INTELLECT_city - Bitcoin Genesis Block DayBitcoin Genesis Block Day is celebrated on January 3 each year, commemorating the creation of the first block in the Bitcoin blockchain, known as the genesis block, by Satoshi Nakamoto on January 3, 2009. This block, block 0, marked the official launch of the Bitcoin network, embedding a message in its coinbase transaction: "The Times 03/Jan/2009 Chancellor on brink of second bailout for banks," referencing a headline from The Times newspaper. This message highlighted Bitcoin’s purpose as a decentralized alternative to centralized financial systems amid the 2008 financial crisis.
The genesis block is unique because it’s hardcoded into the Bitcoin protocol and cannot be spent, containing 50 BTC that remain unspendable. It established the foundation for Bitcoin’s blockchain, with subsequent blocks building upon it through cryptographic hashing. The day symbolizes the birth of cryptocurrency and is celebrated by the crypto community as a milestone in financial and technological innovation.
Ciclos
INTELLECT_city - Bitcoin Whitepaper DayBitcoin Whitepaper Day is celebrated on October 31 each year, marking the anniversary of the publication of the Bitcoin whitepaper by Satoshi Nakamoto in 2008. Titled "Bitcoin: A Peer-to-Peer Electronic Cash System," the nine-page document introduced the concept of a decentralized digital currency that operates without intermediaries like banks, using a peer-to-peer network, blockchain technology, and proof-of-work to solve the double-spending problem.
Published on a cryptography mailing list during the 2008 financial crisis, the whitepaper laid the foundation for Bitcoin and the broader cryptocurrency ecosystem, influencing innovations like Ethereum, decentralized finance (DeFi), and NFTs. It’s a day celebrated by the crypto community to honor the revolutionary ideas that sparked a new era of financial sovereignty and technological innovation. Some note the symbolic connection to October 31, also Reformation Day, suggesting Nakamoto chose it to signify a break from centralized financial systems, though this is speculative.
Pendulum Trend MatrixPendulum Trend Matrix is your all-in-one multi-timeframe dashboard and alert engine:
Up to 10 Timeframes
Choose any 1–10 custom timeframes (TF1–TF10). Blank slots inherit the chart’s current interval.
Four Trend Modules
Per-slot trend detection via ADX (+DI vs –DI), EMA (price vs EMA), VWAP (price vs VWAP), or SuperTrend (ATR-based). Customize ADX length, EMA period, SuperTrend ATR length & multiplier.
Live Countdown
Displays “d h m s” until the next bar closes on each selected timeframe.
Custom Symbols & Styling
Default 🚀/💩 for bullish/bearish but change to anything you like. Font sizes and table corner placement are adjustable.
Built-In Alerts
Countdown Reset Alerts: Fires on every bar close for TF1–TF10.
Trend Change Alerts: Fires whenever the trend flips in each slot.
Alert Behavior & Limitation
Due to TradingView’s execution model, your script only runs on the chart’s timeframe (or on each incoming tick if you choose “Once Per Tick” in the Alert dialog). Consequently:
If you set TF1 = 15S but your chart is on 5 min, the “15 s” reset won’t trigger until the 5 min bar updates or closes.
To receive regular sub-minute alerts, you must run the indicator on a chart interval at or below your shortest TF slot.
Tip: For reliable 1 min or faster alerts, set your chart to 1 min (or smaller) and choose “Once Per Tick” in the Alert dialog. This ensures your Countdown Reset and Trend Change alerts fire as expected, even on fast timeframes.
Advanced Marubozu with 100 EMA Strategy# Advanced Marubozu with EMA Strategy
## Description
This professional-grade strategy identifies high-probability trading opportunities using Marubozu candlestick patterns in conjunction with EMA trend confirmation. Trade signals are generated only at candle close for improved reliability and reduced false signals.
## Key Features
- **Precise Marubozu Pattern Detection**: Identifies bullish and bearish Marubozu candles with customizable shadow percentage tolerance
- **Trend Confirmation**: Uses 32-period EMA to confirm overall market direction
- **Multiple Filter Options**: Includes volatility, momentum, and time-based filters to refine trade entries
- **Advanced Risk Management**: Built-in stop-loss, take-profit, and trailing stop capabilities
- **Visual Indicators**: Clear on-chart markings and information panel
- **Candle Close Signals**: All signals are confirmed only after candle close for reliable entries
## Trading Logic
- **Long Entry**: Bullish Marubozu candlestick when price is above EMA with positive momentum
- **Short Entry**: Bearish Marubozu candlestick when price is below EMA with negative momentum
- **Risk Management**: Automatic stop-loss placement with customizable risk-reward ratio
## Customization Options
- Adjust Marubozu detection parameters to fit your trading instrument
- Modify EMA length for different market conditions
- Fine-tune momentum and volatility filters for optimal performance
- Set custom risk parameters and position sizing
Perfect for day traders and swing traders in any market (crypto, forex, stocks) looking for high-quality candlestick pattern entries with trend confirmation.
*This strategy combines traditional Japanese candlestick analysis with modern technical indicators for a powerful, rules-based trading approach.*
INTELLECT_city - New Year Chinese (Chine)Time of dates.
Sometimes you need to look at the years to find some patterns, especially on Chinese New Year.
ICT Macro and Daye QT ShiftEST Vertical Lines - Auto DST Adjustment
Overview
This indicator draws customizable vertical lines at specific Eastern Time (EST/EDT) points throughout the trading day, automatically adjusting for daylight savings time. Designed for precision trading on 1-minute and 5-minute charts, it highlights key intraday moments when price action tends to accelerate.
Features
- **18 pre-configured NY session times** (09:50-15:45 ET)
- **Auto timezone conversion** - Always shows correct EST/EDT regardless of your local timezone
- **3 line styles** - Choose between solid/dashed/dotted lines
- **Clean labeling** - Optional time markers above each line
- **1m/5m optimized** - Perfect for scalpers and day traders
- **Visual alerts** - "TOUCH" labels when price interacts with lines
Inputs
| Parameter | Description | Default |
|-----------|-------------|---------|
| Line Times | Comma-separated HH:MM times | 09:50,10:10,...15:45 |
| Line Color | Line color | Black |
| Line Width | 1-5px thickness | 2 |
| Line Style | Solid/Dashed/Dotted | Solid |
| Show Labels | Display time markers | true |
How To Use
1. Apply to 1m or 5m charts
2. Lines appear automatically at specified EST times
3. Watch for price reactions at these key levels
4. Customize styles via indicator settings
Ideal For
- NY open/London close traders
- Earnings/News traders
- Breakout traders
- Market open/close strategies
Updates
v1.1 - Added line style customization
v1.0 - Initial release
Yome Kill Zones ProPerfect for US30 Entry ## Yome Kill Zones Pro
**Yome Kill Zones Pro** is a precision trading tool designed for day traders and scalpers who focus on session-based setups, liquidity sweeps, and directional bias during the London–New York overlap.
---
### **Key Features**
- **Customizable Kill Zone Box**
- Marks session high/low from any user-defined time window (default: 6:00–11:30 UTC).
- **Swing Point Sweep Detection**
- Identifies significant highs/lows swept by price with momentum—ideal for supply/demand or S/R zones.
- **Independent Bias Kill Zone**
- Separate bias calculation window with adjustable start/end time to isolate market sentiment.
- **Bias Table (Always-On Display)**
- **Killzone Bias** – Shows direction based on price change during bias time.
- **Long-Term Bias** – Compares price vs. Open and EMA(50) from any selected timeframe (default: 15m).
- **Full Visual Customization**
- Editable sweep labels, line colors, line style, label visibility, and kill zone extensions.
---
### **How to Use**
1. **Set Your Session Times**
- Use the “Killzone Settings” to define high/low tracking time.
- Use “Bias Killzone Settings” to define when to calculate bias direction.
2. **Check the Bias Table**
- Use **Killzone Bias** for short-term session direction.
- Use **Long-Term Bias** to align with higher timeframe market structure.
3. **Watch for Liquidity Sweeps**
- Look for momentum-based breaks of swing highs/lows within your kill zone window.
- Use these levels to anticipate reversals, retests, or continuations.
4. **Customize It Your Way**
- Everything from line styles, sweep label visibility, thickness, and colors can be customized.
---
### **Best For**
- London & New York session scalpers
- Liquidity & structure-based traders
- Traders using ICT, Smart Money Concepts, or Wyckoff-style analysis
---
> **Tip:** Pair with volume or order block tools for enhanced sniper entries.
HoonMhee Data Levels ToolThis tool is designed specifically for drawing horizontal lines based on Hoonmhee trading data. It is not a complete trading strategy and does not generate any buy or sell signals.
OTC COT / smart money Index 2.0 COT/ Smart money Indicator – Institutional Commitment & Position Sizing (Inspired by Bernd Skorupinski Methodology)
📈 Description:
This indicator focuses on visualizing net positions held by commercials (smart money) and other key market participants, using data from the Commitments of Traders (COT) report. Inspired by Bernd Skorupinski’s institutional approach, the tool works hand-in-hand with the COT Index to provide a full picture of institutional sentiment and positioning strength.
👉 Core Functionality:
Displays net-long and net-short positions over time, helping traders understand how heavily institutions are positioned in a market.
Highlights historical extremes in net positions, which can act as warning signs or entry points when combined with technical analysis.
Supports customizable timeframes and asset selection (commodities, forex, indices) for maximum flexibility.
Best used in combination with the COT Index, offering a layered view of both relative extremes (COT Index) and absolute exposure (Net Positions).
The tool is designed to act as a contextual filter—it should complement technical setups rather than provide standalone trade signals.
📊 Applied Example – Gold Trade Using COT Net Position Analysis
To show the practical application, here’s a breakdown of a Gold (GC1!) trade that leveraged both COT Index and COT Net Positions to identify a high-probability setup.
Step 1️⃣ – Identifying Technical Structure:
The analysis started with classic price action review: Gold was approaching a significant demand zone, a well-established area that has historically triggered institutional buying.
Step 2️⃣ – COT Index Confirmation:
Upon reviewing the COT Index, the data revealed a 312-week buying extreme—the most aggressive commercial buying seen in over six years, signaling strong institutional accumulation.
Step 3️⃣ – COT Net Positions Validation:
Next, the COT Net Position Indicator showed that commercials were holding their largest net-long position in over 15 years—a rare and powerful signal of institutional conviction.
Step 4️⃣ – Divergence Check:
For added confirmation, divergence between commercials and retail traders was assessed:
✅ Commercials: Strongly net-long.
❌ Retail traders: Heavily net-short.
This clear divergence between smart money and retail sentiment further validated the setup.
Step 5️⃣ – Trade Execution:
With everything aligned:
Demand zone identified,
312-week COT Index extreme,
15-year high in net positions,
Divergence between commercials and retail,
…the trade was entered with a stop-loss placed just below the demand zone and a target set at a significant prior high. The result: a risk-reward ratio of 1:14.8, reflecting the strength and precision of the setup.
⚙️ What Sets This Tool Apart:
Provides deep insight into institutional exposure, showing both the magnitude of positions and how they evolve over time.
Enhances decision-making by cross-validating positioning extremes with technical levels.
Flexible design allows use across multiple asset classes and timeframes.
📌 Best Practices:
Always pair COT Net Position data with the COT Index to gauge both relative and absolute strength.
Use in conjunction with demand/supply zones or key technical levels for the strongest setups.
Look for divergence signals (institutions vs. retail) to confirm potential reversals.
Indicators Used in the Example:
This trade combined:
🧠 COT Net Position Indicator – to measure institutional exposure.
📊 COT Index – to identify positioning extremes.
📅 Seasonality Forecasting Tool – for time-based confirmation.
Together, these indicators provided a robust, multi-layered framework for high-confidence trading decisions.
OTC - COT Net positions 2.0 COT Net Position Indicator – Institutional Commitment & Position Sizing (Inspired by Bernd Skorupinski Methodology)
📈 Description:
This indicator focuses on visualizing net positions held by commercials (smart money) and other key market participants, using data from the Commitments of Traders (COT) report. Inspired by Bernd Skorupinski’s institutional approach, the tool works hand-in-hand with the COT Index to provide a full picture of institutional sentiment and positioning strength.
👉 Core Functionality:
Displays net-long and net-short positions over time, helping traders understand how heavily institutions are positioned in a market.
Highlights historical extremes in net positions, which can act as warning signs or entry points when combined with technical analysis.
Supports customizable timeframes and asset selection (commodities, forex, indices) for maximum flexibility.
Best used in combination with the COT Index, offering a layered view of both relative extremes (COT Index) and absolute exposure (Net Positions).
The tool is designed to act as a contextual filter—it should complement technical setups rather than provide standalone trade signals.
📊 Applied Example – Gold Trade Using COT Net Position Analysis
To show the practical application, here’s a breakdown of a Gold (GC1!) trade that leveraged both COT Index and COT Net Positions to identify a high-probability setup.
Step 1️⃣ – Identifying Technical Structure:
The analysis started with classic price action review: Gold was approaching a significant demand zone, a well-established area that has historically triggered institutional buying.
Step 2️⃣ – COT Index Confirmation:
Upon reviewing the COT Index, the data revealed a 312-week buying extreme—the most aggressive commercial buying seen in over six years, signaling strong institutional accumulation.
Step 3️⃣ – COT Net Positions Validation:
Next, the COT Net Position Indicator showed that commercials were holding their largest net-long position in over 15 years—a rare and powerful signal of institutional conviction.
Step 4️⃣ – Divergence Check:
For added confirmation, divergence between commercials and retail traders was assessed:
✅ Commercials: Strongly net-long.
❌ Retail traders: Heavily net-short.
This clear divergence between smart money and retail sentiment further validated the setup.
Step 5️⃣ – Trade Execution:
With everything aligned:
Demand zone identified,
312-week COT Index extreme,
15-year high in net positions,
Divergence between commercials and retail,
…the trade was entered with a stop-loss placed just below the demand zone and a target set at a significant prior high. The result: a risk-reward ratio of 1:14.8, reflecting the strength and precision of the setup.
⚙️ What Sets This Tool Apart:
Provides deep insight into institutional exposure, showing both the magnitude of positions and how they evolve over time.
Enhances decision-making by cross-validating positioning extremes with technical levels.
Flexible design allows use across multiple asset classes and timeframes.
📌 Best Practices:
Always pair COT Net Position data with the COT Index to gauge both relative and absolute strength.
Use in conjunction with demand/supply zones or key technical levels for the strongest setups.
Look for divergence signals (institutions vs. retail) to confirm potential reversals.
Indicators Used in the Example:
This trade combined:
🧠 COT Net Position Indicator – to measure institutional exposure.
📊 COT Index – to identify positioning extremes.
📅 Seasonality Forecasting Tool – for time-based confirmation.
Together, these indicators provided a robust, multi-layered framework for high-confidence trading decisions.
OTC Seasonal forecasting tool 2.0Seasonality Forecasting Tool – Advanced Seasonal Pattern Analysis (Inspired by Bernd Skorupinski Methodology)
📈 Description:
This script provides a structured way to analyze seasonal trends across financial markets, helping traders identify historical patterns that tend to repeat at specific times of the year. Inspired by Bernd Skorupinski’s institutional strategy, it has been refined with enhanced smoothing and customization options to improve adaptability across asset classes like commodities, forex, and indices.
👉 Core Functionality:
Analyzes historical price data over multiple lookback periods (5, 10, and 15 years) to calculate average seasonal performance.
Generates a smoothed seasonal curve that visually highlights periods of expected strength or weakness.
Allows users to customize lookback periods and adjust smoothing parameters, offering flexibility based on market type and volatility.
This tool is designed to be used as a contextual filter rather than a trade trigger—adding a layer of time-based confluence to enhance decision-making.
📊 Applied Example – Crude Oil Seasonality & Demand Zone Alignment
To demonstrate practical usage, here’s an example using Light Crude Oil Futures (CL1!) where seasonal tendencies and price structure aligned to create a high-probability setup.
Setup Steps:
1️⃣ Structural Context – Price Reaching a Demand Zone:
The market had been in a decline and approached a well-defined institutional demand area, which historically attracts buying interest.
2️⃣ Seasonality Analysis – Bullish Bias Identified:
The Seasonality Tool was applied using three distinct lookback windows:
5-year average 🟢
10-year average 🔴
15-year average 🔵
All three seasonal curves showed consistent upward trends during the late December to February period, historically signaling accumulation phases in crude oil markets.
3️⃣ Execution – Trade Setup:
With both:
Price action confirming a technical demand zone,
and seasonality indicating a strong historical bullish period,
a long position was taken targeting the next significant supply zone.
Result:
The trade unfolded as anticipated, with price rebounding strongly and delivering a risk-reward ratio of approximately 1:5.8—an outcome consistent with historical seasonal performance patterns.
⚙️ What Sets This Tool Apart:
Combines multi-timeframe seasonal data into a unified, easy-to-interpret visual output.
Includes custom smoothing algorithms to reduce noise, making the seasonal curves clearer and more reliable in fast-moving markets.
Offers flexibility to analyze not only commodities but also forex, indices, and other instruments influenced by recurring cycles (e.g., agricultural products, metals).
📌 Best Practices for Use:
Apply the tool alongside key technical zones (demand/supply) to find optimal trade timing.
Look for confluence across at least two of the seasonal curves (e.g., 5-year and 10-year averages agreeing on direction).
Use in combination with other market analysis tools—such as valuation indicators, COT data, or smart money flow—for full confirmation.
OTC valuation indicator 2.0Valuation Indicator – Relative Asset Valuation Tool (Inspired by Bernd Skorupinski Methodology)
📈 Description:
This script is designed to analyze relative value shifts between two assets—such as Gold (GC1!) and the Dollar Index (DXY)—to identify overvalued and undervalued market conditions. It is inspired by principles from Bernd Skorupinski’s methodology but has been developed with custom adjustments and improvements to enhance flexibility and adaptability across various asset classes.
👉 How It Works:
The script calculates a normalized valuation index by measuring the percentage price deviation between a target asset (e.g., Gold) and a reference asset (e.g., Dollar Index).
A moving average baseline defines fair value, with deviations indicating potential overvaluation or undervaluation.
A volatility-adjusted filter dynamically smooths the output, reducing noise and improving signal accuracy across different market environments.
Parameters such as evaluation period and sensitivity are fully customizable, allowing traders to tailor the tool to commodities, forex, indices, or other asset pairs.
📊 Detailed Example – Gold & Dollar Index Setup:
To demonstrate how the indicator can be used, here’s an example based on a real market scenario:
Context : Identifying high-probability buy setups on Gold when undervaluation is confirmed relative to the Dollar Index.
Conditions :
1️⃣ Gold enters a significant demand zone (identified through traditional technical analysis).
2️⃣ The valuation index (from this script) drops below the -75 level, signaling strong undervaluation
In both October 2022 and October 2023, the valuation index dropped well below -75, and Gold was sitting at major demand zones. The result?
📈 Massive moves to the upside, with Risk-Reward ratios hitting 1:4 or more.
snapshot
This is a textbook Bernd Skorupinski strategy setup, combining macro fundamentals (valuation) with technical structure (demand zones).
This is not just theory — the same conditions repeated multiple times, delivering repeatable, high-probability trades.
This showcases how macro mispricing (Dollar overvalued, Gold undervalued) can be identified visually and quantitatively using the indicator, enabling traders to make more confident, data-backed entry decisions.
⚙️ What Makes It Unique:
Unlike standard correlation or spread indicators, this script combines dynamic volatility filtering with a multi-step comparative analysis to better handle market volatility and price extremes.
It offers flexible asset pairing, allowing traders to adapt the tool to various market scenarios beyond just Gold/DXY—such as Oil vs. Euro or Stocks vs. Forex.
📌 Recommended Use:
Best applied on weekly and daily charts.
Should be combined with other technical tools such as support/resistance levels or demand zones for added confirmation.
Not intended as a standalone signal; it works best as part of a broader market analysis strategy.
IT F&O Basket Avg % ChangeThis indicator calculates the average daily % change of major IT sector F&O stocks. It displays the result prominently on the chart to quickly assess sector strength.
AlphaPulse Luxury Suite Elite🔷 AlphaPulse Luxury Suite — Your Precision Trading Companion
AlphaPulse Luxury Suite is a premium, invite-only multi-strategy indicator designed for traders who demand actionable, real-time insights with institutional-grade clarity. This suite intelligently fuses trend detection, momentum confirmation, volume validation, and risk analytics into one seamless on-chart system.
🔍 What It Does and How It Works
AlphaPulse is more than just a mashup — it’s a unified strategy engine that combines proven trading methodologies into a cohesive decision-support tool. The system monitors real-time trend regimes, filters signal quality using momentum-volume alignment, and dynamically plots entries and exits with risk-managed precision.
✅ Core Components
🔹 Trend Regime Detection (SuperTrend Core)
Uses adaptive SuperTrend logic to identify evolving trend phases.
Gradient overlays reflect trend strength and volatility zones.
🔹 Multi-Layer Signal Confirmation
Signals only appear when momentum (MACD divergence), trend alignment (MA crossovers), and volume shifts agree.
Filters out noise and helps you stay in trades longer with confidence.
🔹 Alpha Dashboard
On-chart HUD includes metrics like:
Trend Strength Score
Momentum Status
Volatility Pressure
Signal Quality Meter
Dynamic Risk Zones
🔹 Risk/Reward Overlay
Uses ATR-based volatility logic to auto-calculate Stop Loss and Take Profit levels.
Customizable for scalpers, swing traders, and longer-term plays.
🔹 Clean Display Toggle
Switch to minimal mode with a single click — keep your chart sleek and focused.
🧠 Strategic Use Cases
AlphaPulse is ideal for:
Intraday scalping on lower timeframes
Swing entries with confirmation layers
Trend-following with risk control
Discretionary setups enhanced by confluence
⚙️ How to Trade with It
Wait for buy/sell label confirmation after confluence triggers.
Confirm with the dashboard: trend, momentum, and volume all aligned.
Use the built-in SL/TP levels or your own system.
Exit when trend weakens, volatility shifts, or opposite signal appears.
Disclaimer: This script is invite-only and does not guarantee profits. Use it as part of a disciplined, tested trading strategy.
AlgoRanger Momentum + Trend - Following//@version=5
indicator("AlgoRanger Momentum + Trend - Following", overlay=true)
startLen = input.int(20, title="Start EMA Length")
step = input.int(5, title="Step between EMAs")
maxCount = 8 // max number of EMAs
getColor(_price, _ema) =>
_price > _ema ? color.rgb(3, 203, 106) : color.rgb(255, 37, 37)
ema1 = ta.ema(close, startLen + 0 * step)
ema2 = ta.ema(close, startLen + 1 * step)
ema3 = ta.ema(close, startLen + 2 * step)
ema4 = ta.ema(close, startLen + 3 * step)
ema5 = ta.ema(close, startLen + 4 * step)
ema6 = ta.ema(close, startLen + 5 * step)
ema7 = ta.ema(close, startLen + 6 * step)
ema8 = ta.ema(close, startLen + 7 * step)
plot(ema1, color=getColor(close, ema1), linewidth=1, title="EMA 1")
plot(ema2, color=getColor(close, ema2), linewidth=1, title="EMA 2")
plot(ema3, color=getColor(close, ema3), linewidth=1, title="EMA 3")
plot(ema4, color=getColor(close, ema4), linewidth=1, title="EMA 4")
plot(ema5, color=getColor(close, ema5), linewidth=1, title="EMA 5")
plot(ema6, color=getColor(close, ema6), linewidth=1, title="EMA 6")
plot(ema7, color=getColor(close, ema7), linewidth=1, title="EMA 7")
plot(ema8, color=getColor(close, ema8), linewidth=1, title="EMA 8")
CMT CMT provides thamn more information than good information it will be a good indicator to set up the things will be a good indicator
Bitcoin Dynamic RibbonThe BTC1D Ribbon Corridor is a multi‑layered, Fibonacci‑based dynamic support/resistance strategy built for the BTC/USD daily chart. This strategy combines custom time‐decay logarithmic bands, polynomial trend forecasts, cycle detection, momentum cross-filters, and Monte Carlo–style projections into a cohesive framework designed to help traders visualize and backtest both mean‐reversion and breakout opportunities.
Key Components:
1. Time‑Weighted Logarithmic Fibonacci Corridor
Computes a dynamic ribbon of eight Fibonacci levels by fitting a log‐decay model to elapsed
time since July 19, 2010.
Intercepts and slopes for support/resistance lines are calibrated via cumulative functions, producing bands that adapt to BTC’s long‑term growth cycle.
2. Polynomial Regression Price Law
Applies a log‑law regression to model BTC’s macro‑trend “price law,” generating center lines and shaded corridors.
Overlays future projections, giving traders visual insight into expected growth paths under historical volatility.
3. Cycle Peak & Bear/Bull Filters
Detects cycle peaks and bottoms using SMA and EMA filters, marking these events with vertical lines and backgrounds.
Applies a color‑gradient background to price bars, dynamically mapping Risk as a 10‑band spectrum—highlighting low (deep blue) through high (bright red) zones.
4. Momentum & Trend‑Filter Strategy Logic
Long Entry when the Risk oscillator dips below 1 (deep blue) and price is below the polynomial support line, signaling oversold mean‑reversion.
Close Long when Risk oscillator exceeds 9 (bright red), or when MA cross signals trend exhaustion.
Bear Market Long entries trigger on aligned short‑term SMA/VWMA and price/VWMA crossovers, offering tactical bull‑market hedges during corrective phases.
Integrated ADX and MA‑spread filters prevent entries during low‑volatility or sideways regimes.
5. Monte Carlo–Style Forecasting
Offers two forecasting modes:
Normal: simulates price paths via Gaussian log‑returns over a user‑set “reference size” (bars) and “forecast length,” plotting best‑/worst‑case envelopes.
Bootstrap: resamples historical log‑returns for faster, lighter projections.
6. Table of live strategy performance
(Realized %, Open %, Total %) embedded top‑right for deeper testing and clarity.
How to Use
Apply to BTCUSD, 1D timeframe.
Configure Date Filters: Default start is Jan 1, 2010; you may adjust “Start Date” and “End Date” under Fib Corridor inputs to focus on specific market cycles.
Forecast Settings: Under the Forecast group, select “Normal” or “Bootstrap,” simulation count, back‑reference size, and forecast length. Toggle “Show Best Case/Worst Case Only” for clarity.
Interpret Bands & Colors:
Thick red/green outer lines mark long‑term log‑law support/resistance.
Inner black lines reflect Fibonacci splits of the log‑decay corridor.
Price bars colored blue→red indicate normalized Risk state.
No existing public script (as far as I am aware) unifies time‑decay Fibonacci corridors, polynomial trend laws, clear cycle labeling, volumetric VWMA filters, oscillator‑based mean reversion, and Monte Carlo projections into one strategy. Every component is crafted to interoperate: the dynamic bands define structural bias; the oscillator times entries; and the simulation engine visualizes potential outcomes. This depth of integration and forward‑projected logic was carefully put together to embody a principled approach to BTC’s unique market dynamics.
I hope you enjoy the insights this strategy offers, I had a lot of fun making it. Feel free to leave any recommendations or criticisms in the comments :)
Happy Trading!
Bitcoin Power Law Bayesian Fit with Residual HistogramTitle: Bayesian Bitcoin Power Law Indicator with Residuals Histogram
Description:
This Pine Script implements a Bitcoin (BTC) price indicator based on a power-law relationship between BTC price and time, modeled using Bayesian regression.
Bayesian regression is one of the most robust regression methods.
The indicator provides a robust framework for understanding BTC price trends, highlighting key statistical levels, based on deviation from the power law trend and visualizing the bimodal nature of BTC price behavior through a residual distribution histogram (distribution of the deviation from the Bayesian power law trend).
Features:
Power Law Model with Confidence Levels:
Models BTC price as a power-law function of time using Bayesian regression, displaying the median trendline.
Includes multiple confidence intervals to reflect statistical uncertainty.
Plots a support power-law line, set at 2 standard deviations below the median trend, serving as a critical lower bound for price expectations.
Bimodal Residual Histogram:
Displays a histogram in a lower panel, illustrating the distribution of model residuals (difference between actual BTC price and the power-law model) over a default 100-day window (user-configurable). This is one of the most innovative components of this indicator because it highlights the current shape of the distribution of recent deviations.
Highlights the bimodal nature of BTC price behavior, with two distinct regimes:
Core Power Law: Represents periods (approximately 2 years) when BTC price closely follows the power-law trend, typically when below the median power-law line.
Turbulent Flow BTC: Captures periods when BTC price is above the median power-law line, exhibiting more chaotic, bull-run behavior.
The histogram provides a range of possible prices based on the observed residual distribution, aiding in probabilistic price forecasting.
These analogies with fluid dynamics are part of the power law framework based on parallels in financial physics.
Purpose:
This indicator is designed for traders and analysts seeking to understand BTC price dynamics through a statistically grounded power-law model. The confidence levels and support line offer clear benchmarks for trend and support analysis, while the bimodal histogram provides insight into whether BTC is in a stable "Core Power Law" phase or a volatile "Turbulent Flow" phase, enabling better decision-making based on market regime.
Usage Notes:
Use the histogram to determine whether BTC is in the Core Power Law (below the power-law trend) or Turbulent Flow (above the trend) regime to contextualize price behavior.
Adjust the residual window (default 100 days) to analyze different timeframes for the distribution.
The support power-law line (2 standard deviations below) serves as a critical level for identifying potential price floors.
Trump/Biden Market RegimesHave you ever wondered if it's Trump's stock market (up) or Biden's stock market (down)? Think no more!
BLCKBOX Buying / Selling SentimentThis indicator attempts to predict buying and selling sentiment. It may help?
AL-SAT Sinyali (Dip AL + Heikin Ashi)Buy: Combines RSI, MACD, volume, and trend signals
Sell: RSI>70 + MACD cross down
Target: Auto 10% line, profit shown
Dip Buy: RSI<30 + dip zone + HA bullish
Note: Use with context; HA may delay signals.
