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Multi Timeframe Bollinger Bands Spectrum [Ata]Multi-Timeframe Bollinger Bands Spectrum
Technical Overview
This script integrates multi-timeframe volatility analysis with volume-derived order flow estimation. By combining Bollinger Bands (statistical deviation) with internal candle volume logic, the indicator qualifies price movements to differentiate between sustained trends, reversals, and exhaustion events.
The system is designed to provide a structural context for price action, visualizing market regimes through a dual-zone spectrum and filtering signals based on the interaction between price location and specific volume thresholds.
Core Logic & Calculation
1. Volume Decomposition Algorithm
Instead of using total volume, the script estimates Buying Pressure vs. Selling Pressure based on the close position relative to the candle's High/Low range:
- Buying Volume (vb): Increases as the close approaches the High.
- Selling Volume (vs): Increases as the close approaches the Low.
This logic allows the detection of directional flow even within standard volume bars.
2. Statistical Spectrum
The indicator renders deviations from the Basis (SMA) as two distinct zones:
- Bullish Zone (Blue): Price positioning between the Basis and Upper Band.
- Bearish Zone (Red): Price positioning between the Basis and Lower Band.
This structure is applied across multiple timeframes (overlay) to visualize the macro trend context without noise.
3. Non-Repainting Execution
To ensure historical accuracy and reliability for backtesting, all higher-timeframe data is requested using "lookahead_off". Signals are confirmed only upon the closure of the respective timeframe's candle.
Signal Definitions
Signals are generated only when specific Volatility and Volume conditions intersect:
Reversal Setups (Reaction to Liquidity)
- WALL: Triggered when price rejects the Upper Band accompanied by Extreme Selling Volume (vs > Limit). This suggests active limit sell orders absorbing the rally.
- FLOOR: Triggered when price rejects the Lower Band accompanied by Extreme Buying Volume (vb > Limit). This suggests active limit buy orders absorbing the drop.
- ABSORP: Identifies absorption near the lower bands where selling pressure is met with passive buying (indicated by lower wicks and relative buy volume).
Momentum Setups (Trend Continuation)
- POWER: Validates a breakout above the Upper Band only if supported by Dominant Buying Volume and a strong candle body.
- PANIC: Validates a breakdown below the Lower Band only if supported by Dominant Selling Volume.
- TRAP: Marks failed breakouts where price exits the bands but volume analysis contradicts the move (e.g., low directional volume).
Exhaustion Setups (Statistical Extremes)
- CLIMAX/CRASH: Identifies anomalies where price deviates significantly from the mean (Extreme Deviation) or when volume reaches unsustainable levels relative to the average, often preceding a mean reversion.
Input Parameters
- Bollinger Logic: Configuration for Length and Standard Deviation Multiplier.
- Volume Thresholds: Adjustable factors for Minimum Volume (Trend) and Extreme Volume (Reversal/Climax).
- Timeframe Layers: Toggle visibility for up to 5 higher timeframes.
- Theme: Adjusts label contrast for Dark/Light backgrounds.
Disclaimer
This indicator is strictly for analytical purposes. It provides a visualization of past market data based on statistical and volumetric formulas. Users should apply their own risk management protocols.
Systemic Net Liquidity (Macro Fuel for Crypto & Stocks)This indicator tracks Systemic Net Liquidity, the single most important macro factor for determining the long-term trend of risk assets like Bitcoin (BTC) and major indices (S&P 500). It measures the amount of actual cash available in the financial system to chase speculative assets, distinguishing between money that is circulating and money that is locked up at the Federal Reserve.
Mechanism (What It Measures)
The script uses direct data from the FRED (Federal Reserve Economic Data) to calculate the true state of market funding:
\text{Net Liquidity} = \text{Fed Assets (WALCL)} - \text{Treasury General Account (TGA)} - \text{Reverse Repo (RRP)}
1. Fed Assets (WALCL): The total balance sheet of the Fed (The overall supply of money).
2. Treasury General Account (TGA): Funds the US Treasury collects via bond issuance. When the TGA rises, liquidity is actively drained from the banking system (A major bearish pressure).
3. Overnight Reverse Repo (RRP): Cash parked by banks and money market funds at the Fed, effectively frozen and not contributing to market activity.
How to Interpret Signals
Treat the Net Liquidity line as the market's "Fuel Gauge":
📈 BULLISH SIGNAL (Liquidity Injection): When the Net Liquidity line is rising, money is flowing back into the system, signalling a tailwind for risk assets.
📉 BEARISH SIGNAL (Liquidity Drain): When the line is falling (often due to high TGA balances), cash is being removed. This signals major friction and pressure on price action.
⚠️ DIVERGENCE WARNING: A strong signal is generated when Price (e.g., BTC) rises, but Net Liquidity falls. This macro divergence strongly suggests a major trend reversal or correction is imminent.
Important Notes
Data Source: Data is directly sourced from FRED and updates daily/weekly. This tool is best used for macro analysis and identifying high-level cycles, not short-term scalping.
Disclaimer: Use this indicator as a confirmation tool within your broader strategy. It is not a standalone trading signal.
Systemic Net Liquidity (Macro Fuel for Crypto & Stocks)This indicator tracks Systemic Net Liquidity, the single most important macro factor for determining the long-term trend of risk assets like Bitcoin (BTC) and major indices (S&P 500). It measures the amount of actual cash available in the financial system to chase speculative assets, distinguishing between money that is circulating and money that is locked up at the Federal Reserve.
Mechanism (What It Measures)
The script uses direct data from the FRED (Federal Reserve Economic Data) to calculate the true state of market funding:
\text{Net Liquidity} = \text{Fed Assets (WALCL)} - \text{Treasury General Account (TGA)} - \text{Reverse Repo (RRP)}
1. Fed Assets (WALCL): The total balance sheet of the Fed (The overall supply of money).
2. Treasury General Account (TGA): Funds the US Treasury collects via bond issuance. When the TGA rises, liquidity is actively drained from the banking system (A major bearish pressure).
3. Overnight Reverse Repo (RRP): Cash parked by banks and money market funds at the Fed, effectively frozen and not contributing to market activity.
How to Interpret Signals
Treat the Net Liquidity line as the market's "Fuel Gauge":
📈 BULLISH SIGNAL (Liquidity Injection): When the Net Liquidity line is rising, money is flowing back into the system, signalling a tailwind for risk assets.
📉 BEARISH SIGNAL (Liquidity Drain): When the line is falling (often due to high TGA balances), cash is being removed. This signals major friction and pressure on price action.
⚠️ DIVERGENCE WARNING: A strong signal is generated when Price (e.g., BTC) rises, but Net Liquidity falls. This macro divergence strongly suggests a major trend reversal or correction is imminent.
Important Notes
Data Source: Data is directly sourced from FRED and updates daily/weekly. This tool is best used for macro analysis and identifying high-level cycles, not short-term scalping.
Disclaimer: Use this indicator as a confirmation tool within your broader strategy. It is not a standalone trading signal.
Mars Signals - Ultimate Institutional Suite v3.0(Joker)Comprehensive Trading Manual
Mars Signals – Ultimate Institutional Suite v3.0 (Joker)
## Chapter 1 – Philosophy & System Architecture
This script is not a simple “buy/sell” indicator.
Mars Signals – UIS v3.0 (Joker) is designed as an institutional-style analytical assistant that layers several methodologies into a single, coherent framework.
The system is built on four core pillars:
1. Smart Money Concepts (SMC)
- Detection of Order Blocks (professional demand/supply zones).
- Detection of Fair Value Gaps (FVGs) (price imbalances).
2. Smart DCA Strategy
- Combination of RSI and Bollinger Bands
- Identifies statistically discounted zones for scaling into spot positions or exiting shorts.
3. Volume Profile (Visible Range Simulation)
- Distribution of volume by price, not by time.
- Identification of POC (Point of Control) and high-/low-volume areas.
4. Wyckoff Helper – Spring
- Detection of bear traps, liquidity grabs, and sharp bullish reversals.
All four pillars feed into a Confluence Engine (Scoring System).
The final output is presented in the Dashboard, with a clear, human-readable signal:
- STRONG LONG 🚀
- WEAK LONG ↗
- NEUTRAL / WAIT
- WEAK SHORT ↘
- STRONG SHORT 🩸
This allows the trader to see *how many* and *which* layers of the system support a bullish or bearish bias at any given time.
## Chapter 2 – Settings Overview
### 2.1 General & Dashboard Group
- Show Dashboard Panel (`show_dash`)
Turns the dashboard table in the corner of the chart ON/OFF.
- Show Signal Recommendation (`show_rec`)
- If enabled, the textual signal (STRONG LONG, WEAK SHORT, etc.) is displayed.
- If disabled, you only see feature status (ON/OFF) and the current price.
- Dashboard Position (`dash_pos`)
Determines where the dashboard appears on the chart:
- `Top Right`
- `Bottom Right`
- `Top Left`
### 2.2 Smart Money (SMC) Group
- Enable SMC Strategy (`show_smc`)
Globally enables or disables the Order Block and FVG logic.
- Order Block Pivot Lookback (`ob_period`)
Main parameter for detecting key pivot highs/lows (swing points).
- Default value: 5
- Concept:
A bar is considered a pivot low if its low is lower than the lows of the previous 5 and the next 5 bars.
Similarly, a pivot high has a high higher than the previous 5 and the next 5 bars.
These pivots are used as anchors for Order Blocks.
- Increasing `ob_period`:
- Fewer levels.
- But levels tend to be more significant and reliable.
- In highly volatile markets (major news, war events, FOMC, etc.),
using values 7–10 is recommended to filter out weak levels.
- Show Fair Value Gaps (`show_fvg`)
Enables/disables the drawing of FVG zones (imbalances).
- Bullish OB Color (`c_ob_bull`)
- Color of Bullish Order Blocks (Demand Zones).
- Default: semi-transparent green (transparency ≈ 80).
- Bearish OB Color (`c_ob_bear`)
- Color of Bearish Order Blocks (Supply Zones).
- Default: semi-transparent red.
- Bullish FVG Color (`c_fvg_bull`)
- Color of Bullish FVG (upward imbalance), typically yellow.
- Bearish FVG Color (`c_fvg_bear`)
- Color of Bearish FVG (downward imbalance), typically purple.
### 2.3 Smart DCA Strategy Group
- Enable DCA Zones (`show_dca`)
Enables the Smart DCA logic and visual labels.
- RSI Length (`rsi_len`)
Lookback period for RSI (default: 14).
- Shorter → more sensitive, more noise.
- Longer → fewer signals, higher reliability.
- Bollinger Bands Length (`bb_len`)
Moving average period for Bollinger Bands (default: 20).
- BB Multiplier (`bb_mult`)
Standard deviation multiplier for Bollinger Bands (default: 2.0).
- For extremely volatile markets, values like 2.5–3.0 can be used so that only extreme deviations trigger a DCA signal.
### 2.4 Volume Profile (Visible Range Sim) Group
- Show Volume Profile (`show_vp`)
Enables the simulated Volume Profile bars on the right side of the chart.
- Volume Lookback Bars (`vp_lookback`)
Number of bars used to compute the Volume Profile (default: 150).
- Higher values → broader historical context, heavier computation.
- Row Count (`vp_rows`)
Number of vertical price segments (rows) to divide the total price range into (default: 30).
- Width (%) (`vp_width`)
Relative width of each volume bar as a percentage.
In the code, bar widths are scaled relative to the row with the maximum volume.
> Technical note: Volume Profile calculations are executed only on the last bar (`barstate.islast`) to keep the script performant even on higher timeframes.
### 2.5 Wyckoff Helper Group
- Show Wyckoff Events (`show_wyc`)
Enables detection and plotting of Wyckoff Spring events.
- Volume MA Length (`vol_ma_len`)
Length of the moving average on volume.
A bar is considered to have Ultra Volume if its volume is more than 2× the volume MA.
## Chapter 3 – Smart Money Strategy (Order Blocks & FVG)
### 3.1 What Is an Order Block?
An Order Block (OB) represents the footprint of large institutional orders:
- Bullish Order Block (Demand Zone)
The last selling region (bearish candle/cluster) before a strong upward move.
- Bearish Order Block (Supply Zone)
The last buying region (bullish candle/cluster) before a strong downward move.
Institutions and large players place heavy orders in these regions. Typical price behavior:
- Price moves away from the zone.
- Later returns to the same zone to fill unfilled orders.
- Then continues the larger trend.
In the script:
- If `pl` (pivot low) forms → a Bullish OB is created.
- If `ph` (pivot high) forms → a Bearish OB is created.
The box is drawn:
- From `bar_index ` to `bar_index`.
- Between `low ` and `high `.
- `extend=extend.right` extends the OB into the future, so it acts as a dynamic support/resistance zone.
- Only the last 4 OB boxes are kept to avoid clutter.
### 3.2 Order Block Color Guide
- Semi-transparent Green (`c_ob_bull`)
- Represents a Bullish Order Block (Demand Zone).
- Interpretation: a price region with a high probability of bullish reaction.
- Semi-transparent Red (`c_ob_bear`)
- Represents a Bearish Order Block (Supply Zone).
- Interpretation: a price region with a high probability of bearish reaction.
Overlap (Multiple OBs in the Same Area)
When two or more Order Blocks overlap:
- The shared area appears visually denser/stronger.
- This suggests higher order density.
- Such zones can be treated as high-priority levels for entries, exits, and stop-loss placement.
### 3.3 Demand/Supply Logic in the Scoring Engine
is_in_demand = low <= ta.lowest(low, 20)
is_in_supply = high >= ta.highest(high, 20)
- If current price is near the lowest lows of the last 20 bars, it is considered in a Demand Zone → positive impact on score.
- If current price is near the highest highs of the last 20 bars, it is considered in a Supply Zone → negative impact on score.
This logic complements Order Blocks and helps the Dashboard distinguish whether:
- Market is currently in a statistically cheap (long-friendly) area, or
- In a statistically expensive (short-friendly) area.
### 3.4 Fair Value Gaps (FVG)
#### Concept
When the market moves aggressively:
- Some price levels are skipped and never traded.
- A gap between wicks/shadows of consecutive candles appears.
- These regions are called Fair Value Gaps (FVGs) or Imbalances.
The market generally “dislikes” imbalance and often:
- Returns to these zones in the future.
- Fills the gap (rebalance).
- Then resumes its dominant direction.
#### Implementation in the Code
Bullish FVG (Yellow)
fvg_bull_cond = show_smc and show_fvg and low > high and close > high
if fvg_bull_cond
box.new(bar_index , high , bar_index, low, ...)
Core condition:
`low > high ` → the current low is above the high of two bars ago; the space between them is an untraded gap.
Bearish FVG (Purple)
fvg_bear_cond = show_smc and show_fvg and high < low and close < low
if fvg_bear_cond
box.new(bar_index , low , bar_index, high, ...)
Core condition:
`high < low ` → the current high is below the low of two bars ago; again a price gap exists.
#### FVG Color Guide
- Transparent Yellow (`c_fvg_bull`) – Bullish FVG
Often acts like a magnet for price:
- Price tends to retrace into this zone,
- Fill the imbalance,
- And then continue higher.
- Transparent Purple (`c_fvg_bear`) – Bearish FVG
Price tends to:
- Retrace upward into the purple area,
- Fill the imbalance,
- And then resume downward movement.
#### Trading with FVGs
- FVGs are *not* standalone entry signals.
They are best used as:
- Targets (take-profit zones), or
- Reaction areas where you expect a pause or reversal.
Examples:
- If you are long, a bearish FVG above is often an excellent take-profit zone.
- If you are short, a bullish FVG below is often a good cover/exit zone.
### 3.5 Core SMC Trading Templates
#### Reversal Long
1. Price trades down into a green Order Block (Demand Zone).
2. A bullish confirmation candle (Close > Open) forms inside or just above the OB.
3. If this zone is close to or aligned with a bullish FVG (yellow), the signal is reinforced.
4. Entry:
- At the close of the confirmation candle, or
- Using a limit order near the upper boundary of the OB.
5. Stop-loss:
- Slightly below the OB.
- If the OB is broken decisively and price consolidates below it, the zone loses validity.
6. Targets:
- The next FVG,
- Or the next red Order Block (Supply Zone) above.
#### Reversal Short
The mirror scenario:
- Price rallies into a red Order Block (Supply).
- A bearish confirmation candle forms (Close < Open).
- FVG/premium structure above can act as a confluence.
- Stop-loss goes above the OB.
- Targets: lower FVGs or subsequent green OBs below.
## Chapter 4 – Smart DCA Strategy (RSI + Bollinger Bands)
### 4.1 Smart DCA Concept
- Classic DCA = buying at fixed time intervals regardless of price.
- Smart DCA = scaling in only when:
- Price is statistically cheaper than usual, and
- The market is in a clear oversold condition.
Code logic:
rsi_val = ta.rsi(close, rsi_len)
= ta.bb(close, bb_len, bb_mult)
dca_buy = show_dca and rsi_val < 30 and close < bb_lower
dca_sell = show_dca and rsi_val > 70 and close > bb_upper
Conditions:
- DCA Buy – Smart Scale-In Zone
- RSI < 30 → oversold.
- Close < lower Bollinger Band → price has broken below its typical volatility envelope.
- DCA Sell – Overbought/Distribution Zone
- RSI > 70 → overbought.
- Close > upper Bollinger Band → price is extended far above the mean.
### 4.2 Visual Representation on the Chart
- Green “DCA” Label Below Candle
- Shape: `labelup`.
- Color: lime background, white text.
- Meaning: statistically attractive level for laddered spot entries or short exits.
- Red “SELL” Label Above Candle
- Warning that the market is in an extended, overbought condition.
- Suitable for profit-taking on longs or considering short entries (with proper confluence and risk management).
- Light Green Background (`bgcolor`)
- When `dca_buy` is true, the candle background turns very light green (high transparency).
- This helps visually identify DCA Zones across the chart at a glance.
### 4.3 Practical Use in Trading
#### Spot Trading
Used to build a better average entry price:
- Every time a DCA label appears, allocate a fixed portion of capital (e.g., 2–5%).
- Combining DCA signals with:
- Green OBs (Demand Zones), and/or
- The Volume Profile POC
makes the zone structurally more important.
#### Futures Trading
- Longs
- Use DCA Buy signals as low-risk zones for opening or adding to longs when:
- Price is inside a green OB, or
- The Dashboard already leans LONG.
- Shorts
- Use DCA Sell signals as:
- Exit zones for longs, or
- Areas to initiate shorts with stops above structural highs.
## Chapter 5 – Volume Profile (Visible Range Simulation)
### 5.1 Concept
Traditional volume (histogram under the chart) shows volume over time.
Volume Profile shows volume by price level:
- At which prices has the highest trading activity occurred?
- Where did buyers and sellers agree the most (High Volume Nodes – HVNs)?
- Where did price move quickly due to low participation (Low Volume Nodes – LVNs)?
### 5.2 Implementation in the Script
Executed only when `show_vp` is enabled and on the last bar:
1. The last `vp_lookback` bars (default 150) are processed.
2. The minimum low and maximum high over this window define the price range.
3. This price range is divided into `vp_rows` segments (e.g., 30 rows).
4. For each row:
- All bars are scanned.
- If the mid-price `(high + low ) / 2` falls inside a row, that bar’s volume is added to the row total.
5. The row with the greatest volume is stored as `max_vol_idx` (the POC row).
6. For each row, a volume box is drawn on the right side of the chart.
### 5.3 Color Scheme
- Semi-transparent Orange
- The row with the maximum volume – the Point of Control (POC).
- Represents the strongest support/resistance level from a volume perspective.
- Semi-transparent Blue
- Other volume rows.
- The taller the bar → the higher the volume → the stronger the interest at that price band.
### 5.4 Trading Applications
- If price is above POC and retraces back into it:
→ POC often acts as support, suitable for long setups.
- If price is below POC and rallies into it:
→ POC often acts as resistance, suitable for short setups or profit-taking.
HVNs (Tall Blue Bars)
- Represent areas of equilibrium where the market has spent time and traded heavily.
- Price tends to consolidate here before choosing a direction.
LVNs (Short or Nearly Empty Bars)
- Represent low participation zones.
- Price often moves quickly through these areas – useful for targeting fast moves.
## Chapter 6 – Wyckoff Helper – Spring
### 6.1 Spring Concept
In the Wyckoff framework:
- A Spring is a false break of support.
- The market briefly trades below a well-defined support level, triggers stop losses,
then sharply reverses upward as institutional buyers absorb liquidity.
This movement:
- Clears out weak hands (retail sellers).
- Provides large players with liquidity to enter long positions.
- Often initiates a new uptrend.
### 6.2 Code Logic
Conditions for a Spring:
1. The current low is lower than the lowest low of the previous 50 bars
→ apparent break of a long-standing support.
2. The bar closes bullish (Close > Open)
→ the breakdown was rejected.
3. Volume is significantly elevated:
→ `volume > 2 × volume_MA` (Ultra Volume).
When all conditions are met and `show_wyc` is enabled:
- A pink diamond is plotted below the bar,
- With the label “Spring” – one of the strongest long signals in this system.
### 6.3 Trading Use
- After a valid Spring, markets frequently enter a meaningful bullish phase.
- The highest quality setups occur when:
- The Spring forms inside a green Order Block, and
- Near or on the Volume Profile POC.
Entries:
- At the close of the Spring bar, or
- On the first pullback into the mid-range of the Spring candle.
Stop-loss:
- Slightly below the Spring’s lowest point (wick low plus a small buffer).
## Chapter 7 – Confluence Engine & Dashboard
### 7.1 Scoring Logic
For each bar, the script:
1. Resets `score` to 0.
2. Adjusts the score based on different signals.
SMC Contribution
if show_smc
if is_in_demand
score += 1
if is_in_supply
score -= 1
- Being in Demand → `+1`
- Being in Supply → `-1`
DCA Contribution
if show_dca
if dca_buy
score += 2
if dca_sell
score -= 2
- DCA Buy → `+2` (strong, statistically driven long signal)
- DCA Sell → `-2`
Wyckoff Spring Contribution
if show_wyc
if wyc_spring
score += 2
- Spring → `+2` (entry of strong money)
### 7.2 Mapping Score to Dashboard Signal
- score ≥ 2 → STRONG LONG 🚀
Multiple bullish conditions aligned.
- score = 1 → WEAK LONG ↗
Some bullish bias, but only one layer clearly positive.
- score = 0 → NEUTRAL / WAIT
Rough balance between buying and selling forces; staying flat is usually preferable.
- score = -1 → WEAK SHORT ↘
Mild bearish bias, suited for cautious or short-term plays.
- score ≤ -2 → STRONG SHORT 🩸
Convergence of several bearish signals.
### 7.3 Dashboard Structure
The dashboard is a two-column table:
- Row 0
- Column 0: `"Mars Signals"` – black background, white text.
- Column 1: `"UIS v3.0"` – black background, yellow text.
- Row 1
- Column 0: `"Price:"` (light grey background).
- Column 1: current closing price (`close`) with a semi-transparent blue background.
- Row 2
- Column 0: `"SMC:"`
- Column 1:
- `"ON"` (green) if `show_smc = true`
- `"OFF"` (grey) otherwise.
- Row 3
- Column 0: `"DCA:"`
- Column 1:
- `"ON"` (green) if `show_dca = true`
- `"OFF"` (grey) otherwise.
- Row 4
- Column 0: `"Signal:"`
- Column 1: signal text (`status_txt`) with background color `status_col`
(green, red, teal, maroon, etc.)
- If `show_rec = false`, these cells are cleared.
## Chapter 8 – Visual Legend (Colors, Shapes & Actions)
For quick reading inside TradingView, the visual elements are described line by line instead of a table.
Chart Element: Green Box
Color / Shape: Transparent green rectangle
Core Meaning: Bullish Order Block (Demand Zone)
Suggested Trader Response: Look for longs, Smart DCA adds, closing or reducing shorts.
Chart Element: Red Box
Color / Shape: Transparent red rectangle
Core Meaning: Bearish Order Block (Supply Zone)
Suggested Trader Response: Look for shorts, or take profit on existing longs.
Chart Element: Yellow Area
Color / Shape: Transparent yellow zone
Core Meaning: Bullish FVG / upside imbalance
Suggested Trader Response: Short take-profit zone or expected rebalance area.
Chart Element: Purple Area
Color / Shape: Transparent purple zone
Core Meaning: Bearish FVG / downside imbalance
Suggested Trader Response: Long take-profit zone or temporary supply region.
Chart Element: Green "DCA" Label
Color / Shape: Green label with white text, plotted below the candle
Core Meaning: Smart ladder-in buy zone, DCA buy opportunity
Suggested Trader Response: Spot DCA entry, partial short exit.
Chart Element: Red "SELL" Label
Color / Shape: Red label with white text, plotted above the candle
Core Meaning: Overbought / distribution zone
Suggested Trader Response: Take profit on longs, consider initiating shorts.
Chart Element: Light Green Background (bgcolor)
Color / Shape: Very transparent light-green background behind bars
Core Meaning: Active DCA Buy zone
Suggested Trader Response: Treat as a discount zone on the chart.
Chart Element: Orange Bar on Right
Color / Shape: Transparent orange horizontal bar in the volume profile
Core Meaning: POC – price with highest traded volume
Suggested Trader Response: Strong support or resistance; key reference level.
Chart Element: Blue Bars on Right
Color / Shape: Transparent blue horizontal bars in the volume profile
Core Meaning: Other volume levels, showing high-volume and low-volume nodes
Suggested Trader Response: Use to identify balance zones (HVN) and fast-move corridors (LVN).
Chart Element: Pink "Spring" Diamond
Color / Shape: Pink diamond with white text below the candle
Core Meaning: Wyckoff Spring – liquidity grab and potential major bullish reversal
Suggested Trader Response: One of the strongest long signals in the suite; look for high-quality long setups with tight risk.
Chart Element: STRONG LONG in Dashboard
Color / Shape: Green background, white text in the Signal row
Core Meaning: Multiple bullish layers in confluence
Suggested Trader Response: Consider initiating or increasing longs with strict risk management.
Chart Element: STRONG SHORT in Dashboard
Color / Shape: Red background, white text in the Signal row
Core Meaning: Multiple bearish layers in confluence
Suggested Trader Response: Consider initiating or increasing shorts with a logical, well-placed stop.
## Chapter 9 – Timeframe-Based Trading Playbook
### 9.1 Timeframe Selection
- Scalping
- Timeframes: 1M, 5M, 15M
- Objective: fast intraday moves (minutes to a few hours).
- Recommendation: focus on SMC + Wyckoff.
Smart DCA on very low timeframes may introduce excessive noise.
- Day Trading
- Timeframes: 15M, 1H, 4H
- Provides a good balance between signal quality and frequency.
- Recommendation: use the full stack – SMC + DCA + Volume Profile + Wyckoff + Dashboard.
- Swing Trading & Position Investing
- Timeframes: Daily, Weekly
- Emphasis on Smart DCA + Volume Profile.
- SMC and Wyckoff are used mainly to fine-tune swing entries within larger trends.
### 9.2 Scenario A – Scalping Long
Example: 5-Minute Chart
1. Price is declining into a green OB (Bullish Demand).
2. A candle with a long lower wick and bullish close (Pin Bar / Rejection) forms inside the OB.
3. A Spring diamond appears below the same candle → very strong confluence.
4. The Dashboard shows at least WEAK LONG ↗, ideally STRONG LONG 🚀.
5. Entry:
- On the close of the confirmation candle, or
- On the first pullback into the mid-range of that candle.
6. Stop-loss:
- Slightly below the OB.
7. Targets:
- Nearby bearish FVG above, and/or
- The next red OB.
### 9.3 Scenario B – Day-Trading Short
Recommended Timeframes: 1H or 4H
1. The market completes a strong impulsive move upward.
2. Price enters a red Order Block (Supply).
3. In the same zone, a purple FVG appears or remains unfilled.
4. On a lower timeframe (e.g., 15M), RSI enters overbought territory and a DCA Sell signal appears.
5. The main timeframe Dashboard (1H) shows WEAK SHORT ↘ or STRONG SHORT 🩸.
Trade Plan
- Open a short near the upper boundary of the red OB.
- Place the stop above the OB or above the last swing high.
- Targets:
- A yellow FVG lower on the chart, and/or
- The next green OB (Demand) below.
### 9.4 Scenario C – Swing / Investment with Smart DCA
Timeframes: Daily / Weekly
1. On the daily or weekly chart, each time a green “DCA” label appears:
- Allocate a fixed fraction of your capital (e.g., 3–5%) to that asset.
2. Check whether this DCA zone aligns with the orange POC of the Volume Profile:
- If yes → the quality of the entry zone is significantly higher.
3. If the DCA signal sits inside a daily green OB, the probability of a medium-term bottom increases.
4. Always build the position laddered, never all-in at a single price.
Exits for investors:
- Near weekly red OBs or large purple FVG zones.
- Ideally via partial profit-taking rather than closing 100% at once.
### 9.5 Case Study 1 – BTCUSDT (15-Minute)
- Context: Price has sold off down towards 65,000 USD.
- A green OB had previously formed at that level.
- Near the lower boundary of this OB, a partially filled yellow FVG is present.
- As price returns to this region, a Spring appears.
- The Dashboard shifts from NEUTRAL / WAIT to WEAK LONG ↗.
Plan
- Enter a long near the OB low.
- Place stop below the Spring low.
- First target: a purple FVG around 66,200.
- Second (optional) target: the first red OB above that level.
### 9.6 Case Study 2 – Meme Coin (PEPE – 4H)
- After a strong pump, price enters a corrective phase.
- On the 4H chart, RSI drops below 30; price breaks below the lower Bollinger Band → a DCA label prints.
- The Volume Profile shows the POC at approximately the same level.
- The Dashboard displays STRONG LONG 🚀.
Plan
- Execute laddered buys in the combined DCA + POC zone.
- Place a protective stop below the last significant swing low.
- Target: an expected 20–30% upside move towards the next red OB or purple FVG.
## Chapter 10 – Risk Management, Psychology & Advanced Tuning
### 10.1 Risk Management
No signal, regardless of its strength, replaces risk control.
Recommendations:
- In futures, do not expose more than 1–3% of account equity to risk per trade.
- Adjust leverage to the volatility of the instrument (lower leverage for highly volatile altcoins).
- Place stop-losses in zones where the idea is clearly invalidated:
- Below/above the relevant Order Block or Spring, not randomly in the middle of the structure.
### 10.2 Market-Specific Parameter Tuning
- Calmer Markets (e.g., major FX pairs)
- `ob_period`: 3–5.
- `bb_mult`: 2.0 is usually sufficient.
- Highly Volatile Markets (Crypto, news-driven assets)
- `ob_period`: 7–10 to highlight only the most robust OBs.
- `bb_mult`: 2.5–3.0 so that only extreme deviations trigger DCA.
- `vol_ma_len`: increase (e.g., to ~30) so that Spring triggers only on truly exceptional
volume spikes.
### 10.3 Trading Psychology
- STRONG LONG 🚀 does not mean “risk-free”.
It means the probability of a successful long, given the model’s logic, is higher than average.
- Treat Mars Signals as a confirmation and context system, not a full replacement for your own decision-making.
- Example of disciplined thinking:
- The Dashboard prints STRONG LONG,
- But price is simultaneously testing a multi-month macro resistance or a major negative news event is imminent,
- In such cases, trade smaller, widen stops appropriately, or skip the trade.
## Chapter 11 – Technical Notes & FAQ
### 11.1 Does the Script Repaint?
- Order Blocks and Springs are based on completed pivot structures and confirmed candles.
- Until a pivot is confirmed, an OB does not exist; after confirmation, behavior is stable under classic SMC assumptions.
- The script is designed to be structurally consistent rather than repainting signals arbitrarily.
### 11.2 Computational Load of Volume Profile
- On the last bar, the script processes up to `vp_lookback` bars × `vp_rows` rows.
- On very low timeframes with heavy zooming, this can become demanding.
- If you experience performance issues:
- Reduce `vp_lookback` or `vp_rows`, or
- Temporarily disable Volume Profile (`show_vp = false`).
### 11.3 Multi-Timeframe Behavior
- This version of the script is not internally multi-timeframe.
All logic (OB, DCA, Spring, Volume Profile) is computed on the active timeframe only.
- Practical workflow:
- Analyze overall structure and key zones on higher timeframes (4H / Daily).
- Use lower timeframes (15M / 1H) with the same tool for timing entries and exits.
## Conclusion
Mars Signals – Ultimate Institutional Suite v3.0 (Joker) is a multi-layer trading framework that unifies:
- Price structure (Order Blocks & FVG),
- Statistical behavior (Smart DCA via RSI + Bollinger),
- Volume distribution by price (Volume Profile with POC, HVN, LVN),
- Liquidity events (Wyckoff Spring),
into a single, coherent system driven by a transparent Confluence Scoring Engine.
The final output is presented in clear, actionable language:
> STRONG LONG / WEAK LONG / NEUTRAL / WEAK SHORT / STRONG SHORT
The system is designed to support professional decision-making, not to replace it.
Used together with strict risk management and disciplined execution,
Mars Signals – UIS v3.0 (Joker) can serve as a central reference manual and operational guide
for your trading workflow, from scalping to swing and investment positioning.
Adaptive Trend Trigger // VX-ATTAdaptive Trend Trigger // VX-ATT is a trend-following bias indicator that combines a baseline EMA with adaptive ATR bands and a momentum override layer.
Core idea:
The EMA defines the baseline trend.
ATR bands above/below the EMA mark zones where volatility is high enough to justify a directional push.
A break above the upper band switches the bias to Long.
A break below the lower band switches the bias to Short.
Strong candle bodies (measured vs. an average body size) can temporarily override the current bias when they close far above/below the EMA (momentum override).
What the indicator does:
Colors the background based on the active bias (Long/Short).
Plots EMA + ATR bands.
Marks strong momentum candles with arrows.
Provides alerts when the bias flips from Long → Short or Short → Long.
Typical use cases:
Trend filter for discretionary entries
Bias layer for strategies or additional indicators
Only trade in the direction of the active bias (e.g., favor Long setups in Long bias, avoid counter-trend scalps)
This is a simplified, free component extracted from my VX toolset (VX-ATT), designed as a clean, plug-and-play trend/bias layer you can combine with your own setups.
RSI MTF Table - 12 Pairs (1,5,15)
The relative strength index measures the speed and magnitude of an asset's recent price changes. Therefore, it is considered a momentum indicator in technical analysis. Essentially, the RSI is the ratio of the days an asset's value increases to decreases over a given period.
Generally speaking, if the RSI is around 50, we do not expect strong movements. RSI above 65 or below 35 are areas we expect. In this context, this chart and the general momentum in 1-5-15 minutes allow us to quickly determine the parity we will trade. It is useful for intraday trading and scalping.
ETH Short-Term VWAP+EMA/RSI (ATR Risk, <1h) (James Logan)ETH Short-Term VWAP + EMA / RSI Strategy (ATR-based Risk Control)
A short-term (< 1 hour) ETH trading system designed for intraday scalps and momentum swings on 5- to 15-minute charts.
It blends trend confirmation (EMA 50 / 200) with intrabar structure (EMA 21 pullback & VWAP filter) and RSI momentum triggers, managing exits dynamically through ATR-based stop, take-profit, and trailing stop targets.
Core logic
• Long when RSI crosses above the threshold within an up-trend (EMA 50 > EMA 200) and price is above VWAP.
• Short when RSI crosses below threshold within a down-trend (EMA 50 < EMA 200) and price is below VWAP.
• Optional pullback confirmation to the 21-EMA for cleaner entries.
• Risk defined by ATR-multiples for stop-loss, take-profit, and an adaptive trailing stop.
• Automatic flat-out exit after a set number of bars (time-based close).
Best use
• 5 min – 15 min ETH/USDT charts (Binance, Bybit, Coinbase, etc.)
• Works with both spot and perpetual data.
• Tune ATR and RSI thresholds per venue; defaults are balanced for 0.05 % per-side fees.
Key parameters
• ATR SL × 1.6 ATR TP × 2.2 ATR Trail × 2.0
• RSI 50 cross | EMA 50/200 trend filter | VWAP confirmation
• Default position sizing = USD-based (e.g. $1 000 per trade).
Notes
• All orders and exits are simulated at bar close; use 1-minute bar magnifier for finer fill modeling.
• No repainting—uses only confirmed bar data.
• Best validated with ≥ 200 trades and profit factor > 1.25 over multi-month backtests.
Trading Blueprint v7 Pro — VWAP-CVD, cPOC Trend MomentumTBv7 Pro is the advanced release of the Trading Blueprint framework — engineered for institutional-style intraday analysis that fuses VWAP location, CVD orderflow, composite profile bias, and momentum curvature into one cohesive system.
Core Framework
VWAP Structure → Adaptive mean anchored to session VWAP with ±1σ / ±2σ deviation envelopes for dynamic equilibrium detection.
vPOC per bar by ruckard ()
Anchored Volume Profile by DGT ()
CVD Orderflow Divergence → Smoothed delta histogram with fractal pivots identifying hidden absorption and exhaustion (patterns (Bull / Bear Div). Cumulative Volume Delta by AustrianTradingMachine )
cPOC Integration (2-Day Composite) by poopsnag (me :)→ Confirms true acceptance or rejection zones across sessions for precision bias alignment.
TMI (Trend Momentum Indicator by TradingRiot()) → Quantifies slope + mean crossover strength, providing actionable momentum confirmation (bullish / bearish support / divergence).
Bias Dashboard → Displays VWAP bias, numerical score, and dynamic color feedback for at-a-glance trade orientation.
Usage Context
Designed for professionals trading 15 m execution inside 1 h / 4 h context. Ideal for VWAP-cPOC location setups, reversion / continuation scalps, and orderflow confirmation using cumulative delta behavior.
🔧 Modules such as RSI / AO are pre-wired and easily activated for full Trading Blueprint confluence mapping.
chart Pattern & Candle sticks Strategy# **XAUUSD Pattern & Candle Strategy - Complete Description**
## **Overview**
This Pine Script indicator is a comprehensive multi-factor trading system specifically designed for **XAUUSD (Gold) scalping and swing trading**. It combines classical technical analysis methods including candlestick patterns, chart patterns, moving averages, and volume analysis to generate high-probability buy/sell signals with automatic stop-loss and take-profit levels.
***
## **Core Components**
### **1. Moving Average System (Triple MA)**
**Purpose:** Identifies trend direction and momentum
- **Fast MA (20-period)** - Short-term price action
- **Medium MA (50-period)** - Intermediate trend
- **Slow MA (200-period)** - Long-term trend direction
**How it works:**
- **Bullish alignment**: MA20 > MA50 > MA200 (all pointing up)
- **Bearish alignment**: MA20 < MA50 < MA200 (all pointing down)
- **Crossover signals**: When Fast MA crosses Medium MA, it triggers buy/sell signals
- **Choice of SMA or EMA**: Adjustable based on preference
**Visual indicators:**
- Blue line = Fast MA
- Orange line = Medium MA
- Light red line = Slow MA
- Green background tint = Bullish trend
- Red background tint = Bearish trend
---
### **2. Candlestick Pattern Recognition (13 Patterns)**
**Purpose:** Identifies reversal and continuation signals based on price action
#### **Bullish Patterns (Signal potential upward moves):**
1. **Hammer** 🔨
- Long lower wick (2x body size)
- Small body at top
- Indicates rejection of lower prices (buyers stepping in)
- Best at support levels
2. **Inverted Hammer**
- Long upper wick
- Small body at bottom
- Shows buying pressure despite initial selling
3. **Bullish Engulfing** 📈
- Green candle completely engulfs previous red candle
- Strong reversal signal
- Body must be 1.2x larger than previous
4. **Morning Star** ⭐
- 3-candle pattern
- Red candle → Small indecision candle → Large green candle
- Powerful reversal at bottoms
5. **Piercing Line** ⚡
- Green candle closes above 50% of previous red candle
- Indicates strong buying interest
6. **Bullish Marubozu**
- Almost no wicks (95% body)
- Very strong bullish momentum
- Body must be 1.3x average size
#### **Bearish Patterns (Signal potential downward moves):**
7. **Shooting Star** 💫
- Long upper wick
- Small body at bottom
- Indicates rejection of higher prices (sellers in control)
- Best at resistance levels
8. **Hanging Man**
- Similar to hammer but appears at top
- Warning of potential reversal down
9. **Bearish Engulfing** 📉
- Red candle completely engulfs previous green candle
- Strong reversal signal
10. **Evening Star** 🌙
- 3-candle pattern (opposite of Morning Star)
- Green → Small → Large red candle
- Powerful top reversal
11. **Dark Cloud Cover** ☁️
- Red candle closes below 50% of previous green candle
- Indicates strong selling pressure
12. **Bearish Marubozu**
- Almost no wicks, pure red body
- Very strong bearish momentum
#### **Neutral Pattern:**
13. **Doji**
- Open and close nearly equal (tiny body)
- Indicates indecision
- Often precedes major moves
**Detection Logic:**
- Compares body size, wick ratios, and position relative to previous candles
- Uses 14-period average body size as reference
- All patterns validated against volume confirmation
***
### **3. Chart Pattern Recognition**
**Purpose:** Identifies major support/resistance and reversal patterns
#### **Patterns Detected:**
**Double Bottom** 📊 (Bullish)
- Two lows at approximately same level
- Indicates strong support
- Breakout above neckline triggers buy signal
- Most reliable at major support zones
**Double Top** 📊 (Bearish)
- Two highs at approximately same level
- Indicates strong resistance
- Breakdown below neckline triggers sell signal
- Most reliable at major resistance zones
**Support & Resistance Levels**
- Automatically plots recent pivot highs (resistance)
- Automatically plots recent pivot lows (support)
- Uses 3-bar strength for validation
- Levels shown as dashed horizontal lines
**Price Action Patterns**
- **Uptrend detection**: Higher highs + higher lows
- **Downtrend detection**: Lower highs + lower lows
- Confirms overall market structure
***
### **4. Volume Analysis**
**Purpose:** Confirms signal strength and filters false signals
**Metrics tracked:**
- **Volume MA (20-period)**: Baseline average volume
- **High volume threshold**: 1.5x the volume average
- **Volume increase**: Current volume > previous 2 bars
**How it's used:**
- All buy/sell signals **require volume confirmation**
- High volume = institutional participation
- Low volume signals are filtered out
- Prevents whipsaw trades during quiet periods
**Visual indicator:**
- Dashboard shows "High" volume in orange when active
- "Normal" shown in gray during low volume
***
### **5. Signal Generation Logic**
**BUY SIGNALS triggered when ANY of these occur:**
1. **Candlestick + Volume**
- Bullish candle pattern detected
- High volume confirmation
- Price above Fast MA
2. **MA Crossover + Volume**
- Fast MA crosses above Medium MA
- High volume confirmation
3. **Double Bottom Breakout**
- Price breaks above support level
- Volume confirmation present
4. **Trend Continuation**
- Uptrend structure intact (higher highs/lows)
- All MAs in bullish alignment
- Price above Fast MA
- Volume confirmation
**SELL SIGNALS triggered when ANY of these occur:**
1. **Candlestick + Volume**
- Bearish candle pattern detected
- High volume confirmation
- Price below Fast MA
2. **MA Crossunder + Volume**
- Fast MA crosses below Medium MA
- High volume confirmation
3. **Double Top Breakdown**
- Price breaks below resistance level
- Volume confirmation present
4. **Trend Continuation**
- Downtrend structure intact (lower highs/lows)
- All MAs in bearish alignment
- Price below Fast MA
- Volume confirmation
***
### **6. Risk Management System**
**Automatic Stop Loss Calculation:**
- Based on ATR (Average True Range) - 14 periods
- **Formula**: Entry price ± (ATR × SL Multiplier)
- **Default multiplier**: 1.5 (adjustable)
- Adapts to market volatility automatically
**Automatic Take Profit Calculation:**
- **Formula**: Entry price ± (ATR × TP Multiplier)
- **Default multiplier**: 2.5 (adjustable)
- **Default Risk:Reward ratio**: 1:1.67
- Higher TP multiplier = more aggressive targets
**Position Management:**
- Tracks ONE position at a time (no pyramiding)
- Automatically closes position when:
- Stop loss is hit
- Take profit is reached
- Opposite MA crossover occurs
- Prevents revenge trading and over-leveraging
**Visual Representation:**
- **Red horizontal line** = Stop Loss level
- **Green horizontal line** = Take Profit level
- Lines remain on chart while position is active
- Automatically disappear when position closes
***
### **7. Visual Elements**
**On-Chart Displays:**
1. **Moving Average Lines**
- Fast MA (Blue, thick)
- Medium MA (Orange, thick)
- Slow MA (Red, thin)
2. **Support/Resistance**
- Green crosses = Support levels
- Red crosses = Resistance levels
3. **Buy/Sell Arrows**
- Large GREEN "BUY" label below bars
- Large RED "SELL" label above bars
4. **Pattern Labels** (Small markers)
- "Hammer", "Bull Engulf", "Morning Star" (green, below bars)
- "Shooting Star", "Bear Engulf", "Evening Star" (red, above bars)
- "Double Bottom" / "Double Top" (blue/orange)
5. **Signal Detail Labels** (Medium size)
- Shows signal reason (e.g., "Bullish Candle", "MA Cross Up")
- Displays Entry, SL, and TP prices
- Color-coded (green for long, red for short)
6. **Background Coloring**
- Light green tint = Bullish MA alignment
- Light red tint = Bearish MA alignment
***
### **8. Information Dashboard**
**Top-right corner table showing:**
| Metric | Description |
|--------|-------------|
| **Position** | Current trade status (LONG/SHORT/None) |
| **MA Trend** | Overall trend direction (Bullish/Bearish/Neutral) |
| **Volume** | Current volume status (High/Normal) |
| **Pattern** | Last detected candlestick pattern |
| **ATR** | Current volatility measurement |
**Purpose:**
- Quick at-a-glance market assessment
- Real-time position tracking
- No need to check multiple indicators
***
### **9. Alert System**
**Complete alert coverage for:**
✅ **Entry Alerts**
- "Buy Signal" - Triggers when buy conditions met
- "Sell Signal" - Triggers when sell conditions met
✅ **Exit Alerts**
- "Long TP Hit" - Take profit reached on long position
- "Long SL Hit" - Stop loss triggered on long position
- "Short TP Hit" - Take profit reached on short position
- "Short SL Hit" - Stop loss triggered on short position
**How to use:**
1. Click "Create Alert" button
2. Select desired alert from dropdown
3. Set notification method (popup, email, SMS, webhook)
4. Never miss a trade opportunity
***
## **Recommended Settings**
### **For Scalping (Quick trades):**
- **Timeframe**: 5-minute
- **Fast MA**: 9
- **Medium MA**: 21
- **Slow MA**: 50
- **SL Multiplier**: 1.0
- **TP Multiplier**: 2.0
- **Volume Threshold**: 1.5x
### **For Swing Trading (Longer holds):**
- **Timeframe**: 1-hour or 4-hour
- **Fast MA**: 20
- **Medium MA**: 50
- **Slow MA**: 200
- **SL Multiplier**: 2.0
- **TP Multiplier**: 3.0
- **Volume Threshold**: 1.3x
### **Best Trading Hours for XAUUSD:**
- **Asian Session**: 00:00 - 08:00 GMT (lower volatility)
- **London Session**: 08:00 - 16:00 GMT (high volatility) ⭐
- **New York Session**: 13:00 - 21:00 GMT (highest volume) ⭐
- **London-NY Overlap**: 13:00 - 16:00 GMT (BEST for scalping) 🔥
***
## **How to Use This Strategy**
### **Step 1: Setup**
1. Open TradingView
2. Load XAUUSD chart
3. Select timeframe (5m, 15m, 1H, or 4H)
4. Add indicator from Pine Editor
5. Adjust settings based on your trading style
### **Step 2: Wait for Signals**
- Watch for GREEN "BUY" or RED "SELL" labels
- Check the signal reason in the detail label
- Verify dashboard shows favorable conditions
- Confirm volume is "High" (not required but preferred)
### **Step 3: Enter Trade**
- Enter at market or limit order near signal price
- Note the displayed Entry, SL, and TP prices
- Set your broker's SL/TP to match indicator levels
### **Step 4: Manage Position**
- Watch for SL/TP lines on chart
- Monitor dashboard for trend changes
- Exit manually if opposite MA crossover occurs
- Let SL/TP do their job (don't move them!)
### **Step 5: Review & Learn**
- Track win rate over 20+ trades
- Adjust multipliers if needed
- Note which patterns work best for you
- Refine entry timing
***
## **Key Advantages**
✅ **Multi-confirmation approach** - Reduces false signals significantly
✅ **Automatic risk management** - No manual calculation needed
✅ **Adapts to volatility** - ATR-based SL/TP adjusts to market conditions
✅ **Volume filtered** - Ensures institutional participation
✅ **Visual clarity** - Easy to understand at a glance
✅ **Complete alert system** - Never miss opportunities
✅ **Pattern education** - Learn patterns as they appear
✅ **Works on all timeframes** - Scalping to swing trading
***
## **Limitations & Considerations**
⚠️ **Not a holy grail** - No strategy wins 100% of trades
⚠️ **Requires practice** - Demo trade first to understand signals
⚠️ **Market conditions matter** - Works best in trending or volatile markets
⚠️ **News events** - Avoid trading during major economic releases
⚠️ **Slippage on 5m** - Fast markets may have execution delays
⚠️ **Pattern subjectivity** - Some patterns may trigger differently than expected
***
## **Risk Management Rules**
1. **Never risk more than 1-2% per trade**
2. **Maximum 3 positions per day** (avoid overtrading)
3. **Don't trade during major news** (NFP, FOMC, etc.)
4. **Use proper position sizing** (0.01 lot per $100 for micro accounts)
5. **Keep trade journal** (track patterns, win rate, mistakes)
6. **Stop trading after 3 consecutive losses** (psychological reset)
7. **Don't move stop loss further away** (accept losses)
8. **Take partial profits** at 1:1 R:R if desired
***
## **Expected Performance**
**Realistic expectations:**
- **Win rate**: 50-65% (depending on market conditions and timeframe)
- **Risk:Reward**: 1:1.67 default (adjustable to 1:2 or 1:3)
- **Signals per day**: 3-8 on 5m, 1-3 on 1H
- **Best months**: High volatility periods (news events, economic uncertainty)
- **Drawdowns**: Expect 3-5 losing trades in a row occasionally
***
## **Customization Options**
All inputs are adjustable in settings panel:
**Moving Averages:**
- Type (SMA or EMA)
- All three period lengths
**Volume:**
- Volume MA length
- High volume multiplier threshold
**Chart Patterns:**
- Pattern strength (bars for pivot detection)
- Show/hide pattern labels
**Risk Management:**
- ATR period
- Stop loss multiplier
- Take profit multiplier
**Display:**
- Toggle pattern labels
- Customize colors (in code)
***
## **Conclusion**
This is a **professional-grade, multi-factor trading system** that combines the best of classical technical analysis with modern risk management. It's designed to give clear, actionable signals while automatically handling the complex calculations of stop loss and take profit levels.
**Best suited for traders who:**
- Understand basic technical analysis
- Can follow rules consistently
- Prefer systematic approach over gut feeling
- Want visual confirmation before entering trades
- Value proper risk management
**Start with demo trading** for at least 20-30 trades to understand how the signals work in different market conditions. Once comfortable and profitable on demo, transition to live trading with minimal risk per trade.
Happy trading! 📈🎯
MTF Multi EMA - IntradayMTF Multi EMA – Intraday
Purpose:
To quickly analyze trend direction and alignment across multiple timeframes (1m, 3m, 5m, 15m, 30m, and 60m) using fast and slow EMAs for each timeframe — and combine them into a simple “stack score” for easy visual decision-making. The script is tuned for Intraday Trading indicator by default.
Concept
Each timeframe (TF) — like 1m, 3m, 5m, etc. — has two EMAs:
A fast EMA (shorter length)
A slow EMA (longer length)
When the fast EMA > slow EMA, that timeframe is bullish.
When the fast EMA < slow EMA, that timeframe is bearish.
By combining multiple timeframes together, the indicator helps you:
Identify when all trends align bullishly (strong buy bias)
Identify when all trends align bearishly (strong sell bias)
Stay out during mixed or sideways phases
Inputs Explained
Setting Description
1m / 3m / 5m / 15m / 30m / 60m EMA Lengths Controls the EMA period for each timeframe’s fast and slow EMAs.
Fast EMA Color Color for all fast EMAs plotted on chart.
Slow EMA Color Color for all slow EMAs plotted on chart.
Use Smooth Interpolation Ensures smoother plots when merging higher TF data into a smaller chart (recommended ON).
Show Toggle visibility of each timeframe’s EMAs.
Table Position Lets you move the mini dashboard to any chart corner.
Stack Score
The Stack Score measures how many timeframes are bullish vs bearish:
Stack Score Meaning
+6 All timeframes bullish → Strong Uptrend
+3 to +5 Majority bullish → Bullish Bias
0 Neutral / Mixed → Sideways Market
−3 to −5 Majority bearish → Bearish Bias
−6 All timeframes bearish → Strong Downtrend
Table Display
At the chosen chart corner, you’ll see:
TF Direction
1m 🟢 B (Bullish) / 🔴 S (Bearish)
3m 🟢 B (Bullish) / 🔴 S (Bearish)
5m 🟢 B (Bullish) / 🔴 S (Bearish)
15m 🟢 B (Bullish) / 🔴 S (Bearish)
30m 🟢 B (Bullish) / 🔴 S (Bearish)
60m 🟢 B (Bullish) / 🔴 S (Bearish)
Score Final alignment score (color-coded)
Color meanings:
🟢 Green cell = bullish for that TF
🔴 Red cell = bearish for that TF
The Score cell background color changes with strength:
Bright green → strong bull
Yellow → neutral
Red / Maroon → strong bear
How to Use for Trading (Intraday NIFTY 5m)
Recommended Chart: 5-minute timeframe on NIFTY Futures or major index stocks.
🔹 1. Identify Trend Alignment
When Score ≥ +3 → Market bias is bullish.
→ Look for long entries (buy breakouts or EMA retests).
When Score ≤ −3 → Market bias is bearish.
→ Look for short entries (sell breakdowns or retests).
When Score is between −2 and +2 → Trend is mixed.
→ Best to wait — avoid trading in choppy conditions.
🔹 2. Combine with Price Action
Use it with:
Trendline breaks or retests
Candle confirmation (e.g. bullish engulfing or rejection)
Volume surge
Example:
On NIFTY 5m — if score = +5, price breaks above a descending trendline, and 1m–15m EMAs are all rising → strong long signal.
🔹 3. Avoid Conflicts
If lower timeframes (1m/3m/5m) are bullish but higher ones (30m/60m) are bearish,
→ Trend is short-term bullish but larger bias is down — scalps only, not swings.
Optional Alerts
If you add alert conditions (as suggested earlier):
“Strong Bullish Alignment” triggers when score ≥ +5
“Strong Bearish Alignment” triggers when score ≤ −5
This gives you early alerts when full trend alignment occurs — ideal for breakout setups.
Some more Tips
Use 5m or 15m chart as your main view.
Use Stack Score as a trend filter — trade with it, not against it.
Combine with Breakout + Retest strategy or Trendline color-coded system you’re building.
In sideways days (score near 0), reduce risk or skip trades.
Auto Fibonacci LevelsAuto Fibonacci Momentum Zones with Visible Range Table
Overview and Originality
The Auto Fibonacci Momentum Zones indicator offers a streamlined, static overlay of Fibonacci retracement levels inspired by extreme RSI momentum thresholds, enhanced with a dynamic table displaying the high and low of the currently visible chart range. This isn't a repackaged RSI oscillator or basic Fib drawer—common in TradingView's library—but a purposeful fusion of geometric harmony (Fibonacci ratios) with momentum psychology (RSI extremes at 35/85), projected as fixed horizontal reference lines on the price chart. The addition of the visible range table, powered by PineCoders' VisibleChart library, provides real-time context for the chart's current view, enabling traders to quickly assess range compression or expansion relative to these zones.
This script's originality stems from its "static momentum mapping": by hardcoding Fib levels on a dynamic chart, it creates universal psychological support/resistance lines that transcend specific assets or timeframes.
Unlike dynamic Fib tools that auto-adjust to price swings (risking noise in ranging markets) or standalone RSI plots (confined to panes), this delivers clean, bias-adjustable overlays for confluence analysis. The visible range table justifies the library integration—it's not a gratuitous add-on but a complementary tool that quantifies the "screen real estate" of price action, helping users correlate Fib touches with actual volatility. Drawn from original code (no auto-generation or public templates), it builds TradingView's body of knowledge by simplifying multi-tool workflows into one indicator, ideal for discretionary traders who value visual efficiency over algorithmic complexity.
How It Works: Underlying Concepts
Fibonacci retracements, derived from the Fibonacci sequence and the golden ratio (≈0.618), identify potential reversal points based on the idea that markets retrace prior moves in predictable proportions: shallow (23.6%, 38.2%), mid (50%), and deep (61.8%, 78.6%).
Adjustable Outputs
1. The "Invert Fibs" toggle (default: true) for bearish/topping bias, can be flipped aligning with trend context.
2. Fibonacci Levels: Seven semi-transparent horizontal lines are drawn using `hline()`:
- 0.0 at high (gray).
- 0.236: high - (range × 0.236) (light cyan, shallow pullback).
- 0.382: high - (range × 0.382) (teal, common retracement).
- 0.5: midpoint average (green, equilibrium).
- 0.618: high - (range × 0.618) (amber, golden pocket for reversals).
- 0.786: high - (range × 0.786) (orange, deep support).
- 1.0 at low (gray).
Colors progress from cool (shallow) to warm (deep) for intuitive scanning.
3. Optional Fib Labels: Right-edge text labels (e.g., "0.618") appear only if enabled, positioned at the last bar + offset for non-cluttering visibility.
4. Visible Range Table: Leveraging the VisibleChart library's `visible.high()` and `visible.low()` functions, a compact 2x2 table (top-right corner) updates on the last bar to show the extrema of bars currently in view. This mashup enhances utility: Fib zones provide fixed anchors, while the table's dynamic values reveal if price is "pinned" to a zone (e.g., visible high hugging 0.382 signals resistance). The library is invoked sparingly for performance, adding value by bridging static geometry with viewport-aware data—unavailable in built-ins without custom code.
How to Use It
1. Setup:
Add to any chart (e.g., 15M for scalps, Daily for swings). As an overlay, lines appear directly on price candles—adjust chart scaling if needed.
2. Input Tweaks:
Invert Fibs: Enable for downtrends (85 top), disable for uptrends (35 bottom).
Show Fibs: Toggle labels for ratio callouts (off for clean charts).
Show Table: Display/hide the visible high/low summary (red for high, green for low, formatted to 2 decimals).
3. Trading Application:
Zone Confluence: Seek price reactions at each fibonacci level—e.g., a doji at 0.618 + rising volume suggests entry; use 0.0/1.0 as invalidation.
Range Context: Check the table: If visible high/low spans <20% of the Fib arc (e.g., both near 0.5), anticipate breakout; wider spans signal consolidation.
Multi-Timeframe: Overlay on higher TF for bias, lower for precision—e.g., Daily Fibs guide 1H entries.
Enhancements: Pair with volume or candlesticks; set alerts on line crosses via TradingView's built-in tools. Backtest on your symbols to validate (e.g., equities favor 0.382, forex the 0.786).
This indicator automates advanced Fibonacci synthesis dynamically, eliminating manual measurement and calculations.
published by ozzy_livin
Grok's xAI Signal (GXS) Indicator for BTC V6Grok's xAI Signal (GXS) Indicator: A Simple Guide
Imagine trying to decide if Bitcoin is a "buy," "sell," or "wait" without staring at 10 different charts. The GXS Indicator does that for you—it's like a smart dashboard for BTC traders, overlaying signals right on your price chart. It boils down complex market clues into one easy score (from -1 "super bearish" to +1 "super bullish") and flashes green/red arrows or shaded zones when action's needed. No fancy math overload; just clear visuals like tiny triangles for trades, colored clouds for trends, and a bottom "mood bar" (green=up vibe, red=down, gray=meh).
At its core, GXS mixes three big-picture checks:
Price Momentum (50% weight): Quick scans of RSI (overbought/oversold vibes), MACD (speed of ups/downs), EMAs (is price riding the trend wave?), and Bollinger Bands (is the market squeezing for a breakout?). This catches short-term "hot or not" energy.
Network Health (30% weight): A simple "NVT" hack using trading volume vs. price to spot if BTC feels undervalued (buy hint) or overhyped (sell warning). It's like checking if the crowd's too excited or chill.
Trend Strength (20% weight): ADX filter ensures signals only fire in "trending" markets (not choppy sideways noise), plus a MACD boost for extra momentum nudge.
Why this approach? BTC's wild—pure price charts give false alarms in flat times, while ignoring volume/network ignores the "why" behind moves. GXS blends old-school TA (reliable for patterns) with on-chain smarts (crypto-specific "under the hood" data) and a trend gate (skips 70% of bad trades). It's conservative: Signals need the score to cross ±0.08 and a strong trend, reducing noise for swing/position traders. Result? Fewer emotional guesses, more "wait for confirmation" patience—perfect for volatile assets like BTC where hype kills.
Quick Tips to Tweak for Better Results
Start with defaults, then experiment on historical charts (backtest via TradingView's strategy tester if pairing with one):
Fewer False Signals: Bump thresholds to ±0.15 (buy/sell)—trades only on stronger conviction, cutting whipsaws by 20-30% in choppy markets. Or raise ADX thresh to 28 for "only big trends."
Faster/Slower Response: Shorten EMAs (e.g., 5/21) or RSI (10) for quicker scalps; lengthen (12/50) for swing holds. Test on 4H/daily BTC.
Volume Sensitivity: If NVT flips too often, extend its length to 20—smooths on-chain noise in bull runs.
Visual Polish: Crank cloud opacity to 80% for subtler fills; toggle off EMAs if they clutter. Enable table for score breakdowns during live trades.
Risk Tip: Always pair with stops (e.g., 2-3% below signals). On BTC, tweak in bull markets (looser thresh) vs. bears (tighter).
In short, GXS is your BTC "sixth sense"—balanced, not black-box. Tweak small, track win rate, and let trends lead. Happy trading!
Kalman VWAP Filter [BackQuant]Kalman VWAP Filter
A precision-engineered price estimator that fuses Kalman filtering with the Volume-Weighted Average Price (VWAP) to create a smooth, adaptive representation of fair value. This hybrid model intelligently balances responsiveness and stability, tracking trend shifts with minimal noise while maintaining a statistically grounded link to volume distribution.
If you would like to see my original Kalman Filter, please find it here:
Concept overview
The Kalman VWAP Filter is built on two core ideas from quantitative finance and control theory:
Kalman filtering — a recursive Bayesian estimator used to infer the true underlying state of a noisy system (in this case, fair price).
VWAP anchoring — a dynamic reference that weights price by traded volume, representing where the majority of transactions have occurred.
By merging these concepts, the filter produces a line that behaves like a "smart moving average": smooth when noise is high, fast when markets trend, and self-adjusting based on both market structure and user-defined noise parameters.
How it works
Measurement blend : Combines the chosen Price Source (e.g., close or hlc3) with either a Session VWAP or a Rolling VWAP baseline. The VWAP Weight input controls how much the filter trusts traded volume versus price movement.
Kalman recursion : Each bar updates an internal "state estimate" using the Kalman gain, which determines how much to trust new observations vs. the prior state.
Noise parameters :
Process Noise controls agility — higher values make the filter more responsive but also more volatile.
Measurement Noise controls smoothness — higher values make it steadier but slower to adapt.
Filter order (N) : Defines how many parallel state estimates are used. Larger orders yield smoother output by layering multiple one-dimensional Kalman passes.
Final output : A refined price trajectory that captures VWAP-adjusted fair value while dynamically adjusting to real-time volatility and order flow.
Why this matters
Most smoothing techniques (EMA, SMA, Hull) trade off lag for smoothness. Kalman filtering, however, adaptively rebalances that tradeoff each bar using probabilistic weighting, allowing it to follow market state changes more efficiently. Anchoring it to VWAP integrates microstructure context — capturing where liquidity truly lies rather than only where price moves.
Use cases
Trend tracking : Color-coded candle painting highlights shifts in slope direction, revealing early trend transitions.
Fair value mapping : The line represents a continuously updated equilibrium price between raw price action and VWAP flow.
Adaptive moving average replacement : Outperforms static MAs in variable volatility regimes by self-adjusting smoothness.
Execution & reversion logic : When price diverges from the Kalman VWAP, it may indicate short-term imbalance or overextension relative to volume-adjusted fair value.
Cross-signal framework : Use with standard VWAP or other filters to identify convergence or divergence between liquidity-weighted and state-estimated prices.
Parameter guidance
Process Noise : 0.01–0.05 for swing traders, 0.1–0.2 for intraday scalping.
Measurement Noise : 2–5 for normal use, 8+ for very smooth tracking.
VWAP Weight : 0.2–0.4 balances both price and VWAP influence; 1.0 locks output directly to VWAP dynamics.
Filter Order (N) : 3–5 for reactive short-term filters; 8–10 for smoother institutional-style baselines.
Interpretation
When price > Kalman VWAP and slope is positive → bullish pressure; buyers dominate above fair value.
When price < Kalman VWAP and slope is negative → bearish pressure; sellers dominate below fair value.
Convergence of price and Kalman VWAP often signals equilibrium; strong divergence suggests imbalance.
Crosses between Kalman VWAP and the base VWAP can hint at shifts in short-term vs. long-term liquidity control.
Summary
The Kalman VWAP Filter blends statistical estimation with market microstructure awareness, offering a refined alternative to static smoothing indicators. It adapts in real time to volatility and order flow, helping traders visualize balance, transition, and momentum through a lens of probabilistic fair value rather than simple price averaging.
Ehlers Autocorrelation Periodogram (EACP)# EACP: Ehlers Autocorrelation Periodogram
## Overview and Purpose
Developed by John F. Ehlers (Technical Analysis of Stocks & Commodities, Sep 2016), the Ehlers Autocorrelation Periodogram (EACP) estimates the dominant market cycle by projecting normalized autocorrelation coefficients onto Fourier basis functions. The indicator blends a roofing filter (high-pass + Super Smoother) with a compact periodogram, yielding low-latency dominant cycle detection suitable for adaptive trading systems. Compared with Hilbert-based methods, the autocorrelation approach resists aliasing and maintains stability in noisy price data.
EACP answers a central question in cycle analysis: “What period currently dominates the market?” It prioritizes spectral power concentration, enabling downstream tools (adaptive moving averages, oscillators) to adjust responsively without the lag present in sliding-window techniques.
## Core Concepts
* **Roofing Filter:** High-pass plus Super Smoother combination removes low-frequency drift while limiting aliasing.
* **Pearson Autocorrelation:** Computes normalized lag correlation to remove amplitude bias.
* **Fourier Projection:** Sums cosine and sine terms of autocorrelation to approximate spectral energy.
* **Gain Normalization:** Automatic gain control prevents stale peaks from dominating power estimates.
* **Warmup Compensation:** Exponential correction guarantees valid output from the very first bar.
## Implementation Notes
**This is not a strict implementation of the TASC September 2016 specification.** It is a more advanced evolution combining the core 2016 concept with techniques Ehlers introduced later. The fundamental Wiener-Khinchin theorem (power spectral density = Fourier transform of autocorrelation) is correctly implemented, but key implementation details differ:
### Differences from Original 2016 TASC Article
1. **Dominant Cycle Calculation:**
- **2016 TASC:** Uses peak-finding to identify the period with maximum power
- **This Implementation:** Uses Center of Gravity (COG) weighted average over bins where power ≥ 0.5
- **Rationale:** COG provides smoother transitions and reduces susceptibility to noise spikes
2. **Roofing Filter:**
- **2016 TASC:** Simple first-order high-pass filter
- **This Implementation:** Canonical 2-pole high-pass with √2 factor followed by Super Smoother bandpass
- **Formula:** `hp := (1-α/2)²·(p-2p +p ) + 2(1-α)·hp - (1-α)²·hp `
- **Rationale:** Evolved filtering provides better attenuation and phase characteristics
3. **Normalized Power Reporting:**
- **2016 TASC:** Reports peak power across all periods
- **This Implementation:** Reports power specifically at the dominant period
- **Rationale:** Provides more meaningful correlation between dominant cycle strength and normalized power
4. **Automatic Gain Control (AGC):**
- Uses decay factor `K = 10^(-0.15/diff)` where `diff = maxPeriod - minPeriod`
- Ensures K < 1 for proper exponential decay of historical peaks
- Prevents stale peaks from dominating current power estimates
### Performance Characteristics
- **Complexity:** O(N²) where N = (maxPeriod - minPeriod)
- **Implementation:** Uses `var` arrays with native PineScript historical operator ` `
- **Warmup:** Exponential compensation (§2 pattern) ensures valid output from bar 1
### Related Implementations
This refined approach aligns with:
- TradingView TASC 2025.02 implementation by blackcat1402
- Modern Ehlers cycle analysis techniques post-2016
- Evolved filtering methods from *Cycle Analytics for Traders*
The code is mathematically sound and production-ready, representing a refined version of the autocorrelation periodogram concept rather than a literal translation of the 2016 article.
## Common Settings and Parameters
| Parameter | Default | Function | When to Adjust |
|-----------|---------|----------|---------------|
| Min Period | 8 | Lower bound of candidate cycles | Increase to ignore microstructure noise; decrease for scalping. |
| Max Period | 48 | Upper bound of candidate cycles | Increase for swing analysis; decrease for intraday focus. |
| Autocorrelation Length | 3 | Averaging window for Pearson correlation | Set to 0 to match lag, or enlarge for smoother spectra. |
| Enhance Resolution | true | Cubic emphasis to highlight peaks | Disable when a flatter spectrum is desired for diagnostics. |
**Pro Tip:** Keep `(maxPeriod - minPeriod)` ≤ 64 to control $O(n^2)$ inner loops and maintain responsiveness on lower timeframes.
## Calculation and Mathematical Foundation
**Explanation:**
1. Apply roofing filter to `source` using coefficients $\alpha_1$, $a_1$, $b_1$, $c_1$, $c_2$, $c_3$.
2. For each lag $L$ compute Pearson correlation $r_L$ over window $M$ (default $L$).
3. For each period $p$, project onto Fourier basis:
$C_p=\sum_{n=2}^{N} r_n \cos\left(\frac{2\pi n}{p}\right)$ and $S_p=\sum_{n=2}^{N} r_n \sin\left(\frac{2\pi n}{p}\right)$.
4. Power $P_p=C_p^2+S_p^2$, smoothed then normalized via adaptive peak tracking.
5. Dominant cycle $D=\frac{\sum p\,\tilde P_p}{\sum \tilde P_p}$ over bins where $\tilde P_p≥0.5$, warmup-compensated.
**Technical formula:**
```
Step 1: hp_t = ((1-α₁)/2)(src_t - src_{t-1}) + α₁ hp_{t-1}
Step 2: filt_t = c₁(hp_t + hp_{t-1})/2 + c₂ filt_{t-1} + c₃ filt_{t-2}
Step 3: r_L = (M Σxy - Σx Σy) / √
Step 4: P_p = (Σ_{n=2}^{N} r_n cos(2πn/p))² + (Σ_{n=2}^{N} r_n sin(2πn/p))²
Step 5: D = Σ_{p∈Ω} p · ĤP_p / Σ_{p∈Ω} ĤP_p with warmup compensation
```
> 🔍 **Technical Note:** Warmup uses $c = 1 / (1 - (1 - \alpha)^{k})$ to scale early-cycle estimates, preventing low values during initial bars.
## Interpretation Details
- **Primary Dominant Cycle:**
- High $D$ (e.g., > 30) implies slow regime; adaptive MAs should lengthen.
- Low $D$ (e.g., < 15) signals rapid oscillations; shorten lookback windows.
- **Normalized Power:**
- Values > 0.8 indicate strong cycle confidence; consider cyclical strategies.
- Values < 0.3 warn of flat spectra; favor trend or volatility approaches.
- **Regime Shifts:**
- Rapid drop in $D$ alongside rising power often precedes volatility expansion.
- Divergence between $D$ and price swings may highlight upcoming breakouts.
## Limitations and Considerations
- **Spectral Leakage:** Limited lag range can smear peaks during abrupt volatility shifts.
- **O(n²) Segment:** Although constrained (≤ 60 loops), wide period spans increase computation.
- **Stationarity Assumption:** Autocorrelation presumes quasi-stationary cycles; regime changes reduce accuracy.
- **Latency in Noise:** Even with roofing, extremely noisy assets may require higher `avgLength`.
- **Downtrend Bias:** Negative trends may clip high-pass output; ensure preprocessing retains signal.
## References
* Ehlers, J. F. (2016). “Past Market Cycles.” *Technical Analysis of Stocks & Commodities*, 34(9), 52-55.
* Thinkorswim Learning Center. “Ehlers Autocorrelation Periodogram.”
* Fab MacCallini. “autocorrPeriodogram.R.” GitHub repository.
* QuantStrat TradeR Blog. “Autocorrelation Periodogram for Adaptive Lookbacks.”
* TradingView Script by blackcat1402. “Ehlers Autocorrelation Periodogram (Updated).”
WorldCup Dashboard + Institutional Sessions© 2025 NewMeta™ — Educational use only.
# Full, Premium Description
## WorldCup Dashboard + Institutional Sessions
**A trade-ready, intraday framework that combines market structure, real flow, and institutional timing.**
This toolkit fuses **Institutional Sessions** with a **price–volume decision engine** so you can see *who is active*, *where value sits*, and *whether the drive is real*. You get: **CVD/Delta**, volume-weighted **Momentum**, **Aggression** spikes, **FVG (MTF)** with nearest side, **Daily Volume Profile (VAH/POC/VAL)**, **ATR regime**, a **24h position gauge**, classic **candle patterns**, IBH/IBL + **first-hour “true close”** lines, and a **10-vote confluence scoreboard**—all in one view.
---
## What’s inside (and how to trade it)
### 🌍 Institutional Sessions (Sydney • Tokyo • London • New York)
* Session boxes + a highlighted **first hour**.
* Plots the **true close** (first-hour close) as a running line with a label.
**Use:** Many desks anchor risk to this print. Above = bullish bias; below = bearish. **IBH/IBL** breaks during London/NY carry the most signal.
### 📊 CVD / Delta (Flow)
* Net buyer vs seller pressure with smooth trend state.
**Use:** **Rising CVD + acceptance above mid/POC** confirms continuation. Bearish price + rising CVD = caution (possible absorption).
### ⚡ Volume-Weighted Momentum
* Momentum adjusted by participation quality (volume).
**Use:** Momentum>MA and >0 → trend drive is “real”; <0 and falling → distribution risk.
### 🔥 Aggression Detector
* ROC × normalized volume × wick factor to flag **forceful** candles.
**Use:** On spikes, avoid fading blindly—wait for pullbacks into **aligned FVG** or for aggression to cool.
### 🟦🟪 Fair Value Gaps (with MTF)
* Detects up to 3 recent FVGs and marks the **nearest** side to price.
**Use:** Trend pullbacks into **bullish FVG** for longs; bounces into **bearish FVG** for shorts. Optional threshold to filter weak gaps.
### 🧭 24h Gauge (positioning)
* Shows current price across the 24h low⇢high with a mid reference.
**Use:** Above mid and pushing upper third = momentum continuation setups; below mid = sell the rips bias.
### 🧱 Daily Volume Profile (manual per day)
* **VAH / POC / VAL** derived from discretized rows.
**Use:** **POC below** supports longs; **POC above** caps rallies. Fade VAH/VAL in ranges; treat them as break/hold levels in trends.
### 📈 ATR Regime
* **ATR vs ATR-avg** with direction and regime flag (**HIGH / NORMAL / LOW**).
**Use:** HIGH ⇒ give trades room & favor trend following. LOW ⇒ fade edges, scale targets.
### 🕯️ Candle Patterns (contextual, not standalone)
* Engulfings, Morning/Evening Star, 3 Soldiers/Crows, Harami, Hammer/Shooting Star, Double Top/Bottom.
**Use:** Only with session + flow + momentum alignment.
### 🤝 Price–Volume Classification
* Labels each bar as **continuation**, **exhaustion**, **distribution**, or **healthy pullback**.
**Use:** Align continuation reads with trend; treat “Price↑ + Vol↓” as a caution flag.
### 🧪 Confluence Scoreboard & B/S Meter
* Ten elements vote: 🔵 bull, ⚪ neutral, 🟣 bear.
**Use:** Execution filter—take setups when the board’s skew matches your trade direction.
---
## Playbooks (actionable)
**Trend Pullback (Long)**
1. London/NY active, Momentum↑, CVD↑, price above 24h mid & POC.
2. Pullback into **nearest bullish FVG**.
3. Invalidate under FVG low or **true-close** line.
4. Targets: IBH → VAH → 24h high.
**Range Fade (Short)**
1. Asia/quiet regime, **Price↑ + Vol↓** into **VAH**, ATR low.
2. Nearest FVG bearish or scoreboard skew bearish.
3. Invalidate above VAH/IBH.
4. Targets: POC → VAL.
**News/Impulse**
Aggression spike? Don’t chase. Let it pull back into the aligned FVG; require CVD/Momentum agreement before entry.
---
## Alerts (included)
* **Bull/Bear Confluence ≥ 7/10**
* **Intraday Target Achieved** / **Daily Target Achieved**
* **Session True-Close Retests** (Sydney/Tokyo/London/NY)
*(Keep alerts “Once per bar” unless you specifically want intrabar triggers.)*
---
## Setup Tips
* **UTC**: Choose the reference that matches how you track sessions (default UTC+2).
* **Volume threshold**: 2.0× is a strong baseline; raise for noisy alts, lower for majors.
* **CVD smoothing**: 14–24 for scalps; 24–34 for slower markets.
* **ATR lengths**: Keep defaults unless your asset has a persistent regime shift.
---
## Why this framework?
Because **timing (sessions)**, **truth (flow)**, and **location (value/FVG)** together beat any single signal. You get *who is trading*, *how strong the push is*, and *where risk lives*—on one screen—so execution is faster and cleaner.
---
**Disclaimer**: Educational use only. Not financial advice. Markets are risky—backtest and size responsibly.
Pivot Regime Anchored VWAP [CHE] Pivot Regime Anchored VWAP — Detects body-based pivot regimes to classify swing highs and lows, anchoring volume-weighted average price lines directly at higher highs and lower lows for adaptive reference levels.
Summary
This indicator identifies shifts between top and bottom regimes through breakouts in candle body highs and lows, labeling swing points as higher highs, lower highs, lower lows, or higher lows. It then draws anchored volume-weighted average price lines starting from the most recent higher high and lower low, providing dynamic support and resistance that evolve with volume flow. These anchored lines differ from standard volume-weighted averages by resetting only at confirmed swing extremes, reducing noise in ranging markets while highlighting momentum shifts in trends.
Motivation: Why this design?
Traders often struggle with static reference lines that fail to adapt to changing market structures, leading to false breaks in volatile conditions or missed continuations in trends. By anchoring volume-weighted average price calculations to body pivot regimes—specifically at higher highs for resistance and lower lows for support—this design creates reference levels tied directly to price structure extremes. This approach addresses the problem of generic moving averages lagging behind swing confirmations, offering a more context-aware tool for intraday or swing trading.
What’s different vs. standard approaches?
- Baseline reference: Traditional volume-weighted average price indicators compute a running total from session start or fixed periods, often ignoring price structure.
- Architecture differences:
- Regime detection via body breakout logic switches between high and low focus dynamically.
- Anchoring limited to confirmed higher highs and lower lows, with historical recalculation for accurate line drawing.
- Polyline rendering rebuilds only on the last bar to manage performance.
- Practical effect: Charts show fewer, more meaningful lines that start at swing points, making it easier to spot confluences with structure breaks rather than cluttered overlays from continuous calculations.
How it works (technical)
The indicator first calculates the maximum and minimum of each candle's open and close to define body highs and lows. It then scans a lookback window for the highest body high and lowest body low. A top regime triggers when the body high from the lookback period exceeds the window's highest, and a bottom regime when the body low falls below the window's lowest. These regime shifts confirm pivots only when crossing from one state to the other.
For top pivots, it compares the new body high against the previous swing high: if greater, it marks a higher high and anchors a new line; otherwise, a lower high. The same logic applies inversely for bottom pivots. Anchored lines use cumulative price-volume products and volumes from the anchor bar onward, subtracting prior cumulatives to isolate the segment. On pivot confirmation, it loops backward from the current bar to the anchor, computing and storing points for the line. New points append as bars advance, ensuring the line reflects ongoing volume weighting.
Initialization uses persistent variables to track the last swing values and anchor bars, starting with neutral states. Data flows from regime detection to pivot classification, then to anchoring and point accumulation, with lines rendered globally on the final bar.
Parameter Guide
Pivot Length — Controls the lookback window for detecting body breakouts, influencing pivot frequency and sensitivity to recent action. Shorter values catch more pivots in choppy conditions; longer smooths for major swings. Default: 30 (bars). Trade-offs/Tips: Min 1; for intraday, try 10–20 to reduce lag but watch for noise; on daily, 50+ for stability.
Show Pivot Labels — Toggles display of text markers at swing points, aiding quick identification of higher highs, lower highs, lower lows, or higher lows. Default: true. Trade-offs/Tips: Disable in multi-indicator setups to declutter; useful for backtesting structure.
HH Color — Sets the line and label color for higher high anchored lines, distinguishing resistance levels. Default: Red (solid). Trade-offs/Tips: Choose contrasting hues for dark/light themes; pair with opacity for fills if added later.
LL Color — Sets the line and label color for lower low anchored lines, distinguishing support levels. Default: Lime (solid). Trade-offs/Tips: As above; green shades work well for bullish contexts without overpowering candles.
Reading & Interpretation
Higher high labels and red lines indicate potential resistance zones where volume weighting begins at a new swing top, suggesting sellers may defend prior highs. Lower low labels and lime lines mark support from a fresh swing bottom, with the line's slope reflecting buyer commitment via volume. Lower highs or higher lows appear as labels without new anchors, signaling possible range-bound action. Line proximity to price shows overextension; crosses may hint at regime shifts, but confirm with volume spikes.
Practical Workflows & Combinations
- Trend following: Enter longs above a rising lower low anchored line after higher low confirmation; filter with rising higher highs for uptrends. Use line breaks as trailing stops.
- Exits/Stops: In downtrends, exit shorts below a higher high line; set aggressive stops above it for scalps, conservative below for swings. Pair with momentum oscillators for divergence.
- Multi-asset/Multi-TF: Defaults suit forex/stocks on 1H–4H; on crypto 15M, shorten length to 15. Scale colors for dark themes; combine with higher timeframe anchors for confluence.
Behavior, Constraints & Performance
Closed-bar logic ensures pivots confirm after the lookback period, with no repainting on historical bars—live bars may adjust until regime shift. No higher timeframe calls, so minimal repaint risk beyond standard delays. Resources include a 2000-bar history limit, label/polyline caps at 200/50, and loops for historical point filling (up to current bar count from anchor, typically under 500 iterations). Known limits: In extreme gaps or low-volume periods, anchors may skew; lines absent until first pivots.
Sensible Defaults & Quick Tuning
Start with the 30-bar length for balanced pivot detection across most assets. For too-frequent pivots in ranges, increase to 50 for fewer signals. If lines lag in trends, reduce to 20 and enable labels for visual cues. In low-volatility assets, widen color contrasts; test on 100-bar history to verify stability.
What this indicator is—and isn’t
This is a structure-aware visualization layer for anchoring volume-weighted references at swing extremes, enhancing manual analysis of regimes and levels. It is not a standalone signal generator or predictive model—always integrate with broader context like order flow or news. Use alongside risk management and position sizing, not as isolated buy/sell triggers.
Many thanks to LuxAlgo for the original script "McDonald's Pattern ". The implementation for body pivots instead of wicks uses a = max(open, close), b = min(open, close) and then highest(a, length) / lowest(b, length). This filters noise from the wicks and detects breakouts over/under bodies. Unusual and targeted, super innovative.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts.
Best regards and happy trading
Chervolino
Dynamic Market Structure (MTF) - Dow TheoryDynamic Market Structure (MTF)
OVERVIEW
This advanced indicator provides a comprehensive and fully customizable solution for analyzing market structure based on classic Dow Theory principles. It automates the identification of key structural points, including Higher Highs (HH), Higher Lows (HL), Lower Lows (LL), and Lower Highs (LH).
Going beyond simple pivot detection, this tool visualizes the flow of the trend by plotting dynamic Breaks of Structure (BOS) and potential reversals with Changes of Character (CHoCH). It is designed to be a flexible and powerful tool for traders who use price action and trend analysis as a core part of their strategy.
CORE CONCEPTS
The indicator is built on the foundational principles of Dow Theory:
Uptrend: A series of Higher Highs and Higher Lows.
Downtrend: A series of Lower Lows and Lower Highs.
Break of Structure (BOS): Occurs when price action continues the current trend by creating a new HH in an uptrend or a new LL in a downtrend.
Change of Character (CHoCH): Occurs when the established trend sequence is broken, signaling a potential reversal. For example, when a Lower Low forms after a series of Higher Highs.
CALCULATION METHODOLOGY
This section explains the indicator's underlying logic:
Pivot Detection: The indicator's core logic is based on TradingView's built-in ta.pivothigh() and ta.pivotlow() functions. The sensitivity of this detection is fully controlled by the user via the Pivot Lookback Left and Pivot Lookback Right settings.
Structure Calculation (BOS/CHoCH): The script identifies market structure by analyzing the sequence of these confirmed pivots.
A bullish BOS is plotted when a new ta.pivothigh is confirmed at a price higher than the previous confirmed ta.pivothigh.
A bearish CHoCH is plotted when a new ta.pivotlow is confirmed at a price lower than the previous confirmed ta.pivotlow , breaking the established sequence of higher lows.
The logic is mirrored for bearish BOS and bullish CHoCH.
Invalidation Levels: This feature identifies the last confirmed pivot before a structure break (e.g., the last ta.pivotlow before a bullish BOS) and plots a dotted line from it to the breakout bar. This level is considered the structural invalidation point for that move.
MTF Confirmation: This unique feature provides confluence by analyzing a second, lower timeframe. When a pivot (e.g., a Higher Low) is confirmed on the main chart, the script requests pivot data from the user-selected lower timeframe. If a corresponding trend reversal is detected on that lower timeframe (e.g., a break of its own minor downtrend), the pivot is labeled "Firm" (FHL); otherwise, it is labeled "Soft" (SHL).
KEY FEATURES
This indicator is packed with advanced features designed to provide a deeper level of market insight:
Dynamic Structure Lines: BOS and CHoCH levels are plotted with clean, dashed lines that dynamically start at the old pivot and terminate precisely at the breakout bar, keeping the chart clean and precise.
Invalidation Levels: For every structure break, the indicator can plot a dotted "Invalidation" line (INV). This marks the critical support or resistance pivot that, if broken, would negate the previous move, providing a clear reference for risk management.
Multi-Timeframe (MTF) Confirmation: Add a layer of confluence to your analysis by confirming pivots on a lower timeframe. The indicator can label Higher Lows and Lower Highs as either "Firm" (FHL/FLH) if confirmed by a reversal on a lower timeframe, or "Soft" (SHL/SLH) if not.
Flexible Pivot Detection: Fully adjustable Pivot Lookback settings for the left and right sides allow you to tune the indicator's sensitivity to match any timeframe or trading style, from long-term investing to short-term scalping.
Full Customization: Take complete control of the indicator's appearance. A dedicated style menu allows you to customize the colors for all bullish, bearish, and reversal elements, including the transparency of the trend-based candle coloring.
HOW TO USE
Trend Identification: Use the sequence of HH/HL and LL/LH, along with the trend-colored candles, to quickly assess the current market direction on any timeframe.
Entry Signals: A confirmed BOS can signal a potential entry in the direction of the trend. A CHoCH can signal a potential reversal, offering an opportunity to enter a new trend early.
Risk Management: Use the automatically plotted "Invalidation" (INV) lines as a logical reference point for placing stop losses. A break of this level indicates that the structure you were trading has failed.
Confluence: Use the "Firm" pivot signals from the MTF analysis to identify high-probability swing points that are supported by price action on multiple timeframes.
SETTINGS BREAKDOWN
Pivot Lookback Left/Right: Controls the sensitivity of pivot detection. Higher numbers find more significant (but fewer) pivots.
MTF Confirmation: Enable/disable the "Firm" vs. "Soft" pivot analysis and select your preferred lower timeframe for confirmation.
Style Settings: Customize all colors and the transparency of the candle coloring to match your chart's theme.
Show Invalidation Levels: Toggle the visibility of the dotted invalidation lines.
This indicator is a powerful tool for visualizing and trading with the trend. Experiment with the settings to find a configuration that best fits your personal trading strategy.
Historical Matrix Analyzer [PhenLabs]📊Historical Matrix Analyzer
Version: PineScriptv6
📌Description
The Historical Matrix Analyzer is an advanced probabilistic trading tool that transforms technical analysis into a data-driven decision support system. By creating a comprehensive 56-cell matrix that tracks every combination of RSI states and multi-indicator conditions, this indicator reveals which market patterns have historically led to profitable outcomes and which have not.
At its core, the indicator continuously monitors seven distinct RSI states (ranging from Extreme Oversold to Extreme Overbought) and eight unique indicator combinations (MACD direction, volume levels, and price momentum). For each of these 56 possible market states, the system calculates average forward returns, win rates, and occurrence counts based on your configurable lookback period. The result is a color-coded probability matrix that shows you exactly where you stand in the historical performance landscape.
The standout feature is the Current State Panel, which provides instant clarity on your active market conditions. This panel displays signal strength classifications (from Strong Bullish to Strong Bearish), the average return percentage for similar past occurrences, an estimated win rate using Bayesian smoothing to prevent small-sample distortions, and a confidence level indicator that warns you when insufficient data exists for reliable conclusions.
🚀Points of Innovation
Multi-dimensional state classification combining 7 RSI levels with 8 indicator combinations for 56 unique trackable market conditions
Bayesian win rate estimation with adjustable smoothing strength to provide stable probability estimates even with limited historical samples
Real-time active cell highlighting with “NOW” marker that visually connects current market conditions to their historical performance data
Configurable color intensity sensitivity allowing traders to adjust heat-map responsiveness from conservative to aggressive visual feedback
Dual-panel display system separating the comprehensive statistics matrix from an easy-to-read current state summary panel
Intelligent confidence scoring that automatically warns traders when occurrence counts fall below reliable thresholds
🔧Core Components
RSI State Classification: Segments RSI readings into 7 distinct zones (Extreme Oversold <20, Oversold 20-30, Weak 30-40, Neutral 40-60, Strong 60-70, Overbought 70-80, Extreme Overbought >80) to capture momentum extremes and transitions
Multi-Indicator Condition Tracking: Simultaneously monitors MACD crossover status (bullish/bearish), volume relative to moving average (high/low), and price direction (rising/falling) creating 8 binary-encoded combinations
Historical Data Storage Arrays: Maintains rolling lookback windows storing RSI states, indicator states, prices, and bar indices for precise forward-return calculations
Forward Performance Calculator: Measures price changes over configurable forward bar periods (1-20 bars) from each historical state, accumulating total returns and win counts per matrix cell
Bayesian Smoothing Engine: Applies statistical prior assumptions (default 50% win rate) weighted by user-defined strength parameter to stabilize estimated win rates when sample sizes are small
Dynamic Color Mapping System: Converts average returns into color-coded heat map with intensity adjusted by sensitivity parameter and transparency modified by confidence levels
🔥Key Features
56-Cell Probability Matrix: Comprehensive grid displaying every possible combination of RSI state and indicator condition, with each cell showing average return percentage, estimated win rate, and occurrence count for complete statistical visibility
Current State Info Panel: Dedicated display showing your exact position in the matrix with signal strength emoji indicators, numerical statistics, and color-coded confidence warnings for immediate situational awareness
Customizable Lookback Period: Adjustable historical window from 50 to 500 bars allowing traders to focus on recent market behavior or capture longer-term pattern stability across different market cycles
Configurable Forward Performance Window: Select target holding periods from 1 to 20 bars ahead to align probability calculations with your trading timeframe, whether day trading or swing trading
Visual Heat Mapping: Color-coded cells transition from red (bearish historical performance) through gray (neutral) to green (bullish performance) with intensity reflecting statistical significance and occurrence frequency
Intelligent Data Filtering: Minimum occurrence threshold (1-10) removes unreliable patterns with insufficient historical samples, displaying gray warning colors for low-confidence cells
Flexible Layout Options: Independent positioning of statistics matrix and info panel to any screen corner, accommodating different chart layouts and personal preferences
Tooltip Details: Hover over any matrix cell to see full RSI label, complete indicator status description, precise average return, estimated win rate, and total occurrence count
🎨Visualization
Statistics Matrix Table: A 9-column by 8-row grid with RSI states labeling vertical axis and indicator combinations on horizontal axis, using compact abbreviations (XOverS, OverB, MACD↑, Vol↓, P↑) for space efficiency
Active Cell Indicator: The current market state cell displays “⦿ NOW ⦿” in yellow text with enhanced color saturation to immediately draw attention to relevant historical performance
Signal Strength Visualization: Info panel uses emoji indicators (🔥 Strong Bullish, ✅ Bullish, ↗️ Weak Bullish, ➖ Neutral, ↘️ Weak Bearish, ⛔ Bearish, ❄️ Strong Bearish, ⚠️ Insufficient Data) for rapid interpretation
Histogram Plot: Below the price chart, a green/red histogram displays the current cell’s average return percentage, providing a time-series view of how historical performance changes as market conditions evolve
Color Intensity Scaling: Cell background transparency and saturation dynamically adjust based on both the magnitude of average returns and the occurrence count, ensuring visual emphasis on reliable patterns
Confidence Level Display: Info panel bottom row shows “High Confidence” (green), “Medium Confidence” (orange), or “Low Confidence” (red) based on occurrence counts relative to minimum threshold multipliers
📖Usage Guidelines
RSI Period
Default: 14
Range: 1 to unlimited
Description: Controls the lookback period for RSI momentum calculation. Standard 14-period provides widely-recognized overbought/oversold levels. Decrease for faster, more sensitive RSI reactions suitable for scalping. Increase (21, 28) for smoother, longer-term momentum assessment in swing trading. Changes affect how quickly the indicator moves between the 7 RSI state classifications.
MACD Fast Length
Default: 12
Range: 1 to unlimited
Description: Sets the faster exponential moving average for MACD calculation. Standard 12-period setting works well for daily charts and captures short-term momentum shifts. Decreasing creates more responsive MACD crossovers but increases false signals. Increasing smooths out noise but delays signal generation, affecting the bullish/bearish indicator state classification.
MACD Slow Length
Default: 26
Range: 1 to unlimited
Description: Defines the slower exponential moving average for MACD calculation. Traditional 26-period setting balances trend identification with responsiveness. Must be greater than Fast Length. Wider spread between fast and slow increases MACD sensitivity to trend changes, impacting the frequency of indicator state transitions in the matrix.
MACD Signal Length
Default: 9
Range: 1 to unlimited
Description: Smoothing period for the MACD signal line that triggers bullish/bearish state changes. Standard 9-period provides reliable crossover signals. Shorter values create more frequent state changes and earlier signals but with more whipsaws. Longer values produce more confirmed, stable signals but with increased lag in detecting momentum shifts.
Volume MA Period
Default: 20
Range: 1 to unlimited
Description: Lookback period for volume moving average used to classify volume as “high” or “low” in indicator state combinations. 20-period default captures typical monthly trading patterns. Shorter periods (10-15) make volume classification more reactive to recent spikes. Longer periods (30-50) require more sustained volume changes to trigger state classification shifts.
Statistics Lookback Period
Default: 200
Range: 50 to 500
Description: Number of historical bars used to calculate matrix statistics. 200 bars provides substantial data for reliable patterns while remaining responsive to regime changes. Lower values (50-100) emphasize recent market behavior and adapt quickly but may produce volatile statistics. Higher values (300-500) capture long-term patterns with stable statistics but slower adaptation to changing market dynamics.
Forward Performance Bars
Default: 5
Range: 1 to 20
Description: Number of bars ahead used to calculate forward returns from each historical state occurrence. 5-bar default suits intraday to short-term swing trading (5 hours on hourly charts, 1 week on daily charts). Lower values (1-3) target short-term momentum trades. Higher values (10-20) align with position trading and longer-term pattern exploitation.
Color Intensity Sensitivity
Default: 2.0
Range: 0.5 to 5.0, step 0.5
Description: Amplifies or dampens the color intensity response to average return magnitudes in the matrix heat map. 2.0 default provides balanced visual emphasis. Lower values (0.5-1.0) create subtle coloring requiring larger returns for full saturation, useful for volatile instruments. Higher values (3.0-5.0) produce vivid colors from smaller returns, highlighting subtle edges in range-bound markets.
Minimum Occurrences for Coloring
Default: 3
Range: 1 to 10
Description: Required minimum sample size before applying color-coded performance to matrix cells. Cells with fewer occurrences display gray “insufficient data” warning. 3-occurrence default filters out rare patterns. Lower threshold (1-2) shows more data but includes unreliable single-event statistics. Higher thresholds (5-10) ensure only well-established patterns receive visual emphasis.
Table Position
Default: top_right
Options: top_left, top_right, bottom_left, bottom_right
Description: Screen location for the 56-cell statistics matrix table. Position to avoid overlapping critical price action or other indicators on your chart. Consider chart orientation and candlestick density when selecting optimal placement.
Show Current State Panel
Default: true
Options: true, false
Description: Toggle visibility of the dedicated current state information panel. When enabled, displays signal strength, RSI value, indicator status, average return, estimated win rate, and confidence level for active market conditions. Disable to declutter charts when only the matrix table is needed.
Info Panel Position
Default: bottom_left
Options: top_left, top_right, bottom_left, bottom_right
Description: Screen location for the current state information panel (when enabled). Position independently from statistics matrix to optimize chart real estate. Typically placed opposite the matrix table for balanced visual layout.
Win Rate Smoothing Strength
Default: 5
Range: 1 to 20
Description: Controls Bayesian prior weighting for estimated win rate calculations. Acts as virtual sample size assuming 50% win rate baseline. Default 5 provides moderate smoothing preventing extreme win rate estimates from small samples. Lower values (1-3) reduce smoothing effect, allowing win rates to reflect raw data more directly. Higher values (10-20) increase conservatism, pulling win rate estimates toward 50% until substantial evidence accumulates.
✅Best Use Cases
Pattern-based discretionary trading where you want historical confirmation before entering setups that “look good” based on current technical alignment
Swing trading with holding periods matching your forward performance bar setting, using high-confidence bullish cells as entry filters
Risk assessment and position sizing, allocating larger size to trades originating from cells with strong positive average returns and high estimated win rates
Market regime identification by observing which RSI states and indicator combinations are currently producing the most reliable historical patterns
Backtesting validation by comparing your manual strategy signals against the historical performance of the corresponding matrix cells
Educational tool for developing intuition about which technical condition combinations have actually worked versus those that feel right but lack historical evidence
⚠️Limitations
Historical patterns do not guarantee future performance, especially during unprecedented market events or regime changes not represented in the lookback period
Small sample sizes (low occurrence counts) produce unreliable statistics despite Bayesian smoothing, requiring caution when acting on low-confidence cells
Matrix statistics lag behind rapidly changing market conditions, as the lookback period must accumulate new state occurrences before updating performance data
Forward return calculations use fixed bar periods that may not align with actual trade exit timing, support/resistance levels, or volatility-adjusted profit targets
💡What Makes This Unique
Multi-Dimensional State Space: Unlike single-indicator tools, simultaneously tracks 56 distinct market condition combinations providing granular pattern resolution unavailable in traditional technical analysis
Bayesian Statistical Rigor: Implements proper probabilistic smoothing to prevent overconfidence from limited data, a critical feature missing from most pattern recognition tools
Real-Time Contextual Feedback: The “NOW” marker and dedicated info panel instantly connect current market conditions to their historical performance profile, eliminating guesswork
Transparent Occurrence Counts: Displays sample sizes directly in each cell, allowing traders to judge statistical reliability themselves rather than hiding data quality issues
Fully Customizable Analysis Window: Complete control over lookback depth and forward return horizons lets traders align the tool precisely with their trading timeframe and strategy requirements
🔬How It Works
1. State Classification and Encoding
Each bar’s RSI value is evaluated and assigned to one of 7 discrete states based on threshold levels (0: <20, 1: 20-30, 2: 30-40, 3: 40-60, 4: 60-70, 5: 70-80, 6: >80)
Simultaneously, three binary conditions are evaluated: MACD line position relative to signal line, current volume relative to its moving average, and current close relative to previous close
These three binary conditions are combined into a single indicator state integer (0-7) using binary encoding, creating 8 possible indicator combinations
The RSI state and indicator state are stored together, defining one of 56 possible market condition cells in the matrix
2. Historical Data Accumulation
As each bar completes, the current state classification, closing price, and bar index are stored in rolling arrays maintained at the size specified by the lookback period
When the arrays reach capacity, the oldest data point is removed and the newest added, creating a sliding historical window
This continuous process builds a comprehensive database of past market conditions and their subsequent price movements
3. Forward Return Calculation and Statistics Update
On each bar, the indicator looks back through the stored historical data to find bars where sufficient forward bars exist to measure outcomes
For each historical occurrence, the price change from that bar to the bar N periods ahead (where N is the forward performance bars setting) is calculated as a percentage return
This percentage return is added to the cumulative return total for the specific matrix cell corresponding to that historical bar’s state classification
Occurrence counts are incremented, and wins are tallied for positive returns, building comprehensive statistics for each of the 56 cells
The Bayesian smoothing formula combines these raw statistics with prior assumptions (neutral 50% win rate) weighted by the smoothing strength parameter to produce estimated win rates that remain stable even with small samples
💡Note:
The Historical Matrix Analyzer is designed as a decision support tool, not a standalone trading system. Best results come from using it to validate discretionary trade ideas or filter systematic strategy signals. Always combine matrix insights with proper risk management, position sizing rules, and awareness of broader market context. The estimated win rate feature uses Bayesian statistics specifically to prevent false confidence from limited data, but no amount of smoothing can create reliable predictions from fundamentally insufficient sample sizes. Focus on high-confidence cells (green-colored confidence indicators) with occurrence counts well above your minimum threshold for the most actionable insights.
DAMMU Swing Trading PRODammu Scalping Pro – Short Notes
1️⃣ Purpose:
Scalping and swing trading tool for 15-min and 1-min charts.
Designed for trend continuation, pullbacks, and reversals.
Works well with Heikin Ashi candles (optional).
2️⃣ Core Components:
EMAs:
Fast: EMA5-12
Medium: EMA12-36 Ribbon
Long: EMA75/89 (1-min), EMA180/200 (15-min), EMA540/633
Price Action Channel (PAC): EMA-based High, Low, Close channel.
Fractals: Regular & filtered (BW) fractals for swing recognition.
Higher Highs / Lower Highs / Higher Lows / Lower Lows (HH, LH, HL, LL).
Pivot Points: Optional display with labels.
3️⃣ Bar Coloring:
Blue: Close above PAC
Red: Close below PAC
Gray: Close inside PAC
4️⃣ Alerts:
Swing Buy/Sell arrows based on PAC breakout and EMA200 filter.
Optional “Big Arrows” mode for visibility.
Alert messages: "SWING_UP" and "SWING_DN"
5️⃣ Workflow / Usage Tips:
Set chart to 15-min (for trend) + 1-min (for entry).
Optionally enable Heikin Ashi candles.
Trade long only above EMA200, short only below EMA200.
Watch for pullbacks into EMA channels or ribbons.
Confirm trend resumption via PAC breakout & bar color change.
Use fractals and pivot points to draw trendlines and locate support/resistance.
6️⃣ Optional Filters:
Filter PAC signals with 200 EMA.
Filter fractals for “Pristine/Ideal” patterns (BW filter).
7️⃣ Visuals:
EMA ribbons, PAC fill, HH/LL squares, fractal triangles.
Pivot labels & candle numbering for patterns.
8️⃣ Notes:
No extra indicators needed except optionally SweetSpot Gold2 for major S/R levels.
Suitable for scalping pullbacks with trend confirmation.
If you want, I can make an even shorter “one-screen cheat sheet” with colors, alerts, and EMAs, perfect for real-time chart reference.
Do you want me to do that?
DAMMU Swing Trading PRODammu Scalping Pro – Short Notes
1️⃣ Purpose:
Scalping and swing trading tool for 15-min and 1-min charts.
Designed for trend continuation, pullbacks, and reversals.
Works well with Heikin Ashi candles (optional).
2️⃣ Core Components:
EMAs:
Fast: EMA5-12
Medium: EMA12-36 Ribbon
Long: EMA75/89 (1-min), EMA180/200 (15-min), EMA540/633
Price Action Channel (PAC): EMA-based High, Low, Close channel.
Fractals: Regular & filtered (BW) fractals for swing recognition.
Higher Highs / Lower Highs / Higher Lows / Lower Lows (HH, LH, HL, LL).
Pivot Points: Optional display with labels.
3️⃣ Bar Coloring:
Blue: Close above PAC
Red: Close below PAC
Gray: Close inside PAC
4️⃣ Alerts:
Swing Buy/Sell arrows based on PAC breakout and EMA200 filter.
Optional “Big Arrows” mode for visibility.
Alert messages: "SWING_UP" and "SWING_DN"
5️⃣ Workflow / Usage Tips:
Set chart to 15-min (for trend) + 1-min (for entry).
Optionally enable Heikin Ashi candles.
Trade long only above EMA200, short only below EMA200.
Watch for pullbacks into EMA channels or ribbons.
Confirm trend resumption via PAC breakout & bar color change.
Use fractals and pivot points to draw trendlines and locate support/resistance.
6️⃣ Optional Filters:
Filter PAC signals with 200 EMA.
Filter fractals for “Pristine/Ideal” patterns (BW filter).
7️⃣ Visuals:
EMA ribbons, PAC fill, HH/LL squares, fractal triangles.
Pivot labels & candle numbering for patterns.
8️⃣ Notes:
No extra indicators needed except optionally SweetSpot Gold2 for major S/R levels.
Suitable for scalping pullbacks with trend confirmation.
If you want, I can make an even shorter “one-screen cheat sheet” with colors, alerts, and EMAs, perfect for real-time charT
nadia
Gold ramon strategy based on 50 candles and atr of 12
You enter the maximum of 50 candles once the most bearish starts to rise, we expect 10 candles, if you don't go up in 10 candles, you don't enter, if you go up before 10 candles, you enter.
When is TP? Enough with 5 candles
The temporality is 1 hour. It can be adjusted to 1 minute temporality for scalping.
It is never lost, because it always exceeds the previous maximums.
Quantum Flux Universal Strategy Summary in one paragraph
Quantum Flux Universal is a regime switching strategy for stocks, ETFs, index futures, major FX pairs, and liquid crypto on intraday and swing timeframes. It helps you act only when the normalized core signal and its guide agree on direction. It is original because the engine fuses three adaptive drivers into the smoothing gains itself. Directional intensity is measured with binary entropy, path efficiency shapes trend quality, and a volatility squash preserves contrast. Add it to a clean chart, watch the polarity lane and background, and trade from positive or negative alignment. For conservative workflows use on bar close in the alert settings when you add alerts in a later version.
Scope and intent
• Markets. Large cap equities and ETFs. Index futures. Major FX pairs. Liquid crypto
• Timeframes. One minute to daily
• Default demo used in the publication. QQQ on one hour
• Purpose. Provide a robust and portable way to detect when momentum and confirmation align, while dampening chop and preserving turns
• Limits. This is a strategy. Orders are simulated on standard candles only
Originality and usefulness
• Unique concept or fusion. The novelty sits in the gain map. Instead of gating separate indicators, the model mixes three drivers into the adaptive gains that power two one pole filters. Directional entropy measures how one sided recent movement has been. Kaufman style path efficiency scores how direct the path has been. A volatility squash stabilizes step size. The drivers are blended into the gains with visible inputs for strength, windows, and clamps.
• What failure mode it addresses. False starts in chop and whipsaw after fast spikes. Efficiency and the squash reduce over reaction in noise.
• Testability. Every component has an input. You can lengthen or shorten each window and change the normalization mode. The polarity plot and background provide a direct readout of state.
• Portable yardstick. The core is normalized with three options. Z score, percent rank mapped to a symmetric range, and MAD based Z score. Clamp bounds define the effective unit so context transfers across symbols.
Method overview in plain language
The strategy computes two smoothed tracks from the chart price source. The fast track and the slow track use gains that are not fixed. Each gain is modulated by three drivers. A driver for directional intensity, a driver for path efficiency, and a driver for volatility. The difference between the fast and the slow tracks forms the raw flux. A small phase assist reduces lag by subtracting a portion of the delayed value. The flux is then normalized. A guide line is an EMA of a small lead on the flux. When the flux and its guide are both above zero, the polarity is positive. When both are below zero, the polarity is negative. Polarity changes create the trade direction.
Base measures
• Return basis. The step is the change in the chosen price source. Its absolute value feeds the volatility estimate. Mean absolute step over the window gives a stable scale.
• Efficiency basis. The ratio of net move to the sum of absolute step over the window gives a value between zero and one. High values mean trend quality. Low values mean chop.
• Intensity basis. The fraction of up moves over the window plugs into binary entropy. Intensity is one minus entropy, which maps to zero in uncertainty and one in very one sided moves.
Components
• Directional Intensity. Measures how one sided recent bars have been. Smoothed with RMA. More intensity increases the gain and makes the fast and slow tracks react sooner.
• Path Efficiency. Measures the straightness of the price path. A gamma input shapes the curve so you can make trend quality count more or less. Higher efficiency lifts the gain in clean trends.
• Volatility Squash. Normalizes the absolute step with Z score then pushes it through an arctangent squash. This caps the effect of spikes so they do not dominate the response.
• Normalizer. Three modes. Z score for familiar units, percent rank for a robust monotone map to a symmetric range, and MAD based Z for outlier resistance.
• Guide Line. EMA of the flux with a small lead term that counteracts lag without heavy overshoot.
Fusion rule
• Weighted sum of the three drivers with fixed weights visible in the code comments. Intensity has fifty percent weight. Efficiency thirty percent. Volatility twenty percent.
• The blend power input scales the driver mix. Zero means fixed spans. One means full driver control.
• Minimum and maximum gain clamps bound the adaptive gain. This protects stability in quiet or violent regimes.
Signal rule
• Long suggestion appears when flux and guide are both above zero. That sets polarity to plus one.
• Short suggestion appears when flux and guide are both below zero. That sets polarity to minus one.
• When polarity flips from plus to minus, the strategy closes any long and enters a short.
• When flux crosses above the guide, the strategy closes any short.
What you will see on the chart
• White polarity plot around the zero line
• A dotted reference line at zero named Zen
• Green background tint for positive polarity and red background tint for negative polarity
• Strategy long and short markers placed by the TradingView engine at entry and at close conditions
• No table in this version to keep the visual clean and portable
Inputs with guidance
Setup
• Price source. Default ohlc4. Stable for noisy symbols.
• Fast span. Typical range 6 to 24. Raising it slows the fast track and can reduce churn. Lowering it makes entries more reactive.
• Slow span. Typical range 20 to 60. Raising it lengthens the baseline horizon. Lowering it brings the slow track closer to price.
Logic
• Guide span. Typical range 4 to 12. A small guide smooths without eating turns.
• Blend power. Typical range 0.25 to 0.85. Raising it lets the drivers modulate gains more. Lowering it pushes behavior toward fixed EMA style smoothing.
• Vol window. Typical range 20 to 80. Larger values calm the volatility driver. Smaller values adapt faster in intraday work.
• Efficiency window. Typical range 10 to 60. Larger values focus on smoother trends. Smaller values react faster but accept more noise.
• Efficiency gamma. Typical range 0.8 to 2.0. Above one increases contrast between clean trends and chop. Below one flattens the curve.
• Min alpha multiplier. Typical range 0.30 to 0.80. Lower values increase smoothing when the mix is weak.
• Max alpha multiplier. Typical range 1.2 to 3.0. Higher values shorten smoothing when the mix is strong.
• Normalization window. Typical range 100 to 300. Larger values reduce drift in the baseline.
• Normalization mode. Z score, percent rank, or MAD Z. Use MAD Z for outlier heavy symbols.
• Clamp level. Typical range 2.0 to 4.0. Lower clamps reduce the influence of extreme runs.
Filters
• Efficiency filter is implicit in the gain map. Raising efficiency gamma and the efficiency window increases the preference for clean trends.
• Micro versus macro relation is handled by the fast and slow spans. Increase separation for swing, reduce for scalping.
• Location filter is not included in v1.0. If you need distance gates from a reference such as VWAP or a moving mean, add them before publication of a new version.
Alerts
• This version does not include alertcondition lines to keep the core minimal. If you prefer alerts, add names Long Polarity Up, Short Polarity Down, Exit Short on Flux Cross Up in a later version and select on bar close for conservative workflows.
Strategy has been currently adapted for the QQQ asset with 30/60min timeframe.
For other assets may require new optimization
Properties visible in this publication
• Initial capital 25000
• Base currency Default
• Default order size method percent of equity with value 5
• Pyramiding 1
• Commission 0.05 percent
• Slippage 10 ticks
• Process orders on close ON
• Bar magnifier ON
• Recalculate after order is filled OFF
• Calc on every tick OFF
Honest limitations and failure modes
• Past results do not guarantee future outcomes
• Economic releases, circuit breakers, and thin books can break the assumptions behind intensity and efficiency
• Gap heavy symbols may benefit from the MAD Z normalization
• Very quiet regimes can reduce signal contrast. Use longer windows or higher guide span to stabilize context
• Session time is the exchange time of the chart
• If both stop and target can be hit in one bar, tie handling would matter. This strategy has no fixed stops or targets. It uses polarity flips for exits. If you add stops later, declare the preference
Open source reuse and credits
• None beyond public domain building blocks and Pine built ins such as EMA, SMA, standard deviation, RMA, and percent rank
• Method and fusion are original in construction and disclosure
Legal
Education and research only. Not investment advice. You are responsible for your decisions. Test on historical data and in simulation before any live use. Use realistic costs.
Strategy add on block
Strategy notice
Orders are simulated by the TradingView engine on standard candles. No request.security() calls are used.
Entries and exits
• Entry logic. Enter long when both the normalized flux and its guide line are above zero. Enter short when both are below zero
• Exit logic. When polarity flips from plus to minus, close any long and open a short. When the flux crosses above the guide line, close any short
• Risk model. No initial stop or target in v1.0. The model is a regime flipper. You can add a stop or trail in later versions if needed
• Tie handling. Not applicable in this version because there are no fixed stops or targets
Position sizing
• Percent of equity in the Properties panel. Five percent is the default for examples. Risk per trade should not exceed five to ten percent of equity. One to two percent is a common choice
Properties used on the published chart
• Initial capital 25000
• Base currency Default
• Default order size percent of equity with value 5
• Pyramiding 1
• Commission 0.05 percent
• Slippage 10 ticks
• Process orders on close ON
• Bar magnifier ON
• Recalculate after order is filled OFF
• Calc on every tick OFF
Dataset and sample size
• Test window Jan 2, 2014 to Oct 16, 2025 on QQQ one hour
• Trade count in sample 324 on the example chart
Release notes template for future updates
Version 1.1.
• Add alertcondition lines for long, short, and exit short
• Add optional table with component readouts
• Add optional stop model with a distance unit expressed as ATR or a percent of price
Notes. Backward compatibility Yes. Inputs migrated Yes.
