GEEKSDOBYTE IFVG w/ Buy/Sell Signals1. Inputs & Configuration
Swing Lookback (swingLen)
Controls how many bars on each side are checked to mark a swing high or swing low (default = 5).
Booleans to Toggle Plotting
showSwings – Show small triangle markers at swing highs/lows
showFVG – Show Fair Value Gap zones
showSignals – Show “BUY”/“SELL” labels when price inverts an FVG
showDDLine – Show a yellow “DD” line at the close of the inversion bar
showCE – Show an orange dashed “CE” line at the midpoint of the gap area
2. Swing High / Low Detection
isSwingHigh = ta.pivothigh(high, swingLen, swingLen)
Marks a bar as a swing high if its high is higher than the highs of the previous swingLen bars and the next swingLen bars.
isSwingLow = ta.pivotlow(low, swingLen, swingLen)
Marks a bar as a swing low if its low is lower than the lows of the previous and next swingLen bars.
Plotting
If showSwings is true, small red downward triangles appear above swing highs, and green upward triangles below swing lows.
3. Fair Value Gap (3‐Bar) Identification
A Fair Value Gap (FVG) is defined here using a simple three‐bar logic (sometimes called an “inefficiency” in price):
Bullish FVG (bullFVG)
Checks if, two bars ago, the low of that bar (low ) is strictly greater than the current bar’s high (high).
In other words:
bullFVG = low > high
Bearish FVG (bearFVG)
Checks if, two bars ago, the high of that bar (high ) is strictly less than the current bar’s low (low).
In other words:
bearFVG = high < low
When either condition is true, it identifies a three‐bar “gap” or unfilled imbalance in the market.
4. Drawing FVG Zones
If showFVG is enabled, each time a bullish or bearish FVG is detected:
Bullish FVG Zone
Draws a semi‐transparent green box from the bar two bars ago (where the gap began) at low up to the current bar’s high.
Bearish FVG Zone
Draws a semi‐transparent red box from the bar two bars ago at high down to the current bar’s low.
These colored boxes visually highlight the “fair value imbalance” area on the chart.
5. Inversion (Fill) Detection & Entry Signals
An inversion is defined as the price “closing through” that previously drawn FVG:
Bullish Inversion (bullInversion)
Occurs when a bullish FVG was identified on bar-2 (bullFVG), and on the current bar the close is greater than that old bar-2 low:
bullInversion = bullFVG and close > low
Bearish Inversion (bearInversion)
Occurs when a bearish FVG was identified on bar-2 (bearFVG), and on the current bar the close is lower than that old bar-2 high:
bearInversion = bearFVG and close < high
When an inversion is true, the indicator optionally draws two lines and a label (depending on input toggles):
Draw “DD” Line (yellow, solid)
Plots a horizontal yellow line from the current bar’s close price extending five bars forward (bar_index + 5). This is often referred to as a “Demand/Daily Demand” line, marking where price inverted the gap.
Draw “CE” Line (orange, dashed)
Calculates the midpoint (ce) of the original FVG zone.
For a bullish inversion:
ce = (low + high) / 2
For a bearish inversion:
ce = (high + low) / 2
Plots a horizontal dashed orange line at that midpoint for five bars forward.
Plot Label (“BUY” / “SELL”)
If showSignals is true, a green “BUY” label is placed at the low of the current bar when a bullish inversion occurs.
Likewise, a red “SELL” label at the high of the current bar when a bearish inversion happens.
6. Putting It All Together
Swing Markers (Optional):
Visually confirm recent swing highs and swing lows with small triangles.
FVG Zones (Optional):
Highlight areas where price left a 3-bar gap (bullish in green, bearish in red).
Inversion Confirmation:
Wait for price to close beyond the old FVG boundary.
Once that happens, draw the yellow “DD” line at the close, the orange dashed “CE” line at the zone’s midpoint, and place a “BUY” or “SELL” label exactly on that bar.
User Controls:
All of the above elements can be individually toggled on/off (showSwings, showFVG, showSignals, showDDLine, showCE).
In Practice
A bullish FVG forms whenever a strong drop leaves a gap in liquidity (three bars ago low > current high).
When price later “fills” that gap by closing above the old low, the script signals a potential long entry (BUY), draws a demand line at the closing price, and marks the midpoint of that gap.
Conversely, a bearish FVG marks a potential short zone (three bars ago high < current low). When price closes below that gap’s high, it signals a SELL, with similar lines drawn.
By combining these elements, the indicator helps users visually identify inefficiencies (FVGs), confirm when price inverts/fills them, and place straightforward buy/sell labels alongside reference lines for trade management.
Cerca negli script per "demand"
Advanced Petroleum Market Model (APMM)Advanced Petroleum Market Model (APMM): A Multi-Factor Fundamental Analysis Framework for Oil Market Assessment
## 1. Introduction
The petroleum market represents one of the most complex and globally significant commodity markets, characterized by intricate supply-demand dynamics, geopolitical influences, and substantial price volatility (Hamilton, 2009). Traditional fundamental analysis approaches often struggle to synthesize the multitude of relevant indicators into actionable insights due to data heterogeneity, temporal misalignment, and subjective weighting schemes (Baumeister & Kilian, 2016).
The Advanced Petroleum Market Model addresses these limitations through a systematic, quantitative approach that integrates 16 verified fundamental indicators across five critical market dimensions. The model builds upon established financial engineering principles while incorporating petroleum-specific market dynamics and adaptive learning mechanisms.
## 2. Theoretical Framework
### 2.1 Market Efficiency and Information Integration
The model operates under the assumption of semi-strong market efficiency, where fundamental information is gradually incorporated into prices with varying degrees of lag (Fama, 1970). The petroleum market's unique characteristics, including storage costs, transportation constraints, and geopolitical risk premiums, create opportunities for fundamental analysis to provide predictive value (Kilian, 2009).
### 2.2 Multi-Factor Asset Pricing Theory
Drawing from Ross's (1976) Arbitrage Pricing Theory, the model treats petroleum prices as driven by multiple systematic risk factors. The five-factor decomposition (Supply, Inventory, Demand, Trade, Sentiment) represents economically meaningful sources of systematic risk in petroleum markets (Chen et al., 1986).
## 3. Methodology
### 3.1 Data Sources and Quality Framework
The model integrates 16 fundamental indicators sourced from verified TradingView economic data feeds:
Supply Indicators:
- US Oil Production (ECONOMICS:USCOP)
- US Oil Rigs Count (ECONOMICS:USCOR)
- API Crude Runs (ECONOMICS:USACR)
Inventory Indicators:
- US Crude Stock Changes (ECONOMICS:USCOSC)
- Cushing Stocks (ECONOMICS:USCCOS)
- API Crude Stocks (ECONOMICS:USCSC)
- API Gasoline Stocks (ECONOMICS:USGS)
- API Distillate Stocks (ECONOMICS:USDS)
Demand Indicators:
- Refinery Crude Runs (ECONOMICS:USRCR)
- Gasoline Production (ECONOMICS:USGPRO)
- Distillate Production (ECONOMICS:USDFP)
- Industrial Production Index (FRED:INDPRO)
Trade Indicators:
- US Crude Imports (ECONOMICS:USCOI)
- US Oil Exports (ECONOMICS:USOE)
- API Crude Imports (ECONOMICS:USCI)
- Dollar Index (TVC:DXY)
Sentiment Indicators:
- Oil Volatility Index (CBOE:OVX)
### 3.2 Data Quality Monitoring System
Following best practices in quantitative finance (Lopez de Prado, 2018), the model implements comprehensive data quality monitoring:
Data Quality Score = Σ(Individual Indicator Validity) / Total Indicators
Where validity is determined by:
- Non-null data availability
- Positive value validation
- Temporal consistency checks
### 3.3 Statistical Normalization Framework
#### 3.3.1 Z-Score Normalization
The model employs robust Z-score normalization as established by Sharpe (1994) for cross-indicator comparability:
Z_i,t = (X_i,t - μ_i) / σ_i
Where:
- X_i,t = Raw value of indicator i at time t
- μ_i = Sample mean of indicator i
- σ_i = Sample standard deviation of indicator i
Z-scores are capped at ±3 to mitigate outlier influence (Tukey, 1977).
#### 3.3.2 Percentile Rank Transformation
For intuitive interpretation, Z-scores are converted to percentile ranks following the methodology of Conover (1999):
Percentile_Rank = (Number of values < current_value) / Total_observations × 100
### 3.4 Exponential Smoothing Framework
Signal smoothing employs exponential weighted moving averages (Brown, 1963) with adaptive alpha parameter:
S_t = α × X_t + (1-α) × S_{t-1}
Where α = 2/(N+1) and N represents the smoothing period.
### 3.5 Dynamic Threshold Optimization
The model implements adaptive thresholds using Bollinger Band methodology (Bollinger, 1992):
Dynamic_Threshold = μ ± (k × σ)
Where k is the threshold multiplier adjusted for market volatility regime.
### 3.6 Composite Score Calculation
The fundamental score integrates component scores through weighted averaging:
Fundamental_Score = Σ(w_i × Score_i × Quality_i)
Where:
- w_i = Normalized component weight
- Score_i = Component fundamental score
- Quality_i = Data quality adjustment factor
## 4. Implementation Architecture
### 4.1 Adaptive Parameter Framework
The model incorporates regime-specific adjustments based on market volatility:
Volatility_Regime = σ_price / μ_price × 100
High volatility regimes (>25%) trigger enhanced weighting for inventory and sentiment components, reflecting increased market sensitivity to supply disruptions and psychological factors.
### 4.2 Data Synchronization Protocol
Given varying publication frequencies (daily, weekly, monthly), the model employs forward-fill synchronization to maintain temporal alignment across all indicators.
### 4.3 Quality-Adjusted Scoring
Component scores are adjusted for data quality to prevent degraded inputs from contaminating the composite signal:
Adjusted_Score = Raw_Score × Quality_Factor + 50 × (1 - Quality_Factor)
This formulation ensures that poor-quality data reverts toward neutral (50) rather than contributing noise.
## 5. Usage Guidelines and Best Practices
### 5.1 Configuration Recommendations
For Short-term Analysis (1-4 weeks):
- Lookback Period: 26 weeks
- Smoothing Length: 3-5 periods
- Confidence Period: 13 weeks
- Increase inventory and sentiment weights
For Medium-term Analysis (1-3 months):
- Lookback Period: 52 weeks
- Smoothing Length: 5-8 periods
- Confidence Period: 26 weeks
- Balanced component weights
For Long-term Analysis (3+ months):
- Lookback Period: 104 weeks
- Smoothing Length: 8-12 periods
- Confidence Period: 52 weeks
- Increase supply and demand weights
### 5.2 Signal Interpretation Framework
Bullish Signals (Score > 70):
- Fundamental conditions favor price appreciation
- Consider long positions or reduced short exposure
- Monitor for trend confirmation across multiple timeframes
Bearish Signals (Score < 30):
- Fundamental conditions suggest price weakness
- Consider short positions or reduced long exposure
- Evaluate downside protection strategies
Neutral Range (30-70):
- Mixed fundamental environment
- Favor range-bound or volatility strategies
- Wait for clearer directional signals
### 5.3 Risk Management Considerations
1. Data Quality Monitoring: Continuously monitor the data quality dashboard. Scores below 75% warrant increased caution.
2. Regime Awareness: Adjust position sizing based on volatility regime indicators. High volatility periods require reduced exposure.
3. Correlation Analysis: Monitor correlation with crude oil prices to validate model effectiveness.
4. Fundamental-Technical Divergence: Pay attention when fundamental signals diverge from technical indicators, as this may signal regime changes.
### 5.4 Alert System Optimization
Configure alerts conservatively to avoid false signals:
- Set alert threshold at 75+ for high-confidence signals
- Enable data quality warnings to maintain system integrity
- Use trend reversal alerts for early regime change detection
## 6. Model Validation and Performance Metrics
### 6.1 Statistical Validation
The model's statistical robustness is ensured through:
- Out-of-sample testing protocols
- Rolling window validation
- Bootstrap confidence intervals
- Regime-specific performance analysis
### 6.2 Economic Validation
Fundamental accuracy is validated against:
- Energy Information Administration (EIA) official reports
- International Energy Agency (IEA) market assessments
- Commercial inventory data verification
## 7. Limitations and Considerations
### 7.1 Model Limitations
1. Data Dependency: Model performance is contingent on data availability and quality from external sources.
2. US Market Focus: Primary data sources are US-centric, potentially limiting global applicability.
3. Lag Effects: Some fundamental indicators exhibit publication lags that may delay signal generation.
4. Regime Shifts: Structural market changes may require model recalibration.
### 7.2 Market Environment Considerations
The model is optimized for normal market conditions. During extreme events (e.g., geopolitical crises, pandemics), additional qualitative factors should be considered alongside quantitative signals.
## References
Baumeister, C., & Kilian, L. (2016). Forty years of oil price fluctuations: Why the price of oil may still surprise us. *Journal of Economic Perspectives*, 30(1), 139-160.
Bollinger, J. (1992). *Bollinger on Bollinger Bands*. McGraw-Hill.
Brown, R. G. (1963). *Smoothing, Forecasting and Prediction of Discrete Time Series*. Prentice-Hall.
Chen, N. F., Roll, R., & Ross, S. A. (1986). Economic forces and the stock market. *Journal of Business*, 59(3), 383-403.
Conover, W. J. (1999). *Practical Nonparametric Statistics* (3rd ed.). John Wiley & Sons.
Fama, E. F. (1970). Efficient capital markets: A review of theory and empirical work. *Journal of Finance*, 25(2), 383-417.
Hamilton, J. D. (2009). Understanding crude oil prices. *Energy Journal*, 30(2), 179-206.
Kilian, L. (2009). Not all oil price shocks are alike: Disentangling demand and supply shocks in the crude oil market. *American Economic Review*, 99(3), 1053-1069.
Lopez de Prado, M. (2018). *Advances in Financial Machine Learning*. John Wiley & Sons.
Ross, S. A. (1976). The arbitrage theory of capital asset pricing. *Journal of Economic Theory*, 13(3), 341-360.
Sharpe, W. F. (1994). The Sharpe ratio. *Journal of Portfolio Management*, 21(1), 49-58.
Tukey, J. W. (1977). *Exploratory Data Analysis*. Addison-Wesley.
Long Wick Detector [LuxAlgo]The Long Wick Detector tool allows traders to identify candle wicks longer than a user-defined volatility threshold. This makes it useful for spotting zones with high supply or demand.
The tool displays mitigated and unmitigated levels and changes the color of the candles based on wick size and level breakouts.
🔶 USAGE
By default, the tool displays long mitigated and unmitigated candle wicks, with a maximum duration for an unmitigated long wick of 1,000 bars. What does all this mean?
🔹 Wick Threshold
Traders can adjust the volatility threshold to identify long wicks, with a higher threshold detecting more significant wicks.
As we can see in the image above, the tool detects more wicks with a smaller threshold compared to a higher one.
🔹 Level %
Traders can choose the percentage of the wick at which the level is located. By default, the level is displayed at the extremes of the wick. This parameter accepts values between 0 and 100.
100: extreme of the wick
50: middle of the wick
0: start of the wick
🔹 Max Duration
This parameter allows traders to specify the number of bars for the levels. The tool will only display mitigated or unmitigated levels up to the specified number of bars.
As shown in the above image, a longer duration allows more room for mitigation, displaying more levels.
🔹 Colored Candles
The tool allows for color customization using two parameters from the settings panel. The chart shows the different outputs.
The setting "Wick-Based Transparency" makes candles with smaller wicks less visible and candles with longer wicks more visible.
On the other hand, "Breakout-Based Color" changes the base color of the candles based on the mitigation of long wicks. When the price breaks above a detected top wick, the bullish color is used. When the price breaks below a detected bottom wick, the bearish color is used.
🔶 SETTINGS
Wick Threshold: The volatility threshold for wick detection. Use a smaller value to detect smaller wicks.
Level %: Placement of the plotted level relative to the wick.
Max Duration: The maximum duration in bars of mitigated wicks.
Mitigated Wicks: Enable or disable mitigated wicks.
🔹 Style
Wick Based Transparency: Make candles with smaller wicks more transparent and candles with longer wicks more solid.
Breakout Based Color: Change the base color based on wick mitigation.
Bullish & Bearish Colors
Institutional Support/Resistance Locator🏛️ Institutional Support/Resistance Locator
Overview
The Institutional Support/Resistance Locator identifies high-probability demand and supply zones based on strong price rejection, large candle bodies, and elevated volume . These zones are commonly targeted or defended by institutional participants, helping traders anticipate potential reversal or continuation areas.
⸻
How It Works
The indicator uses a confluence of conditions to detect zones:
• Large Body Candles: Body size must exceed the moving average body size multiplied by a user-defined factor.
• High Volume: Volume must exceed the moving average volume by a configurable multiplier.
• Wick Rejection: Candles must show strong upper or lower wicks indicating aggressive rejection.
• If all criteria are met:
• Bullish candles form a Demand Zone.
• Bearish candles form a Supply Zone.
Each zone is plotted for a customizable number of future bars, representing areas where institutions may re-engage with the market.
⸻
Key Features
• ✅ Highlights institutional demand and supply areas dynamically
• ✅ Customizable sensitivity: body, volume, wick, padding, and zone extension
• ✅ Zones plotted as translucent regions with auto-expiry
• ✅ Works across all timeframes and markets
⸻
How to Use
• Trend Traders: Use demand zones for potential bounce entries in uptrends, and supply zones for pullback short entries in downtrends.
• Range Traders: Use zones as potential reversal points inside sideways market structures.
• Scalpers & Intraday Traders: Combine with volume or price action near zones for refined entries.
Always validate zone reactions with supporting indicators or price behavior.
⸻
Why This Combination?
The combination of wick rejection, volume confirmation, and large candle structure is designed to reflect footprints of smart money. Rather than relying on fixed pivots or subjective zones, this logic adapts to the current market context with statistically grounded conditions.
⸻
Why It’s Worth Using
This tool offers traders a structured way to interpret institutional activity on charts without relying on guesswork. By plotting potential high-impact areas, it helps improve reaction time.
⸻
Note :
• This script is open-source and non-commercial.
• No performance guarantees or unrealistic claims are made.
• It is intended for educational and analytical purposes only.
Stablecoin Supply Ratio [Alpha Extract]Stablecoin Supply Ratio Indicator
The Stablecoin Supply Ratio (SSR) indicator compares Bitcoin's market capitalization to the aggregate supply of major stablecoins, offering insights into relative purchasing power and liquidity. This tool helps traders:
✔ Assess Bitcoin's buying power relative to the available stablecoin liquidity.
✔ Detect periods of capital inflow or outflow from stablecoins.
✔ Identify market sentiment shifts based on stablecoin reserves.
🔶 CALCULATION
The indicator aggregates the supply of key stablecoins and compares it to Bitcoin's market cap:
Stablecoin Aggregation
• Inputs:
USDT, USDC, DAI, USDD (daily closing values).
BUSD Market Cap (Glassnode data).
• Total Stablecoin Supply:
Sum of the listed stablecoins' market caps.
Stablecoin Supply Ratio (SSR)
• Formula:
SSR = Bitcoin Market Cap / Total Stablecoin Supply
• Normalized SSR:
Normalized by dividing SSR by its 200-day SMA.
Bollinger Bands
• Bands are applied to the normalized SSR using a configurable moving average type and 2 standard deviations.
Example Calculation:
ssr = btcmc / stablecoin_liq
ratio = ssr / ta.sma(ssr, 200)
basis = ta.sma(ratio, 200)
dev = 2 * ta.stdev(ratio, 200)
upper = basis + dev
lower = basis - dev
🔶 DETAILS
Visual Features:
• Normalized SSR:
Plotted as a light green line.
• Upper Band:
Red line indicating SSR overbought zone.
• Lower Band:
Green line signaling SSR oversold zone.
Interpretation:
• High SSR: Indicates stablecoin reserves are low relative to Bitcoin's market cap, reducing stablecoin buying power.
• Low SSR: Suggests high stablecoin liquidity relative to Bitcoin's market cap, increasing potential buying pressure.
• Band Crosses: Movements beyond the upper or lower bands may signal sentiment extremes.
🔶 EXAMPLES
Market insights include:
• Capital Outflows: SSR rising into the upper band may reflect decreasing stablecoin reserves, potentially signaling a liquidity drain.
• Capital Inflows: SSR dropping near the lower band could indicate growing stablecoin reserves, potentially fueling Bitcoin demand.
🔶 SETTINGS
Customization Options:
• MA Type: Choose between SMA, EMA, WMA, SMMA, and VWMA for band calculation.
• Period: Adjust the 200-day smoothing period.
• Deviation Multiplier: Modify the standard deviation multiplier (default: 2).
The Stablecoin Supply Ratio indicator is a valuable tool for traders monitoring liquidity dynamics and stablecoin trends to anticipate Bitcoin market moves and capital flows.
Volume Range Profile with Fair Value (Zeiierman)█ Overview
The Volume Range Profile with Fair Value (Zeiierman) is a precision-built volume-mapping tool designed to help traders visualize where institutional-level activity is occurring within the price range — and how that volume behavior shifts over time.
Unlike traditional volume profiles that rely on fixed session boundaries or static anchors, this tool dynamically calculates and displays volume zones across both the upper and lower ends of a price range, revealing point-of-control (POC) levels, directional volume flow, and a fair value drift line that updates live with each candle.
You’re not just looking at volume anymore. You’re dissecting who’s in control — and at what price.
⚪ In simple terms:
Upper Zone = The upper portion of the price range, showing concentrated volume activity — typically where selling or distribution may occur
Lower Zone = The lower portion of the price range, highlighting areas of high volume — often associated with buying or accumulation
POC Bin = The bin (price level) with the highest traded volume in the zone — considered the most accepted price by the market
Fair Value Trend = A dynamic trend line tracking the average POC price over time — visualizing the evolving fair value
Zone Labels = Display real-time breakdown of buy/sell volume within each zone and inside the POC — revealing who’s in control
█ How It Works
⚪ Volume Zones
Upper Zone: Anchored at the highest high in the lookback period
Lower Zone: Anchored at the lowest low in the lookback period
Width is user-defined via % of range
Each zone is divided into a series of volume bins
⚪ Volume Bins (Histograms)
Each zone is split into N bins that show how much volume occurred at each level:
Taller = More volume
The POC bin (Point of Control) is highlighted
Labels show % of volume in the POC relative to the whole zone
⚪ Buy vs Sell Breakdown
Each volume bin is split by:
Buy Volume = Close ≥ Open
Sell Volume = Close < Open
The script accumulates these and displays total Buy/Sell volume per zone.
⚪ Fair Value Drift Line
A POC trend is plotted over time:
Represents where volume was most active across each range
Color changes dynamically — green for rising, red for falling
Serves as a real-time fair value anchor across changing market structure
█ How to Use
⚪ Identify Key Control Zones
Use Upper/Lower Zone structures to understand where supply and demand is building.
Zones automatically adapt to recent highs/lows and re-center volume accordingly.
⚪ Follow Institutional Activity
Watch for POC clustering near price tops or bottoms.
Large volumes near extremes may indicate accumulation or distribution.
⚪ Spot Fair Value Drift
The fair value trend line (average POC price) gives insight into market equilibrium.
One strategy can be to trade a re-test of the fair value trend, trades are taken in the direction of the current trend.
█ Understanding Buy & Sell Volume Labels (Zone Totals)
These labels show the total buy and sell volume accumulated within each zone over the selected lookback period:
Buy Vol (green label) → Total volume where candles closed bullish
Sell Vol (red label) → Total volume where candles closed bearish
Together, they tell you which side dominated:
Higher Buy Vol → Bullish accumulation zone
Higher Sell Vol → Bearish distribution zone
This gives a quick visual insight into who controlled the zone, helping you spot areas of demand or supply imbalance.
█ Understanding POC Volume Labels
The POC (Point of Control) represents the price level where the most volume occurred within the zone. These labels break down that volume into:
Buy % – How much of the volume was buying (price closed up)
Sell % – How much was selling (price closed down)
Total % – How much of the entire zone’s volume happened at the POC
Use it to spot strong demand or supply zones:
High Buy % + High Total % → Strong buying interest = likely support
High Sell % + High Total % → Strong selling pressure = likely resistance
It gives a deeper look into who was in control at the most important price level.
█ Why It’s Useful
Track where fair value is truly forming
Detect aggressive volume accumulation or dumping
Visually split buyer/seller control at the most relevant price levels
Adapt volume structures to current trend direction
█ Settings Explained
Lookback Period: Number of bars to scan for highs/lows. Higher = smoother zones, Lower = reactive.
Zone Width (% of Range): Controls how much of the range is used to define each zone. Higher = broader zones.
Bins per Zone: Number of volume slices per zone. Higher = more detail, but heavier on resources.
-----------------
Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Volume Order Blocks [BigBeluga]Volume Order Blocks is a powerful indicator that identifies significant order blocks based on price structure, helping traders spot key supply and demand zones. The tool leverages EMA crossovers to determine the formation of bullish and bearish order blocks while visualizing their associated volume and relative strength.
🔵 Key Features:
Order Block Detection via EMA Crossovers:
Plots bullish order blocks at recent lows when the short EMA crosses above the long EMA.
Plots bearish order blocks at recent highs when the short EMA crosses below the long EMA.
Uses customizable sensitivity through the “Sensitivity Detection” setting to fine-tune block formation.
Volume Collection and Visualization:
Calculates the total volume between the EMA crossover bar and the corresponding high (bearish OB) or low (bullish OB).
Displays the absolute volume amount next to each order block for clear volume insights.
Percentage Volume Distribution:
Shows the percentage distribution of volume among bullish or bearish order blocks.
100% represents the cumulative volume of all OBs in the same category (bullish or bearish).
Order Block Removal Conditions:
Bullish order blocks are removed when the price closes below the bottom of the block.
Bearish order blocks are removed when the price closes above the top of the block.
Helps maintain chart clarity by only displaying relevant and active levels.
Midline Feature:
Dashed midline inside each order block indicates the midpoint between the upper and lower boundaries.
Traders can toggle the midline on or off through the settings.
Shadow Trend:
Shadow Trend dynamically visualizes trend strength and direction by adapting its color intensity based on price movement.
🔵 Usage:
Supply & Demand Zones: Use bullish and bearish order blocks to identify key market reversal or continuation points.
Volume Strength Analysis: Compare volume percentages to gauge which order blocks hold stronger market significance.
Breakout Confirmation: Monitor block removal conditions for potential breakout signals beyond support or resistance zones.
Trend Reversals: Combine EMA crossovers with order block formation for early trend reversal detection.
Risk Management: Use OB boundaries as potential stop-loss or entry points.
Volume Order Blocks is an essential tool for traders seeking to incorporate volume-based supply and demand analysis into their trading strategy. By combining price action, volume data, and EMA crossovers, it offers a comprehensive view of market structure and potential turning points.
Wyckoff Event Detection [Alpha Extract]Wyckoff Event Detection
A powerful and intelligent indicator designed to detect key Wyckoff events in real time, helping traders analyze market structure and anticipate potential trend shifts. Using volume and price action, this script automatically identifies distribution and accumulation phases, providing traders with valuable insights into market behavior.
🔶 Phase-Based Detection
Utilizes a phase detection algorithm that evaluates price and volume conditions to identify accumulation (bullish) and distribution (bearish) events. This method ensures the script effectively captures major market turning points and avoids noise.
🔶 Multi-Factor Event Recognition
Incorporates multiple event conditions, including upthrusts, selling climaxes, and springs, to detect high-probability entry and exit points. Each event is filtered through customizable sensitivity settings, ensuring precise detection aligned with different trading styles.
🔶 Customizable Parameters
Fine-tune event detection with adjustable thresholds for volume, price movement, trend strength, and event spacing. These inputs allow traders to personalize the script to match their strategy and risk tolerance.
// === USER INPUTS ===
i_volLen = input.int(20, "Volume MA Length", minval=1)
i_priceLookback = input.int(20, "Price Pattern Lookback", minval=5)
i_lineLength = input.int(15, "Line Length", minval=5)
i_labelSpacing = input.int(5, "Minimum Label Spacing (bars)", minval=1, maxval=20)
❓How It Works
🔶 Event Identification
The script scans for key Wyckoff events by analyzing volume spikes, price deviations, and trend shifts within a user-defined lookback period. It categorizes events into bullish (accumulation) or bearish (distribution) structures and plots them directly on the chart.
// === EVENT DETECTION ===
volMA = ta.sma(volume, i_volLen)
highestHigh = ta.highest(high, i_priceLookback)
lowestLow = ta.lowest(low, i_priceLookback)
🔶 Automatic Filtering & Cleanup
Unconfirmed or weak signals are filtered out using customizable strength multipliers and volume thresholds. Events that do not meet the minimum conditions are discarded to keep the chart clean and informative.
🔶 Phase Strength Analysis
The script continuously tracks bullish and bearish event counts to determine whether the market is currently in an accumulation, distribution, or neutral phase. This allows traders to align their strategies accordingly.
🔶 Visual Alerts & Labels
Detects and labels key Wyckoff events directly on the chart, providing immediate insights into market conditions:
- PSY (Preliminary Supply) and UT (Upthrust) for distribution phases.
- PS (Preliminary Support) and SC (Selling Climax) for accumulation phases.
- Labels adjust dynamically to avoid chart clutter and improve readability.
🔶 Entry & Exit Optimization
By highlighting supply and demand imbalances, the script assists traders in identifying optimal entry and exit points. Wyckoff concepts such as springs and upthrusts provide clear trade signals based on market structure.
🔶 Trend Confirmation & Risk Management
Observing how price reacts to detected events helps confirm trend direction and potential reversals. Traders can place stop-loss and take-profit levels based on Wyckoff phase analysis, ensuring strategic trade execution.
🔶 Table-Based Market Analysis (Table)
A built-in table summarizes:
- Market Phase: Accumulation, Distribution, or Neutral.
- Strength of Phase: Weak, Moderate, or Strong.
- Price Positioning: Whether price is near support, resistance, or in a trading range.
- Supply/Demand State: Identifies whether the market is supply or demand dominant.
🔶 Why Choose Wyckoff Market Phases - Alpha Extract?
This indicator offers a systematic approach to understanding market mechanics through the lens of Wyckoff's time-tested principles. By providing clear and actionable insights into market phases, it empowers traders to make informed decisions, enhancing both confidence and performance in various trading environments.
[TehThomas] - ICT Volume ImbalanceThis script is a Volume Imbalance (VI) detector and visualizer for use on the TradingView platform. The goal of the script is to automatically identify areas where there are significant imbalances in the volume of trades between consecutive candlesticks and visually highlight these areas. These imbalances can provide traders with valuable insights about the market’s current condition, often signaling potential reversal or continuation points based on price and volume action.
ICT (Inner Circle Trader) Concept of Volume Imbalances
Volume imbalances are a critical concept in the ICT trading methodology. They refer to situations where there is an unusual or significant difference in volume between two consecutive candlesticks, which might indicate institutional or large player activity. According to ICT principles, these imbalances can show us areas of market inefficiency or potential price manipulation. By identifying these imbalances, traders can gain an edge in understanding where the market is likely to move next.
Bullish and Bearish Volume Imbalances:
Bullish Volume Imbalance: This occurs when there is a strong increase in buying pressure, typically indicated by a higher volume on a candle that closes significantly above the previous one, often leaving a gap or larger price movement. The market could be preparing to push higher, and the volume shows a clear shift in buying demand.
Bearish Volume Imbalance:
Conversely, a bearish imbalance occurs when there is a strong increase in selling pressure, typically signaled by a candle that closes significantly lower than the previous one, again with higher volume. This could indicate that large players are offloading positions, and the price is likely to drop further.
Key Features and Functions of the Script
The script automates the process of detecting these volume imbalances and visually marking them on a price chart. Let’s explore its functionality in detail.
1. Inputs Section
The script allows for significant customization through its input options, which help traders adjust the detection and visualization of volume imbalances based on their individual preferences and trading style. Below are the details:
lookback (250 bars): This input specifies the number of bars (or candles) the script should look back when analyzing the volume imbalance. By setting this to 250, the user is looking at the last 250 bars on the chart to detect any significant volume imbalances. This period is adjustable between 50 to 500 bars.
volumeThreshold (1.0 multiplier): This input helps set the sensitivity for identifying volume imbalances. The script compares the volume of the current candle with the previous one, and if the current volume exceeds the previous volume by this threshold multiplier (in this case, 1.0 means at least equal to the previous volume), then it triggers an imbalance. Users can adjust the multiplier to suit different market conditions.
showBoxes (true/false): This toggle determines whether the boxes representing volume imbalances are drawn on the chart. When enabled, the script visually highlights the imbalances with colored boxes.
fillBaseColor (orange with 80% opacity): This is the color setting for the background of the imbalance boxes. A softer color (like orange with opacity) ensures the imbalance is highlighted without obscuring the price action.
borderColor (gray): The color of the border around the imbalance boxes. This adds a visual distinction to make the imbalance areas more visible.
borderWidth (1 pixel): This controls the width of the box's border to adjust how prominent it appears.
rightOffset (30 bars): This input controls how far the imbalance box extends to the right on the chart. It helps users anticipate the potential continuation of the imbalance beyond the current candle.
allowWickOverlap (true/false): This setting allows imbalances to be identified even if the wicks of the two consecutive candlesticks overlap. If set to false, only imbalances where the bodies of the candlesticks don’t overlap are considered.
showBrokenBoxes (true/false): If enabled, once a volume imbalance no longer holds true (i.e., the price breaks through the box), the box is marked as "broken." If disabled, the box is deleted when the imbalance condition no longer applies.
brokenBoxColor (red): This controls the color of the box when it is broken, which can be used as a visual cue that the imbalance was invalidated or no longer valid for analysis.
2. Volume Imbalance Function
This is the core function of the script, where the logic to detect bullish and bearish volume imbalances is implemented.
Bullish Imbalance Condition:
The first condition checks if the low of the current candle is greater than the high of the previous candle. This suggests that the market is moving upward with buying pressure.
The second condition checks whether the volume of the current candle is higher than the previous candle by the volumeThreshold multiplier. If both conditions are satisfied, a bullish imbalance is detected.
Bearish Imbalance Condition:
The first condition checks if the high of the current candle is lower than the low of the previous candle. This suggests downward price action with selling pressure.
The second condition checks whether the current volume exceeds the previous volume by the threshold
Allow Wick Overlap: If allowWickOverlap is set to true, the script will still detect imbalances if the wicks of the two candles overlap (common in volatile markets). If false, imbalances are only considered if the wicks do not overlap.
3. Box Creation and Management
When a volume imbalance is detected, the script creates a box on the chart:
The bullish imbalance box is drawn using the minimum of the open and close of the current bar as the top boundary and the maximum of the open and close of the previous bar as the bottom boundary.
Conversely, the bearish imbalance box is drawn in reverse, using the maximum of the current bar’s open and close as the top boundary and the minimum of the previous bar’s open and close as the bottom boundary.
Once the box is created, it is displayed on the chart with the specified background color, border color, and width.
4. Processing Existing Boxes
After detecting a new imbalance and drawing a box, the script checks whether the box should still remain on the chart:
If the price moves beyond the boundaries of the imbalance box, the box is marked as broken (if showBrokenBoxes is enabled), and its color is changed to red, signifying that the imbalance is no longer valid.
If the box remains intact (i.e., the price has not broken the defined boundaries), the script keeps the box extended to the right as the market continues to evolve.
5. Removing Outdated Boxes
Lastly, the script removes boxes that are older than the specified lookback period. For example, if a box was created 250 bars ago, it will be deleted after that period. This ensures the chart stays clean and only focuses on relevant imbalances.
Why This Script is Useful for Traders
This script is extremely valuable for traders, especially those following the ICT methodology, because it automates the process of detecting market inefficiencies or imbalances that might signal future price action. Here’s why it’s particularly useful:
Identifying Key Areas of Interest: Volume imbalances often point to areas where institutional or large-scale traders have entered the market. These areas could provide clues about the next significant move in the market.
Visualizing Market Structure: By automatically drawing boxes around volume imbalances, the script helps traders visually identify potential areas of support, resistance, or turning points, enabling them to make informed trading decisions.
Time Efficiency: Instead of manually analyzing each candlestick and volume spike, this script does the heavy lifting, saving traders valuable time and allowing them to focus on other aspects of their strategy.
Enhanced Trade Entries and Exits: By understanding where volume imbalances are occurring, traders can time their entries (buying during bullish imbalances and selling during bearish ones) and exits (as imbalances break) more effectively, thus improving their chances of success.
Conclusion
In summary, this script is a powerful tool for traders looking to implement volume imbalance strategies based on the ICT methodology. It automates the identification and visualization of significant imbalances in price and volume, offering traders a clear visual representation of potential market turning points. By customizing the settings, traders can tailor the script to their preferred timeframes and sensitivity, making it a flexible and effective tool for any trading strategy.
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MMXM ICT [TradingFinder] Market Maker Model PO3 CHoCH/CSID + FVG🔵 Introduction
The MMXM Smart Money Reversal leverages key metrics such as SMT Divergence, Liquidity Sweep, HTF PD Array, Market Structure Shift (MSS) or (ChoCh), CISD, and Fair Value Gap (FVG) to identify critical turning points in the market. Designed for traders aiming to analyze the behavior of major market participants, this setup pinpoints strategic areas for making informed trading decisions.
The document introduces the MMXM model, a trading strategy that identifies market maker activity to predict price movements. The model operates across five distinct stages: original consolidation, price run, smart money reversal, accumulation/distribution, and completion. This systematic approach allows traders to differentiate between buyside and sellside curves, offering a structured framework for interpreting price action.
Market makers play a pivotal role in facilitating these movements by bridging liquidity gaps. They continuously quote bid (buy) and ask (sell) prices for assets, ensuring smooth trading conditions.
By maintaining liquidity, market makers prevent scenarios where buyers are left without sellers and vice versa, making their activity a cornerstone of the MMXM strategy.
SMT Divergence serves as the first signal of a potential trend reversal, arising from discrepancies between the movements of related assets or indices. This divergence is detected when two or more highly correlated assets or indices move in opposite directions, signaling a likely shift in market trends.
Liquidity Sweep occurs when the market targets liquidity in specific zones through false price movements. This process allows major market participants to execute their orders efficiently by collecting the necessary liquidity to enter or exit positions.
The HTF PD Array refers to premium and discount zones on higher timeframes. These zones highlight price levels where the market is in a premium (ideal for selling) or discount (ideal for buying). These areas are identified based on higher timeframe market behavior and guide traders toward lucrative opportunities.
Market Structure Shift (MSS), also referred to as ChoCh, indicates a change in market structure, often marked by breaking key support or resistance levels. This shift confirms the directional movement of the market, signaling the start of a new trend.
CISD (Change in State of Delivery) reflects a transition in price delivery mechanisms. Typically occurring after MSS, CISD confirms the continuation of price movement in the new direction.
Fair Value Gap (FVG) represents zones where price imbalance exists between buyers and sellers. These gaps often act as price targets for filling, offering traders opportunities for entry or exit.
By combining all these metrics, the Smart Money Reversal provides a comprehensive tool for analyzing market behavior and identifying key trading opportunities. It enables traders to anticipate the actions of major players and align their strategies accordingly.
MMBM :
MMSM :
🔵 How to Use
The Smart Money Reversal operates in two primary states: MMBM (Market Maker Buy Model) and MMSM (Market Maker Sell Model). Each state highlights critical structural changes in market trends, focusing on liquidity behavior and price reactions at key levels to offer precise and effective trading opportunities.
The MMXM model expands on this by identifying five distinct stages of market behavior: original consolidation, price run, smart money reversal, accumulation/distribution, and completion. These stages provide traders with a detailed roadmap for interpreting price action and anticipating market maker activity.
🟣 Market Maker Buy Model
In the MMBM state, the market transitions from a bearish trend to a bullish trend. Initially, SMT Divergence between related assets or indices reveals weaknesses in the bearish trend. Subsequently, a Liquidity Sweep collects liquidity from lower levels through false breakouts.
After this, the price reacts to discount zones identified in the HTF PD Array, where major market participants often execute buy orders. The market confirms the bullish trend with a Market Structure Shift (MSS) and a change in price delivery state (CISD). During this phase, an FVG emerges as a key trading opportunity. Traders can open long positions upon a pullback to this FVG zone, capitalizing on the bullish continuation.
🟣 Market Maker Sell Model
In the MMSM state, the market shifts from a bullish trend to a bearish trend. Here, SMT Divergence highlights weaknesses in the bullish trend. A Liquidity Sweep then gathers liquidity from higher levels.
The price reacts to premium zones identified in the HTF PD Array, where major sellers enter the market and reverse the price direction. A Market Structure Shift (MSS) and a change in delivery state (CISD) confirm the bearish trend. The FVG then acts as a target for the price. Traders can initiate short positions upon a pullback to this FVG zone, profiting from the bearish continuation.
Market makers actively bridge liquidity gaps throughout these stages, quoting continuous bid and ask prices for assets. This ensures that trades are executed seamlessly, even during periods of low market participation, and supports the structured progression of the MMXM model.
The price’s reaction to FVG zones in both states provides traders with opportunities to reduce risk and enhance precision. These pullbacks to FVG zones not only represent optimal entry points but also create avenues for maximizing returns with minimal risk.
🔵 Settings
Higher TimeFrame PD Array : Selects the timeframe for identifying premium/discount arrays on higher timeframes.
PD Array Period : Specifies the number of candles for identifying key swing points.
ATR Coefficient Threshold : Defines the threshold for acceptable volatility based on ATR.
Max Swing Back Method : Choose between analyzing all swings ("All") or a fixed number ("Custom").
Max Swing Back : Sets the maximum number of candles to consider for swing analysis (if "Custom" is selected).
Second Symbol for SMT : Specifies the second asset or index for detecting SMT divergence.
SMT Fractal Periods : Sets the number of candles required to identify SMT fractals.
FVG Validity Period : Defines the validity duration for FVG zones.
MSS Validity Period : Sets the validity duration for MSS zones.
FVG Filter : Activates filtering for FVG zones based on width.
FVG Filter Type : Selects the filtering level from "Very Aggressive" to "Very Defensive."
Mitigation Level FVG : Determines the level within the FVG zone (proximal, 50%, or distal) that price reacts to.
Demand FVG : Enables the display of demand FVG zones.
Supply FVG : Enables the display of supply FVG zones.
Zone Colors : Allows customization of colors for demand and supply FVG zones.
Bottom Line & Label : Enables or disables the SMT divergence line and label from the bottom.
Top Line & Label : Enables or disables the SMT divergence line and label from the top.
Show All HTF Levels : Displays all premium/discount levels on higher timeframes.
High/Low Levels : Activates the display of high/low levels.
Color Options : Customizes the colors for high/low lines and labels.
Show All MSS Levels : Enables display of all MSS zones.
High/Low MSS Levels : Activates the display of high/low MSS levels.
Color Options : Customizes the colors for MSS lines and labels.
🔵 Conclusion
The Smart Money Reversal model represents one of the most advanced tools for technical analysis, enabling traders to identify critical market turning points. By leveraging metrics such as SMT Divergence, Liquidity Sweep, HTF PD Array, MSS, CISD, and FVG, traders can predict future price movements with precision.
The price’s interaction with key zones such as PD Array and FVG, combined with pullbacks to imbalance areas, offers exceptional opportunities with favorable risk-to-reward ratios. This approach empowers traders to analyze the behavior of major market participants and adopt professional strategies for entry and exit.
By employing this analytical framework, traders can reduce errors, make more informed decisions, and capitalize on profitable opportunities. The Smart Money Reversal focuses on liquidity behavior and structural changes, making it an indispensable tool for financial market success.
Bitcoin Premium [SAKANE]Overview
"Bitcoin Premium " is an indicator designed to analyze the price differences (premiums) of Bitcoin between major exchanges. By using this tool, you can visualize these differences and trends across exchanges, helping you make more informed trading decisions.
Features
1. Premium Calculation and Display
- Calculates and visualizes the price differences between major exchanges like Coinbase, Bitfinex, Upbit, and Binance.
- Premiums are displayed in a histogram format for intuitive analysis.
2. Forex Rate Adjustment
- Prices quoted in KRW (e.g., from Upbit) are converted to USD using real-time KRW/USD forex rates.
3. Moving Average Option
- Displays moving averages (SMA or EMA) of premiums for a clearer view of long-term trends.
4. Customizable Settings
- Toggle the premium display for each exchange on or off.
- Includes label displays to support visual analysis.
What Can It Do for You?
1. Identify Arbitrage Opportunities
By observing price differences (premiums) between exchanges, you can identify arbitrage opportunities.
Example: If Bitcoin is cheaper on Binance and more expensive on Coinbase, you could buy on Binance and sell on Coinbase to capture the price difference.
2. Understand Regional Supply and Demand Trends
Each exchange's premium reflects the supply and demand dynamics of its respective region.
Example: A high premium on Upbit may indicate excess demand or regulatory impacts in the South Korean market.
3. Analyze Liquidity
Price differences often highlight liquidity disparities between exchanges. Markets with lower trading volumes tend to have larger premiums due to price distortions.
4. Evaluate Macroeconomic Impacts
Premium movements may reflect changes in macroeconomic factors, such as exchange rates, regulations, or financial conditions specific to each region.
5. Analyze Trends and Market Sentiment
By tracking premium trends, you can gauge market sentiment and understand regional or exchange-specific behaviors to inform your investment decisions.
6. Support Strategic Trading
This tool is useful for short-term arbitrage strategies as well as long-term evaluations of market health.
Exchange Characteristics and Premium Implications
The meaning of premiums varies by exchange.
- Coinbase (US Market)
Primarily used by investors buying directly with fiat currency (USD). A higher premium often signals bullish sentiment among institutional and retail investors.
- Bitfinex (Global Market)
A trader-focused exchange with active large-scale and leveraged trading. Premiums may reflect liquidity and risk appetite.
- Upbit (South Korean Market)
Priced in KRW, making it subject to forex rates and local market dynamics. High premiums may indicate strong demand or regulatory influences in South Korea.
- Binance (Global Market)
The largest exchange by trading volume. Premiums here are often a reflection of the overall market balance.
Notes
- This indicator is for reference only and does not guarantee trading decisions.
- Please consider the characteristics and conditions of each exchange when using this tool.
Big Money by ChartedhighsBig Money by Chartedhighs
Script Overview:
The "Big Money" indicator is designed to help traders easily identify significant price movements on their charts. This script visually highlights candles where the price change from open to close exceeds a user-defined threshold. It draws attention to these key moments, providing a clear indication of potential big-money moves in the market.
Key Features:
Customizable Threshold:
Allows users to set a specific price change threshold via the input menu (Highlight Threshold).
Only candles with a price change greater than or equal to this value are highlighted.
Candle Highlighting:
Uses color-coded bars to emphasize candles meeting the threshold condition.
Candles are highlighted in yellow for immediate visual clarity.
Dynamic Box Annotation:
Draws a semi-transparent yellow box around highlighted candles.
Extends the box dynamically to subsequent bars, providing an area of interest for continued analysis.
Labeling for Key Moments:
Automatically adds a label ("BigMoney") above highlighted bars to further indicate significant price action.
How It Works:
The script calculates the price change for each bar (close - open) and compares it to the user-defined threshold.
If the price change meets or exceeds the threshold:
The bar color changes to yellow.
A box is drawn around the candle to highlight the price movement visually.
A label is added above the candle to emphasize its significance.
The box extends dynamically until the next highlighted candle, allowing users to track zones of activity.
Customization Options:
Highlight Threshold: Modify the threshold value to suit your trading style or instrument volatility.
Use Case:
This indicator is ideal for traders looking to identify significant price movements quickly. It helps to locate areas where "big money" might be flowing into the market, offering potential entry or exit opportunities.
How to Use:
Add the "Big Money by Chartedhighs" script to your TradingView chart.
Set the Highlight Threshold to a value suitable for your market or timeframe.
Observe highlighted candles and boxes for potential trading signals or areas of interest.
This script is highly visual, intuitive, and customizable, making it a great addition to any trader's toolkit!
faiz MACDMACD: Moving Average Convergence Divergence
The Moving Average Convergence Divergence (MACD) is a popular momentum indicator used in technical analysis to gauge the strength, direction, and potential reversal points of a trend in a financial asset's price movement. Developed by Gerald Appel in the late 1970s, MACD is particularly favored by traders for its ability to capture both trend-following and momentum aspects of price behavior.
Components of the MACD
The MACD is derived from two exponential moving averages (EMAs) of a security's price:
MACD Line: This is the difference between the 12-day and 26-day EMAs. The shorter 12-day EMA reacts more quickly to price changes, while the 26-day EMA smooths out price fluctuations, offering a longer-term perspective.
Formula: MACD Line = 12-day EMA - 26-day EMA
Signal Line: This is the 1-day EMA of the MACD Line itself. The signal line is used to generate buy and sell signals when it crosses the MACD line.
Formula: Signal Line = 1-day EMA of the MACD Line
MACD Histogram: The histogram represents the difference between the MACD Line and the Signal Line. It is displayed as bars that oscillate above and below a zero line, helping to visualize the convergence or divergence between the two lines.
Formula: Histogram = MACD Line - Signal Line
Interpretation of MACD
The MACD indicator is used to identify potential buy and sell signals based on the following observations:
MACD Line and Signal Line Crossovers:
Bullish Crossover: A buy signal occurs when the MACD Line crosses above the Signal Line. This suggests that the momentum is shifting in favor of the bulls, indicating a potential upward price movement.
Bearish Crossover: A sell signal occurs when the MACD Line crosses below the Signal Line. This suggests a bearish trend may be emerging, signaling a potential downward movement.
Divergence:
Bullish Divergence: Occurs when the price of the asset is making new lows, but the MACD is forming higher lows. This suggests that the downward momentum is weakening and a potential reversal to the upside may be imminent.
Bearish Divergence: Occurs when the price is making new highs, but the MACD is forming lower highs. This suggests that the upward momentum is weakening and a reversal to the downside may occur.
Only use it in timeframe m1, and solely use for XAUUSD pair.
Advisable to use it as a confirmation with other indicator such as
BBMA, SMC, SUPPORT RESISTANCE, SUPPLY AND DEMAND.
how to use :
MA 5 Crossing above MA9, will generate BUY signals
MA 5 Crossing below MA9, will generate SELL signals
Trade at your own SKILLS.
I dont mind people using this script for free.
All I want is just prayer for me and my family success.
Thank You and Have a nice and pleasant day :-)
ICT Setup 03 [TradingFinder] Judas Swing NY 9:30am + CHoCH/FVG🔵 Introduction
Judas Swing is an advanced trading setup designed to identify false price movements early in the trading day. This advanced trading strategy operates on the principle that major market players, or "smart money," drive price in a certain direction during the early hours to mislead smaller traders.
This deceptive movement attracts liquidity at specific levels, allowing larger players to execute primary trades in the opposite direction, ultimately causing the price to return to its true path.
The Judas Swing setup functions within two primary time frames, tailored separately for Forex and Stock markets. In the Forex market, the setup uses the 8:15 to 8:30 AM window to identify the high and low points, followed by the 8:30 to 8:45 AM frame to execute the Judas move and identify the CISD Level break, where Order Block and Fair Value Gap (FVG) zones are subsequently detected.
In the Stock market, these time frames shift to 9:15 to 9:30 AM for identifying highs and lows and 9:30 to 9:45 AM for executing the Judas move and CISD Level break.
Concepts such as Order Block and Fair Value Gap (FVG) are crucial in this setup. An Order Block represents a chart region with a high volume of buy or sell orders placed by major financial institutions, marking significant levels where price reacts.
Fair Value Gap (FVG) refers to areas where price has moved rapidly without balance between supply and demand, highlighting zones of potential price action and future liquidity.
Bullish Setup :
Bearish Setup :
🔵 How to Use
The Judas Swing setup enables traders to pinpoint entry and exit points by utilizing Order Block and FVG concepts, helping them align with liquidity-driven moves orchestrated by smart money. This setup applies two distinct time frames for Forex and Stocks to capture early deceptive movements, offering traders optimized entry or exit moments.
🟣 Bullish Setup
In the Bullish Judas Swing setup, the first step is to identify High and Low points within the initial time frame. These levels serve as key points where price may react, forming the basis for analyzing the setup and assisting traders in anticipating future market shifts.
In the second time frame, a critical stage of the bullish setup begins. During this phase, the price may create a false break or Fake Break below the low level, a deceptive move by major players to absorb liquidity. This false move often causes smaller traders to enter positions incorrectly. After this fake-out, the price reverses upward, breaking the CISD Level, a critical point in the market structure, signaling a potential bullish trend.
Upon breaking the CISD Level and reversing upward, the indicator identifies both the Order Block and Fair Value Gap (FVG). The Order Block is an area where major players typically place large buy orders, signaling potential price support. Meanwhile, the FVG marks a region of supply-demand imbalance, signaling areas where price might react.
Ultimately, after these key zones are identified, a trader may open a buy position if the price reaches one of these critical areas—Order Block or FVG—and reacts positively. Trading at these levels enhances the chance of success due to liquidity absorption and support from smart money, marking an opportune time for entering a long position.
🟣 Bearish Setup
In the Bearish Judas Swing setup, analysis begins with marking the High and Low levels in the initial time frame. These levels serve as key zones where price could react, helping to signal possible trend reversals. Identifying these levels is essential for locating significant bearish zones and positioning traders to capitalize on downward movements.
In the second time frame, the primary bearish setup unfolds. During this stage, price may exhibit a Fake Break above the high, causing a brief move upward and misleading smaller traders into incorrect positions. After this false move, the price typically returns downward, breaking the CISD Level—a crucial bearish trend indicator.
With the CISD Level broken and a bearish trend confirmed, the indicator identifies the Order Block and Fair Value Gap (FVG). The Bearish Order Block is a region where smart money places significant sell orders, prompting a negative price reaction. The FVG denotes an area of supply-demand imbalance, signifying potential selling pressure.
When the price reaches one of these critical areas—the Bearish Order Block or FVG—and reacts downward, a trader may initiate a sell position. Entering trades at these levels, due to increased selling pressure and liquidity absorption, offers traders an advantage in profiting from price declines.
🔵 Settings
Market : The indicator allows users to choose between Forex and Stocks, automatically adjusting the time frames for the "Opening Range" and "Trading Permit" accordingly: Forex: 8:15–8:30 AM for identifying High and Low points, and 8:30–8:45 AM for capturing the Judas move and CISD Level break. Stocks: 9:15–9:30 AM for identifying High and Low points, and 9:30–9:45 AM for executing the Judas move and CISD Level break.
Refine Order Block : Enables finer adjustments to Order Block levels for more accurate price responses.
Mitigation Level OB : Allows users to set specific reaction points within an Order Block, including: Proximal: Closest level to the current price. 50% OB: Midpoint of the Order Block. Distal: Farthest level from the current price.
FVG Filter : The Judas Swing indicator includes a filter for Fair Value Gap (FVG), allowing different filtering based on FVG width: FVG Filter Type: Can be set to "Very Aggressive," "Aggressive," "Defensive," or "Very Defensive." Higher defensiveness narrows the FVG width, focusing on narrower gaps.
Mitigation Level FVG : Like the Order Block, you can set price reaction levels for FVG with options such as Proximal, 50% OB, and Distal.
CISD : The Bar Back Check option enables traders to specify the number of past candles checked for identifying the CISD Level, enhancing CISD Level accuracy on the chart.
🔵 Conclusion
The Judas Swing indicator helps traders spot reliable trading opportunities by detecting false price movements and key levels such as Order Block and FVG. With a focus on early market movements, this tool allows traders to align with major market participants, selecting entry and exit points with greater precision, thereby reducing trading risks.
Its extensive customization options enable adjustments for various market types and trading conditions, giving traders the flexibility to optimize their strategies. Based on ICT techniques and liquidity analysis, this indicator can be highly effective for those seeking precision in their entry points.
Overall, Judas Swing empowers traders to capitalize on significant market movements by leveraging price volatility. Offering precise and dependable signals, this tool presents an excellent opportunity for enhancing trading accuracy and improving performance
Implied Fair Value Gap (IFVG) ICT [TradingFinder] Hidden FVG OTE🔵 Introduction
The Implied Fair Value Gap (IFVG) is distinctive due to its unique three-candlestick formation, which differentiates it from conventional Fair Value Gaps.
Implied fair value represents an estimated worth of an asset—often a business or its goodwill—based on the price likely to be received in a structured transaction between market participants at a specific point in time.
In the ever-evolving world of technical analysis, pinpointing price reversal points and market anomalies can significantly enhance trading strategies and decision-making for traders and investors. Among the advanced concepts gaining traction in this field is the Implied Fair Value Gap (IFVG), introduced by the renowned analyst Inner Circle Trader (ICT).
This tool has proven to be an effective method for identifying hidden supply and demand zones in financial markets, offering a unique edge to traders looking for high-probability setups.
Unlike traditional gaps that are visible on price charts, IFVG is a hidden gap that doesn’t appear explicitly on the chart and thus requires specialized technical analysis tools for accurate identification.
This hidden gap can signal potential price reversals and offers traders insight into high-liquidity areas where price is likely to react. This article will guide you through using the ICT Implied Fair Value Gap Indicator effectively, covering its settings, usage strategies, and key features to help you make informed decisions in the market.
🟣 Bullish Implied FVG
🟣 Bearish Implied FVG
🔵 How to Use
The IFVG indicator is designed to assist traders in recognizing hidden support and resistance zones by identifying Bullish and Bearish IFVG patterns. With this tool, traders can make better-informed decisions about suitable entry and exit points for their trades based on these patterns.
🟣 Bullish Implied Fair Value Gap
This pattern occurs in an uptrend when a large bullish candlestick forms, with the wicks of the previous and following candles overlapping the body of the central candlestick.
This overlap creates a demand zone or a hidden support level, which can act as an ideal entry point for buy trades. Often, when the price returns to this area, it is likely to resume its upward trend, presenting a profitable buying opportunity.
🟣 Bearish Implied Fair Value Gap
This pattern is similar but forms in downtrends. Here, a large bearish candlestick appears on the chart, with the wicks of adjacent candles overlapping its body. This overlap defines a supply zone or a hidden resistance level and serves as a signal for potential sell trades.
When the price returns to this zone, it often continues its downward trend, providing an optimal point for entering sell trades.
The IFVG indicator also includes various filters that traders can use to refine their analysis based on market conditions. These filters, including Very Aggressive, Aggressive, Defensive, and Very Defensive, allow users to customize the IFVG zones' width, offering flexibility according to the trader’s risk tolerance and trading style.
🟣 Example Trading Scenarios
Suppose you’re in a strong uptrend and the IFVG indicator identifies a Bullish IFVG zone. In this scenario, you could consider entering a buy trade when the price retraces to this zone, expecting the uptrend to resume. Conversely, in a downtrend, a Bearish IFVG zone can signal a favorable entry point for short trades when the price revisits this area.
🔵 Settings
Implied Block Validity Period: This parameter specifies the validity period of each identified block, taking into account the number of bars that have passed since its formation. Proper adjustment of this period helps traders focus only on relevant zones, increasing the accuracy of the analysis.
Mitigation Level OB : This option defines the mitigation level for supply and demand blocks (Order Blocks), with settings including Proximal, 50% OB, and Distal.
Depending on the selected level, the indicator will focus on closer, mid-range, or farther points for block identification, allowing traders to adjust for the level of precision required.
Implied Filter : Activating this filter allows traders to apply conditions based on the width of the IFVG zones. With options like Very Aggressive and Very Defensive, traders can control the width of IFVG zones to suit their risk management strategy—whether they prefer high-risk setups or low-risk setups.
Display and Color Settings : This section enables users to customize the appearance of the IFVG zones on their charts. Traders can set different colors for Bullish and Bearish zones, allowing for easier distinction and improved visualization.
Alert Settings : One of the standout features of the IFVG indicator is the alert system. By setting up alerts, users can be notified whenever the price approaches a demand or supply zone.
Alerts can be customized to trigger Once Per Bar (one alert per bar) or Per Bar Close (alert at the close of each bar), ensuring that traders stay updated on critical price movements without needing to monitor the chart continuously.
🔵 Conclusion
The ICT Implied Fair Value Gap (IFVG) indicator is a powerful and sophisticated tool in technical analysis, allowing professional traders to identify hidden supply and demand zones and use them as entry and exit points for buy and sell trades.
This indicator’s automatic detection of IFVG zones helps traders uncover hidden trading opportunities that can enhance their analysis.
While the IFVG indicator offers numerous advantages, it is important to use it in conjunction with other technical analysis tools and sound risk management practices.
IFVG alone does not guarantee profitability in trading; it works best when combined with other indicators such as volume analysis and trend-following indicators for a comprehensive trading strategy.
Globex Trap ZoneGlobex Trap Indicator
A powerful tool designed to identify potential trading opportunities by analyzing the relationship between Globex session ranges and Supply & Demand zones during regular trading hours.
Key Features
Tracks and visualizes Globex session price ranges
Identifies key Supply & Demand zones during regular trading hours
Highlights potential trap areas where price might experience significant reactions
Fully customizable time ranges and visual settings
Clear labeling of Globex highs and lows
How It Works
The indicator tracks two key periods:
Globex Session (Default: 6:00 PM - 9:30 AM)
Monitors overnight price action
Marks session high and low
Helps identify potential range breakouts
Supply & Demand Zone (Default: 8:00 AM - 11:00 AM)
Tracks price action during key market hours
Identifies potential reaction zones
Helps spot institutional trading areas
Best Practices for Using This Indicator
Use on 1-hour timeframe or lower for optimal visualization
Best suited for futures and other instruments traded during Globex sessions
Pay attention to areas where Globex range and Supply/Demand zones overlap
Use in conjunction with your existing trading strategy for confirmation
Recommended minimum of 10 days of historical data for context
Settings Explanation
Globex Session: Customizable time range for overnight trading session
Supply & Demand Zone: Adjustable time range for regular trading hours
Days to Look Back: Number of historical days to display (default: 10)
Visual Settings: Customizable colors and transparency for both zones
Important Notes
All times are based on exchange timezone
The indicator respects overnight sessions and properly handles timezone transitions
Historical data requirements: Minimum 10 days recommended
Performance impact: Optimized for smooth operation with minimal resource usage
Disclaimer
Past performance is not indicative of future results. This indicator is designed to be used as part of a comprehensive trading strategy and should not be relied upon as the sole basis for trading decisions.
Updates and Support
I actively maintain this indicator and welcome feedback from the trading community. Please feel free to leave comments or suggestions for improvements.
S&P 100 Option Expiration Week StrategyThe Option Expiration Week Strategy aims to capitalize on increased volatility and trading volume that often occur during the week leading up to the expiration of options on stocks in the S&P 100 index. This period, known as the option expiration week, culminates on the third Friday of each month when stock options typically expire in the U.S. During this week, investors in this strategy take a long position in S&P 100 stocks or an equivalent ETF from the Monday preceding the third Friday, holding until Friday. The strategy capitalizes on potential upward price pressures caused by increased option-related trading activity, rebalancing, and hedging practices.
The phenomenon leveraged by this strategy is well-documented in finance literature. Studies demonstrate that options expiration dates have a significant impact on stock returns, trading volume, and volatility. This effect is driven by various market dynamics, including portfolio rebalancing, delta hedging by option market makers, and the unwinding of positions by institutional investors (Stoll & Whaley, 1987; Ni, Pearson, & Poteshman, 2005). These market activities intensify near option expiration, causing price adjustments that may create short-term profitable opportunities for those aware of these patterns (Roll, Schwartz, & Subrahmanyam, 2009).
The paper by Johnson and So (2013), Returns and Option Activity over the Option-Expiration Week for S&P 100 Stocks, provides empirical evidence supporting this strategy. The study analyzes the impact of option expiration on S&P 100 stocks, showing that these stocks tend to exhibit abnormal returns and increased volume during the expiration week. The authors attribute these patterns to intensified option trading activity, where demand for hedging and arbitrage around options expiration causes temporary price adjustments.
Scientific Explanation
Research has found that option expiration weeks are marked by predictable increases in stock returns and volatility, largely due to the role of options market makers and institutional investors. Option market makers often use delta hedging to manage exposure, which requires frequent buying or selling of the underlying stock to maintain a hedged position. As expiration approaches, their activity can amplify price fluctuations. Additionally, institutional investors often roll over or unwind positions during expiration weeks, creating further demand for underlying stocks (Stoll & Whaley, 1987). This increased demand around expiration week typically leads to temporary stock price increases, offering profitable opportunities for short-term strategies.
Key Research and Bibliography
Johnson, T. C., & So, E. C. (2013). Returns and Option Activity over the Option-Expiration Week for S&P 100 Stocks. Journal of Banking and Finance, 37(11), 4226-4240.
This study specifically examines the S&P 100 stocks and demonstrates that option expiration weeks are associated with abnormal returns and trading volume due to increased activity in the options market.
Stoll, H. R., & Whaley, R. E. (1987). Program Trading and Expiration-Day Effects. Financial Analysts Journal, 43(2), 16-28.
Stoll and Whaley analyze how program trading and portfolio insurance strategies around expiration days impact stock prices, leading to temporary volatility and increased trading volume.
Ni, S. X., Pearson, N. D., & Poteshman, A. M. (2005). Stock Price Clustering on Option Expiration Dates. Journal of Financial Economics, 78(1), 49-87.
This paper investigates how option expiration dates affect stock price clustering and volume, driven by delta hedging and other option-related trading activities.
Roll, R., Schwartz, E., & Subrahmanyam, A. (2009). Options Trading Activity and Firm Valuation. Journal of Financial Markets, 12(3), 519-534.
The authors explore how options trading activity influences firm valuation, finding that higher options volume around expiration dates can lead to temporary price movements in underlying stocks.
Cao, C., & Wei, J. (2010). Option Market Liquidity and Stock Return Volatility. Journal of Financial and Quantitative Analysis, 45(2), 481-507.
This study examines the relationship between options market liquidity and stock return volatility, finding that increased liquidity needs during expiration weeks can heighten volatility, impacting stock returns.
Summary
The Option Expiration Week Strategy utilizes well-researched financial market phenomena related to option expiration. By positioning long in S&P 100 stocks or ETFs during this period, traders can potentially capture abnormal returns driven by option market dynamics. The literature suggests that options-related activities—such as delta hedging, position rollovers, and portfolio adjustments—intensify demand for underlying assets, creating short-term profit opportunities around these key dates.
ICT Panther (By Obicrypto) V1 ICT Panther Indicator: Full and Detailed Description
The ICT Panther Indicator, created by Obicrypto, is an advanced technical analysis tool designed specifically for traders looking to identify key price action events based on institutional trading techniques, particularly in the context of the Inner Circle Trader (ICT) methodology. This indicator helps traders spot market structure breaks, order blocks, and potential trade opportunities driven by institutional behaviors in the market. Here's a detailed breakdown of its features and how it works:
What Does the ICT Panther Indicator Do?
1. Market Structure Breaks (MSB) Identification:
The ICT Panther identifies critical points where the market changes direction, commonly referred to as a break of structure (BoS). When the price breaks above or below certain key levels (based on highs and lows or opens and closes), it signals a potential shift in market sentiment. These break-of-structure points are essential for traders to determine whether the market is likely to continue its trend or reverse.
2. Order Blocks Visualization:
The indicator plots demand (bullish) and supply (bearish) boxes, which represent areas where institutional traders might place significant buy or sell orders. These zones, known as order blocks, are areas where the price tends to pause or reverse, giving traders key insights into potential entry and exit points. The indicator shows these areas graphically as colored boxes on the chart, which can be used to plan trades based on market structure and price action.
3. Pivot Point Detection:
The ICT Panther identifies important pivot points by tracking higher highs and lower lows. These pivot points are critical in determining the strength of a trend and can help traders confirm the direction of the market. The indicator uses a unique algorithm to detect two levels of pivot points:
- First-Order Pivots: Major pivot points where the price makes notable highs and lows.
- Second-Order Pivots: Smaller pivot points, useful for detecting microtrends within the larger market structure.
4. Bullish and Bearish Break of Structure Lines:
When a significant market structure break (BoS) occurs, the indicator will automatically draw red lines (for bearish break of structure) and green lines (for bullish break of structure) at key price levels. These lines help traders quickly see where institutional moves have occurred in the past and where potential future price moves could originate from.
5. Tested and Filled Boxes:
The ICT Panther also has a built-in mechanism to dim previously tested order blocks. When the price tests an order block (returns to a previous demand or supply zone), the box's color dims to indicate that the area has already been tested, reducing its significance. If the price fully fills an order block, the box stops plotting, providing a clear and clutter-free chart.
Key Features
1. Market Structure Break (MSB) Trigger:
- The indicator allows users to select between highs/lows or opens/closes as the trigger for market structure breaks. This flexibility lets traders adjust the indicator to suit their personal trading style or the behavior of specific assets.
2. Order Block Detection and Visualization:
- The tool automatically plots bullish and bearish demand and supply boxes, representing institutional order blocks on the chart. These boxes provide visual cues for areas of potential price action, where institutional traders might be active.
3. Second-Order Pivot Highlighting:
- The ICT Panther offers an option to plot second-order pivots, highlighting smaller pivot points within the larger market structure. These pivots can be helpful for short-term traders who need to react to smaller price movements while still keeping the larger trend in mind.
4. Box Test and Fill Delays:
- Users can configure delays for box tests and box fills, meaning the indicator will only mark a box as tested or filled after a certain number of bars. This prevents false signals and helps confirm that a zone is truly significant in the market.
5. Customization and Visual Clarity:
- The indicator is highly customizable, allowing users to turn on or off various features like:
- Displaying second-order pivots.
- Highlighting candles that broke structure.
- Plotting market structure broke lines.
- Showing or hiding tested and filled demand boxes.
- Setting custom delays for box testing and filling to suit different market conditions.
6. Tested and Filled Order Block Visualization:
- The indicator visually adjusts the tested and filled order blocks, dimming tested zones and removing filled zones to avoid clutter on the chart. This ensures that traders can focus on active trading opportunities without distractions from historical data.
How Does It Work?
1. Detecting Market Structure Breaks (BoS):
- The indicator continuously tracks the market for key price action signals. When the price breaks through previous highs or lows (or opens and closes, depending on your selection), the indicator marks this as a break of structure. This is a critical signal used by institutional traders and retail traders alike to determine potential future price movements.
2. Order Block Identification:
- Whenever a bullish break of structure occurs, the indicator plots a green demand box to show the area where institutional buyers might have placed significant orders. Similarly, for a bearish break of structure, it plots a red supply box representing areas where institutional sellers are active.
3. Pivot Analysis and Tracking:
- As the market moves, the indicator continuously updates first-order and second-order pivot points based on highs and lows. These points help traders identify whether the market is trending or consolidating. Traders can use these pivot points in combination with the order blocks to make informed trading decisions.
4. Box Testing and Filling:
- When the price retests an existing order block, the box dims to show it has been tested. If the price fully fills the box, it is no longer shown, which helps traders focus on the most relevant, untested order blocks.
Benefits for Traders
- Improved Decision-Making: With clear visuals and advanced logic based on institutional trading strategies, this indicator provides a deeper understanding of market structure and price action.
- Reduced Clutter: The indicator intelligently manages the display of order blocks and pivot points, ensuring that traders focus only on the most relevant information.
- Adaptability: Whether you are a swing trader or a day trader, the ICT Panther can be adjusted to fit your trading style, offering robust and flexible tools for tracking market structure and order blocks.
- Institutional Edge: By identifying institutional-level order blocks and market structure breaks, traders using this indicator can trade in line with the strategies of large market participants.
Who Should Use the ICT Panther Indicator?
This indicator is ideal for:
- Crypto, Forex, and Stock Traders who want to incorporate institutional trading concepts into their strategies.
- Technical Analysts looking for precise tools to measure the market structure and price action.
- ICT Traders who follow the Inner Circle Trader methodology and want an advanced tool to automate and enhance their analysis.
- Price Action Traders seeking a reliable indicator to track pivot points, order blocks, and market structure breaks.
The ICT Panther Indicator is a powerful, versatile tool that brings institutional trading techniques to the fingertips of retail traders. Whether you are looking to identify key market structure breaks, order blocks, or crucial pivot points, this indicator offers detailed visualizations and customizable options to help you make more informed trading decisions. With its ability to track the activities of institutional traders, the ICT Panther Indicator equips traders with the insights needed to stay ahead of the market and trade with confidence.
With the ICT Panther Indicator, traders can follow the movements of institutional money, making it easier to predict market direction and capitalize on high-probability trading opportunities.
Enjoy it and share it with your friends!
CANSLIM Screener [TrendX_]INTRODUCTION:
The CANSLIM investment strategy, developed by William J. O'Neil, is a powerful tool for identifying growth stocks that have the potential to outperform the market. TrendX has enhanced this approach with its unique indicators, making it easier for investors to assess stocks based on seven critical criteria.
➊ C: Current Quarterly EPS or PE with Growth Benchmark
The first criterion focuses on the Earnings Per Share (EPS) growth in the most recent quarter compared to previous quarters. A company should demonstrate significant EPS growth, ideally exceeding expectations and benchmarks within its industry.
➋ A: Average Annual EPS Growth with Growth Benchmark
This aspect evaluates a company's average annual EPS growth over the last three years. A consistent upward trend suggests that the company is effectively increasing its profitability. TrendX provides a customizable benchmark to help investors identify firms with sustainable growth trajectories.
➌ N: New Highs or New Product Development
TrendX interprets this criterion through an Annual Research & Development to Revenue Ratio (RNDR). A decreasing RNDR ratio may indicate that a company is finishing new products, which could lead to reduced revenue if product launches are unsuccessful.
➍ S: Supply and Demand
This component assesses supply and demand dynamics by analyzing the movement of Float Shares Outstanding. A decrease in float shares typically indicates higher demand for the stock, suggesting that the company is in good shape for future growth.
➎ L: Leader
TrendX employs comparative analysis between the Relative Strength Index (RSI) of a company and that of the overall market. If a company's RSI is higher than the market's, it signifies that the stock is leading rather than lagging.
➏ I: Institutional Sponsorship
Institutional sponsorship is gauged through the total dividends paid by a company. High dividend payouts can signal strong institutional interest, support and confidence in the company's future prospects.
➐ M: Market Direction
TrendX evaluates market direction by comparing a company's RSI against its Moving Average of RSI, along with utilizing Market Structure in Smart Money Concept indicator for alternative trend insights.
HOW TO USE
The TrendX CANSLIM indicator provides an evaluation score based on each of the seven criteria outlined above, which displays in a table containing:
Scoring System: Each letter in CANSLIM contributes to a total score out of 100%. A stock does not need to meet all seven criteria; achieving a score above 70% (5 out of 7) is generally considered indicative of a promising growth stock.
Screening Feature: The tool includes a screening feature that evaluates multiple stocks simultaneously, allowing investors to compare their CANSLIM scores efficiently. This feature streamlines identifying potential investment opportunities across various sectors.
DISCLAIMER
This indicator is not financial advice, it can only help traders make better decisions. There are many factors and uncertainties that can affect the outcome of any endeavor, and no one can guarantee or predict with certainty what will occur.
Therefore, one should always exercise caution and judgment when making decisions based on past performance.
Volume on levels @gauranshgVolume on Levels @gauranshg is a powerful Pine Script designed to visualize trading volume across price levels directly on the chart. This script allows users to observe volume intensity, offering a clearer perspective on price action and potential support/resistance areas. By utilizing a dynamic, customizable multiplier, the volume is normalized and displayed in proportion, ensuring better scalability across various timeframes and assets.
Usage:
Normalization of Volume: Users can input a multiplier to adjust the normalization of volume. This is useful when analyzing assets with differing price and volume ranges.
Input of 1 means 1 Million volume will be marked with green color of opacity 1 and 2 Million as 2 and so on. In case you are looking at chart with very high volume, you might want to increase the multiplies
Default multiplier is set to 1, and can be customized for different scales.
Volume Visualization: The volume is displayed on the chart as background boxes behind price levels, with the opacity of the boxes changing based on the normalized volume. This helps to quickly visualize areas of high and low trading activity.
This script is ideal for investors who wish to enhance their volume analysis by visualizing it directly on price levels in a clear, normalized format.
Breaker Blocks + Order Blocks confirm [TradingFinder] BBOB Alert🔵 Introduction
In the realm of technical analysis, various tools and concepts are employed to identify key levels on price charts. These tools assist traders in analyzing market trends with greater precision, enabling them to optimize their trading decisions. Among these tools, the Order Block and Breaker Block hold a significant place, serving as effective instruments for analyzing market structure.
🟣 Order Block
An Order Block refers to zones on a chart where large financial institutions and high-volume traders place their orders. Due to the substantial volume of buy or sell orders in these areas, they are often regarded as pivotal points for potential price reversals or temporary pauses in a trend. Order Blocks are particularly crucial when prices react to these zones after a strong market move, acting as strong support or resistance levels.
🟣 Breaker Block
On the other hand, a Breaker Block refers to areas on a chart that previously functioned as Order Blocks but where the price has managed to break through and continue in the opposite direction. These zones are typically recognized as key points where market trends might shift, helping traders identify potential reversal points in the market.
🟣 Overlapping Block (BBOB)
Now, imagine a scenario where these two essential concepts in technical analysis—Order Blocks and Breaker Blocks—overlap on a chart. Although this overlap is not specifically discussed within the ICT (Inner Circle Trader) trading framework, exploring and utilizing this overlap can provide traders with powerful insights into strong support and resistance zones. The combination of these two robust concepts can highlight critical areas in trading, potentially offering significant advantages in making informed trading decisions.
In this article, we will delve into the concept of this overlap, explaining how to utilize it in trading strategies. Additionally, we will analyze the potential outcomes and benefits of incorporating this concept into your trading decisions.
Bullish Overlapping Block (BBOB) :
Bearish Overlapping Block (BBOB) :
🔵 How to Use
The overlap between Order Blocks and Breaker Blocks is a compelling and powerful concept that can help traders identify key levels on the chart with a high probability of success. This overlap is particularly valuable because it combines two well-regarded concepts in technical analysis—zones of high order volume and critical market shifts.
🟣 Here’s how to effectively use this overlap in your trading
1. Dentifying the Overlapping Block : To make the most of the overlap between Order Blocks and Breaker Blocks, begin by identifying these zones separately. Order Blocks are areas where price typically reacts and reverses after a strong market move.
Breaker Blocks are areas where a previous Order Block has been breached, and the price continues in the opposite direction. When these two zones overlap on a chart, it’s crucial to pay close attention to this area, as it represents a high-probability reaction zone.
2. Analyzing the Overlapping Block : After identifying the overlap zone, carefully analyze price action within this region. Candlestick patterns and price behavior can provide essential clues.
If the price reaches this overlap zone and strong reversal patterns such as Pin Bars or Engulfing patterns are observed, it’s likely that this zone will act as a pivotal reversal point. In such cases, entering a trade with confidence becomes more feasible.
3. Entering the Trade : When sufficient signs of price reaction are present in the overlap zone, you can proceed to enter the trade. If the overlap zone is within an uptrend and bullish reversal signals are evident, a long position might be appropriate.
Conversely, if the overlap zone is in a downtrend and bearish reversal signals are observed, a short position would be more suitable.
4. Risk Management : One of the most critical aspects of trading in overlap zones is managing risk. To protect your capital, place your stop loss near the lowest point of the Order Block (for buy trades) or the highest point (for sell trades). This approach minimizes potential losses if the overlap zone fails to hold.
5. Price Targets : After entering the trade, set your price targets based on other key levels on the chart. These targets could include other support and resistance zones, Fibonacci levels, or pivot points.
Bullish Overlapping Block :
Bearish Overlapping Block :
🟣 Benefits of the Overlapping Block Between Order Block and Breaker Block
1. Enhanced Precision in Identifying Key Levels : The overlap between these two zones usually acts as a highly reliable area for price reactions, increasing the accuracy of identifying entry and exit points.
2. Reduced Trading Risk : Given the high importance of the overlap zone, the likelihood of making incorrect decisions is reduced, contributing to overall lower trading risk.
3. Increased Probability of Success : The overlap between Order Blocks and Breaker Blocks combines two powerful concepts, enhancing the likelihood of success in trades, as multiple indicators confirm the importance of the area.
4. Creation of Better Trading Opportunities : Overlap zones often provide traders with more robust trading opportunities, as these areas typically represent strong reversal points in the market.
5. Compatibility with Other Technical Tools : This concept seamlessly integrates with other technical analysis tools such as Fibonacci retracements, trend lines, and chart patterns, offering a more comprehensive market analysis.
🔵 Setting
🟣 Global Setting
Pivot Period of Order Blocks Detector : Enter the desired pivot period to identify the Order Block.
Order Block Validity Period (Bar) : You can specify the maximum time the Order Block remains valid based on the number of candles from the origin.
Mitigation Level Order Block : Determining the basic level of a Order Block. When the price hits the basic level, the Order Block due to mitigation.
Mitigation Level Breaker Block : Determining the basic level of a Breaker Block. When the price hits the basic level, the Breaker Block due to mitigation.
Mitigation Level Overlapping Block : Determining the basic level of a Overlapping Block. When the price hits the basic level, the Overlapping Block due to mitigation.
🟣 Overlapping Block Display
Show All Overlapping Block : If it is turned off, only the last Order Block will be displayed.
Demand Overlapping Block : Show or not show and specify color.
Supply Overlapping Block : Show or not show and specify color.
🟣 Order Block Display
Show All Order Block : If it is turned off, only the last Order Block will be displayed.
Demand Main Order Block : Show or not show and specify color.
Demand Sub (Propulsion & BoS Origin) Order Block : Show or not show and specify color.
Supply Main Order Block : Show or not show and specify color.
Supply Sub (Propulsion & BoS Origin) Order Block : Show or not show and specify color.
🟣 Breaker Block Display
Show All Breaker Block : If it is turned off, only the last Breaker Block will be displayed.
Demand Main Breaker Block : Show or not show and specify color.
Demand Sub (Propulsion & BoS Origin) Breaker Block : Show or not show and specify color.
Supply Main Breaker Block : Show or not show and specify color.
Supply Sub (Propulsion & BoS Origin) Breaker Block : Show or not show and specify color.
🟣 Order Block Refinement
Refine Order Blocks : Enable or disable the refinement feature. Mode selection.
🟣 Alert
Alert Name : The name of the alert you receive.
Alert Overlapping Block Mitigation :
On / Off
Message Frequency :
This string parameter defines the announcement frequency. Choices include: "All" (activates the alert every time the function is called), "Once Per Bar" (activates the alert only on the first call within the bar), and "Once Per Bar Close" (the alert is activated only by a call at the last script execution of the real-time bar upon closing). The default setting is "Once per Bar".
Show Alert Time by Time Zone :
The date, hour, and minute you receive in alert messages can be based on any time zone you choose. For example, if you want New York time, you should enter "UTC-4". This input is set to the time zone "UTC" by default.
🔵 Conclusion
The overlap between Order Blocks and Breaker Blocks represents a critical and powerful area in technical analysis that can serve as an effective tool for determining entry and exit points in trading.
These zones, due to the combination of two key concepts in technical analysis, hold significant importance and can help traders make more confident trading decisions.
Although this concept is not specifically discussed in the ICT framework and is introduced as a new idea, traders can achieve better results in their trades through practice and testing.
Utilizing the overlap between Order Blocks and Breaker Blocks, in conjunction with other technical analysis tools, can significantly improve the chances of success in trading.
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.
Uptrick: Adaptive Trend Strength Index (ATSI)### **Adaptive Trend Strength Index (ATSI): Trend Detection Tool**
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### Introduction
The **Adaptive Trend Strength Index (ATSI)** is a state-of-the-art indicator designed to offer traders an unparalleled view into market trends. By combining the principles of adaptive trend analysis with advanced volatility filtering, ATSI provides a powerful and visually intuitive method for identifying and following market trends. Its unique algorithm and customizable features make it an essential tool for traders across all markets—whether you're trading stocks, forex, commodities, or cryptocurrencies.
### The Purpose and Design Philosophy
At its core, the ATSI was built with the understanding that financial markets are dynamic, ever-changing entities influenced by a multitude of factors, including market sentiment, economic data, geopolitical events, and, critically, volatility. Traditional trend indicators often fall short by either over-smoothing price data (thus lagging behind the actual trend) or reacting too quickly to minor price fluctuations, resulting in false signals.
**ATSI solves this dilemma by adapting to market conditions in real-time.** It effectively filters out market noise while being sensitive enough to detect meaningful shifts in trend direction. The result is a trend line that is both responsive and smooth, providing traders with a clear, actionable view of the market's current trajectory.
### Key Features and Functionality
#### 1. **Adaptive Trend Calculation**
The heart of ATSI is its adaptive trend algorithm, which adjusts based on market conditions. It leverages a combination of price action analysis and volatility filtering to determine the strength and direction of the trend. Here’s how it works:
- **Volatility Sensitivity:** ATSI incorporates the Average True Range (ATR) to measure market volatility. This volatility measure is then adjusted by a user-defined sensitivity factor. This ensures that the indicator responds dynamically to different market environments—be it high-volatility breakouts or low-volatility consolidations.
- **Adaptive Smoothing:** The trend calculation is further enhanced by an exponential moving average (EMA) applied not just to the raw price data, but also to the resulting trend line itself. This dual-layer smoothing process helps to eliminate noise, resulting in a cleaner and more reliable trend line.
- **Real-Time Adaptation:** Unlike rigid indicators that require constant tweaking to stay relevant in changing market conditions, ATSI adapts in real-time. This adaptability makes it particularly valuable in fast-moving markets where conditions can change rapidly.
#### 2. **Visual Clarity**
In trading, visual clarity can make the difference between spotting a lucrative trend and missing out. ATSI excels in this regard by offering a clear, color-coded trend line that provides instant feedback on market conditions:
- **Thicker and Smoother Line:** ATSI’s trend line is designed to be visually prominent. By default, it is thicker than most standard indicators, making it easy to spot even in dense charts. Additionally, the smoothing applied to the line ensures that it flows smoothly, avoiding the jagged, noisy appearance that can plague other indicators.
- **Color-Coded Trends:** The trend line changes color based on the direction and strength of the trend:
- **Green Line**: Indicates a bullish trend, suggesting upward momentum in the market.
- **Red Line**: Indicates a bearish trend, signaling downward momentum.
- **Gold Line**: Represents a neutral or weak trend, where the market is consolidating or where there is no clear direction.
This color-coding is not just for aesthetics—it’s a critical feature that allows traders to quickly assess market conditions at a glance.
#### 3. **Customizable Parameters**
ATSI is built with the understanding that every trader’s strategy is unique. Whether you’re a day trader looking for short-term trends or a swing trader interested in catching longer moves, ATSI can be tailored to fit your needs:
- **Trend Length:** The length parameter controls how much historical data is considered in the trend calculation. A shorter length will make the indicator more sensitive to recent price changes, while a longer length will smooth out short-term fluctuations, focusing on the broader trend.
- **Smoothing Factor:** This parameter controls the level of smoothing applied to the trend line. A higher smoothing factor will result in a smoother, more stable trend line, while a lower factor will make the line more responsive to quick changes in price.
- **Volatility Sensitivity:** By adjusting the volatility sensitivity, you can control how reactive the indicator is to market volatility. A higher sensitivity makes the indicator more likely to detect trends in volatile markets, while a lower sensitivity helps to filter out noise in calmer markets.
- **Line Width:** ATSI allows you to adjust the thickness of the trend line, ensuring that it stands out on your chart. This is particularly useful when trading on charts with a lot of overlays or when you need a clear, bold line to guide your trading decisions.
- **Color Customization:** The colors for bullish, bearish, and neutral trends can be fully customized to match your personal preferences or to integrate seamlessly with your existing chart setup.
### Practical Applications
ATSI is a versatile indicator that can be applied to a wide range of trading strategies. Here’s how it can enhance your trading:
#### 1. **Trend Following**
For traders who thrive on catching and riding trends, ATSI is a game-changer. Its adaptive nature ensures that you stay in the trend for as long as possible without being shaken out by minor fluctuations. The clear color-coded line makes it easy to identify when a trend starts and ends, providing clear entry and exit signals.
#### 2. **Risk Management**
One of the biggest challenges in trading is managing risk, particularly in volatile markets. ATSI’s volatility sensitivity feature helps traders adjust their strategies based on current market conditions. For example, in a high-volatility environment, the indicator will become more sensitive, allowing you to tighten your stop losses or take profits earlier. Conversely, in a low-volatility market, the indicator will smooth out minor fluctuations, reducing the risk of being stopped out prematurely.
#### 3. **Trend Reversals and Consolidations**
ATSI is also highly effective in identifying trend reversals and periods of consolidation. The neutral (gold) line indicates periods where the market is undecided, which can often precede significant moves. Recognizing these periods can help you avoid getting caught in choppy markets and position yourself for the next big move.
#### 4. **Market Timing**
Timing the market is often seen as the holy grail of trading. While no indicator can predict the future with 100% accuracy, ATSI’s real-time adaptation gives you a significant edge. By responding to changes in market conditions as they happen, ATSI helps you make timely decisions, whether you’re entering a trade, exiting a position, or adjusting your risk parameters.
### Comparative Advantage
What sets ATSI apart from other trend indicators is its combination of adaptability, visual clarity, and ease of use:
- **Adaptability:** Most trend indicators are static—they apply the same calculations regardless of market conditions. ATSI, however, adapts to the market in real-time, ensuring that it remains relevant and reliable across different market environments.
- **Visual Clarity:** The thicker, smoother, color-coded line is not just aesthetically pleasing—it’s a functional design choice that helps you quickly interpret market conditions. Whether you’re glancing at your chart or conducting an in-depth analysis, the ATSI line stands out, providing immediate insight.
- **Ease of Use:** Despite its advanced features, ATSI is incredibly easy to use. The default settings are optimized for general use, but the indicator offers a high degree of customization for those who want to tailor it to their specific trading strategy.
### Conclusion
The **Adaptive Trend Strength Index (ATSI)** is more than just another trend indicator—it’s a comprehensive tool designed to give traders an edge in today’s fast-paced, volatile markets. By combining adaptive trend analysis with advanced volatility filtering, ATSI offers a unique blend of responsiveness and reliability. Its clear, color-coded visual representation of trends makes it easy to use, even for traders who are new to technical analysis, while its customizable parameters provide the flexibility that experienced traders demand.
Whether you’re looking to ride the next big trend, manage your risk more effectively, or simply get a clearer picture of the market’s current direction, ATSI is an invaluable addition to your trading toolkit. With its cutting-edge design and powerful functionality, ATSI is poised to become the go-to indicator for traders seeking to enhance their market analysis and improve their trading outcomes.
