Market Entropy Strategy V2.5This strategy is an updated version of a market entropy-based trading system. It removes EMA dependencies and introduces two indicators:
1. **Volatility Momentum Index (VMI)**: Measures volatility acceleration for timing entries (from calm to active phases) and exits (at peak chaos).
2. **Volume-Weighted Price Center (VWPC)**: A volume-weighted trend filter using typical price to determine overall market direction.
The strategy enters trades on transitions from low volatility ("calm") to increasing activity, filtered by trend direction. Exits occur when volatility reaches a high "chaos" threshold. It supports long, short, or both directions, with configurable parameters for optimization.
Backtest results depend on market conditions; use with caution and combine with your own analysis. No guarantees of performance.
Bitcoin (Criptovaluta)
3 SMAs 7/20/50 Bullish/Bearish Screener For Day TradeAll SMAs Bullish/Bearish Screener (Visually Enhanced) - Detailed Description
Overview
The "All SMAs Bullish/Bearish Screener (Visually Enhanced)" is a comprehensive trend analysis tool designed to provide traders with a clear, multi-faceted view of market momentum. It goes beyond simple moving average crossovers by integrating a suite of confirmation indicators—RSI, Volume, and Momentum (ROC)—to generate high-conviction trading signals. The primary goal of this script is to identify periods where the short, medium, and long-term trends are aligned and confirmed by underlying market strength, helping traders to enter positions with greater confidence and avoid choppy, directionless markets.
Visually, the indicator is designed for maximum clarity. It uses color-coded moving averages, clear on-chart signals (up/down triangles), an optional background color to highlight the dominant trend, and a persistent on-screen status table that provides an at-a-glance summary of the current market condition.
Key Features
Multi-SMA Trend Alignment: The core of the indicator is based on the alignment of the 7, 20, and 50-period Simple Moving Averages (SMAs). A signal is only considered when the price is decisively above or below all three, indicating a unified trend.
Three-Factor Confirmation: To filter out weak or false signals, the script requires confirmation from three classic indicators:
RSI (Relative Strength Index): Ensures that the trend is supported by underlying strength (RSI > 50 for bullish, < 50 for bearish).
Volume: Confirms that there is conviction behind the move by checking if the volume is above its 20-period average.
Momentum (Rate of Change): Verifies that the price is actively moving in the direction of the trend (positive ROC for bullish, negative for bearish).
Clear Visual Signals:
Green Triangle (Below Bar): A "Strongly Bullish" signal appears when the price is above all SMAs and all three confirmation indicators are met.
Red Triangle (Above Bar): A "Strongly Bearish" signal appears when the price is below all SMAs and all three confirmation indicators are met.
Status Table: A corner display provides real-time text updates: "Strongly Bullish," "Strongly Bearish," "SMAs Bullish (No Confirmation)," or "SMAs Mixed."
Customizable Background Color: An optional background tint (green for bullish, red for bearish) provides an immediate visual sense of the prevailing confirmed trend.
How to Use the Indicator
This indicator is best used as a tool for trend confirmation and entry timing.
Identify the Trend: The primary use is to wait for a "Strongly Bullish" or "Strongly Bearish" signal to appear in the status table, indicated by a corresponding green or red triangle on the chart. These are your highest-probability signals.
Entry: A common strategy is to enter a trade on the close of the candle where the signal appears. For a bullish signal (green triangle), this would be a long (buy) entry. For a bearish signal (red triangle), this would be a short (sell) entry.
Context is Key: Avoid taking signals in isolation. Pay attention to the broader market structure. For example, a bullish signal is stronger if it appears after breaking a key resistance level or forming a bullish chart pattern (like a double bottom).
Setting Stop-Loss and Profit Targets
This script does not provide explicit stop-loss or target levels; these should be determined based on your personal risk management strategy. The following are general guidelines:
Stop-Loss Placement:
For Bullish Trades (Long): A logical place for a stop-loss is below a recent significant swing low. Alternatively, you could place it just below one of the key moving averages, such as the 20-period or 50-period SMA, as a break below these would invalidate the immediate trend.
For Bearish Trades (Short): Place a stop-loss above a recent significant swing high or just above the 20 or 50-period SMA.
Profit Targets:
Risk/Reward Ratio: A simple approach is to set a profit target that is a multiple of your risk (e.g., 1.5x, 2x, or 3x the distance from your entry to your stop-loss).
Support & Resistance: Target previous, significant support (for short trades) or resistance (for long trades) levels on the chart.
Trailing Stop: For capturing longer trends, you can trail your stop-loss. For example, in a long trade, you could manually move your stop-loss up to just below the 20-period SMA as the price continues to rise. You would exit the trade only when the price closes below it.
Disclaimer: This indicator is a tool for analysis, not a trading system that guarantees profit. All trading involves significant risk. Always backtest any strategy and use proper risk management before trading with real capital.
#TradingView #PineScript #TechnicalAnalysis #TradingStrategy #TrendFollowing #MovingAverage #SMA #RSI #VolumeAnalysis #Momentum #TradingSignals #DayTrading #SwingTrading #StockMarket #Crypto
Market to NAV Premium Arbitrage Alpha IndicatorMARKET TO NAV PREMIUM ARBITRAGE ALPHA INDICATOR
A quantitative tool for identifying statistical mispricings between market capitalization and net asset value (NAV), designed specifically for arbitrage strategies and alpha generation in Bitcoin-holding companies like MicroStrategy (MSTR), companies or SPACS used mostly to hold crypto, Bitcoin ETFs, and other NAV-based instruments. Can probably be also used in certain spin-offs.
📊 KEY FEATURES:
✅ Real-time Premium/Discount Calculation
• Automatically retrieves market cap data from TradingView
• Calculates precise NAV based on underlying asset holdings
• Formula: (Market Cap - NAV) / NAV × 100
✅ Statistical Analysis Framework
• Historical percentile rankings (customizable lookback period)
• Standard deviation bands (2σ) for extreme value detection
• Smoothing options to reduce noise
✅ Multi-Source Market Cap Detection
• Priority system: TradingView data → Calculated → Manual override
• Automatic fallback mechanisms for data reliability
✅ Advanced NAV Modeling
• Basic NAV: Asset holdings + cash
• Adjusted NAV: Includes software business value, debt, preferred shares. If the company has a lot of this kind of intrinsic value, put it in the "cash" field
• Support for any underlying asset (BTC, ETH, etc.)
📈 TRADING APPLICATIONS:
🎯 Pairs Trading Signals
• Long/Short opportunities when premium reaches statistical extremes
• Mean reversion strategies based on historical ranges
• Risk-adjusted position sizing using percentile ranks
🎯 Arbitrage Detection
• Identifies when market pricing significantly deviates from fair value
• Quantifies the magnitude of mispricing for profit potential
• Historical context for timing entry/exit points
🔧 CONFIGURATION OPTIONS:
• Underlying Asset: Any symbol (default: COINBASE:BTCUSD) NEED MANUAL INPUT
• Asset Quantity: Precise holdings amount. NEED MANUAL INPUT
• Cash Holdings: Additional liquid assets. NEED MANUAL INPUT
• Market Cap Mode: Auto-detect, calculated, or manual
• Advanced Adjustments: Business value, debt, preferred shares
• Display Settings: Lookback period, smoothing, custom colors
🎯 PERFECT FOR:
• Quantitative traders focused on statistical arbitrage
• Institutional investors monitoring NAV-based instruments
• Bitcoin ETF and MSTR traders seeking alpha generation
• Risk managers tracking premium/discount exposures
• Academic researchers studying market efficiency (as you can see, markets are not efficient 😉)
🔗 CONNECT & SUPPORT:
Follow for updates and additional quantitative trading tools. Feedback and suggestions welcome!
AV BTC Pi Cycle OscillatorPi Cycle Oscillator
The oscillator version of the Pi Cycle Top Indicator. While I have found great differences in scales being used for the oscillator across various sources. The shape of the oscillator line is on the other hand the same across the board. With 2 specific versions. Either using the 111 Day SMA or the 2*350 SMA for division.
We allow for both versions. It is possible to select the formula for calculation on the input tab.
Either using (111 SMA - 2*350 SMA) / 111 SMA (default) or (111 SMA - 2*350 SMA) / 2*350 SMA .
We multiply the result by -100 so that overbought conditions fall at the top of the indicator chart and oversold at the bottom. Everyone has their own idea of the value range. This is no different.
For both formulas around 0 is overbought zone, while -200 and -70 are oversold areas. Thresholds are configurable in the input tab. I made an arbitrary choice for the thresholds.
If you want to see overbought and oversold areas on the price chart: Enable the Overbought and oversold Overlay area in the style tab. It is disabled by default.
Additionally: Pi Cycle Tops are marked with a red circle. ATH tops are marked with yellow diamonds. Grey lines marks halving days.
HIFI BTC Daily Hashrate Momentum OscillatorThe "HIFI BTC Daily Hashrate Momentum Oscillator" indicator is an oscillator that analyzes the "health" and confidence of miners in the Bitcoin network. It measures the momentum of hashrate changes using its deviation from the 30-day and 60-day moving averages. A rising hashrate is often a leading or confirming bullish trend indicator for the price of BTC.
Main Idea
Hashrate is the total computing power involved in mining. Its growth indicates increased investment in network security and miners' confidence in future profitability.
Blue Oscillator (fast): Shows the short-term dynamics of hashrate growth.
Green Oscillator (slow): Indicates the long-term trend of hash rate changes.
Chart background: The green background signals the acceleration of the hash rate growth (short-term momentum is higher than long-term), which is a positive sign.
How to Read Signals
A Buy signal appears when two fundamental conditions coincide:
Growth acceleration: The short-term hashrate momentum becomes stronger than the long-term one (the blue line crosses the green one from bottom to top). This indicates that miners are actively building capacity.
Exit from stagnation: This acceleration occurs after a period of weak hashrate growth or decline (the green line is below the red dashed line).
This combination indicates the potential start of a new cycle of growth and confidence in the network, which historically has often preceded the rise in the price of Bitcoin itself.
Disclamer: This indicator is an analysis tool and should not be considered as a direct financial recommendation. Always do your own analysis before making trades.
BTC/USD Auto S/R LevelsRelease Notes
Take your Bitcoin (BTCUSD) trading to the next level with this smart and accurate Support-Resistance indicator, designed specifically for intraday and swing traders who value clarity, precision, and speed in their decision-making.
🔍 What This Indicator Does:
✅ Automatically detects dynamic Support & Resistance levels using advanced logic tailored for BTCUSD price behavior
✅ Adapts in real time as new highs/lows are formed—no need to redraw or guess key zones
✅ Filters out noise and focuses on true, price-respected zones, improving your trade timing
✅ Works seamlessly on multiple timeframes—whether you trade the 5min for scalps or higher TFs for swing entries
🚀 Why Traders Love It:
No more guesswork—clean, minimal, and to-the-point levels
Great confluence with price action, VWAP, and volume-based strategies
Can be used for breakout trades, rejections, reversals, or even building option strategies
Zero repaint – Levels stay consistent, even after the candle closes
🔧 Built for:
Intraday Traders
BTCUSD Option Buyers & Sellers
Price Action Purists
Smart Money Concept (SMC) Followers
Anyone who wants to trade BTCUSD with clarity
💡 Pro Tip: Combine this with a momentum indicator or VWAP to build high-conviction trades with minimal noise.
AV BTC Pi Cycle Top (with ATH) OverlayPi Cycle Top Indicator
Created by Phillip Swift . It works by comparing the 111-day SMA (blue) and the 350-day SMA. The value of the 350-day SMA is multiplied by 2 and referred to as 2*350 SMA (purple). Note: The number of days is not multiplied; the 350-day SMA is not doubled to calculate a 700-day SMA.
These two moving averages were selected because 350 / 111 ≈ 3.153, an approximation of the number Pi.
When the 111-day SMA (blue) crosses over the 2*350 SMA (purple), it signals a market cycle peak. Historically, this has worked extremely well. However, with the growth of BTC Futures and ETFs, this indicator might lose its edge.
A label and a red circle signal crossover. The indicator also marks all ATH (All-Time High) bars with yellow diamonds. The ATH line is hidden by default but can be enabled in the style tab. Additionally, halving days are marked with grey vertical lines and labels. Feel free to hide certain elements in the style tab.
For marking overbought and oversold areas, I believe looking at the Pi Cycle Oscillator is a better choice. For this reason, this indicator does not highlight overbought or oversold areas; it only marks market tops.
AV BTC Top Cap ModelThe Bitcoin Top Cap
Developed by Willy Woo to identify market cycle tops. Top Cap is calculated by multiplying the Average Cap by 35. Average cap is calculated by taking the cumulative sum of daily market cap divided by the age of market in days. Additional Top Cap using 15x multiplier is included to show sensitivity and to gauge the effect of diminishing returns.
For the use on BTC Market Cap Chart : No changes necessary. Switching to logarithmic scale in recommended.
For the use on BTC Price Chart : After adding the indicator, enable Convert to price setting.
Customization of multipliers is enabled in the settings.
Data sources used: GLASSNODE:BTC_MARKETCAP and GLASSNODE:BTC_SUPPLY (for price conversion)
Note: Use with caution. I coded this for learning. This model might be past it's usefulness date. I am also seeing single digit % difference between this indicator values and top cap indicators available online.
AV BTC Investor ToolThe Investor Tool
Created by Philip Swift . Intended to be used by long term investors . The tool uses two simple moving averages of price as the basis for under/overvalued conditions: the 2-year MA (green) and a 5x multiple of the 2-year MA (red).
Price below the 2-year average: often means good profits and a bear market bottom .
Price above the 5x average: usually shows a bull market top , so investors may want to be cautious.
BTCUSD 5m Aggressive Buy/Sell Signals v2 with AlertsThis indicator highlights potential buy and sell opportunities on the BTCUSD 5-minute chart. It plots visual signals on the chart and includes optional TradingView alerts for fast notifications.
Key features:
- Aggressive scalp-style signals
- 5-minute timeframe focus
- Simple and clean logic with clear markers
- Integrated alerts for buy and sell triggers
⚠️ Disclaimer: This script is for educational and informational purposes only. It is not financial advice. Use at your own risk and always manage your positions responsibly.
AlgoChadLin's BITCOIN H1 Breakout Strategy No.545Strategy Overview
AlgoChadLin's BITCOIN H1 Breakout Strategy No.545 is a sophisticated breakout trading system designed for Bitcoin on the H1 timeframe. It integrates multiple volatility and price action indicators to identify high-probability breakout opportunities, aiming to capitalize on significant market movements.
Auther: @algochadlin
Strategy Logic
Breakout Confirmation: Utilizes a combination of Average True Range (ATR) and Bollinger Bands to identify periods of low volatility followed by sharp price movements.
Long: Initiated when the price breaks above the previous hour's upper Bollinger Band, with ATR confirming increased volatility.
Short: Triggered when the price breaks below the previous hour's lower Bollinger Band, with ATR indicating heightened volatility.
Parameters
Price Entry Multiplier: Adjusts the entry price relative to the breakout level.
Exit After Bars: Specifies the number of bars to hold the position before exiting.
Profit Target (%): Defines the percentage gain at which to take profit.
Stop Loss Coefficient: Multiplier for ATR to calculate stop-loss distance.
Trailing Stop Coefficients: Defines the trailing stop parameters.
Biggest Range Period: Determines the lookback period for identifying the largest price range.
Setup
Timeframe: 1-Hour (H1)
Asset: Bitcoin, also suitable for ETH
Wavelet-Trend ML Integration [Alpha Extract]Alpha-Extract Volatility Quality Indicator
The Alpha-Extract Volatility Quality (AVQ) Indicator provides traders with deep insights into market volatility by measuring the directional strength of price movements. This sophisticated momentum-based tool helps identify overbought and oversold conditions, offering actionable buy and sell signals based on volatility trends and standard deviation bands.
🔶 CALCULATION
The indicator processes volatility quality data through a series of analytical steps:
Bar Range Calculation: Measures true range (TR) to capture price volatility.
Directional Weighting: Applies directional bias (positive for bullish candles, negative for bearish) to the true range.
VQI Computation: Uses an exponential moving average (EMA) of weighted volatility to derive the Volatility Quality Index (VQI).
Smoothing: Applies an additional EMA to smooth the VQI for clearer signals.
Normalization: Optionally normalizes VQI to a -100/+100 scale based on historical highs and lows.
Standard Deviation Bands: Calculates three upper and lower bands using standard deviation multipliers for volatility thresholds.
Signal Generation: Produces overbought/oversold signals when VQI reaches extreme levels (±200 in normalized mode).
Formula:
Bar Range = True Range (TR)
Weighted Volatility = Bar Range × (Close > Open ? 1 : Close < Open ? -1 : 0)
VQI Raw = EMA(Weighted Volatility, VQI Length)
VQI Smoothed = EMA(VQI Raw, Smoothing Length)
VQI Normalized = ((VQI Smoothed - Lowest VQI) / (Highest VQI - Lowest VQI) - 0.5) × 200
Upper Band N = VQI Smoothed + (StdDev(VQI Smoothed, VQI Length) × Multiplier N)
Lower Band N = VQI Smoothed - (StdDev(VQI Smoothed, VQI Length) × Multiplier N)
🔶 DETAILS
Visual Features:
VQI Plot: Displays VQI as a line or histogram (lime for positive, red for negative).
Standard Deviation Bands: Plots three upper and lower bands (teal for upper, grayscale for lower) to indicate volatility thresholds.
Reference Levels: Horizontal lines at 0 (neutral), +100, and -100 (in normalized mode) for context.
Zone Highlighting: Overbought (⋎ above bars) and oversold (⋏ below bars) signals for extreme VQI levels (±200 in normalized mode).
Candle Coloring: Optional candle overlay colored by VQI direction (lime for positive, red for negative).
Interpretation:
VQI ≥ 200 (Normalized): Overbought condition, strong sell signal.
VQI 100–200: High volatility, potential selling opportunity.
VQI 0–100: Neutral bullish momentum.
VQI 0 to -100: Neutral bearish momentum.
VQI -100 to -200: High volatility, strong bearish momentum.
VQI ≤ -200 (Normalized): Oversold condition, strong buy signal.
🔶 EXAMPLES
Overbought Signal Detection: When VQI exceeds 200 (normalized), the indicator flags potential market tops with a red ⋎ symbol.
Example: During strong uptrends, VQI reaching 200 has historically preceded corrections, allowing traders to secure profits.
Oversold Signal Detection: When VQI falls below -200 (normalized), a lime ⋏ symbol highlights potential buying opportunities.
Example: In bearish markets, VQI dropping below -200 has marked reversal points for profitable long entries.
Volatility Trend Tracking: The VQI plot and bands help traders visualize shifts in market momentum.
Example: A rising VQI crossing above zero with widening bands indicates strengthening bullish momentum, guiding traders to hold or enter long positions.
Dynamic Support/Resistance: Standard deviation bands act as dynamic volatility thresholds during price movements.
Example: Price reversals often occur near the third standard deviation bands, providing reliable entry/exit points during volatile periods.
🔶 SETTINGS
Customization Options:
VQI Length: Adjust the EMA period for VQI calculation (default: 14, range: 1–50).
Smoothing Length: Set the EMA period for smoothing (default: 5, range: 1–50).
Standard Deviation Multipliers: Customize multipliers for bands (defaults: 1.0, 2.0, 3.0).
Normalization: Toggle normalization to -100/+100 scale and adjust lookback period (default: 200, min: 50).
Display Style: Switch between line or histogram plot for VQI.
Candle Overlay: Enable/disable VQI-colored candles (lime for positive, red for negative).
The Alpha-Extract Volatility Quality Indicator empowers traders with a robust tool to navigate market volatility. By combining directional price range analysis with smoothed volatility metrics, it identifies overbought and oversold conditions, offering clear buy and sell signals. The customizable standard deviation bands and optional normalization provide precise context for market conditions, enabling traders to make informed decisions across various market cycles.
Bitcoin Power Law Clock [LuxAlgo]The Bitcoin Power Law Clock is a unique representation of Bitcoin prices proposed by famous Bitcoin analyst and modeler Giovanni Santostasi.
It displays a clock-like figure with the Bitcoin price and average lines as spirals, as well as the 12, 3, 6, and 9 hour marks as key points in the cycle.
🔶 USAGE
Giovanni Santostasi, Ph.D., is the creator and discoverer of the Bitcoin Power Law Theory. He is passionate about Bitcoin and has 12 years of experience analyzing it and creating price models.
As we can see in the above chart, the tool is super intuitive. It displays a clock-like figure with the current Bitcoin price at 10:20 on a 12-hour scale.
This tool only works on the 1D INDEX:BTCUSD chart. The ticker and timeframe must be exact to ensure proper functionality.
According to the Bitcoin Power Law Theory, the key cycle points are marked at the extremes of the clock: 12, 3, 6, and 9 hours. According to the theory, the current Bitcoin prices are in a frenzied bull market on their way to the top of the cycle.
🔹 Enable/Disable Elements
All of the elements on the clock can be disabled. If you disable them all, only an empty space will remain.
The different charts above show various combinations. Traders can customize the tool to their needs.
🔹 Auto scale
The clock has an auto-scale feature that is enabled by default. Traders can adjust the size of the clock by disabling this feature and setting the size in the settings panel.
The image above shows different configurations of this feature.
🔶 SETTINGS
🔹 Price
Price: Enable/disable price spiral, select color, and enable/disable curved mode
Average: Enable/disable average spiral, select color, and enable/disable curved mode
🔹 Style
Auto scale: Enable/disable automatic scaling or set manual fixed scaling for the spirals
Lines width: Width of each spiral line
Text Size: Select text size for date tags and price scales
Prices: Enable/disable price scales on the x-axis
Handle: Enable/disable clock handle
Halvings: Enable/disable Halvings
Hours: Enable/disable hours and key cycle points
🔹 Time & Price Dashboard
Show Time & Price: Enable/disable time & price dashboard
Location: Dashboard location
Size: Dashboard size
Bitcoin Power Law [LuxAlgo]The Bitcoin Power Law tool is a representation of Bitcoin prices first proposed by Giovanni Santostasi, Ph.D. It plots BTCUSD daily closes on a log10-log10 scale, and fits a linear regression channel to the data.
This channel helps traders visualise when the price is historically in a zone prone to tops or located within a discounted zone subject to future growth.
🔶 USAGE
Giovanni Santostasi, Ph.D. originated the Bitcoin Power-Law Theory; this implementation places it directly on a TradingView chart. The white line shows the daily closing price, while the cyan line is the best-fit regression.
A channel is constructed from the linear fit root mean squared error (RMSE), we can observe how price has repeatedly oscillated between each channel areas through every bull-bear cycle.
Excursions into the upper channel area can be followed by price surges and finishing on a top, whereas price touching the lower channel area coincides with a cycle low.
Users can change the channel areas multipliers, helping capture moves more precisely depending on the intended usage.
This tool only works on the daily BTCUSD chart. Ticker and timeframe must match exactly for the calculations to remain valid.
🔹 Linear Scale
Users can toggle on a linear scale for the time axis, in order to obtain a higher resolution of the price, (this will affect the linear regression channel fit, making it look poorer).
🔶 DETAILS
One of the advantages of the Power Law Theory proposed by Giovanni Santostasi is its ability to explain multiple behaviors of Bitcoin. We describe some key points below.
🔹 Power-Law Overview
A power law has the form y = A·xⁿ , and Bitcoin’s key variables follow this pattern across many orders of magnitude. Empirically, price rises roughly with t⁶, hash-rate with t¹² and the number of active addresses with t³.
When we plot these on log-log axes they appear as straight lines, revealing a scale-invariant system whose behaviour repeats proportionally as it grows.
🔹 Feedback-Loop Dynamics
Growth begins with new users, whose presence pushes the price higher via a Metcalfe-style square-law. A richer price pool funds more mining hardware; the Difficulty Adjustment immediately raises the hash-rate requirement, keeping profit margins razor-thin.
A higher hash rate secures the network, which in turn attracts the next wave of users. Because risk and Difficulty act as braking forces, user adoption advances as a power of three in time rather than an unchecked S-curve. This circular causality repeats without end, producing the familiar boom-and-bust cadence around the long-term power-law channel.
🔹 Scale Invariance & Predictions
Scale invariance means that enlarging the timeline in log-log space leaves the trajectory unchanged.
The same geometric proportions that described the first dollar of value can therefore extend to a projected million-dollar bitcoin, provided no catastrophic break occurs. Institutional ETF inflows supply fresh capital but do not bend the underlying slope; only a persistent deviation from the line would falsify the current model.
🔹 Implications
The theory assigns scarcity no direct role; iterative feedback and the Difficulty Adjustment are sufficient to govern Bitcoin’s expansion. Long-term valuation should focus on position within the power-law channel, while bubbles—sharp departures above trend that later revert—are expected punctuations of an otherwise steady climb.
Beyond about 2040, disruptive technological shifts could alter the parameters, but for the next order of magnitude the present slope remains the simplest, most robust guide.
Bitcoin behaves less like a traditional asset and more like a self-organising digital organism whose value, security, and adoption co-evolve according to immutable power-law rules.
🔶 SETTINGS
🔹 General
Start Calculation: Determine the start date used by the calculation, with any prior prices being ignored. (default - 15 Jul 2010)
Use Linear Scale for X-Axis: Convert the horizontal axis from log(time) to linear calendar time
🔹 Linear Regression
Show Regression Line: Enable/disable the central power-law trend line
Regression Line Color: Choose the colour of the regression line
Mult 1: Toggle line & fill, set multiplier (default +1), pick line colour and area fill colour
Mult 2: Toggle line & fill, set multiplier (default +0.5), pick line colour and area fill colour
Mult 3: Toggle line & fill, set multiplier (default -0.5), pick line colour and area fill colour
Mult 4: Toggle line & fill, set multiplier (default -1), pick line colour and area fill colour
🔹 Style
Price Line Color: Select the colour of the BTC price plot
Auto Color: Automatically choose the best contrast colour for the price line
Price Line Width: Set the thickness of the price line (1 – 5 px)
Show Halvings: Enable/disable dotted vertical lines at each Bitcoin halving
Halvings Color: Choose the colour of the halving lines
CHN BUY SELL with EMA 200Overview
This indicator combines RSI 7 momentum signals with EMA 200 trend filtering to generate high-probability BUY and SELL entry points. It uses colored candles to highlight key market conditions and displays clear trading signals with built-in cooldown periods to prevent signal spam.
Key Features
Colored Candles: Visual momentum indicators based on RSI 7 levels
Trend Filtering: EMA 200 confirms overall market direction
Signal Cooldown: Prevents over-trading with adjustable waiting periods
Clean Interface: Simple BUY/SELL labels without clutter
How It Works
Candle Coloring System
Yellow Candles: Appear when RSI 7 ≥ 70 (overbought momentum)
Purple Candles: Appear when RSI 7 ≤ 30 (oversold momentum)
Normal Candles: All other market conditions
Trading Signals
BUY Signal: Triggered when closing price > EMA 200 AND yellow candle appears
SELL Signal: Triggered when closing price < EMA 200 AND purple candle appears
Signal Cooldown
After a BUY or SELL signal appears, the same signal type is suppressed for a specified number of candles (default: 5) to prevent excessive signals in ranging markets.
Settings
RSI 7 Length: Period for RSI calculation (default: 7)
RSI 7 Overbought: Threshold for yellow candles (default: 70)
RSI 7 Oversold: Threshold for purple candles (default: 30)
EMA Length: Period for trend filter (default: 200)
Signal Cooldown: Candles to wait between same signal type (default: 5)
How to Use
Apply the indicator to your chart
Look for yellow or purple colored candles
For LONG entries: Wait for yellow candle above EMA 200, then enter BUY when signal appears
For SHORT entries: Wait for purple candle below EMA 200, then enter SELL when signal appears
Use appropriate risk management and position sizing
Best Practices
Works best on timeframes M15 and higher
Suitable for Forex, Gold, Crypto, and Stock markets
Consider market volatility when setting stop-loss and take-profit levels
Use in conjunction with proper risk management strategies
Technical Details
Overlay: True (plots directly on price chart)
Calculation: Based on RSI momentum and EMA trend analysis
Signal Logic: Combines momentum exhaustion with trend direction
Visual Feedback: Colored candles provide immediate market condition awareness
SectorRotationRadarThe Sector Rotation Radar is a powerful visual analysis tool designed to track the relative strength and momentum of a stock compared to a benchmark index and its associated sector ETF. It helps traders and investors identify where an asset stands within the broader market cycle and spot rotation patterns across sectors and timeframes.
🔧 Key Features:
Benchmark Comparison: Measures the relative performance (strength and momentum) of the current symbol against a chosen benchmark (default: SPX), highlighting over- or underperformance.
Automatic Sector Detection: Automatically links stocks to their relevant sector ETFs (e.g., XLK, XLF, XLU), based on an extensive internal symbol map.
Multi-Timeframe Analysis: Supports simultaneous comparison across the current, next, and even third-higher timeframes (e.g., Daily → Weekly → Monthly), providing a bigger-picture perspective of trend shifts.
Tail Visualization: Displays a "trail" of price behavior over time, visualizing how the asset has moved in terms of relative strength and momentum across a user-defined period.
Quadrant-Based Layout: The chart is divided into four dynamic main zones, each representing a phase in the strength/momentum cycle:
🔄 Improving: Gaining strength and momentum
🚀 Leading: High strength and high momentum — top performers
💤 Weakening: Losing momentum while still strong
🐢 Lagging: Low strength and low momentum — underperformers
Clean Chart Visualization:
Background grid with axis labels
Dynamic tails and data points for each symbol
Option to include the associated sector ETF for context
Descriptive labels showing exact strength/momentum values per point
⚙️ Customization Options:
Benchmark Selector: Choose any symbol to compare against (e.g., SPX, Nasdaq, custom index)
Start Date Control: Option to fix a historical start point or use the current data range
Trail Length: Set the number of previous data points to display
Additional Timeframes: Enable analysis of one or two higher timeframes beyond the current
Sector ETF Display: Toggle to show or hide the related sector ETF alongside the asset
📚 Technical Architecture:
The indicator relies on external modules for:
Statistical modeling
Relative strength and momentum calculations
Chart rendering and label drawing
These components work together to compute and display a dynamic, real-time map of asset performance over time.
🧠 Use Case:
Sector Rotation Radar is ideal for traders looking to:
Spot stocks or sectors rotating into strength or weakness
Confirm alignment across multiple timeframes
Identify sector leaders and laggards
Understand how a symbol is positioned relative to the broader market and its peers
This tool is especially valuable for swing traders, sector rotation strategies, and macro-aware investors who want a visual edge in decision-making.
SuperSmoothed Volume Zone Oscillator------------------------------------------------------------------------------------
SUPERSMOOTHED VOLUME ZONE OSCILLATOR (SSVZO)
TECHNICAL INDICATOR DOCUMENTATION
------------------------------------------------------------------------------------
Table of Contents:
1. Original VZO Background
2. SuperSmoother Technology
3. SSVZO Components
3.1. Main SSVZO Oscillator
3.2. Momentum Velocity Component
3.3. Adaptive Levels
3.4. Static Levels
3.5. Trend Shift Detection
3.6. Glow Effect Visualization
4. References & Further Reading
------------------------------------------------------------------------------------
1. ORIGINAL VOLUME ZONE OSCILLATOR (VZO) BACKGROUND
------------------------------------------------------------------------------------
Creator: Walid Khalil (November 2009, Technical Analysis of Stocks & Commodities)
History: Khalil designed the VZO to address limitations in other volume indicators
by focusing on the relative balance between buying and selling volume while filtering
out market noise. The indicator identifies accumulation and distribution patterns.
Traditional Usage: The classic VZO uses a 14-period calculation setting and is
interpreted on a scale from -60% to +60%:
- Readings above +40% indicate strong buying pressure (potential overbought)
- Readings below -40% indicate strong selling pressure (potential oversold)
- The zero line acts as a key reference for trend changes
- Divergences between VZO and price offer valuable trading signals
Difference from Other Volume Indicators: Unlike simple volume indicators that only
track total volume, the VZO tracks the relative difference between up-volume and
down-volume, more effectively identifying buying/selling pressure imbalances and
potential reversal points.
------------------------------------------------------------------------------------
2. SUPERSMOOTHER FILTER TECHNOLOGY
------------------------------------------------------------------------------------
Creator: John F. Ehlers, an engineer specializing in digital signal processing for
trading systems.
Origins: Introduced in "Rocket Science for Traders" (2001) and refined in "Cybernetic
Analysis for Stocks and Futures" (2004). Represents the application of digital signal
processing techniques to financial markets.
Technical Foundation: The SuperSmoother is a two-pole low-pass filter specifically
designed to eliminate noise while preserving the underlying signal. It combines
principles of Butterworth and Gaussian filters to minimize both phase shift and
passband ripple.
Mathematical Implementation:
a1 = exp(-π * sqrt(2) / period)
b1 = 2 * a1 * cos(sqrt(2) * π / period)
c2 = b1
c3 = -a1²
c1 = 1 - c2 - c3
Advantages Over Traditional Filters:
- Reduces lag compared to simple moving averages
- Eliminates high-frequency market noise more effectively
- Minimizes unwanted ripples in the output signal
- Preserves important turning points in the data
- Superior handling of sudden market movements
According to Ehlers: "Conventional moving averages are plagued by excessive lag and/or
rippling in their passband. The SuperSmoother eliminates virtually all of this ripple
and has excellent transient response characteristics." (TASC Magazine, 2014)
------------------------------------------------------------------------------------
3. SSVZO COMPONENTS
------------------------------------------------------------------------------------
3.1. MAIN SSVZO OSCILLATOR
------------------------------------------------------------------------------------
Description: The core component measuring buying vs. selling volume pressure using
the SuperSmoother filter for enhanced noise reduction.
Calculation: SSVZO analyzes the relationship between up-volume (volume on rising
prices) and down-volume (volume on falling prices), applying exponential moving
averages to both components, then calculating their relative strength. The
SuperSmoother filter reduces market noise while preserving the underlying trend signal.
Implementation Advantage: By applying the SuperSmoother filter to the VZO calculation,
the SSVZO provides significantly cleaner signals with fewer false crossovers and more
accurate identification of true trend changes.
Interpretation:
- Values above zero indicate bullish volume dominance
- Values below zero indicate bearish volume dominance
- Readings above +60 suggest overbought conditions
- Readings below -60 suggest oversold conditions
- Crossovers of the zero line signal potential trend changes
Trading Application: Use SSVZO as a primary volume-based momentum indicator to
confirm price trends, identify divergences, and spot potential reversal zones.
------------------------------------------------------------------------------------
3.2. MOMENTUM VELOCITY COMPONENT
------------------------------------------------------------------------------------
Description: A histogram displaying the rate of change of momentum, showing how
quickly buying or selling pressure is accelerating or decelerating.
Calculation: Derived from price momentum over a user-defined period, with optional
adaptive filtering that adjusts sensitivity based on market volatility. The velocity
component shows the first derivative of momentum – essentially the "acceleration" of
market movement.
Technical Origin: Inspired by Ehlers' work on Hilbert Transforms and research on
cyclic components in financial markets, as detailed in "Cycle Analytics for Traders"
(2013).
Interpretation:
- Positive readings (teal bars) indicate accelerating upward momentum
- Negative readings (orange bars) suggest accelerating downward momentum
- Larger bars indicate stronger momentum acceleration
- Shrinking bars signal momentum deceleration
Trading Application: Use as an early warning system for potential trend exhaustion
or confirmation of a new trending move. When momentum velocity diverges from price,
it often precedes a reversal.
------------------------------------------------------------------------------------
3.3. ADAPTIVE LEVELS
------------------------------------------------------------------------------------
Description: Dynamic overbought and oversold boundaries that adjust to market
conditions, providing context-aware trading signals.
Calculation: Uses statistical methods based on the standard deviation of the SSVZO
values over a longer period. These levels automatically widen during higher volatility
periods and narrow during consolidation.
Research Base: Draws from Perry Kaufman's work on Adaptive Moving Averages (AMA) and
Bollinger's research on dynamic volatility bands, as published in "Trading Systems
and Methods" (2013).
Interpretation:
- Adaptive Overbought (dotted circles above): Dynamic ceiling that expands/contracts
based on market volatility
- Adaptive Oversold (dotted circles below): Dynamic floor that expands/contracts based
on market volatility
Trading Application: More reliable for identifying extremes than static levels,
particularly in changing market conditions or different instruments. Touching these
levels often provides higher-probability reversal signals.
------------------------------------------------------------------------------------
3.4. STATIC LEVELS
------------------------------------------------------------------------------------
Description: Fixed overbought and oversold horizontal lines that provide consistent
reference points for excess market conditions.
Calculation: Preset at +60 (overbought) and -60 (oversold) based on historical
analysis of volume behavior across multiple markets, extending the classic VZO range.
Interpretation:
- Readings above +60 suggest potential buying exhaustion
- Readings below -60 indicate potential selling exhaustion
- Duration spent beyond these levels correlates with reversal probability
Trading Application: Use as baseline reference points for extreme conditions. Most
effective when combined with other confirmation signals like divergences or
candlestick patterns.
------------------------------------------------------------------------------------
3.5. TREND SHIFT DETECTION
------------------------------------------------------------------------------------
Description: Visual markers and optional background shading highlighting potential
trend changes when the SSVZO crosses the zero line.
Calculation: Based on mathematical crossovers of the SSVZO value above or below the
zero line, with pattern recognition to reduce false signals.
Research Foundation: Incorporates concepts from Dr. Alexander Elder's "triple screen
trading system" and Mark Chaikin's volume-based trend identification research.
Interpretation:
- Upward triangles indicate bullish trend shifts (SSVZO crossing above zero)
- Downward triangles indicate bearish trend shifts (SSVZO crossing below zero)
- Background shading emphasizes the new trend direction
Trading Application: These signals often precede price trend changes and can serve
as entry triggers when aligned with the higher timeframe trend.
------------------------------------------------------------------------------------
3.6. GLOW EFFECT VISUALIZATION
------------------------------------------------------------------------------------
Description: An aesthetic enhancement creating a gradient "glow" around the main SSVZO
line, improving visual clarity and emphasizing signal strength.
Calculation: Generated using percentage-based bands around the main SSVZO value, with
multiple translucent layers to create a subtle illumination effect.
Design Inspiration: Inspired by modern UI/UX design principles for financial
dashboards and the MATS (Moving Average Trend Sniper) indicator's visual presentation,
enhancing perception of signal strength through visual intensity.
Interpretation:
- Teal glow indicates positive SSVZO values (bullish)
- Orange glow indicates negative SSVZO values (bearish)
- Glow intensity correlates with the strength of the signal
Trading Application: Beyond aesthetics, the glow creates visual emphasis that makes
trend direction, strength, and changes more immediately apparent, particularly useful
during fast-moving market conditions.
------------------------------------------------------------------------------------
4. REFERENCES & FURTHER READING
------------------------------------------------------------------------------------
1. Ehlers, J. F. (2001). "Rocket Science for Traders: Digital Signal Processing
Applications." John Wiley & Sons.
2. Ehlers, J. F. (2004). "Cybernetic Analysis for Stocks and Futures: Cutting-Edge
DSP Technology to Improve Your Trading." John Wiley & Sons.
3. Ehlers, J. F. (2013). "Cycle Analytics for Traders: Advanced Technical Trading
Concepts." John Wiley & Sons.
4. Khalil, W. (2009). "The Volume Zone Oscillator." Technical Analysis of Stocks &
Commodities, November 2009.
5. Kaufman, P. J. (2013). "Trading Systems and Methods." 5th Edition, Wiley Trading.
6. Elder, A. (2002). "Come Into My Trading Room: A Complete Guide to Trading."
John Wiley & Sons.
7. Bollinger, J. (2002). "Bollinger on Bollinger Bands." McGraw-Hill Education.
------------------------------------------------------------------------------------
END OF DOCUMENTATION
------------------------------------------------------------------------------------
Bitcoin Power Law OscillatorThis is the oscillator version of the script. The main body of the script can be found here.
Understanding the Bitcoin Power Law Model
Also called the Long-Term Bitcoin Power Law Model. The Bitcoin Power Law model tries to capture and predict Bitcoin's price growth over time. It assumes that Bitcoin's price follows an exponential growth pattern, where the price increases over time according to a mathematical relationship.
By fitting a power law to historical data, the model creates a trend line that represents this growth. It then generates additional parallel lines (support and resistance lines) to show potential price boundaries, helping to visualize where Bitcoin’s price could move within certain ranges.
In simple terms, the model helps us understand Bitcoin's general growth trajectory and provides a framework to visualize how its price could behave over the long term.
The Bitcoin Power Law has the following function:
Power Law = 10^(a + b * log10(d))
Consisting of the following parameters:
a: Power Law Intercept (default: -17.668).
b: Power Law Slope (default: 5.926).
d: Number of days since a reference point(calculated by counting bars from the reference point with an offset).
Explanation of the a and b parameters:
Roughly explained, the optimal values for the a and b parameters are determined through a process of linear regression on a log-log scale (after applying a logarithmic transformation to both the x and y axes). On this log-log scale, the power law relationship becomes linear, making it possible to apply linear regression. The best fit for the regression is then evaluated using metrics like the R-squared value, residual error analysis, and visual inspection. This process can be quite complex and is beyond the scope of this post.
Applying vertical shifts to generate the other lines:
Once the initial power-law is created, additional lines are generated by applying a vertical shift. This shift is achieved by adding a specific number of days (or years in case of this script) to the d-parameter. This creates new lines perfectly parallel to the initial power law with an added vertical shift, maintaining the same slope and intercept.
In the case of this script, shifts are made by adding +365 days, +2 * 365 days, +3 * 365 days, +4 * 365 days, and +5 * 365 days, effectively introducing one to five years of shifts. This results in a total of six Power Law lines, as outlined below (From lowest to highest):
Base Power Law Line (no shift)
1-year shifted line
2-year shifted line
3-year shifted line
4-year shifted line
5-year shifted line
The six power law lines:
Bitcoin Power Law Oscillator
This publication also includes the oscillator version of the Bitcoin Power Law. This version applies a logarithmic transformation to the price, Base Power Law Line, and 5-year shifted line using the formula: log10(x) .
The log-transformed price is then normalized using min-max normalization relative to the log-transformed Base Power Law Line and 5-year shifted line with the formula:
normalized price = log(close) - log(Base Power Law Line) / log(5-year shifted line) - log(Base Power Law Line)
Finally, the normalized price was multiplied by 5 to map its value between 0 and 5, aligning with the shifted lines.
Interpretation of the Bitcoin Power Law Model:
The shifted Power Law lines provide a framework for predicting Bitcoin's future price movements based on historical trends. These lines are created by applying a vertical shift to the initial Power Law line, with each shifted line representing a future time frame (e.g., 1 year, 2 years, 3 years, etc.).
By analyzing these shifted lines, users can make predictions about minimum price levels at specific future dates. For example, the 5-year shifted line will act as the main support level for Bitcoin’s price in 5 years, meaning that Bitcoin’s price should not fall below this line, ensuring that Bitcoin will be valued at least at this level by that time. Similarly, the 2-year shifted line will serve as the support line for Bitcoin's price in 2 years, establishing that the price should not drop below this line within that time frame.
On the other hand, the 5-year shifted line also functions as an absolute resistance , meaning Bitcoin's price will not exceed this line prior to the 5-year mark. This provides a prediction that Bitcoin cannot reach certain price levels before a specific date. For example, the price of Bitcoin is unlikely to reach $100,000 before 2021, and it will not exceed this price before the 5-year shifted line becomes relevant. After 2028, however, the price is predicted to never fall below $100,000, thanks to the support established by the shifted lines.
In essence, the shifted Power Law lines offer a way to predict both the minimum price levels that Bitcoin will hit by certain dates and the earliest dates by which certain price points will be reached. These lines help frame Bitcoin's potential future price range, offering insight into long-term price behavior and providing a guide for investors and analysts. Lets examine some examples:
Example 1:
In Example 1 it can be seen that point A on the 5-year shifted line acts as major resistance . Also it can be seen that 5 years later this price level now corresponds to the Base Power Law Line and acts as a major support at point B(Note: Vertical yearly grid lines have been added for this purpose👍).
Example 2:
In Example 2, the price level at point C on the 3-year shifted line becomes a major support three years later at point D, now aligning with the Base Power Law Line.
Finally, let's explore some future price predictions, as this script provides projections on the weekly timeframe :
Example 3:
In Example 3, the Bitcoin Power Law indicates that Bitcoin's price cannot surpass approximately $808K before 2030 as can be seen at point E, while also ensuring it will be at least $224K by then (point F).
Bitcoin Power LawThis is the main body version of the script. The Oscillator version can be found here.
Understanding the Bitcoin Power Law Model
Also called the Long-Term Bitcoin Power Law Model. The Bitcoin Power Law model tries to capture and predict Bitcoin's price growth over time. It assumes that Bitcoin's price follows an exponential growth pattern, where the price increases over time according to a mathematical relationship.
By fitting a power law to historical data, the model creates a trend line that represents this growth. It then generates additional parallel lines (support and resistance lines) to show potential price boundaries, helping to visualize where Bitcoin’s price could move within certain ranges.
In simple terms, the model helps us understand Bitcoin's general growth trajectory and provides a framework to visualize how its price could behave over the long term.
The Bitcoin Power Law has the following function:
Power Law = 10^(a + b * log10(d))
Consisting of the following parameters:
a: Power Law Intercept (default: -17.668).
b: Power Law Slope (default: 5.926).
d: Number of days since a reference point(calculated by counting bars from the reference point with an offset).
Explanation of the a and b parameters:
Roughly explained, the optimal values for the a and b parameters are determined through a process of linear regression on a log-log scale (after applying a logarithmic transformation to both the x and y axes). On this log-log scale, the power law relationship becomes linear, making it possible to apply linear regression. The best fit for the regression is then evaluated using metrics like the R-squared value, residual error analysis, and visual inspection. This process can be quite complex and is beyond the scope of this post.
Applying vertical shifts to generate the other lines:
Once the initial power-law is created, additional lines are generated by applying a vertical shift. This shift is achieved by adding a specific number of days (or years in case of this script) to the d-parameter. This creates new lines perfectly parallel to the initial power law with an added vertical shift, maintaining the same slope and intercept.
In the case of this script, shifts are made by adding +365 days, +2 * 365 days, +3 * 365 days, +4 * 365 days, and +5 * 365 days, effectively introducing one to five years of shifts. This results in a total of six Power Law lines, as outlined below (From lowest to highest):
Base Power Law Line (no shift)
1-year shifted line
2-year shifted line
3-year shifted line
4-year shifted line
5-year shifted line
The six power law lines:
Bitcoin Power Law Oscillator
This publication also includes the oscillator version of the Bitcoin Power Law. This version applies a logarithmic transformation to the price, Base Power Law Line, and 5-year shifted line using the formula: log10(x) .
The log-transformed price is then normalized using min-max normalization relative to the log-transformed Base Power Law Line and 5-year shifted line with the formula:
normalized price = log(close) - log(Base Power Law Line) / log(5-year shifted line) - log(Base Power Law Line)
Finally, the normalized price was multiplied by 5 to map its value between 0 and 5, aligning with the shifted lines.
Interpretation of the Bitcoin Power Law Model:
The shifted Power Law lines provide a framework for predicting Bitcoin's future price movements based on historical trends. These lines are created by applying a vertical shift to the initial Power Law line, with each shifted line representing a future time frame (e.g., 1 year, 2 years, 3 years, etc.).
By analyzing these shifted lines, users can make predictions about minimum price levels at specific future dates. For example, the 5-year shifted line will act as the main support level for Bitcoin’s price in 5 years, meaning that Bitcoin’s price should not fall below this line, ensuring that Bitcoin will be valued at least at this level by that time. Similarly, the 2-year shifted line will serve as the support line for Bitcoin's price in 2 years, establishing that the price should not drop below this line within that time frame.
On the other hand, the 5-year shifted line also functions as an absolute resistance , meaning Bitcoin's price will not exceed this line prior to the 5-year mark. This provides a prediction that Bitcoin cannot reach certain price levels before a specific date. For example, the price of Bitcoin is unlikely to reach $100,000 before 2021, and it will not exceed this price before the 5-year shifted line becomes relevant. After 2028, however, the price is predicted to never fall below $100,000, thanks to the support established by the shifted lines.
In essence, the shifted Power Law lines offer a way to predict both the minimum price levels that Bitcoin will hit by certain dates and the earliest dates by which certain price points will be reached. These lines help frame Bitcoin's potential future price range, offering insight into long-term price behavior and providing a guide for investors and analysts. Lets examine some examples:
Example 1:
In Example 1 it can be seen that point A on the 5-year shifted line acts as major resistance . Also it can be seen that 5 years later this price level now corresponds to the Base Power Law Line and acts as a major support at point B (Note: Vertical yearly grid lines have been added for this purpose👍).
Example 2:
In Example 2, the price level at point C on the 3-year shifted line becomes a major support three years later at point D, now aligning with the Base Power Law Line.
Finally, let's explore some future price predictions, as this script provides projections on the weekly timeframe :
Example 3:
In Example 3, the Bitcoin Power Law indicates that Bitcoin's price cannot surpass approximately $808K before 2030 as can be seen at point E, while also ensuring it will be at least $224K by then (point F).
PORTFOLIO TABLE Full [Titans_Invest]PORTFOLIO TABLE Full
This is a complete table for monitoring your assets or cryptocurrencies in your SPOT wallet without needing to access your broker’s website or app.
⯁ HOW TO USE THIS TABLE❓
Simply select the asset and enter the amount you hold.
The table will display the value of each asset and the total value of your portfolio.
You can monitor up to 19 assets in real time.
⯁ CONVERT VALUES
You can also enable and select a currency for conversion.
For example, cryptocurrencies are calculated in US dollars by default, but you can choose euros as the conversion currency.
The values originally in dollars will then be displayed in euros.
⯁ TRACK THE DAILY VARIATION OF YOUR PORTFOLIO
You’ll be able to monitor your portfolio’s raw daily variation in real time.
🔶 Track your Portfolio in real time:
🔶 Add your local Currency to Convert Values:
🔶 Follow your Portfolio Live:
___________________________________________________________
📜 SCRIPT : PORTFOLIO TABLE Full
🎴 Art by : @Titans_Invest & @DiFlip
👨💻 Dev by : @Titans_Invest & @DiFlip
🎑 Titans Invest — The Wizards Without Gloves 🧤
✨ Enjoy!
___________________________________________________________
o Mission 🗺
• Inspire Traders to manifest Magic in the Market.
o Vision 𐓏
• To elevate collective Energy 𐓷𐓏
Bitcoin Weekend FadeThis indicator is a tool for setting a bias based on weekend price movements, with the assumption that the crypto market often experiences stronger moves over the weekend due to thinner order books. It helps identify potential fade opportunities, suggesting that price movements from Saturday and Sunday may reverse during the weekdays.
How to use:
Sets a bias based on weekend price action.
Sets a bias based on weekend price action.
Use weekday price action for confirmation before acting on the bias.
Best suited for range-bound markets, where the price tends to revert to the mean.
Avoid fading high-timeframe breakouts, as they often indicate strong trends.
SwingTrade VWAP Strategy[TiamatCrypto]V1.1This Pine Script® code creates a trading strategy called "SwingTrade VWAP Strategy V1.1." This strategy incorporates various trading tools, such as VWAP (Volume Weighted Average Price), ADX (Average Directional Index), and volume signals. Below is an explanation of the components and logic within the script:
### Overview of Features
- **VWAP:** A volume-weighted moving average that assesses price trends relative to the VWAP level.
- **ADX:** A trend strength indicator that helps confirm the strength of bullish or bearish trends.
- **Volume Analysis:** Leverages volume data to gauge momentum and identify volume-weighted buy/sell conditions.
- **Dynamic Entry/Exit Signals:** Combines the above indicators to produce actionable buy/sell or exit signals.
- **Customizable Inputs:** Inputs for tuning parameters like VWAP period, ADX thresholds, and volume sensitivity.
---
### **Code Breakdown**
#### **Input Parameters**
The script begins by defining several user-configurable variables under groups. These include indicators' on/off switches (`showVWAP`, `enableADX`, `enableVolume`) and input parameters for VWAP, ADX thresholds, and volume sensitivity:
- **VWAP Period and Threshold:** Controls sensitivity for VWAP signal generation.
- **ADX Settings:** Allows users to configure the ADX period and strength threshold.
- **Volume Ratio:** Detects bullish/bearish conditions based on relative volume patterns.
---
#### **VWAP Calculation**
The script calculates VWAP using the formula:
\
Where `P` is the typical price (`(high + low + close)/3`) and `V` is the volume.
- It resets cumulative values (`sumPV` and `sumV`) at the start of each day.
- Delta percentage (`deltaPercent`) is calculated as the percentage difference between the close price and the VWAP.
---
#### **Indicators and Signals**
1. **VWAP Trend Signals:**
- Identifies bullish/bearish conditions based on price movement (`aboveVWAP`, `belowVWAP`) and whether the price is crossing the VWAP level (`crossingUp`, `crossingDown`).
- Also detects rising/falling delta changes based on the VWAP threshold.
2. **ADX Calculation:**
- Calculates the directional movement (`PlusDM`, `MinusDM`) and smoothed values for `PlusDI`, `MinusDI`, and `ADX`.
- Confirms strong bullish/bearish trends when ADX crosses the defined threshold.
3. **Volume-Based Signals:**
- Evaluates the ratio of bullish volume (when `close > VWAP`) to bearish volume (when `close < VWAP`) over a specified lookback period.
---
#### **Trade Signals**
The buy and sell signals are determined by combining conditions from the VWAP, ADX, and volume signals:
- **Buy Signal:** Triggered when price upward crossover VWAP, delta rises above the threshold, ADX indicates a strong bullish trend, and volume confirms bullish momentum.
- **Sell Signal:** Triggered under inverse conditions.
- Additionally, exit conditions (`exitLong` and `exitShort`) are based on VWAP crossovers combined with the reversal of delta values.
---
#### **Plotting and Display**
The strategy plots VWAP on the chart and adds signal markers for:
- **Buy/Long Entry:** Green triangle below bars.
- **Sell/Short Entry:** Red triangle above bars.
- **Exit Signals:** Lime or orange "X" shapes for exits from long/short positions.
- Additionally, optional text labels are displayed to indicate the type of signal.
---
#### **Trading Logic**
The script's trading logic executes as follows:
- **Entries:**
- Executes long trades when the `buySignal` condition is true.
- Executes short trades when the `sellSignal` condition is true.
- **Exits:**
- Closes long positions upon `exitLong` conditions.
- Closes short positions upon `exitShort` conditions.
- The strategy calculates profits and visualizes the trade entry, exit, and running profit within the chart.
---
#### **Alerts**
Alerts are set up to notify traders via custom signals for buy and sell trades.
---
### **Use Case**
This script is suitable for day traders, swing traders, or algorithmic traders who rely on confluence signals from VWAP, ADX, and volume momentum. Its modular structure (e.g., the ability to enable/disable specific indicators) makes it highly customizable for various trading styles and financial instruments.
#### **Customizability**
- Adjust VWAP, ADX, and volume sensitivity levels to fit unique market conditions or asset classes.
- Turn off specific criteria to focus only on VWAP or ADX signals if desired.
#### **Caution**
As with all trading strategies, this script should be used for backtesting and analysis before live implementation. It's essential to validate its performance on historical data while considering factors like slippage and transaction costs.
PORTFOLIO TABLE Simple [Titans_Invest]PORTFOLIO TABLE Simple
This is a simple table for you to monitor your assets or cryptocurrencies in your SPOT wallet without needing to access your broker’s website or wallet app.
⯁ HOW TO USE THIS TABLE❓
You only need to select the asset and enter the amount of each one.
The table will show how much you have of each asset and the total value of your portfolio.
You’ll be able to monitor up to 39 assets in real time.
⯁ CONVERT VALUES
You can also activate and select a currency for conversion.
For example, cryptocurrency assets are calculated in US dollars, but you can select euros as the conversion currency.
The values originally in dollars will then be displayed in euros.
⯁ Track your Portfolio in real time:
⯁ Add your local Currency to Convert Values:
⯁ Follow your Portfolio Live:
___________________________________________________________
📜 SCRIPT : PORTFOLIO TABLE Simple
🎴 Art by : @Titans_Invest & @DiFlip
👨💻 Dev by : @Titans_Invest & @DiFlip
🎑 Titans Invest — The Wizards Without Gloves 🧤
✨ Enjoy!
___________________________________________________________
o Mission 🗺
• Inspire Traders to manifest Magic in the Market.
o Vision 𐓏
• To elevate collective Energy 𐓷𐓏
