变化
WhaleTrackBITGET:BTCUSDT.P
WhaleTrack – Volume Heatmap to Uncover Institutional Trading Activity
Overview
WhaleTrack is a volume-based heatmap indicator designed to reveal areas of high institutional trading activity. The indicator helps traders identify hidden support and resistance levels, analyze trend sustainability, and optimize stop-loss placements by displaying where significant market participants (whales) have historically traded in large volumes.
Institutions and large traders often push price into areas of historical liquidity to trigger retail stop-losses and fill their own large orders at optimal prices. WhaleTrack visualizes these critical areas, allowing traders to anticipate future price movements based on past institutional behavior.
How WhaleTrack Works
WhaleTrack analyzes historical trading volume and calculates a normalized volume intensity relative to the moving average (SMA). This data is then mapped onto a heatmap that highlights key liquidity zones.
1. Volume Normalization & SMA-Based Calculation
The script calculates the ratio of current volume to its SMA-based average.
Zones with significantly high volume spikes are identified as key liquidity areas where large traders may have accumulated or distributed assets.
The volume is quantized into different levels, ranging from Low to Extreme, creating a clear heatmap gradient.
2. Why Do Whales Manipulate Liquidity?
Large traders (whales) need liquidity to execute their orders.
They push price into historical high-volume areas to trigger stop-losses and force retail traders into selling.
This behavior allows them to accumulate at lower prices or distribute at higher prices before a major move.
Whale zones often act as support/resistance because institutions tend to protect their previous accumulation or distribution levels.
3. Heatmap Color Model & Zone Classification
WhaleTrack assigns volume intensity levels based on historical market participation:
Low → Minimal volume, weak interest
Low-Mid → Slightly increased volume
Mid → Standard trading activity, no major anomalies
Mid-High → Significant increase in volume, possible whale activity
High → Strong liquidity pool, institutional interest
Extreme → Highly concentrated volume, key reversal area
By observing these zones, traders can determine whether a price level is likely to hold as support or resistance , or if a breakout has the strength to sustain.
Trading Applications of WhaleTrack
WhaleTrack can be used to identify trade setups based on liquidity behavior:
1. Identifying Hidden Reversal Points (Support & Resistance)
Large Whale Zones below price → Likely strong support.
Large Whale Zones above price → Likely strong resistance.
These zones often lead to reversals, as large traders defend their previous positions.
2. Evaluating Trend Sustainability
A strong uptrend should leave multiple high-volume zones behind.
If no new high-volume zones form, the trend may be unsustainable.
High volume clusters in trend direction? → Likely trend continuation.
3. Optimizing Stop-Loss Placement
Placing stops inside whale zones increases stop-out risk.
Setting stops below whale buy zones protects against premature liquidation.
Stops above whale sell zones help avoid fake breakouts.
Customization & Settings
WhaleTrack is designed with flexibility in mind, offering multiple customization options:
1. Layout & Color Models
WhaleTrack Default – optimized for whale volume tracking
Model 1 & Model 2 – alternative heatmap color schemes
Contrast Mode – high visibility
White-Black & Black-White – for different chart backgrounds
Custom 1 & Custom 2 – user-defined color configurations
2. Advanced Options
Draw Full Candle Boxes – display full candle height or a partial range
Legend Visibility & Positioning – control placement of the heatmap legend
Exponential Color Model – choose between logarithmic and linear volume representation
Max Transparency Settings – adjust visibility of older zones
Number of Heatmap Colors – set the gradient sensitivity
3. Data Optimization Settings
Lookback Period – define how many bars are analyzed for volume normalization
Max Box Display – limit the number of displayed volume zones
Data Saver Mode – increase range at the expense of detail
Minimum Volume Threshold – filter out insignificant volume clusters
Disclaimer
This indicator is for educational and informational purposes only. It does not provide financial advice or guarantee future performance. Trading is risky—conduct your own research before making any investment decisions.
Volume Delta Imbalance Index [PhenLabs]📊 Volume Delta Imbalance Index (VDII)
Version: PineScript™ v6
Description
The Volume Delta Imbalance Index is an advanced technical analysis tool that combines volume profile analysis with price movement dynamics to identify significant market imbalances. It features a sophisticated analysis system that weighs recent versus historical volume delta imbalance patterns, providing traders with insights into potential market reversals and trend continuation scenarios.
Points of Innovation:
Custom volume delta calculation incorporating price and volume relationships
Adaptive smoothing system based on market volatility
Multi-component analysis combining flow, acceleration, and strength metrics
Real-time volume profile integration with historical context
🔧 Core Components
Volume Profile Analysis: Dynamic volume delta imbalance distribution assessment
Flow Imbalance Detection: Buy/sell pressure evaluation
Strength Analysis: Composite market strength measurement
Acceleration Framework: Volume movement dynamics
Statistical Bands: Adaptive threshold system
🚨 Key Features 🚨
The indicator provides comprehensive analysis through:
Volume Delta: Up to date volume imbalance measurement
Market Structure: Support/resistance level identification
Flow Analysis: Buy/sell pressure visualization
Acceleration Signals: Movement momentum detection
Adaptive Bands: Dynamic overbought/oversold levels
📈 Visualization
Color-coded Columns: Shows direction and strength of imbalance
Signal Lines: Strong buy/sell level indicators
Statistical Bands: Shows normal trading ranges
Gradient Fills: Indicates extreme market conditions
Dynamic Opacity: Reflects trend strength
📌 Usage Guidelines
The indicator offers several customization options:
Basic Settings:
Lookback Period: Analysis timeframe adjustment
Sensitivity Level: Signal response calibration
History Depth: Historical context range
Memory Setting: Recent vs. historical data weight
Visual Settings:
Color Scheme: Bullish/bearish signal colors
Signal Levels: Strong buy/sell thresholds
Band Display: Statistical range visualization
✅ Best Use Cases / Things To Look For:
Wait for establishment in the initial trend when the VDII comes back towards zero and the color of the volume becomes more faint
Once this is established and the VDII pushes through to the other side look for small retracements above the zero line on the VDII leading you to believe it is a likely area for price to retrace and continue in its prior direction
Make sure you see the volume bars become more faint in color to give yo further confluence price will continue in its priorly established direction
⚠️ Limitations
Requires sufficient volume data
Most effective in liquid markets
Historical depth affects calculation speed
Possible lag in highly volatile conditions
What Makes This Unique
Composite Volume Analysis: Combines multiple volume metrics
Adaptive Calculation: Adjusts to market volatility
Profile Integration: Incorporates volume profile analysis
Multi-component Scoring: Weighted analysis system
Memory-efficient Design: Optimized for real-time analysis
🔧 How It Works
The indicator processes market data through four main components:
1. Volume Profile Analysis:
Creates dynamic volume delta distribution profiles
Weights recent versus historical data
Identifies significant price levels
2. Flow Imbalance Detection:
Analyzes buying versus selling pressure
Calculates normalized flow ratios
Determines market bias
3. Strength Analysis:
Measures composite market strength
Incorporates volume-weighted movements
Provides trend strength indication
4. Final Score Calculation:
Combines all components with weighted importance
Applies volatility-based smoothing
Generates final signal output
5. VDII Potential Reversal Confluences
Bars between signal confluence is default set to 10 but you can change it to whatever you’d prefer
Signals are a compiled look at the indicator as a whole determining where it think reversals or retracements are likely
💡 Note:
The indicator performs best in markets with consistent volume and clear trending or ranging conditions. Its sophisticated volume analysis provides valuable insights into market dynamics beyond traditional price-based indicators.
Supply and Demand RebalancingPlease do not use this rudimentary script to lose money. As far as I can tell it has ZERO EDGE on its own.
Supply and Demand Pattern Detection Script
Overview
This script identifies potential supply and demand zones by detecting a specific double-wick pattern formation. It's designed as an educational tool and research aid for traders interested in price action and supply/demand concepts.
Pattern Detection
Looks for consecutive candles with long wicks (tails) that align with each other
The wicks must be larger than a specified percentile of recent wick lengths
The candle bodies must be relatively small compared to their wicks
Volume and volatility filters can be optionally applied
Higher timeframe trend confirmation is available as an optional filter
Visual Aids
Green triangles appear when a long setup is detected
Red triangles appear when a short setup is detected
Boxes show the risk zone (red) and reward zone (green)
Boxes extend until the trade reaches either its target or stop loss
A performance table shows win rate and profit factor statistics
Key Settings
1. Pattern Detection:
Wick Alignment Tolerance: How closely the wicks need to align
Min Wick Length Percentile: Minimum size requirement for wicks
Max Body/Wick Ratio: Controls maximum candle body size relative to wick
2. Additional Filters:
Volume Filter: Optional volume confirmation
ATR Filter: Optional volatility confirmation
Higher Timeframe Confirmation: Optional trend alignment
3. Trade Parameters:
Risk/Reward Ratio: Default 2:1
Bars to Wait for Outcome: How long to track trade results
Important Disclaimers
This is an educational tool and should NOT be used to trade real money without extensive testing and modification. Please do not use this rudimentary script to lose money. As far as I can tell it has zero edge on its own.
Historical backtesting results are not indicative of future performance. The script may miss some valid setups or generate false signals. Trade outcomes are simplified and don't account for:
Slippage
Trading fees
Market liquidity
Gap risk
Real-world execution challenges
Recommended Usage
Use as a learning tool to understand supply/demand concepts
Practice identifying these patterns manually
Paper trade the setups first
Combine with other forms of analysis and risk management
Consider it one tool among many, not a complete trading system
Best Practices
Always use proper risk management
Test thoroughly on demo accounts first
Keep detailed trading logs
Understand why each pattern forms
Study both winning and losing trades to improve pattern recognition
Remember: No trading script can guarantee profits. This tool is meant for educational purposes and should be part of a broader trading education and development process.
Quantify [Entry Model] | FractalystWhat’s the indicator’s purpose and functionality?
Quantify is a machine learning entry model designed to help traders identify high-probability setups to refine their strategies.
➙ Simply pick your bias, select your entry timeframes, and let Quantify handle the rest for you.
Can the indicator be applied to any market approach/trading strategy?
Absolutely, all trading strategies share one fundamental element: Directional Bias
Once you’ve determined the market bias using your own personal approach, whether it’s through technical analysis or fundamental analysis, select the trend direction in the Quantify user inputs.
The algorithm will then adjust its calculations to provide optimal entry levels aligned with your chosen bias. This involves analyzing historical patterns to identify setups with the highest potential expected values, ensuring your setups are aligned with the selected direction.
Can the indicator be used for different timeframes or trading styles?
Yes, regardless of the timeframe you’d like to take your entries, the indicator adapts to your trading style.
Whether you’re a swing trader, scalper, or even a position trader, the algorithm dynamically evaluates market conditions across your chosen timeframe.
How can this indicator help me to refine my trading strategy?
1. Focus on Positive Expected Value
• The indicator evaluates every setup to ensure it has a positive expected value, helping you focus only on trades that statistically favor long-term profitability.
2. Adapt to Market Conditions
• By analyzing real-time market behavior and historical patterns, the algorithm adjusts its calculations to match current conditions, keeping your strategy relevant and adaptable.
3. Eliminate Emotional Bias
• With clear probabilities, expected values, and data-driven insights, the indicator removes guesswork and helps you avoid emotional decisions that can damage your edge.
4. Optimize Entry Levels
• The indicator identifies optimal entry levels based on your selected bias and timeframes, improving robustness in your trades.
5. Enhance Risk Management
• Using tools like the Kelly Criterion, the indicator suggests optimal position sizes and risk levels, ensuring that your strategy maintains consistency and discipline.
6. Avoid Overtrading
• By highlighting only high-potential setups, the indicator keeps you focused on quality over quantity, helping you refine your strategy and avoid unnecessary losses.
How can I get started to use the indicator for my entries?
1. Set Your Market Bias
• Determine whether the market trend is Bullish or Bearish using your own approach.
• Select the corresponding bias in the indicator’s user inputs to align it with your analysis.
2. Choose Your Entry Timeframes
• Specify the timeframes you want to focus on for trade entries.
• The indicator will dynamically analyze these timeframes to provide optimal setups.
3. Let the Algorithm Analyze
• Quantify evaluates historical data and real-time price action to calculate probabilities and expected values.
• It highlights setups with the highest potential based on your selected bias and timeframes.
4. Refine Your Entries
• Use the insights provided—entry levels, probabilities, and risk calculations—to align your trades with a math-driven edge.
• Avoid overtrading by focusing only on setups with positive expected value.
5. Adapt to Market Conditions
• The indicator continuously adapts to real-time market behavior, ensuring its recommendations stay relevant and precise as conditions change.
How does the indicator calculate the current range?
The indicator calculates the current range by analyzing swing points from the very first bar on your charts to the latest available bar it identifies external liquidity levels, also known as BSLQ (buy-side liquidity levels) and SSLQ (sell-side liquidity levels).
What's the purpose of these levels? What are the underlying calculations?
1. Understanding Swing highs and Swing Lows
Swing High: A Swing High is formed when there is a high with 2 lower highs to the left and right.
Swing Low: A Swing Low is formed when there is a low with 2 higher lows to the left and right.
2. Understanding the purpose and the underlying calculations behind Buyside, Sellside and Pivot levels.
3. Identifying Discount and Premium Zones.
4. Importance of Risk-Reward in Premium and Discount Ranges
How does the script calculate probabilities?
The script calculates the probability of each liquidity level individually. Here's the breakdown:
1. Upon the formation of a new range, the script waits for the price to reach and tap into pivot level level. Status: "■" - Inactive
2. Once pivot level is tapped into, the pivot status becomes activated and it waits for either liquidity side to be hit. Status: "▶" - Active
3. If the buyside liquidity is hit, the script adds to the count of successful buyside liquidity occurrences. Similarly, if the sellside is tapped, it records successful sellside liquidity occurrences.
4. Finally, the number of successful occurrences for each side is divided by the overall count individually to calculate the range probabilities.
Note: The calculations are performed independently for each directional range. A range is considered bearish if the previous breakout was through a sellside liquidity. Conversely, a range is considered bullish if the most recent breakout was through a buyside liquidity.
What does the multi-timeframe functionality offer?
You can incorporate up to 4 higher timeframe probabilities directly into the table.
This feature allows you to analyze the probabilities of buyside and sellside liquidity across multiple timeframes, without the need to manually switch between them.
By viewing these higher timeframe probabilities in one place, traders can spot larger market trends and refine their entries and exits with a better understanding of the overall market context.
What are the multi-timeframe underlying calculations?
The script uses the same calculations (mentioned above) and uses security function to request the data such as price levels, bar time, probabilities and booleans from the user-input timeframe.
How does the Indicator Identifies Positive Expected Values?
Quantify instantly calculates whether a trade setup has the potential to generate positive expected value (EV).
To determine a positive EV setup, the indicator uses the formula:
EV = ( P(Win) × R(Win) ) − ( P(Loss) × R(Loss))
where:
- P(Win) is the probability of a winning trade.
- R(Win) is the reward or return for a winning trade, determined by the current risk-to-reward ratio (RR).
- P(Loss) is the probability of a losing trade.
- R(Loss) is the loss incurred per losing trade, typically assumed to be -1.
By calculating these values based on historical data and the current trading setup, the indicator helps you understand whether your trade has a positive expected value.
How can I know that the setup I'm going to trade with has a positive EV?
If the indicator detects that the adjusted pivot and buy/sell side probabilities have generated positive expected value (EV) in historical data, the risk-to-reward (RR) label within the range box will be colored blue and red .
If the setup does not produce positive EV, the RR label will appear gray.
This indicates that even the risk-to-reward ratio is greater than 1:1, the setup is not likely to yield a positive EV because, according to historical data, the number of losses outweighs the number of wins relative to the RR gain per winning trade.
What is the confidence level in the indicator, and how is it determined?
The confidence level in the indicator reflects the reliability of the probabilities calculated based on historical data. It is determined by the sample size of the probabilities used in the calculations. A larger sample size generally increases the confidence level, indicating that the probabilities are more reliable and consistent with past performance.
How does the confidence level affect the risk-to-reward (RR) label?
The confidence level (★) is visually represented alongside the probability label. A higher confidence level indicates that the probabilities used to determine the RR label are based on a larger and more reliable sample size.
How can traders use the confidence level to make better trading decisions?
Traders can use the confidence level to gauge the reliability of the probabilities and expected value (EV) calculations provided by the indicator. A confidence level above 95% is considered statistically significant and indicates that the historical data supporting the probabilities is robust. This high confidence level suggests that the probabilities are reliable and that the indicator’s recommendations are more likely to be accurate.
In data science and statistics, a confidence level above 95% generally means that there is less than a 5% chance that the observed results are due to random variation. This threshold is widely accepted in research and industry as a marker of statistical significance. Studies such as those published in the Journal of Statistical Software and the American Statistical Association support this threshold, emphasizing that a confidence level above 95% provides a strong assurance of data reliability and validity.
Conversely, a confidence level below 95% indicates that the sample size may be insufficient and that the data might be less reliable. In such cases, traders should approach the indicator’s recommendations with caution and consider additional factors or further analysis before making trading decisions.
How does the sample size affect the confidence level, and how does it relate to my TradingView plan?
The sample size for calculating the confidence level is directly influenced by the amount of historical data available on your charts. A larger sample size typically leads to more reliable probabilities and higher confidence levels.
Here’s how the TradingView plans affect your data access:
Essential Plan
The Essential Plan provides basic data access with a limited amount of historical data. This can lead to smaller sample sizes and lower confidence levels, which may weaken the robustness of your probability calculations. Suitable for casual traders who do not require extensive historical analysis.
Plus Plan
The Plus Plan offers more historical data than the Essential Plan, allowing for larger sample sizes and more accurate confidence levels. This enhancement improves the reliability of indicator calculations. This plan is ideal for more active traders looking to refine their strategies with better data.
Premium Plan
The Premium Plan grants access to extensive historical data, enabling the largest sample sizes and the highest confidence levels. This plan provides the most reliable data for accurate calculations, with up to 20,000 historical bars available for analysis. It is designed for serious traders who need comprehensive data for in-depth market analysis.
PRO+ Plans
The PRO+ Plans offer the most extensive historical data, allowing for the largest sample sizes and the highest confidence levels. These plans are tailored for professional traders who require advanced features and significant historical data to support their trading strategies effectively.
For many traders, the Premium Plan offers a good balance of affordability and sufficient sample size for accurate confidence levels.
What is the HTF probability table and how does it work?
The HTF (Higher Time Frame) probability table is a feature that allows you to view buy and sellside probabilities and their status from timeframes higher than your current chart timeframe.
Here’s how it works:
Data Request: The table requests and retrieves data from user-defined higher timeframes (HTFs) that you select.
Probability Display: It displays the buy and sellside probabilities for each of these HTFs, providing insights into the likelihood of price movements based on higher timeframe data.
Detailed Tooltips: The table includes detailed tooltips for each timeframe, offering additional context and explanations to help you understand the data better.
What do the different colors in the HTF probability table indicate?
The colors in the HTF probability table provide visual cues about the expected value (EV) of trading setups based on higher timeframe probabilities:
Blue: Suggests that entering a long position from the HTF user-defined pivot point, targeting buyside liquidity, is likely to result in a positive expected value (EV) based on historical data and sample size.
Red: Indicates that entering a short position from the HTF user-defined pivot point, targeting sellside liquidity, is likely to result in a positive expected value (EV) based on historical data and sample size.
Gray: Shows that neither long nor short trades from the HTF user-defined pivot point are expected to generate positive EV, suggesting that trading these setups may not be favorable.
What machine learning techniques are used in Quantify?
Quantify offers two main machine learning approaches:
1. Adaptive Learning (Fixed Sample Size): The algorithm learns from the entire dataset without resampling, maintaining a stable model that adapts to the latest market conditions.
2. Bootstrap Resampling: This method creates multiple subsets of the historical data, allowing the model to train on varying sample sizes. This technique enhances the robustness of predictions by ensuring that the model is not overfitting to a single dataset.
How does machine learning affect the expected value calculations in Quantify?
Machine learning plays a key role in improving the accuracy of expected value (EV) calculations. By analyzing historical price action, liquidity hits, and market bias patterns, the model continuously adjusts its understanding of risk and reward, allowing the expected value to reflect the most likely market movements. This results in more precise EV predictions, helping traders focus on setups that maximize profitability.
What is the Kelly Criterion, and how does it work in Quantify?
The Kelly Criterion is a mathematical formula used to determine the optimal position size for each trade, maximizing long-term growth while minimizing the risk of large drawdowns. It calculates the percentage of your portfolio to risk on a trade based on the probability of winning and the expected payoff.
Quantify integrates this with user-defined inputs to dynamically calculate the most effective position size in percentage, aligning with the trader’s risk tolerance and desired exposure.
How does Quantify use the Kelly Criterion in practice?
Quantify uses the Kelly Criterion to optimize position sizing based on the following factors:
1. Confidence Level: The model assesses the confidence level in the trade setup based on historical data and sample size. A higher confidence level increases the suggested position size because the trade has a higher probability of success.
2. Max Allowed Drawdown (User-Defined): Traders can set their preferred maximum allowed drawdown, which dictates how much loss is acceptable before reducing position size or stopping trading. Quantify uses this input to ensure that risk exposure aligns with the trader’s risk tolerance.
3. Probabilities: Quantify calculates the probabilities of success for each trade setup. The higher the probability of a successful trade (based on historical price action and liquidity levels), the larger the position size suggested by the Kelly Criterion.
What is a trailing stoploss, and how does it work in Quantify?
A trailing stoploss is a dynamic risk management tool that moves with the price as the market trend continues in the trader’s favor. Unlike a fixed take profit, which stays at a set level, the trailing stoploss automatically adjusts itself as the market moves, locking in profits as the price advances.
In Quantify, the trailing stoploss is enhanced by incorporating market structure liquidity levels (explain above). This ensures that the stoploss adjusts intelligently based on key price levels, allowing the trader to stay in the trade as long as the trend remains intact, while also protecting profits if the market reverses.
Why would a trader prefer a trailing stoploss based on liquidity levels instead of a fixed take-profit level?
Traders who use trailing stoplosses based on liquidity levels prefer this method because:
1. Market-Driven Flexibility: The stoploss follows the market structure rather than being static at a pre-defined level. This means the stoploss is less likely to be hit by small market fluctuations or false reversals. The stoploss remains adaptive, moving as the market moves.
2. Riding the Trend: Traders can capture more profit during a sustained trend because the trailing stop will adjust only when the trend starts to reverse significantly, based on key liquidity levels. This allows them to hold positions longer without prematurely locking in profits.
3. Avoiding Premature Exits: Fixed stoploss levels may exit a trade too early in volatile markets, while liquidity-based trailing stoploss levels respect the natural flow of price action, preventing the trader from exiting too soon during pullbacks or minor retracements.
🎲 Becoming the House: Gaining an Edge Over the Market
In American roulette, the casino has a 5.26% edge due to the presence of the 0 and 00 pockets. On even-money bets, players face a 47.37% chance of winning, while true 50/50 odds would require a 50% chance. This edge—the gap between the payout odds and the true probabilities—ensures that, statistically, the casino will always win over time, even if individual players win occasionally.
From a Trader’s Perspective
In trading, your edge comes from identifying and executing setups with a positive expected value (EV). For example:
• If you identify a setup with a 55.48% chance of winning and a 1:1 risk-to-reward (RR) ratio, your trade has a statistical advantage over a neutral (50/50) probability.
This edge works in your favor when applied consistently across a series of trades, just as the casino’s edge ensures profitability across thousands of spins.
🎰 Applying the Concept to Trading
Like casinos leverage their mathematical edge in games of chance, you can achieve long-term success in trading by focusing on setups with positive EV and managing your trades systematically. Here’s how:
1. Probability Advantage: Prioritize trades where the probability of success (win rate) exceeds the breakeven rate for your chosen risk-to-reward ratio.
• Example: With a 1:1 RR, you need a win rate above 50% to achieve positive EV.
2. Risk-to-Reward Ratio (RR): Even with a win rate below 50%, you can gain an edge by increasing your RR (e.g., a 40% win rate with a 2:1 RR still has positive EV).
3. Consistency and Discipline: Just as casinos profit by sticking to their mathematical advantage over thousands of spins, traders must rely on their edge across many trades, avoiding emotional decisions or overleveraging.
By targeting favorable probabilities and managing trades effectively, you “become the house” in your trading. This approach allows you to leverage statistical advantages to enhance your overall performance and achieve sustainable profitability.
What Makes the Quantify Indicator Original?
1. Data-Driven Edge
Unlike traditional indicators that rely on static formulas, Quantify leverages probability-based analysis and machine learning. It calculates expected value (EV) and confidence levels to help traders identify setups with a true statistical edge.
2. Integration of Market Structure
Quantify uses market structure liquidity levels to dynamically adapt. It identifies key zones like swing highs/lows and liquidity traps, enabling users to align entries and exits with where the market is most likely to react. This bridges the gap between price action analysis and quantitative trading.
3. Sophisticated Risk Management
The Kelly Criterion implementation is unique. Quantify allows traders to input their maximum allowed drawdown, dynamically adjusting risk exposure to maintain optimal position sizing. This ensures risk is scientifically controlled while maximizing potential growth.
4. Multi-Timeframe and Liquidity-Based Trailing Stops
The indicator doesn’t just suggest fixed profit-taking levels. It offers market structure-based trailing stop-loss functionality, letting traders ride trends as long as liquidity and probabilities favor the position, which is rare in most tools.
5. Customizable Bias and Adaptive Learning
• Directional Bias: Traders can set a bullish or bearish bias, and the indicator recalculates probabilities to align with the trader’s market outlook.
• Adaptive Learning: The machine learning model adapts to changes in data (via resampling or bootstrap methods), ensuring that predictions stay relevant in evolving markets.
6. Positive EV Focus
The focus on positive EV setups differentiates it from reactive indicators. It shifts trading from chasing signals to acting on setups that statistically favor profitability, akin to how professional quant funds operate.
7. User Empowerment
Through features like customizable timeframes, real-time probability updates, and visualization tools, Quantify empowers users to make data-informed decisions.
Terms and Conditions | Disclaimer
Our charting tools are provided for informational and educational purposes only and should not be construed as financial, investment, or trading advice. They are not intended to forecast market movements or offer specific recommendations. Users should understand that past performance does not guarantee future results and should not base financial decisions solely on historical data.
Built-in components, features, and functionalities of our charting tools are the intellectual property of @Fractalyst use, reproduction, or distribution of these proprietary elements is prohibited.
By continuing to use our charting tools, the user acknowledges and accepts the Terms and Conditions outlined in this legal disclaimer and agrees to respect our intellectual property rights and comply with all applicable laws and regulations.
LIT_Globas_sys - Liquidity Inducement Theorem (SMC, IDM)LIT_GLOBAL_SYS Trading Tool Documentation, is a comprehensive market analysis tool that includes all components needed for trading according to Liquidity Inducement Theorem (LIT). LIT differs from classical trading methods and is considered a highly effective and profitable strategy.
What can LIT_GLOBAL_SYS do?
--- Market Structure
The main feature of Liquidity Inducement Theorem is building the correct structure, specifically construction taking into account inducement (IDM). Thus, a new HH or LL can only form when the price has taken the first correct pullback - inducement (IDM), and after this, we understand the location of BoS (break of structure) and CHoCH (change of character).
LIT_GLOBAL_SYS automatically and perfectly displays the correct structure following all LIT rules. Looking at the indicator, a trader always understands which range the price is currently in and where it's trending at the moment. The indicator also shows dynamic (live) levels, providing a clear understanding of the market structure in real-time.
The indicator settings allow customization of each structural element according to trader preferences. For example, you can change the style, color, and shape of structural objects.
--- Correct Pullbacks and Inside Bars
In Liquidity Inducement Theorem, correct pullbacks are fundamental. The structure, order blocks, liquidity levels, order flow, and single candle order blocks (CSOB) are all built based on pullbacks.
What is a pullback?
- When the next candle updates the low of the previous candle, we can finish drawing an upward pullback
- We can start drawing a downward correct pullback when the next candle updates the low of the previous candle
- The downward movement will continue until the opposite occurs - updating the high of the previous candle
There are complexities in determining pullbacks - these are inside bars. In Liquidity Inducement Theorem, inside bars are completely ignored!
For example, in an upward movement, at some point, candles may stop updating the high and low of the previous candle and remain within the boundaries of the previous candle. Theoretically, there could be any number of such candles from 1 to infinity. In such cases, it's important to wait for the price to exit the mother candle (the candle after which other candles remained within its high and low range).
LIT_GLOBAL_SYS easily handles this and displays both pullbacks and inside bars correctly.
--- Order Blocks and Fair Value Gaps (FVG)
In Liquidity Inducement Theorem, order blocks are defined differently from classical order blocks:
1. The order block must take liquidity from the previous candle
2. The order block must have Fair Value Gaps (FVG) before it
3. Inside bars are completely ignored for both Order Blocks and FVG
4. If an OB fulfills the first condition (taking liquidity from the previous candle) but doesn't have FVG before it, this block is moved forward along the candles until there is an imbalance before it
There are two most important order blocks in LIT strategy:
1. Inducement order block (idm ob) - the first order block after Inducement
2. Extreme order block (Ext ob) - the first order block before CHoCH
LIT_GLOBAL_SYS perfectly displays correct order blocks and Fair Value Gaps following all rules. It offers full customization options:
- Specify the number of displayed OBs
- Disable all order blocks except idm ob and Ext ob
- Change block frame color and style
- Disable or modify text display in blocks
--- Single Candle Order Block (Scob)
Rules for building Scob:
1. The candle takes liquidity from the previous candle and closes within the body of the previous candle
2. The candle following the Scob candle must close its body below the previous candle
3. Scob forms in continuation of the trend movement
4. Scob completely ignores inside bars
LIT_GLOBAL_SYS accurately displays Scob as triangles and fully ignores inside bars both left and right. The menu allows complete customization of display and quantity of displayed Scobs.
--- Liquidity Lines, Order Flow, and Three-Minute Rule
Auxiliary functions include:
- Liquidity Lines -
Each pullback is marked with a line, showing where unclosed liquidity exists. Completed lines can be hidden to help predict price movement and enter trades correctly.
- Order Flow -
The indicator implements order flow by drawing a line when a pullback is broken (closed by body) in the opposite direction until the second touch. If price moves away without a second touch, the line remains, showing unclosed OF and potential price return zones.
- Three-Minute Rule -
Some LIT traders use the three-minute rule: price manipulations in the last and first three minutes of each 15-minute candle are additional entry factors, especially in the last quarter of an hourly candle. LIT_GLOBAL_SYS displays this rule only on the one-minute timeframe with symbols below for M15 and H1.
--- Trading Sessions, PDH/PDL, and EMA
The system includes:
- Trading sessions (Tokyo, Frankfurt, London, New York) with customizable time settings
- Previous Day High and Previous Day Low (pdh/pdl) levels
- Exponential Moving Average (EMA) with adjustable length
- Equilibrium display between current BoS and CHoCH levels
--- Alert System
LIT_GLOBAL_SYS includes all necessary alerts for Liquidity Inducement Theorem:
1. SCOB
2. EMA
3. BoS, ChoCh, Sweep
4. IDM
5. IDM OB and Ext OB
Users can simply check the desired alerts in the menu and activate them to receive notifications when price reaches specified zones.
OrderFlow [Adjustable] | FractalystWhat's the indicator's purpose and functionality?
This indicator is designed to assist traders in identifying real-time probabilities of buyside and sellside liquidity .
It allows for an adjustable pivot level , enabling traders to customize the level they want to use for their entries.
By doing so, traders can evaluate whether their chosen entry point would yield a positive expected value over a large sample size, optimizing their strategy for long-term profitability.
For advanced traders looking to enhance their analysis, the indicator supports the incorporation of up to 7 higher timeframe biases .
Additionally, the higher timeframe pivot level can be adjusted according to the trader's preferences,
Offering maximum adaptability to different strategies and needs, further helping to maximize positive EV.
EV=(P(Win)×R(Win))−(P(Loss)×R(Loss))
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What's the purpose of these levels? What are the underlying calculations?
1. Understanding Swing highs and Swing Lows
Swing High: A Swing High is formed when there is a high with 2 lower highs to the left and right.
Swing Low: A Swing Low is formed when there is a low with 2 higher lows to the left and right.
2. Understanding the purpose and the underlying calculations behind Buyside, Sellside and Pivot levels.
3. Identifying Discount and Premium Zones.
4. Importance of Risk-Reward in Premium and Discount Ranges
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How does the script calculate probabilities?
The script calculates the probability of each liquidity level individually. Here's the breakdown:
1. Upon the formation of a new range, the script waits for the price to reach and tap into pivot level level. Status: "⏸" - Inactive
2. Once pivot level is tapped into, the pivot status becomes activated and it waits for either liquidity side to be hit. Status: "▶" - Active
3. If the buyside liquidity is hit, the script adds to the count of successful buyside liquidity occurrences. Similarly, if the sellside is tapped, it records successful sellside liquidity occurrences.
4. Finally, the number of successful occurrences for each side is divided by the overall count individually to calculate the range probabilities.
Note: The calculations are performed independently for each directional range. A range is considered bearish if the previous breakout was through a sellside liquidity. Conversely, a range is considered bullish if the most recent breakout was through a buyside liquidity.
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What does the multi-timeframe functionality offer?
In the adjustable version of the orderflow indicator, you can incorporate up to 7 higher timeframe probabilities directly into the table.
This feature allows you to analyze the probabilities of buyside and sellside liquidity across multiple timeframes, without the need to manually switch between them.
By viewing these higher timeframe probabilities in one place, traders can spot larger market trends and refine their entries and exits with a better understanding of the overall market context.
This multi-timeframe functionality helps traders:
1. Simplify decision-making by offering a comprehensive view of multiple timeframes at once.
2. Identify confluence between timeframes, enhancing the confidence in trade setups.
3. Adapt strategies more effectively, as the higher timeframe pivot levels can be customized to meet individual preferences and goals.
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What are the multi-timeframe underlying calculations?
The script uses the same calculations (mentioned above) and uses security function to request the data such as price levels, bar time, probabilities and booleans from the user-input timeframe.
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How does the Indicator Identifies Positive Expected Values?
OrderFlow indicator instantly calculates whether a trade setup has the potential for positive expected value (EV) in the long run.
To determine a positive EV setup, the indicator uses the formula:
EV=(P(Win)×R(Win))−(P(Loss)×R(Loss))
where:
P(Win) is the probability of a winning trade.
R(Win) is the reward or return for a winning trade, determined by the current risk-to-reward ratio (RR).
P(Loss) is the probability of a losing trade.
R(Loss) is the loss incurred per losing trade, typically assumed to be -1.
By calculating these values based on historical data and the current trading setup, the indicator helps you understand whether your trade has a positive expected value over a large sample size.
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How can I know that the setup I'm going to trade with has a postive EV?
If the indicator detects that the adjusted pivot and buy/sell side probabilities have generated positive expected value (EV) in historical data, the risk-to-reward (RR) label within the range box will be colored blue and red .
If the setup does not produce positive EV, the RR label will appear gray.
This indicates that even the risk-to-reward ratio is greater than 1:1, the setup is not likely to yield a positive EV because, according to historical data, the number of losses outweighs the number of wins relative to the RR gain per winning trade.
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What is the confidence level in the indicator, and how is it determined?
The confidence level in the indicator reflects the reliability of the probabilities calculated based on historical data. It is determined by the sample size of the probabilities used in the calculations. A larger sample size generally increases the confidence level, indicating that the probabilities are more reliable and consistent with past performance.
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How does the confidence level affect the risk-to-reward (RR) label?
The confidence level (★) is visually represented alongside the probability label. A higher confidence level indicates that the probabilities used to determine the RR label are based on a larger and more reliable sample size.
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How can traders use the confidence level to make better trading decisions?
Traders can use the confidence level to gauge the reliability of the probabilities and expected value (EV) calculations provided by the indicator. A confidence level above 95% is considered statistically significant and indicates that the historical data supporting the probabilities is robust. This high confidence level suggests that the probabilities are reliable and that the indicator’s recommendations are more likely to be accurate.
In data science and statistics, a confidence level above 95% generally means that there is less than a 5% chance that the observed results are due to random variation. This threshold is widely accepted in research and industry as a marker of statistical significance. Studies such as those published in the Journal of Statistical Software and the American Statistical Association support this threshold, emphasizing that a confidence level above 95% provides a strong assurance of data reliability and validity.
Conversely, a confidence level below 95% indicates that the sample size may be insufficient and that the data might be less reliable . In such cases, traders should approach the indicator’s recommendations with caution and consider additional factors or further analysis before making trading decisions.
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How does the sample size affect the confidence level, and how does it relate to my TradingView plan?
The sample size for calculating the confidence level is directly influenced by the amount of historical data available on your charts. A larger sample size typically leads to more reliable probabilities and higher confidence levels.
Here’s how the TradingView plans affect your data access:
Essential Plan
The Essential Plan provides basic data access with a limited amount of historical data. This can lead to smaller sample sizes and lower confidence levels, which may weaken the robustness of your probability calculations. Suitable for casual traders who do not require extensive historical analysis.
Plus Plan
The Plus Plan offers more historical data than the Essential Plan, allowing for larger sample sizes and more accurate confidence levels. This enhancement improves the reliability of indicator calculations. This plan is ideal for more active traders looking to refine their strategies with better data.
Premium Plan
The Premium Plan grants access to extensive historical data, enabling the largest sample sizes and the highest confidence levels. This plan provides the most reliable data for accurate calculations, with up to 20,000 historical bars available for analysis. It is designed for serious traders who need comprehensive data for in-depth market analysis.
PRO+ Plans
The PRO+ Plans offer the most extensive historical data, allowing for the largest sample sizes and the highest confidence levels. These plans are tailored for professional traders who require advanced features and significant historical data to support their trading strategies effectively.
For many traders, the Premium Plan offers a good balance of affordability and sufficient sample size for accurate confidence levels.
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What is the HTF probability table and how does it work?
The HTF (Higher Time Frame) probability table is a feature that allows you to view buy and sellside probabilities and their status from timeframes higher than your current chart timeframe.
Here’s how it works:
Data Request : The table requests and retrieves data from user-defined higher timeframes (HTFs) that you select.
Probability Display: It displays the buy and sellside probabilities for each of these HTFs, providing insights into the likelihood of price movements based on higher timeframe data.
Detailed Tooltips: The table includes detailed tooltips for each timeframe, offering additional context and explanations to help you understand the data better.
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What do the different colors in the HTF probability table indicate?
The colors in the HTF probability table provide visual cues about the expected value (EV) of trading setups based on higher timeframe probabilities:
Blue: Suggests that entering a long position from the HTF user-defined pivot point, targeting buyside liquidity, is likely to result in a positive expected value (EV) based on historical data and sample size.
Red: Indicates that entering a short position from the HTF user-defined pivot point, targeting sellside liquidity, is likely to result in a positive expected value (EV) based on historical data and sample size.
Gray: Shows that neither long nor short trades from the HTF user-defined pivot point are expected to generate positive EV, suggesting that trading these setups may not be favorable.
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How to use the indicator effectively?
For Amateur Traders:
Start Simple: Begin by focusing on one timeframe at a time with the pivot level set to the default (50%). This helps you understand the basic functionality of the indicator.
Entry and Exit Strategy: Focus on entering trades at the pivot level while targeting the higher probability side for take profit and the lower probability side for stop loss.
Use simulation or paper trading to practice this strategy.
Adjustments: Once you have a solid understanding of how the indicator works, you can start adjusting the pivot level to other values that suit your strategy.
Ensure that the RR labels are colored (blue or red) to indicate positive EV setups before executing trades.
For Advanced Traders:
1. Select Higher Timeframe Bias: Choose a higher timeframe (HTF) as your main bias. Start with the default pivot level and ensure the confidence level is above 95% to validate the probabilities.
2. Align Lower Timeframes: Switch between lower timeframes to identify which ones align with your predefined HTF bias. This helps in synchronizing your trading decisions across different timeframes.
3. Set Entries with Current Pivot Level: Use the current pivot level for trade entries. Ensure the HTF status label is active, indicating that the probabilities are valid and in play.
4. Target HTF Liquidity Level: Aim for liquidity levels that correspond to the higher timeframe, as these levels are likely to offer better trading opportunities.
5. Adjust Pivot Levels: As you gain experience, adjust the pivot levels to further optimize your strategy for high EV. Fine-tune these levels based on the aggregated data from multiple timeframes.
6. Practice on Paper Trading: Test your strategies through paper trading to eliminate discretion and refine your approach without financial risk.
7. Focus on Trade Management: Ultimately, effective trade management is crucial. Concentrate on managing your trades well to ensure long-term success. By aiming for setups that produce positive EV, you can position yourself similarly to how a casino operates.
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🎲 Becoming the House (Gaining Edge Over the Market):
In American roulette, the house has a 5.26% edge due to the 0 and 00. This means that while players have a 47.37% chance of winning on even-money bets, the true odds are 50%. The discrepancy between the true odds and the payout ensures that, statistically, the casino will win over time.
From the Trader's Perspective: In trading, you gain an edge by focusing on setups with positive expected value (EV). If you have a 55.48% chance of winning with a 1:1 risk-to-reward ratio, your setup has a higher probability of profitability than the losing side. By consistently targeting such setups and managing your trades effectively, you create a statistical advantage, similar to the casino’s edge.
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🎰 Applying the Concept to Trading:
Just as casinos rely on their mathematical edge, you can achieve long-term success in trading by focusing on setups with positive EV. By ensuring that your probabilities and risk-to-reward (RR) ratios are in your favor, you create an edge similar to that of the house.
And by systematically targeting trades with favorable probabilities and managing your trades effectively, you improve your chances of profitability over the long run. Which is going to help you “become the house” in your trading, leveraging statistical advantages to enhance your overall performance.
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What makes this indicator original?
Real-Time Probability Calculations: The indicator provides real-time calculations of buy and sell probabilities based on historical data, allowing traders to assess the likelihood of positive expected value (EV) setups instantly.
Adjustable Pivot Levels: It features an adjustable pivot level that traders can modify according to their preferences, enhancing the flexibility to align with different trading strategies.
Multi-Timeframe Integration: The indicator supports up to 7 higher timeframes, displaying their probabilities and biases in a single view, which helps traders make informed decisions without switching timeframes.
Confidence Levels: It includes confidence levels based on sample sizes, offering insights into the reliability of the probabilities. Traders can gauge the strength of the data before making trades.
Dynamic EV Labels: The indicator provides color-coded EV labels that change based on the validity of the setup. Blue indicates positive EV in a long bias, red indicates positive EV in a short bias and gray signals caution, making it easier for traders to identify high-quality setups.
HTF Probability Table: The HTF probability table displays buy and sell probabilities from user-defined higher timeframes, helping traders integrate broader market context into their decision-making process.
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Terms and Conditions | Disclaimer
Our charting tools are provided for informational and educational purposes only and should not be construed as financial, investment, or trading advice. They are not intended to forecast market movements or offer specific recommendations. Users should understand that past performance does not guarantee future results and should not base financial decisions solely on historical data.
Built-in components, features, and functionalities of our charting tools are the intellectual property of @Fractalyst use, reproduction, or distribution of these proprietary elements is prohibited.
By continuing to use our charting tools, the user acknowledges and accepts the Terms and Conditions outlined in this legal disclaimer and agrees to respect our intellectual property rights and comply with all applicable laws and regulations.
Cumulative Delta [TradingFinder] Volume + Periodic + EMA🔵 Introduction
To fully grasp the concept of Cumulative Volume Delta (CVD), it's essential first to understand Volume Delta. In trading and technical analysis, the term "Delta" typically refers to the difference between two values or the rate of change between two data points.
Volume Delta represents the difference between buying and selling pressure, calculated for each candlestick on a chart. This difference can vary across different timeframes.
A positive delta indicates that buying volume exceeds selling volume, while a negative delta shows that selling volume is greater. When buying and selling volumes are equal, the volume delta equals zero.
🟣 What is Cumulative Volume Delta (CVD)?
Cumulative Volume Delta (CVD) is a powerful tool in technical analysis that aggregates delta values for each candlestick, creating a comprehensive indicator that helps traders assess market trends.
Unlike the standard Volume Delta, which compares delta on a candle-by-candle basis, CVD provides insight into the overall buying and selling pressure during key market swings. A downward-trending CVD suggests that selling pressure is dominating, which is typically a bearish signal.
Conversely, an upward-trending CVD indicates bullish sentiment. This analysis becomes even more significant when comparing CVD with price action and market structure, helping traders to predict asset price directions.
By evaluating market highs and lows, one can determine the market trend. A consistent rise in these points indicates an uptrend, while a consistent fall suggests a downtrend.
🔵 How to Use
Understanding how to detect trend changes using Cumulative Volume Delta is crucial for traders. Typically, CVD aligns with market structure, moving in the same direction as price trends.
However, divergences between CVD and price trends or signs of exhaustion in volume can be powerful indicators of potential market reversals. Recognizing these patterns can help traders make informed decisions and improve their trading strategies.
🟣 Identifying Trend Exhaustion with Cumulative Volume Delta (CVD)
The Cumulative Volume Delta (CVD) indicator is especially effective in identifying weakening trends in the market. For instance, if gold's price hits a new low, but CVD does not follow suit, this may indicate a lack of seller interest despite the new low, signaling potential seller exhaustion.
Most traders interpret this as a possible reversal from a bearish to a bullish trend. Similarly, if gold reaches a new high but CVD fails to do the same, it can suggest that buyers lack the strength to push the market higher, indicating a possible trend reversal.
🟣 Utilizing Cumulative Volume Delta (CVD) Divergence in Price Trend Analysis
Another effective use of CVD is identifying divergences in price trends. For example, if CVD breaks a previous high or low while the price remains stable, this divergence often indicates that buying or selling pressure is being absorbed.
For instance, if CVD rises sharply without a corresponding increase in gold prices, it may suggest that sellers are absorbing the buying pressure, potentially leading to a strong sell-off. Conversely, if gold prices remain stable while CVD declines, it could indicate that buyers are absorbing selling pressure, likely leading to a price increase once selling subsides.
🔵 Setting
Cumulative Mode : It has three modes "Total", "Periodic" and "EMA". In "Total" mode, it collects the volume from the beginning to the end. In "Periodic" mode, it accumulates the volume periodically and in "EMA" mode, it calculates the moving average of the volume.
Period : You can set the period of " Periodic " and " EMA " modes.
Market Ultra Data : If you turn on this feature, 26 large brokers will be included in the calculation of the trading volume.
The advantage of this capability is to have more reliable volume data. You should be careful to specify the market you are in, FOREX brokers and Crypto brokers are different.
🔵 Conclusion
Cumulative Volume Delta (CVD) is a powerful analytical tool in financial markets that helps analysts and traders assess buying and selling pressure by aggregating and combining the volume delta for each candlestick.
CVD can indicate the strength or weakness of a market trend. When CVD moves upward, it signals that buying pressure is dominant and is considered a bullish signal; conversely, a downward movement in CVD indicates that selling pressure is stronger and is viewed as a bearish signal.
This indicator is particularly effective in identifying divergences and exhaustion in market trends. For example, if CVD does not align with price movements, it may suggest a potential trend reversal.
Traders use this information to make more informed trading decisions, especially when identifying entry and exit points in the market.
Overall, CVD is a tool that enables analysts to better understand market fluctuations and more accurately predict future market trends.
Efficiency Weighted OrderFlow [AlgoAlpha]Introducing the Efficiency Weighted Orderflow Indicator by AlgoAlpha! 📈✨
Elevate your trading game with our cutting-edge Efficiency Weighted Orderflow Indicator, designed to provide clear insights into market trends and potential reversals. This tool is perfect for traders seeking to understand the underlying market dynamics through efficiency-weighted volume calculations.
🌟 Key Features 🌟
✨ Smooth OrderFlow Calculation : Option to smooth order flow data for more consistent signals.
🔧 Customizable Parameters : Adjust the Order Flow Period and HMA Smoothing Length to fit your trading strategy.
🔍 Visual Clarity : Easily distinguish between bullish and bearish trends with customizable colors.
📊 Standard Deviation Normalization : Keeps order flow values normalized for better comparison across different market conditions.
🔔 Trend Reversal Alerts : Stay ahead with built-in alert conditions for significant order flow changes.
🚀 Quick Guide to Using the Efficiency Weighted Orderflow Indicator
🛠 Add the Indicator: Search for "Efficiency Weighted Orderflow " in TradingView's Indicators & Strategies. Customize settings like smoothing and order flow period to fit your trading style.
📊 Market Analysis: Watch for trend reversal alerts to capture trading opportunities by studying the behaviour of the indicator.
🔔 Alerts: Enable notifications for significant order flow changes to stay updated on market trends.
🔍 How It Works
The Efficiency Weighted Orderflow Indicator starts by calculating the efficiency of price movements using the absolute difference between the close and open prices, divided by volume. The order flow is then computed by summing these efficiency-weighted volumes over a specified period, with an option to apply Hull Moving Average (HMA) smoothing for enhanced signal stability. To ensure robust comparison, the order flow is normalized using standard deviation. The indicator plots these values as columns, with distinct colors representing bullish and bearish trends. Customizable parameters for period length and smoothing allow traders to tailor the indicator to their strategies. Additionally, visual cues and alert conditions for trend reversals and significant order flow changes keep traders informed and ready to act. This indicator improves on the Orderflow aspect of our Standardized Orderflow indicator. The Efficiency Weighted Orderflow is less susceptible to noise and is also quicker at detecting trend changes.
Activity and Volume Orderflow Profile [AlgoAlpha]🔍 Activity and Volume Orderflow Profile 📊
🚀 Unlock the power of market order flow analysis with the Activity and Volume Orderflow Profile indicator by AlgoAlpha . This versatile tool helps you visualize and understand the dynamics of buying and selling pressure within a specified lookback period. Perfect for traders who want to dig deeper into volume-based market insights!
Key Features:
📊 Profile Type Options : Choose between "Comparison" and "Net Order Flow" to analyze market activity based on your preferred method.
🔎 Adjustable Lookback Period : Customize the lookback period to fit your trading strategy.
🎨 Flexible Appearance Settings : Toggle the display of the profile, lookback period visualization, and heatmap to suit your preferences.
🖍 Color Customization : Set your preferred colors for up and down volumes.
🕹 High Activity Highlight : Use the minimum transparency setting to highlight areas of significant activity.
Quick Guide to Using the Activity and Volume Orderflow Profile
🛠 Add the Indicator: Add the indicator to your favorites. Customize settings like profile type, lookback period, and resolution to fit your trading style.
📊 Market Analysis: Use the profile to identify areas of high buying or selling pressure. In "Comparison" mode, look for significant volume differences; in "Net Order Flow" mode, focus on net volume changes. Additionally, you can use the activity heatmap to find key levels that can act as support and resistance as price is likely to react to the zones as indicated by the heatmap.
How it Works:
The indicator operates by first gathering data on high and low prices, as well as buy and sell volumes, over a user-defined lookback period. It then calculates the maximum and minimum prices during this period and divides this range into bins based on the chosen resolution. For each bin, it computes the total volume of buy and sell orders. In "Comparison" mode, it displays side-by-side boxes representing buy and sell volumes, while in "Net Order Flow" mode, it shows the net volume difference. The indicator visually presents these profiles on the chart with customizable colors, transparency levels, and the option to display a heatmap for enhanced volume activity insights.
Maximize your trading with the Activity and Volume Orderflow Profile from AlgoAlpha! 🚀✨
OrderFlow Absorption IndicatorWhat it Does
The OrderFlow Absorption Indicator marks areas where the price absorbs a large volume of aggressive market trades. This indicates areas where price may bounce back due to large limit (resting) orders absorbing significant aggressor volume (market orders). Absorption can also be seen as "preventing" or "stopping" the other side from breaking through a price level (e.g. bids stopping an influx of sell market orders). Absorption may signal a change in sentiment, potentially leading to a pullback or reversal.
An Example of Absorption
Of course, it is not always the case that such bullish absorption will initiate a trend as the example above. The OrderFlow Absorption Indicator merely serves as a tool for spotting possible absorption points in the market which you can incorporate into your trading arsenal.
How it Works
The indicator actively monitors price changes and records volume accumulated at a price level. If the price bounces back to at least where it was before the current price move, the indicator records this as absorption, provided it meets the Volume Requirement and optional Time Requirement.
How to Use it
1. Set Parameters
Choose your desired tick size and volume filter value. If unsure, refer to the table on the top right of the chart for recommended values. An automatic volume limit filter mode is also available.
Automatic Limit Mode : Enable this mode to have the indicator automatically select a volume filter value. It calculates the standard deviation of the last n minutes of volume and multiplies it by a volume multiplier. You can adjust these parameters.
Higher Volume Filter : Setting a higher volume filter value results in fewer, but higher quality detections, reducing noise.
2. Enabling the Time Limit
Enabling the time limit further improves detection quality by filtering out price levels that can defend against quick, sudden aggressive orders, acting as confirmation and indicating strong sentiment and resilient liquidity.
3. Enabling Historical Data Absorption
The indicator can also detect absorption in historical data, though less accurately than in real-time due to OHLCV aggregation.
You can select the granularity of historical data.
Lower granularity (e.g., 1 second) : Provides more accurate detections but may slow down the indicator.
Higher granularity : Improves speed but reduces detection accuracy.
Other Features
Hovering : When hovering over an absorption point, the interface reveals the price where the absorption occurred, along with the volume absorbed by the bids and asks, as well as the volume filter value used.
Delta Mode : In Delta mode, the system calculates the difference between the volume absorbed by bids and asks, revealing points only when the absolute value of this difference exceeds the volume filter value. Especially useful for larger tick sizes.
Troubleshooting
If the indicator doesn't mark anything, it means the traded volume hasn't exceeded the set volume filter value within the specified price intervals(tick size) and time limit. Adjust these settings as necessary.
Net Buying/Selling Flows Toolkit [AlgoAlpha]🌟📊 Introducing the Net Buying/Selling Flows Toolkit by AlgoAlpha 📈🚀
🔍 Explore the intricate dynamics of market movements with the Net Buying/Selling Flows Toolkit designed for precision and effectiveness in visualizing money inflows and outflows and their impact on asset prices.
🔀 Multiple Display Modes : Choose from "Flow Comparison", "Net Flow", or "Sum of Flows" to view the data in the most relevant way for your analysis.
📏 Adjustable Unit Display : Easily manage the magnitude of the values displayed with options like "1 Billion", "1 Million", "1 Thousand", or "None".
🔧 Lookback Period Customization : Tailor the sum calculation window with a configurable lookback period, applicable in "Sum of Flows" mode.
📊 Deviation Thresholds : Set up lower and upper deviation thresholds to identify significant changes in flow data.
🔄 Reversal Signals and Deviation Bands : Enable signals for potential reversals and visualize deviation bands for comparative analysis.
🎨 Color-coded Visualization : Distinct colors for upward and downward movements make it easy to distinguish between buying and selling pressures.
🚀 Quick Guide to Using the Net Buying/Selling Flows Toolkit :
🔍 Add the Indicator : Add the indicator to you favorites. Customize the settings to fit your trading requirements.
👁️🗨️ Data Analysis : Compare the trend of Buying and Selling to help indicate whether bulls or bears are in control of the market. Utilize the different display modes to present the data in different form to suite your analysis style.
🔔 Set Alerts : Activate alerts for reversal conditions to keep abreast of significant market movements without having to monitor the charts constantly.
🌐 How It Works :
The toolkit processes volume data on a lower timeframe to distinguish between buying and selling pressures based on intra-bar price closing higher or lower than it opened. It aggregates these transactions and finds the net selling and buying that took place during that bar, offering a clearer view of market fundamentals. The indicator then plots this data visually with multiple modes including comparisons between buying/selling and the net flow of the asset. Deviation thresholds help in identifying significant changes, allowing traders to spot potential buying or selling opportunities based on the money flow dynamics. The "Sum of Flows" mode is unique from other trend following indicators as it does not determine trend based on price action, but rather based on the net buying/selling. Therefore in some cases the "Sum of Flows" mode can be a leading indicator showing bullish/bearish net flows even before the prices move significantly.
Embark on a more informed trading journey with this dynamic and insightful tool, tailor-made for those who demand precision and clarity in their trading strategies. 🌟📉📈
OrderFlow [Probabilities] | FractalystWhat's the indicator's purpose and functionality?
The indicator is designed to incorporate probabilities with buyside and sellside liquidity, as well as premium and discount ranges within the market. It also provides traders with a multi-timeframe functionality for observing liquidity levels and probabilities across two timeframes without the need to manually switch between them.
These levels are often used in smart money trading concepts for identifying key areas of interest, such as potential reversal points, areas of accumulation or distribution, and zones of high liquidity.
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What's the purpose of these levels? What are the underlying calculations?
1. Understanding Swing highs and Swing Lows
Swing High: A Swing High is formed when there is a high with 2 lower highs to the left and right.
Swing Low: A Swing Low is formed when there is a low with 2 higher lows to the left and right.
2. Understanding the purpose and the underlying calculations behind Buyside , Sellside and Equilibrium levels.
3. Identifying Discount and Premium Zones.
4. Importance of Risk-Reward in Premium and Discount Ranges
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How does the script calculate probabilities?
The script calculates the probability of each liquidity level individually. Here's the breakdown:
1. Upon the formation of a new range, the script waits for the price to reach and tap into equilibrium or the 50% level. Status: "⏸" - Inactive
2. Once equilibrium is tapped into, the equilibrium status becomes activated and it waits for either liquidity side to be hit. Status: "▶" - Active
3. If the buyside liquidity is hit, the script adds to the count of successful buyside liquidity occurrences. Similarly, if the sellside is tapped, it records successful sellside liquidity occurrences.
5. Finally, the number of successful occurrences for each side is divided by the overall count individually to calculate the range probabilities.
Note: The calculations are performed independently for each directional range. A range is considered bearish if the previous breakout was through a sellside liquidity. Conversely, a range is considered bullish if the most recent breakout was through a buyside liquidity.
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What does the multi-timeframe functionality offer?
Enabling and selecting a higher timeframe in the indicator's user-input settings allows you to access not only the current range information but also the liquidity sides, status, price levels, and probabilities of a higher timeframe without needing to switch between timeframes and mark up the levels manually.
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What are the multi-timeframe underlying calculations?
The script uses the same calculations (mentioned above) and requests the data such as price levels, bar time, probabilities and booleans from the user-input timeframe.
Non-repainting Security Function with Lookahead ON
//Function to fetch data for a given timeframe
getHTFData(timeframe_,exp_) =>
request.security(syminfo.tickerid, timeframe_,exp_ ,lookahead = barmerge.lookahead_on)
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How to use the indicator?
1. Add the indicator to your TradingView chart.
2. Choose the pair you want to analyze/trade.
3. Enable the HTF in user-input settings and choose a timeframe as for your higher timeframe bias.
4. (Important) : Ensure that the probabilities on both timeframes are aligned in one direction. If not, switch between timeframes until you find a pair of timeframes that are in line with each other and have higher probabilities on one liquidity side.
For Swing traders:
Use Hourly timeframes (1H/2H/4H/8H/12H) as your current timeframe and 1D/3D/1W/2W for your higher timeframe (HTF).
Entry: Hourly Equilibrium level. (Limit order)
Stoploss: Place it on the side where the probability is lower than 50%.
Break-even level/TP1: Hourly breakout of the liquidity.
TP2: Target the Higher Timeframe (HTF) liquidity level where the probability is higher than 50%.
2H/1D COINBASE:BTCUSD
For Day traders:
Use minutely timeframes (5m/15m/30m) as your current timeframe and 1H/2H/4H/8H/12H for your higher timeframe (HTF).
Entry: Minutely Equilibrium level. (Limit order)
Stoploss: Place it on the side where the probability is lower than 50%.
Break-even level/TP1: Minutely breakout of the liquidity.
TP2: Target the Higher Timeframe (HTF) liquidity level where the probability is higher than 50%.
1H/5m COINBASE:BTCUSD
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User-input settings and customizations
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What makes this indicator original?
1. Real-time calculation of probabilities directly on your charts.
2. Multi-timeframe functionality, enabling effortless observation of liquidity levels and probabilities across two timeframes.
3. Status label for clear identification of whether price has reached equilibrium.
4. All levels are updated only upon candle closure above or below liquidity levels, ensuring it remains a non-repainting indicator.
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Terms and Conditions | Disclaimer
Our charting tools are provided for informational and educational purposes only and should not be construed as financial, investment, or trading advice. They are not intended to forecast market movements or offer specific recommendations. Users should understand that past performance does not guarantee future results and should not base financial decisions solely on historical data.
By continuing to use our charting tools, the user acknowledges and accepts the Terms and Conditions outlined in this legal disclaimer.
Mxwll Liquidation Ranges - Mxwll CapitalIntroducing: Mxwll Liquidation Ranges
Mxwll Liquidation Ranges gathers data outside of TradingView to provide the highest quality, highest accuracy liquidation levels and ranges for popular crypto currencies.
Features
Real liquidation ranges and levels calculated outside of TradingView.
Real net position delta
Average leverage for long positions
Average leverage for short positions
Real number of bids for the cryptocurrency by the day
Real number of asks for the cryptocurrency by the day
Real Bid/Ask Ratio
Real Bid/Ask Delta
Real number of long market orders
Real number of short market orders
Real number of long limit orders
Real number of short limit orders
How do we obtain this data?
Using a now deprecated feature called "TradingView Pine Seeds", we are able to calculate the metrics listed above outside of TradingView and, consequently, import the data to TradingView for public use.
This means no indicators on TradingView that attempt to show liquidation levels, limit orders, net position delta, etc. can be as accurate as ours.
Why aren't other liquidation ranges indicators on TradingView as accurate as ours?
Simple: the data required to calculate liquidation levels and ranges isn't available on TradingView. No level 2 data, bids, asks, leverage information, pending limit orders, etc. This means any custom-coded indicator on TradingView attempting to use or show this information is just a guess, and is naturally inaccurate.
Mxwll Liquidation Ranges has access to all of the required data outside of TradingView, to which liquidation levels/ranges and other pertinent metrics are calculated and uploaded directly to TradingView using the Pine Seeds feature. This means that all information displayed by our indicator uses legitimate level 2 data outside of TradingView. Which means no "estimates" are required to produce this information. Consequently, unless a custom-coded indicator has access to the Pine Seeds feature and calculates liquidation levels and other level 2 data metrics outside of TradingView, then that indicator is inaccurate.
Liquidation Heatmap
The above image shows our liquidation heatmaps, which are calculated using level 2 data, in action.
Liquidation ranges are color coded. Purple/blue colored ranges indicate a lower number of net liquidations should the range be violated.
Green/yellow ranges indicate a liquidation range where the net number of liquidated positions, should the price range be violated, is substantial. Expect volatile price action around these areas and plan accordingly.
Yellow labels indicate the four highest liquidation ranges for the asset over the period.
Liquidation Levels
In addition to calculating a liquidation heatmap, Mxwll Liquidation Ranges also calculates liquidation levels by leverage. Level 2 data outside of TradingView is used.
Levels are colored coded by leverage used.
Green levels are 25x leverage liquidation areas.
Purple levels are 50x leverage liquidation areas.
Orange levels are 100x leverage liquidation areas.
Use this information to improve your trading plan and better pinpoint entries, exits, and key levels of expected volatility.
Other Metrics
Mxwll Liquidation Ranges uses level 2 data and the orderbook to calculate various metrics.
Average leverage for long positions
Average leverage for short positions
Real number of bids for the cryptocurrency by the day
Real number of asks for the cryptocurrency by the day
Real Bid/Ask Ratio
Real Bid/Ask Delta
Real number of long market orders
Real number of short market orders
Real number of long limit orders
Real number of short limit orders
How To Use
Understanding and interpreting heatmaps for predicting liquidation levels in trading can provide a significant edge. Here’s a basic guide on how to interpret these charts:
Understanding Liquidation Levels: Liquidation levels indicate where traders who are using leverage might be forced to exit their positions due to insufficient margin to cover their trades. These levels are crucial because they can trigger sudden price movements if many positions are liquidated at once.
Clusters on the Heatmap: On the heatmap, clusters of liquidation levels are represented by color-coded areas. These clusters show where significant numbers of leveraged positions are concentrated. The color intensity often indicates the density of liquidation points – darker or brighter colors suggest higher concentrations of liquidation risks.
Price Movements: By knowing where these clusters are, traders can anticipate potential price movements. For example, if a significant price drop moves the market closer to a cluster of liquidation levels, there’s an increased risk of those levels being triggered, potentially causing a sharp further drop due to cascading liquidations.
Strategic Trading: With this information, traders can strategically place their own stop losses or prepare to enter trades. Knowing where others might be forced to close their positions can help in predicting bullish or bearish movements.
Risk Management: Understanding liquidation levels helps in managing your own risk. Setting stop losses away from common liquidation points can avoid being caught in volatile price swings caused by mass liquidations.
- Mxwll Capital
[AlbaTherium] MTF External Ranges Analysis - ERA-Orion for SMC MTF External Ranges Analysis - ERA - Orion for Smart Money Concepts
Introduction:
The MTF External Ranges Analysis - ERA - Orion offers enhanced insights into multi-timeframe external structure points, swing structure points, POIs (Points of Interest), and order blocks (OB) . By incorporating this enhancement, your multi-timeframe analysis are streamlined, simplifying the process and reducing chart workload, no need for manual chart drawing anymore, stay focus on Low Time Frame and get High Time Frame insights in one single Time frame.
This identification process remains effective even when focusing on Lower Time Frames (LTF), providing detailed insights without sacrificing the broader market perspective.
The MTF External Ranges Analysis - ERA – Orion is specifically designed to be used in conjunction with OptiStruct™ Premium for Smart Money Concepts . This strategic combination enhances the workflow of identifying optimal entry points. OptiStruct acts as the analysis tool for Lower Time Frames (LTF), zeroing in on immediate interest areas, while Orion expands this analysis to Higher Time Frames (HTF), providing a broader view of market trends and importants key levels . The integration of Orion with OptiStruct seamlessly merges LTF and HTF analyses, ensuring a thorough understanding of market dynamics for informed and strategic decision-making. This toolkit in one package assembly is pivotal for traders relying on Smart Money Concepts, offering unmatched clarity and actionable insights to navigate the markets effectively.
This tool offers an advanced smart money technical analysis to improve your trading experience. It introduces four key concepts:
Main Features:
Entries Enhancements
Inducements HTF
High/Low Markings HTF
Multiple Timeframes and Confluences on Extreme, Dec and SMT Order Blocks
By integrating these concepts into one, traders can identify high-probability zones across multiple timeframes and develop a thorough understanding of market dynamics. These confluence zones enhance order block skills and potential, establishing them as essential pillars in smart money trading strategies and enabling traders to make more informed decisions.
Settings Overview:
HTF Settings Enable HTF Analysis
Select timeframe {Select or 4H Chart}
Labels Alignment for Lines and Boxes
Inside bar ranges HTF
Break of Structure /Change of Character HTF
Inducements HTF
High/Low Markings HTF
High/Low Sweeps HTF
Extreme Order Blocks HTF
Decisional Order Blocks HTF
Smart Money Traps HTF
IDM Demands and Supplies HTF
Historical Order Blocks HTF
OB Mitigation HTF {touch/ extended}
Understanding the Features:
Chapter 1: Entries Enhancements
In this chapter, we delve into strategies to refine trading entries, focusing on the multi-timeframe analysis of extreme or decisional order blocks in the High Time Frame timeframe as a key point of interest. We highlight the significance of transitioning to the Low Time Frame chart for observing pivotal shifts in market behavior. By examining these concepts, traders can gain deeper insights into market dynamics and make more informed entries decisions at critical junctures.
Practical Example:
We had an Order Block Extreme on the 1-hour timeframe, and currently, we are on the recommended chart for trade entry, which is the 5-minute timeframe. We are patiently waiting to observe a 5-minute ChoCh in the market to enter a buying position since it's an OB Extreme Demand on the 1-hour timeframe. Here, it's crucial and important to focus on the entry timeframe rather than checking what's happening in the higher timeframe. The indicator facilitates this task as it provides us with real-time perspective and visibility of everything happening in the higher timeframe.
Chapter 2: Inducements HTF
It is important and useful to be aware of the various liquidity points across the different timeframes we use; sometimes, a reliable entry point in the Lower Time Frame (LTF) may be surrounded by inducements. Consequently, this point becomes unreliable, and prior to the arrival of this functionality, such anomalies could not be detected, especially when focusing on the market in the LTF. From now on, there will be no more such issues.
Practical Example:
Suppose we identify an Order Block Extreme on the 5M timeframe, indicating a potential entry level. However, when we switch to the 5M timeframe to look for an entry point, we observe an accumulation of inducements around this Order Block coming from a higher timeframe, whether it's M15 or H1. This suggests a potential weakness in the entry point and significant market liquidity, which will act as a trap zone. Before the introduction of this feature, we might have missed this crucial observation, but now we can detect these anomalies and adjust our strategy accordingly.
The only practical way to see theses confluences is to use this Indicator, see the example below
Chapter 03: High/Low – Bos - ChoCh Markings HTF
The High/Low Markings HTF feature in the MTF External Ranges Analysis - ERA - Orion provides a comprehensive view into the market's heartbeat across different timeframes, right from within the convenience of the Lower Time Frame (LTF). It meticulously highlights pivotal shifts, allowing traders to seamlessly discern market sentiment and anticipate potential price reversals without needing to toggle between multiple charts. This innovation ensures that critical market movements and sentiment across various timeframes are visible and actionable from a single, focused LTF perspective, enhancing decision-making and strategic planning in trading activities.
Understanding High/Low Markings in HTF Analysis
High/Low Markings in High Time Frame (HTF) analysis mark the market's extremities within a given period, pinpointing potential areas for reversals or continuation and delineating crucial support and resistance levels. These markings are not arbitrary but represent significant market responses, serving as essential indicators for traders and analysts to gauge market momentum and sentiment.
The Role of HTF in Market Analysis
HTF analysis extends a comprehensive view over market movements, distinguishing between ephemeral fluctuations and substantial trend shifts. By scrutinizing these high and low points across wider time frames, analysts can unravel the underlying market momentum, enabling more strategic, informed trading decisions.
Identifying High/Low Markings
Identifying these crucial points entails detailed chart analysis over extended durations—daily, weekly, or monthly. The search focuses on the utmost highs and lows within these periods, which are more than mere points on a chart. They are significant market levels that have historically elicited robust market reactions, serving as key indicators for future market behavior.
Real-world Example:
Chapter 04: Multiple Timeframes and Confluences on Extreme, Dec and SMT Order Blocks Across HTF
The Orion indicator serves as a bridge between the multiple dimensions of the market, enabling a unified and strategic interpretation of potential movements. It's an indispensable tool for those seeking to capitalize on major opportunity zones, where the convergence of diverse perspectives creates ideal conditions for significant market movements.
Designed to navigate through the data of different timeframes and market analysis, Orion provides a clear and consolidated view of major points of interest. With this indicator, traders can not only spot opportunity zones where consensus is strongest but also adjust their strategies based on the dynamic interaction of various market participants, all while remaining within the Lower Time Frame (LTF).
Conclusion:
MTF External Ranges Analysis - ERA - Orion for Smart Money Concepts as “ The Orion ” indicator captures consensus among scalpers, day traders , swing traders, and investors, turning key areas into major opportunities. It allows for precise identification of areas of interest by analyzing the convergence of actions from various market participants. In short, Orion is crucial for detecting and leveraging the most promising points of convergence in the market.
This identification occurs even while focusing on Lower Time Frames (LTF), allowing for detailed insights without losing the broader market perspective.
This document provides an extensive overview of MTF External Ranges Analysis - ERA - Orion , emphasizing its importance in comprehending market dynamics and utilizing essential smart money concepts trading principles.
Order Chain [Kioseff Trading]Hello!
This indicator "Order Chain" uses live tick data (varip) to retrieve live tick volume.
This indicator must be used on a live market with volume data
Features
Live Tick Volume
Live Tick Volume Delta
Orders are appended to boxes, whose width and height are scaled proportional to the size of the order.
CVD recorded at relevant tick levels
Order chain spans up to 450 ticks (might include aggregates)
The image above shows key features for the indicator!
The image above explains line and color placements.
The image above shows the indicator in action for a live market!
How It Works
The indicator records the difference in volume from "now" and the previous tick. Predicated on whether the "now" price is greater than or less than price one tick prior, the difference in volume is recorded as "buy" or "sell" volume.
This filled order (or aggregates) is colored in congruence with price direction. The filled order is subsequently appended to its relevant tick level and added (buy order) or subtracted (sell order) from the CVD value at the identified tick level.
Of course, thank you to @PineCoders and @RicardoSantos for their awesome libraries :D
Thank you!
CBO (Candle Bias Oscillator)The Candle Bias Oscillator (CBO) with volume and ATR scaling is a unique technical analysis tool designed to capture market sentiment through the analysis of candlestick patterns, volume momentum, and market volatility. This indicator is built on the foundation of assessing the bias within a candlestick's body and wicks, adjusted for market volatility using the Average True Range (ATR), and further refined by comparing the Rate of Change (ROC) in volume and the adjusted bias. The culmination of these calculations results in the CBO, a smoothed oscillator that highlights potential market turning points through divergence analysis.
Key Features:
Bias Calculations: Utilizes the relationship between the candle's body and wicks to determine the market's immediate bias, offering a nuanced view beyond simple price action. Have you ever wanted to quantify exactly how bullish or bearish a particular candle or candlestick pattern is? Whether it's dojis, hammers, engulfing, gravestones, evening morning star, three soldiers etc. you don't have to memorize 50 candlestick patterns anymore.
Volatility Adjustment: Employs the ATR to adjust the bias calculation, ensuring the oscillator remains relevant across varying market conditions by accounting for volatility.
Momentum and Divergence: Measures the momentum in volume and bias through ROC calculations, identifying divergence that may signal reversals or significant price movements.
Signal Line: A smoothed version of the CBO, derived from its own values, serving as a benchmark for identifying potential crossovers and divergences.
Utility and Application:
The CBO with Divergence Scaling is developed for traders who seek a deeper understanding of market dynamics beyond price movements alone. It is particularly useful for identifying potential reversals or continuation patterns early, by highlighting divergence between market sentiment (as expressed through candlestick bias) and actual volume movements. In this way, it aligns us retail traders with institutional traders and smart money. This indicator is versatile and can be applied across various time frames and market instruments, offering value to both short-term traders and long-term investors.
How to Use:
Trend Identification: The direction and value of the CBO provide insights into the prevailing market trend. A positive oscillator value may indicate bullish sentiment, while a negative value suggests bearish sentiment.
Signal Line Crossovers: Crossovers between the CBO and its signal line can be used as potential buy or sell signals. A crossover above the signal line might indicate a buying opportunity, whereas a crossover below could suggest a selling point.
Divergence: Discrepancies between the CBO and price action (especially when confirmed by volume ROC) can highlight potential reversals.
Customization and Parameters: This script allows users to adjust several parameters, including oscillator periods, signal line periods, ATR periods, and ROC periods for divergence, to best fit their trading strategy and the characteristics of the market they are analyzing.
Conclusion:
The Custom Bias Oscillator with Divergence Scaling is a comprehensive tool designed to offer traders a multi-faceted view of market conditions, combining elements of price action, volatility, and momentum. By integrating these aspects into a single indicator, it aims to provide a more rounded and actionable insight into market trends and potential turning points.
To comply with best practices and ensure clarity regarding the informational nature of the Custom Bias Oscillator (CBO) tool, it's crucial to include a disclaimer about the non-advisory nature of the script. Here's a suitable disclaimer that you can add to the end of your script description or publication:
Disclaimer:
The Custom Bias Oscillator (CBO) with Divergence Scaling and its accompanying analysis are provided as tools for educational and informational purposes only and should not be construed as financial advice. The creator of this indicator does not guarantee any specific outcomes or profit, and all users should be aware of the risks involved in trading and investing. Users should conduct their own research and consult with a professional financial advisor before making any investment decisions. The use of this indicator is at the user's own risk, and the creator bears no responsibility for any direct or consequential loss arising from any use of this tool or the information provided herein.
Standardized Orderflow [AlgoAlpha]Introducing the Standardized Orderflow indicator by AlgoAlpha. This innovative tool is designed to enhance your trading strategy by providing a detailed analysis of order flow and velocity. Perfect for traders who seek a deeper insight into market dynamics, it's packed with features that cater to various trading styles. 🚀📊
Key Features:
📈 Order Flow Analysis: At its core, the indicator analyzes order flow, distinguishing between bullish and bearish volume within a specified period. It uses a unique standard deviation calculation for normalization, offering a clear view of market sentiment.
🔄 Smoothing Options: Users can opt for a smoothed representation of order flow, using a Hull Moving Average (HMA) for a more refined analysis.
🌪️ Velocity Tracking: The indicator tracks the velocity of order flow changes, providing insights into the market's momentum.
🎨 Customizable Display: Tailor the display mode to focus on either order flow, order velocity, or both, depending on your analysis needs.
🔔 Alerts for Critical Events: Set up alerts for crucial market events like crossover/crossunder of the zero line and overbought/oversold conditions.
How to Use:
1. Setup: Easily configure the indicator to match your trading strategy with customizable input parameters such as order flow period, smoothing length, and moving average types.
2. Interpretation: Watch for bullish and bearish columns in the order flow chart, utilize the Heiken Ashi RSI candle calculation, and look our for reversal notations for additional market insights.
3. Alerts: Stay informed with real-time alerts for key market events.
Code Explanation:
- Order Flow Calculation:
The core of the indicator is the calculation of order flow, which is the sum of volumes for bullish or bearish price movements. This is followed by normalization using standard deviation.
orderFlow = math.sum(close > close ? volume : (close < close ? -volume : 0), orderFlowWindow)
orderFlow := useSmoothing ? ta.hma(orderFlow, smoothingLength) : orderFlow
stdDev = ta.stdev(orderFlow, 45) * 1
normalizedOrderFlow = orderFlow/(stdDev + stdDev)
- Velocity Calculation:
The velocity of order flow changes is calculated using moving averages, providing a dynamic view of market momentum.
velocityDiff = ma((normalizedOrderFlow - ma(normalizedOrderFlow, velocitySignalLength, maTypeInput)) * 10, velocityCalcLength, maTypeInput)
- Display Options:
Users can choose their preferred display mode, focusing on either order flow, order velocity, or both.
orderFlowDisplayCond = displayMode != "Order Velocity" ? display.all : display.none
wideDisplayCond = displayMode != "Order Flow" ? display.all : display.none
- Reversal Indicators and Divergences:
The indicator also includes plots for potential bullish and bearish reversals, as well as regular and hidden divergences, adding depth to your market analysis.
bullishReversalCond = reversalType == "Order Flow" ? ta.crossover(normalizedOrderFlow, -1.5) : (reversalType == "Order Velocity" ? ta.crossover(velocityDiff, -4) : (ta.crossover(velocityDiff, -4) or ta.crossover(normalizedOrderFlow, -1.5)) )
bearishReversalCond = reversalType == "Order Flow" ? ta.crossunder(normalizedOrderFlow, 1.5) : (reversalType == "Order Velocity" ? ta.crossunder(velocityDiff, 4) : (ta.crossunder(velocityDiff, 4) or ta.crossunder(normalizedOrderFlow, 1.5)) )
In summary, the Standardized Orderflow indicator by AlgoAlpha is a versatile tool for traders aiming to enhance their market analysis. Whether you're focused on short-term momentum or long-term trends, this indicator provides valuable insights into market dynamics. 🌟📉📈
Whalemap [BigBeluga]The Whalemap indicator aims to spot big buying and selling activity represented as big orders for a possible bottom or top formation on the chart.
🔶 CALCULATION
The indicator uses volume to spot big volume activity represented as big orders in the market.
for i = 0 to len - 1
blV.vol += (close > close ? volume : 0)
brV.vol += (close < close ? volume : 0)
When volume exceeds its own threshold, it is a sign that volume is exceeding its normal value and is considered as a "Whale order" or "Whale activity," which is then plotted on the chart as circles.
🔶 DETAILS
The indicator plots Bubbles on the chart with different sizes indicating the buying or selling activity. The bigger the circle, the more impact it will have on the market.
On each circle is also plotted a line, and its own weight is also determined by the strength of its own circle; the bigger the circle, the bigger the line.
Old buying/selling activity can also be used for future support and resistance to spot interesting areas.
The more price enters old buying/selling activity and starts producing orders of the same direction, it might be an interesting point to take a closer look.
🔶 EXAMPLES
The chart above is showing us price reacting to big orders, finding good bottoms in price and good tops in confluence with old activity.
🔶 SETTINGS
Users will have the options to:
Filter options to adjust buying and selling sensitivity.
Display/Hide Lines
Display/Hide Bubbles
Choose which orders to display (from smallest to biggest)
Footprint Chart + Volume ProfileFootprint charts provide volume information to candlestick charts. This indicator specifically provides the quantity of Market Orders executed on each side of the Order Book, thereby showing you the number of contracts that had hit the bid or the offer - and it does so on each bar.
In addition, it visualises a Volume Profile for each bar, providing you an even better visualisation, contrasted to that which renders the numbers alone.
This Footprint Chart calculates executed orders by getting the change in volume for every price move and pooling them on their corresponding "tick bucket". Their specific "tick bucket" is calculated on the nearest "tick", the size of which you will provide by setting the "Tick Size/ Increment" to whichever tick size you need .
For instance, volume changes on a price of 10.4 on a 1 tick Footprint Chart will be recorded as part of the nearest whole number(10), while on a 3 tick Footprint Chart, it will be recorded as part of 9 as it is the nearest multiple of 3.
Calculating the "tick bucket" this way is most conservative, however, if you would like it calculated differently — Having the volume changes recorded on the succeeding tick, e.g. Recording 10.4 as 12 on a 3 tick Footprint Chart. Simply set the "Tick Basket Assignment" to "Next Tick", While setting the same to "Previous Tick" records volume changes on the preceding tick. Default is "Nearest Tick".
How to read the Footprint Chart?
This Footprint Chart depicts a portion of the Depth of Market, arranged in such a way that the left side represents the bid, while the right side represents the ask. It is therefore natural that orders hitting the bid (Market Sells) are to be placed on the Left Side of the chart while orders hitting the ask (Market Buys) are to be placed on the Right Side. This way, you can visualise how the current price came to be, as well as observe with the several order flow analysis concepts and ideas you can apply. In summary, numbers on the Left represents Sell Orders and numbers on the Right represents Buy Orders.
If, however, you wish to see only the total volume that transacted within the bar, you may do so by toggling the "Split Buy and Sell" option.
Footprint Chart showing only the total volume:
Furthermore, this chart has its own candles, the width of which can be adjusted accordingly.
Volume Profile
This Footprint Chart offers a Stacked Volume Profile and an Unstacked Volume Profile, the former renders a Volume Profile which compares the buys from the sells, the better to visualise levels of activity, the latter renders a standard Volume Profile which shows the total volume that transacted on a price tick.
The type of Volume Profile that this Footprint Chart renders is similar to that of a Periodic Volume Profile, which renders Volume Profiles for every bar on the chart. Furthermore, the width of each Volume Profile bar of this Footprint Chart is relative to the largest volume transacted on the current session, the session beginning from the point you have opened the Footprint Chart until the 500th bar, capped for optimisational purposes, and shall adjust the session start accordingly once this limit had been reached. The Volume Profile bars' width will therefore change agreeably to each significant volume update, and sized relatively with that of the others.
Optimisation
This Footprint Chart utilises several drawings and calculations for attaining its visuals, the arrangement of which makes it more pleasing and easier to understand. Several optimisations have been implemented within the code, e.g. utilising queues, however, if you wish for it to be even more optimised, you can use an "Unstacked" Volume Profile, using larger tick sizes, as well as using 0 decimal placements for the Footprint Chart.
Furthermore, deselecting "Use Stacked Bars" will allow more boxes to be drawn, and will double the amount of boxes the volume profile can use.
Limitations
No historical tick data have yet been made available for use and so this Footprint Chart only has realtime data at its disposal. Historical footprints are therefore not rendered, the boundary of which is delineated by a vertical broken line.
Tips
This Footprint Chart is best viewed on a chart of its own, and it is therefore ideal to clear the chart of other candles by hiding them or utilising a line chart alternatively . In addition, stretch the time scale to its utmost capacity, the better to see properly the Volume Profile, as well as stretch the price scale to a proper height, the better to read the footprint volumes inscribed on the indicator.
Warnings
Changing settings may cause the Footprint Chart to reset. If, in case you have been accumulating Footprint Charts and wish to change some settings for the benefit of your charting, it is best to take a snapshot of your chart prior, for recent changes may cause resets to occur.
