CVD Divergence + Volume MarkerHere is a Pine Script concept to mark candlestick chart candles when cumulative delta is divergent to price action and volume is above average. Cumulative delta divergence typically occurs when the price forms new highs/lows while cumulative delta forms lower highs/lows (or vice versa). The script should include a marker only when this divergence occurs alongside above-average volume, increasing signal strength and filtering out weak setups.
Coding Concept
Calculate cumulative delta (approximation using price and volume if true bid/ask volume is unavailable, e.g., on spot).
Calculate moving average of volume.
Detect bullish divergence (price makes lower low, cumulative delta makes higher low) and bearish divergence (price makes higher high, cumulative delta makes lower high).
Mark candle with above-average volume when divergence is present.
Göstergeler ve stratejiler
Puell Multiple Variants [OperationHeadLessChicken]Overview
This script contains three different, but related indicators to visualise Bitcoin miner revenue.
The classical Puell Multiple : historically, it has been good at signaling Bitcoin cycle tops and bottoms, but due to the diminishing rewards miners get after each halving, it is not clear how you determine overvalued and undervalued territories on it. Here is how the other two modified versions come into play:
Halving-Corrected Puell Multiple : The idea is to multiply the miner revenue after each halving with a correction factor, so overvalued levels are made comparable by a horizontal line across cycles. After experimentation, this correction factor turned out to be around 1.63. This brings cycle tops close to each other, but we lose the ability to see undervalued territories as a horizontal region. The third variant aims to fix this:
Miner Revenue Relative Strength Index (Miner Revenue RSI) : It uses RSI to map miner revenue into the 0-100 range, making it easy to visualise over/undervalued territories. With correct parameter settings, it eliminates the diminishing nature of the original Puell Multiple, and shows both over- and undervalued revenues correctly.
Example usage
The goal is to determine cycle tops and bottoms. I recommend using it on high timeframes, like monthly or weekly . Lower than that, you will see a lot of noise, but it could still be used. Here I use monthly as the example.
The classical Puell Multiple is included for reference. It is calculated as Miner Revenue divided by the 365-day Moving Average of the Miner Revenue . As you can see in the picture below, it has been good at signaling tops at 1,3,5,7.
The problems:
- I have to switch the Puell Multiple to a logarithmic scale
- Still, I cannot use a horizontal oversold territory
- 5 didn't touch the trendline, despite being a cycle top
- 9 touched the trendline despite not being a cycle top
Halving-Corrected Puell Multiple (yellow): Multiplies the Puell Multiple by 1.63 (a number determined via experimentation) after each halving. In the picture below, you can see how the Classical (white) and Corrected (yellow) Puell Multiples compare:
Advantages:
- Now you can set a constant overvalued level (12.49 in my case)
- 1,3,7 are signaled correctly as cycle tops
- 9 is correctly not signaled as a cycle top
Caveats:
- Now you don't have bottom signals anymore
- 5 is still not signaled as cycle top
Let's see if we can further improve this:
Miner Revenue RSI (blue):
On the monthly, you can see that an RSI period of 6, an overvalued threshold of 90, and an undervalued threshold of 35 have given historically pretty good signals.
Advantages:
- Uses two simple and clear horizontal levels for undervalued and overvalued levels
- Signaling 1,3,5,7 correctly as cycle tops
- Correctly does not signal 9 as a cycle top
- Signaling 4,6,8 correctly as cycle bottoms
Caveats:
- Misses two as a cycle bottom, although it was a long time ago when the Bitcoin market was much less mature
- In the past, gave some early overvalued signals
Usage
Using the example above, you can apply these indicators to any timeframe you like and tweak their parameters to obtain signals for overvalued/undervalued BTC prices
You can show or hide any of the three indicators individually
Set overvalued/undervalued thresholds for each => the background will highlight in green (undervalued) or red (overvalued)
Set special parameters for the given indicators: correction factor for the Corrected Puell and RSI period for Revenue RSI
Show or hide halving events on the indicator panel
All parameters and colours are adjustable
SMA 10 & 50SMA10&50
SMA 10 & 50 is a simple dual moving average indicator that plots two Simple Moving Averages (SMA) on the price chart: SMA10 and SMA50.
Features:
- SMA10 (fast): Period 10
- SMA50 (slow): Period 50
- Customizable source for each SMA
- Distinct colors for better visualization
Ideal for identifying short-term vs long-term trends, crossovers, and dynamic support/resistance levels.
VWAP H/L Break - NQVWAP crossover with fib targets
bar closing over VWAP(high) go long
bar closing under VWAP (low) go short
fib targets based on closing candle and previous candle.
Open Interest FaraGroup Editionopen interest for a closed group :)
An open interest chart is used, as well as additional functionality.
The ability to specify any data as a source, not just public interest.
EMA Oscillator (21, 50, 100, 200) — Separated + OB/OS//@version=5
indicator("EMA Oscillator (21, 50, 100, 200) — Separated + OB/OS", overlay=false)
// === INPUTS ===
lookback = input.int(500, "Lookback for normalization", minval=100)
// === EMAs ===
ema21 = ta.ema(close, 21)
ema50 = ta.ema(close, 50)
ema100 = ta.ema(close, 100)
ema200 = ta.ema(close, 200)
// === Normalization Function (per EMA) ===
normalize(src) =>
minVal = ta.lowest(src, lookback)
maxVal = ta.highest(src, lookback)
100 * (src - minVal) / (maxVal - minVal)
// === Normalize Each Separately ===
n21 = normalize(ema21)
n50 = normalize(ema50)
n100 = normalize(ema100)
n200 = normalize(ema200)
// === Plot EMAs (Separated Offsets for Clarity) ===
plot(n21, color=color.yellow, title="EMA 21", linewidth=2)
plot(n50 - 5, color=color.orange, title="EMA 50", linewidth=2)
plot(n100 - 10, color=color.blue, title="EMA 100", linewidth=2)
plot(n200 - 15, color=color.red, title="EMA 200", linewidth=2)
// === Overbought/Oversold Lines ===
hline(80, "Overbought", color=color.new(color.red, 60), linestyle=hline.style_dotted)
hline(20, "Oversold", color=color.new(color.green, 60), linestyle=hline.style_dotted)
hline(50, "Midline", color=color.new(color.gray, 80))
Money Line ApproximationSimilar to Ivan's money line minus the Macro data.
How to Interpret and Use It
Bullish Setup : Green line + buy signal = Potential entry (e.g., buy on pullback to the line). Expect upward momentum if RSI stays below 75.
Bearish Setup : Red line + sell signal = Potential exit or short (e.g., sell near the line). Watch for RSI above 25 confirming downside.
Neutral Periods : Yellow line indicates indecision—best to wait for a flip rather than force trades.
Strengths : Simple, visual, and filtered against extremes; works well in trending markets by blending EMAs and using RSI to avoid overbought buys or oversold sells.
Low Range Predictor [NR4/NR7 after WR4/WR7/WR20, within 1-3Days]Indicator Overview
The Low Range Predictor is a TradingView indicator displayed in a single panel below the chart. It spots volatility contraction setups (NR4/NR7 within 1–3 days of WR4/WR7/WR20) to predict low-range moves (e.g., <0.5% daily on SPY) over 2–5 days, perfect for your weekly 15/22 DTE put calendar spread strategy.
What You See
• Red Histograms (WR, Volatility Climax):
• WR4: Half-length red bars, widest range in 4 bars.
• WR7: Three-quarter-length red bars, widest in 7 bars.
• WR20: Full-length red bars, widest in 20 bars.
• Green Histograms (NR, Entry Signals):
• NR4: Half-length green bars, only on NR4 days (tightest range in 4 bars) within 1–3 days of a WR4.
• NR7: Full-length green bars, only on NR7 days within 1–3 days of a WR7.
• Panel: All signals (red WR4/WR7/WR20, green NR4/NR7) show in one panel below the chart, with green bars marking put calendar entry days.
Probabilities
• Volatility Contraction:
• NR4 after WR4: 65–70% chance of daily ranges <0.5% on SPY for 2–5 days (ATR drops 20–30%). Occurs ~2–3 times/month.
• NR7 after WR7: 60–65% chance of similar low ranges, less frequent (~1–2 times/month).
• Backtest (SPY, 2000–2025): 65% of NR4/NR7 signals lead to reduced volatility (<0.7% daily range) vs. 50% for random days.
• Signal Frequency: NR4 signals are more common than NR7, ideal for weekly entries. WR20 provides context but isn’t tied to NR signals.
RSI Value Table – match builtin🧭 Overview
“RSI Value Table – match builtin” displays the exact RSI value (identical to TradingView’s built-in RSI) for any selected timeframe — directly on your chart.
It’s designed for professional traders who need quick RSI confirmation without switching panels or opening multiple indicators.
⚙️ Core Logic
Reads RSI from any timeframe using request.security() with gaps_off and lookahead_off — ensuring a perfect match with the native RSI.
Optional EMA smoothing (non-standard) for visual stability.
Color-coded cell:
🟩 Green → RSI > 50 (bullish momentum)
🟥 Red → RSI < 50 (bearish momentum)
🟨 Yellow → Neutral zone around 50
Adjustable table position: top/bottom, left/right corners.
⚡ Alerts
Built-in alert conditions trigger automatically:
RSI > 50 → bullish momentum confirmation.
RSI < 50 → bearish momentum confirmation.
📈 How to Use
Select your preferred RSI timeframe (e.g., Daily, Weekly, 4H).
Watch the color-coded cell:
Green → trade long bias only.
Red → short bias only.
Ideal as a confirmation module for multi-timeframe systems or smart signal engines.
Flip to GreenPurpose:
This indicator applies a Lorentzian-distance–based machine-learning model to classify market conditions and highlight probable momentum shifts.
Where traditional indicators react to price movement, this one uses statistical pattern recognition to predict when momentum is likely to flip direction — the classic “flip to green” signal.
Concept:
Financial markets don’t move linearly; they bend and distort around major catalysts (news, FOMC meetings, earnings, etc.) in a way similar to how gravity warps space-time.
This indicator accounts for that distortion by measuring distance in Lorentzian space instead of the usual Euclidean space.
In simple terms: it adapts to volatility “warping,” allowing the model to detect structural momentum changes that normal math misses.
Core logic:
Imports two custom libraries:
MLExtensions for machine-learning utilities
KernelFunctions for advanced distance calculations
Computes relationships among multiple features (e.g., RSI, ADX, or other inputs).
Uses Lorentzian geometry to weight how recent price-time behavior influences current classification.
Outputs a visual “flip” cue when the probability of trend reversal exceeds threshold confidence.
Why it matters:
Most indicators measure what has already happened.
Lorentzian Classification attempts to capture what’s about to happen by comparing the present market state to a trained historical distribution under warped “price-time” geometry.
It’s particularly useful for spotting early accumulation or exhaustion zones before they become obvious on standard momentum tools.
Recommended use:
Run it as a background trend classifier or color overlay.
Combine it with volume-based confirmation tools (e.g., Dollar Volume Ownership Gauge) and structural analysis.
A “flip to green” suggests buyers are regaining control; a fade or flip to red implies control returning to sellers.
지표//@version=5
indicator("BTC Cycle DEMA x Stoch RSI", overlay=false)
// ====== 기본 설정 ======
len_stoch = input.int(14, "Stoch RSI Length")
len_rsi = input.int(14, "RSI Length")
len_k = input.int(3, "K Smoothing")
len_d = input.int(3, "D Smoothing")
// ====== Stochastic RSI 계산 ======
rsi_ = ta.rsi(close, len_rsi)
stoch_rsi = ta.stoch(rsi_, rsi_, rsi_, len_stoch)
k = ta.sma(stoch_rsi, len_k)
d = ta.sma(k, len_d)
// ====== DEMA 3중 구조 ======
dema1 = ta.dema(k, 36) // 첫 번째 DEMA
dema2 = ta.dema(dema1, 52) // 두 번째 DEMA
dema3 = ta.dema(dema2, 72) // 세 번째 DEMA
// ====== 시각화 ======
plot(dema1, color=color.white, linewidth=2, title="DEMA (36, Stoch RSI:K)")
plot(dema2, color=color.red, linewidth=2, title="DEMA (52, DEMA)")
plot(dema3, color=color.purple, linewidth=2, title="DEMA (72, DEMA)")
// ====== CROSS 시점 표시 ======
crossUp = ta.crossover(dema2, dema3)
crossDown = ta.crossunder(dema2, dema3)
plotshape(crossUp, title="CROSS UP", location=location.bottom, color=color.new(color.lime, 0), style=shape.triangleup, size=size.large, text="CROSS ↑")
plotshape(crossDown, title="CROSS DOWN", location=location.top, color=color.new(color.orange, 0), style=shape.triangledown, size=size.large, text="CROSS ↓")
// ====== 배경 표시 (BULL RUN 구간 강조) ======
bgcolor(crossUp ? color.new(color.green, 85) : na)
Gold–Bitcoin Correlation (Offset Model) by KManus88This indicator analyzes the correlation between Gold (XAU/USD) and Bitcoin (BTC/USD) using a time-offset model adjustable by the user.
The goal is to detect cyclical leads or lags between both assets, highlighting how capital flows into Gold may precede or follow movements in the crypto market.
Key Features:
Dynamic correlation calculation between Gold and Bitcoin.
Adjustable offset in days (default: 107) to fine-tune the temporal shift.
Automatic labels and on-chart visualization.
Compatible with multiple timeframes and logarithmic scales.
Interpretation:
Positive correlation suggests synchronized trends between both assets.
Negative correlation signals divergence or rotation of liquidity.
The time-offset parameter helps estimate when a shift in Gold could later reflect in Bitcoin.
Recommended use:
For macro-financial and global liquidity cycle analysis.
As a complementary tool in cross-asset momentum strategies.
© 2025 – Developed by KManus88 | Inspired by monetary correlation studies and global liquidity cycles.
This script is for educational purposes only and does not constitute financial advice.
Moon_TimeBreaks_Indicator🌙 Moon + Timeframe Breaks (Daily, Weekly, Monthly, Quarterly, Yearly)
A unique indicator that combines lunar cycles with major time-based breaks to reveal potential rhythm and cycle shifts in price behavior.
🔹 Features
Displays New Moon and Full Moon phases directly on the chart.
Highlights background color during lunar events.
Draws dynamic timeframe separators for Day, Week, Month, Quarter, and Year.
Helps identify cyclical turning points and time-based reactions in markets.
🔹 Customization
Toggle moon phases, background, or time breaks individually.
Adjust colors for each period (daily, weekly, etc.).
Works on all instruments and timeframes.
🔹 Use Case
Perfect for traders interested in time-price harmony, cyclical analysis, or astro-based market timing.
It pairs well with structure or liquidity tools to enhance timing accuracy.
AUTOMATIC ANALYSIS MODULE🧭 Overview
“Automatic Analysis Module” is a professional, multi-indicator system that interprets market conditions in real time using TSI, RSI, and ATR metrics.
It automatically detects trend reversals, volatility compressions, and momentum exhaustion, helping traders identify high-probability setups without manual analysis.
⚙️ Core Logic
The script continuously evaluates:
TSI (True Strength Index) → trend direction, strength, and early reversal zones.
RSI (Relative Strength Index) → momentum extremes and technical divergences.
ATR (Average True Range) → volatility expansion or compression phases.
Multi-timeframe ATR comparison → detects whether the weekly structure supports or contradicts the local move.
The system combines these signals to produce an automatic interpretation displayed directly on the chart.
📊 Interpretation Table
At every new bar close, the indicator updates a compact dashboard (bottom right corner) showing:
🔵 Main interpretation → trend, reversal, exhaustion, or trap scenario.
🟢 Micro ATR context → volatility check and flow analysis (stable / expanding / contracting).
Each condition is expressed in plain English for quick decision-making — ideal for professional traders who manage multiple charts.
📈 How to Use
1️⃣ Load the indicator on your preferred asset and timeframe (recommended: Daily or 4H).
2️⃣ Watch the blue line message for the main trend interpretation.
3️⃣ Use the green line message as a volatility gauge before entering.
4️⃣ Confirm entries with your own strategy or price structure.
Typical examples:
“Possible bullish reversal” → early accumulation signal.
“Compression phase → wait for breakout” → avoid premature trades.
“Confirmed uptrend” → trend continuation zone.
⚡ Key Features
Real-time auto-interpretation of TSI/RSI/ATR signals.
Detects both bull/bear traps and trend exhaustion zones.
Highlights volatility transitions before breakouts occur.
Works across all assets and timeframes.
No repainting — stable on historical data.
✅ Ideal For
Swing traders, position traders, and institutional analysts who want automated context recognition instead of manual indicator reading.
Spread Trading Z-ScoreIndicator: Z-Score Spread Indicator
Description
The "Z-Score Spread Indicator" is a powerful tool for traders employing mean-reversion strategies on the spread between two financial assets (e.g., futures contracts like MNQ and MES). This indicator calculates and plots the Z-score of the price spread, indicating how far the current spread deviates from its historical mean. It features customizable entry and exit thresholds with adjustable offsets, along with an estimated p-value displayed in a table to assess statistical significance.
Key Features
Asset Selection: Allows users to select two asset symbols (e.g., CME_MINI:MNQ1! and CME_MINI:MES1!) via customizable inputs.
Z-Score Calculation: Computes the Z-score based on the spread’s simple moving average and standard deviation over a user-defined lookback period.
Customizable Thresholds with Offset: Offers adjustable base entry and exit thresholds, with an optional offset to fine-tune trading levels, plotted as horizontal lines.
P-Value Estimation: Provides an approximate p-value to evaluate the statistical significance of the Z-score, displayed in a table anchored to the top-left corner.
Visual Representation: Plots the Z-score with a zero line and threshold lines for intuitive interpretation.
Adjustable Parameters
Asset A Symbol: Symbol for Asset A (default: CME_MINI:MNQ1!).
Asset B Symbol: Symbol for Asset B (default: CME_MINI:MES1!).
Z-Score Lookback: Lookback period for Z-score calculation (default: 40, minimum 2).
Base Entry Threshold: Threshold for entry signals (default: 1.8, adjustable with a step of 0.1).
Base Exit Threshold: Threshold for exit signals (default: 0.5, adjustable with a step of 0.1).
Threshold Offset (+/-): Offset to adjust entry and exit thresholds symmetrically (default: 0.0, range -5.0 to 5.0, step 0.1).
Usage
Add the indicator to your chart via the "Indicators" tab.
Customize the parameters based on your preferred assets and trading strategy (lookback period, thresholds, offset).
Observe the Z-score plot and threshold lines (red for short entry, green for long entry, orange dotted for exits) to identify potential trade setups.
Check the p-value table in the top-left corner to assess the statistical significance of the current Z-score.
Use this data to inform mean-reversion trading decisions, ideally in conjunction with other indicators.
Notes
A Z-score above the entry threshold (positive) or below the negative entry threshold suggests a potential short or long entry, respectively. Exits are signaled when the Z-score crosses the exit thresholds.
The p-value is an approximation based on the normal distribution; a value below 0.05 typically indicates statistical significance, but further validation is recommended.
The indicator uses a simple spread (Asset A - Asset B) without volatility adjustments; consider pairing it with a lots calculator for hedging.
Limitations
The p-value is an approximation and may not reflect advanced statistical tests (e.g., ADF) due to Pine Script constraints.
No automatic trading signals are generated; it provides data for manual analysis.
Author
Developed by grogusama, October 15, 2025, 07:29 PM CEST.
Smart Money Concepts Pro – OB, FVG, Liquidity + Trade SetupsThis script is a complete Smart Money Concepts (SMC) toolkit designed for traders who want clean and actionable charts without clutter.
It combines the most important institutional concepts into one indicator:
Order Blocks (OB): auto-detection of bullish and bearish order blocks with mitigation tracking, merging and TTL (time-to-live).
Fair Value Gaps (FVG): automatic gap recognition with size filters, mitigation tracking and lifetime control.
Liquidity Pools (EQH/EQL): equal highs and equal lows marked with tolerance (ATR-based or fixed).
Break of Structure (BOS): up/down structure shifts plotted directly on the chart.
Multi-Timeframe (HTF): option to use higher timeframe data (e.g. H4, Daily) for stronger zones.
Trend Filter: show zones only in the direction of market structure.
Trade Setups: automatic signals for OB Retest + Trend setups, with entry, stop-loss and take-profit levels (custom R-R).
Flexible Zone Extension: choose between extending zones to the live bar or fixed box width for a cleaner look when scrolling.
Features
Fully customizable (pivot length, ATR filters, box width, TTL, zone colors)
Separate presets for Scalping, Intraday, Swing trading styles
Visual trade planning with entry/SL/TP lines and optional labels
Works across all markets (crypto, forex, indices, stocks)
How to use
Bias: identify overall direction (BOS + HTF zones).
Wait: for price to return to an unmitigated OB or FVG.
Entry: take the setup signal (OB retest + trend filter).
Risk: stop-loss at opposite OB boundary.
Target: TP based on chosen R-R multiple (default 2R).
⚡ Whether you scalp short-term moves or swing trade HTF zones, this indicator gives you a clear institutional edge in spotting supply/demand imbalances and high-probability setups.
Criteriosseveral criterias to select stocks, shows for a selected instrument conditions related to EMAs, MA, relative strenght.
I use this table as a final step to select my IN.
VBE Pro - Advanced Volatility Bands with Zero Lag & PredictionVBE Pro: Zero-Lag Predictive Bands
A next-gen volatility envelope that blends zero-lag smoothing with forward-looking volatility models (EWMA/GARCH/HAR/ML) to keep bands tight in calm markets, responsive in shocks, and adaptive across regimes.
What it does
Builds volatility from multiple methods (ATR, StDev, Parkinson, Garman-Klass, Rogers-Satchell, Yang-Zhang).
Projects near-term vol with your choice of predictor, then blends it via a weight slider.
Applies zero-lag smoothing (ZLEMA/ZLMA/DEMA/TEMA/HMA/JMA/Ehlers/Kalman/T3) to cut delay without over-shoot.
Auto-adapts band width by regime (high/low/normal) and can expand dynamically with price acceleration.
Optional displacement to align with your execution style.
On-chart
Upper/Lower zero-lag bands with optional fill.
Middle line (ZL-smoothed source).
Regime-tinted background (High/Low).
Displacement marker (if used).
Compact top-right info table: current vs predicted vol, regime, squeeze, multiplier, methods, ZL gain, est. lag reduction.
Signals & Alerts
Break↑ / Break↓ when price crosses the bands.
Vol↑ / Vol↓ expansion/contraction sequences.
“Squeeze” when band width compresses vs its ZL average.
“ZL” marker when significant zero-lag is active.
Prediction divergence ⚠ when projected vol deviates > threshold.
Built-in alertconditions for all of the above.
Quick start
Method: ATR or Hybrid for robustness.
Smoothing: ZLEMA, length 5–8, ZL gain 2–3 (push higher only if you accept more projection).
Bands: Multiplier 2.0, Adaptive on, Dynamic off to start.
Prediction: EWMA, weight 0.25–0.35. Move to GARCH in mean-reverty tapes; HAR-RV for mixed regimes.
Regime lookback: 50.
FDF — EMAs+VWAP with setup & entry (stable scale)FDF updated test - 9, 21 ema - 90% candle off 21 - entry system
Levels[cz]Description
Levels is a proportional price grid indicator that draws adaptive horizontal levels based on higher timeframe (HTF) closes.
Instead of relying on swing highs/lows or pivots, it builds structured support and resistance zones using fixed percentage increments from a Daily, Weekly, or Monthly reference close.
This creates a consistent geometric framework that helps traders visualize price zones where reactions or consolidations often occur.
How It Works
The script retrieves the last HTF close (Daily/Weekly/Monthly).
It then calculates percentage-based increments (e.g., 0.5%, 1%, 2%, 4%) above and below that reference.
Each percentage forms a distinct “level group,” creating layered grids of potential reaction zones.
Levels are automatically filtered to avoid overlap between different groups, keeping the chart clean.
Visibility is dynamically controlled by timeframe:
Level 1 → up to 15m
Level 2 → up to 1h
Level 3 → up to 4h
Level 4 → up to 1D
This ensures the right amount of structural detail at every zoom level.
How to Use
Identify confluence zones where multiple levels cluster — often areas of strong liquidity or reversals.
Use the grid as a support/resistance map for entries, targets, and stop placement.
Combine with trend or momentum indicators to validate reactions at key price bands.
Adjust the percentage increments and reference timeframe to match the volatility of your instrument (e.g., smaller steps for crypto, larger for indices).
Concept
The indicator is based on the idea that markets move in proportional price steps, not random fluctuations.
By anchoring levels to a higher-timeframe close and expanding outward geometrically, Levels highlights recurring equilibrium and expansion zones — areas where traders can anticipate probable turning points or consolidations.
Features
4 customizable percentage-based level sets
Dynamic visibility by timeframe
Non-overlapping level hierarchy
Lightweight on performance
Fully customizable colors, styles, and widths
Sonic R BOTOnly EMA 144 and 610, you can find the supply and demand zone to open the position. You must confirm the trend
