Litecoin LTC Logarithmic Fibonacci Growth CurvesHOW THIS SCRIPT IS ORIGINAL: there is no similar script dedicated to LTC, although there are similar ones dedicated to BTC. (This was created by modifying an old public and open source similar script dedicated to BTC.)
WHAT THIS SCRIPT DOES: draws a channel containing the price of LTC within which the Fibonacci extensions are highlighted. The reference chart to use is LTC/USD on Bitfinex (because it has the oldest data, given that Tradingview has not yet created an LTC index), suggested with weekly or monthly timeframe.
HOW IT DOES IT: starting from two basic curves that average the upper and lower peaks of the price, the relative Fibonacci extensions are then built on the basis of these: 0.9098, 0.8541, 0.7639, 0.618, 0.5, 0.382, 0.2361, 0.1459, 0.0902.
HOW TO USE IT: after activating the script you will notice the presence of two areas of particular interest, the upper area, delimited in red, which follows the upper peaks of the price, and the lower area, delimited in green, which follows the lower peaks of the price. Furthermore, the main curves, namely the two extremes and the median, are also projected into the future to predict an indicative trend. This script is therefore useful for understanding where the price will go in the future and can be useful for understanding when to buy (near the green lines) or when to sell (near the red lines). It is also possible to configure the script by choosing the colors and types of lines, as well as the main parameters to define the upper and lower curve, from which the script deduces all the other lines that are in the middle.
Very easy to read and interpret. I hope this description is sufficient, but it is certainly easier to use it than to describe it.
Jalur dan Saluran
Channels by SmanovIndicator Description
“Channels by Smanov” is a multi-channel indicator that plots dynamic support and resistance zones around a moving average line. It is composed of two main parts:
FL 1 (Flexible Channels):
A Simple Moving Average (SMA) serves as the Basis.
Upper and lower bands are calculated by adding and subtracting an ATR-based buffer from the Basis.
User-defined inputs (such as Half Length, ATR Period, and ATR Multiplier) allow for flexibility in adapting the channel width to different market conditions.
FL 2 (Fixed Channels):
Eight additional bands expand on the same SMA + ATR logic but use fixed ATR multipliers (ranging from 2.2 up to 5.0).
These extra lines can help you gauge more distant levels of potential support or resistance.
By combining an SMA (to smooth price data) with ATR (to gauge volatility), this indicator highlights areas where price may be “stretched” relative to recent volatility. Traders often use channel-based indicators to identify potential “overbought” or “oversold” conditions, as well as to spot trend continuations or reversals.
How to Use / Trading Strategy
Trend Identification (Basis Line):
The middle line (the SMA) can be used as a trend filter:
If price consistently stays above the basis, it suggests an uptrend.
If price consistently stays below the basis, it suggests a downtrend.
Reversal Opportunities (Outer Bands):
When price moves into or beyond the upper bands, it may signal overbought conditions, creating potential short (or profit-taking) opportunities.
Conversely, when price dips into or beyond the lower bands, it may signal oversold conditions, which some traders use for initiating or adding to long positions.
Breakout or Continuation Signals:
In a strong trend, price may “ride” along the outer channels.
A clear break above/below a channel that previously acted as resistance/support could hint at trend continuation.
Failure to break these levels could suggest a potential reversal or consolidation phase.
Stop-Loss Placement:
Traders often place stops just outside a relevant band. For example, if you go long on a dip near a lower band, you might place your stop slightly below that band, relying on the ATR-based buffer to reflect normal volatility.
Multiple Timeframe Analysis:
Consider confirming signals on a higher timeframe (e.g., 4-hour or daily) while taking entries on a lower timeframe.
Channels on higher timeframes can act as stronger support or resistance, offering additional confluence.
Disclaimer
This indicator is provided for educational purposes and does not guarantee specific results. Trading involves risk, and individual traders are responsible for managing their own risk and capital. Always conduct thorough analysis and use appropriate risk management (e.g., stop-losses) when entering any market positions.
Enjoy using Channels by Smanov! Your feedback and personal insights can further refine the indicator’s settings for your preferred trading style. Good luck and trade responsibly!
This Pine Script™ code is subject to the terms of the Mozilla Public License 2.0.
© Smanov_I
Breakout Josip strategy is focused on analyzing price movements during specific time intervals (from 9:00 AM to 12:00 PM) each day. It tracks the highest and lowest prices in that period and uses them to set targets for potential trades, placing horizontal lines based on these levels. Additionally, you're interested in tracking the success and failure of trades based on whether price breaks certain levels during this time range. The strategy also calculates various metrics like the percentage of successful trades, failed trades, and total trades during a selected time range.
Quantitative Breakout Bands (AIBitcoinTrend)Quantitative Breakout Bands (AIBitcoinTrend) is an advanced indicator designed to adapt to dynamic market conditions by utilizing a Kalman filter for real-time data analysis and trend detection. This innovative tool empowers traders to identify price breakouts, evaluate trends, and refine their trading strategies with precision.
👽 What Are Quantitative Breakout Bands, and Why Are They Unique?
Quantitative Breakout Bands combine advanced filtering techniques (Kalman Filters) with statistical measures such as mean absolute error (MAE) to create adaptive price bands. These bands adjust to market conditions dynamically, providing insights into volatility, trend strength, and breakout opportunities.
What sets this indicator apart is its ability to incorporate both position (price) and velocity (rate of price change) into its calculations, making it highly responsive yet smooth. This dual consideration ensures traders get reliable signals without excessive lag or noise.
👽 The Math Behind the Indicator
👾 Kalman Filter Estimation:
At the core of the indicator is the Kalman Filter, a recursive algorithm used to predict the next state of a system based on past observations. It incorporates two primary elements:
State Prediction: The indicator predicts future price (position) and velocity based on previous values.
Error Covariance Adjustment: The process and measurement noise parameters refine the prediction's accuracy by balancing smoothness and responsiveness.
👾 Breakout Bands Calculation:
The breakout bands are derived from the mean absolute error (MAE) of price deviations relative to the filtered trendline:
float upperBand = kalmanPrice + bandMultiplier * mae
float lowerBand = kalmanPrice - bandMultiplier * mae
The multiplier allows traders to adjust the sensitivity of the bands to market volatility.
👾 Slope-Based Trend Detection:
A weighted slope calculation measures the gradient of the filtered price over a configurable window. This slope determines whether the market is trending bullish, bearish, or neutral.
👾 Trailing Stop Mechanism:
The trailing stop employs the Average True Range (ATR) to calculate dynamic stop levels. This ensures positions are protected during volatile moves while minimizing premature exits.
👽 How It Adapts to Price Movements
Dynamic Noise Calibration: By adjusting process and measurement noise inputs, the indicator balances smoothness (to reduce noise) with responsiveness (to adapt to sharp price changes).
Trend Responsiveness: The Kalman Filter ensures that trend changes are quickly identified, while the slope calculation adds confirmation.
Volatility Sensitivity: The MAE-based bands expand and contract in response to changes in market volatility, making them ideal for breakout detection.
👽 How Traders Can Use the Indicator
👾 Breakout Detection:
Bullish Breakouts: When the price moves above the upper band, it signals a potential upward breakout.
Bearish Breakouts: When the price moves below the lower band, it signals a potential downward breakout.
The trailing stop feature offers a dynamic way to lock in profits or minimize losses during trending moves.
👾 Trend Confirmation:
The color-coded Kalman line and slope provide visual cues:
Bullish Trend: Positive slope, green line.
Bearish Trend: Negative slope, red line.
👽 Why It’s Useful for Traders
Dynamic and Adaptive: The indicator adjusts to changing market conditions, ensuring relevance across timeframes and asset classes.
Noise Reduction: The Kalman Filter smooths price data, eliminating false signals caused by short-term noise.
Comprehensive Insights: By combining breakout detection, trend analysis, and risk management, it offers a holistic trading tool.
👽 Indicator Settings
Process Noise (Position & Velocity): Adjusts filter responsiveness to price changes.
Measurement Noise: Defines expected price noise for smoother trend detection.
Slope Window: Configures the lookback for slope calculation.
Lookback Period for MAE: Defines the sensitivity of the bands to volatility.
Band Multiplier: Controls the band width.
ATR Multiplier: Adjusts the sensitivity of the trailing stop.
Line Width: Customizes the appearance of the trailing stop line.
Disclaimer: This indicator is designed for educational purposes and does not constitute financial advice. Please consult a qualified financial advisor before making investment decisions.
Donchian Cloud-V1The Donchian Cloud-V1 is a technical analysis indicator inspired by the Ichimoku Cloud, but with a twist. It utilizes two Donchian Channel midline calculations to create a cloud-like price zone. This indicator aims to help traders identify potential areas of support and resistance, and also suggests that trades should be avoided when prices are within the cloud.
How it Works?
The Donchian Cloud-V1 calculates two Donchian Channel midlines:
Fast Donchian Channel: This midline is based on a shorter period, making it more responsive to price changes.
Slow Donchian Channel: This midline is based on a longer period, providing a smoother and more stable cloud formation.
The upper and lower bands of the traditional Donchian Channels are discarded, and the midlines become the cloud's upper and lower boundaries.
Interpretation
Price Above the Cloud: A price move above the cloud can be interpreted as a bullish signal, suggesting potential upward momentum.
Price Below the Cloud: A price move below the cloud can be interpreted as a bearish signal, suggesting potential downward momentum.
Price Within the Cloud: The indicator advises against taking any trades when the price is within the cloud itself, as the market may be unclear or ranging.
Benefits of Using the Donchian Cloud-V1
Visually Appealing: The cloud can provide a clear and concise view of potential support and resistance zones.
Customizable: The lengths of the fast and slow Donchian Channels can be adjusted to suit your trading style and preferred timeframe.
Complements Other Indicators: The Donchian Cloud-V1 can be used in conjunction with other technical indicators to strengthen trade signals.
Limitations to Consider
Lagging Indicator: Like many technical indicators, the Donchian Cloud-V1 is based on past price data and may not always perfectly predict future price movements.
False Signals: The cloud can generate false signals, especially in volatile markets.
Not a Standalone Strategy: The Donchian Cloud-V1 should ideally be used alongside other trading strategies and risk management techniques.
The Donchian Cloud-V1 is a valuable tool for traders who want to identify potential support and resistance zones and avoid making trades during periods of market uncertainty. Remember, it's important to backtest and paper trade any indicator before using it with real capital.
Half-Trend Channel [BigBeluga]Half Trend Channel is a powerful trend-following indicator designed to identify trend direction, fakeouts, and potential reversal points. The combination of upper/lower bands, midline coloring, and specific signals makes it ideal for spotting trend continuation and market reversals.
The base of the channel is calculated using smoothed half-trend logic.
// Initialize half trend on the first bar
if barstate.isfirst
hl_t := close
// Update half trend value based on conditions
switch
closeMA < hl_t and highestHigh < hl_t => hl_t := highestHigh
closeMA > hl_t and lowestLow > hl_t => hl_t := lowestLow
=> hl_t := hl_t
// Smooth
float s_hlt = ta.hma(hl_t, len)
🔵 Key Features:
Upper and Lower Bands:
The bands adapt dynamically to market volatility.
Price movements toward the bands help identify areas of overextension and potential reversal points.
Midline Trend Signal:
The midline changes color to reflect the current trend:
Green Midline: Indicates an uptrend.
Purple Midline: Signals a downtrend.
Fakeout Signals ("X"):
"X" markers appear when price briefly breaches the outer bands but fails to sustain the move.
Fakeouts help traders identify areas where price momentum weakens.
Reversal Signals (Triangles):
Triangles (▲ and ▼) mark potential tops and bottoms:
▲ Up Triangles: Suggest a potential bottom and a reversal to the upside.
▼ Down Triangles: Indicate a potential top and a reversal to the downside.
Dynamic Trend Labels:
At the last bar, the indicator displays labels like "Trend Up" or "Trend Dn" , reflecting the current trend direction.
🔵 Usage:
Use the colored midline to determine the overall trend direction.
Monitor "X" fakeout signals to spot failed breakouts or momentum exhaustion near the bands.
Watch for reversal triangles (▲ and ▼) to identify potential trend reversals at tops or bottoms.
Combine the bands and midline signals to confirm trade entries and exits:
Enter long trades when price bounces off the lower band with a green midline.
Consider short trades when price reverses from the upper band with a purple midline.
Use the trend label (e.g., "Trend Up" or "Trend Dn") for quick confirmation of the current market state.
The Half Trend Channel is an essential tool for traders who want to follow trends, avoid fakeouts, and identify reliable tops and bottoms to optimize their trading decisions.
RSI Bands with Volume and EMAThis script is a comprehensive technical analysis tool designed to help traders identify key market signals using RSI bands, volume, and multiple Exponential Moving Averages (EMAs). It overlays the following on the chart:
RSI Bands: The script calculates and plots two bands based on the Relative Strength Index (RSI), indicating overbought and oversold levels. These bands act as dynamic support and resistance zones:
Resistance Band (Upper Band): Plotted when the RSI exceeds the overbought level, typically indicating a potential sell signal.
Support Band (Lower Band): Plotted when the RSI falls below the oversold level, typically indicating a potential buy signal.
Midline: The average of the upper and lower bands, acting as a neutral reference.
Buy/Sell Labels: Labels are dynamically added to the chart when price reaches the overbought or oversold levels.
A "Buy" label appears when the price reaches the oversold (lower) band.
A "Sell" label appears when the price reaches the overbought (upper) band.
Volume Indicator: The script visualizes trading volume as histograms, with red or green bars representing decreasing or increasing volume, respectively. The volume height is visually reduced for better clarity and comparison.
Exponential Moving Averages (EMAs): The script calculates and plots four key EMAs (12, 26, 50, and 200) to highlight short-term, medium-term, and long-term trends:
EMA 12: Blue
EMA 26: Orange
EMA 50: Purple
EMA 200: Green
The combined use of RSI, volume, and EMAs offers traders a multi-faceted view of the market, assisting in making informed decisions about potential price reversals, trends, and volume analysis. The script is particularly useful for identifying entry and exit points on charts like BTC/USDT, although it can be applied to any asset.
G. Santostasi' Active Addresses and Hash Rate Power LawThe Bitcoin Power Law Indicator is a groundbreaking tool designed for investors, analysts, and enthusiasts who seek to understand Bitcoin's price behavior through its fundamental network metrics. This invite-only indicator leverages the Giovanni Santostasi Power Law Model, which reveals the deep interconnections between Bitcoin's core parameters and its price evolution over time.
Features and Functionality:
Bitcoin Price vs. Active Addresses Model
Using Giovanni Santostasi’s power law framework, the indicator establishes a quantitative relationship between Bitcoin's price and the number of active addresses. Active addresses, a critical on-chain metric, reflect network activity and adoption. This model generates a theoretical Bitcoin price based solely on the behavior of active addresses, highlighting how network usage underpins price movements.
Bitcoin Price vs. Hash Rate Model
The indicator applies the same power law methodology to analyze the relationship between Bitcoin's price and its hash rate. The hash rate, representing the computational power securing the network, is a fundamental measure of the network's security and robustness. This model estimates Bitcoin’s price as a function of the hash rate, showcasing the symbiotic relationship between miner activity and market valuation.
Comparison with Bitcoin Price vs. Time Model
Both the active addresses and hash rate-based models are compared against the classic Bitcoin price vs. time power law. This comparison provides insight into the alignment or divergence of Bitcoin’s price with its fundamental network metrics and long-term temporal trends.
Visualization of Interconnectedness
The indicator synthesizes on-chain data to visually and quantitatively demonstrate the interconnectedness of Bitcoin's key parameters—price, network activity, and mining security. It provides a real-time measure of the strength of the Bitcoin network, offering a holistic perspective on its health and resilience.
Utility for Investors:
Enhanced Market Understanding:
By breaking down Bitcoin's price into its fundamental drivers—active addresses, hash rate, and time—investors gain a clearer picture of what underpins price trends. This knowledge can inform long-term investment strategies and improve confidence during volatile periods.
Network Health Monitoring:
The indicator serves as a robust measure of network strength. Divergences between the models and actual price may indicate periods of mispricing or anomalies in network activity, offering potential trading opportunities.
Validation of the Power Law Theory:
Investors can track Bitcoin's adherence to the power law, which has demonstrated remarkable consistency over the years. This provides a scientific framework for understanding Bitcoin’s growth trajectory, helping investors separate signal from noise in the market.
Risk Management and Opportunity Identification:
Understanding when Bitcoin's price deviates from its fundamental power law models can help investors identify potential overvaluation, undervaluation, or turning points in the market. These insights can be critical for both short-term trading and long-term portfolio allocation.
This indicator is a must-have for those who value a data-driven, scientific approach to Bitcoin analysis. By combining cutting-edge research with real-time analytics, it offers a unique lens to view Bitcoin not just as a speculative asset but as a robust, interconnected system that adheres to fundamental physical and social principles.
Drawdown from 22-Day High (Daily Anchored)This Pine Script indicator, titled "Drawdown from 22-Day High (Daily Anchored)," is designed to plot various drawdown levels from the highest high over the past 22 days. This helps traders visualize the performance and potential risk of the security in terms of its recent high points.
Key Features:
Daily High Data:
Fetches daily high prices using the request.security function with a daily timeframe.
Highest High Calculation:
Calculates the highest high over the last 22 days using daily data. This represents the highest price the security has reached in this period.
Drawdown Levels:
Computes various drawdown levels from the highest high:
2% Drawdown
5% Drawdown
10% Drawdown
15% Drawdown
25% Drawdown
45% Drawdown
50% Drawdown
Dynamic Line Coloring:
The color of the 2% drawdown line changes dynamically based on the current closing price:
Green (#02ff0b) if the close is above the 2% drawdown level.
Red (#ff0000) if the close is below the 2% drawdown level.
Plotting Drawdown Levels:
Plots each drawdown level on the chart with specific colors and line widths for easy visual distinction:
2% Drawdown: Green or Red, depending on the closing price.
5% Drawdown: Orange.
10% Drawdown: Blue.
15% Drawdown: Maroon.
25% Drawdown: Purple.
45% Drawdown: Yellow.
50% Drawdown: Black.
Labels for Drawdown Levels:
Adds labels at the end of each drawdown line to indicate the percentage drawdown:
Labels display "2% WVF," "5% WVF," "10% WVF," "15% WVF," "25% WVF," "45% WVF," and "50% WVF" respectively.
The labels are positioned dynamically at the latest bar index to ensure they are always visible.
Explanation of Williams VIX Fix (WVF)
The Williams VIX Fix (WVF) is a volatility indicator designed to replicate the behavior of the VIX (Volatility Index) using price data instead of options prices. It helps traders identify market bottoms and volatility spikes.
Key Aspects of WVF:
Calculation:
The WVF measures the highest high over a specified period (typically 22 days) and compares it to the current closing price.
It is calculated as:
WVF
=
highest high over period
−
current close
highest high over period
×
100
This formula provides a percentage measure of how far the price has fallen from its recent high.
Interpretation:
High WVF Values: Indicate increased volatility and potential market bottoms, suggesting oversold conditions.
Low WVF Values: Suggest lower volatility and potentially overbought conditions.
Usage:
WVF can be used in conjunction with other indicators (e.g., moving averages, RSI) to confirm signals.
It is particularly useful for identifying periods of significant price declines and potential reversals.
In the script, the WVF concept is incorporated into the drawdown levels, providing a visual representation of how far the price has fallen from its 22-day high.
Example Use Cases:
Risk Management: Quickly identify significant drawdown levels to assess the risk of current positions.
Volatility Monitoring: Use the WVF-based drawdown levels to gauge market volatility.
Support Levels: Utilize drawdown levels as potential support levels where price might find buying interest.
This script offers traders and analysts an efficient way to visualize and track important drawdown levels from recent highs, helping in better risk management and decision-making. The dynamic color and label features enhance the readability and usability of the indicator.
Trading Hub 3.0 JukaThe smart money concept suggests that institutional traders have a greater understanding of the market and often have access to more information than retail traders. Therefore, by analyzing market structure, retail traders can align themselves with the actions of smart money and potentially profit from their moves.
This indicator considerably simplifies the process of identification of market structure for traders based on the TradingHUB-3 technical method. Therefore, it is quite different from the existing market structure or trend detection tools, even the other smart-money-based indicators.
How it works:
The indicator starts candlestick analysis from the given start point detecting followings items.
1) Identify valid pullbacks (minor Zigzag):
Uptrend: In the upward trend, each candle that hits a higher high (HH), acts as our checking candle, and if the next candle hits its low, a valid pullback is formed, and we marked the checking candle as the end of a minor leg. Note that we do not take inside bars into account. If the highest point of the leg hit, the lowest point is marked as the end of pullback leg. On the other hand, if the lowest point of the upward leg is hit, the pullback checking procedure is restarted as a downtrend. Note that the downward checking is restarted from the highest point (previous checking candle).
Downtrend: The pullback detection for downtrend follows the reverse procedure of uptrend.
2) Identify inducements (IDM)
The last pullback point (on the minor zigzag) considers as the inducement level. In the uptrend, if the price hit the IDM, the highest point on the major leg is accepted as a major higher high. Note, if the IDM point is equal to a major HL and hit by price, the highest point is accepted as a new HH and the previous HH and LL are deleted (i.e. the HH is transferred).
In the downtrend, it acts conversely.
3) Identify valid break of structures (BOS)
In the uptrend, if the price closed above the highest point between the previous accepted HH to the current candle, a BOS is accrued, and the lowest point in this time interval is accepted as a higher low (HL). In the downtrend, it acts contrariwise.
4) Identify valid change of characters (Choch)
In the uptrend, if the price closed below the lowest point between the previous accepted HL to the current candle, a Choch is accrued, and the major trend changes from uptrend to downtrend, and a new reverse IDM will be detected. In the downtrend, it acts inversely.
5) Identify major HH/HL/LL/LH points
By following the above steps, the major higher highs, higher lows, lower highs, and lower lows, as well as the major trend are detected. The major high and lows on the major trend can be displayed by zigzag style or bullet points with corresponding up/down color.
Bollingers Bands Fibonacci ratios_copy of FOMOBollinger Bands Fibonacci Ratios (FiBB)
This TradingView script is a powerful tool that combines the classic Bollinger Bands with Fibonacci ratios to help traders identify potential support and resistance zones based on market volatility.
Key Features:
Dynamic Fibonacci Levels: The script calculates additional levels around a Simple Moving Average (SMA) using Fibonacci ratios (default: 1.618, 2.618, and 4.236). These levels adapt to market volatility using the Average True Range (ATR).
Customizable Parameters: Users can modify the length of the SMA and the Fibonacci ratios to fit their trading strategy and time frame.
Visual Representation: The indicator plots three upper and three lower bands, with color-coded transparency for easy interpretation.
Central SMA Line: The core SMA line provides a baseline for price movement and trend direction.
Shaded Range: The script visually fills the area between the outermost bands to highlight the overall range of price action.
How to Use:
Use the upper bands as potential resistance zones and the lower bands as potential support zones.
Look for price interactions with these levels to identify opportunities for breakout, trend continuation, or reversal trades.
Combine with other indicators or price action analysis to enhance decision-making.
This script is ideal for traders who want a unique blend of Fibonacci-based analysis and Bollinger Bands to better navigate market movements.
Futures Engulfing Candle Size Strategy (Ticks, TP/SL)The Futures Candle Size Strategy is designed to identify and trade significant price movements in the futures market based on candle size. It is optimized for futures instruments like ES, NQ, or CL, where precise tick-level calculations are essential. The strategy includes a customizable take profit and stop loss in ticks and operates only within a specified time window (e.g., 7:00 AM to 9:15 AM CST).
Key Features:
Candle Size Threshold: Trades are triggered when the candle's high-to-low range exceeds the defined threshold in ticks.
Time Filter: Limits trades to the most active market hours, specifically between 7:00 AM and 9:15 AM CST.
Take Profit and Stop Loss: Customizable exit levels in ticks to manage risk and lock in profits.
Long and Short Trades: Automatically places buy or sell orders based on the candle's direction (bullish or bearish).
Alerts: Sends alerts whenever a trade is triggered, helping you stay informed in real-time.
How It Works:
The strategy calculates the size of each candle in ticks and compares it to the user-defined threshold.
If the candle size meets or exceeds the threshold within the specified time range, it triggers a long or short trade.
The trade automatically exits when the price hits the take profit or stop loss levels.
RSI Volatility Suppression Zones [BigBeluga]RSI Volatility Suppression Zones is an advanced indicator that identifies periods of suppressed RSI volatility and visualizes these suppression zones on the main chart. It also highlights breakout dynamics, giving traders actionable insights into potential market momentum.
🔵 Key Features:
Detection of Suppression Zones:
Identifies periods where RSI volatility is suppressed and marks these zones on the main price chart.
Breakout Visualization:
When the price breaks above the suppression zone, the box turns aqua, and an upward label is drawn to indicate a bullish breakout.
If the price breaks below the zone, the box turns purple, and a downward label is drawn for a bearish breakout.
Breakouts accompanied by a "+" label represent strong moves caused by short-lived, tight zones, signaling significant momentum.
Wave Labels for Consolidation:
If the suppression zone remains unbroken, a "wave" label is displayed within the gray box, signifying continued price stability within the range.
Gradient Intensity Below RSI:
A gradient strip below the RSI line increases in intensity based on the duration of the suppressed RSI volatility period.
This visual aid helps traders gauge how extended the low volatility phase is.
🔵 Usage:
Identify Breakouts: Use color-coded boxes and labels to detect breakouts and their direction, confirming potential trend continuation or reversals.
Evaluate Market Momentum: Leverage "+" labels for strong breakout signals caused by short suppression phases, indicating significant market moves.
Monitor Price Consolidation: Observe gray boxes and wave labels to understand ongoing consolidation phases.
Analyze RSI Behavior: Utilize the gradient strip to measure the longevity of suppressed volatility phases and anticipate breakout potential.
RSI Volatility Suppression Zones provides a powerful visual representation of RSI volatility suppression, breakout signals, and price consolidation, making it a must-have tool for traders seeking to anticipate market movements effectively.
Relative Risk MetricOVERVIEW
The Relative Risk Metric is designed to provide a relative measure of an asset's price, within a specified range, over a log scale.
PURPOSE
Relative Position Assessment: Visualizes where the current price stands within a user-defined range, adjusted for log scale.
Logarithmic Transformation: Utilizes the natural log to account for a log scale of prices, offering a more accurate representation of relative positions.
Calculation: The indicator calculates a normalized value via the function Relative Price = / log(UpperBound) − log(LowerBound) . The result is a value between 0 and 1, where 0 corresponds to the lower bound and 1 corresponds to the upper bound on a log scale.
VISUALIZATION
The indicator plots three series:
Risk Metric - a plot of the risk metric value that’s computed from an asset's relative price so that it lies within a logarithmic range between 0.0 & 1.0.
Smoothed Risk Metric - a plot of the risk metric that’s been smoothed.
Entry/Exit - a scatter plot for identified entry and exit. Values are expressed as percent and are coded as red being exit and green being entity. E.g., a red dot at 0.02 implies exit 2% of the held asset. A green dot at 0.01 implies use 1% of a designated capital reserve.
USAGE
Risk Metric
The risk metric transformation function has several parameters. These control aspects such as decay, sensitivity, bounds and time offset.
Decay - Acts as an exponent multiplier and controls how quickly dynamic bounds change as a function of the bar_index.
Time Offset - provides a centering effect of the exponential transformation relative to the current bar_index.
Sensitivity - controls how sensitive to time the dynamic bound adjustments should be.
Baseline control - Serves as an additive offset for dynamic bounds computation which ensures that bounds never become too small or negative.
UpperBound - provides headroom to accomodate growth an assets price from the baseline. For example, an upperbound of 3.5 accommodates a 3.5x growth from the baseline value (e.g., $100 -> $350).
LowerBound - provides log scale compression such that the overall metric provides meaningful insights for prices well below the average whilst avoiding extreme scaling. A lowerbound of 0.25 corresponds to a price that is approx one quarter of a normalised baseline in a log context.
Weighted Entry/Exit
This feature provides a weighted system for identifying DCA entry and exit. This weighting mechanism adjusts the metric's interpretation to highlight conditions based on dynamic thresholds and user-defined parameters to identify high-probability zones for entry/exit actions and provide risk-adjusted insights.
Weighting Parameters
The weighting function supports fine-tuning of the computed weighted entry/exit values
Base: determines the foundational multiplier for weighting the entry/exit value. A higher base amplifies the weighting effect, making the weighted values more pronounced. It acts as a scaling factor to control the overall magnitude of the weighting.
Exponent: adjusts the curve of the weighting function. Higher exponent values increase sensitivity, emphasizing differences between risk metric values near the entry or exit thresholds. This creates a steeper gradient for the computed entry/exit value making it more responsive to subtle shifts in risk levels.
Cut Off: specifies the maximum percentage (expressed as a fraction of 1.0) that the weighted entry/exit value can reach. This cap ensures the metric remains within a meaningful range and avoids skewing
Exit condition: Defines a threshold for exit. When the risk metric is below the exit threshold (but above the entry threshold) then entry/exit is neutral.
Entry condition: Defines a threshold for entry. When the risk metric is above the entry threshold (but below the exit threshold) then entry/exit is neutral.
Weighting Behaviour
For entry conditions - value is more heavily weighted as the metric approaches the entry threshold, emphasizing lower risk levels.
For exit conditions - value is more heavily weighted as the metric nears the exit threshold, emphasizing increased risk levels.
USE-CASES
Identifying potential overbought or oversold conditions within the specified logarithmic range.
Assisting in assessing how the current price compares to historical price levels on a logarithmic scale.
Guiding decision-making processes by providing insights into the relative positioning of prices within a log context
CONSIDERATIONS
Validation: It's recommended that backtesting over historical data be done before acting on any identified entry/exit values.
User Discretion: This indicator focus on price risk. Consider other risk factors and general market conditions as well.
NIFTY BANKNIFTY MIDCAP SENSEX FINNIFTY LEVELS)this indicator uses Gann's methods which are based on the idea that markets move in predictable geometric patterns and are influenced by time and price.
Key Concepts of Gann Levels:
Gann Angles:
Gann believed that specific angles could indicate the trend of a market. The most notable is the 45-degree angle, which he called the "1x1" or "45-degree line."
Angles are drawn from a significant price point, such as a high or low, and represent the speed or slope of the price movement.
Gann Square of 9:
A mathematical tool that calculates support and resistance levels based on the square root of numbers and their geometric relationships.
It aligns numbers in a spiral format, starting from a central point, and helps identify key price levels at certain degrees.
Gann Fan:
A series of lines drawn at specific angles from a significant high or low. Common angles include 1x1 (45°), 2x1 (26.25°), and 1x2 (63.75°).
These angles help traders identify potential areas where the trend might accelerate, decelerate, or reverse.
Gann Retracements:
Levels based on key price ratios derived from natural laws and geometric principles. Common Gann retracement levels include 12.5%, 25%, 50%, and 75%.
Time Analysis:
Gann emphasized the importance of time cycles. He believed markets move in time-based patterns, such as yearly cycles, seasonal cycles, or specific time intervals.
Daily Close Levels with ATR and Custom OffsetsDescription:
This Pine Script visualizes daily close levels, calculates key price zones based on custom offsets and ATR (Average True Range), and is an essential tool for traders analyzing support and resistance zones.
Features
Close Value Line: Displays the daily close value as a line on the chart.
ATR Values: Shows the ATR value in both price and tick format.
Custom Offsets:
Calculates positive and negative price levels based on a user-defined tick offset.
Supports multipliers for extended zones (e.g., 2x offset).
Labels:
Displays the close value and ATR on the chart.
Annotates calculated price levels directly on the corresponding lines.
Time Control: Calculates levels at a user-defined hour (e.g., 20:00).
Customizable Parameters:
Close Time (Hour): Choose the specific hour for analyzing the close price.
Custom Line Offset: Define the price offset in ticks.
ATR Length: Adjust the ATR calculation length.
Timezone Offset: Supports time adjustments for different time zones.
Enable/Disable Labels and Values: Toggle the display of labels and values on the chart.
[GrandAlgo] Automatic Parallel ChannelThe Automatic Parallel Channel indicator is designed to automate the process of drawing parallel channels on the chart. By analyzing price swings and slopes, it identifies trend-aligned channels that provide insights into market structure, potential reversals, and continuation patterns. This tool saves traders time and effort by eliminating the need to manually draw channels while ensuring accuracy and consistency.
How It Works
The indicator evaluates price action and detects significant swing highs and swing lows to define the boundaries of the parallel channels.
Channels are categorized as green for potential support zones and red for potential resistance zones, ensuring easy visual identification of price trends.
Customizable parameters such as Strength, Max. Slope Steepness, and Fibonacci Line Levels allow traders to adapt the channel detection to different market conditions.
A third line can optionally be drawn at a Fibonacci level for additional confluence.
Key Features
Automatic Channel Detection:
Identifies and plots parallel channels based on swing highs and swing lows, ensuring accuracy and efficiency.
Customizable Strength Parameter:
Adjust the sensitivity of channel detection to focus on minor, intermediate, or major trends.
Fibonacci Line Integration:
Optionally draw a third line within the channel at a user-defined Fibonacci level, offering additional reference points for trend analysis.
Dual Channel Visualization:
Displays green channels to represent potential support and red channels for potential resistance, simplifying visual analysis.
Slope Control:
Set the Max. Slope Steepness to filter out channels that do not meet your trend steepness criteria.
Real-Time Updates:
Channels are dynamically updated as price action evolves, ensuring relevance to current market conditions.
Use Cases
Identify trend channels to determine the overall market direction.
Spot potential reversal or continuation zones using channel boundaries.
Use the third Fibonacci line as a key level for potential price reactions.
Suitable for trend-following strategies and breakout trading setups.
Adaptable across Forex, crypto, stocks, and other markets.
Disclaimer:
This indicator is a technical analysis tool designed to assist traders by providing insights into market conditions. It does not guarantee future price movements or trading outcomes and should not be relied upon as a sole decision-making tool. The effectiveness of this indicator depends on its application, which requires your trading knowledge, experience, and judgment.
Trading involves significant financial risk, including the potential loss of capital. Past performance of any tool or indicator does not guarantee future results. This script is intended for educational and informational purposes only and does not constitute financial or investment advice. Users are strongly encouraged to perform their own analysis and consult with a qualified financial professional before making trading decisions.
Mean Reversion Pro Strategy [tradeviZion]Mean Reversion Pro Strategy : User Guide
A mean reversion trading strategy for daily timeframe trading.
Introduction
Mean Reversion Pro Strategy is a technical trading system that operates on the daily timeframe. The strategy uses a dual Simple Moving Average (SMA) system combined with price range analysis to identify potential trading opportunities. It can be used on major indices and other markets with sufficient liquidity.
The strategy includes:
Trading System
Fast SMA for entry/exit points (5, 10, 15, 20 periods)
Slow SMA for trend reference (100, 200 periods)
Price range analysis (20% threshold)
Position management rules
Visual Elements
Gradient color indicators
Three themes (Dark/Light/Custom)
ATR-based visuals
Signal zones
Status Table
Current position information
Basic performance metrics
Strategy parameters
Optional messages
📊 Strategy Settings
Main Settings
Trading Mode
Options: Long Only, Short Only, Both
Default: Long Only
Position Size: 10% of equity
Starting Capital: $20,000
Moving Averages
Fast SMA: 5, 10, 15, or 20 periods
Slow SMA: 100 or 200 periods
Default: Fast=5, Slow=100
🎯 Entry and Exit Rules
Long Entry Conditions
All conditions must be met:
Price below Fast SMA
Price below 20% of current bar's range
Price above Slow SMA
No existing position
Short Entry Conditions
All conditions must be met:
Price above Fast SMA
Price above 80% of current bar's range
Price below Slow SMA
No existing position
Exit Rules
Long Positions
Exit when price crosses above Fast SMA
No fixed take-profit levels
No stop-loss (mean reversion approach)
Short Positions
Exit when price crosses below Fast SMA
No fixed take-profit levels
No stop-loss (mean reversion approach)
💼 Risk Management
Position Sizing
Default: 10% of equity per trade
Initial capital: $20,000
Commission: 0.01%
Slippage: 2 points
Maximum one position at a time
Risk Control
Use daily timeframe only
Avoid trading during major news events
Consider market conditions
Monitor overall exposure
📊 Performance Dashboard
The strategy includes a comprehensive status table displaying:
Strategy Parameters
Current SMA settings
Trading direction
Fast/Slow SMA ratio
Current Status
Active position (Flat/Long/Short)
Current price with color coding
Position status indicators
Performance Metrics
Net Profit (USD and %)
Win Rate with color grading
Profit Factor with thresholds
Maximum Drawdown percentage
Average Trade value
📱 Alert Settings
Entry Alerts
Long Entry (Buy Signal)
Short Entry (Sell Signal)
Exit Alerts
Long Exit (Take Profit)
Short Exit (Take Profit)
Alert Message Format
Strategy name
Signal type and direction
Current price
Fast SMA value
Slow SMA value
💡 Usage Tips
Consider starting with Long Only mode
Begin with default settings
Keep track of your trades
Review results regularly
Adjust settings as needed
Follow your trading plan
⚠️ Disclaimer
This strategy is for educational and informational purposes only. It is not financial advice. Always:
Conduct your own research
Test thoroughly before live trading
Use proper risk management
Consider your trading goals
Monitor market conditions
Never risk more than you can afford to lose
📋 Release Notes
14 January 2025
Added New Fast & Slow SMA Options:
Fibonacci-based periods: 8, 13, 21, 144, 233, 377
Additional period: 50
Complete Fast SMA options now: 5, 8, 10, 13, 15, 20, 21, 34, 50
Complete Slow SMA options now: 100, 144, 200, 233, 377
Bug Fixes:
Fixed Maximum Drawdown calculation in the performance table
Now using strategy.max_drawdown_percent for accurate DD reporting
Previous version showed incorrect DD values
Performance metrics now accurately reflect trading results
Performance Note:
Strategy tested with Fast/Slow SMA 13/377
Test conducted with 10% equity risk allocation
Daily Timeframe
For Beginners - How to Modify SMA Levels:
Find this line in the code:
fastLength = input.int(title="Fast SMA Length", defval=5, options= )
To add a new Fast SMA period: Add the number to the options list, e.g.,
To remove a Fast SMA period: Remove the number from the options list
For Slow SMA, find:
slowLength = input.int(title="Slow SMA Length", defval=100, options= )
Modify the options list the same way
⚠️ Note: Keep the periods that make sense for your trading timeframe
💡 Tip: Test any new combinations thoroughly before live trading
"Trade with Discipline, Manage Risk, Stay Consistent" - tradeviZion
[LeonidasCrypto]Volume Force IndexVolume Force Index (VFI)
Overview
The Volume Force Index (VFI) is a technical indicator that measures the balance between buying and selling pressure in the market by analyzing volume patterns. It helps traders identify potential trend reversals and confirm trend strength.
What It Measures
Buying vs. selling volume pressure
Market momentum
Potential overbought/oversold conditions
Volume trend strength
How to Read the Indicator
Main Components:
Main Line (Green/Red)
Green: Buying pressure is dominant
Red: Selling pressure is dominant
The steeper the slope, the stronger the pressure
Signal Line (Yellow)
Fast EMA that helps identify trend changes
Acts as an early warning system for potential reversals
Dynamic Bands (Red/Green lines)
Adapt to market volatility
Help identify extreme conditions
Based on actual market volatility rather than fixed levels
Signals to Watch
Trend Direction:
Rising oscillator = Increasing buying pressure
Falling oscillator = Increasing selling pressure
Signal Line Crossovers:
Main line crosses above signal line = Potential bullish signal
Main line crosses below signal line = Potential bearish signal
Band Touches:
Touching upper band = Possible buying exhaustion
Touching lower band = Possible selling exhaustion
Color Changes:
Green to Red = Shift to selling pressure
Red to Green = Shift to buying pressure
Best Practices
When to Use:
Trend confirmation
Identifying potential reversals
Volume analysis
Market strength assessment
Tips:
Use in conjunction with price action
Look for divergences with price
More reliable on higher timeframes
Consider market context
Default Settings:
MA Period: 14 (volume calculation)
Smooth Length: 3 (noise reduction)
EMA Period: 4 (signal line)
Volatility Period: 20 (band calculation)
Volatility Multiplier: 1.5 (band width)
Best Markets to Apply
Any market with reliable volume data
Summary
The VFI is a powerful tool that combines volume analysis with trend identification. Its adaptive nature makes it suitable for various market conditions, but it should be used as part of a complete trading strategy, not in isolation.
Volume profile [Signals] - By Leviathan [Mindyourbuisness]Market Sessions and Volume Profile with Sweep Signals - Based on Leviathan's Volume Profile
This indicator is an enhanced version of Leviathan's Volume Profile indicator, adding session-based value area analysis and sweep detection signals. It combines volume profile analysis with market structure concepts to identify potential reversal opportunities.
Features
- Session-based volume profiles (Daily, Weekly, Monthly, Quarterly, Yearly)
- Forex sessions support (Tokyo, London, New York)
- Value Area analysis with POC, VAH, and VAL levels
- Extended level visualization for the last completed session
- Sweep detection signals for key value area levels
Sweep Signals Explanation
The indicator detects two types of sweeps at VAH, VAL, and POC levels:
Bearish Sweeps (Red Triangle Down)
Conditions:
- Price makes a high above the level (VAH/VAL/POC)
- Closes below the level
- Closes below the previous candle's low
- Previous candle must be bullish
Trading Implication: Suggests a failed breakout and potential reversal to the downside. These sweeps often indicate stop-loss hunting above key levels followed by institutional selling.
Bullish Sweeps (Green Triangle Up)
Conditions:
- Price makes a low below the level (VAH/VAL/POC)
- Closes above the level
- Closes above the previous candle's high
- Previous candle must be bearish
Trading Implication: Suggests a failed breakdown and potential reversal to the upside. These sweeps often indicate stop-loss hunting below key levels followed by institutional buying.
Trading Guidelines
1. Use sweep signals in conjunction with the overall trend
2. Look for additional confirmation like:
- Volume surge during the sweep
- Price action patterns
- Support/resistance levels
3. Consider the session's volatility and time of day
4. More reliable signals often occur at VAH and VAL levels
5. POC sweeps might indicate stronger reversals due to their significance as fair value levels
Notes
- The indicator works best on higher timeframes (1H and above)
- Sweep signals are more reliable during active market hours
- Consider using multiple timeframe analysis for better confirmation
- Past performance is not indicative of future results
Credits: Original Volume Profile indicator by Leviathan
Trendilo ARTrendilo AR is a custom trading indicator designed to identify market trends using advanced techniques such as the Arnaud Legoux Moving Average (ALMA), volume confirmations, and dynamic volatility bands. This indicator provides a clear visualization of trends, including significant changes and custom alerts.
Review of Indicators Used
1. ALMA
Description:
ALMA is a moving average that applies an advanced filter to smooth price data, reducing noise and focusing on actual trends.
Usage in the Indicator:
Used to calculate the smoothed percentage price change and determine trend direction. Customizable parameters include:
- Length: Defines the number of bars to consider.
- Offset: Adjusts sensitivity toward recent prices.
- Sigma: Controls the degree of smoothing.
Advantages:
- Reduced lag in trend detection.
- Resistance to market noise.
2. ATR
Description:
ATR measures the market’s average volatility by considering the range between high and low prices over a given period.
Usage in the Indicator:
ATR is used to calculate "dynamic smoothing", adjusting the indicator’s sensitivity based on current market volatility.
Advantages:
- Adapts to high or low volatility conditions.
- Helps define dynamic support and resistance levels.
3. SMA
Description:
SMA calculates the average of prices or volume over a specific time period.
Usage in the Indicator:
Used to calculate the volume moving average (Volume SMA) to confirm whether the current volume supports the detected trend.
Advantages:
- Easy to understand and calculate.
- Provides volume-based trend confirmation.
4. RMS Bands
Description:
RMS Bands calculate the standard deviation of percentage price changes, creating upper and lower levels that act as overbought and oversold indicators.
Usage in the Indicator:
- Define the range within which the market is considered neutral.
- Crosses above or below the bands indicate trend changes.
Advantages:
- Visual identification of strong trends.
- Helps filter false signals.
Colors and Visuals Used in the Indicator
1. ALMA Line
Colors:
- Green: Indicates a confirmed uptrend (with sufficient volume).
- Red: Indicates a confirmed downtrend (with sufficient volume).
- Gray: Indicates a neutral phase or insufficient volume to confirm a trend.
2. RMS Bands
- Upper and Lower Lines:
- Purple (with transparency): These lines represent the RMS bands (upper and lower) and
adjust opacity based on trend strength.
- Stronger trends result in less transparency (more solid colors).
3. Highlighted Background (Strong Trends)
- Color:
- Light Green (transparent): Highlights a strong trend when the smoothed percentage change (ALMA) exceeds 1.5 times the RMS.
4. Horizontal Lines
- Baseline (0):
- Dark Gray: Serves as a central reference to identify the directionality of percentage changes.
- Additional Line (0.1):
- Blue: A customizable line to mark user-defined key levels.
5. Bar Colors
- Bar Colors:
- Green: When the price is in a confirmed uptrend.
- Red: When the price is in a confirmed downtrend.
- No color: When there is insufficient volume or no clear trend.
How to Use the Indicator
1. Initial Setup
1. Add the Indicator to Your Chart: Copy the code into the Pine Editor on TradingView and apply it to your chart.
2. Customize Parameters: Adjust values based on your trading strategy:
- Smoothing: Controls the level of smoothing for percentage changes.
- Lookback Length: Defines the observation period for calculations.
- Band Multiplier: Adjusts the width of RMS bands.
2. Signal Interpretation
1. Indicator Colors:
- Green: Confirmed uptrend.
- Red: Confirmed downtrend.
- Gray: No clear trend or insufficient volume.
2. RMS Bands:
- If the ALMA line (smoothed percentage change) crosses above the upper RMS band, it signals a potential uptrend.
- If it crosses below the lower RMS band, it signals a potential downtrend.
3. Volume Confirmation:
- The indicator's color activates only if the current volume exceeds the Volume SMA.
3. Alerts and Decisions
1. Trend Change Alerts:
- The indicator automatically triggers alerts when an uptrend or downtrend is detected.
- Configure these alerts to receive real-time notifications.
2. Strong Trend Signals:
- When the magnitude of the percentage change exceeds 1.5 times the RMS, the chart background highlights the strong trend.
4. Trading Strategies
1. Buy:
- Enter long positions when:
- The indicator turns green.
- Volume confirms the trend.
- Consider placing a stop-loss just below the lower RMS band.
2. Sell:
- Enter short positions when:
- The indicator turns red.
- Volume confirms the trend.
- Consider placing a stop-loss just above the upper RMS band.
3. Neutral:
- Avoid trading when the indicator is gray, as no clear trend or insufficient volume is present.
Disclaimer: As this is my first published indicator, please use it with caution. Feedback is highly appreciated to improve its performance.
Happy Trading!
Trend Filter (2-pole) [BigBeluga]Trend Filter (2-pole)
The Trend Filter (2-pole) is an advanced trend-following indicator based on a two-pole filter, which smooths out market noise while effectively highlighting trends and their strength. It incorporates color gradients and support/resistance dots to enhance trend visualization and decision-making for traders.
SP500:
🔵What is a Two-Pole Filter?
A two-pole filter is a digital signal processing technique widely used in electronics, control systems, and time series data analysis to smooth data and reduce noise.
//@function Two-pole filter
//@param src (series float) Source data (e.g., price)
//@param length (float) Length of the filter (higher value means smoother output)
//@param damping (float) Damping factor for the filter
//@returns (series float) Filtered value
method two_pole_filter(float src, int length, float damping) =>
// Calculate filter coefficients
float omega = 2.0 * math.pi / length
float alpha = damping * omega
float beta = math.pow(omega, 2)
// Initialize the filter variables
var float f1 = na
var float f2 = na
// Update the filter
f1 := nz(f1 ) + alpha * (src - nz(f1 ))
f2 := nz(f2 ) + beta * (f1 - nz(f2 ))
f2
It operates using two cascaded smoothing stages (poles), allowing for a more refined and responsive output compared to simple moving averages or other basic filters.
Two-pole filters are particularly valued for their ability to maintain smooth transitions while reducing lag, making them ideal for applications where precision and responsiveness are critical.
In trading, this filter helps detect trends by smoothing price data while preserving significant directional changes.
🔵Key Features of the Indicator:
Gradient-Colored Trend Filter Line: The main filter line dynamically changes color based on trend strength and direction:
- Green: Strong uptrend.
- Red: Strong downtrend.
- Yellow: Indicates a transition phase, signaling potential trend shifts.
Support and Resistance Dots with Signals:
- Dots are plotted below the filter line during uptrends and above it during downtrends.
- These dots represent consecutive rising or falling conditions of the filter line, which traders can set in the settings (e.g., the number of consecutive rises or falls required).
- The dots often act as dynamic support or resistance levels, providing valuable guidance during trends.
- Trend Signals:
Customizable Sensitivity: The indicator allows traders to adjust the filter length, damping factor, and the threshold for rising/falling conditions, enabling it to adapt to different trading styles and timeframes.
Bar Color Option: The indicator can optionally color bars to match the gradient of the filter line, enhancing visual clarity of trends directly on the price chart.
🔵How It Works:
The Trend Filter (2-pole) smooths price data using a two-pole filter, which reduces noise and highlights the underlying trend.
The gradient coloring of the filter line helps traders visually assess the strength and direction of trends.
Rising and falling conditions of the filter line are tracked, and dots are plotted when consecutive conditions meet the threshold, acting as potential support or resistance levels during trends.
The yellow transition color signals periods of indecision, helping traders anticipate potential reversals or consolidations.
🔵Use Cases:
Identify and follow strong uptrends and downtrends with gradient-based visual cues.
Use the yellow transition color to anticipate trend shifts or consolidation zones.
Leverage the plotted dots as dynamic support and resistance levels to refine entry and exit strategies.
Combine with other indicators for confirmation of trends and reversals.
This indicator is perfect for traders who want a visually intuitive and highly customizable tool to spot trends, gauge their strength, and make informed trading decisions.
G. Santostasi's Bimodal Regimes Power Law G. Santostasi's Bimodal Regimes Power Law Model
Invite-Only TradingView Indicator
The Bimodal Power Law Model is a powerful TradingView indicator that provides a detailed visualization of Bitcoin's price behavior relative to its long-term power law trend. By leveraging volatility-normalized deviations, this model uncovers critical upper and lower bounds that govern Bitcoin’s price dynamics.
Key Features:
Power Law Support Line:
The model highlights the power law support line, a natural lower bound that has consistently defined Bitcoin's price floor over time. This line provides a crucial reference point for identifying accumulation zones.
Volatility-Normalized Upper Bound:
The indicator introduces a volatility-normalized upper channel, dynamically defined by the deviations from the power law. This bound represents the natural ceiling for Bitcoin’s price action and adjusts in real time to reflect changes in market volatility.
Color-Shaded Volatility Bounds:
The upper and lower bounds are visualized as color-shaded regions that represent the range of current volatility relative to the power law trend. These shaded regions dynamically expand or contract based on the level of market volatility, providing an intuitive view of Bitcoin’s expected price behavior under normalized conditions.
Two Regime Analysis:
Using a Gaussian Hidden Markov Model (HMM), the indicator separates Bitcoin's price action into two distinct regimes:
Above the power law:
Bullish phases characterized by overextensions.
Below the power law:
Bearish or accumulation phases where price consolidates below the trend.
Dynamic Bounds with Standard Deviations:
The model plots 2 standard deviation bands for both regimes, offering precise insights into the natural limits of Bitcoin’s price fluctuations. Peaks exceeding these bounds are contextualized as anomalies caused by historically higher volatility, emphasizing the consistency of normalized deviations.
Enhanced Visualization and Analysis:
The indicator integrates running averages calculated using deviations from the power law trend and smoothed volatility data to ensure a visually intuitive representation of Bitcoin’s price behavior. These insights help traders and researchers identify when price action is approaching statistically significant levels.
Use Cases:
Support and Resistance Identification:
Use the power law support line and upper volatility bounds to identify critical levels for buying or taking profit.
Cycle Analysis:
Distinguish between sustainable trends and speculative bubbles based on deviations from the power law.
Risk Management:
The shaded volatility regions provide a dynamic measure of risk, helping traders gauge when Bitcoin is overbought or oversold relative to its historical norms.
Market Timing: Understand Bitcoin’s cyclical behavior to time entries and exits based on its position within the shaded bounds.
Note:
This indicator is designed for long-term Bitcoin investors, researchers, and advanced traders who seek to leverage statistical regularities in Bitcoin’s price behavior. Available by invitation only.
