Options Confluence Overlay - Stocks (1D) The Options Confluence Overlay — Stocks is a daily timeframe indicator designed for equities and ETFs, with a focus on timing, structure, and risk clarity rather than frequent signals.
This tool combines price structure, volatility, and momentum timing into a single visual framework that helps traders decide when to trade, when to stand aside, and where risk and exits are clearly defined.
Unlike fast-signal indicators, this script emphasizes trade quality over trade quantity.
🔍 What the indicator does
The indicator evaluates four core components on the daily chart, with an optional weekly trend filter:
• Mean + Deviation Band (Band 1) to define structure
• ATR-based targets to project realistic price expansion
• Momentum timing using Stochastic RSI (cross or approach)
• Confluence scoring to allow or block trades
Only when these elements align does the indicator permit a CALL, PUT, or display NO-TRADE.
🟩 Preferred Entry Zone (PEZ)
When a CALL or PUT is allowed, the indicator highlights a Preferred Entry Zone (PEZ):
• CALL PEZ: Mean → Lower Band
• PUT PEZ: Mean → Upper Band
This zone represents areas where risk is better defined and entries are typically more favorable.
🎯 Primary Exit (Partial ATR)
Instead of encouraging traders to chase full volatility expansion, the indicator includes a Primary Exit level:
• A configurable percentage of ATR
• Designed to capture early, high-probability movement
• Especially useful for shorter-term trades or profit protection
Full ATR targets are still shown, but the Primary Exit is intended as the first decision point, not a promise of full extension.
🧠 Entry Quality (Informational)
When enabled, the dashboard displays an Entry Quality hint:
• PEZ Deep — price is deeper into the zone (higher potential, higher patience required)
• PEZ Shallow — price is closer to the mean (faster, but less extended setups)
This is informational only and does not block trades.
🚦 Trade states
The dashboard clearly communicates one of three states:
• CALL allowed
• PUT allowed
• NO-TRADE (conditions are mixed or incomplete)
The indicator is intentionally conservative during NO-TRADE periods.
⚠️ Important notes
• Designed for stocks and ETFs, not crypto
• Intended for daily timeframe analysis
• Not financial advice
• Always combine with proper risk management
📘 Model Trade Example (CALL)
The dashboard shows CALL allowed
Price pulls back into the green PEZ
Weekly filter confirms bullish direction
Enter near the PEZ (no chasing breakouts)
Risk: below Band 1 low
Primary Exit: at the yellow Primary Exit level
Optional: hold partial size toward full ATR target if momentum remains strong
If the dashboard changes to NO-TRADE, no new entries are taken.
📕 Model Trade Example (PUT)
The dashboard shows PUT allowed
Price rallies into the red PEZ
Weekly filter confirms bearish direction
Enter near resistance inside PEZ
Risk: above Band 1 high
Primary Exit: at the yellow Primary Exit level
Avoid holding through momentum exhaustion
อินดิเคเตอร์และกลยุทธ์
Angle-able Thick Linean options to get thicker/thick trendlines. personally i dont think 4 pixels is wide enough so i made this, here you go
Bullish, Bearish, & Normal RSI1. Identifying "True" Momentum (The Aqua/Fuchsia Logic)The most useful part of this script is the comparison between the three lines.Bullish Conviction (Aqua): When both the Bullish and Bearish lines are above the Normal RSI, it suggests that even on "down" candles (red candles), the price isn't losing significant ground. The overall structure is buoyant.Bearish Conviction (Fuchsia): When both are below the Normal RSI, it indicates that even when you get "up" candles (green candles), they lack the strength to lift the average momentum. The sellers are effectively "smothering" the bounces.
2. Spotting Hidden Weakness/Strength (Spread Analysis)The "Spread" (the gap between rsiBull and rsiBear) provides a unique utility:ScenarioInterpretationUtilityWide SpreadHigh volatility and indecision. Green candles are very strong, but red candles are also very weak.Avoid trend-following; wait for a "squeeze" or narrowing.Tight SpreadHigh agreement in price action. Most candles are moving in a similar direction or with similar intensity.Great for identifying stable, trending moves with low noise.Bull/Bear CrossIf the Bullish RSI crosses above the Bearish RSI significantly.Can act as an early entry signal before the Standard RSI hits the 50-midline.
3. Practical Strategy Use CasesFilter for Breakouts: If you see a price breakout but the RSI color remains Gray, the move might lack "conviction." You ideally want to see the color flip to Aqua (for long) or Fuchsia (for short) as the breakout occurs.Exhaustion Signal: If the Normal RSI is overbought ($>70$) but the rsiBull begins to dip toward the rsiNormal, it suggests that the "green candle strength" is waning even if the price is staying high—a potential warning of a reversal.Potential Drawbacks to WatchLag: Like all RSI-based indicators, this is lagging. Because you are using a 14-period lookback on three different calculations, it may take a few bars to confirm a sentiment shift.Whipsaw in Sideways Markets: In a tight range-bound market, the color may flip between Aqua and Fuchsia rapidly, creating "noise."Pro-Tip: This indicator would be most effective when used in conjunction with Volume. If you get an "Aqua" signal on rising volume, the probability of a sustained trend is significantly higher.
Multi Cycles Slope-Fit System MLMulti Cycles Predictive System : A Slope-Adaptive Ensemble
Executive Summary:
The MCPS-Slope (Multi Cycles Slope-Fit System) represents a paradigm shift from static technical analysis to adaptive, probabilistic market modeling. Unlike traditional indicators that rely on a single algorithm with fixed settings, this system deploys a "Mixture of Experts" (MoE) ensemble comprising 13 distinct cycle and trend algorithms.
Using a Gradient-Based Memory (GBM) learning engine, the system dynamically solves the "Cycle Mode" problem by real-time weighting. It aggressively curve-fits the Slope of component cycles to the Slope of the price action, rewarding algorithms that successfully predict direction while suppressing those that fail.
This is a non-repainting, adaptive oscillator designed to identify market regimes, pinpoint high-probability reversals via OB/OS logic, and visualize the aggregate consensus of advanced signal processing mathematics.
1. The Core Philosophy: Why "Slope" Matters:
In technical analysis, most traders focus on Levels (Price is above X) or Values (RSI is at 70). However, the primary driver of price action is Momentum, which is mathematically defined as the Rate of Change, or the Slope.
This script introduces a novel approach: Slope Fitting.
Instead of asking "Is the cycle high or low?", this system asks: "Is the trajectory (Slope) of this cycle matching the trajectory of the price?"
The Dual-Functionality of the Normalized Oscillator
The final output is a normalized oscillator bounded between -1.0 and +1.0. This structure serves two critical functions simultaneously:
Directional Bias (The Slope):
When the Combined Cycle line is rising (Positive Slope), the aggregate consensus of the 13 algorithms suggests bullish momentum. When falling (Negative Slope), it suggests bearish momentum. The script measures how well these slopes correlate with price action over a rolling lookback window to assign confidence weights.
Overbought / Oversold (OB/OS) Identification:
Because the output is mathematically clipped and normalized:
Approaching +1.0 (Overbought): Indicates that the top-weighted algorithms have reached their theoretical maximum amplitude. This is a statistical extreme, often preceding a mean reversion or trend exhaustion.
Approaching -1.0 (Oversold): Indicates the aggregate cycle has reached maximum bearish extension, signaling a potential accumulation zone.
Zero Line (0.0): The equilibrium point. A cross of the Zero Line is the most traditional signal of a trend shift.
2. The "Mixture of Experts" (MoE) Architecture:
Markets are dynamic. Sometimes they trend (Trend Following works), sometimes they chop (Mean Reversion works), and sometimes they cycle cleanly (Signal Processing works). No single indicator works in all regimes.
This system solves that problem by running 13 Algorithms simultaneously and voting on the outcome.
The 13 "Experts" Inside the Code:
All algorithms have been engineered to be Non-Repainting.
Ehlers Bandpass Filter: Extracts cycle components within a specific frequency bandwidth.
Schaff Trend Cycle: A double-smoothed stochastic of the MACD, excellent for cycle turning points.
Fisher Transform: Normalizes prices into a Gaussian distribution to pinpoint turning points.
Zero-Lag EMA (ZLEMA): Reduces lag to track price changes faster than standard MAs.
Coppock Curve: A momentum indicator originally designed for long-term market bottoms.
Detrended Price Oscillator (DPO): Removes trend to isolate short-term cycles.
MESA Adaptive (Sine Wave): Uses Phase accumulation to detect cycle turns.
Goertzel Algorithm: Uses Digital Signal Processing (DSP) to detect the magnitude of specific frequencies.
Hilbert Transform: Measures the instantaneous position of the cycle.
Autocorrelation: measures the correlation of the current price series with a lagged version of itself.
SSA (Simplified): Singular Spectrum Analysis approximation (Lag-compensated, non-repainting).
Wavelet (Simplified): Decomposes price into approximation and detail coefficients.
EMD (Simplified): Empirical Mode Decomposition approximation using envelope theory.
3. The Adaptive "GBM" Learning Engine
This is the "Machine Learning" component of the script. It does not use pre-trained weights; it learns live on your chart.
How it works:
Fitting Window: On every bar, the system looks back 20 days (configurable).
Slope Correlation: It calculates the correlation between the Slope of each of the 13 algorithms and the Slope of the Price.
Directional Bonus: It checks if the algorithm is pointing in the same direction as the price.
Weight Optimization:
Algorithms that match the price direction and correlation receive a higher "Fit Score."
Algorithms that diverge from price action are penalized.
A "Softmax" style temperature function and memory decay allow the weights to shift smoothly but aggressively.
The Result: If the market enters a clean sine-wave cycle, the Ehlers and Goertzel weights will spike. If the market explodes into a linear trend, ZLEMA and Schaff will take over, suppressing the cycle indicators that would otherwise call for a premature top.
4. How to Read the Interface:
The visual interface is designed for maximum information density without clutter.
The Dashboard (Bottom Left - GBM Stats)
Combined Fit: A percentage score (0-100%). High values (>70%) mean the system is "Locked In" and tracking price accurately. Low values suggest market chaos/noise.
Entropy: A measure of disorder. High entropy means the algorithms disagree (Neutral/Chop). Low entropy means the algorithms are unanimous (Strong Trend).
Top 1 / Top 3 Weight: Shows how concentrated the decision is. If Top 1 Weight is 50%, one algorithm is dominating the decision.
The Matrix (Bottom Right - Weight Table)
This table lifts the hood on the engine.
Fit Score: How well this specific algo is performing right now.
Corr/Dir: Raw correlation and Direction Match stats.
Weight: The actual percentage influence this algorithm has on the final line.
Cycle: The current value of that specific algorithm.
Regime: Identifies if the consensus is Bullish, Bearish, or Neutral.
The Chart Overlay
The Line: The Gradient-Colored line is the Weighted Ensemble Prediction.
Green: Bullish Slope.
Red: Bearish Slope.
Triangles: Zero-Cross signals (Bullish/Bearish).
"STRONG" Labels: Appears when the cycle sustains a value above +0.5 or below -0.5, indicating strong momentum.
Background Color: Changes subtly to reflect the aggregate Regime (Strong Up, Bullish, Neutral, Bearish, Strong Down).
5. Trading Strategies:
A. The Slope Reversal (OB/OS Fade)
Concept: Catching tops and bottoms using the -1/+1 normalization.
Signal: Wait for the Combined Cycle to reach extreme values (>0.8 or <-0.8).
Trigger: The entry is taken not when it hits the level, but when the Slope flips.
Short: Cycle hits +0.9, color turns from Green to Red (Slope becomes negative).
Long: Cycle hits -0.9, color turns from Red to Green (Slope becomes positive).
B. The Zero-Line Trend Join
Concept: Joining an established trend after a correction.
Signal: Price is trending, but the Cycle pulls back to the Zero line.
Trigger: A "Triangle" signal appears as the cycle crosses Zero in the direction of the higher timeframe trend.
C. Divergence Analysis
Concept: Using the "Fit Score" to identify weak moves.
Signal: Price makes a Higher High, but the Combined Cycle makes a Lower High.
Confirmation: Check the GBM Stats table. If "Combined Fit" is dropping while price is rising, the trend is decoupling from the cycle logic. This is a high-probability reversal warning.
6. Technical Configuration:
Fitting Window (Default: 20): The number of bars the ML engine looks back to judge algorithm performance. Lower (10-15) for scalping/quick adaptation. Higher (30-50) for swing trading and stability.
GBM Learning Rate (Default: 0.25): Controls how fast weights change.
High (>0.3): The system reacts instantly to new behaviors but may be "jumpy."
Low (<0.15): The system is very smooth but may lag in regime changes.
Max Single Weight (Default: 0.55): Prevents one single algorithm from completely hijacking the system, ensuring an ensemble effect remains.
Slope Lookback: The period over which the slope (velocity) is calculated.
7. Disclaimer & Notes:
Repainting: This indicator utilizes closed bar data for calculations and employs non-repainting approximations of SSA, EMD, and Wavelets. It does not repaint historical signals.
Calculations: The "ML" label refers to the adaptive weighting algorithm (Gradient-based optimization), not a neural network black box.
Risk: No indicator guarantees future performance. The "Fit Score" is a backward-looking metric of recent performance; market regimes can shift instantly. Always use proper risk management.
Author's Note
The MCPS-Slope was built to solve the frustration of "indicator shopping." Instead of switching between an RSI, a MACD, and a Stochastic depending on the day, this system mathematically determines which one is working best right now and presents you with a single, synthesized data stream.
If you find this tool useful, please leave a Boost and a Comment below!
My Swiftlike Algo Backtest ATR SL/TP HH/HL/LH/LL BOS/CHOCHSwift-Like Algo is a trend-following strategy that trades pullbacks using EMA trend direction, market structure (HH/HL/LH/LL), and ATR-based risk management.
It enters only in the direction of the trend, with automatic Stop-Loss, TP1, and TP2, and supports full strategy backtesting.
Best used on 15m–4H timeframes for crypto, forex, and indices.
⚠️ For educational and testing purposes only.
Spearman Correlation🔗 Spearman Correlation – Ranked Relationship Tracker
Overview:
This indicator calculates and plots the Spearman Rank Correlation Coefficient between the current chart’s asset and a custom comparison ticker (the example shown is BTC vs the OTHERS market cap for crypto). Unlike Pearson correlation, which measures linear relationships, Spearman correlation captures monotonic (ranked) relationships—making it better suited for analysing assets that move in sync but not necessarily in a linear fashion.
🧠 What It Does:
Computes ranked correlation between two assets over a user-defined lookback period
Smooths the correlation curve for better readability
Visually shades the background by correlation strength and direction:
🟩 Strong Positive (+0.5 to +1)
🟨 Weak Positive (+0.1 to +0.5)
⬜ No Correlation (–0.1 to +0.1)
🟧 Weak Negative (–0.5 to –0.1)
🟥 Strong Negative (–1 to –0.5)
⚙️ User Inputs:
Lookback Period: Number of bars used to calculate correlation
Comparison Ticker: Choose any asset to compare against
Shading Toggles: Customize which correlation zones are highlighted
📈 Use Cases:
Identify evolving relationships between assets (e.g., BTC vs DXY, ETH vs SPX)
Spot when assets become inversely correlated or lose correlation entirely
Track regime shifts where traditional relationships break down or re-align
Use alongside trend or momentum strategies to add a cross-asset confirmation layer
🔍 Interpreting the Correlation:
+1 → Perfect positive (ranks match exactly)
+0.5 to +1 → Strong positive relationship
+0.1 to +0.5 → Weak but positive relationship
–0.1 to +0.1 → Essentially uncorrelated
–0.5 to –0.1 → Weak negative correlation
–1 to –0.5 → Strong inverse relationship
–1 → Perfect negative (rankings are completely opposite)
🧪 Technical Notes:
Calculation uses ranked returns to better reflect monotonic relationships
Smoothed with a simple moving average (SMA) for stability
Arrays are managed internally to maintain performance and adaptability
This script is ideal for traders seeking deeper insight into cross-asset dynamics, portfolio hedging, or timing divergence-based strategies.
Directional Comparisons - Two Tickers📊 Directional Comparisons – Two Tickers
Overview:
This tool allows you to visually and statistically compare the directional behaviour of any two assets on any chart timeframe. It identifies and color-codes each bar based on how both the current asset and your chosen comparison asset performed in that period (e.g., both up, both down, diverging). A statistical summary table dynamically updates in the corner of your chart, tracking the probability and streak performance of each condition.
🛠 How It Works:
Each candle is analysed and color-coded based on the relationship between the current chart's asset and a comparison asset of your choice:
✅ Green – Both tickers closed higher (bullish alignment)
🔻 Red – Both tickers closed lower (bearish alignment)
🔷 Blue – Current ticker up, comparison ticker down (positive divergence)
🟧 Orange – Current ticker down, comparison ticker up (negative divergence)
You can toggle each colour condition on/off independently.
📈 Statistical Table (Top Right):
For the candles in the visible chart range, the indicator displays:
The frequency (probability) of each condition
Longest, shortest, and average streaks for each condition
Average % change for both the current and comparison asset under each scenario
All stats auto-update as you zoom or scroll through the chart.
🔧 User Inputs:
Comparison Ticker: Choose any ticker symbol to compare against the current chart
Toggle Conditions: Enable or disable individual directional conditions (color-coded)
✅ Use Cases:
Spot high-probability alignment zones between two assets (e.g., BTC vs ETH, SPX vs VIX)
Identify divergence opportunities for trading signals
Analyse historical relationships and co-movements between assets
Perform correlation streak studies directly on the chart
🔍 Notes:
The script works across all timeframes (1min to monthly).
Stats only consider visible bars on your chart for responsiveness.
Ideal for pair traders, macro analysts, or anyone interested in cross-asset relationships.
Swift-like Algo (V1) Trend Pullback ATR Risk AlimojanidThis indicator is a simple, rule-based trend-following system designed to help identify potential LONG and SHORT opportunities using market structure, momentum, and volatility.
It is inspired by professional “algo-style” tools, but built from scratch for learning, transparency, and flexibility.
🔹 How it works
1️⃣ Trend Detection
Uses Fast EMA vs Slow EMA
Only looks for:
LONGs in bullish trends
SHORTs in bearish trends
2️⃣ Entry Logic
Waits for a pullback toward the fast EMA
Confirms direction using price behavior
Optional RSI filter to avoid weak momentum trades
3️⃣ Risk Management
Stop Loss (SL) and Take Profit (TP) levels are calculated using ATR
Risk is defined in R-multiples (TP1, TP2)
Designed to adapt to market volatility
4️⃣ Visual & Alerts
Clear LONG / SHORT arrows
Automatic SL / TP level plotting
Built-in alert conditions for trade notifications
⚙️ Settings You Can Adjust
EMA lengths (trend sensitivity)
RSI confirmation (on/off)
ATR stop size
Risk-reward targets
Cooldown bars to avoid over-trading
⚠️ Disclaimer
This indicator is NOT a guaranteed trading system and should not be used as financial advice.
Always:
Backtest on your own market and timeframe
Use proper risk management
Paper trade before using real funds
The author is not responsible for any trading losses.
💡 Notes
Best used on trending markets
Works on Forex, Crypto, Indices, and Commodities
Timeframes: 15m and higher recommended
EMA 8 48 System v1Short Description:
A trend-following indicator using EMA crossovers, ATR-based volatility filter, and a cooldown period to reduce false signals. Designed for clear buy/sell signals in trending markets.
Full Description:
What is this indicator?
This script implements a dual EMA crossover system (8-period and 48-period EMAs) with a trend filter (EMA200), ATR-based volatility filter, and a cooldown period to avoid overtrading.
It visually plots EMAs, buy/sell signals, and ATR-based stop loss/target levels.
Why is it useful?
Helps traders identify high-probability trend entries and avoid choppy, low-volatility conditions.
Reduces false signals by requiring trend confirmation, sufficient volatility, and spacing out trades.
Suitable for intraday and swing trading on most liquid assets.
When to use:
Best used in markets showing clear trends (not sideways).
Works on most timeframes, but higher timeframes (15m, 1h, 4h, daily) tend to give more reliable signals.
How to spot buy and sell:
Buy: Green “BUY” label appears when EMA8 crosses above EMA48, price is above EMA200, and ATR is above the minimum threshold.
Sell: Red “SELL” label appears when EMA8 crosses below EMA48, price is below EMA200, and ATR is above the minimum threshold.
ATR-based stop loss and target levels are plotted for each signal.
Additional tips:
Adjust the minimum ATR and cooldown settings to match your asset’s volatility and your trading style.
Use in conjunction with price action or higher timeframe analysis for best results.
Avoid trading during low volatility or sideways markets, as signals may be less reliable.
Always backtest and forward-test before using live.
How to add signals and update settings:
Use the script’s input panel to adjust EMA lengths, ATR settings, minimum ATR, and cooldown period.
To add alerts, use TradingView’s “Add Alert” feature and select the buy or sell conditions from the script’s alert options.
For further customization, you can edit the script to add additional filters or notification logic.
This indicator is for educational purposes only. Always use proper risk management and do your own research before trading.
Disclaimer:
This script is for informational and educational purposes only and does not constitute financial advice or a recommendation to buy or sell any financial instrument.
Trading involves risk. Past performance is not indicative of future results. Always do your own research and use proper risk management.
The author is not responsible for any losses incurred from the use of this script. By using this script, you agree to take full responsibility for your trading decisions.
Micro Futures Risk Calculator (Minimal)risk calculator based off of stop distance. to keep risk consistent for consistent growth
Rolling DrawdownRolling Drawdown, trying to get an auto updating drawdown. work in progress. will edit in future
Crypto Session Range 📄 INDICATOR DESCRIPTION (ENGLISH)
Crypto Session Range (Custom Timezone) is a lightweight and accurate session-based indicator designed specifically for cryptocurrency markets (24/7).
This indicator allows traders to define custom trading time windows using any global timezone, solving common issues found in traditional session indicators that are built for stock markets.
🔹 Key Features
Custom timezone support (e.g. America/Puerto_Rico, America/New_York, UTC)
Up to 3 configurable trading sessions
Visual background highlighting during active sessions
Automatic High & Low range tracking for each session
Optional range extension after the session ends
Works on all crypto pairs and timeframes
🔹 Who Is This For?
Crypto traders who want precise session control
Day traders, scalpers, and session-based strategies
Traders who operate during specific market windows (London / NY / custom)
🔹 Notes
This indicator is not restricted to exchange trading hours and is fully compatible with 24/7 markets like crypto, unlike many default session tools.
Trap longs - Hamza Naveed// This source code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org
//@version=5
indicator("Trap Longs - Hamza Naveed", max_labels_count = 500, overlay = false, format = format.volume)
g1 = '📊 Net Positions '
g2 = '📈 Moving Averages (VWMA/EMA) '
g3 = '⚙️ Additional Settings '
g4 = '🎚️ Profile '
g5 = '🖥️ Statistics '
g6 = '⚖️ Divergences'
// User inputs - General settings
dtype = input.string('Net Positions', 'Type', options = )
disp = input.string('Candles', 'Display as', options = )
cumu = input.string('Full Data', 'Cumulation', options = )
denom = input.string('Quote Currency', 'Quoted in', options = )
// User inputs - Data Source Settings
binance = input.bool(true, 'Binance USDT.P', inline = 'src')
binance2 = input.bool(true, 'Binance USD.P', inline = 'src')
binance3 = input.bool(true, 'Binance BUSD.P', inline = 'src2')
bitmex = input.bool(true, 'BitMEX USD.P', inline = 'src2')
bitmex2 = input.bool(true, 'BitMEX USDT.P ', inline = 'src3')
kraken = input.bool(true, 'Kraken USD.P', inline = 'src3')
// User inputs - Net Positions
showL = input.bool(true, 'NET LONGS ►', group = g1, inline='l')
showS = input.bool(false, 'NET SHORTS ►', group = g1, inline='s')
showD = input.bool(false, 'NET DELTA ►', group = g1, inline='d')
showR = input.bool(false, 'NET RATIO ►', group = g1, inline='r')
pcolL = input.color(#a5d6a7, '', group = g1, inline = 'l')
ncolL = input.color(#f77c80, '', group = g1, inline = 'l')
lcolL = input.color(#a5d6a7, '━', group = g1, inline = 'l')
pcolS = input.color(#a5d6a7, '', group = g1, inline = 's')
ncolS = input.color(#f77c80, '', group = g1, inline = 's')
lcolS = input.color(#faa1a4, '━', group = g1, inline = 's')
pcolD = input.color(#a5d6a7, '', group = g1, inline = 'd')
ncolD = input.color(#f77c80, '', group = g1, inline = 'd')
lcolD = input.color(#90bff9, '━', group = g1, inline = 'd')
pcolR = input.color(#a5d6a7, '', group = g1, inline = 'r')
ncolR = input.color(#f77c80, '', group = g1, inline = 'r')
lcolR = input.color(#f9d690, '━', group = g1, inline = 'r')
// User inputs - Net Positions EMAs
mat = input.string('VWMA', 'Type', options= , group=g2)
emaL = input.bool(false, 'LONGS ', group=g2, inline='emal')
emaS = input.bool(false, 'SHORTS ', group=g2, inline='emas')
emaD = input.bool(false, 'DELTA ',group=g2, inline='emad')
emaR = input.bool(false, 'RATIO ',group=g2, inline='emar')
emaLl = input.int(100, '', group=g2, inline='emal')
emaSl = input.int(100, '', group=g2, inline='emas')
emaDl = input.int(100, '', group=g2, inline='emad')
emaRl = input.int(100, '', group=g2, inline='emar')
emaLc = input.color(color.rgb(165, 214, 167, 60), '', group=g2, inline='emal')
emaSc = input.color(color.rgb(250, 161, 164, 60), '', group=g2, inline='emas')
emaDc = input.color(color.rgb(144, 191, 249, 60), '', group=g2, inline='emad')
emaRc = input.color(color.rgb(249, 214, 144, 60), '', group=g2, inline='emar')
// User inputs - Additional settings
volhm = input.bool(false, 'Volume HM', group=g3, inline='vol')
volc2 = input.color(color.rgb(49, 121, 245),'', group=g3, inline = 'vol')
offs = input.int (10, 'Label Offset', group=g3)
length = input.int (14, 'Position RSI Length', group=g3)
vlbl = input.bool(true, 'Value Labels', group=g3, inline='lv')
nlbl = input.bool(true, 'Data Labels', group=g3, inline='lv')
wick = input.bool(false, 'Show Candle Wicks', group=g3)
// User inputs - Profile settings
prof = input.bool (false, 'Generate a profile', group=g4)
profsrc = input.string('Net Longs', 'Profile Data', options = , group=g4)
vapct = input.float (70, 'Value Area %', minval = 5, maxval = 95, group = g4)
ori = input.string("Left", 'Position', options = , group = g4)
profSize = input.int (2, 'Node Size', minval = 1, group = g4)
rows = input.int (40, 'Rows', minval = 6, maxval = 500, step = 25, group = g4) - 1
vancol = input.color (color.new(color.blue, 75), 'Node Colors ', group = g4, inline = 'nc')
nvancol = input.color (color.new(color.gray, 75), '━', group = g4, inline = 'nc')
poc = input.bool (false, 'POC', group = g4, inline = 'POC'),
poccol = input.color (color.new(color.red, 50), ' ', group = g4, inline = "POC")
val = input.bool (false, 'VA', group = g4, inline = "VA")
vafill = input.color (color.new(color.blue, 95), ' ', group = g4, inline = 'VA')
// User inputs - Statistics
stats = input.bool(false, 'Show Stats', group = g5)
chg_b = input.int(50, 'Bars Back', group = g5)
tablevpos = input.string('Horizontal', 'Orientation', options= , group = g5)
tablepos = input.string('Bottom Center', 'Position', options= , group = g5)
stat_oi = input.bool(true, 'OI ━', group = g5, inline = 'oi')
stat_nl = input.bool(true, 'NL ━', group = g5, inline = 'nl')
stat_ns = input.bool(true, 'NS ━', group = g5, inline = 'ns')
stat_nd = input.bool(true, 'ND ━', group = g5, inline = 'nd')
stat_oi_c = input.bool(true, 'OI Change ━', group = g5, inline = 'oi')
stat_nl_c = input.bool(true, 'NL Change ━', group = g5, inline = 'nl')
stat_ns_c = input.bool(true, 'NS Change ━', group = g5, inline = 'ns')
stat_nd_c = input.bool(true, 'ND Change ━', group = g5, inline = 'nd')
stat_oi_r = input.bool(true, 'OI RSI', group = g5, inline = 'oi')
stat_nl_r = input.bool(true, 'NL RSI', group = g5, inline = 'nl')
stat_ns_r = input.bool(true, 'NS RSI', group = g5, inline = 'ns')
stat_nd_r = input.bool(true, 'ND RSI', group = g5, inline = 'nd')
// User inputs - Divergence Finder
showdiv = input.bool(false, 'Divergence finder', group = g6)
divsrc = input.string('Net Longs', 'Source', options = , group=g6)
pivotDistance = input.int(5, 'Maximum Distance', minval=0, group=g6)
leftPivot = input.int(8, 'Lookback Bars Left', minval=1, group=g6)
rightPivot = input.int(8, 'Lookback Bars Right', minval=1, group=g6)
pHH_npLH = input.bool(true, 'Price HH + Data LH', group = g6, inline='div1')
pLH_npHH = input.bool(true, 'Price LH + Data HH', group = g6, inline='div2')
pLL_npHL = input.bool(true, 'Price LL + Data HL ', group = g6, inline='div3')
pHL_npLL = input.bool(true, 'Price HL + Data LL ', group = g6, inline='div4')
pHH_npLHcol = input.color(color.red, '', group = g6, inline='div1')
pLH_npHHcol = input.color(color.red, '', group = g6, inline='div2')
pLL_npHLcol = input.color(color.green, '', group = g6, inline='div3')
pHL_npLLcol = input.color(color.green, '', group = g6, inline='div4')
// Getting OI data
mex = syminfo.basecurrency=='BTC' ? 'XBT' : string(syminfo.basecurrency)
= request.security('BINANCE' + ":" + string(syminfo.basecurrency) + 'USDT.P_OI', timeframe.period, [close-close , close], ignore_invalid_symbol = true)
= request.security('BINANCE' + ":" + string(syminfo.basecurrency) + 'USD.P_OI', timeframe.period, [close-close , close], ignore_invalid_symbol = true)
= request.security('BINANCE' + ":" + string(syminfo.basecurrency) + 'BUSD.P_OI', timeframe.period, [close-close , close], ignore_invalid_symbol = true)
= request.security('BITMEX' + ":" + mex + 'USD.P_OI', timeframe.period, [close-close , close], ignore_invalid_symbol = true)
= request.security('BITMEX' + ":" + mex + 'USDT.P_OI', timeframe.period, [close-close , close], ignore_invalid_symbol = true)
= request.security('KRAKEN' + ":" + string(syminfo.basecurrency) + 'USD.P_OI', timeframe.period, [close-close , close], ignore_invalid_symbol = true)
deltaOI = (binance ? nz(oid1,0) : 0) + (binance2 ? nz(oid2,0)/close : 0) + (binance3 ? nz(oid3,0) : 0) + (bitmex ? nz(oid4,0)/close : 0) + (bitmex2 ? nz(oid5,0)/close : 0) + (kraken ? nz(oid6,0)/close : 0)
OI = (binance ? nz(oi1,0) : 0) + (binance2 ? nz(oi2,0)/close : 0) + (binance3 ? nz(oi3,0) : 0) + (bitmex ? nz(oi4,0)/close : 0) + (bitmex2 ? nz(oi5,0)/close : 0) + (kraken ? nz(oi6,0)/close : 0)
// Conditions for positions entering and exiting
priceUP = close>open
priceDOWN = close0
oiDOWN = deltaOI<0
newlongs = oiUP and priceUP
rektlongs = oiDOWN and priceDOWN
newshorts = oiUP and priceDOWN
rektshorts = oiDOWN and priceUP
// Visible range
vrc = cumu=='Visible Range' ? time > chart.left_visible_bar_time and time <= chart.right_visible_bar_time : true
// Cumulation of positions entering and exiting
longs_entering = ta.cum(newlongs and vrc ? (denom=='Base Currency' ? deltaOI : deltaOI * close) : 0)
longs_exiting = ta.cum(rektlongs and vrc ? (denom=='Base Currency' ? deltaOI : deltaOI * close) : 0)
shorts_entering = ta.cum(newshorts and vrc ? (denom=='Base Currency' ? deltaOI : deltaOI * close) : 0)
shorts_exiting = ta.cum(rektshorts and vrc ? (denom=='Base Currency' ? deltaOI : deltaOI * close) : 0)
// Output data
net_longs = longs_entering - math.abs(longs_exiting)
net_shorts = shorts_entering - math.abs(shorts_exiting)
net_delta = net_longs - net_shorts
net_ratio = net_longs / net_shorts
// Calculating Relative Strength
longs_strength = ta.rsi(net_longs, length)
shorts_strength = ta.rsi(net_shorts, length)
delta_strength = ta.rsi(net_delta, length)
ratio_strength = ta.rsi(net_ratio, length)
oi_strength = ta.rsi(OI, length)
// Calculating candle OHLC
src = dtype=='Net Positions' ? net_longs : longs_strength
OpenL = wick ? ta.sma(src , 2) : src
HighL = ta.highest(src, 1)
LowL = ta.lowest(src, 1)
CloseL = wick ? ta.sma(src, 2) : src
src2 = dtype=='Net Positions' ? net_shorts : shorts_strength
OpenS = wick ? ta.sma(src2 , 2) : src2
HighS = ta.highest(src2, 1)
LowS = ta.lowest(src2, 1)
CloseS = wick ? ta.sma(src2, 2) : src2
src3 = dtype=='Net Positions' ? net_delta : delta_strength
OpenD = wick ? ta.sma(src3 , 2) : src3
HighD = ta.highest(src3, 1)
LowD = ta.lowest(src3, 1)
CloseD = wick ? ta.sma(src3, 2) : src3
src4 = dtype=='Net Positions' ? net_ratio : ratio_strength
OpenR = wick ? ta.sma(src4 , 2) : src4
HighR = ta.highest(src4, 1)
LowR = ta.lowest(src4, 1)
CloseR = wick ? ta.sma(src4, 2) : src4
// Calculating EMAs
Lema = mat=='EMA' ? ta.ema(src, emaLl) : ta.vwma(src, emaLl)
Sema = mat=='EMA' ? ta.ema(src2, emaSl) : ta.vwma(src2, emaSl)
Dema = mat=='EMA' ? ta.ema(src3, emaDl) : ta.vwma(src3, emaDl)
Rema = mat=='EMA' ? ta.ema(src4, emaRl) : ta.vwma(src4, emaRl)
// Conditions
lcondL = showL and (disp=='Line' or disp=='Columns'), ccondL = showL and disp=='Candles'
lcondS = showS and (disp=='Line' or disp=='Columns'), ccondS = showS and disp=='Candles'
lcondD = showD and (disp=='Line' or disp=='Columns'), ccondD = showD and disp=='Candles'
lcondR = showR and (disp=='Line' or disp=='Columns'), ccondR = showR and disp=='Candles'
// Plotting Lines
plot(lcondL ? src : na, title="Net Longs", color=disp=='Line' ? lcolL : (net_longs >0 ? pcolL : ncolL), linewidth=1, style = disp=='Line' ? plot.style_line : disp=='Columns' ? plot.style_columns : na, editable = false)
plot(lcondS ? src2 : na, title="Net Shorts", color=disp=='Line' ? lcolS : (net_shorts >0 ? pcolS : ncolS), linewidth=1, style = disp=='Line' ? plot.style_line : disp=='Columns' ? plot.style_columns : na, editable = false)
plot(lcondD ? src3 : na, title="Net Shorts", color=disp=='Line' ? lcolD : (net_delta >0 ? pcolD : ncolD), linewidth=1, style = disp=='Line' ? plot.style_line : disp=='Columns' ? plot.style_columns : na, editable = false)
plot(lcondR ? src4 : na, title="Net Ratio", color=disp=='Line' ? lcolR : (net_ratio >0 ? pcolR : ncolR), linewidth=1, style = disp=='Line' ? plot.style_line : disp=='Columns' ? plot.style_columns : na, editable = false)
// Plotting Candles
plotcandle(ccondL ? OpenL : na, ccondL ? HighL : na, ccondL ? LowL : na, ccondL ? CloseL : na, "Longs", CloseL>OpenL ? pcolL : ncolL, CloseL>OpenL ? pcolL : ncolL, false, bordercolor = CloseL>OpenL ? pcolL : ncolL)
plotcandle(ccondS ? OpenS : na, ccondS ? HighS : na, ccondS ? LowS : na, ccondS ? CloseS : na, "Shorts", CloseS>OpenS ? pcolS : ncolS, CloseS>OpenS ? pcolS : ncolS, false, bordercolor = CloseS>OpenS ? pcolS : ncolS)
plotcandle(ccondD ? OpenD : na, ccondD ? HighD : na, ccondD ? LowD : na, ccondD ? CloseD : na, "Delta", CloseD>OpenD ? pcolD : ncolD, CloseD>OpenD ? pcolD : ncolD, false, bordercolor = CloseD>OpenD ? pcolD : ncolD)
plotcandle(ccondR ? OpenR : na, ccondR ? HighR : na, ccondR ? LowR : na, ccondR ? CloseR : na, "Ratio", CloseR>OpenR ? pcolR : ncolR, CloseR>OpenR ? pcolR : ncolR, false, bordercolor = CloseR>OpenR ? pcolR : ncolR)
// Plotting EMAs
plot(emaL ? Lema : na, color=emaLc, editable = false)
plot(emaS ? Sema : na, color=emaSc, editable = false)
plot(emaD ? Dema : na, color=emaDc, editable = false)
plot(emaR ? Rema : na, color=emaRc, editable = false)
// Plotting Relative Strength
plot(dtype=='Position RSI' ? 100 : na, color=color.rgb(120, 123, 134, 90), title = 'RSI 100')
plot(dtype=='Position RSI' ? 70 : na, color=color.rgb(120, 123, 134, 72), title = 'RSI 70')
plot(dtype=='Position RSI' ? 50 : na, color=color.rgb(120, 123, 134, 90), title = 'RSI 50')
plot(dtype=='Position RSI' ? 30 : na, color=color.rgb(120, 123, 134, 72), title = 'RSI 30')
plot(dtype=='Position RSI' ? 0 : na, color=color.rgb(120, 123, 134, 90), title = 'RSI 0')
// Volume Heatmap
vol = volume
volmax = ta.highest(volume, 50)
col = color.from_gradient(volume, 0, volmax, chart.bg_color, volc2)
plotshape(time>chart.left_visible_bar_time and volhm, style=shape.square, size=size.normal,location = location.bottom, color=col, editable = false)
// Labels
if vlbl and disp=='Candles'
vLlabel = showL ? label.new(bar_index, CloseL>OpenL ? HighL : LowL, newlongs or rektlongs ? str.tostring(deltaOI, format.volume) : na, size = size.auto, color=color.rgb(255, 255, 255, 100), textcolor = chart.fg_color, style = CloseL>OpenL ? label.style_label_down : label.style_label_up) : na
vSlabel = showS ? label.new(bar_index, CloseS>OpenS ? HighS : LowS, newshorts or rektshorts ? str.tostring(deltaOI, format.volume) : na, size = size.auto, color=color.rgb(255, 255, 255, 100), textcolor = chart.fg_color, style = CloseS>OpenS ? label.style_label_down : label.style_label_up) : na
vDlabel = showD ? label.new(bar_index, CloseD>OpenD ? HighD : LowD, str.tostring(deltaOI, format.volume), size = size.auto, color=color.rgb(255, 255, 255, 100), textcolor = chart.fg_color, style = CloseD>OpenD ? label.style_label_down : label.style_label_up) : na
vRlabel = showR ? label.new(bar_index, CloseR>OpenR ? HighR : LowR, str.tostring(deltaOI, format.volume), size = size.auto, color=color.rgb(255, 255, 255, 100), textcolor = chart.fg_color, style = CloseR>OpenR ? label.style_label_down : label.style_label_up) : na
if nlbl and disp!='Columns'
Llabel = showL ? label.new(bar_index+offs, src, 'NET LONGS', size = size.tiny, color=lcolL, textcolor = color.black, style = label.style_label_left) : na
Slabel = showS ? label.new(bar_index+offs, src2, 'NET SHORTS', size = size.tiny, color=lcolS, textcolor = color.black, style = label.style_label_left) : na
Dlabel = showD ? label.new(bar_index+offs, src3, 'NET DELTA', size = size.tiny, color=lcolD, textcolor = color.black, style = label.style_label_left) : na
Rlabel = showR ? label.new(bar_index+offs, src4, 'NET RATIO', size = size.tiny, color=lcolR, textcolor = color.black, style = label.style_label_left) : na
label.delete(Llabel )
label.delete(Slabel )
label.delete(Dlabel )
label.delete(Rlabel )
// Generating a profile - Code from @KioseffTrading's "Profile Any Indicator" script (used with their permission)
srcp = profsrc=='Net Longs' ? src : profsrc=='Net Shorts' ? src2 : profsrc=='Net Delta' ? src3 : src4
var int timeArray = array.new_int()
var float dist = array.new_float()
var int x2 = array.new_int(rows + 1, 5)
var vh = matrix.new(1, 1)
array.unshift(timeArray, math.round(time))
if prof and time >= chart.left_visible_bar_time and time <= chart.right_visible_bar_time
matrix.add_col(vh)
matrix.set(vh, 0, matrix.columns(vh) - 1, srcp)
if prof and barstate.islast
= switch ori
"Left" =>
=>
calc = (matrix.max(vh) - matrix.min(vh)) / (rows + 1)
for i = 0 to rows
array.push(dist, matrix.min(vh) + (i * calc))
for i = 1 to matrix.columns(vh) - 1
for x = 0 to array.size(dist) - 1
if matrix.get(vh, 0, i) >= matrix.get(vh, 0, i - 1)
if array.get(dist, x) >= matrix.get(vh, 0, i - 1) and array.get(dist, x) <= matrix.get(vh, 0, i)
array.set(x2, x, array.get(x2, x) + profSize)
else
if array.get(dist, x) >= matrix.get(vh, 0, i) and array.get(dist, x) <= matrix.get(vh, 0, i - 1)
array.set(x2, x, array.get(x2, x) + profSize)
boc = array.new_box()
for i = 1 to rows
right = array.get(timeArray, n + array.get(x2, i))
if ori == "Left"
switch math.sign(n - array.get(x2, i))
-1 => right := chart.right_visible_bar_time
=> right := array.get(timeArray, n - array.get(x2, i))
array.push(boc, box.new(pos, array.get(dist, i - 1),
right, array.get(dist, i), xloc = xloc.bar_time, border_color =
nvancol, bgcolor = nvancol
))
if i == rows
array.push(boc, box.new(pos, array.get(dist, array.size(dist) - 1),
right, array.get(dist, array.size(dist) - 1) + calc, xloc = xloc.bar_time, border_color =
nvancol, bgcolor = nvancol
))
array.shift(x2), nx = array.indexof(x2, array.max(x2))
nz = nx - 1, nz2 = 0, nz3 = 0, nz4 = 0
for i = 0 to array.size(x2) - 1
if nz > -1 and nx <= array.size(x2) - 1
switch array.get(x2, nx) >= array.get(x2, nz)
true => nz2 += array.get(x2, nx), nx += 1
=> nz2 += array.get(x2, nz), nz -= 1
else if nz <= -1
nz2 += array.get(x2, nx), nx += 1
else if nx >= array.size(x2)
nz2 += array.get(x2, nz), nz -= 1
if nz2 >= array.sum(x2) * (vapct / 100)
nz3 := nx <= array.size(x2) - 1 ? nx : array.size(x2) - 1, nz4 := nz <= -1 ? 0 : nz
break
for i = nz3 to nz4
box.set_border_color(array.get(boc, i), vancol)
box.set_bgcolor(array.get(boc, i), vancol)
if poc
var pocL = line(na)
y = math.avg(box.get_top(array.get(boc, array.indexof(x2, array.max(x2)))), box.get_bottom(array.get(boc, array.indexof(x2, array.max(x2)))))
if na(pocL)
pocL := line.new(chart.left_visible_bar_time, y, chart.right_visible_bar_time, y, xloc = xloc.bar_time, color = poccol, width = 1)
else
line.set_xy1(pocL, chart.left_visible_bar_time, y)
line.set_xy2(pocL, chart.right_visible_bar_time, y)
if val
var vaup = line(na), var vadn = line(na)
ydn = box.get_bottom(array.get(boc, nz3)), yup = box.get_top(array.get(boc, nz4))
if na(vaup)
vadn := line.new(chart.left_visible_bar_time, ydn, chart.right_visible_bar_time, ydn, xloc = xloc.bar_time, color = vancol, width = 1)
vaup := line.new(chart.left_visible_bar_time, yup, chart.right_visible_bar_time, yup, xloc = xloc.bar_time, color = vancol, width = 1)
else
line.set_xy1(vadn, chart.left_visible_bar_time, ydn), line.set_xy2(vadn, chart.right_visible_bar_time, ydn)
line.set_xy1(vaup, chart.left_visible_bar_time, yup), line.set_xy2(vaup, chart.right_visible_bar_time, yup)
linefill.new(vadn, vaup, vafill)
//Generating tables for Stats
switchpos(tablepos) =>
switch tablepos
'Top Left' => position.top_left
'Top Center' => position.top_center
'Top Right' => position.top_right
'Bottom Left' => position.bottom_left
'Bottom Center' => position.bottom_center
'Bottom right' => position.bottom_right
dataTable = table.new(switchpos(tablepos), columns=15, rows=15, bgcolor=color.rgb(120, 123, 134, 56))
fill_rows(cond, txt, c, r) =>
if cond
table.cell(table_id=dataTable, column = tablevpos=='Horizontal' ? c : 0, row = tablevpos=='Horizontal' ? 0 : r, text = txt, height=0, text_color=color.white, text_halign=text.align_center, text_valign= text.align_center)
if barstate.islast and stats and dtype!='Position RSI'
txt = ' •𝗢𝗜: ' + (denom=='Quote Currency' ? '$' : '') + str.tostring(denom=='Base Currency' ? OI : OI*close, format = format.volume) + ' ' + (denom=='Base Currency' ? str.tostring(string(syminfo.basecurrency)) : '')
txt2 = ' •𝗡𝗟: ' + (denom=='Quote Currency' ? '$' : '') + str.tostring(net_longs, format = format.volume) + ' ' + (denom=='Base Currency' ? str.tostring(string(syminfo.basecurrency)) : '')
txt3 = ' •𝗡𝗦: ' + (denom=='Quote Currency' ? '$' : '') + str.tostring(net_shorts, format = format.volume) + ' ' + (denom=='Base Currency' ? str.tostring(string(syminfo.basecurrency)) : '')
txt4 = ' •𝗡𝗗: ' + (denom=='Quote Currency' ? '$' : '') + str.tostring(net_delta, format = format.volume) + ' ' + (denom=='Base Currency' ? str.tostring(string(syminfo.basecurrency)) : '')
txt5 = ' •𝗢𝗜𝗖: ' + (denom=='Quote Currency' ? '$' : '') + str.tostring(denom=='Base Currency' ? OI-OI : (OI-OI ) * close, format = format.volume) + ' ' + (denom=='Base Currency' ? str.tostring(string(syminfo.basecurrency)) : '')
txt6 = ' •𝗡𝗟𝗖: ' + (denom=='Quote Currency' ? '$' : '') + str.tostring(net_longs - net_longs , format = format.volume) + ' ' + (denom=='Base Currency' ? str.tostring(string(syminfo.basecurrency)) : '')
txt7 = ' •𝗡𝗦𝗖: ' + (denom=='Quote Currency' ? '$' : '') + str.tostring(net_shorts - net_shorts , format = format.volume) + ' ' + (denom=='Base Currency' ? str.tostring(string(syminfo.basecurrency)) : '')
txt8 = ' •𝗡𝗗𝗖: ' + (denom=='Quote Currency' ? '$' : '') + str.tostring(net_delta - net_delta , format = format.volume) + ' ' + (denom=='Base Currency' ? str.tostring(string(syminfo.basecurrency)) : '')
txt9 = ' •𝗢𝗜 𝗥𝗦𝗜: ' + str.tostring(math.round(oi_strength,1))
txt10 = ' •𝗡𝗟 𝗥𝗦𝗜: ' + str.tostring(math.round(longs_strength,1))
txt11 = ' •𝗡𝗦 𝗥𝗦𝗜: ' + str.tostring(math.round(shorts_strength, 1))
txt12 = ' •𝗡𝗗 𝗥𝗦𝗜: ' + str.tostring(math.round(delta_strength, 1))
fill_rows(stat_oi, txt, 0, 0)
fill_rows(stat_nl, txt2, 1, 1)
fill_rows(stat_ns, txt3, 2, 2)
fill_rows(stat_nd, txt4, 3, 3)
fill_rows(stat_oi_c, txt5, 4, 4)
fill_rows(stat_nl_c, txt6, 5, 5)
fill_rows(stat_ns_c, txt7, 6, 6)
fill_rows(stat_nd_c, txt8, 7, 7)
fill_rows(stat_oi_r, txt9, 8, 8)
fill_rows(stat_nl_r, txt10, 9, 9)
fill_rows(stat_ns_r, txt11, 10, 10)
fill_rows(stat_nd_r, txt12, 11, 11)
// Divergence Finder
switchdivsrc(divsrc) =>
switch divsrc
'Net Longs' => src
'Net Shorts' => src2
'Net Delta' => src3
'Net Ratio' => src4
np = switchdivsrc(divsrc)
var priceHigh = array.new_float(0), var priceLow = array.new_float(0)
var priceHighIndex = array.new_int (0), var priceLowIndex = array.new_int (0)
var npHigh = array.new_float(0), var npLow = array.new_float(0)
var npHighIndex = array.new_int (0), var npLowIndex = array.new_int (0)
var priceHighTrend = 0, var priceLowTrend = 0
var npHighTrend = 0, var npLowTrend = 0
bool closeRecentHighs = false, bool closeOldHighs = false
bool closeHighs = false, bool closeRecentLows = false
bool closeOldLows = false, bool closeLows = false
curPriceHigh = ta.pivothigh(close, leftPivot, rightPivot)
curPriceLow = ta.pivotlow (close, leftPivot, rightPivot)
curnpHigh = ta.pivothigh(np, leftPivot, rightPivot)
curnpLow = ta.pivotlow (np, leftPivot, rightPivot)
if not na(curPriceHigh)
array.push(priceHigh, curPriceHigh)
array.push(priceHighIndex, bar_index-rightPivot)
if not na(curPriceLow)
array.push(priceLow, curPriceLow)
array.push(priceLowIndex, bar_index-rightPivot)
if not na(curnpHigh)
array.push(npHigh, curnpHigh)
array.push(npHighIndex, bar_index-rightPivot)
if not na(curnpLow)
array.push(npLow, curnpLow)
array.push(npLowIndex, bar_index-rightPivot)
if showdiv
if array.size(priceHigh) >= 2 and not na(curPriceHigh)
if array.get(priceHigh, array.size(priceHigh)-1) >= array.get(priceHigh, array.size(priceHigh)-2)
priceHighTrend := 1
else
priceHighTrend := -1
if array.size(priceLow) >= 2 and not na(curPriceLow)
if array.get(priceLow, array.size(priceLow)-1) >= array.get(priceLow, array.size(priceLow)-2)
priceLowTrend := 1
else
priceLowTrend := -1
if array.size(npHigh) >= 2 and not na(curnpHigh)
if array.get(npHigh, array.size(npHigh)-1) >= array.get(npHigh, array.size(npHigh)-2)
npHighTrend := 1
else
npHighTrend := -1
if array.size(npLow) >= 2 and not na(curnpLow)
if array.get(npLow, array.size(npLow)-1) >= array.get(npLow, array.size(npLow)-2)
npLowTrend := 1
else
npLowTrend := -1
if array.size(priceHighIndex) >= 2 and array.size(npHighIndex) >=2
closeRecentHighs := math.abs(array.get(priceHighIndex, array.size(priceHighIndex)-1) - array.get(npHighIndex, array.size(npHighIndex)-1)) <= pivotDistance
closeOldHighs := math.abs(array.get(priceHighIndex, array.size(priceHighIndex)-2) - array.get(npHighIndex, array.size(npHighIndex)-2)) <= pivotDistance
closeHighs := closeRecentHighs and closeOldHighs
if array.size(priceLowIndex) >= 2 and array.size(npLowIndex) >=2
closeRecentLows := math.abs(array.get(priceLowIndex, array.size(priceLowIndex)-1) - array.get(npLowIndex, array.size(npLowIndex)-1)) <= pivotDistance
closeOldLows := math.abs(array.get(priceLowIndex, array.size(priceLowIndex)-2) - array.get(npLowIndex, array.size(npLowIndex)-2)) <= pivotDistance
closeLows := closeRecentLows and closeOldLows
bool uptrendExhuastion = closeHighs and priceHighTrend > 0 and npHighTrend < 0 and (not na(curnpHigh) or not na(curPriceHigh))
bool uptrendAbsorption = closeHighs and priceHighTrend < 0 and npHighTrend > 0 and (not na(curnpHigh) or not na(curPriceHigh))
bool downtrendExhuastion = closeLows and priceLowTrend < 0 and npLowTrend > 0 and (not na(curnpLow) or not na(curPriceLow))
bool downtrendAbsorption = closeLows and priceLowTrend > 0 and npLowTrend < 0 and (not na(curnpLow) or not na(curPriceLow))
drawDiv(time1, price1, time2, price2, type) =>
dcol = type == 'Uptrend Exhuastion' ? pHH_npLHcol : type == 'Uptrend Absorption' ? pLH_npHHcol : type == 'Downtrend Exhaustion' ? pLL_npHLcol : type == 'Downtrend Absorption' ? pHL_npLLcol : na
line.new(x1=time1, y1=price1, x2=time2, y2=price2, color=dcol, width=1)
if uptrendAbsorption or uptrendExhuastion and showdiv
highTime1 = array.get(npHighIndex, array.size(npHighIndex)-1)
highPrice1 = array.get(npHigh, array.size(npHigh)-1)
highTime2 = array.get(npHighIndex, array.size(npHighIndex)-2)
highPrice2 = array.get(npHigh, array.size(npHigh)-2)
if uptrendExhuastion and pHH_npLH
drawDiv(highTime1, highPrice1, highTime2, highPrice2, 'Uptrend Exhuastion')
if uptrendAbsorption and pLH_npHH
drawDiv(highTime1, highPrice1, highTime2, highPrice2, 'Uptrend Absorption')
if downtrendAbsorption or downtrendExhuastion and showdiv
lowTime1 = array.get(npLowIndex, array.size(npLowIndex)-1)
lowPrice1 = array.get(npLow, array.size(npLow)-1)
lowTime2 = array.get(npLowIndex, array.size(npLowIndex)-2)
lowPrice2 = array.get(npLow, array.size(npLow)-2)
if downtrendExhuastion and pLL_npHL
drawDiv(lowTime1, lowPrice1, lowTime2, lowPrice2, 'Downtrend Exhuastion')
if downtrendAbsorption and pHL_npLL
drawDiv(lowTime1, lowPrice1, lowTime2, lowPrice2, 'Downtrend Absorption')
Segment 4h modifiable via inputsSegment 4h modifiable via inputs : pour positionner un segment n'importe ou en modifiant le prix pour la hauteur dans la configuration et déplaçable facilement à la souris temporellement.
4-hour segment modifiable via inputs: to position a segment anywhere by modifying the price for the height in the configuration and easily movable with the mouse in terms of time
SMA by EVEV Simple Moving Average (SMA) is a lightweight, open-source SMA indicator with configurable length, price source, and visual offset. It is designed to provide a clean moving-average reference for trend context and mean reversion workflows on any market and timeframe. The offset parameter shifts the plotted line for visualization only and does not affect the underlying calculation.
Adaptive Log Trend Zones + Retest SignalsAdaptive Log Trend Zones + Retest Signals
Adaptive Log Trend Zones is a trend-following overlay built to identify high-probability breakout retests in strong market conditions. It combines logarithmic regression , volatility-adaptive behavior , and ATR-based trend zones to help traders stay aligned with dominant momentum while avoiding chop.
🔹 Core Features
Logarithmic Regression Midline
Uses linear regression on log price to better handle exponential market moves
Produces smoother, more realistic trend structure on higher timeframes
Volatility-Adaptive Lookback
Automatically expands or contracts the regression length based on ATR volatility
Reacts faster in high volatility, smoother in consolidation
Dynamic Trend Zones
Upper and lower bands are ATR-adjusted and trend-colored
Optional future projection for visual trend guidance
Breakout → Retest Signal Logic
Detects clean breakouts beyond the trend zone
Waits for a controlled pullback (retest) before signaling
Signals only trigger when trend strength is confirmed
Trend Quality Filter
Internal regime detection filters out low-quality, sideways conditions
Uses slope strength and volatility compression to validate entries
🔹 Signals
BUY : Bullish breakout followed by a valid retest in a trending regime
SELL : Bearish breakout followed by a valid retest in a trending regime
Signals are designed for trend continuation , not mean reversion.
🔹 Best Use Cases
Crypto, Forex, and Index markets
Higher timeframes (15m+ recommended)
Trend continuation and pullback strategies
⚠️ Notes
This indicator is not a standalone trading system . Always use proper risk management and confirm signals with structure, volume, or higher-timeframe context.
Designed for traders who prefer structure, patience, and momentum alignment.
TDPOWERSYS vs Market-Cap Weighted Peersfor QIC - UnCut Diamonds team..
to compare one company vs its peers bundled as basket.
editable..
Daily Extension from 50DMA (adjustable) in ATR%Indicator to easily spot over extended prices in relation to ATR.
ATR or ADR easily referenced
Live Candle Range Position SizerThis script displays a fixed execution HUD on the chart that continuously measures the current candle range (high–low) and automatically calculates position size based on a fixed Risk Unit (RU).
Cloud Gold TrendTrend Filter (Ichimoku): If the price is above the cloud (Kumo), look only for "Long" signals. If it is below, look only for "Short" signals.
Entry Signal (Bollinger): When the price touches the Lower Band while you are above the Cloud, it could be a great buying point in an uptrend.
Volatility Confirmation: If the Bollinger Bands squeeze within the cloud, get ready for a strong directional move as soon as the price breaks one of the two levels.
