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VS Score [SpiritualHealer117]An experimental indicator that uses historical prices and readings of technical indicators to give the probability that stock and crypto prices will be in a certain range on the next close. This indicator may be helpful for options traders or for traders who want to see the probability of a move.
It classifies returns into five categories:
Extreme Rise - Over 2 standard deviations above normal returns
Rise - Between 0.5 standard deviations and 2 standard deviations above normal returns
Flat - Falling in the range of +/- 0.5 standard deviations of normal returns
Fall - Between 0.5 standard deviations and 2 standard deviations below normal returns
Extreme Fall - Over 2 standard deviations below normal returns
It is an adaptive probability model, which trains on the previous 1000 data points, and is calculated by creating probability vectors for the current reading of the PPO, MA, volume histogram, and previous return, and combining them into one probability vector.
features complete buy and sell code Below is a single TradingView (Pine Script v5) indicator that fuses the key futures intraday ingredients you asked for — VWAP, EMAs, MACD, volume spike, synthetic order-flow (CVD), prior day levels, ATR proximity, and Fib-pullback logic from recent swings — into a buy/sell timing score with signals and alerts.
It’s designed for ES/MES/NQ/CL/GC etc., but works on any intraday chart. Footprint/true bid-ask delta isn’t available in Pine, so I implement a synthetic delta/CVD (industry standard approximation) that’s reliable enough for timing confirmation.
Bias: price vs VWAP & 200 EMA; above = bullish bias; below = bearish.
Momentum: 8/21 EMA alignment and MACD histogram.
Order flow (synthetic): bar delta & CVD slope.
Volume: spike vs SMA.
Levels: previous day High/Low/Close + ATR proximity.
Fibonacci: uses pivots to auto-anchor last impulse and watch for 50–61.8% pullbacks with confirmation.
Score: sums weighted conditions → fires BUY/SELL when threshold is met.
Alerts: ready to use (Create Alert… on this indicator).
Advanced Correlation Monitor📊 Advanced Correlation Monitor - Pine Script v6
🎯 What does this indicator do?
Monitors real-time correlations between 13 different asset pairs and alerts you when historically strong correlations break, indicating potential trading opportunities or changes in market dynamics.
🚀 Key Features
✨ Multi-Market Monitoring
7 Forex Pairs (GBPUSD/DXY, EURUSD/GBPUSD, etc.)
6 Index/Stock Pairs (SPY/S&P500, DAX/NASDAQ, TSLA/NVDA, etc.)
Fully configurable - change any pair from inputs
📈 Dual Correlation Analysis
Long Period (90 bars): Identifies historically strong correlations
Short Period (6 bars): Detects recent breakdowns
Pearson Correlation using Pine Script v6 native functions
🎨 Intuitive Visualization
Real-time table with 6 information columns
Color coding: Green (correlated), Red (broken), Gray (normal)
Visual states: 🟢 OK, 🔴 BROKEN, ⚫ NORMAL
🚨 Smart Alert System
Only alerts previously correlated pairs (>80% historical)
Detects breakdowns when short correlation <80%
Consolidated alert with all affected pairs
🛠️ Flexible Configuration
Adjustable Parameters:
📅 Periods: Long (30-500), Short (2-50)
🎯 Threshold: 50%-99% (default 80%)
🎨 Table: Configurable position and size
📊 Symbols: All pairs are configurable
Default Pairs:
FOREX: INDICES/STOCKS:
- GBPUSD vs DXY • SPY vs S&P500
- EURUSD vs GBPUSD • DAX vs S&P500
- EURUSD vs DXY • DAX vs NASDAQ
- USDCHF vs DXY • TSLA vs NVDA
- GBPUSD vs USDCHF • MSFT vs NVDA
- EURUSD vs USDCHF • AAPL vs NVDA
- EURUSD vs EURCAD
💡 Practical Use Cases
🔄 Pairs Trading
Detects when strong correlations break for:
Statistical arbitrage
Mean reversion trading
Divergence opportunities
🛡️ Risk Management
Identifies when "safe" assets start moving independently:
Portfolio diversification
Smart hedging
Regime change detection
📊 Market Analysis
Understand underlying market structure:
Forex/DXY correlations
Tech sector rotation
Regional market disconnection
🎓 Results Interpretation
Reading Example:
EURUSD vs DXY: -98.57% → -98.27% | 🟢 OK
└─ Perfect negative correlation maintained (EUR rises when DXY falls)
TSLA vs NVDA: 78.12% → 0% | ⚫ NORMAL
└─ Lost tech correlation (divergence opportunity)
Trading Signals:
🟢 → 🔴: Broken correlation = Possible opportunity
Large difference: Indicates correlation tension
Multiple breaks: Market regime change
Super EMA PrismThis script implements the Binary Trade Logic (BTL) algorithm to calculate two distinct scores that range from 0 to 7. One score is calculated assigning a power of 2 weight to the positive sign of 3 Phi^3 distant Moving Average (MA) slopes. The other score is calculated assigning a power of 2 weight to the sign of the difference between the price and the value of 3 Phi^3 distant Moving Average (MA).
For the first score, hereafter called as the angle score (AS), the largest MA slope positive sign receives weight 4, the middle length MA slope positive sign receives weight 2 and the shortest MA slope positive sign receives weight 1. The positive sign of an MA is defined as 1 if the slope of the MA is positive and 0, otherwise. Therefore, for MAs 305, 72 and 17, if slope(MA305) > 0, slope(MA72) < 0 and slope(MA17) > 0, then score will be 4*1 + 2*0 + 1*1 = 5. Up to my knowledge, this score was first proposed by Bo Williams and named by him as Prisma.
For the second score, hereafter called as the value score (VS), if the price > largest MA, it receives weight 4. If the price > the middle length MA, it receives weight 2 and if the price > the the shortest MA, it receives weight 1. Therefore, for MAs 305, 72 and 17, if price < MA305, price > MA72 and price > MA17, then score will be 4*0 + 2*1 + 1*1 = 3. Up to my knowledge, this score was first proposed by Bo Williams and named by him as Prisma.
Both AS and VS are calculated for Phi^3 lengths (610, 144, 34) and for Phi^3/2 lengths (305, 72, 17). The scores of the same kind calculated for each set of length are combined multiplying the Phi^3 length score by 10 and adding with with the Phi^3/2 score, therefore providing a 2 digit score ranging from 0 to 77. For instance, if we have AS(610, 144, 34) = 7 and AS(305, 72, 17) = 5, we have AS=75. At the same time, if we have VS(610, 144, 34) = 6 and VS(305, 72, 17) = 4, we have VS=64.
VS score is plotted by default in black, but it can be on white for dark themes. AS is plotted with the color of the longest MA used.
Chart background is colored according to the range of values for AS and VS, checked in the following order:
if AS >= 13 and VS <= 13 then back color = red
if AS >= 13 or VS <= 13 then back color = orange
if AS >= 64 and VS >= 64 then back color = green
if AS >= 64 or VS >= 64 then back color = blue
otherwise back color = none (white o black)
Cross-Correlation Lead/Lag AnalyzerCross-Correlation Lead/Lag Analyzer (XCorr)
Discover which instrument moves first with advanced cross-correlation analysis.
This indicator analyzes the lead/lag relationship between any two financial instruments using rolling cross-correlation at multiple time offsets. Perfect for pairs trading, market timing, and understanding inter-market relationships.
Key Features:
Universal compatibility - Works with any two symbols (stocks, futures, forex, crypto, commodities)
Multi-timeframe analysis - Automatically adjusts lag periods based on your chart timeframe
Real-time correlation table - Shows current correlation values for all lag scenarios
Visual lead/lag detection - Color-coded plots make it easy to spot which instrument leads
Smart "Best" indicator - Automatically identifies the strongest relationship
How to Use:
Set your symbols in the indicator settings (default: NQ1! vs RTY1!)
Adjust correlation length (default: 20 periods for smooth but responsive analysis)
Watch the colored lines:
• Red/Orange: Symbol 2 leads Symbol 1 by 1-2 periods
• Blue: Instruments move simultaneously
• Green/Purple: Symbol 1 leads Symbol 2 by 1-2 periods
Check the table for exact correlation values and the "Best" relationship
Interpreting Results:
Correlation > 0.7: Strong positive relationship
Correlation 0.3-0.7: Moderate relationship
Correlation < 0.3: Weak/no relationship
Highest line indicates the optimal timing relationship
Popular Use Cases:
Index Futures : NQ vs ES, RTY vs IWM
Sector Rotation : XLF vs XLK, QQQ vs SPY
Commodities : GC vs SI, CL vs NG
Currency Pairs : EURUSD vs GBPUSD
Crypto : BTC vs ETH correlation analysis
Technical Notes:
Cross-correlation measures linear relationships between two time series at different time lags. This implementation uses Pearson correlation with adjustable periods, calculating correlations from -2 to +2 period offsets to detect leading/lagging behavior.
Perfect for quantitative analysts, pairs traders, and anyone studying inter-market relationships.
Ichimoku Power Indicator# Ichimoku Power Indicator
## Overview
The Ichimoku Power Indicator is an advanced tool that combines the traditional Ichimoku Cloud system with a unique power ranking mechanism. This indicator provides traders with a comprehensive view of market trends and potential reversal points, all while quantifying the strength of bullish and bearish signals.
## Key Features
1. **Full Ichimoku Cloud Visualization:** Displays all components of the Ichimoku Cloud system, including Conversion Line (Tenkan-sen), Base Line (Kijun-sen), Leading Span A and B (Kumo), and Lagging Span (Chikou Span).
2. **Power Ranking System:** Calculates and displays a bullish and bearish power score based on 11 different Ichimoku-derived conditions.
3. **Real-time Updates:** Power scores are updated in real-time as market conditions change.
4. **Easy-to-Read Display:** A clear, color-coded table shows the current bullish and bearish power scores.
5. **Customizable Parameters:** Allows adjustment of key Ichimoku settings to suit different trading styles and timeframes.
## How It Works
The indicator evaluates 11 different conditions derived from Ichimoku Cloud components:
1. Cloud color
2. Price position relative to the cloud
3. Tenkan-sen vs Kijun-sen
4. Price vs Tenkan-sen
5. Price vs Kijun-sen
6. Tenkan-sen vs Cloud
7. Kijun-sen vs Cloud
8. Chikou Span vs Cloud
9. Chikou Span vs Tenkan-sen
10. Chikou Span vs Kijun-sen
11. Chikou Span vs Price
Each bullish condition adds a point to the bullish power score, while each bearish condition adds a point to the bearish power score. The maximum score for each is 11.
## Interpretation
- Higher bullish scores suggest stronger upward trends or potential bullish reversals.
- Higher bearish scores indicate stronger downward trends or potential bearish reversals.
- When scores are close, it may indicate a period of consolidation or uncertainty.
## Use Cases
- Trend Confirmation: Use in conjunction with price action to confirm the strength of current trends.
- Reversal Detection: Watch for changes in power scores as early indicators of potential trend reversals.
- Entry and Exit Signals: High power scores can be used to identify optimal entry or exit points.
- Market Analysis: Gain a quick overview of market conditions across multiple assets or timeframes.
## Note
This indicator is designed to complement your existing trading strategy. Always use it in conjunction with other forms of analysis and proper risk management techniques.
Experiment with different timeframes and settings to find the configuration that best suits your trading style and the assets you trade.
Happy trading!
Price Divergence IndicatorThis Price Divergence Indicator indicator modifies the standard Divergence Indicator to look for price divergences between the current chart and any other selected TradingView chart.
The thesis that this indicator is built upon:
Prices on assets or indices that are normally correlated move in lock step. Where there are deviations between the confirmed highs or lows of two assets or indices it is likely that they will "catch up" in the near future.
By default it will load the price data for the SPX and look for price divergences on the current chart timeframe. Any TradingView Symbol can be selected as the 'Comparison Source' and any timeframe. Some of the options I've been trying out include:
SPX vs NDQ
XAO vs SPX
UK100 vs NDQM
MSFT vs NDQM
GOOG vs NDQM
AMZN vs MSFT
BTC vs ETH
BTC vs NDQ
BTC vs DXY
I've found looking for divergences on a longer timeframe can be useful and don't expect any meaningful results if you set it to shorter than chart timeframes.
Alerts can be created based on any of the divergences and the 'Backtest Buy Signal' can be used to send notification to a backtester (bull = 2, hidden bull = 1, neutral = 0, hidden bear = -1, bear = -2), this is plotted to display.none, so enable it in Settings - Style and disable all other plots to see it.
Divergences are measured between the CONFIRMED peaks of the two charts. The confirmation timeframe is set using 'Pivot Lookback Right'. The lower the lookback the quicker the signal and the more likely it is to not have hit an actual peak, a higher lookback will give a much more dependable signal but the move may be finished by the time the alert actually fires. The "Plot When Alerts Fire" option should give you an idea (top and bottom triangles) of what to expect, but you should watch bar replays to understand how your setting will impact when alerts are created and potential false positives.
Chart-Only Scanner — Pro Table v2.5.1Chart-Only Scanner — Pro Table v2.5
User Manual (Pine Script v6)
What this tool does (in one line)
A compact, on-chart table that scores the current chart symbol (or an optional override) using momentum, volume, trend, volatility, and pattern checks—so you can quickly decide UP, DOWN, or WAIT.
Quick Start (90 seconds)
Add the indicator to any chart and timeframe (1m…1M).
Leave “Override chart symbol” = OFF to auto-use the chart’s symbol.
Choose your layout:
Row (wide horizontal strip), or Grid (title + labeled cells).
Pick a size preset (Micro, Small, Medium, Large, Mobile).
Optional: turn on “Use Higher TF (EMA 20/50)” and set HTF Multiplier (e.g., 4 ⇒ if chart is 15m, HTF is 60m).
Watch the table:
DIR (↑/↓/→), ROC%, MOM, VOL, EMA stack, HTF, REV, SCORE, ACT.
Add an alert if you want: the script fires when |SCORE| ≥ Action threshold.
What to expect
A small table appears on the chart corner you choose, updating each bar (or only at bar close if you keep default smart-update).
The ACT cell shows 🔥 (strong), 👀 (medium), or ⏳ (weak).
Panels & Settings (every option explained)
Core
Momentum Period: Lookback for rate-of-change (ROC%). Shorter = more reactive; longer = smoother.
ROC% Threshold: Minimum absolute ROC% to call direction UP (↑) or DOWN (↓); otherwise →.
Require Volume Confirmation: If ON and VOL ≤ 1.0, the SCORE is forced to 0 (prevents low-volume false positives).
Override chart symbol + Custom symbol: By default, the indicator uses the chart’s symbol. Turn this ON to lock to a specific ticker (e.g., a perpetual).
Higher TF
Use Higher TF (EMA 20/50): Compares EMA20 vs EMA50 on a higher timeframe.
HTF Multiplier: Higher TF = (chart TF × multiplier).
Example: on 3H chart with multiplier 2 ⇒ HTF = 6H.
Volatility & Oscillators
ATR Length: Used to show ATR% (ATR relative to price).
RSI Length: Standard RSI; colors: green ≤30 (oversold), red ≥70 (overbought).
Stoch %K Length: With %D = SMA(%K, 3).
MACD Fast/Slow/Signal: Standard MACD values; we display Line, Signal, Histogram (L/S/H).
ADX Length (Wilder): Wilder’s smoothing (internal derivation); also shows +DI / −DI if you enable the ADX column.
EMAs / Trend
EMA Fast/Mid/Slow: We compute EMA(20/50/200) by default (editable).
EMA Stack: Bull if Fast > Mid > Slow; Bear if Fast < Mid < Slow; Flat otherwise.
Benchmark (optional, OFF by default)
Show Relative Strength vs Benchmark: Displays RS% = ROC(symbol) − ROC(benchmark) over the Momentum Period.
Benchmark Symbol: Ticker used for comparison (e.g., BTCUSDT as a market proxy).
Columns (show/hide)
Toggle which fields appear in the table. Hiding unused fields keeps the layout clean (especially on mobile).
Display
Layout Mode:
Row = a single two-row strip; each column is a metric.
Grid = a title row plus labeled pairs (label/value) arranged in rows.
Size Preset: Micro, Small, Medium, Large, Mobile change text size and the grid density.
Table Corner: Where the panel sits (e.g., Top Right).
Opaque Table Background: ON = dark card; OFF = transparent(ish).
Update Every Bar: ON = update intra-bar; OFF = smart update (last bar / real-time / confirmed history).
Action threshold (|score|): The cutoff for 🔥 and alert firing (default 70).
How to read each field
CHART: The active symbol name (or your custom override).
DIR: ↑ (ROC% > threshold), ↓ (ROC% < −threshold), → otherwise.
ROC%: Rate of change over Momentum Period.
Formula: (Close − Close ) / Close × 100.
MOM: A scaled momentum score: min(100, |ROC%| × 10).
VOL: Volume ratio vs 20-bar SMA: Volume / SMA(Volume,20).
1.5 highlights as yellow (significant participation).
ATR%: (ATR / Close) × 100 (volatility relative to price).
RSI: Colored for extremes: ≤30 green, ≥70 red.
Stoch K/D: %K and %D numbers.
MACD L/S/H: Line, Signal, Histogram. Histogram color reflects sign (green > 0, red < 0).
ADX, +DI, −DI: Trend strength and directional components (Wilder). ADX ≥ 25 is highlighted.
EMA 20/50/200: Current EMA values (editable lengths).
STACK: Bull/Bear/Flat as defined above.
VWAP%: (Close − VWAP) / Close × 100 (premium/discount to VWAP).
HTF: ▲ if HTF EMA20 > EMA50; ▼ if <; · if flat/off.
RS%: Symbol’s ROC% − Benchmark ROC% (positive = outperforming).
REV (reversal):
🟢 Eng/Pin = bullish engulfing or bullish pin detected,
🔴 Eng/Pin = bearish engulfing or bearish pin,
· = none.
SCORE (absolute shown as a number; sign shown via DIR and ACT):
Components:
base = MOM × 0.4
volBonus = VOL > 1.5 ? 20 : VOL × 13.33
htfBonus = use_mtf ? (HTF == DIR ? 30 : HTF == 0 ? 15 : 0) : 0
trendBonus = (STACK == DIR) ? 10 : 0
macdBonus = 0 (placeholder for future versions)
scoreRaw = base + volBonus + htfBonus + trendBonus + macdBonus
SCORE = DIR ≥ 0 ? scoreRaw : −scoreRaw
If Require Volume Confirmation and VOL ≤ 1.0 ⇒ SCORE = 0.
ACT:
🔥 if |SCORE| ≥ threshold
👀 if 50 < |SCORE| < threshold
⏳ otherwise
Practical examples
Strong long (trend + participation)
DIR = ↑, ROC% = +3.2, MOM ≈ 32, VOL = 1.9, STACK = Bull, HTF = ▲, REV = 🟢
SCORE: base(12.8) + volBonus(20) + htfBonus(30) + trend(10) ≈ 73 → ACT = 🔥
Action idea: look for longs on pullbacks; confirm risk with ATR%.
Weak long (no volume)
DIR = ↑, ROC% = +1.0, but VOL = 0.8 and Require Volume Confirmation = ON
SCORE forced to 0 → ACT = ⏳
Action: wait for volume > 1.0 or turn off confirmation knowingly.
Bearish reversal warning
DIR = →, REV = 🔴 (bearish engulfing), RSI = 68, HTF = ▼
SCORE may be mid-range; ACT = 👀
Action: watch for breakdown and rising VOL.
Alerts (how to use)
The script calls alert() whenever |SCORE| ≥ Action threshold.
To receive pop-ups, sounds, or emails: click “⏰ Alerts” in TradingView, choose this indicator, and pick “Any alert() function call.”
The alert message includes: symbol, |SCORE|, DIR.
Layout, Size, and Corner tips
Row is best when you want a compact status ribbon across the top.
Grid is clearer on big screens or when you enable many columns.
Size:
Mobile = one pair per row (tall, readable)
Micro/Small = dense; good for many fields
Large = presentation/screenshots
Corner: If the table overlaps price, change the corner or set Opaque Background = OFF.
Repaint & timeframe behavior
Default smart update prefers stability (last bar / live / confirmed history).
For a stricter, “close-only” behavior (less repaint): turn Update Every Bar = OFF and avoid Heikin Ashi when you want raw market OHLC (HA modifies price inputs).
HTF logic is derived from a clean, integer multiple of your chart timeframe (via multiplier). It works with 3H/4H and any TF.
Performance notes
The script analyzes one symbol (chart or override) with multiple metrics using efficient tuple requests.
If you later want a multi-symbol grid, do it with pages (10–15 per page + rotate) to stay within platform limits (recommended future add-on).
Troubleshooting
No table visible
Ensure the indicator is added and not hidden.
Try toggling Opaque Background or switch Corner (it might be behind other drawings).
Keep Columns count reasonable for the chosen Size.
If you turned ON Override, verify the Custom symbol exists on your data provider.
Numbers look different on HA candles
Heikin Ashi modifies OHLC; switch to regular candles if you need raw price metrics.
3H/4H issues
Use integer HTF Multiplier (e.g., 2, 4). The tool builds the correct string internally; no manual timeframe strings needed.
Power user tips
Volume gating: keeping Require Volume Confirmation = ON filters most fake moves; if you’re a scalper, reduce strictness or turn it off.
Action threshold: 60–80 is typical. Higher = fewer but stronger signals.
Benchmark RS%: great for spotting leaders/laggards; positive RS% = outperformance vs benchmark.
Change policy & safety
This version doesn’t alter your historical logic you tested (no radical changes).
Any future “radical” change (score weights, HTF logic, UI hiding data) will ship with a toggle and an Impact Statement so you can keep old behavior if you prefer.
Glossary (quick)
ROC%: Percent change over N bars.
MOM: Scaled momentum (0–100).
VOL ratio: Volume vs 20-bar average.
ATR%: ATR as % of price.
ADX/DI: Trend strength / direction components (Wilder).
EMA stack: Relationship between EMAs (bullish/bearish/flat).
VWAP%: Premium/discount to VWAP.
RS%: Relative strength vs benchmark.
Asset Premium/Discount Monitor📊 Overview
The Asset Premium/Discount Monitor is a tool for analyzing the relative value between two correlated assets. It measures when one asset is trading at a premium or discount compared to its historical relationship with another asset, helping traders identify potential mean reversion opportunities, or pairs trading opportunities.
🎯 Use Cases
Perfect for analyzing:
NASDAQ:MSTR vs CRYPTO:BTCUSD - MicroStrategy's premium/discount to Bitcoin
NASDAQ:COIN vs BITSTAMP:BTCUSD - Coinbase's relative value to Bitcoin
NASDAQ:TSLA vs NASDAQ:QQQ - Tesla's premium to tech sector
Regional banks AMEX:KRE vs AMEX:XLF - Individual bank stocks vs financial sector
Any two correlated assets where relative value matters
Example of a trade: MSTR vs BTC - When indicator shows MSTR at 95% percentile (extreme premium): Short MSTR, Buy BTC. Then exit when the spread reverts to the mean, say 40-60% percentile.
🔧 How It Works
Core Calculation
Ratio Analysis: Calculates the price ratio between your asset and the correlated asset
Historical Baseline: Establishes the "normal" relationship using a 252-day moving average. You can change this.
Premium Measurement: Measures current deviation from historical average as a percentage
Statistical Context: Provides percentile rankings and standard deviation bands
The Math
Premium % = (Current Ratio / Historical Average Ratio - 1) × 100
🎨 Customization Options
Correlated Asset: Choose any symbol for comparison
Lookback Period: Adjust historical baseline (50-1000 days)
Smoothing: Reduce noise with moving average (1-50 days)
Visual Toggles: Show/hide bands and percentile lines
Color Themes: Customize premium/discount colors
📊 Interpretation Guide
Premium/Discount Reading
Positive %: Asset trading above historical relationship (premium)
Negative %: Asset trading below historical relationship (discount)
Near 0%: Asset at fair value relative to correlation
Percentile Ranking
90%+: Near recent highs - potential selling opportunity
10% and below: Near recent lows - potential buying opportunity
25-75%: Normal trading range
Signal Classifications
🔴 SELL PREMIUM: Asset expensive relative to recent range
🟡 Premium Rich: Moderately expensive, monitor for reversal
⚪ NEUTRAL: Fair value territory
🟡 Discount Opportunity: Moderately cheap, potential accumulation zone
🟢 BUY DISCOUNT: Asset cheap relative to recent range
🚨 Built-in Alerts
Extreme Premium Alert: Triggers when percentile > 95%
Extreme Discount Alert: Triggers when percentile < 5%
⚠️ Important Notes
Works best with highly correlated assets
Historical relationships can change - monitor correlation strength
Not investment advice - use as one factor in your analysis
Backtest thoroughly before implementing any strategy
🔄 Updates & Future Features
This indicator will be continuously improved based on user feedback. So... please give me your feedback!
SynchroTrend Oscillator (STO) [PhenLabs]📊 SynchroTrend Oscillator
Version: PineScript™ v5
📌 Description
The SynchroTrend Oscillator (STO) is a multi-timeframe synchronization tool that combines trend information from three distinct timeframes into a single, easy-to-interpret oscillator ranging from -100 to +100.
This indicator solves the common problem of having to analyze multiple timeframe charts separately by consolidating trend direction and strength across different time horizons. The STO helps traders identify when markets are truly synchronized across timeframes, potentially indicating stronger trend conditions and higher probability trading opportunities.
Using either Moving Average crossovers or RSI analysis as the trend definition metric, the STO provides a comprehensive view of market structure that adapts to various trading strategies and market conditions.
🚀 Points of Innovation
Triple-timeframe synchronization in a single view eliminates chart switching
Dual trend detection methods (MA vs Price or RSI) for flexibility across different markets
Dynamic color intensity that automatically increases with signal strength
Scaled oscillator format (-100 to +100) for intuitive trend strength interpretation
Customizable signal thresholds to match your risk tolerance and trading style
Visual alerts when markets reach full synchronization states
🔧 Core Components
Trend Scoring System: Calculates a binary score (+1, -1, or 0) for each timeframe based on selected metrics, providing clear trend direction
Multi-Timeframe Synchronization: Combines and scales trend scores from all three timeframes into a single oscillator
Dynamic Visualization: Adjusts color transparency based on signal strength, creating an intuitive visual guide
Threshold System: Provides customizable levels for identifying potentially significant trading opportunities
🔥 Key Features
Triple Timeframe Analysis: Synchronizes three user-defined timeframes (default: 60min, 15min, 5min) into one view
Dual Trend Detection Methods: Choose between Moving Average vs Price or RSI-based trend determination
Adjustable Signal Smoothing: Apply EMA, SMA, or no smoothing to the oscillator output for your preferred signal responsiveness
Dynamic Color Intensity: Colors become more vibrant as signal strength increases, helping identify strongest setups
Customizable Thresholds: Set your own buy/sell threshold levels to match your trading strategy
Comprehensive Alerts: Six different alert conditions for crossing thresholds, zero line, and full synchronization states
🎨 Visualization
Oscillator Line: The main line showing the synchronized trend value from -100 to +100
Dynamic Fill: Area between oscillator and zero line changes transparency based on signal strength
Threshold Lines: Optional dotted lines indicating buy/sell thresholds for visual reference
Color Coding: Green for bullish synchronization, red for bearish synchronization
📖 Usage Guidelines
Timeframe Settings
Timeframe 1: Default: 60 (1 hour) - Primary higher timeframe for trend definition
Timeframe 2: Default: 15 (15 minutes) - Intermediate timeframe for trend definition
Timeframe 3: Default: 5 (5 minutes) - Lower timeframe for trend definition
Trend Calculation Settings
Trend Definition Metric: Default: “MA vs Price” - Method used to determine trend on each timeframe
MA Type: Default: EMA - Moving Average type when using MA vs Price method
MA Length: Default: 21 - Moving Average period when using MA vs Price method
RSI Length: Default: 14 - RSI period when using RSI method
RSI Source: Default: close - Price data source for RSI calculation
Oscillator Settings
Smoothing Type: Default: SMA - Applies smoothing to the final oscillator
Smoothing Length: Default: 5 - Period for the smoothing function
Visual & Threshold Settings
Up/Down Colors: Customize colors for bullish and bearish signals
Transparency Range: Control how transparency changes with signal strength
Line Width: Adjust oscillator line thickness
Buy/Sell Thresholds: Set levels for potential entry/exit signals
✅ Best Use Cases
Trend confirmation across multiple timeframes
Finding high-probability entry points when all timeframes align
Early detection of potential trend reversals
Filtering trade signals from other indicators
Market structure analysis
Identifying potential divergences between timeframes
⚠️ Limitations
Like all indicators, can produce false signals during choppy or ranging markets
Works best in trending market conditions
Should not be used in isolation for trading decisions
Past performance is not indicative of future results
May require different settings for different markets or instruments
💡 What Makes This Unique
Combines three timeframes in a single visualization without requiring multiple chart windows
Dynamic transparency feature that automatically emphasizes stronger signals
Flexible trend definition methods suitable for different market conditions
Visual system that makes multi-timeframe analysis intuitive and accessible
🔬 How It Works
1. Trend Evaluation:
For each timeframe, the indicator calculates a trend score (+1, -1, or 0) using either:
MA vs Price: Comparing close price to a moving average
RSI: Determining if RSI is above or below 50
2. Score Aggregation:
The three trend scores are combined and then scaled to a range of -100 to +100
A value of +100 indicates all timeframes show bullish conditions
A value of -100 indicates all timeframes show bearish conditions
Values in between indicate varying degrees of alignment
3. Signal Processing:
The raw oscillator value can be smoothed using EMA, SMA, or left unsmoothed
The final value determines line color, fill color, and transparency settings
Threshold levels are applied to identify potential trading opportunities
💡 Note:
The SynchroTrend Oscillator is most effective when used as part of a comprehensive trading strategy that includes proper risk management techniques. For best results, consider using the oscillator in conjunction with support/resistance levels, price action analysis, and other complementary indicators that align with your trading style.
OverUnder Yield Spread🗺️ OverUnder is a structural regime visualizer , engineered to diagnose the shape, tone, and trajectory of the yield curve. Rather than signaling trades directly, it informs traders of the world they’re operating in. Yield curve steepening or flattening, normalizing or inverting — each regime reflects a macro pressure zone that impacts duration demand, liquidity conditions, and systemic risk appetite. OverUnder abstracts that complexity into a color-coded compression map, helping traders orient themselves before making risk decisions. Whether you’re in bonds, currencies, crypto, or equities, the regime matters — and OverUnder makes it visible.
🧠 Core Logic
Built to show the slope and intent of a selected rate pair, the OverUnder Yield Spread defaults to 🇺🇸US10Y-US2Y, but can just as easily compare global sovereign curves or even dislocated monetary systems. This value is continuously monitored and passed through a debounce filter to determine whether the curve is:
• Inverted, or
• Steepening
If the curve is flattening below zero: the world is bracing for contraction. Policy lags. Risk appetite deteriorates. Duration gets bid, but only as protection. Stocks and speculative assets suffer, regardless of positioning.
📍 Curve Regimes in Bull and Bear Contexts
• Flattening occurs when the short and long ends compress . In a bull regime, flattening may reflect long-end demand or fading growth expectations. In a bear regime, flattening often precedes or confirms central bank tightening.
• Steepening indicates expanding spread . In a bull context, this may signal healthy risk appetite or early expansion. In a bear or crisis context, it may reflect aggressive front-end cuts and dislocation between short- and long-term expectations.
• If the curve is steepening above zero: the world is rotating into early expansion. Risk assets behave constructively. Bond traders position for normalization. Equities and crypto begin trending higher on rising forward expectations.
🖐️ Dynamically Colored Spread Line Reflects 1 of 4 Regime States
• 🟢 Normal / Steepening — early expansion or reflation
• 🔵 Normal / Flattening — late-cycle or neutral slowdown
• 🟠 Inverted / Steepening — policy reversal or soft landing attempt
• 🔴 Inverted / Flattening — hard contraction, credit stress, policy lag
🍋 The Lemon Label
At every bar, an anchored label floats directly on the spread line. It displays the active regime (in plain English) and the precise spread in percent (or basis points, depending on resolution). Colored lemon yellow, neither green nor red, the label is always legible — a design choice to de-emphasize bias and center the data .
🎨 Fill Zones
These bands offer spatial, persistent views of macro compression or inversion depth.
• Blue fill appears above the zero line in normal (non-inverted) conditions
• Red fill appears below the zero line during inversion
🧪 Sample Reading: 1W chart of TLT
OverUnder reveals a multi-year arc of structural inversion and regime transition. From mid-2021 through late 2023, the spread remains decisively inverted, signaling persistent flattening and credit stress as bond prices trended sharply lower. This prolonged inversion aligns with a high-volatility phase in TLT, marked by lower highs and an accelerating downtrend, confirming policy lag and macro tightening conditions.
As of early 2025, the spread has crossed back above the zero baseline into a “Normal / Steepening” regime (annotated at +0.56%), suggesting a macro inflection point. Price action remains subdued, but the shift in yield structure may foreshadow a change in trend context — particularly if follow-through in steepening persists.
🎭 Different Traders Respond Differently:
• Bond traders monitor slope change to anticipate policy pivots or recession signals.
• Equity traders use regime shifts to time rotations, from growth into defense, or from contraction into reflation.
• Currency traders interpret curve steepening as yield compression or divergence depending on region.
• Crypto traders treat inversion as a liquidity vacuum — and steepening as an early-phase risk unlock.
🛡️ Can It Compare Different Bond Markets?
Yes — with caveats. The indicator can be used to compare distinct sovereign yield instruments, for example:
• 🇫🇷FR10Y vs 🇩🇪DE10Y - France vs Germany
• 🇯🇵JP10Y vs 🇺🇸US10Y - BoJ vs Fed policy curves
However:
🙈 This no longer visualizes the domestic yield curve, but rather the differential between rate expectations across regions
🙉 The interpretation of “inversion” changes — it reflects spread compression across nations , not within a domestic yield structure
🙊 Color regimes should then be viewed as relative rate positioning , not absolute curve health
🙋🏻 Example: OverUnder compares French vs German 10Y yields
1. 🇫🇷 Change the long-duration ticker to FR10Y
2. 🇩🇪 Set the short-duration ticker to DE10Y
3. 🤔 Interpret the result as: “How much higher is France’s long-term borrowing cost vs Germany’s?”
You’ll see steepening when the spread rises (France decoupling), flattening when the spread compresses (convergence), and inversions when Germany yields rise above France’s — historically rare and meaningful.
🧐 Suggested Use
OverUnder is not a signal engine — it’s a context map. Its value comes from situating any trade idea within the prevailing yield regime. Use it before entries, not after them.
• On the 1W timeframe, OverUnder excels as a macro overlay. Yield regime shifts unfold over quarters, not days. Weekly structure smooths out rate volatility and reveals the true curvature of policy response and liquidity pressure. Use this view to orient your portfolio, define directional bias, or confirm long-duration trend turns in assets like TLT, SPX, or BTC.
• On the 1D timeframe, the indicator becomes tactically useful — especially when aligning breakout setups or trend continuations with steepening or flattening transitions. Daily views can also identify early-stage regime cracks that may not yet be visible on the weekly.
• Avoid sub-daily use unless you’re anchoring a thesis already built on higher timeframe structure. The yield curve is a macro construct — it doesn’t oscillate cleanly at intraday speeds. Shorter views may offer clarity during event-driven spikes (like FOMC reactions), but they do not replace weekly context.
Ultimately, OverUnder helps you decide: What kind of world am I trading in? Use it to confirm macro context, avoid fighting the curve, and lean into trades aligned with the broader pressure regime.
See inside Candles: Directionality %; Constituent Bars & GapsSee inside candles based on user-input LTF setting: get data on 'Directionality' of your candle; Gaps (total and Sum; UP and DOWN); Number of Bull or Bear constituent candles
//Features:
-DIRECTIONALITY: compare length of the 'zig-zag' random walk of lower time frame constituent candles, to the full height of the current candle. Resulting % I refer to as 'directionality'.
-GAPs: what i refer to as 'gaps' are also known as Volume imbalances: the gap between previous candles close and current candle's open (if there is one).
--Gaps total (up vs down gaps). Number of Up gaps printed above bar in green, down gaps printed below bar in red.
--Gaps Sum (total summed UP gap, total summed down gaps. Sum of Up gaps printed above bar in green, Sum of down gaps printed below bar in red.
-Candles Total: Numer of LTF up vs down candles within current timeframe candle. Number of up candles printed above bar in green, Number of down candles printed below bar in red.
//USAGE:
-Primary purpose in this was the Directionality aspect. Wanted to get a measure of how choppy vs how directional the internals of a candle were. Idea being that a candle with high % directionality (approaching 100) would imply trending conditions; while a candle which was large range and full bodies but had a low % directionality would imply the internals were back-and-forth and => rebalanced, potentially indicating price may not need to retrace back into it and rebalance further. All rather experimental, please treat it as such: have a play around with it.
-Number of gaps, Sums of up and down gaps, ratio of up and down constituent candles also intended to serve a similar purpose as the above.
-Set the input lower timeframe; this must obviously be lower then your current timeframe. You will significant differences in results depending on the ratio your timeframes (chart timeframe vs user-input timeframe).
//User Inputs:
-Lower timeframe input (setting child candle size within current chart parent candle).
-Choose function from the four listed above.
-typical formating options: Bull color/bear color txt for gaps functions.
-display % unit or not.
-display vertical or horizontal text.
-Set min / max directionality thresholds; and color code results.
-Toggle on/off 'hide results outside of threshold' to declutter the chart.
-choose label style.
//NOTES:
-Directionality thresholds can be set manually; Max and Min thresholds can be set to filter out 'non-extreme' readings.
-Note that directionality % can sometimes exceed 100%, in cases where price trends very strongly and gaps up continuously such that sum of constituent candles is less than total range of parent candle.
-Personally i like the idea of seeking bold, large-range, full bodied candles, with a lower than typical directionality %; indicating that a price move is both significant and it's already done it's rebalancing; I would see this as potentially favourable for continuation (obviously depending on context).
---- Showcase of the other functions beyond Directionality percentage ----
Candles Total (bull vs Bear). ES1! Hourly; ltf = 5min: Candles total: LTF up candles and LTF down candles making up the current HTF candle (constituent number of UP candles printed above in green, Down candles printed below in red):
Gaps SUM. SPX hourly, ltf = 5min. Sum of 'UP' gaps within candle printed above in green, sum of 'DOWN' gaps printed below in red:
Gaps TOTAL: SPX hourly, ltf = 1min. Simply the total of 'up' gaps vs 'down' gaps withing our candle; based on the user input constituent candles within:
Correlation Coefficient: Visible Range Dynamic Average R -Correlation Coefficient with Dynamic Average R (shows R average for the visible chart only, changes as you zoom in or out)
-Label: Vis-Avg-R = Visable Average R
-the Correlation Coefficient function for Pearson's R is taken from "BA🐷 CC" indicator by @balipour (highly recommended; more thorough treatment of R and other stats, but without the dynamic average)
-I wrote this primarily to add a dynamic Average R, showing correlation for arbitrary start times/end times; whether it be the last month, last year, of some specific period from the past (backtest mode)
-I have been using this to get an idea of correlation regimes over time between Bonds vs Stocks (ZB1! vs ES1!).
-As you see from the above, most of 2022 has seen an unusually strong positive correlation between Bonds and Stocks
~~inputs:
-lookback length for calculation of R
-Backtest mode (true by default): displays Average R for ONLY the visible range displayed on any part of chart history (LHS to RHS of screen only)
-source for both Ticker and compared Asset (close, open, high, low, ohlc4.. etc)
~~some other assets worth comparing:
Aussie vs Gold; Aussie vs ES; Btc vs ES; Copper vs ES
Spread AnalysisSpread Analysis - Futures vs Spot Price Analysis
Advanced spread analysis tool that compares futures/perp prices with spot prices across multiple exchanges, providing insights into market sentiment and potential trading opportunities.
Multi-Asset Support: Automatically detects and analyzes crypto perpetual vs spot spreads, index futures vs cash indices (ES/SPX, NQ/NDX, YM/DJI), and commodity futures vs spot prices (GC/GOLD, CL/USOIL)
Multi-Exchange Aggregation: For crypto, aggregates prices from Binance, BitMEX, Kraken, Bybit, OKX, and Coinbase to calculate mean perp and spot prices
Z-Score Based Alerts: Uses statistical Z-score analysis to identify extreme spread conditions that may signal potential reversals or continuation patterns
Visual Histogram Display: Shows spread differences as colored columns - green for futures premium, red for futures discount
Flexible Calculation Methods: Supports absolute price differences, percentage spreads, or basis point calculations
Trading Applications: Identify market sentiment divergence, spot potential reversal opportunities, and confirm trend strength
Risk Management: Use extreme Z-scores to identify overvalued conditions and potential mean reversion setups
Market Analysis: Understand the relationship between futures and spot markets across different asset classes
Timing Tool: Spread momentum often precedes price moves, providing early signals for entry/exit decisions
Perfect for traders who want to understand the relationship between futures and spot markets, identify divergences, and spot potential reversal opportunities across crypto, indices, and commodities.
Key Features:
• Automatic asset detection and appropriate spread calculation
• Configurable Z-score alerts for extreme conditions
• Comprehensive tooltips and information guide
• Multiple calculation methods (absolute, percentage, basis points)
• Clean, customizable visual display
Use Cases:
• Crypto traders analyzing perp vs spot relationships
• Futures traders monitoring basis relationships
• Mean reversion strategies using extreme spreads
• Trend confirmation using spread momentum
• Market sentiment analysis across asset classes
AMF_LibraryLibrary "AMF_Library"
Adaptive Momentum Flow (AMF) Library - A comprehensive momentum oscillator that adapts to market volatility
@author B3AR_Trades
f_ema(source, length)
Custom EMA calculation that accepts a series length
Parameters:
source (float) : (float) Source data for calculation
length (float) : (float) EMA length (can be series)
Returns: (float) EMA value
f_dema(source, length)
Custom DEMA calculation that accepts a series length
Parameters:
source (float) : (float) Source data for calculation
length (float) : (float) DEMA length (can be series)
Returns: (float) DEMA value
f_sum(source, length)
Custom sum function for rolling sum calculation
Parameters:
source (float) : (float) Source data for summation
length (int) : (int) Number of periods to sum
Returns: (float) Sum value
get_average(data, length, ma_type)
Get various moving average types for fixed lengths
Parameters:
data (float) : (float) Source data
length (simple int) : (int) MA length
ma_type (string) : (string) MA type: "SMA", "EMA", "WMA", "DEMA"
Returns: (float) Moving average value
calculate_adaptive_lookback(base_length, min_lookback, max_lookback, volatility_sensitivity)
Calculate adaptive lookback length based on volatility
Parameters:
base_length (int) : (int) Base lookback length
min_lookback (int) : (int) Minimum allowed lookback
max_lookback (int) : (int) Maximum allowed lookback
volatility_sensitivity (float) : (float) Sensitivity to volatility changes
Returns: (int) Adaptive lookback length
get_volatility_ratio()
Get current volatility ratio
Returns: (float) Current volatility ratio vs 50-period average
calculate_volume_analysis(vzo_length, smooth_length, smooth_type)
Calculate volume-based buying/selling pressure
Parameters:
vzo_length (int) : (int) Lookback length for volume analysis
smooth_length (simple int) : (int) Smoothing length
smooth_type (string) : (string) Smoothing MA type
Returns: (float) Volume analysis value (-100 to 100)
calculate_amf(base_length, smooth_length, smooth_type, signal_length, signal_type, min_lookback, max_lookback, volatility_sensitivity, medium_multiplier, slow_multiplier, vzo_length, vzo_smooth_length, vzo_smooth_type, price_vs_fast_weight, fast_vs_medium_weight, medium_vs_slow_weight, vzo_weight)
Calculate complete AMF oscillator
Parameters:
base_length (int) : (int) Base lookback length
smooth_length (simple int) : (int) Final smoothing length
smooth_type (string) : (string) Final smoothing MA type
signal_length (simple int) : (int) Signal line length
signal_type (string) : (string) Signal line MA type
min_lookback (int) : (int) Minimum adaptive lookback
max_lookback (int) : (int) Maximum adaptive lookback
volatility_sensitivity (float) : (float) Volatility adaptation sensitivity
medium_multiplier (float) : (float) Medium DEMA length multiplier
slow_multiplier (float) : (float) Slow DEMA length multiplier
vzo_length (int) : (int) Volume analysis lookback
vzo_smooth_length (simple int) : (int) Volume analysis smoothing
vzo_smooth_type (string) : (string) Volume analysis smoothing type
price_vs_fast_weight (float) : (float) Weight for price vs fast DEMA
fast_vs_medium_weight (float) : (float) Weight for fast vs medium DEMA
medium_vs_slow_weight (float) : (float) Weight for medium vs slow DEMA
vzo_weight (float) : (float) Weight for volume analysis component
Returns: (AMFResult) Complete AMF calculation results
calculate_amf_default()
Calculate AMF with default parameters
Returns: (AMFResult) AMF result with standard settings
amf_oscillator()
Get just the main AMF oscillator value with default parameters
Returns: (float) Main AMF oscillator value
amf_signal()
Get just the AMF signal line with default parameters
Returns: (float) AMF signal line value
is_overbought(overbought_level)
Check if AMF is in overbought condition
Parameters:
overbought_level (float) : (float) Overbought threshold (default 70)
Returns: (bool) True if overbought
is_oversold(oversold_level)
Check if AMF is in oversold condition
Parameters:
oversold_level (float) : (float) Oversold threshold (default -70)
Returns: (bool) True if oversold
bullish_crossover()
Detect bullish crossover (main line crosses above signal)
Returns: (bool) True on bullish crossover
bearish_crossover()
Detect bearish crossover (main line crosses below signal)
Returns: (bool) True on bearish crossover
AMFResult
AMF calculation results
Fields:
main_oscillator (series float) : The main AMF oscillator value (-100 to 100)
signal_line (series float) : The signal line for crossover signals
dema_fast (series float) : Fast adaptive DEMA value
dema_medium (series float) : Medium adaptive DEMA value
dema_slow (series float) : Slow adaptive DEMA value
volume_analysis (series float) : Volume-based buying/selling pressure (-100 to 100)
adaptive_lookback (series int) : Current adaptive lookback length
volatility_ratio (series float) : Current volatility ratio vs average
AllMA Trend Radar [trade_lexx]📈 AllMA Trend Radar is your universal trend analysis tool!
📊 What is AllMA Trend Radar?
AllMA Trend Radar is a powerful indicator that uses various types of Moving Averages (MA) to analyze trends and generate trading signals. The indicator allows you to choose from more than 30 different types of moving averages and adjust their parameters to suit your trading style.
💡 The main components of the indicator
📈 Fast and slow moving averages
The indicator uses two main lines:
- Fast MA (blue line): reacts faster to price changes
- Slow MA (red line): smoother, reflects a long-term trend
The combined use of fast and slow MA allows you to get trend confirmation and entry/exit points from the market.
🔄 Wide range of moving averages
There are more than 30 types of moving averages at your disposal:
- SMA: Simple moving average
- EMA: Exponential moving average
- WMA: Weighted moving average
- DEMA: double exponential MA
- TEMA: triple exponential MA
- HMA: Hull Moving Average
- LSMA: Moving average of least squares
- JMA: Eureka Moving Average
- ALMA: Arnaud Legoux Moving Average
- ZLEMA: moving average with zero delay
- And many others!
🔍 Indicator signals
1️⃣ Fast 🆚 Slow MA signals (intersection and ratio of fast and slow MA)
Up/Down signals (intersection)
- Buy (Up) signal:
- What happens: the fast MA crosses the slow MA from bottom to top
- What does the green triangle with the "Buy" label under the candle look
like - What does it mean: a likely upward trend reversal or an uptrend strengthening
- Sell signal (Down):
- What happens: the fast MA crosses the slow MA from top to bottom
- What does it look like: a red triangle with a "Sell" mark above the candle
- What does it mean: a likely downtrend reversal or an increase in the downtrend
Greater/Less signals (ratio)
- Buy signal (Greater):
- What happens: the fast MA becomes higher than the slow MA
- What does it look like: a green triangle with a "Buy" label under the candle
- What does it mean: the formation or confirmation of an uptrend
- Sell signal (Less):
- What happens: the fast MA becomes lower than the slow MA
- What does it look like: a red triangle with a "Sell" mark above the candle
- What does it mean: the formation or confirmation of a downtrend
2️⃣ Signals ⚡️ Fast MA (fast MA and price)
Up/Down signals (intersection)
- Buy signal (Up Fast):
- What happens: the price crosses the fast MA from bottom to top
- What does it look like: a green triangle with a "Buy" label under the candle
- What does it mean: a short-term price growth signal
- Sell signal (Down Fast):
- What happens: the price crosses the fast MA from top to bottom
- What does it look like: a red triangle with a "Sell" label above the candle
- What does it mean: a short-term price drop signal
Greater/Less signals (ratio)
- Buy signal (Greater Fast):
- What happens: the price is getting higher than the fast MA
- What does it look like: a green triangle with a "Buy" label under the candle
- What does it mean: the price is above the fast MA, which indicates an upward movement
- Sell signal (Less Fast):
- What happens: the price is getting lower than the fast MA
- What does it look like: a red triangle with a "Sell" mark above the candle
- What does it mean: the price is under the fast MA, which indicates a downward movement
3️⃣ Signals 🐢 Slow MA (slow MA and price)
Up/Down signals (intersection)
- Buy signal (Up Slow):
- What happens: the price crosses the slow MA from bottom to top
- What does it look like: a green triangle with a "Buy" label under the candle
- What does it mean: a potential medium-term upward trend reversal
- Sell signal (Down Slow):
- What happens: the price crosses the slow MA from top to bottom
- What does it look like: a red triangle with a "Sell" label above the candle
- What does it mean: a potential medium-term downward trend reversal
Greater/Less signals (ratio)
- Buy signal (Greater Slow):
- What happens: the price is getting above the slow MA
- What does it look like: a green triangle with a "Buy" label under the candle
- What does it mean: the price is above the slow MA, which indicates a strong upward movement
- Sell signal (Less Slow):
- What is happening: the price is getting below the slow MA
- What does it look like: a red triangle with a "Sell" mark above the candle
- What does it mean: the price is under the slow MA, which indicates a strong downward movement
🛠 Filters to filter out false signals
1️⃣ Minimum distance between the signals
- What it does: sets the minimum number of candles between signals of the same type
- Why it is needed: it prevents the appearance of too frequent signals, especially during periods of high volatility
- How to set it up: Set a different value for each signal type (default: 3-5 bars)
- Example: if the value is 3 for Up/Down signals, after the buy signal appears, the next buy signal may appear no earlier than 3 bars later
2️⃣ Advanced indicator filters
🔍 RSI Filter
- What it does: Checks the Relative Strength Index (RSI) value before generating a signal
- Why it is needed: it helps to avoid countertrend entries and catch reversal points
- How to set up:
- For buy signals (🔋 Buy): set the RSI range, usually in the oversold zone (for example, 1-30)
- For sell signals (🪫 Sell): set the RSI range, usually in the overbought zone (for example, 70-100)
- Example: if the RSI = 25 (in the range 1-30), the buy signal will be confirmed
📊 MFI Filter (Cash Flow Index)
- What it does: analyzes volumes and the direction of price movement
- Why it is needed: confirms signals with data on the activity of cash flows
- How to set up:
- For buy signals (🔋 Buy): set the MFI range in the oversold zone (for example, 1-25)
- For sell signals (🪫 Sell): set the MFI range in the overbought zone (for example, 75-100)
- Example: if MFI = 80 (in the range of 75-100), the sell signal will be confirmed
📈 Stochastic Filter
- What it does: analyzes the position of the current price relative to the price range
- Why it is needed: confirms signals based on overbought/oversold conditions
- How to configure:
- You can configure the K Length, D Length and Smoothing parameters
- For buy signals (🔋 Buy): set the stochastic range in the oversold zone (for example, 1-20)
- For sell signals (🪫 Sell): set the stochastic range in the overbought zone (for example, 80-100)
- Example: if stochastic = 15 (is in the range of 1-20), the buy signal will be confirmed
🔌 Connecting to trading strategies
The indicator provides various connectors to connect to your trading strategies.:
1️⃣ Individual connectors for each type of signal
- 🔌Fast vs Slow Up/Down MA Signal🔌: signals for the intersection of fast and slow MA
- 🔌Fast vs Slow Greater/Less MA Signal🔌: signals of the ratio of fast and slow MA
- 🔌Fast Up/Down MA Signal🔌: signals of the intersection of price and fast MA
- 🔌Fast Greater/Less MA Signal🔌: signals of the ratio of price and fast MA
- 🔌Slow Up/Down MA Signal🔌: signals of the intersection of price and slow MA
- 🔌Slow Greater/Less MA Signal🔌: Price versus slow MA signals
2️⃣ Combined connectors
- 🔌Combined Up/Down MA Signal🔌: combines all the crossing signals (Up/Down)
- 🔌Combined Greater/Less MA Signal🔌: combines all the signals of the ratio (Greater/Less)
- 🔌Combined All MA Signals🔌: combines all signals (Up/Down and Greater/Less)
❗️ All connectors return values:
- 1: buy signal
- -1: sell signal
- 0: no signal
📚 How to start using AllMA Trend Radar
1️⃣ Selection of types of moving averages
- Add an indicator to the chart
- Select the type and period for the fast MA (default: DEMA with a period of 14)
- Select the type and period for the slow MA (default: SMA with a period of 14)
- Experiment with different types of MA to find the best combination for your trading style
2️⃣ Signal settings
- Turn on the desired signal types (Up/Down, Greater/Less)
- Set the minimum distance between the signals
- Activate and configure the necessary filters (RSI, MFI, Stochastic)
3️⃣ Checking on historical data
- Analyze how the indicator works based on historical data
- Pay attention to the accuracy of the signals and the presence of false alarms
- Adjust the settings if necessary
4️⃣ Introduction to the trading strategy
- Decide which signals will be used to enter the position.
- Determine which signals will be used to exit the position.
- Connect the indicator to your trading strategy through the appropriate connectors
🌟 Practical application examples
Scalping strategy
- Fast MA: TEMA with a period of 8
- Slow MA: EMA with a period of 21
- Active signals: Fast MA Up/Down
- Filters: RSI (range 1-40 for purchases, 60-100 for sales)
- Signal spacing: 3 bars
Strategy for day trading
- Fast MA: TEMA with a period of 10
- Slow MA: SMA with a period of 20
- Active signals: Fast MA Up/Down and Fast vs Slow Greater/Less
- Filters: MFI (range 1-25 for purchases, 75-100 for sales)
- Signal spacing: 5 bars
Swing Trading Strategy
- Fast MA: DEMA with a period of 14
- Slow MA: VWMA with a period of 30
- Active signals: Fast vs Slow Up/Down and Slow MA Greater/Less
- Filters: Stochastic (range 1-20 for purchases, 80-100 for sales)
- Signal spacing: 8 bars
A strategy for positional trading
- Fast MA: HMA with a period of 21
- Slow MA: SMA with a period of 50
- Active signals: Slow MA Up/Down and Fast vs Slow Greater/Less
- Filters: RSI and MFI at the same time
- The distance between the signals: 10 bars
💡 Tips for using AllMA Trend Radar
1. Select the types of MA for market conditions:
- For trending markets: DEMA, TEMA, HMA (fast MA)
- For sideways markets: SMA, WMA, VWMA (smoothed MA)
- For volatile markets: KAMA, AMA, VAMA (adaptive MA)
2. Combine different types of signals:
- Up/Down signals work better when moving from a sideways trend to a directional
one - Greater/Less signals are optimal for fixing a stable trend
3. Use filters effectively:
- The RSI filter works great in trending markets
- MFI filter helps to confirm the strength of volume movement
- Stochastic filter works well in lateral ranges
4. Adjust the minimum distance between the signals:
- Small values (2-3 bars) for short-term trading
- Average values (5-8 bars) for medium-term trading
- Large values (10+ bars) for long-term trading
5. Use combination connectors:
- For more reliable signals, connect the indicator through the combined connectors
💰 With the AllMA Trend Radar indicator, you get a universal trend analysis tool that can be customized for any trading style and timeframe. The combination of different types of moving averages and advanced filters allows you to significantly improve the accuracy of signals and the effectiveness of your trading strategy!
Seasonality - Session Performance - Morning Afternoon EveningUse this indicator on Intraday Timeframe. Higher the timeframe, more the data
This script calculates the performance of an instrument for different sessions.
Session inputs can be updated to study performance of
- Morning vs Afternoon vs Evening
- Pre-Market vs Market vs Post-Market (provided the data feed supports pre and post market)
- Overnight vs Intraday
Three session inputs are provided to tweak the session range
Performance is calculated as session close / session open - 1
Session timeframes can be set for various countries. Make sure the session timeframe aligns with the Candle open/close for the timeframe you choose. Some examples below
US Markets: 0930-1130 1130-1430 1430-1630 Timeframe 1 hour
India Markets: 0915-1030 1030-1415 1415-15:30 Timeframe 75min
TASC 2022.10 RS VA EMA█ OVERVIEW
TASC's October 2022 edition Traders' Tips includes the second part of the "Relative Strength Moving Averages" article series authored by Vitali Apirine. This is the code that implements the Relative Strength Volume-Adjusted Exponential Moving Average (RS VA EMA) presented in this publication.
█ CONCEPTS
In his article series, the author argues that the relative strength of price, volume, and volatility can potentially be used to filter price movements and define turning points. In particular, the RS VA EMA indicator is designed to account for the relative strength of volume. Like the traditional exponential moving average (EMA) , it is a lagging trend-following indicator. The difference is that it responds more quickly.
In a trading strategy, RS VA EMA is suggested to be used in combination with EMA of the same length to determine the overall trend or in combination with RS VA EMA of a different length to identify turning points and filter price movements.
█ CALCULATIONS
The calculation of RS VA EMA is based on the concept of volume strength (VS). By definition, VS measures the difference between "positive" and "negative" volume flow. Volume is indicated as "positive" when the close is higher than the previous close and "negative" when the close is below the previous close.
The following steps are used in the calculation process:
• Calculate the volume strength (VS) of a given length.
• Multiply VS by a predefined multiplier and calculate the EMA of the resulting time series.
The values of 10,10,10 are the typical input settings for RS VA EMA, where the first parameter is the length of the moving average, the second is the length of VS, and the third is the volume strength multiplier.
Strategy Oil Z ScoreObjective is to find forward looking indicators to find good entries into major index's.
In similar vein to my Combo Z Score script I have implemented one looking at oil and oil volatility. Interestingly the script out performs WITHOUT applying the EMA in longer timeframes but under performs in shorter timeframes, for example 2007 vs 2019. Likely due to the bullish nature of the past decade (by and large). You have some options on the underlying included Oil vs OVX (Best), MOVE vs OVX and VIX vs OVX. Oil vs OVX out performs Combo Z Script. Favours Spy over QQQ or derivations (SPXL etc).
GBTC holdings USD market valueThis script estimates GBTC bitcoins per share, rather than hardcoding as in other scripts. Its result is an estimate of GBTC holdings USD market value.
Per share bitcoin estimates are adjusted by 2.0% / 365 per day from 2019 year end holdings. Calendar year 2019 ending bitcoins and shares were 261,192 bitcoins and 269,445,300 shares. From the 2019 Form 10-K: 'The Trust’s only ordinary recurring expense is the Sponsor’s Fee. The Sponsor’s Fee accrues daily in U.S. dollars at an annual rate of 2.0% of the Bitcoin Holdings.. The Sponsor’s Fee is payable in Bitcoins to the Sponsor monthly in arrears.'
No attempt is made to account for leap years.
Per share bitcoin estimate is converted to USD market value by multiplying by the simple average BTCUSD price at Coinbase and Bitstamp. Grayscale uses the TradeBlock XBX index, a volume weighted average of Coinbase Pro, Kraken, LMAX Digital and Bitstamp prices.
Spot checks vs archive.org captures of daily bitcoins per share and the chart on Grayscale's site:
The estimate for market close January 22 2021 is 0.00094899 bitcoins per share, the published datum on Grayscale's web site was 0.00094898. The estimate matches at 20:30 rather than at 16:00.
The estimate for December 31 2018 is 0.000988965 vs a published 0.00098895.
The estimate for December 29 2017 market value is $14.58 vs $14.65.
The estimate for December 30 2016 market value is $0.99 vs $0.98.
The estimate for January 4 2016 market value is $0.46 vs $0.45.
No estimates before 2016.
The default style is to draw a blue line with two thirds transparency outside market hours and for first/last minutes of trading, switching to daily or greater periodicity hides this.
No warranty is expressed or implied , I am not a lawyer, etc etc etc.
This is not investing advice . Always do your own due diligence .
Market Internals [Makit0] MARKET INTERNALS INDICATOR v0.5beta
Market Internals are suitable for day trade equity indices, named SPY or /ES, please do your own research about what they are and how to use them
This scripts plots the NYSE market internals charts as an indicator for an easy and full visualization of market internal structure all in one chart, useful for SPY and /ES trading
Description of the Market Internals
- TICK: NYSE stocks ticking up vs stocks ticking down, extreme values may point to trend continuation on trending days or reversal in non trending days, example of extreme values can be 800 and 1000
- ADD: NYSE stocks going up vs stocks going down, if price auctions around the zero line may be a non trend day, otherwise may be a trend day
- VOLD: NYSE volume of stocks up vs volume of stocks going down, identify clearly where the volume is going, as example if volume is flowing down may be a good idea no to place longs
- TRIN: NYSE up stocks vs down stocks ratio divided by up volume vs down volume ratio. A value of 1 indicates parity, below that the strength is on the long side, above the strength is in the short side.
A basic use of market internals may be looking for divergences, for example:
- /ES is trading in a range but ADD and VOLD are trending up nonstop, may /ES will break the range to the upside
- /ES is trading in a range and ADD and VOLD are trading around the zero line but got an extreme reading on TICK, may be a non trending day and the TICK extreme reading is at one of the extremes of the /ES range, may be a good probability trade to fade that move
- /ES is trading in a trend to the downside, ADD and VOLD too, you catch a good portion of the move but are fearful to flat and miss more gains, you see in the TICK a lot of extreme values below -800 so your're confident in the continuation of the downtrend, until the TICK goes beyond -1000 and you use that signal to go flat
Market internals give you context and confirmation, price in /ES may be trending but if market internals do not confirm the move may a reversal is on its way
Price is an advertise, you can see the real move in the structure below, in the behavior of the individual components of the market, those are the real questions:
- How many stocks are going up/down (ADD)
- How many volume is flowing up/down (VOLD)
- How many stocks are ticking up/down (TICK)
- What is the overall volume breath of the market (TRIN)
FEATURES:
- Plot one of the four basic market internal indices: TICK, ADD, VOLD and TRIN
- Show labels with values beyond an user defined threshold
- Show ZERO line
- Show user defined Dotted and Dashed lines
- Show user defined moving average
SETTINGS:
- Market internal: ticker to plot in the indicator, four options to choose from (TICK, ADD, VOLD and TRIN)
- Labels threshold: all values beyond this will be ploted as labels
- Dot lines at: two dotted lines will be plotted at this value above and below the zero line
- Dash lines at: two dashed lines will be plotted at this value above and below the zero line
- MA type: two options avaiable SMA (Simple Moving Average) or EMA (Exponential Moving Average)
- MA length: number of bars to calculate the moving average
- Show zero line: show or hide zero line
- Show dot line: show or hide dotted lines
- Show dash line: show or hide dashed lines
- Show labels: show or hide labels
GOOD LUCK AND HAPPY TRADING
