DOPT---
## 🔍 **DOPT - Daily Open & Price Time Markers**
This script is designed to support directional bias development and price behavior analysis around key time-based reference points on the **1H and 4H timeframes**.
### ✨ **What It Does**
- **1800 Open Marker** (6 PM NY time): Plots the **daily open** from 1800 in **black dotted lines**.
- **0000 Open Marker** (Midnight NY time): Plots the **midnight open** in **blue dotted lines**.
- **Day Letters**: Each 1800 open is labeled with the corresponding **day of the week** (e.g., M, T, W...), helping visually segment your chart.
- **Hour Labels**: Select specific candles (e.g., 0000 = '0', 0800 = '8') to be labeled above the bar. These are fully customizable.
- **Candle Midpoints**: Option to mark the **50% level** of a specific candle (good for CE or CRT references).
- **CRT High/Low Tracking**: Ability to plot **extended high and low lines** from a selected candle back (e.g., for CRT modeling).
- **4H Timeframe Candle Numbering**: Helpful when analyzing sequences on the 4-hour timeframe. Candles are numbered `1`, `5`, and `9` for reference.
---
### 🧠 **How I Use It**
- I mostly use this on the **1-hour timeframe** to decide **directional bias** for the day:
- If price **closes above 1800 open**, I consider that a **green daily close** — potential bullish sentiment.
- If price **closes below**, I treat it as a **red daily close** — potential bearish behavior.
- Price often uses these opens as **support/resistance**, so I watch for reactions there.
- On the **4H**, the candle numbers help track structure and flow.
- Combine with CRT tools to mark **key candle highs/lows** and their **equilibrium (50%)** — great for refining entries or understanding how price is respecting a particular candle.
---
### ⚠️ **Note on Daylight Savings**
This is a **daylight saving time-dependent script**. When DST kicks in or out, you’ll need to **adjust the time inputs** accordingly to keep the opens accurate (e.g., 1800 might shift to 1700 depending on the season).
---
### 🔁 **Backtesting & Reference**
- The **1800 and 0000 opens** are plotted for **as far back** as your chart loads, making it great for backtesting historical reactions.
- The CRT marking tools only go back **50 candles max**, so use that for recent structure only.
---
Search in scripts for "Cycle"
Fourier Trend Energy (Prototype)Fourier Trend Energy (Prototype)
This indicator brings the logic of Fourier-based trend analysis into Pine Script.
It estimates two key components:
Low-Frequency Energy — representing the strength of the underlying trend
High-Frequency Energy — representing noise, volatility, or deviation from the trend
🔹 Green line → trend strength
🔸 Orange line → short-term noise
🟩🟥 Background color → shows whether trend energy is increasing or decreasing
You can use it to:
Detect early trend formation
Filter fakeouts during consolidation
Spot momentum shifts based on energy crossovers
This is not a traditional oscillator — it’s a frequency-inspired tool to help you understand when the market is charging for a move.
Fuzzy SMA with DCTI Confirmation[FibonacciFlux]FibonacciFlux: Advanced Fuzzy Logic System with Donchian Trend Confirmation
Institutional-grade trend analysis combining adaptive Fuzzy Logic with Donchian Channel Trend Intensity for superior signal quality
Conceptual Framework & Research Foundation
FibonacciFlux represents a significant advancement in quantitative technical analysis, merging two powerful analytical methodologies: normalized fuzzy logic systems and Donchian Channel Trend Intensity (DCTI). This sophisticated indicator addresses a fundamental challenge in market analysis – the inherent imprecision of trend identification in dynamic, multi-dimensional market environments.
While traditional indicators often produce simplistic binary signals, markets exist in states of continuous, graduated transition. FibonacciFlux embraces this complexity through its implementation of fuzzy set theory, enhanced by DCTI's structural trend confirmation capabilities. The result is an indicator that provides nuanced, probabilistic trend assessment with institutional-grade signal quality.
Core Technological Components
1. Advanced Fuzzy Logic System with Percentile Normalization
At the foundation of FibonacciFlux lies a comprehensive fuzzy logic system that transforms conventional technical metrics into degrees of membership in linguistic variables:
// Fuzzy triangular membership function with robust error handling
fuzzy_triangle(val, left, center, right) =>
if na(val)
0.0
float denominator1 = math.max(1e-10, center - left)
float denominator2 = math.max(1e-10, right - center)
math.max(0.0, math.min(left == center ? val <= center ? 1.0 : 0.0 : (val - left) / denominator1,
center == right ? val >= center ? 1.0 : 0.0 : (right - val) / denominator2))
The system employs percentile-based normalization for SMA deviation – a critical innovation that enables self-calibration across different assets and market regimes:
// Percentile-based normalization for adaptive calibration
raw_diff = price_src - sma_val
diff_abs_percentile = ta.percentile_linear_interpolation(math.abs(raw_diff), normLookback, percRank) + 1e-10
normalized_diff_raw = raw_diff / diff_abs_percentile
normalized_diff = useClamping ? math.max(-clampValue, math.min(clampValue, normalized_diff_raw)) : normalized_diff_raw
This normalization approach represents a significant advancement over fixed-threshold systems, allowing the indicator to automatically adapt to varying volatility environments and maintain consistent signal quality across diverse market conditions.
2. Donchian Channel Trend Intensity (DCTI) Integration
FibonacciFlux significantly enhances fuzzy logic analysis through the integration of Donchian Channel Trend Intensity (DCTI) – a sophisticated measure of trend strength based on the relationship between short-term and long-term price extremes:
// DCTI calculation for structural trend confirmation
f_dcti(src, majorPer, minorPer, sigPer) =>
H = ta.highest(high, majorPer) // Major period high
L = ta.lowest(low, majorPer) // Major period low
h = ta.highest(high, minorPer) // Minor period high
l = ta.lowest(low, minorPer) // Minor period low
float pdiv = not na(L) ? l - L : 0 // Positive divergence (low vs major low)
float ndiv = not na(H) ? H - h : 0 // Negative divergence (major high vs high)
float divisor = pdiv + ndiv
dctiValue = divisor == 0 ? 0 : 100 * ((pdiv - ndiv) / divisor) // Normalized to -100 to +100 range
sigValue = ta.ema(dctiValue, sigPer)
DCTI provides a complementary structural perspective on market trends by quantifying the relationship between short-term and long-term price extremes. This creates a multi-dimensional analysis framework that combines adaptive deviation measurement (fuzzy SMA) with channel-based trend intensity confirmation (DCTI).
Multi-Dimensional Fuzzy Input Variables
FibonacciFlux processes four distinct technical dimensions through its fuzzy system:
Normalized SMA Deviation: Measures price displacement relative to historical volatility context
Rate of Change (ROC): Captures price momentum over configurable timeframes
Relative Strength Index (RSI): Evaluates cyclical overbought/oversold conditions
Donchian Channel Trend Intensity (DCTI): Provides structural trend confirmation through channel analysis
Each dimension is processed through comprehensive fuzzy sets that transform crisp numerical values into linguistic variables:
// Normalized SMA Deviation - Self-calibrating to volatility regimes
ndiff_LP := fuzzy_triangle(normalized_diff, norm_scale * 0.3, norm_scale * 0.7, norm_scale * 1.1)
ndiff_SP := fuzzy_triangle(normalized_diff, norm_scale * 0.05, norm_scale * 0.25, norm_scale * 0.5)
ndiff_NZ := fuzzy_triangle(normalized_diff, -norm_scale * 0.1, 0.0, norm_scale * 0.1)
ndiff_SN := fuzzy_triangle(normalized_diff, -norm_scale * 0.5, -norm_scale * 0.25, -norm_scale * 0.05)
ndiff_LN := fuzzy_triangle(normalized_diff, -norm_scale * 1.1, -norm_scale * 0.7, -norm_scale * 0.3)
// DCTI - Structural trend measurement
dcti_SP := fuzzy_triangle(dcti_val, 60.0, 85.0, 101.0) // Strong Positive Trend (> ~85)
dcti_WP := fuzzy_triangle(dcti_val, 20.0, 45.0, 70.0) // Weak Positive Trend (~30-60)
dcti_Z := fuzzy_triangle(dcti_val, -30.0, 0.0, 30.0) // Near Zero / Trendless (~+/- 20)
dcti_WN := fuzzy_triangle(dcti_val, -70.0, -45.0, -20.0) // Weak Negative Trend (~-30 - -60)
dcti_SN := fuzzy_triangle(dcti_val, -101.0, -85.0, -60.0) // Strong Negative Trend (< ~-85)
Advanced Fuzzy Rule System with DCTI Confirmation
The core intelligence of FibonacciFlux lies in its sophisticated fuzzy rule system – a structured knowledge representation that encodes expert understanding of market dynamics:
// Base Trend Rules with DCTI Confirmation
cond1 = math.min(ndiff_LP, roc_HP, rsi_M)
strength_SB := math.max(strength_SB, cond1 * (dcti_SP > 0.5 ? 1.2 : dcti_Z > 0.1 ? 0.5 : 1.0))
// DCTI Override Rules - Structural trend confirmation with momentum alignment
cond14 = math.min(ndiff_NZ, roc_HP, dcti_SP)
strength_SB := math.max(strength_SB, cond14 * 0.5)
The rule system implements 15 distinct fuzzy rules that evaluate various market conditions including:
Established Trends: Strong deviations with confirming momentum and DCTI alignment
Emerging Trends: Early deviation patterns with initial momentum and DCTI confirmation
Weakening Trends: Divergent signals between deviation, momentum, and DCTI
Reversal Conditions: Counter-trend signals with DCTI confirmation
Neutral Consolidations: Minimal deviation with low momentum and neutral DCTI
A key innovation is the weighted influence of DCTI on rule activation. When strong DCTI readings align with other indicators, rule strength is amplified (up to 1.2x). Conversely, when DCTI contradicts other indicators, rule impact is reduced (as low as 0.5x). This creates a dynamic, self-adjusting system that prioritizes high-conviction signals.
Defuzzification & Signal Generation
The final step transforms fuzzy outputs into a precise trend score through center-of-gravity defuzzification:
// Defuzzification with precise floating-point handling
denominator = strength_SB + strength_WB + strength_N + strength_WBe + strength_SBe
if denominator > 1e-10
fuzzyTrendScore := (strength_SB * STRONG_BULL + strength_WB * WEAK_BULL +
strength_N * NEUTRAL + strength_WBe * WEAK_BEAR +
strength_SBe * STRONG_BEAR) / denominator
The resulting FuzzyTrendScore ranges from -1.0 (Strong Bear) to +1.0 (Strong Bull), with critical threshold zones at ±0.3 (Weak trend) and ±0.7 (Strong trend). The histogram visualization employs intuitive color-coding for immediate trend assessment.
Strategic Applications for Institutional Trading
FibonacciFlux provides substantial advantages for sophisticated trading operations:
Multi-Timeframe Signal Confirmation: Institutional-grade signal validation across multiple technical dimensions
Trend Strength Quantification: Precise measurement of trend conviction with noise filtration
Early Trend Identification: Detection of emerging trends before traditional indicators through fuzzy pattern recognition
Adaptive Market Regime Analysis: Self-calibrating analysis across varying volatility environments
Algorithmic Strategy Integration: Well-defined numerical output suitable for systematic trading frameworks
Risk Management Enhancement: Superior signal fidelity for risk exposure optimization
Customization Parameters
FibonacciFlux offers extensive customization to align with specific trading mandates and market conditions:
Fuzzy SMA Settings: Configure baseline trend identification parameters including SMA, ROC, and RSI lengths
Normalization Settings: Fine-tune the self-calibration mechanism with adjustable lookback period, percentile rank, and optional clamping
DCTI Parameters: Optimize trend structure confirmation with adjustable major/minor periods and signal smoothing
Visualization Controls: Customize display transparency for optimal chart integration
These parameters enable precise calibration for different asset classes, timeframes, and market regimes while maintaining the core analytical framework.
Implementation Notes
For optimal implementation, consider the following guidance:
Higher timeframes (4H+) benefit from increased normalization lookback (800+) for stability
Volatile assets may require adjusted clamping values (2.5-4.0) for optimal signal sensitivity
DCTI parameters should be aligned with chart timeframe (higher timeframes require increased major/minor periods)
The indicator performs exceptionally well as a trend filter for systematic trading strategies
Acknowledgments
FibonacciFlux builds upon the pioneering work of Donovan Wall in Donchian Channel Trend Intensity analysis. The normalization approach draws inspiration from percentile-based statistical techniques in quantitative finance. This indicator is shared for educational and analytical purposes under Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) license.
Past performance does not guarantee future results. All trading involves risk. This indicator should be used as one component of a comprehensive analysis framework.
Shout out @DonovanWall
Fuzzy SMA Trend Analyzer (experimental)[FibonacciFlux]Fuzzy SMA Trend Analyzer (Normalized): Advanced Market Trend Detection Using Fuzzy Logic Theory
Elevate your technical analysis with institutional-grade fuzzy logic implementation
Research Genesis & Conceptual Framework
This indicator represents the culmination of extensive research into applying fuzzy logic theory to financial markets. While traditional technical indicators often produce binary outcomes, market conditions exist on a continuous spectrum. The Fuzzy SMA Trend Analyzer addresses this limitation by implementing a sophisticated fuzzy logic system that captures the nuanced, multi-dimensional nature of market trends.
Core Fuzzy Logic Principles
At the heart of this indicator lies fuzzy logic theory - a mathematical framework designed to handle imprecision and uncertainty:
// Improved fuzzy_triangle function with guard clauses for NA and invalid parameters.
fuzzy_triangle(val, left, center, right) =>
if na(val) or na(left) or na(center) or na(right) or left > center or center > right // Guard checks
0.0
else if left == center and center == right // Crisp set (single point)
val == center ? 1.0 : 0.0
else if left == center // Left-shoulder shape (ramp down from 1 at center to 0 at right)
val >= right ? 0.0 : val <= center ? 1.0 : (right - val) / (right - center)
else if center == right // Right-shoulder shape (ramp up from 0 at left to 1 at center)
val <= left ? 0.0 : val >= center ? 1.0 : (val - left) / (center - left)
else // Standard triangle
math.max(0.0, math.min((val - left) / (center - left), (right - val) / (right - center)))
This implementation of triangular membership functions enables the indicator to transform crisp numerical values into degrees of membership in linguistic variables like "Large Positive" or "Small Negative," creating a more nuanced representation of market conditions.
Dynamic Percentile Normalization
A critical innovation in this indicator is the implementation of percentile-based normalization for SMA deviation:
// ----- Deviation Scale Estimation using Percentile -----
// Calculate the percentile rank of the *absolute* deviation over the lookback period.
// This gives an estimate of the 'typical maximum' deviation magnitude recently.
diff_abs_percentile = ta.percentile_linear_interpolation(math.abs(raw_diff), normLookback, percRank) + 1e-10
// ----- Normalize the Raw Deviation -----
// Divide the raw deviation by the estimated 'typical max' magnitude.
normalized_diff = raw_diff / diff_abs_percentile
// ----- Clamp the Normalized Deviation -----
normalized_diff_clamped = math.max(-3.0, math.min(3.0, normalized_diff))
This percentile normalization approach creates a self-adapting system that automatically calibrates to different assets and market regimes. Rather than using fixed thresholds, the indicator dynamically adjusts based on recent volatility patterns, significantly enhancing signal quality across diverse market environments.
Multi-Factor Fuzzy Rule System
The indicator implements a comprehensive fuzzy rule system that evaluates multiple technical factors:
SMA Deviation (Normalized): Measures price displacement from the Simple Moving Average
Rate of Change (ROC): Captures price momentum over a specified period
Relative Strength Index (RSI): Assesses overbought/oversold conditions
These factors are processed through a sophisticated fuzzy inference system with linguistic variables:
// ----- 3.1 Fuzzy Sets for Normalized Deviation -----
diffN_LP := fuzzy_triangle(normalized_diff_clamped, 0.7, 1.5, 3.0) // Large Positive (around/above percentile)
diffN_SP := fuzzy_triangle(normalized_diff_clamped, 0.1, 0.5, 0.9) // Small Positive
diffN_NZ := fuzzy_triangle(normalized_diff_clamped, -0.2, 0.0, 0.2) // Near Zero
diffN_SN := fuzzy_triangle(normalized_diff_clamped, -0.9, -0.5, -0.1) // Small Negative
diffN_LN := fuzzy_triangle(normalized_diff_clamped, -3.0, -1.5, -0.7) // Large Negative (around/below percentile)
// ----- 3.2 Fuzzy Sets for ROC -----
roc_HN := fuzzy_triangle(roc_val, -8.0, -5.0, -2.0)
roc_WN := fuzzy_triangle(roc_val, -3.0, -1.0, -0.1)
roc_NZ := fuzzy_triangle(roc_val, -0.3, 0.0, 0.3)
roc_WP := fuzzy_triangle(roc_val, 0.1, 1.0, 3.0)
roc_HP := fuzzy_triangle(roc_val, 2.0, 5.0, 8.0)
// ----- 3.3 Fuzzy Sets for RSI -----
rsi_L := fuzzy_triangle(rsi_val, 0.0, 25.0, 40.0)
rsi_M := fuzzy_triangle(rsi_val, 35.0, 50.0, 65.0)
rsi_H := fuzzy_triangle(rsi_val, 60.0, 75.0, 100.0)
Advanced Fuzzy Inference Rules
The indicator employs a comprehensive set of fuzzy rules that encode expert knowledge about market behavior:
// --- Fuzzy Rules using Normalized Deviation (diffN_*) ---
cond1 = math.min(diffN_LP, roc_HP, math.max(rsi_M, rsi_H)) // Strong Bullish: Large pos dev, strong pos roc, rsi ok
strength_SB := math.max(strength_SB, cond1)
cond2 = math.min(diffN_SP, roc_WP, rsi_M) // Weak Bullish: Small pos dev, weak pos roc, rsi mid
strength_WB := math.max(strength_WB, cond2)
cond3 = math.min(diffN_SP, roc_NZ, rsi_H) // Weakening Bullish: Small pos dev, flat roc, rsi high
strength_N := math.max(strength_N, cond3 * 0.6) // More neutral
strength_WB := math.max(strength_WB, cond3 * 0.2) // Less weak bullish
This rule system evaluates multiple conditions simultaneously, weighting them by their degree of membership to produce a comprehensive trend assessment. The rules are designed to identify various market conditions including strong trends, weakening trends, potential reversals, and neutral consolidations.
Defuzzification Process
The final step transforms the fuzzy result back into a crisp numerical value representing the overall trend strength:
// --- Step 6: Defuzzification ---
denominator = strength_SB + strength_WB + strength_N + strength_WBe + strength_SBe
if denominator > 1e-10 // Use small epsilon instead of != 0.0 for float comparison
fuzzyTrendScore := (strength_SB * STRONG_BULL +
strength_WB * WEAK_BULL +
strength_N * NEUTRAL +
strength_WBe * WEAK_BEAR +
strength_SBe * STRONG_BEAR) / denominator
The resulting FuzzyTrendScore ranges from -1 (strong bearish) to +1 (strong bullish), providing a smooth, continuous evaluation of market conditions that avoids the abrupt signal changes common in traditional indicators.
Advanced Visualization with Rainbow Gradient
The indicator incorporates sophisticated visualization using a rainbow gradient coloring system:
// Normalize score to for gradient function
normalizedScore = na(fuzzyTrendScore) ? 0.5 : math.max(0.0, math.min(1.0, (fuzzyTrendScore + 1) / 2))
// Get the color based on gradient setting and normalized score
final_color = get_gradient(normalizedScore, gradient_type)
This color-coding system provides intuitive visual feedback, with color intensity reflecting trend strength and direction. The gradient can be customized between Red-to-Green or Red-to-Blue configurations based on user preference.
Practical Applications
The Fuzzy SMA Trend Analyzer excels in several key applications:
Trend Identification: Precisely identifies market trend direction and strength with nuanced gradation
Market Regime Detection: Distinguishes between trending markets and consolidation phases
Divergence Analysis: Highlights potential reversals when price action and fuzzy trend score diverge
Filter for Trading Systems: Provides high-quality trend filtering for other trading strategies
Risk Management: Offers early warning of potential trend weakening or reversal
Parameter Customization
The indicator offers extensive customization options:
SMA Length: Adjusts the baseline moving average period
ROC Length: Controls momentum sensitivity
RSI Length: Configures overbought/oversold sensitivity
Normalization Lookback: Determines the adaptive calculation window for percentile normalization
Percentile Rank: Sets the statistical threshold for deviation normalization
Gradient Type: Selects the preferred color scheme for visualization
These parameters enable fine-tuning to specific market conditions, trading styles, and timeframes.
Acknowledgments
The rainbow gradient visualization component draws inspiration from LuxAlgo's "Rainbow Adaptive RSI" (used under CC BY-NC-SA 4.0 license). This implementation of fuzzy logic in technical analysis builds upon Fermi estimation principles to overcome the inherent limitations of crisp binary indicators.
This indicator is shared under Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) license.
Remember that past performance does not guarantee future results. Always conduct thorough testing before implementing any technical indicator in live trading.
Statistical Price Bands with Trend Filtering by QTX Algo SystemsStatistical Price Bands with Trend Filtering by QTX Algo Systems
Overview
This indicator generates adaptive support and resistance bands by fusing statistical analysis with real-time volatility and trend measurements. It highlights areas where prices appear overextended, providing traders with clear visual cues for potential reversals or risk management adjustments.
How It Works
Baseline Statistical Calculation:
The indicator begins by deriving a baseline price range from historical data using a statistical percentile approach. This percentile reflects the typical extremes observed over a significant period, forming the foundation for the bands.
Volatility Adjustment:
A dynamic volatility factor is then calculated by comparing the moving standard deviation of price to its moving average. This factor adjusts the baseline, ensuring that the bands reflect current market variability. The use of both a long-term dispersion measure and a short-term percentile-based volatility metric helps confirm that overall market volatility remains above a minimum threshold.
Trend Filtering:
In parallel, the indicator assesses trend direction by comparing the current price to a volume-weighted moving average (VWMA). This trend component shifts the bands in the direction of the prevailing market bias—moving the bands upward during uptrends and downward during downtrends.
Why It’s Different
Unlike traditional static support/resistance tools, this indicator integrates multiple layers of analysis—statistical extremes, real-time volatility, and trend direction—to create bands that continuously adapt to market conditions. This synthesis produces a dynamic framework that not only identifies potential overextended price areas but also provides practical stop loss levels, setting it apart from other basic band or moving average models.
How to Use
Customize the baseline statistical setting to match your trading style. Use the dynamically adjusted bands as visual cues for potential reversal zones or as guides for setting stop losses. Combine these insights with other technical tools to refine your entry and exit decisions.
Disclaimer
This indicator is for educational purposes only and is intended to support your trading strategy. It does not guarantee performance, and past results are not indicative of future outcomes. Always use proper risk management and perform your own analysis before trading.
alphaJohnny Dynamic RSI IndicatorAlphaJohnny Dynamic RSI Indicator (Dyn RSI)
The Dynamic RSI Indicator (Dyn RSI) is a custom Pine Script tool designed for TradingView that aggregates Relative Strength Index (RSI) signals from multiple timeframes to provide a comprehensive view of market momentum. It combines RSI data from Weekly, Daily, 4-hour, 1-hour, and 30-minute intervals, offering traders a flexible and customizable way to analyze trends across different periods.
Key Features:
Multi-Timeframe RSI Aggregation: Combines RSI signals from user-selected timeframes for a holistic momentum assessment.
Dynamic or Equal Weighting: Choose between correlation-based dynamic weights (adjusting based on each timeframe’s correlation with price changes) or equal weights for simplicity.
Smoothed Momentum Line: A visually intuitive line that reflects the strength of the aggregate signal, smoothed for clarity.
Color-Coded Signal Strength:
Dark Green: Strong buy signal
Light Green: Weak buy signal
Yellow: Neutral
Light Red: Weak sell signal
Dark Red: Strong sell signal
Visual Markers: Large green triangles at the bottom for strong buy signals and red triangles at the top for strong sell signals.
How to Use:
Apply to Chart: Add the indicator to your TradingView chart (it will appear in a separate pane).
Customize Settings: Adjust inputs like RSI period, signal thresholds, included timeframes, weighting method, and smoothing period to fit your trading style.
Interpret Signals:
Momentum Line: Watch for color changes to gauge market conditions.
Triangles: Green at the bottom for strong buy opportunities, red at the top for strong sell opportunities.
Notes:
The indicator is designed for a separate pane (overlay=false), with triangles positioned relative to the pane’s range.
Fine-tune thresholds and weights based on your strategy and the asset being analyzed.
The source code is open for modification to suit your needs.
This indicator is ideal for traders seeking a multi-timeframe perspective on RSI to identify potential trend reversals and momentum shifts.
M2SL/DXY RatioThis is the ratio of M2 money supply (M2SL) to the U.S. dollar index (DXY), taking into account the impact of U.S. dollar strength and weakness on liquidity.
M2SL/DXY better represents the current impact of the United States on cryptocurrency prices.
US Presidents (Alternating Fills by Order)📜 Indicator Description: US Presidents Background Fill
This indicator highlights the terms of U.S. Presidents on your chart with alternating red and blue background fills based on their political party:
• 🟥 Republicans = Red
• 🟦 Democrats = Blue
• 🎨 Dark/Light shading alternates with each new president to clearly distinguish consecutive terms, even within the same party.
The fill starts from President Ulysses S. Grant (18th President, 1873) through to the 47th president in 2025. It is designed to work with any asset and automatically adapts to the visible date range on your chart.
Ideal for visualizing macro trends, historical context, and how markets may have reacted under different political administrations.
[COG]S&P 500 Weekly Seasonality ProjectionS&P 500 Weekly Seasonality Projection
This indicator visualizes S&P 500 seasonality patterns based on historical weekly performance data. It projects price movements for up to 26 weeks ahead, highlighting key seasonal periods that have historically affected market performance.
Key Features:
Projects price movements based on historical S&P 500 weekly seasonality patterns (2005-2024)
Highlights six key seasonal periods: Jan-Feb Momentum, March Lows, April-May Strength, Summer Strength, September Dip, and Year-End Rally
Customizable forecast length from 1-26 weeks with quick timeframe selection buttons
Optional moving average smoothing for more gradual projections
Detailed statistics table showing projected price and percentage change
Seasonality mini-map showing the full annual pattern with current position
Customizable colors and visual elements
How to Use:
Apply to S&P 500 index or related instruments (daily timeframe or higher recommended)
Set your desired forecast length (1-26 weeks)
Monitor highlighted seasonal zones that have historically shown consistent patterns
Use the projection line as a general guideline for potential price movement
Settings:
Forecast length: Configure from 1-26 weeks or use quick select buttons (1M, 3M, 6M, 1Y)
Visual options: Customize colors, backgrounds, label sizes, and table position
Display options: Toggle statistics table, period highlights, labels, and mini-map
This indicator is designed as a visual guide to help identify potential seasonal tendencies in the S&P 500. Historical patterns are not guarantees of future performance, but understanding these seasonal biases can provide valuable context for your trading decisions.
Note: For optimal visualization, use on Daily timeframe or higher. Intraday timeframes will display a warning message.
[COG]Nasdaq Weekly Seasonality ProjectionNasdaq Weekly Seasonality Projection
This indicator provides a visualization of Nasdaq seasonality patterns based on historical weekly performance data. It projects price movements for up to 26 weeks ahead, highlighting key seasonal periods that have historically affected tech stocks.
Key Features:
Projects price movements based on historical Nasdaq weekly seasonality patterns
Highlights six key seasonal periods: January Effect, March Lows, April-May Strength, Tech Summer Rally, September Dip, and Q4 Tech Rally
Customizable forecast length from 1-26 weeks with quick timeframe selection buttons
Optional moving average smoothing for more gradual projections
Detailed statistics table showing projected price and percentage change
Seasonality mini-map showing the full annual pattern with current position
Customizable colors and visual elements
How to Use:
Apply to Nasdaq indices or tech-focused instruments (daily timeframe or higher recommended)
Set your desired forecast length (1-26 weeks)
Monitor highlighted seasonal zones that have historically shown consistent patterns
Use the projection line as a general guideline for potential price movement
Settings:
Forecast length: Configure from 1-26 weeks or use quick select buttons (1M, 3M, 6M, 1Y)
Visual options: Customize colors, backgrounds, label sizes, and table position
Display options: Toggle statistics table, period highlights, labels, and mini-map
This indicator is designed as a visual guide to help identify potential seasonal tendencies in Nasdaq and tech stocks. Historical patterns are not guarantees of future performance, but understanding these seasonal biases can provide valuable context for your trading decisions.
Note: For optimal visualization, use on Daily timeframe or higher. Intraday timeframes will display a warning message.
HTF Coloured PeriodThe "HTF Coloured Period" indicator colors the candles on the current chart based on the direction of a higher timeframe (HTF) candle. Here's how it works:
Higher Timeframe Selection :
- The user can set the higher timeframe period, which can be adjusted in minute increments. The default is 1 day (1440 minutes) , but it can be customized to any desired timeframe.
Higher Timeframe Data :
- The indicator compares the open and close prices of the higher timeframe's candle.
Direction Determination :
- If the higher timeframe candle is bullish ( close > open ), it considers the candle as green .
Coloring Candles :
- If the higher timeframe candle is bullish, the current chart's candles are colored green . If it's bearish, the candles are colored red .
The result is a visual indicator where the lower timeframe candles are color-coded based on whether the higher timeframe candle is bullish or bearish, helping to identify alignment with the higher timeframe trend.
Correlation X macroeconomicsFind the correlation between financial assets and the main Brazilian macroeconomic variables:
SELIC rate (Red)
PIB (Green)
Inflation (Blue)
Employment and income (Yellow)
Unlike other indicators that measure the correlation between two assets, the indicator "Correlation X macroeconomics" measures, for example, the correlation that the VALE3 asset has with the SELIC rate.
The correlation is obtained by calculating the variation suffered by a given asset on the day a given Brazilian macroeconomic variable is released.
This indicator can be used on any financial asset.
Use time frame chart = 1 day.
To calculate the correlation, data published by IBGE and the Central Bank of Brazil over a period of time are used. This time period is different depending on the selected macroeconomic variable. Namely:
16 PIB disclosures (4 years)
24 SELIC rate disclosures (3 years)
24 disclosures of IPCA and employment and income data (2 years)
You can select one or more macroeconomic variables to check the effect of correlation separately on each of them.
This indicator "Correlation X macroeconomics" will be updated monthly, as detailed below:
At the end of the day on which the PIB is released
At the end of the day on which employment and income data are released
At the end of the day following the day on which the SELIC rate is published
On the last business day of the month if none of the aforementioned disclosures occur
Label Selected DayThis Pine Script indicator allows users to highlight a specific day of the week on the chart. Users can select a day using the dropdown menu, and the script will mark all occurrences of that day.
The indicator is lightweight and non-intrusive, making it a great addition for traders who analyze market movements relative to specific days.
Wall Street Ai**Wall Street Ai – Advanced Technical Indicator for Market Analysis**
**Overview**
Wall Street Ai is an advanced, AI-powered technical indicator meticulously engineered to provide traders with in-depth market analysis and insight. By leveraging state-of-the-art artificial intelligence algorithms and comprehensive historical price data, Wall Street Ai is designed to identify significant market turning points and key price levels. Its sophisticated analytical framework enables traders to uncover potential shifts in market momentum, assisting in the formulation of strategic trading decisions while maintaining the highest standards of objectivity and reliability.
**Key Features**
- **Intelligent Pattern Recognition:**
Wall Street Ai employs advanced machine learning techniques to analyze historical price movements and detect recurring patterns. This capability allows it to differentiate between typical market noise and meaningful signals indicative of potential trend reversals.
- **Robust Noise Reduction:**
The indicator incorporates a refined volatility filtering system that minimizes the impact of minor price fluctuations. By isolating significant price movements, it ensures that the analytical output focuses on substantial market shifts rather than ephemeral variations.
- **Customizable Analytical Parameters:**
With a wide range of adjustable settings, Wall Street Ai can be fine-tuned to align with diverse trading strategies and risk appetites. Traders can modify sensitivity, threshold levels, and other critical parameters to optimize the indicator’s performance under various market conditions.
- **Comprehensive Data Analysis:**
By harnessing the power of artificial intelligence, Wall Street Ai performs a deep analysis of historical data, identifying statistically significant highs and lows. This analysis not only reflects past market behavior but also provides valuable insights into potential future turning points, thereby enhancing the predictive aspect of your trading strategy.
- **Adaptive Market Insights:**
The indicator’s dynamic algorithm continuously adjusts to current market conditions, adapting its analysis based on real-time data inputs. This adaptive quality ensures that the indicator remains relevant and effective across different market environments, whether the market is trending strongly, consolidating, or experiencing volatility.
- **Objective and Reliable Analysis:**
Wall Street Ai is built on a foundation of robust statistical methods and rigorous data validation. Its outputs are designed to be objective and free from any exaggerated claims, ensuring that traders receive a clear, unbiased view of market conditions.
**How It Works**
Wall Street Ai integrates advanced AI and deep learning methodologies to analyze a vast array of historical price data. Its core algorithm identifies and evaluates critical market levels by detecting patterns that have historically preceded significant market movements. By filtering out non-essential fluctuations, the indicator emphasizes key price extremes and trend changes that are likely to impact market behavior. The system’s adaptive nature allows it to recalibrate its analytical parameters in response to evolving market dynamics, providing a consistently reliable framework for market analysis.
**Usage Recommendations**
- **Optimal Timeframes:**
For the most effective application, it is recommended to utilize Wall Street Ai on higher timeframe charts, such as hourly (H1) or higher. This approach enhances the clarity of the detected patterns and provides a more comprehensive view of long-term market trends.
- **Market Versatility:**
Wall Street Ai is versatile and can be applied across a broad range of financial markets, including Forex, indices, commodities, cryptocurrencies, and equities. Its adaptable design ensures consistent performance regardless of the asset class being analyzed.
- **Complementary Analytical Tools:**
While Wall Street Ai provides profound insights into market behavior, it is best utilized in combination with other analytical tools and techniques. Integrating its analysis with additional indicators—such as trend lines, support/resistance levels, or momentum oscillators—can further refine your trading strategy and enhance decision-making.
- **Strategy Testing and Optimization:**
Traders are encouraged to test Wall Street Ai extensively in a simulated trading environment before deploying it in live markets. This allows for thorough calibration of its settings according to individual trading styles and risk management strategies, ensuring optimal performance across diverse market conditions.
**Risk Management and Best Practices**
Wall Street Ai is intended to serve as an analytical tool that supports informed trading decisions. However, as with any technical indicator, its outputs should be interpreted as part of a comprehensive trading strategy that includes robust risk management practices. Traders should continuously validate the indicator’s findings with additional analysis and maintain a disciplined approach to position sizing and risk control. Regular review and adjustment of trading strategies in response to market changes are essential to mitigate potential losses.
**Conclusion**
Wall Street Ai offers a cutting-edge, AI-driven approach to technical analysis, empowering traders with detailed market insights and the ability to identify potential turning points with precision. Its intelligent pattern recognition, adaptive analytical capabilities, and extensive noise reduction make it a valuable asset for both experienced traders and those new to market analysis. By integrating Wall Street Ai into your trading toolkit, you can enhance your understanding of market dynamics and develop a more robust, data-driven trading strategy—all while adhering to the highest standards of analytical integrity and performance.
Highs, Lows & SessionsHigh Low & Sessions Indicator - Purpose & Usage
The High Low & Sessions indicator is designed to provide key price levels and session-based market insights to help traders make informed decisions. It focuses on daily highs/lows, weekly highs/lows, and major trading sessions to identify support, resistance, and volatility patterns.
Key Functions of the High Low & Sessions Indicator:
Tracks Daily & Weekly Highs and Lows
Previous Day’s High & Low: Helps traders identify breakout points and potential reversals.
Previous Week’s High & Low: Provides key resistance/support levels for swing trading strategies.
Trading Session Zones
London Session: High volatility, often setting the daily trend.
New York Session: Strong liquidity, continuation or reversal of the London move.
Asian Session (Tokyo & Sydney): Lower volatility, potential accumulation phase.
Custom Time Alert with Vertical Line📌 Detailed Explanation of the Custom Time Alert with Vertical Line in Pine Script v5
This script is a time-based alert system designed for TradingView. It allows traders to set a specific hour and minute for alerts and provides visual indicators on the chart, including a marker when the alert triggers and a vertical line at the alert time.
🔹 Main Features
Custom Alert Time → Users can specify the exact hour and minute for an alert.
Time Zone Offset Support → Users can manually adjust their local UTC offset to ensure alerts trigger at the correct time.
Real-Time Alert Condition → When the market reaches the set time, an alert notification is triggered.
Chart Visualization → A red marker appears when the alert is activated, and a blue vertical line is drawn at the alert time.
Automated Calculation → The script adjusts the alert time based on the user’s time zone settings.
🛠️ How It Works
User Input for Alert Time
The script allows users to enter their desired alert hour (0-23) and minute (0-59).
This ensures the alert triggers at the exact specified time.
Time Zone Offset Handling
Users enter their UTC offset (e.g., New York is -5, Tokyo is +9).
This ensures alerts work correctly regardless of the user’s location.
Time Calculation
The script adjusts the TradingView time by adding the time zone offset in milliseconds.
This converts the UTC-based TradingView time into the user’s local time.
Checking for a Time Match
The script constantly checks if the current hour and minute match the user-defined alert time.
If they match, the script activates an alert.
Triggering Alerts
The script uses TradingView’s alertcondition() function to create an alert.
When the time matches, TradingView sends a notification (e.g., pop-up, sound, or mobile alert).
Chart Markers for Visual Alerts
A red marker is displayed on the chart when the alert triggers.
A blue vertical line is drawn at the exact alert time.
📌 Example Use Cases
📈 1. Forex Traders Monitoring Market Opens
A forex trader who trades the London session wants an alert when the market opens at 8:00 AM UTC.
The trader sets:
Alert Hour = 8
Alert Minute = 0
Time Zone Offset = 0 (for UTC)
When the market reaches 8:00 AM UTC, the script triggers an alert.
📈 2. Stock Market Open Alerts
A trader in New York (EST) wants an alert at 9:30 AM Eastern Time (New York Stock Exchange open).
New York’s UTC offset is -5.
The trader sets:
Alert Hour = 9
Alert Minute = 30
Time Zone Offset = -5
The script ensures the alert triggers at 9:30 AM EST.
📈 3. Crypto Trader Watching a Specific Time
A crypto trader wants an alert for a specific strategy at 3:00 PM in Tokyo (UTC+9).
Tokyo’s UTC offset is +9.
The trader sets:
Alert Hour = 15
Alert Minute = 0
Time Zone Offset = +9
The script ensures the alert triggers exactly at 3:00 PM Tokyo time.
Personal Time Zone: Days of WeekThis is probably the simplest indicator I have ever made.
It just gives you a the days of weeks in your specified time zone and puts the day on the first bar in your time zone.
You can use UTC time format or named time zones like the default.
Just for fun I tried to give it symbols that sort of relate the old gods that the days of week were named after and even colors that one could argue match, but it was all in fun because it was so simple I felt I had to add something.
Enjoy.
Bitcoin MVRV Z-Score Indicator### **What This Script Does (In Plain English)**
Imagine Bitcoin has a "fair price" based on what people *actually paid* for it (called the **Realized Value**). This script tells you if Bitcoin is currently **overpriced** or **underpriced** compared to that fair price, using math.
---
### **How It Works (Like a Car Dashboard)**
1. **The Speedometer (Z-Score Line)**
- The blue line (**Z-Score**) acts like a speedometer for Bitcoin’s price:
- **Above Red Line** → Bitcoin is "speeding" (overpriced).
- **Below Green Line** → Bitcoin is "parked" (underpriced).
2. **The Warning Lights (Colors)**
- **Red Background**: "Slow down!" – Bitcoin might be too expensive.
- **Green Background**: "Time to fuel up!" – Bitcoin might be a bargain.
3. **The Alarms (Alerts)**
- Your phone buzzes when:
- Green light turns on → "Buy opportunity!"
- Red light turns on → "Be careful – might be time to sell!"
---
### **Real-Life Example**
- **2021 Bitcoin Crash**:
- The red light turned on when Bitcoin hit $60,000+ (Z-Score >7).
- A few months later, Bitcoin crashed to $30,000.
- **2023 Rally**:
- The green light turned on when Bitcoin was around $20,000 (Z-Score <0.1).
- Bitcoin later rallied to $35,000.
---
### **How to Use It (3 Simple Steps)**
1. **Look at the Blue Line**:
- If it’s **rising toward the red zone**, Bitcoin is getting expensive.
- If it’s **falling toward the green zone**, Bitcoin is getting cheap.
2. **Check the Colors**:
- Trade carefully when the background is **red**.
- Look for buying chances when it’s **green**.
3. **Set Alerts**:
- Get notified when Bitcoin enters "cheap" or "expensive" zones.
---
### **Important Notes**
- **Not Magic**: This tool helps spot trends but isn’t perfect. Always combine it with other indicators.
- **Best for Bitcoin**: Works great for Bitcoin, not as well for altcoins.
- **Long-Term Focus**: Signals work best over months/years, not hours.
---
Think of it as a **thermometer for Bitcoin’s price fever** – it tells you when the market is "hot" or "cold." 🔥❄️
HTF Anchored FanSimilar to an Anchored VWAP, this lets you click a bar on an Daily, Weekly, or Monthly chart to add an "Anchored Fan" which displays lines at up to 6 levels above and below the chosen Anchor Point. Useful to measure the retracement during swing moves.
You can reposition the fan by either hovering over the anchor or by clicking the name of the study to "activate" it, and then dragging. You can also change the Anchor Point in Settings.
By default the anchor uses the bar Close, but you can change this manually in settings OR you can use the fancy "Auto high/low" mode which is handy if you are mainly dropping the fan on local swing highs and lows.
The default line measures were chosen for ES (Futures) but the study should be usable with nearly anything as long as you adjust the settings to something appropriate for the ticker. If you want to use this on NQ, for example, it would be reasonable to multiple each of these settings by 3.5 or so.
NOTE: If the fan is way off the left side of the chart it's generally easiest to use Settings to move it back to close to "now".
Percentage Retracement from HighPercentage Retracement Indicator
Description
The Percentage Retracement Indicator is a powerful analytical tool that visualizes price pullbacks from historical highs in percentage terms. Unlike traditional retracement tools that overlay on the price chart, this indicator displays the exact percentage drawdown in a dedicated pane below the chart, allowing for precise measurement of market corrections.
Key Features
Clear Visualization: Displays the current percentage retracement from a reference high in a separate pane, making it easy to gauge correction depth
Multiple Reference Points: Choose from ATH (All-Time High), Period High, Weekly High, Monthly High, Quarterly High, or Yearly High as your reference point
Color-Coded Levels: Intuitive color gradient from green (shallow pullbacks) to red and purple (deep corrections)
Customizable Thresholds: Set your own percentage levels for monitoring corrections (-5%, -10%, -20%, etc.)
Time-Based Labels: Clearly labeled percentage levels positioned along the timeline
Trading Applications
Identify Entry Points: Recognize historical pullback patterns to find optimal entry zones
Risk Management: Set stop-losses based on historical retracement behavior
Market Phases Analysis: Distinguish between healthy pullbacks and potential trend reversals
Comparative Analysis: Compare current drawdowns to historical corrections to gauge market sentiment
Volatility Assessment: Track the depth of pullbacks across different market regimes
Benefits
This indicator provides a clear, quantitative view of market corrections that isn't immediately obvious from price action alone. By transforming price movements into percentage terms, it creates an objective framework for analyzing pullbacks across different assets and timeframes.
Perfect for swing traders, position traders, and investors looking to add objective measures for market entry and exit during retracements.
Simple Sessions========== TLDR ==========
The "Simple Sessions" indicator plots vertical lines and labels at the open and close of the US (New York), Asia (Tokyo), and Europe (London), daily session. The existing session indicators I could find all changed the background color of the chart for the entire session or added extra information to the chart that cluttered up my view. This is meant to be a less noisy and easy to interpret indication that the session you trade has started or is ending.
========== Features ==========
- Show or hide vertical lines for session opens and closes
- Show or hide labels for session opens and closes
- Show or hide each session individually
- Show or hide just the session close indications
- Change the color used for each session open and close
- Change the labels text, size, and text color
========== Limitations ==========
The session start and end times are hard coded in for their time zones and can't be changed:
- US (New York) - 9:30 - 16:00
- Asia (Tokyo) - 9:00 - 15:00
- Europe (London) - 8:30 - 16:30
========== Use Cases ==========
- Easily see when each session started and ended without the chart being too noisy
- Make it easier to identify price action patterns and trade setups that may occur on the open of each session
=============================
If you'd like more features or options feel free to request them in the comments.
Global M2 Money Supply (USD) GrowthThe Global M2 Growth indicator evaluates the total liquid money supply, including cash, checking deposits, and assets that can be easily converted to cash. It reflects changes in global liquidity by tracking year-on-year (YoY) changes in the Global M2 money supply rather than its absolute value. This approach highlights the velocity of liquidity expansion or contraction, offering a clearer understanding of its correlation with asset performance, such as Bitcoin.
How It Works
When the Global M2 money supply expands, it reflects an increase in available liquidity. This often leads to an influx of capital into higher-yielding and riskier assets like Bitcoin, equities, and commodities. Conversely, when M2 contracts, liquidity tightens, leading to declines in the values of these assets.
An essential insight is that Bitcoin's price is not immediately affected by changes in M2. Research shows a lag of approximately 56-60 days (around two months) between liquidity changes and Bitcoin's price movements. Shifting the liquidity data forward by this period improves the correlation between Global M2 and Bitcoin performance.
How to Use
Track Global M2 YoY Change: Focus on liquidity's yearly change to identify trends. Rapid increases in liquidity often signify favorable conditions for Bitcoin and other risk assets to rise, while contractions often predict price declines or consolidation phases.
Account for the Lag Effect: Incorporate the two-month lag into your analysis to predict Bitcoin's potential moves more accurately. For instance, a recent resurgence in liquidity growth could signal a Bitcoin rally within the next two months.
Use as a Macro Indicator: Monitor liquidity trends alongside other economic indicators and asset performance metrics to build a more comprehensive investment framework.
By tracking these dynamics, traders and investors can better anticipate Bitcoin's trajectory and make informed decisions.
Supertrend with RSI FilterThis indicator is an enhanced version of the classic Supertrend, incorporating an RSI (Relative Strength Index) filter to refine trend signals. Here is a detailed explanation of its functionality and key advantages over the traditional Supertrend.
1. Indicator Functionality
The indicator uses ATR (Average True Range) to calculate the Supertrend line, just like the classic version. However, it introduces an additional condition based on RSI to strengthen or weaken the Supertrend color based on market momentum.
2. Interpretation of Colors
The indicator displays the Supertrend line with dynamic colors based on trend direction and RSI strength:
- Uptrend (Supertrend in buy mode):
- Dark green (Teal): RSI above the defined threshold (default 50) → Strong bullish confirmation.
- Light gray: RSI below the threshold → Indicates a weaker uptrend or lack of confirmation.
- Downtrend (Supertrend in sell mode):
- Dark red: RSI below the threshold → Strong bearish confirmation.
- Light gray: RSI above the threshold → Indicates a weaker downtrend or lack of confirmation.
The opacity of the color dynamically adjusts based on how far RSI is from its threshold. The greater the difference, the more vivid the color, signaling a stronger trend.
3. Key Advantages Over the Classic Supertrend
- Filters out false signals: The RSI integration helps reduce false signals by only validating trends when RSI aligns with the Supertrend direction.
- Weakens uncertain signals: When RSI is close to its threshold, the color becomes more transparent, alerting traders to a less reliable trend.
- Classic mode available: The 'Use Classic Supertrend' option allows switching to a standard Supertrend display (fixed red/green) without the RSI effect.
4. Customizable Parameters
- ATR Length & ATR Factor: Define the sensitivity of the Supertrend.
- RSI Period & RSI Threshold: Allow refining the RSI filter based on market volatility.
- Classic mode: Enables/disables the RSI filtering to revert to the original Supertrend.
This indicator is especially valuable for traders looking to refine their trend signals based on market momentum measured by RSI.
This indicator is for informational purposes only and should not be considered financial advice. Trading involves risks, and past performance does not guarantee future results. Always conduct your own analysis before making any trading decisions.
M2 Global Liquidity Index - 10 Week Lead
M2 Global Liquidity Index - Forward Projection (10 Weeks)
This indicator provides a 10-week forward projection of the M2 Global Liquidity Index, offering traders insight into potential future market conditions based on global money supply trends.
What This Indicator Shows
The M2 Global Liquidity Index aggregates M2 money stock data from five major economies:
- China (CNY)
- United States (USD)
- European Union (EUR)
- Japan (JPY)
- Great Britain (GBP)
All values are converted to USD and presented as a unified global liquidity metric, providing a comprehensive view of worldwide monetary conditions.
Forward Projection Feature
This adaptation displays the indicator 10 weeks ahead of the current price, allowing you to visualize potential future liquidity conditions that might influence market behavior. The projection maintains data integrity while providing an advanced view of the liquidity landscape.
Trading Applications
- Anticipate potential market reactions to changing global liquidity conditions
- Identify divergences between projected liquidity and current price action
- Develop longer-term strategic positions based on forward liquidity projections
- Enhance your macro-economic analysis toolkit
Credit
This indicator is an adaptation of the original "M2 Global Liquidity Index" created by Mik3Christ3ns3n. Full credit for the original concept and implementation goes to the original author. This version simply adds a 10-week forward projection to the existing calculations.
Disclaimer
This indicator is for informational purposes only and should be used as one of many tools in your analysis. Past performance and projections are not guarantees of future results.
