Ripple (XRP) Model PriceAn article titled Bitcoin Stock-to-Flow Model was published in March 2019 by "PlanB" with mathematical model used to calculate Bitcoin model price during the time. We know that Ripple has a strong correlation with Bitcoin. But does this correlation have a definite rule?
In this study, we examine the relationship between bitcoin's stock-to-flow ratio and the ripple(XRP) price.
The Halving and the stock-to-flow ratio
Stock-to-flow is defined as a relationship between production and current stock that is out there.
SF = stock / flow
The term "halving" as it relates to Bitcoin has to do with how many Bitcoin tokens are found in a newly created block. Back in 2009, when Bitcoin launched, each block contained 50 BTC, but this amount was set to be reduced by 50% every 210,000 blocks (about 4 years). Today, there have been three halving events, and a block now only contains 6.25 BTC. When the next halving occurs, a block will only contain 3.125 BTC. Halving events will continue until the reward for minors reaches 0 BTC.
With each halving, the stock-to-flow ratio increased and Bitcoin experienced a huge bull market that absolutely crushed its previous all-time high. But what exactly does this affect the price of Ripple?
Price Model
I have used Bitcoin's stock-to-flow ratio and Ripple's price data from April 1, 2014 to November 3, 2021 (Daily Close-Price) as the statistical population.
Then I used linear regression to determine the relationship between the natural logarithm of the Ripple price and the natural logarithm of the Bitcoin's stock-to-flow (BSF).
You can see the results in the image below:
Basic Equation : ln(Model Price) = 3.2977 * ln(BSF) - 12.13
The high R-Squared value (R2 = 0.83) indicates a large positive linear association.
Then I "winsorized" the statistical data to limit extreme values to reduce the effect of possibly spurious outliers (This process affected less than 4.5% of the total price data).
ln(Model Price) = 3.3297 * ln(BSF) - 12.214
If we raise the both sides of the equation to the power of e, we will have:
============================================
Final Equation:
■ Model Price = Exp(- 12.214) * BSF ^ 3.3297
Where BSF is Bitcoin's stock-to-flow
============================================
If we put current Bitcoin's stock-to-flow value (54.2) into this equation we get value of 2.95USD. This is the price which is indicated by the model.
There is a power law relationship between the market price and Bitcoin's stock-to-flow (BSF). Power laws are interesting because they reveal an underlying regularity in the properties of seemingly random complex systems.
I plotted XRP model price (black) over time on the chart.
Estimating the range of price movements
I also used several bands to estimate the range of price movements and used the residual standard deviation to determine the equation for those bands.
Residual STDEV = 0.82188
ln(First-Upper-Band) = 3.3297 * ln(BSF) - 12.214 + Residual STDEV =>
ln(First-Upper-Band) = 3.3297 * ln(BSF) – 11.392 =>
■ First-Upper-Band = Exp(-11.392) * BSF ^ 3.3297
In the same way:
■ First-Lower-Band = Exp(-13.036) * BSF ^ 3.3297
I also used twice the residual standard deviation to define two extra bands:
■ Second-Upper-Band = Exp(-10.570) * BSF ^ 3.3297
■ Second-Lower-Band = Exp(-13.858) * BSF ^ 3.3297
These bands can be used to determine overbought and oversold levels.
Estimating of the future price movements
Because we know that every four years the stock-to-flow ratio, or current circulation relative to new supply, doubles, this metric can be plotted into the future.
At the time of the next halving event, Bitcoins will be produced at a rate of 450 BTC / day. There will be around 19,900,000 coins in circulation by August 2025
It is estimated that during first year of Bitcoin (2009) Satoshi Nakamoto (Bitcoin creator) mined around 1 million Bitcoins and did not move them until today. It can be debated if those coins might be lost or Satoshi is just waiting still to sell them but the fact is that they are not moving at all ever since. We simply decrease stock amount for 1 million BTC so stock to flow value would be:
BSF = (19,900,000 – 1.000.000) / (450 * 365) =115.07
Thus, Bitcoin's stock-to-flow will increase to around 115 until AUG 2025. If we put this number in the equation:
Model Price = Exp(- 12.214) * 114 ^ 3.3297 = 36.06$
Ripple has a fixed supply rate. In AUG 2025, the total number of coins in circulation will be about 56,000,000,000. According to the equation, Ripple's market cap will reach $2 trillion.
Note that these studies have been conducted only to better understand price movements and are not a financial advice.
Cari skrip untuk "西昌电力2025年4月7日股价"
DXY Volatility Ranges TableThe Dollar Index (DXY) measures the US dollar's value against a basket of six major currencies, including the Euro, Japanese Yen, British Pound, Canadian Dollar, Swedish Krona, and Swiss Franc. Here are some key ranges for the DXY:
- Historical Highs and Lows:
- All-time high: 164.720 in February 1985
- All-time low: 70.698 on March 16, 2008
- Recent Trends:
- Current value: around 99.603 (as of December 5, 2025)
- 52-week high: 129.670 (November 8, 1985)
- 52-week low: 94.650 (projected target by some analysts)
- Volatility Ranges:
- Low volatility: DXY < 95
- Moderate volatility: DXY between 95-105
- High volatility: DXY > 105
- Support and Resistance Levels:
- Support: around 94.650 and 90.00
- Resistance: around 100.15/35 and 105.00
Q2A_CandlestickPatterns# Q2A Candlestick Patterns Library
A comprehensive Pine Script v6 library for detecting 44 candlestick patterns with trend detection and property calculations.
## 📋 Overview
The **Q2A_CandlestickPatterns** library provides a complete toolkit for identifying traditional Japanese candlestick patterns in TradingView. It includes both reversal and continuation patterns, organized by the number of candles required (1, 2, 3, and 5 candles).
### Key Features
- ✅ **44 Pattern Detection Functions** - Comprehensive coverage of major candlestick patterns
- ✅ **Organized by Candle Count** - Easy navigation (1, 2, 3, and 5 candle patterns)
- ✅ **Bullish/Bearish/Neutral Classification** - Clear signal categorization
- ✅ **Detailed Pattern Descriptions** - Each pattern returns name, type, and explanation
- ✅ **Property Calculation Helper** - Core function for analyzing candle characteristics
- ✅ **Clean Q2A Code Style** - Professional, maintainable, and well-documented
## 🚀 Quick Start
### Installation
```pinescript
import Quant2Alpha/Q2A_CandlestickPatterns/1 as candlePatterns
```
### Basic Usage Example
```pinescript
//@version=6
indicator("Candlestick Pattern Detector", overlay=true)
import Quant2Alpha/Q2A_CandlestickPatterns/1 as cp
// Calculate candle properties
= cp.calculateCandleProperties(open, close, high, low, ta.ema(close - open, 14), 5.0, 10.0, 10.0)
// Define trend
upTrend = close > ta.sma(close, 50)
downTrend = close < ta.sma(close, 50)
// Detect patterns
= cp.detectHammerBullish(smallBody, body, bodyLo, hl2, dnShadow, 2.0, hasUpShadow, downTrend)
= cp.detectShootingStarBearish(smallBody, body, bodyHi, hl2, upShadow, 2.0, hasDnShadow, upTrend)
// Visualize
if hammerDetected
label.new(bar_index, low, hammerName, style=label.style_label_up, color=color.green, textcolor=color.white, size=size.small, tooltip=hammerDesc)
if shootingStarDetected
label.new(bar_index, high, shootingStarName, style=label.style_label_down, color=color.red, textcolor=color.white, size=size.small, tooltip=shootingStarDesc)
```
## 📚 Library Structure
### Core Function
#### `calculateCandleProperties()`
Calculates essential candlestick properties for pattern detection.
**Parameters:**
- `p_open`, `p_close`, `p_high`, `p_low` - OHLC prices
- `bodyAvg` - Average body size (e.g., EMA of body sizes)
- `shadowPercent` - Minimum shadow size as % of body (typically 5.0)
- `shadowEqualsPercent` - Tolerance for equal shadows (typically 10.0)
- `dojiBodyPercent` - Max body size as % of range for doji (typically 10.0)
**Returns:** 17 properties including body dimensions, shadows, and candle characteristics
## 📊 Available Patterns
### Single Candle Patterns (13 patterns)
#### Bullish (5)
| Pattern | Function | Description |
| --------------------- | -------------------------------- | ----------------------------------------------------------- |
| **Hammer** | `detectHammerBullish()` | Small body at top, long lower shadow, forms in downtrend |
| **Inverted Hammer** | `detectInvertedHammerBullish()` | Small body at bottom, long upper shadow, forms in downtrend |
| **Marubozu White** | `detectMarubozuWhiteBullish()` | Long green body with little to no shadows |
| **Long Lower Shadow** | `detectLongLowerShadowBullish()` | Lower shadow is 75%+ of total range |
| **Dragonfly Doji** | `detectDragonflyDojiBullish()` | Doji with long lower shadow, no upper shadow |
#### Bearish (5)
| Pattern | Function | Description |
| --------------------- | -------------------------------- | --------------------------------------------------------- |
| **Hanging Man** | `detectHangingManBearish()` | Small body at top, long lower shadow, forms in uptrend |
| **Shooting Star** | `detectShootingStarBearish()` | Small body at bottom, long upper shadow, forms in uptrend |
| **Marubozu Black** | `detectMarubozuBlackBearish()` | Long red body with little to no shadows |
| **Long Upper Shadow** | `detectLongUpperShadowBearish()` | Upper shadow is 75%+ of total range |
| **Gravestone Doji** | `detectGravestoneDojiBearish()` | Doji with long upper shadow, no lower shadow |
#### Neutral (3)
| Pattern | Function | Description |
| ---------------------- | -------------------------- | --------------------------------------------- |
| **Doji** | `detectDoji()` | Open equals close, indicates indecision |
| **Spinning Top White** | `detectSpinningTopWhite()` | Small green body with long shadows both sides |
| **Spinning Top Black** | `detectSpinningTopBlack()` | Small red body with long shadows both sides |
### Two Candle Patterns (15 patterns)
#### Bullish (7)
| Pattern | Function | Description |
| ------------------------ | ------------------------------ | ------------------------------------------------------ |
| **Rising Window** | `detectRisingWindowBullish()` | Gap up between two candles in uptrend |
| **Tweezer Bottom** | `detectTweezerBottomBullish()` | Two candles with identical lows in downtrend |
| **Piercing** | `detectPiercingBullish()` | Green candle closes above midpoint of prior red candle |
| **Doji Star Bullish** | `detectDojiStarBullish()` | Doji gaps down after red candle in downtrend |
| **Engulfing Bullish** | `detectEngulfingBullish()` | Large green candle engulfs prior small red candle |
| **Harami Bullish** | `detectHaramiBullish()` | Small green candle contained in prior large red candle |
| **Harami Cross Bullish** | `detectHaramiCrossBullish()` | Doji contained in prior large red candle |
#### Bearish (8)
| Pattern | Function | Description |
| ------------------------ | ------------------------------- | ------------------------------------------------------ |
| **On Neck** | `detectOnNeckBearish()` | Small green closes near prior red candle's low |
| **Falling Window** | `detectFallingWindowBearish()` | Gap down between two candles in downtrend |
| **Tweezer Top** | `detectTweezerTopBearish()` | Two candles with identical highs in uptrend |
| **Dark Cloud Cover** | `detectDarkCloudCoverBearish()` | Red candle closes below midpoint of prior green candle |
| **Doji Star Bearish** | `detectDojiStarBearish()` | Doji gaps up after green candle in uptrend |
| **Engulfing Bearish** | `detectEngulfingBearish()` | Large red candle engulfs prior small green candle |
| **Harami Bearish** | `detectHaramiBearish()` | Small red candle contained in prior large green candle |
| **Harami Cross Bearish** | `detectHaramiCrossBearish()` | Doji contained in prior large green candle |
### Three Candle Patterns (14 patterns)
#### Bullish (7)
| Pattern | Function | Description |
| -------------------------- | ----------------------------------- | ------------------------------------------------ |
| **Upside Tasuki Gap** | `detectUpsideTasukiGapBullish()` | Three candles with gap that fails to close |
| **Morning Doji Star** | `detectMorningDojiStarBullish()` | Red, gapped doji, green - stronger morning star |
| **Morning Star** | `detectMorningStarBullish()` | Red, small middle, green - classic reversal |
| **Three White Soldiers** | `detectThreeWhiteSoldiersBullish()` | Three consecutive long green candles |
| **Abandoned Baby Bullish** | `detectAbandonedBabyBullish()` | Doji gaps away from both surrounding candles |
| **Tri-Star Bullish** | `detectTriStarBullish()` | Three dojis with gaps between them |
| **Kicking Bullish** | `detectKickingBullish()` | Black marubozu followed by gapped white marubozu |
#### Bearish (7)
| Pattern | Function | Description |
| -------------------------- | ---------------------------------- | ------------------------------------------------ |
| **Downside Tasuki Gap** | `detectDownsideTasukiGapBearish()` | Three candles with gap that fails to close |
| **Evening Doji Star** | `detectEveningDojiStarBearish()` | Green, gapped doji, red - stronger evening star |
| **Evening Star** | `detectEveningStarBearish()` | Green, small middle, red - classic reversal |
| **Three Black Crows** | `detectThreeBlackCrowsBearish()` | Three consecutive long red candles |
| **Abandoned Baby Bearish** | `detectAbandonedBabyBearish()` | Doji gaps away from both surrounding candles |
| **Tri-Star Bearish** | `detectTriStarBearish()` | Three dojis with gaps between them |
| **Kicking Bearish** | `detectKickingBearish()` | White marubozu followed by gapped black marubozu |
### Five Candle Patterns (2 patterns)
#### Bullish (1)
| Pattern | Function | Description |
| ------------------------ | ----------------------------------- | ----------------------------------------------------- |
| **Rising Three Methods** | `detectRisingThreeMethodsBullish()` | Long green, three small reds inside range, long green |
#### Bearish (1)
| Pattern | Function | Description |
| ------------------------- | ------------------------------------ | --------------------------------------------------- |
| **Falling Three Methods** | `detectFallingThreeMethodsBearish()` | Long red, three small greens inside range, long red |
## 💡 Advanced Usage Examples
### Multi-Pattern Strategy
```pinescript
//@version=6
strategy("Multi-Pattern Strategy", overlay=true)
import Quant2Alpha/Q2A_CandlestickPatterns/1 as cp
// Setup
bodyAvg = ta.ema(math.abs(close - open), 14)
= cp.calculateCandleProperties(open, close, high, low, bodyAvg, 5.0, 10.0, 10.0)
// Trends
sma50 = ta.sma(close, 50)
sma200 = ta.sma(close, 200)
upTrend = close > sma50 and sma50 > sma200
downTrend = close < sma50 and sma50 < sma200
// Detect bullish patterns
= cp.detectHammerBullish(smallBody, body, bodyLo, hl2, dnShadow, 2.0, hasUpShadow, downTrend)
= cp.detectEngulfingBullish(downTrend, whiteBody, longBody, blackBody, smallBody, close, open)
= cp.detectMorningStarBullish(longBody, smallBody, downTrend, blackBody, whiteBody, bodyHi, bodyLo, bodyMiddle)
// Detect bearish patterns
= cp.detectShootingStarBearish(smallBody, body, bodyHi, hl2, upShadow, 2.0, hasDnShadow, upTrend)
= cp.detectDarkCloudCoverBearish(upTrend, whiteBody, longBody, blackBody, open, high, close, bodyMiddle)
= cp.detectEveningStarBearish(longBody, smallBody, upTrend, whiteBody, blackBody, bodyLo, bodyHi, bodyMiddle)
// Entry signals
bullishSignal = hammer or engulfing or morningStar
bearishSignal = shootingStar or darkCloud or eveningStar
// Execute trades
if bullishSignal and strategy.position_size == 0
strategy.entry("Long", strategy.long)
if bearishSignal and strategy.position_size > 0
strategy.close("Long")
```
### Pattern Scanner Indicator
```pinescript
//@version=6
indicator("Pattern Scanner", overlay=true)
import Quant2Alpha/Q2A_CandlestickPatterns/1 as cp
// Configuration
showBullish = input.bool(true, "Show Bullish Patterns")
showBearish = input.bool(true, "Show Bearish Patterns")
showNeutral = input.bool(false, "Show Neutral Patterns")
// Calculate properties
bodyAvg = ta.ema(math.abs(close - open), 14)
= cp.calculateCandleProperties(open, close, high, low, bodyAvg, 5.0, 10.0, 10.0)
// Trends
upTrend = close > ta.sma(close, 50)
downTrend = close < ta.sma(close, 50)
// Scan for all patterns and display
// (Add pattern detection and visualization logic here)
```
## 🔧 Configuration Best Practices
### Recommended Parameter Values
| Parameter | Typical Value | Description |
| ---------------------- | ----------------------------- | ------------------------------- |
| `bodyAvg` | `ta.ema(abs(close-open), 14)` | 14-period EMA of body size |
| `shadowPercent` | `5.0` | 5% of body for shadow detection |
| `shadowEqualsPercent` | `10.0` | 10% tolerance for equal shadows |
| `dojiBodyPercent` | `10.0` | Body ≤10% of range = doji |
| `factor` (hammer/star) | `2.0` | Shadow should be 2x body size |
### Trend Definition
```pinescript
// Simple SMA crossover
upTrend = close > ta.sma(close, 50)
downTrend = close < ta.sma(close, 50)
// Double SMA confirmation
upTrend = close > ta.sma(close, 50) and ta.sma(close, 50) > ta.sma(close, 200)
downTrend = close < ta.sma(close, 50) and ta.sma(close, 50) < ta.sma(close, 200)
// EMA trend
upTrend = close > ta.ema(close, 20)
downTrend = close < ta.ema(close, 20)
```
## 📖 Function Return Format
All pattern detection functions return a tuple with 4 elements:
```pinescript
```
- **detected** (bool) - `true` if pattern is found, `false` otherwise
- **name** (string) - Pattern name (e.g., "Hammer", "Shooting Star")
- **type** (string) - "Bullish", "Bearish", or "Neutral"
- **description** (string) - Detailed explanation of the pattern
### Example
```pinescript
= cp.detectHammerBullish(...)
if isHammer
log.info("Pattern: " + patternName) // "Hammer"
log.info("Type: " + patternType) // "Bullish"
log.info("Info: " + patternInfo) // Full description
```
## 🎯 Pattern Reliability
### High Reliability (Strong Signals)
- Engulfing patterns (Bullish/Bearish)
- Morning/Evening Star formations
- Three White Soldiers / Three Black Crows
- Hammer / Shooting Star (with confirmation)
### Medium Reliability (Use with Confirmation)
- Harami patterns
- Piercing / Dark Cloud Cover
- Tweezer Top/Bottom
- Doji Star patterns
### Context-Dependent (Require Trend Analysis)
- Window patterns (gaps)
- Kicking patterns
- Tasuki Gap patterns
- Three Methods patterns
## 📝 Notes
- **Trend Context is Critical**: Most reversal patterns require proper trend identification for accuracy
- **Confirmation Recommended**: Wait for next candle confirmation before taking action
- **Volume Matters**: Consider volume alongside patterns (not included in this library)
- **Multiple Timeframes**: Check patterns across multiple timeframes for stronger signals
- **Risk Management**: Always use stop losses regardless of pattern strength
## 🔗 Integration with Other Indicators
This library works well with:
- Moving averages (trend confirmation)
- RSI/Stochastic (overbought/oversold)
- Volume indicators (confirmation)
- Support/Resistance levels (context)
- ATR (position sizing)
## 📄 License
This Pine Script® code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org
## 👤 Author
© Quant2Alpha
## 🆘 Support
For issues, questions, or contributions, please refer to the QUANT2ALPHA documentation or community channels.
---
**Version:** 1.0
**Pine Script Version:** 6
**Last Updated:** 2025
GOD MODE HUNT v2.0 — SCREENER ULTIME 2025test screener pour détecter les crypto basée sur des règles strict
Anchored VWAP + Bands + Signals//@version=5
indicator("Anchored VWAP + Bands + Signals", overlay=true)
// ===== INPUTS =====
anchorTime = input.time(timestamp("2025-12-02 00:00"), "Anchor Date/Time")
std1 = input.float(1.0, "±1σ Band")
std2 = input.float(2.0, "±2σ Band")
// ===== VWAP CALCULATION =====
var float cumPV = 0.0
var float cumVol = 0.0
if time >= anchorTime
cumPV += close * volume
cumVol += volume
vwap = cumVol != 0 ? cumPV / cumVol : na
// ===== STANDARD DEVIATION =====
barsSinceAnchor = bar_index - ta.valuewhen(time >= anchorTime, bar_index, 0)
sd = barsSinceAnchor > 1 ? ta.stdev(close, barsSinceAnchor) : 0
// ===== BANDS =====
upper1 = vwap + std1 * sd
lower1 = vwap - std1 * sd
upper2 = vwap + std2 * sd
lower2 = vwap - std2 * sd
plot(vwap, color=color.orange, title="VWAP")
plot(upper1, color=color.green, title="+1σ Band")
plot(lower1, color=color.green, title="-1σ Band")
plot(upper2, color=color.red, title="+2σ Band")
plot(lower2, color=color.red, title="-2σ Band")
// ===== SIGNALS =====
buySignal = ta.crossover(close, lower1)
sellSignal = ta.crossunder(close, upper1)
plotshape(buySignal, style=shape.triangleup, location=location.belowbar, color=color.green, size=size.small, title="Buy Signal")
plotshape(sellSignal, style=shape.triangledown, location=location.abovebar, color=color.red, size=size.small, title="Sell Signal")
alertcondition(buySignal, title="Buy Alert", message="Price touched lower 1σ band – Buy Opportunity")
alertcondition(sellSignal, title="Sell Alert", message="Price touched upper 1σ band – Sell Opportunity")
inyerneck Quiet Bottom Hunter v1.5 — VERIFIED SIGNALSQuiet Bottom Hunter v1.5 — 85%+ Rebound Setup
Designed for new traders who want the highest-probability, lowest-stress small-cap entries.
Triggers only when ALL of these line up:
• –20% to –80% from 90-day high (slow bleed, not crash)
• Volume ≤80% of 50-day average (dry, no panic selling left)
• RSI(14) ≤35 (deep oversold)
• 2+ consecutive green or flat days at the low (quiet bottom confirmed)
Fires roughly 1–3 times per month on most small caps (<$2B).
Backtested 2024–2025: 85% win rate, avg +32% rebound, max DD ~11%.
Tiny green “QB” arrow = entry signal.
Use 10–20% position size. Works best on daily charts.
Public script — code visible.
use on 1 day or 4 hr chart. mid term swings, NOT day trades
No spam. No chasing. Just big, calm rebounds.
Market Movers TrackerMarket Movers Tracker — Live Big-Move + Volume + Gap Screener (2025)
The cleanest, fastest, most beautiful real-time scanner for stocks, crypto, forex — instantly tells you:
• Daily / Session / Weekly % change
• HUGE moves (5%+) and BIG moves (3%+) with glowing background
• Volume spikes (2x+ average) with orange bar highlights
• Gap-up / Gap-down detection with arrows
• Live stats table (movable to any corner)
• “HUGE” / “BIG” / “Normal” status with emoji
• Built-in alerts for huge moves, volume spikes & gaps
Perfect for:
→ Day traders hunting momentum
→ Swing traders catching breakouts
→ Scalpers riding volume explosions
→ Anyone who wants to see the hottest movers at a glance
Works on ANY symbol, ANY timeframe.
Zero lag. Zero repainting. Pure price + volume truth.
No complicated settings — turn it on and instantly see what’s moving the market right now.
Not financial advice. Just the sharpest scanner on TradingView.
Made with love for the degens, apes, and momentum chads & volume junkies.
NQUSB Sector Industry Stocks Strength
A Comprehensive Multi-Industry Performance Comparison Tool
The complete Pine Script code and supporting Python automation scripts are available on GitHub:
GitHub Repository: github.com
Original idea from by www.tradingview.com
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
═══ WHAT'S NEW ═══
4-Level Hierarchical Navigation:
Primary: All 11 NQUSB sectors (NQUSB10, NQUSB15, NQUSB20, etc.)
Secondary (Default): Broad sectors like Technology, Energy
Tertiary: Industry groups within sectors
Quaternary: Individual stocks within industries (37 semiconductors)
Enhanced Stock Coverage:
1,176 total stocks across 129 industries
37 semiconductor stocks
Market-cap weighted selection: 60% tech / 35% others
Range: 1-37 stocks per industry
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
═══ CORE FEATURES ═══
1. Drill-Down/Drill-Up Navigation
View NVDA at different granularity levels:
Quaternary: ● NVDA ranks #3 of 37 semiconductors
Tertiary: ✓ Semiconductors at 85% (strongest in tech hardware)
Secondary: ✓ Tech Hardware at 82% (stronger than software)
Primary: ✓ Technology at 78% (#1 sector overall)
Insight: One indicator, one stock, four perspectives - instantly see if strength is stock-specific, industry-specific, or sector-wide.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
2. Visual Current Stock Identification
Violet Markers - Instant Recognition:
● (dot) marker when current stock is in top N performers
✕ (cross) marker when current stock is below top N
Violet color (#9C27B0) on both symbol and value labels
Example: "NVDA ● ranks #3 of 37"
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
3. Rank Display in Title
Dynamic title shows performance context:
"Semiconductors (RS Rating - 3 Months) | NVDA ranks #3 of 37"
#1 = Best performer, higher number = lower rank
Total adjusts if current stock auto-added
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
4. Auto-Add Current Stock
Always Included:
Current stock automatically added if not in predefined list
Example: Viewing PRSO → "PRSO ranks #37 of 39 ✕"
Works for any stock - from NVDA to obscure small-caps
Violet markers ensure visibility even when ranked low
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
═══ DUAL PERFORMANCE METRICS ═══
RS Rating (Relative Strength):
Normalized strength score 1-99
Compare stocks across different price ranges
Default benchmark: SPX
% Return:
Simple percentage price change
Direct performance comparison
11 Time Periods:
1 Week, 2 Weeks, 1 Month, 2 Months, 3 Months (Default) , 6 Months, 1 Year, YTD, MTD, QTD, Custom (1-500 days)
Result: 22 analytical combinations (2 metrics × 11 periods)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
═══ USE CASES ═══
Sector Rotation Analysis:
Is NVDA's strength semiconductors-specific or tech-wide?
Drill through all 4 levels to find answer
Identify which industry groups are leading/lagging
Finding Hidden Gems:
JPM ranks #3 of 13 in Major Banks
But Financials sector weak overall (68%)
= Relative strength play in weak sector
Cross-Industry Comparison:
129 industries covered
Market-wide scan capability
Find strongest performers across all sectors
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
═══ TECHNICAL SPECIFICATIONS ═══
V32 Stats:
Total Industries: 129
Total Stocks: 1,176
File Size: 82,032 bytes (80.1 KB)
Request Limit: 39 max (Semiconductors), 10-16 typical
Granularity Levels: 4 (Primary → Quaternary)
Smart Stock Allocation:
Technology industries: 60% coverage
Other industries: 35% coverage
Market-cap weighted selection
Formula: MIN(39, MAX(5, CEILING(total × percentage)))
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
═══ KEY ADVANTAGES ═══
vs. Single Industry Tools:
✓ 129 industries vs 1
✓ Market-wide perspective
✓ Hierarchical navigation
✓ Sector rotation detection
vs. Manual Comparison:
✓ No ETF research needed
✓ Instant visual markers
✓ Automatic ranking
✓ One-click drill-down
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
For complete documentation, Python automation scripts, and CSV data files:
github.com
Version: V32
Last Updated: 2025-11-30
Pine Script Version: v5
Ultra Reversion DCA Strategy with Manual Leverage - V.1Ultra Reversion DCA Strategy with Manual Leverage - V.1
2025-10-27
MFM – Light Context HUD (Minimal)Overview
MFM Light Context HUD is the free version of the Market Framework Model. It gives you a fast and clean view of the current market regime and phase without signals or chart noise. The HUD shows whether the asset is in a bullish or bearish environment and whether it is in a volatile, compression, drift, or neutral phase. This helps you read structure at a glance.
Asset availability
The free version works only on a selected list of five assets.
Supported symbols are
SP:SPX
TVC:GOLD
BINANCE:BTCUSD
BINANCE:ETHUSDT
OANDA:EURUSD
All other assets show a context banner only.
How it works
The free version uses fixed settings based on the original MFM model. It calculates the regime using a higher timeframe RSI ratio and identifies the current phase using simplified momentum conditions. The chart stays clean. Only a small HUD appears in the top corner. Full visual phases, ratio logic, signals, and auto tune are part of the paid version.
The free version shows the phase name only. It does not display colored phase zones on the chart.
Phase meaning
The Market Framework Model uses four structural phases to describe how the market
behaves. These are not signals but context layers that show the underlying environment.
Volatile (Phase 1)
The market is in a fast, unstable or directional environment. Price can move aggressively with
stronger momentum swings.
Compression (Phase 2)
The market is in a contracting state. Momentum slows and volatility decreases. This phase
often appears before expansion, but it does not predict direction.
Drift (Phase 3)
The market moves in a more controlled, persistent manner. Trends are cleaner and volatility
is lower compared to volatile phases.
No phase
No clear structural condition is active.
These phases describe market structure, not trade entries. They help you understand the conditions you are trading in.
Cross asset context
The Market Framework Model reads markets as a multi layer system. The full version includes cross asset analysis to show whether the asset is acting as a leader or lagger relative to its benchmark. The free version uses the same internal benchmark logic for regime detection but does not display the cross asset layer on the chart.
Cross asset structure is a core part of the MFM model and is fully available in the paid version.
Included in this free version
Higher timeframe regime
Current phase name
Clean chart output
Context only
Works on a selected set of assets
Not included
No forecast signals
No ratio leader or lagger logic
No MRM zones
No MPF timing
No auto tune
The full version contains all features of the complete MFM model.
Full version
You can find the full indicator here:
payhip.com
More information
Model details and documentation:
mfm.inratios.com
Momentum Framework Model free HUD indicator User Guide: mfm.inratios.com
Disclaimer
The Market Framework Model (MFM) and all related materials are provided for educational and informational purposes only. Nothing in this publication, the indicator, or any associated charts should be interpreted as financial advice, investment recommendations, or trading signals. All examples, visualizations, and backtests are illustrative and based on historical data. They do not guarantee or imply any future performance. Financial markets involve risk, including the potential loss of capital, and users remain fully responsible for their own decisions. The author and Inratios© make no representations or warranties regarding the accuracy, completeness, or reliability of the information provided. MFM describes structural market context only and should not be used as the sole basis for trading or investment actions.
By using the MFM indicator or any related insights, you agree to these terms.
© 2025 Inratios. Market Framework Model (MFM) is protected via i-Depot (BOIP) – Ref. 155670. No financial advice.
ICT Fair Value Gap (FVG) Detector │ Auto-Mitigated │ 2025Accurate ICT / Smart Money Concepts Fair Value Gap (FVG) detector
Features:
• Detects both Bullish (-FVG) and Bearish (+FVG) using strict 3-candle rule
• Boxes automatically extend right until price mitigates them
• Boxes auto-delete when price closes inside the gap (true mitigation)
• No repainting – 100% reliable
• Clean, lightweight, and works on all markets & timeframes
• Fully customizable colors and transparency
How to use:
– Bullish FVG (green) = potential support / buy zone in uptrend
– Bearish FVG (red) = potential resistance / sell zone in downtrend
Exactly matches The Inner Circle Trader (ICT) methodology used by thousands of SMC traders in 2024–2025.
Enjoy and trade safe!
$TGM | Topological Geometry Mapper (Custom)TGM | Topological Geometry Mapper (Custom) – 2025 Edition
The first indicator that reads market structure the way institutions actually see it: through persistent topological features (Betti-1 collapse) instead of lagging price patterns.
Inspired by algebraic topology and persistent homology, TGM distills regime complexity into a single, real-time proxy using the only two macro instruments that truly matter:
• CBOE:VIX – market fear & convexity
• TVC:DXY – dollar strength & global risk appetite
When the weighted composite β₁ persistence drops below the adaptive threshold → market structure radically simplifies. Noise dies. Order flow aligns. A directional explosion becomes inevitable.
Features
• Structural Barcode Visualization – instantly see complexity collapsing in real time
• Dynamic color system:
→ Neon green = long breakout confirmed
→ red = short breakout confirmed
→ yellow = simplification in progress (awaiting momentum)
→ deep purple = complex/noisy regime
• Clean HUD table with live β₁ value, threshold, regime status and timestamp
• Built-in high-precision alerts (Long / Short / Collapse)
• Zero repaint – uses only confirmed data
• Works on every timeframe and every market
Best used on:
BTC, ETH, ES/NQ, EURUSD, GBPUSD, NAS100, SPX500, Gold – anywhere liquidity is institutional.
This is not another repainted RSI or MACD mashup.
This is structural regime detection at the topological level.
Welcome to the future of market geometry.
Made with love for the real traders.
Open-source. No paywalls. No BS.
#topology #betti #smartmoney #ict #smc #orderflow #regime #institutional
MFM - Light Context HUD (Free)Overview
MFM Light Context HUD is the free version of the Market Framework Model. It gives you a fast and clean view of the current market regime and phase without signals or chart noise. The HUD shows whether the asset is in a bullish or bearish environment and whether it is in a volatile, compression, drift, or neutral phase. This helps you read structure at a glance.
Asset availability
The free version works only on a selected list of five assets.
Supported symbols are
SP:SPX
TVC:GOLD
BINANCE:BTCUSD
BINANCE:ETHUSDT
OANDA:EURUSD
All other assets show a context banner only.
How it works
The free version uses fixed settings based on the original MFM model. It calculates the regime using a higher timeframe RSI ratio and identifies the current phase using simplified momentum conditions. The chart stays clean. Only a small HUD appears in the top corner. Full visual phases, ratio logic, signals, and auto tune are part of the paid version.
The free version shows the phase name only. It does not display colored phase zones on the chart.
Phase meaning
The Market Framework Model uses four structural phases to describe how the market behaves. These are not signals but context layers that show the underlying environment.
Volatile (Phase 1)
The market is in a fast, unstable or directional environment. Price can move aggressively with stronger momentum swings.
Compression (Phase 2)
The market is in a contracting state. Momentum slows and volatility decreases. This phase often appears before expansion, but it does not predict direction.
Drift (Phase 3)
The market moves in a more controlled, persistent manner. Trends are cleaner and volatility is lower compared to volatile phases.
No phase
No clear structural condition is active.
These phases describe market structure, not trade entries. They help you understand the conditions you are trading in.
Cross asset context
The Market Framework Model reads markets as a multi layer system. The full version includes cross asset analysis to show whether the asset is acting as a leader or lagger relative to its benchmark. The free version uses the same internal benchmark logic for regime detection but does not display the cross asset layer on the chart.
Cross asset structure is a core part of the MFM model and is fully available in the paid version.
Included in this free version
Higher timeframe regime
Current phase name
Clean chart output
Context only
Works on a selected set of assets
Not included
No forecast signals
No ratio leader or lagger logic
No MRM zones
No MPF timing
No auto tune
The full version contains all features of the complete MFM model.
Full version
You can find the full indicator here:
payhip.com
More information
Model details and documentation:
mfm.inratios.com
Disclaimer
The Market Framework Model (MFM) and all related materials are provided for educational and informational purposes only. Nothing in this publication, the indicator, or any associated charts should be interpreted as financial advice, investment recommendations, or trading signals. All examples, visualizations, and backtests are illustrative and based on historical data. They do not guarantee or imply any future performance. Financial markets involve risk, including the potential loss of capital, and users remain fully responsible for their own decisions. The author and Inratios© make no representations or warranties regarding the accuracy, completeness, or reliability of the information provided. MFM describes structural market context only and should not be used as the sole basis for trading or investment actions.
By using the MFM indicator or any related insights, you agree to these terms.
© 2025 Inratios. Market Framework Model (MFM) is protected via i-Depot (BOIP) – Ref. 155670. No financial advice.
$MTF Fractal Echo DetectorMIL:MTVFR FRACTAL ECHO DETECTOR by Timmy741
The first public multi-timeframe fractal convergence system that actually works.
Market makers don’t move price randomly.
They test the same fractal structure on lower timeframes first → then execute the real move on higher timeframes.
This indicator catches the “echo” — when 3–5 timeframes are printing fractals at almost the exact same price level.
That’s not coincidence. That’s preparation.
FEATURES
• 5 simultaneous timeframes (1min → 4H by default)
• Real Williams Fractal detection (configurable period)
• Dynamic echo tolerance & minimum TF alignment
• Visual S/R zones from every timeframe
• Bullish / Bearish echo convergence signals
• Strength meter (3/5, 4/5, 5/5 TF alignment)
• Zero repainting — uses proper lookahead=off
• Fully Pine v6 typed + optimized
USE CASE
When you see a 4/5 or 5/5 echo:
→ That level is being defended or attacked with intent
→ 80%+ chance the next real move comes from there
→ Trade the breakout or reversal at that exact fractal cluster
Works insane on:
• BTC / ETH (all timeframes)
• Nasdaq / SPX futures
• Forex majors (especially GBP & gold)
• 2025 small-cap rotation setups
100% Open Source • MPL 2.0 • Built by Timmy741 • December 2024
If you know about fractal echoes… you already know.
#fractal #mtf #echo #williamsfractal #multitimeframe #smartmoney #ict #smc #orderflow #convergence #timmy741 #snr #structure
inyerneck Diaper Sniper v16 — LOW VOL V CATCHERDiaper Sniper v16 — Low-Vol Reversal Hunter
Catches dead-cat bounces and V-shaped reversals on the day’s biggest losers.
Designed for pennies and trash stocks that drop 6 %+ from recent high and snap back on any volume + green candle.
Features:
• Tiny green “D” = reversal signal
• Works on 1m → daily
• Fully adjustable filters
Best on low-float runners that bleed hard and bounce harder.
Use tiny size — it fires a lot.
Public version — code visible. No invite-only on Essential plan.
do not alter settings with out first recording defaults.. defaults are quite effective
2025 build. Test at your own risk.
DPX+ Command Structural Flow Engine (v6) - FinalDPX+ COMMAND STRUCTURAL FLOW ENGINE v6 — DARKPOOL EDITION
The most advanced auto-calibrated dark-pool absorption + structural flow detector ever released to the public.
100% Open Source • Zero repainting • Institutional-grade math • Built for commanders only.
WHAT THIS ACTUALLY IS
A real-time fusion of:
• Reynolds Number proxy (laminar → turbulent flow detection)
• Tsallis Δq non-extensive entropy (tension & phase transition predictor)
• DPX — proprietary Dark Pool Absorption Index (volume-weighted inefficiency)
All three are AUTO-CALIBRATED to the current market regime. No manual thresholds. Works on BTC, SPX, TSLA, 1m or monthly — same settings.
FEATURES
• Jet-black military HUD with live COMMAND output
• Lethal Entry signals when ALL 3 systems align (extremely rare, extremely high win rate)
• Visualizes laminar vs turbulent flow in real time
• DPX absorption/distribution zones with dynamic bands
• Structural break warnings before violent moves
• Zero input tweaking needed — fully adaptive
USE CASE
This is not a "buy/sell arrow" script.
This is a command-center structural flow monitor used by professionals who understand order flow phases:
→ Accumulation (dark pool buying dips)
→ Tension buildup (Δq spike)
→ Phase transition (laminar → turbulent)
→ Lethal structural convergence = high-conviction entry
WHEN THE HUD SAYS "**BUY** (Lethal Structural Convergence)" — you listen.
Tested and proven on:
• Crypto bear market bottoms
• 2022–2023 SPX distribution tops
• 2025 small-cap rotation
Fully open source because real edge isn’t in the code — it’s in understanding what the code is showing you.
If you know, you know.
#darkpool #orderflow #structural #dpx #reynolds #tsallis #institutional #smartmoney #accumulation #distribution #phasechange #ict #smc #commandcenter
Made with respect for the craft.
Drop a ♥ if this speaks to you.
Classic Wave: The Easy WayClassic Wave is a simple strategy with few rules and no over-optimization. Despite its simplicity, it is backed by a nearly century-long historical track record, delivering excellent returns on the weekly chart of the SPX (TVC).
I also recommend observing its strong performance on the SPY (weekly), which is the perfect instrument for executing this strategy with futures in the future.
Strategy Rules and Parameters
When a bullish candle closes above the 20-period EMA, we place the stop-loss below the low of that candle and target a risk-reward ratio of 1:1.
A second, more profitable variant is to change the risk-reward ratio in the code to 2:1.
-Total capital: $10,000
-We use 10% of the total capital per trade.
-Commissions: 0.1% per trade.
The code construction is simple and very well detailed within the script itself.
Risk-Reward Ratio 2:1
Using a 2:1 risk-reward ratio reduces the win rate but significantly increases profitability.
Across the full historical data of the SPX index (weekly), the system would have generated 236 trades, with a win rate of 51.27% and a profit factor of 2.53.
From January 1, 2023, to November 28, 2025, the system would have generated 5 trades, with an 80% win rate and a profit factor of 9.244.
What makes this system so good?
-It takes advantage of the long-term bullish bias of U.S. stock indices and traditional markets.
-It filters out a lot of noise thanks to the weekly timeframe.
-It uses simple parameters with no over-optimization.
Final Notes:
This strategy has consistently outperformed the returns offered by most traditional funds over time, with fewer drawdowns and significantly less stress. I hope you like it.
Crypto Signals & Overlays –29-11-2025Nebula Crypto Signals & Overlays
Nebula is a multi-timeframe trend and momentum indicator designed for high-cap crypto pairs (BTC, ETH, SOL, DOGE, etc.).
• Uses 21/50/200 EMAs + higher-timeframe EMA for trend filtering
• RSI and Bollinger Bands for momentum and squeeze detection
• Generates BUY/SELL labels on trend-side pullbacks
• ATR line as a dynamic stop/target guide, plus pivot-based support/resistance zones
• Background colors: green = bullish regime, red = bearish regime, yellow = low-volatility squeeze
Not financial advice. Always backtest and use proper risk management before trading live.
WSMR v3.8 — WhaleSplash → Mean Reversal# WSMR v3.8 — WhaleSplash → Mean Reversal
### Global, Anchored, Non-Repainting Signal Framework for Futures, Crypto & Index Markets
**WSMR v3.8** is a volatility-anchored market-structure framework designed to detect two high-probability turning points:
## 1️⃣ WhaleSplash (WS) — Short Impulse Exhaustion
A “WhaleSplash” is a large downside impulse characterised by:
- bar range ≥ *k × ATR*
- strong % move
- volume expansion vs SMA(20)
- deep Z-Score oversold
- compression away from VWAP
- RSI weakness
When these conditions align, the indicator marks a short exhaustion event and prints a 🐋 icon below the bar. This is a **non-repainting bar-close confirmation**.
---
## 2️⃣ Mean Reversal (MR) — Bullish Reversal Setup
The MR module combines:
- RSI bullish divergence (pivot-based, safe)
- Z-Score reset above threshold
- SMA20 reclaim with positive slope
- Higher-low structure
When confirmed at bar-close, the indicator identifies conditions favourable for a **mean-reversion long**.
MR signals can optionally trigger an “**1st green candle after MR**” confirmation within a user-defined TTL (default 12 bars).
---
# 🎯 Key Features
### ✔ Non-Repainting Confirmed Signals
WS & MR only fire **after** bar close, using cooldown logic to avoid clustering and noise.
### ✔ VWAP-Anchored Z-Score Framework
All signals reference price distance and statistical deviation from VWAP, producing adaptive, volatility-aware setups.
### ✔ Session Filter (Asia-Optimised)
Optional session gating allows signals only between **23:00–09:00 UTC**, ideal for systematic Asia-session breakout & mean-reversion traders.
### ✔ Volatility Monitor (Normal → Extreme)
Dynamic volatility classification using:
- ATR baseline ratio
- wickiness index
- range Z-Score
States: **Normal → Wicky → Spiky → Extreme**
Displayed with colour-coded background in the status panel.
### ✔ Rolling WhaleSplash Frequency (Analytics Panel)
WSMR tracks the frequency of WhaleSplash events over a rolling window (Bars/Days/Weeks/Months) and estimates average WS/day (on minute timeframes).
### ✔ Status Panel (Bottom-Right)
Live display of:
- Mode (Global/Asia)
- Timeframe + TTL status
- WhaleSplash frequency
- Volatility state
- ATR/Range information
---
# 📌 Best Timeframes
Optimised and validated on **5-minute charts**, but compatible with all intraday timeframes.
---
# 🚨 Alerts Included
- WhaleSplash SHORT
- WhaleSplash LONG
- Volatility Warning (Spiky/Extreme)
---
# ⚠️ Notes
WSMR v3.8 is not a buy/sell system. It is a **signal framework** highlighting exhaustion and reversal conditions. Always combine with market structure, session context, and risk management. Past performance does not guarantee future results.
---
# 💬 Credits
Script created by **John Nolan (JohnFrancisNolan)**
Pine Script® v6
© 2024–2025 — Published under the **Mozilla Public License 2.0**
Consolidation Breakout PRO — Clean Boxes + 200 EMA Trend Filter High-probability range breakout detector that draws perfect, always-visible consolidation boxes and only alerts when price breaks out with strong volume and (optionally) in the direction of the prevailing trend.
Features
Automatically draws and extends clean consolidation boxes in real time
Boxes stop extending the moment the breakout occurs — no more “ghost” lines
Optional but powerful 200 EMA trend filter (dramatically reduces false breakouts)
Stronger volume confirmation (default 1.8× the 20-period average, fully adjustable)
Auto-deletes old boxes so your chart stays perfectly clean even after hundreds of signals
Clear “BREAKOUT ↑” and “BREAKDOWN ↓” labels + ready-to-use alerts
Works on any market and any timeframe (best on 1H, 4H, Daily)
How to trade it (edge > 65 % when used correctly)
Wait for the labeled breakout candle to close
Enter on pullback/retest of the box edge (or on strong close + retest)
Stop-loss just outside the opposite side of the box
Take-profit: minimum 1:2, ideally measured move (box height added/subtracted) or trailing with the 20 EMA
This is the cleanest and most professional public consolidation breakout tool available in 2025 — no repainting, no lag, no chart clutter.
Created and continuously improved with love for the TradingView community.
Turtle Momentum StrategyTurtle momentum strategy as per Momentum Trading Strategy article on Substack (Nov 26, 2025)
EMA 12-26-100 Momentum Strategy# Triple EMA Multi-Signal Momentum Strategy
## 📊 Overview
**Triple EMA Multi-Signal** is a comprehensive trend-following momentum strategy designed specifically for cryptocurrency markets. It combines multiple technical indicators and signal types to identify high-probability trading opportunities while maintaining strict risk management protocols.
The strategy excels in trending markets and uses adaptive position sizing with trailing stops to maximize profits during strong trends while protecting capital during choppy conditions.
## 🎯 Core Algorithm
### Triple EMA System
The strategy employs a three-layer EMA system to identify trend direction and strength:
- **Fast EMA (12)**: Quick response to price changes
- **Slow EMA (26)**: Confirmation of trend direction
- **Trend EMA (100)**: Overall market bias filter
Trades are only taken when all three EMAs align in the same direction, ensuring we trade with the dominant trend.
### Multi-Signal Confirmation (8 Signal Types)
The strategy requires at least 1-2 confirmed signals from multiple independent sources before entering a position:
1. **EMA Crossover** - Fast EMA crossing Slow EMA (primary signal)
2. **MACD Cross** - MACD line crossing signal line (momentum confirmation)
3. **RSI Reversal** - RSI bouncing from oversold/overbought zones
4. **Price Action** - Strong bullish/bearish candles (>60% of range)
5. **Volume Spike** - Above-average volume confirmation
6. **Breakout** - Price breaking 20-period high/low with volume
7. **Pullback to EMA** - Trend continuation after healthy retracement
8. **Bollinger Bounce** - Price bouncing from BB bands
This multi-signal approach significantly reduces false signals and improves win rate.
## 💰 Risk Management
### Position Sizing
- Default: 20-25% of equity per trade
- Adjustable based on risk tolerance
- Smaller positions recommended for leveraged trading
### Stop Loss & Take Profit
- **Stop Loss**: 2.0% (tight control of risk)
- **Take Profit**: 5.5% (2.75:1 reward-to-risk ratio)
- Both levels are fixed at entry to avoid emotional decisions
### Trailing Stop System
- Activates after 1.8% profit
- Trails at 1.3% below current price
- Locks in profits during extended trends
- Automatically adjusts as price moves in your favor
### Maximum Hold Time
- 36-48 hours maximum (configurable)
- Designed to minimize funding rate costs on futures
- Forces position closure to avoid excessive exposure
- Helps maintain capital velocity
## 📈 Key Features
### Trend Filters
- **ADX Filter**: Ensures sufficient trend strength (threshold: 20)
- **EMA Alignment**: All three EMAs must confirm trend direction
- **RSI Boundaries**: Avoids extreme overbought/oversold entries
### Volume Analysis
- Volume must exceed 20-period moving average
- Configurable multiplier (default: 1.0x)
- Helps identify institutional participation
### Automatic Exit Conditions
1. Take Profit target reached
2. Stop Loss triggered
3. Trailing stop activated
4. Trend reversal (EMA cross in opposite direction)
5. Maximum hold time exceeded
## 🎮 Recommended Settings
### For Spot Trading (Conservative)
```
Position Size: 15-20%
Stop Loss: 2.5%
Take Profit: 6.0%
Max Hold: 72 hours
Leverage: 1x
```
### For Futures 3-5x Leverage (Balanced)
```
Position Size: 12-15%
Stop Loss: 2.0%
Take Profit: 5.5%
Max Hold: 36 hours
Trailing: Active
```
### For Aggressive Trading 5-10x (High Risk)
```
Position Size: 8-12%
Stop Loss: 1.5%
Take Profit: 4.5%
Max Hold: 24 hours
ADX Filter: Disabled
```
## 📊 Performance Metrics
### Backtested Results (BTC/USDT 1H, 2 years)
- **Total Return**: ~19% (spot) / ~75% (5x leverage)*
- **Total Trades**: 240-300
- **Win Rate**: 49-52%
- **Profit Factor**: 1.25-1.50
- **Max Drawdown**: ~18-22%
- **Average Trade**: 0.5-3 days
*Leverage results exclude funding rates and real-world slippage
### Optimal Timeframes
- **1 Hour**: Best for active trading (recommended)
- **4 Hour**: More stable, fewer signals
- **15 Min**: High frequency (requires monitoring)
### Best Performing Assets
- BTC/USDT (most tested)
- ETH/USDT
- Major altcoins with good liquidity
- Not recommended for low-cap or illiquid pairs
## ⚙️ How to Use
1. **Add to Chart**: Apply strategy to 1H BTC/USDT chart
2. **Adjust Settings**: Configure risk parameters based on your preference
3. **Review Signals**: Green = Long, Red = Short, labels show signal count
4. **Monitor Performance**: Check strategy tester for detailed statistics
5. **Optimize**: Use strategy optimization to find best parameters for your market
## 🎨 Visual Indicators
The strategy provides clear visual feedback:
- **EMA Lines**: Blue (Fast), Red (Slow), Orange (Trend)
- **BUY/SELL Labels**: Show entry points with signal count
- **Stop/Target Lines**: Red (SL), Green (TP) displayed during active trades
- **Background Color**: Light green (long), light red (short) when in position
- **Info Panel**: Shows current trend, RSI, ADX, and volume status
## ⚠️ Important Notes
### Risk Disclaimer
- This strategy is for educational purposes only
- Past performance does not guarantee future results
- Cryptocurrency trading involves substantial risk
- Only trade with capital you can afford to lose
- Always use proper position sizing and risk management
### Limitations
- Performs poorly in sideways/choppy markets
- Requires sufficient liquidity for best execution
- Backtests do not include:
- Real-world slippage (especially during volatility)
- Funding rates (for perpetual futures)
- Exchange downtime or connection issues
- Emotional trading decisions
### For Futures Trading
If using this strategy on futures with leverage:
- Reduce position size proportionally to leverage
- Account for funding rates (~0.01% per 8h)
- Set max hold time to minimize funding costs
- Use lower leverage (3-5x max recommended)
- Monitor liquidation price carefully
## 🔧 Customization
All parameters are fully customizable:
- EMA periods (fast/slow/trend)
- MACD settings (12/26/9)
- RSI levels (30/70)
- Stop Loss / Take Profit percentages
- Trailing stop activation and offset
- Volume multiplier
- ADX threshold
- Maximum hold time
## 📚 Strategy Logic
The strategy follows this decision tree:
```
1. Check Trend Direction (EMA alignment)
↓
2. Scan for Entry Signals (8 types)
↓
3. Confirm with Filters (ADX, Volume, RSI)
↓
4. Enter Position with Fixed SL/TP
↓
5. Monitor for Exit Conditions:
- TP Hit → Close with profit
- SL Hit → Close with loss
- Trailing Active → Follow price
- Trend Reversal → Close position
- Max Time → Force close
```
## 🎓 Best Practices
1. **Start Conservative**: Use smaller position sizes initially
2. **Track Performance**: Monitor actual vs backtested results
3. **Optimize Regularly**: Market conditions change, adapt parameters
4. **Combine with Analysis**: Don't rely solely on automated signals
5. **Manage Emotions**: Stick to the system, avoid manual overrides
6. **Paper Trade First**: Test on demo before risking real capital
## 📞 Support & Updates
This strategy is actively maintained and updated based on:
- Market condition changes
- User feedback and suggestions
- Performance optimization
- Bug fixes and improvements
## 🏆 Conclusion
Triple EMA Multi-Signal Strategy offers a robust, systematic approach to cryptocurrency trading by combining trend following, momentum indicators, and strict risk management. Its multi-signal confirmation system helps filter false signals while the trailing stop mechanism captures extended trends.
The strategy is suitable for both manual traders looking for high-probability setups and algorithmic traders seeking a proven systematic approach.
**Remember**: No strategy wins 100% of the time. Success comes from consistent application, proper risk management, and continuous adaptation to changing market conditions.
---
*Version: 1.0*
*Last Updated: November 2025*
*Tested on: BTC/USDT, ETH/USDT (1H, 4H timeframes)*
*Recommended Capital: $5,000+ for optimal position sizing*
BybitMinOrderSizeBybit Order Quantity Compliance Library
This library provides all utility functions required for TradingView strategies
that execute orders on Bybit via webhooks.
Problem:
Bybit enforces two strict rules on every order submitted:
Minimum Order Size – each symbol has its own minimum quantity.
Quantity Precision – each symbol requires rounding to the correct number of decimals.
TradingView does not expose this metadata, so strategies can easily submit
quantities that Bybit rejects as invalid.
Solution (This Library):
This library embeds full Bybit contract metadata, including:
A complete mapping of Bybit symbols → minimum order size
A complete mapping of Bybit symbols → allowed precision (decimal places)
A helper to normalize tickers (removing `.P` suffix for Bybit perpetuals)
It also exposes utility functions to automatically make your quantities valid:
`normalizeTicker()` — removes `.P` for consistent lookup
`getMinOrderSize()` — returns the correct minimum order size
`getPrecisionForTicker()` — returns required quantity precision
`floorQty()` — floors quantities to valid minimum increments
`roundQty()` — rounds quantities to valid decimal precision
Use Cases:
Ensuring webhook strategies never send too-small orders
Rounding limit/market orders correctly before execution
Making Pine strategies execution-accurate for Bybit
Avoiding "order rejected: qty too small / invalid precision" errors
This library is recommended for:
Live trading via TradingView → Bybit webhooks
Backtesting strategies that simulate real Bybit constraints
Source: www.bybit.com
Updated: 2025-11-25 — Bybit contract metadata
normalizeTicker(symbol)
Normalizes Bybit perpetual tickers by removing the ".P" suffix.
precisionFromMinOrder(minOrder)
Derives precision (decimal places) from minimum order size.
getMinOrderSize(symbol)
Retrieves the minimum order size for the current or given symbol.
getPrecisionForTicker(symbol)
Retrieves the required quantity precision (decimal places) for a given Bybit symbol.
floorQty(qty, symbol)
Rounds a quantity down to the nearest valid minimum order size for a given symbol.
roundQty(qty, symbol)
Rounds a quantity to the valid precision for the specified symbol.
