TechniTrend: Dynamic Local Fibonacci LevelsTechniTrend: Dynamic Local Fibonacci Levels
Description: The "Dynamic Local Fibonacci Levels" indicator dynamically displays Fibonacci levels only when the market is experiencing significant volatility. By detecting volatile price movements, this tool helps traders focus on Fibonacci retracement levels that are most relevant during high market activity, reducing noise from calm market periods.
Key Features:
Adaptive Fibonacci Levels: The indicator calculates and plots Fibonacci levels (from 0 to 1) only during periods of high volatility. This helps traders focus on actionable levels during significant price swings.
Customizable Chart Type: Users can choose between Candlestick charts (including shadows) or Line charts (excluding shadows) to determine the high and low price points for Fibonacci level calculations.
Volatility-Based Detection: The Average True Range (ATR) is used to detect significant volatility. Traders can adjust the ATR multiplier to fine-tune the sensitivity of the indicator to price movements.
Fully Customizable Fibonacci Levels: Traders can modify the default Fibonacci levels according to their preferences or trading strategies.
Real-Time Volatility Confirmation: Fibonacci levels are displayed only if the price range between the local high and low exceeds a user-defined volatility threshold, ensuring that these levels are only plotted when the market is truly volatile.
Customization Options:
Chart Type: Select between "Candles (Includes Shadows)" and "Line (Excludes Shadows)" for detecting price highs and lows.
Length for High/Low Detection: Choose the period for detecting the highest and lowest price in the given time frame.
ATR Multiplier for Volatility Detection: Adjust the sensitivity of the volatility threshold by setting the ATR multiplier.
Fibonacci Levels: Customize the specific Fibonacci levels to be displayed, from 0 to 1.
Usage Tips:
Focus on Key Levels During Volatility: This indicator is best suited for periods of high volatility. It can help traders identify potential support and resistance levels that may be more significant in turbulent markets.
Adjust ATR Multiplier: Depending on the asset you're trading, you might want to fine-tune the ATR multiplier to better suit the market conditions and volatility.
Recommended Settings:
ATR Multiplier: 1.5
Fibonacci Levels: Default levels set to 0.00, 0.114, 0.236, 0.382, 0.5, 0.618, 0.786, and 1.0
Length for High/Low Detection: 55
Use this indicator to detect key Fibonacci retracement levels in volatile market conditions and make more informed trading decisions based on price dynamics and volatility.
Cerca negli script per "Volatility"
Inter-Exchanges Crypto Price Spread Clouds (Tartigradia)Display variations in min-max and median values of high, low and close across exchanges. It's a kind of realized volatility indicator, as the idea is that in times of high volatility (high emotions, fear, uncertainty), it's more likely that market inefficiencies will appear for the same asset between different market makers, ie, the price can temporarily differ a lot. This indicator will catch these instants of high differences between exchanges, even if they lasted only an instant (because we use high and low values).
Compared with my other "Inter-Exchanges Crypto Price Spread Deviation" indicator, this one overlays directly on the chart, and offers a different take based on the same premisses. Instead of summarizing volatility via standard deviation, here we display clouds of the range of values that were observed.
A big advantage of this approach is that it can also be used to determine safe stop loss levels, especially the values of percentile rank (i.e., what are the high values that were observed in at least 50% of exchanges?).
Indeed, all price levels are displayed in the indicator's status bar:
green for high values,
red for low values,
aqua for median,
purple for average,
The first two values are max and min values of high across exchanges (in green).
The next two values are max and min of low across exchanges (in red).
The next two values are median (aqua) and average (purple).
The last two values are percentile rank values for high (green) and low (red) respectively.
Another advantage is that the high (green) vs low (red) clouds can be seen as representing the buying or selling pressure respectively across exchanges, and this may in itself provide a signal to know whether one side is winning.
Link to my other complementary indicator:
Compared to other inter-exchanges spread indicators, this one offers two major features:
The symbol automatically adapts to the symbol currently selected in user's chart. Hence, switching between tickers does not require the user to modify any option, everything is dynamically updated behind the scenes.
It's easy to add more exchanges (requires some code editing because PineScript v5 does not allow dynamical request.security() calls).
Limitations/things to know:
History is limited to what the ticker itself display. Ie, even if the exchanges specified in this indicator have more data than the ticker currently displayed in the user's chart, the indicator will show only a timeperiod as long as the chart.
The indicator can manage multiple exchanges of different historical length (ie, some exchanges having more data going way earlier in the past than others), in which case they will simply be ignored from calculations when far back in the past. Hence, you should be aware that the further you go in the past, the less exchanges will have such data, and hence the less accurate the measures will be (because the deviation will be calculated from less sources than more recent bars). This is thanks to how the array.* math functions behave in case of na values, they simply skip them from calculations, contrary to math.* functions.
Advanced Trend and Volatility Indicator with Alerts by ZaimonThis script presents a comprehensive analytical tool that integrates multiple technical indicators to provide a holistic view of market trends and volatility. By uniquely combining Moving Averages (MA), Relative Strength Index (RSI), Stochastic Oscillator, Bollinger Bands, and Average True Range (ATR), it offers nuanced insights into price movements and helps identify potential trading opportunities.
---
### **Key Features and Integration:**
1. **Moving Averages (MA20 & MA50):**
- **Trend Identification:**
- **Methodology:** Calculates two Simple Moving Averages—MA20 (short-term) and MA50 (long-term).
- **Bullish Trend:** When MA20 crosses above MA50, indicating upward momentum.
- **Bearish Trend:** When MA20 crosses below MA50, signaling downward momentum.
- **Golden Cross & Death Cross Alerts:**
- **Golden Cross:** MA20 crossing above MA50 generates a bullish alert and visual symbol.
- **Death Cross:** MA20 crossing below MA50 triggers a bearish alert and visual symbol.
- **Integration:**
- Serves as the foundational trend indicator, influencing interpretations of other indicators within the script.
2. **Relative Strength Index (RSI):**
- **Momentum Measurement:**
- **Methodology:** Calculates RSI to assess the speed and change of price movements over a 14-period length.
- **Overbought/Oversold Conditions:** Customizable thresholds set at 70 (overbought) and 30 (oversold).
- **Alerts:**
- Generates alerts when RSI crosses above or below the specified thresholds.
- **Integration:**
- Confirms trend strength identified by MAs.
- Overbought/Oversold signals can precede potential trend reversals, especially when aligned with MA crossovers.
3. **Stochastic Oscillator:**
- **Momentum and Reversal Signals:**
- **Methodology:** Uses %K and %D lines to evaluate price momentum relative to high-low range over recent periods.
- **Bullish Signal:** %K crossing above %D in oversold territory (below 20).
- **Bearish Signal:** %K crossing below %D in overbought territory (above 80).
- **Alerts:**
- Provides alerts on bullish and bearish crossovers in extreme regions.
- **Integration:**
- Enhances RSI signals by providing additional momentum confirmation.
- When both RSI and Stochastic indicate overbought/oversold conditions, it strengthens the likelihood of a reversal.
4. **Bollinger Bands:**
- **Volatility Visualization:**
- **Methodology:** Plots upper and lower bands based on standard deviations from a moving average (BB Basis).
- **Dynamic Support/Resistance:** Prices touching or exceeding the bands may indicate potential reversals.
- **Integration:**
- Works with RSI and Stochastic to identify overextended price movements.
- Helps in assessing volatility alongside trend and momentum indicators.
5. **Average True Range (ATR):**
- **Volatility Assessment:**
- **Methodology:** Calculates ATR over a 14-period length to measure market volatility.
- **ATR Bands:** Plots upper and lower bands relative to the current price using an ATR multiplier.
- **Integration:**
- Assists in setting stop-loss and take-profit levels based on current volatility.
- Complements Bollinger Bands for a comprehensive volatility analysis.
6. **Information Table:**
- **Real-Time Data Display:**
- Shows current values of MA20, MA50, RSI, Stochastic %K and %D, BB Basis, ATR, and Trend Status.
- **Trend Status Indicator:**
- Displays "Bullish," "Bearish," or "Sideways" based on MA conditions.
- **Integration:**
- Provides a consolidated view for quick decision-making without analyzing individual indicators separately.
7. **Periodic Labels:**
- **Enhanced Visibility:**
- Adds labels every 50 bars showing RSI and Stochastic values.
- **Integration:**
- Helps track momentum changes over time and spot longer-term patterns.
---
### **How the Components Work Together:**
- **Synergistic Analysis:**
- **Trend Confirmation:** MA crossovers establish the primary trend, while RSI and Stochastic confirm momentum within that trend.
- **Volatility Context:** Bollinger Bands and ATR provide context on market volatility, refining entry and exit points suggested by trend and momentum indicators.
- **Signal Strength:** Concurrent signals from multiple indicators increase confidence in trading decisions.
---
### **Usage Guidelines:**
1. **Trend Analysis:**
- **Identify Trend Direction:**
- Observe MA20 and MA50 crossovers.
- Refer to the Trend Status in the information table.
- **Confirm with Momentum Indicators:**
- Ensure RSI and Stochastic support the identified trend.
2. **Entry and Exit Points:**
- **Overbought/Oversold Conditions:**
- Look for RSI and Stochastic reaching extreme levels.
- Consider entering positions when oversold in a bullish trend or overbought in a bearish trend.
- **Bollinger Band Interactions:**
- Use price interactions with Bollinger Bands to identify potential reversal zones.
3. **Risk Management:**
- **ATR-Based Levels:**
- Set stop-loss and take-profit levels using ATR bands to account for current volatility.
- **Adjusting to Volatility:**
- Modify position sizes and targets based on Bollinger Band width and ATR values.
4. **Alerts Setup:**
- **Customize Alert Thresholds:**
- Configure alerts for MA crossovers, RSI levels, and Stochastic crossovers according to your trading strategy.
- **Stay Informed:**
- Use alerts to monitor key events without constant chart observation.
---
### **Customization:**
- **Flexible Parameters:**
- All indicator lengths, thresholds, and settings are adjustable to suit different trading styles and timeframes.
- **Adjustable Visuals:**
- Modify plot colors, line styles, and label positions to enhance chart readability.
---
### **Originality and Value Addition:**
This script differentiates itself by:
- **Integrated Approach:**
- Seamlessly combining multiple indicators to provide a more comprehensive analysis than using each indicator separately.
- **Enhanced Visualization:**
- Utilizing plots, fills, labels, and an information table to present data intuitively.
- **User-Friendly Features:**
- Pre-configured alerts and real-time data displays reduce the need for manual monitoring.
By explaining how each component interacts and contributes to the overall analysis, the script adds substantial value to traders seeking a multi-faceted tool for market analysis.
---
### **Additional Notes:**
- **Learning Resource:**
- The script is well-commented, serving as an educational tool for those learning Pine Script and technical analysis integration.
- **Further Enhancements:**
- Opportunities exist to incorporate additional indicators like MACD or ADX, and to develop advanced alert logic, such as RSI or Stochastic divergences.
---
### **Disclaimer:**
- **Educational Purpose Only:**
- This script is provided for informational purposes and should not be construed as financial advice.
- **Risk Acknowledgment:**
- Trading involves significant risk; past performance is not indicative of future results.
- **Due Diligence:**
- Users should conduct their own analysis and consider consulting a financial professional before making trading decisions.
---
By providing detailed explanations of the methodologies and the synergistic use of multiple indicators, this script aligns with TradingView's guidelines for originality and usefulness. It offers traders a unique tool that enhances market analysis through the thoughtful integration of technical indicators.
Strategy Myth-Busting #11 - TrendMagic+SqzMom+CDV - [MYN]This is part of a new series we are calling "Strategy Myth-Busting" where we take open public manual trading strategies and automate them. The goal is to not only validate the authenticity of the claims but to provide an automated version for traders who wish to trade autonomously.
Our 11th one is an automated version of the "Magic Trading Strategy : Most Profitable Indicator : 1 Minute Scalping Strategy Crypto" strategy from "Fx MENTOR US" who doesn't make any official claims but given the indicators he was using, it looked like on the surface that this might actually work. The strategy author uses this on the 1 minute and 3 minute timeframes on mostly FOREX and Heiken Ashi candles but as the title of his strategy indicates is designed for Crypto. So who knows..
To backtest this accurately and get a better picture we resolved the Heiken Ashi bars to standard candlesticks . Even so, I was unable to sustain any consistency in my results on either the 1 or 3 min time frames and both FOREX and Crypto. 10000% Busted.
This strategy uses a combination of 3 open-source public indicators:
Trend Magic by KivancOzbilgic
Squeeze Momentum by LazyBear
Cumulative Delta Volume by LonesomeTheBlue
Trend Magic consists of two main indicators to validate momentum and volatility. It uses an ATR like a trailing Stop to determine the overarching momentum and CCI as a means to validate volatility. Together these are used as the primary indicator in this strategy. When the CCI is above 0 this is confirmation of a volatility event is occurring with affirmation based upon current momentum (ATR).
The CCI volatility indicator gets confirmation by the the Cumulative Delta Volume indicator which calculates the difference between buying and selling pressure. Volume Delta is calculated by taking the difference of the volume that traded at the offer price and the volume that traded at the bid price. The more volume that is traded at the bid price, the more likely there is momentum in the market.
And lastly the Squeeze Momentum indicator which uses a combination of Bollinger Bands, Keltner Channels and Momentum are used to again confirm momentum and volatility. During periods of low volatility, Bollinger bands narrow and trade inside Keltner channels. They can only contract so much before it can’t contain the energy it’s been building. When the Bollinger bands come back out, it explodes higher. When we see the histogram bar exploding into green above 0 that is a clear confirmation of increased momentum and volatile. The opposite (red) below 0 is true when there are low periods. This indicator is used as a means to really determine when there is premium selling plays going on leading to big directional movements again confirming the positive or negative momentum and volatility direction.
If you know of or have a strategy you want to see myth-busted or just have an idea for one, please feel free to message me.
Trading Rules
1 - 3 min candles
FOREX or Crypto
Stop loss at swing high/low | 1.5 risk/ratio
Long Condition
Trend Magic line is Blue ( CCI is above 0) and above the current close on the bar
Squeeze Momentum's histogram bar is green/lime
Cumulative Delta Volume line is green
Short Condition
Trend Magic line is Red ( CCI is below 0) and below the current close on the bar
Squeeze Momentum's histogram bar is red/maroon
Cumulative Delta Volume line is peach
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.
Information Asymmetry Gradient (IAG) What is the Information Asymmetry Gradient (IAG)?
The Information Asymmetry Gradient (IAG) is a unique market regime and imbalance detector that quantifies the subtle, directional “information flow” in price and volume. Inspired by information theory and market microstructure, IAG is designed to help traders spot the early buildup of conviction or surprise—the kind of hidden imbalance that often precedes major price moves.
Unlike traditional volume or momentum indicators, IAG focuses on the efficiency and directionality of information transfer: how much “informational energy” is being revealed by up-moves versus down-moves, normalized by price movement. It’s not just about net flow, but about the quality and asymmetry of that flow.
Theoretical Foundation
Information Asymmetry: Markets move when new information is revealed. If one side (buyers or sellers) is consistently more “informationally efficient” per unit of price change, an imbalance is building—even if price hasn’t moved much yet.
Gradient: By tracking the rate of change (gradient) between fast and slow information flows, IAG highlights when a subtle imbalance is accelerating.
Volatility of Asymmetry: Sudden spikes in the volatility of information asymmetry often signal regime uncertainty or the approach of a “surprise” move.
How IAG Works
Directional Information Content: For each bar, IAG estimates the “information per unit of price change” for both up-moves and down-moves, using volume and price action.
Asymmetry Calculation: Computes the difference (or ratio) between up and down information content, revealing directional bias.
Gradient Detection: Calculates both a fast and slow EMA of the asymmetry, then measures their difference (the “gradient”), normalized as a Z-score.
Volatility of Asymmetry: Tracks the standard deviation of asymmetry over a rolling window, with Z-score normalization to spot “information shocks.”
Flow Strength: Quantifies the conviction of the current information flow on a 0–100 scale.
Regime Detection: Flags “extreme” asymmetry, “building” flow, and “high volatility” states.
Inputs:
🌌 Core Asymmetry Parameters
Fast Information Period (short_len, default 8): EMA period for detecting immediate information flow changes.
5–8: Scalping (1–5min)
8–12: Day trading (15min–1hr)
12–20: Swing trading (4hr+)
Slow Information Period (long_len, default 34): EMA period for baseline information context. Should be 3–5x fast period.
Default (34): Fibonacci number, stable for most assets.
Gradient Smoothing (gradient_smooth, default 3): Smooths the gradient calculation.
1–2: Raw, responsive
3–5: Balanced
6–10: Very smooth
📊 Asymmetry Method
Calculation Mode (calc_mode, default "Weighted"):
“Simple”: Basic volume split by direction
“Weighted”: Volume × price movement (default, most robust)
“Logarithmic”: Log-scaled for large moves
Use Ratio (show_ratio, default false):
“Difference”: UpInfo – DownInfo (additive)
“Ratio”: UpInfo / DownInfo (multiplicative, better for comparing volatility regimes)
🌊 Volatility Analysis
Volatility Window (stdev_len, default 21): Lookback for measuring asymmetry volatility.
Volatility Alert Level (vol_threshold, default 1.5): Z-score threshold for volatility alerts.
🎨 Visual Settings
Color Theme (color_theme, default "Starry Night"):
Van Gogh-inspired palettes:
“Starry Night”: Deep blues and yellows
“Sunflowers”: Warm yellows and browns
“Café Terrace”: Night blues and warm lights
“Wheat Field”: Golden and sky blue
Show Swirl Effects (show_swirls, default true): Adds swirling background to visualize information turbulence.
Show Signal Stars (show_stars, default true): Star markers at significant asymmetry points.
Show Info Dashboard (show_dashboard, default true): Top-right panel with current metrics and market state.
Show Flow Visualization (show_flow, default true): Main gradient line with artistic effects.
Color Schemes
Dynamic color gradients adapt to both the direction and intensity of the information gradient, using Van Gogh-inspired palettes for visual clarity and artistic flair.
Glow and aura effects: The main line is layered with glows for depth and to highlight strong signals.
Swirl background: Visualizes the “turbulence” of information flow, darker and more intense as flow strength and volatility rise.
Visual Logic
Main Gradient Line: Plots the normalized information gradient (Z-score), color-coded by direction and intensity.
Glow/Aura: Multiple layers for visual depth and to highlight strong signals.
Threshold Zones: Dotted lines and filled areas mark “Building” and “Extreme” asymmetry zones.
Volatility Ribbon: Area plot of volatility Z-score, highlighting information shocks.
Signal Stars: Circular markers at each “Extreme” event, color-coded for bullish/bearish; cross markers for volatility spikes.
Dashboard: Top-right panel shows current status (Extreme, Building, High Volatility, Balanced), gradient value, flow strength, information balance, and volatility status.
Trading Guide: Bottom-left panel explains all states and how to interpret them.
How to Use IAG
🌟 EXTREME: Major information imbalance—potential for explosive move or reversal.
🌙 BUILDING: Asymmetry is forming—watch for a breakout or trend acceleration.
🌪️ HIGH VOLATILITY: Information flow is unstable—expect regime uncertainty or “surprise” moves.
☁️ BALANCED: No clear bias—market is in equilibrium.
Positive Gradient: Bullish information flow (buyers have the edge).
Negative Gradient: Bearish information flow (sellers have the edge).
Flow >66%: Strong conviction—crowd is acting in unison.
Volatility Spike: Regime uncertainty—be alert for sudden moves.
Tips:
- Use lower periods for scalping, higher for swing trading.
- “Weighted” mode is most robust for most assets.
- Combine with price action or your own system for confirmation.
- Works on all assets and timeframes—tune to your style.
Alerts
IAG Extreme Asymmetry: Extreme information asymmetry detected.
IAG Building Flow: Information flow building.
IAG High Volatility: Information volatility spike.
IAG Bullish/Bearish Extreme: Directional extreme detected.
Originality & Usefulness
IAG is not a mashup of existing indicators. It is a novel approach to quantifying the “surprise” or “conviction” element in market moves, focusing on the efficiency and directionality of information transfer per unit of price change. The multi-layered color logic, artistic visual effects, and regime dashboard are unique to this script. IAG is designed for anticipation, not confirmation—helping you see subtle imbalances before they become obvious in price.
Chart Info
Script Name: Information Asymmetry Gradient (IAG) – Starry Night
Recommended Use: Any asset, any timeframe. Tune parameters to your style.
Disclaimer
This script is for research and educational purposes only. It does not provide financial advice or direct buy/sell signals. Always use proper risk management and combine with your own strategy. Past performance is not indicative of future results.
Trade with insight. Trade with anticipation.
— Dskyz , for DAFE Trading Systems
Dual-Phase Trend Regime Oscillator (Zeiierman)█ Overview
Trend Regime: Dual-Phase Oscillator (Zeiierman) is a volatility-sensitive trend classification tool that dynamically switches between two oscillators, one optimized for low volatility, the other for high volatility.
By analyzing standard deviation-based volatility states and applying correlation-derived oscillators, this indicator reveals not only whether the market is trending but also what kind of trend regime it is in —Bullish or Bearish —and how that regime reacts to market volatility.
█ Its Uniqueness
Most trend indicators assume a static market environment; they don't adjust their logic when the underlying volatility shifts. That often leads to false signals in choppy conditions or late entries in trending phases.
Trend Regime: Dual-Phase Oscillator solves this by introducing volatility-aware adaptability. It switches between a slow, stable oscillator in calm markets and a fast, reactive oscillator in volatile ones, ensuring the right sensitivity at the right time.
█ How It Works
⚪ Volatility State Engine
Calculates returns-based volatility using standard deviation of price change
Smooths the current volatility with a moving average
Builds a volatility history window and performs median clustering to determine typical "Low" and "High" volatility zones
Dynamically assigns the chart to one of two internal volatility regimes: Low or High
⚪ Dual Oscillators
In Low Volatility, it uses a Slow Trend Oscillator (longer lookback, smoother)
In High Volatility, it switches to a Fast Trend Oscillator (shorter lookback, responsive)
Both oscillators use price-time correlation as a measure of directional strength
The output is normalized between 0 and 1, allowing for consistent interpretation
⚪ Trend Regime Classification
The active oscillator is compared to a neutral threshold (0.5)
If above: Bullish Regime, if below: Bearish Regime, else: Neutral
The background and markers update to reflect regime changes visually
Triangle markers highlight bullish/bearish regime shifts
█ How to Use
⚪ Identify Current Trend Regime
Use the background color and chart table to immediately recognize whether the market is trending up or down.
⚪ Trade Regime Shifts
Use triangle markers (▲ / ▼) to spot fresh regime entries, which are ideal for confirming breakouts within trends.
⚪ Pullback Trading
Look for pullbacks when the trend is in a stable condition and the slow oscillator remains consistently near the upper or lower threshold. Watch for moments when the fast oscillator retraces back toward the midline, or slightly above/below it — this often signals a potential pullback entry in the direction of the prevailing trend.
█ Settings Explained
Length (Slow Trend Oscillator) – Used in calm conditions. Longer = smoother signals
Length (Fast Trend Oscillator) – Used in volatile conditions. Shorter = more responsive
Volatility Refit Interval – Controls how often the system recalculates Low/High volatility levels
Current Volatility Period – Lookback used for immediate volatility measurement
Volatility Smoothing Length – Applies an SMA to the raw volatility to reduce noise
-----------------
Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Zero Lag Trend Signals (MTF) [AlgoAlpha]Zero Lag Trend Signals 🚀📈
Ready to take your trend-following strategy to the next level? Say hello to Zero Lag Trend Signals , a precision-engineered Pine Script™ indicator designed to eliminate lag and provide rapid trend insights across multiple timeframes. 💡 This tool blends zero-lag EMA (ZLEMA) logic with volatility bands, trend-shift markers, and dynamic alerts. The result? Timely signals with minimal noise for clearer decision-making, whether you're trading intraday or on longer horizons. 🔄
🟢 Zero-Lag Trend Detection : Uses a zero-lag EMA (ZLEMA) to smooth price data while minimizing delay.
⚡ Multi-Timeframe Signals : Displays trends across up to 5 timeframes (from 5 minutes to daily) on a sleek table.
📊 Volatility-Based Bands : Adaptive upper and lower bands, helping you identify trend reversals with reduced false signals.
🔔 Custom Alerts : Get notified of key trend changes instantly with built-in alert conditions.
🎨 Color-Coded Visualization : Bullish and bearish signals pop with clear color coding, ensuring easy chart reading.
⚙️ Fully Configurable : Modify EMA length, band multiplier, colors, and timeframe settings to suit your strategy.
How to Use 📚
⭐ Add the Indicator : Add the indicator to favorites by pressing the star icon. Set your preferred EMA length and band multiplier. Choose your desired timeframes for multi-frame trend monitoring.
💻 Watch the Table & Chart : The top-right table dynamically updates with bullish or bearish signals across multiple timeframes. Colored arrows on the chart indicate potential entry points when the price crosses the ZLEMA with confirmation from volatility bands.
🔔 Enable Alerts : Configure alerts for real-time notifications when trends shift—no need to monitor charts constantly.
How It Works 🧠
The script calculates the zero-lag EMA (ZLEMA) by compensating for data lag, giving traders more responsive moving averages. It checks for volatility shifts using the Average True Range (ATR), multiplied to create upper and lower deviation bands. If the price crosses above or below these bands, it marks the start of new trends. Additionally, the indicator aggregates trend data from up to five configurable timeframes and displays them in a neat summary table. This helps you confirm trends across different intervals—ideal for multi-timeframe analysis. The visual signals include upward and downward arrows on the chart, denoting potential entries or exits when trends align across timeframes. Traders can use these cues to make well-timed trades and avoid lag-related pitfalls.
$TUBR: Stop Loss IndicatorATR-Based Stop Loss Indicator for TradingView by The Ultimate Bull Run Community: TUBR
**Overview**
The ATR-Based Stop Loss Indicator is a custom tool designed for traders using TradingView. It helps you determine optimal stop loss levels by leveraging the Average True Range (ATR), a popular measure of market volatility. By adapting to current market conditions, this indicator aims to minimize premature stop-outs and enhance your risk management strategy.
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**Key Features**
- **Dynamic Stop Loss Levels**: Calculates stop loss prices based on the ATR, providing both long and short stop loss suggestions.
- **Customizable Parameters**: Adjust the ATR period, multiplier, and smoothing method to suit your trading style and the specific instrument you're trading.
- **Visual Aids**: Plots stop loss lines directly on your chart for easy visualization.
- **Alerts and Notifications** (Optional): Set up alerts to notify you when the price approaches or hits your stop loss levels.
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**Understanding the Indicator**
1. **Average True Range (ATR)**:
- **What It Is**: ATR measures market volatility by calculating the average range between high and low prices over a specified period.
- **Why It's Useful**: A higher ATR indicates higher volatility, which can help you set stop losses that accommodate market fluctuations.
2. **ATR Multiplier**:
- **Purpose**: Determines how far your stop loss is placed from the current price based on the ATR.
- **Example**: An ATR multiplier of 1.5 means the stop loss is set at 1.5 times the ATR away from the current price.
3. **Smoothing Methods**:
- **Options**: Choose from RMA (default), SMA, EMA, WMA, or Hull MA.
- **Effect**: Different smoothing methods can make the ATR more responsive or smoother, affecting where the stop loss is placed.
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**How the Indicator Works**
- **Long Stop Loss Calculation**:
- **Formula**: `Long Stop Loss = Close Price - (ATR * ATR Multiplier)`
- **Purpose**: For long positions, the stop loss is set below the current price to protect against downside risk.
- **Short Stop Loss Calculation**:
- **Formula**: `Short Stop Loss = Close Price + (ATR * ATR Multiplier)`
- **Purpose**: For short positions, the stop loss is set above the current price to protect against upside risk.
- **Plotting on the Chart**:
- **Green Line**: Represents the suggested stop loss level for long positions.
- **Red Line**: Represents the suggested stop loss level for short positions.
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**How to Use the Indicator**
1. **Adding the Indicator to Your Chart**:
- **Step 1**: Copy the PineScript code of the indicator.
- **Step 2**: In TradingView, click on **Pine Editor** at the bottom of the platform.
- **Step 3**: Paste the code into the editor and click **Add to Chart**.
- **Step 4**: The indicator will appear on your chart with the default settings.
2. **Adjusting the Settings**:
- **ATR Period**:
- **Definition**: Number of periods over which the ATR is calculated.
- **Adjustment**: Increase for a smoother ATR; decrease for a more responsive ATR.
- **ATR Multiplier**:
- **Definition**: Factor by which the ATR is multiplied to set the stop loss distance.
- **Adjustment**: Increase to widen the stop loss (less likely to be hit); decrease to tighten the stop loss.
- **Smoothing Method**:
- **Options**: RMA, SMA, EMA, WMA, Hull MA.
- **Adjustment**: Experiment to see which method aligns best with your trading strategy.
- **Display Options**:
- **Show Long Stop Loss**: Toggle to display or hide the long stop loss line.
- **Show Short Stop Loss**: Toggle to display or hide the short stop loss line.
3. **Interpreting the Indicator**:
- **Long Positions**:
- **Action**: Set your stop loss at the value indicated by the green line when entering a long trade.
- **Short Positions**:
- **Action**: Set your stop loss at the value indicated by the red line when entering a short trade.
- **Adjusting Stop Losses**:
- **Trailing Stops**: You may choose to adjust your stop loss over time, moving it in the direction of your trade as the ATR-based stop loss levels change.
4. **Implementing in Your Trading Strategy**:
- **Risk Management**:
- **Position Sizing**: Use the stop loss distance to calculate your position size based on your risk tolerance.
- **Consistency**: Apply the same settings consistently to maintain discipline.
- **Combining with Other Indicators**:
- **Enhance Decision-Making**: Use in conjunction with trend indicators, support and resistance levels, or other technical analysis tools.
- **Alerts Setup** (If included in the code):
- **Purpose**: Receive notifications when the price approaches or hits your stop loss level.
- **Configuration**: Set up alerts in TradingView based on the alert conditions defined in the indicator.
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**Benefits of Using This Indicator**
- **Adaptive Risk Management**: By accounting for current market volatility, the indicator helps prevent setting stop losses that are too tight or too wide.
- **Minimize Premature Stop-Outs**: Reduces the likelihood of being stopped out due to normal price fluctuations.
- **Flexibility**: Customizable settings allow you to tailor the indicator to different trading instruments and timeframes.
- **Visualization**: Clear visual representation of stop loss levels aids in quick decision-making.
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**Things to Consider**
- **Market Conditions**:
- **High Volatility**: Be cautious as ATR values—and thus stop loss distances—can widen, increasing potential losses.
- **Low Volatility**: Tighter stop losses may increase the chance of being stopped out by minor price movements.
- **Backtesting and Optimization**:
- **Historical Analysis**: Test the indicator on past data to evaluate its effectiveness and adjust settings accordingly.
- **Continuous Improvement**: Regularly reassess and fine-tune the parameters to adapt to changing market conditions.
- **Risk Per Trade**:
- **Alignment with Risk Tolerance**: Ensure the stop loss level keeps potential losses within your acceptable risk per trade (e.g., 1-2% of your trading capital).
- **Emotional Discipline**:
- **Stick to Your Plan**: Avoid making impulsive changes to your stop loss levels based on emotions rather than analysis.
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**Example Usage Scenario**
1. **Setting Up a Long Trade**:
- **Entry Price**: $100
- **ATR Value**: $2
- **ATR Multiplier**: 1.5
- **Calculated Stop Loss**: $100 - ($2 * 1.5) = $97
- **Action**: Place a stop loss order at $97.
2. **During the Trade**:
- **Price Increases to $105**
- **ATR Remains at $2**
- **New Stop Loss Level**: $105 - ($2 * 1.5) = $102
- **Action**: Move your stop loss up to $102 to lock in profits.
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**Final Tips**
- **Documentation**: Keep a trading journal to record your trades, stop loss levels, and observations for future reference.
- **Education**: Continuously educate yourself on risk management and technical analysis to enhance your trading skills.
- **Support**: Engage with trading communities or seek professional advice if you're unsure about implementing the indicator effectively.
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**Conclusion**
The ATR-Based Stop Loss Indicator is a valuable tool for traders looking to enhance their risk management by setting stop losses that adapt to market volatility. By integrating this indicator into your trading routine, you can improve your ability to protect capital and potentially increase profitability. Remember to use it as part of a comprehensive trading strategy, and always adhere to sound risk management principles.
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**How to Access the Indicator**
To start using the ATR-Based Stop Loss Indicator, follow these steps:
1. **Obtain the Code**: Copy the PineScript code provided for the indicator.
2. **Create a New Indicator in TradingView**:
- Open TradingView and navigate to the **Pine Editor**.
- Paste the code into the editor.
- Click **Save** and give your indicator a name.
3. **Add to Chart**: Click **Add to Chart** to apply the indicator to your current chart.
4. **Customize Settings**: Adjust the input parameters to suit your preferences and start integrating the indicator into your trading strategy.
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**Disclaimer**
Trading involves significant risk, and it's possible to lose all your capital. The ATR-Based Stop Loss Indicator is a tool to aid in decision-making but does not guarantee profits or prevent losses. Always conduct your own analysis and consider seeking advice from a financial professional before making trading decisions.
Coiled Moving AveragesThis indicator detects when 3 moving averages converge and become coiled. This indicates volatility contraction which often leads to volatility expansion, i.e. large price movements.
Moving averages are considered coiled when the percent difference from each moving average to the others is less than the Coil Tolerance % input value.
This indicator is unique in that it detects when moving averages converge within a specified percent range. This is in contrast to other indicators that only detect moving average crossovers, or the distance between price and a moving average.
This indicator includes options such as:
- % difference between the MAs to be considered coiled
- type and length of MAs
- background color to indicate when the MAs are coiled
- arrows to indicate if price is above or below the MAs when they become coiled
While coiling predicts an increased probability for volatility expansion, it does not necessarily predict the direction of expansion. However, the arrows which indicate whether price is above or below the moving average coil may increase the odds of a move in that direction. Bullish alignment of the moving averages (faster MAs above the slower MAs) may also increase the odds of a bullish break, while bearish alignment may increase the odds of a bearish break.
Note that mean reversion back to the MA coil is common after initial volatility expansion. This can present an entry opportunity for traders, as mean reversion may be followed by continuation in the direction of the initial break.
Experiment with different settings and timeframes to see how coiled MAs can help predict the onset of volatility.
Williams Vix Fix ultra complete indicator (Tartigradia)Williams VixFix is a realized volatility indicator developed by Larry Williams, and can help in finding market bottoms.
Indeed, as Williams describe in his paper, markets tend to find the lowest prices during times of highest volatility, which usually accompany times of highest fear. The VixFix is calculated as how much the current low price statistically deviates from the maximum within a given look-back period.
Although the VixFix originally only indicates market bottoms, its inverse may indicate market tops. As masa_crypto writes : "The inverse can be formulated by considering "how much the current high value statistically deviates from the minimum within a given look-back period." This transformation equates Vix_Fix_inverse. This indicator can be used for finding market tops, and therefore, is a good signal for a timing for taking a short position." However, in practice, the Inverse VixFix is much less reliable than the classical VixFix, but is nevertheless a good addition to get some additional context.
For more information on the Vix Fix, which is a strategy published under public domain:
* The VIX Fix, Larry Williams, Active Trader magazine, December 2007, web.archive.org
* Fixing the VIX: An Indicator to Beat Fear, Amber Hestla-Barnhart, Journal of Technical Analysis, March 13, 2015, ssrn.com
* Replicating the CBOE VIX using a synthetic volatility index trading algorithm, Dayne Cary and Gary van Vuuren, Cogent Economics & Finance, Volume 7, 2019, Issue 1, doi.org
Created By ChrisMoody on 12-26-2014...
V3 MAJOR Update on 1-05-2014
tista merged LazyBear's Black Dots filter in 2020:
Extended by Tartigradia in 10-2022:
* Can select a symbol different from current to calculate vixfix, allows to select SP:SPX to mimic the original VIX index.
* Inverse VixFix (from masa_crypto and web.archive.org)
* VixFix OHLC Bars plot
* Price / VixFix Candles plot (Pro Tip: draw trend lines to find good entry/exit points)
* Add ADX filtering, Minimaxis signals, Minimaxis filtering (from samgozman )
* Convert to pinescript v5
* Allow timeframe selection (MTF)
* Skip off days (more accurate reproduction of original VIX)
* Reorganized, cleaned up code, commented out parts, commented out or removed unused code (eg, some of the KC calculations)
* Changed default Bollinger Band settings to reduce false positives in crypto markets.
Set Index symbol to SPX, and index_current = false, and timeframe Weekly, to reproduce the original VIX as close as possible by the VIXFIX (use the Add Symbol option, because you want to plot CBOE:VIX on the same timeframe as the current chart, which may include extended session / weekends). With the Weekly timeframe, off days / extended session days should not change much, but with lower timeframes this is important, because nights and weekends can change how the graph appears and seemingly make them different because of timing misalignment when in reality they are not when properly aligned.
Anchored Geometric Brownian Motion Projections w/EVAnchored GBM (Geometric Brownian Motion) Projections + EV & Confidence Bands
Version: Pine Script v6
Overlay: Yes
Author:
Published On:
Overview
The Anchored GBM Projections + EV & Confidence Bands indicator leverages the Geometric Brownian Motion (GBM) model to project future price movements based on historical data. By simulating multiple potential future price paths, it provides traders with insights into possible price trajectories, their expected values, and confidence intervals. Additionally, it offers a "Mean of EV" (EV of EV) line, representing the running average of expected values across the projection period.
Key Features
Anchor Time Setup:
Define a specific point in time from which the projections commence.
By default, it uses the current bar's timestamp but can be customized.
Projection Parameters:
Projection Candles (Bars): Determines the number of future bars (time periods) to project.
Number of Simulations: Specifies how many GBM paths to simulate, ensuring statistical relevance via the Central Limit Theorem (CLT).
Display Toggles:
Simulation Lines: Visual representation of individual GBM simulation paths.
Expected Value (EV) Line: The average price across all simulations at each projection bar.
Upper & Lower Confidence Bands: 95% confidence intervals indicating potential price boundaries.
EV of EV Line: Running average of EV values, providing a smoothed central tendency across the projection period. Additionally, this line often acts as an indicator of trend direction.
Visualization:
Clear and distinguishable lines with customizable colors and styles.
Overlayed on the price chart for direct comparison with actual price movements.
Mathematical Foundation
Geometric Brownian Motion (GBM):
Definition: GBM is a continuous-time stochastic process used to model stock prices. It assumes that the logarithm of the stock price follows a Brownian motion with drift.
Equation:
S(t)=S0⋅e(μ−12σ2)t+σW(t)
S(t)=S0⋅e(μ−21σ2)t+σW(t) Where:
S(t)S(t) = Stock price at time tt
S0S0 = Initial stock price
μμ = Drift coefficient (average return)
σσ = Volatility coefficient (standard deviation of returns)
W(t)W(t) = Wiener process (standard Brownian motion)
Drift (μμ) and Volatility (σσ):
Drift (μμ) represents the expected return of the stock.
Volatility (σσ) measures the stock's price fluctuation intensity.
Central Limit Theorem (CLT):
Principle: With a sufficiently large number of independent simulations, the distribution of the sample mean (EV) approaches a normal distribution, regardless of the underlying distribution.
Application: Ensures that the EV and confidence bands are statistically reliable.
Expected Value (EV) and Confidence Bands:
EV: The mean price across all simulations at each projection bar.
Confidence Bands: Range within which the actual price is expected to lie with a specified probability (e.g., 95%).
EV of EV (Mean of Sample Means):
Definition: Represents the running average of EV values across the projection period, offering a smoothed central tendency.
Methodology
Anchor Time Setup:
The indicator starts projecting from a user-defined Anchor Time. If not customized, it defaults to the current bar's timestamp.
Purpose: Allows users to analyze projections from a specific historical point or the latest market data.
Calculating Drift and Volatility:
Returns Calculation: Computes the logarithmic returns from the Anchor Time to the current bar.
returns=ln(StSt−1)
returns=ln(St−1St)
Drift (μμ): Calculated as the simple moving average (SMA) of returns over the period since the Anchor Time.
Volatility (σσ): Determined using the standard deviation (stdev) of returns over the same period.
Simulation Generation:
Number of Simulations: The user defines how many GBM paths to simulate (e.g., 30).
Projection Candles: Determines the number of future bars to project (e.g., 12).
Process:
For each simulation:
Start from the current close price.
For each projection bar:
Generate a random number zz from a standard normal distribution.
Calculate the next price using the GBM formula:
St+1=St⋅e(μ−12σ2)+σz
St+1=St⋅e(μ−21σ2)+σz
Store the projected price in an array.
Expected Value (EV) and Confidence Bands Calculation:
EV Path: At each projection bar, compute the mean of all simulated prices.
Variance and Standard Deviation: Calculate the variance and standard deviation of simulated prices to determine the confidence intervals.
Confidence Bands: Using the standard normal z-score (1.96 for 95% confidence), establish upper and lower bounds:
Upper Band=EV+z⋅σEV
Upper Band=EV+z⋅σEV
Lower Band=EV−z⋅σEV
Lower Band=EV−z⋅σEV
EV of EV (Running Average of EV Values):
Calculation: For each projection bar, compute the average of all EV values up to that bar.
EV of EV =1j+1∑k=0jEV
EV of EV =j+11k=0∑jEV
Visualization: Plotted as a dynamic line reflecting the evolving average EV across the projection period.
Visualization Elements
Simulation Lines:
Appearance: Semi-transparent blue lines representing individual GBM simulation paths.
Purpose: Illustrate a range of possible future price trajectories based on current drift and volatility.
Expected Value (EV) Line:
Appearance: Solid orange line.
Purpose: Shows the average projected price at each future bar across all simulations.
Confidence Bands:
Upper Band: Dashed green line indicating the upper 95% confidence boundary.
Lower Band: Dashed red line indicating the lower 95% confidence boundary.
Purpose: Highlight the range within which the price is statistically expected to remain with 95% confidence.
EV of EV Line:
Appearance: Dashed purple line.
Purpose: Displays the running average of EV values, providing a smoothed trend of the central tendency across the projection period. As the mean of sample means it approximates the population mean (i.e. the trend since the anchor point.)
Current Price:
Appearance: Semi-transparent white line.
Purpose: Serves as a reference point for comparing actual price movements against projected paths.
Usage Instructions
Configuring User Inputs:
Anchor Time:
Set to a specific timestamp to start projections from a historical point or leave it as default to use the current bar's time.
Projection Candles (Bars):
Define the number of future bars to project (e.g., 12). Adjust based on your trading timeframe and analysis needs.
Number of Simulations:
Specify the number of GBM paths to simulate (e.g., 30). Higher numbers yield more accurate EV and confidence bands but may impact performance.
Display Toggles:
Show Simulation Lines: Toggle to display or hide individual GBM simulation paths.
Show Expected Value Line: Toggle to display or hide the EV path.
Show Upper Confidence Band: Toggle to display or hide the upper confidence boundary.
Show Lower Confidence Band: Toggle to display or hide the lower confidence boundary.
Show EV of EV Line: Toggle to display or hide the running average of EV values.
Managing TradingView's Object Limits:
Understanding Limits:
TradingView imposes a limit on the number of graphical objects (e.g., lines) that can be rendered. High values for projection candles and simulations can quickly consume these limits. TradingView appears to only allow a total of 55 candles to be projected, so if you want to see two complete lines, you would have to set the projection length to 27: since 27 * 2 = 54 and 54 < 55.
Optimizing Performance:
Use Toggles: Enable only the necessary visual elements. For instance, disable simulation lines and confidence bands when focusing on the EV and EV of EV lines. You can also use the maximum projection length of 55 with the lower limit confidence band as the only line, visualizing a long horizon for your risk.
Adjust Parameters: Lower the number of projection candles or simulations to stay within object limits without compromising essential insights.
Interpreting the Indicator:
Simulation Lines (Blue):
Represent individual potential future price paths based on GBM. A wider spread indicates higher volatility.
Expected Value (EV) Line (Goldenrod):
Shows the mean projected price at each future bar, providing a central trend.
Confidence Bands (Green & Red):
Indicate the statistical range (95% confidence) within which the price is expected to remain.
EV of EV Line (Dotted Line - Goldenrod):
Reflects the running average of EV values, offering a smoothed perspective of expected price trends over the projection period.
Current Price (White):
Serves as a benchmark for assessing how actual prices compare to projected paths.
Practical Applications
Risk Management:
Confidence Bands: Help in identifying potential support and resistance levels based on statistical confidence intervals.
EV Path: Assists in setting realistic target prices and stop-loss levels aligned with projected expectations.
Trend Analysis:
EV of EV Line: Offers a smoothed trendline, aiding in identifying overarching market directions amidst price volatility. Indicative of the population mean/overall trend of the data since your anchor point.
Scenario Planning:
Simulation Lines: Enable traders to visualize multiple potential outcomes, fostering better decision-making under uncertainty.
Performance Evaluation:
Comparing Actual vs. Projected Prices: Assess how actual price movements align with projected scenarios, refining trading strategies over time.
Mathematical and Statistical Insights
Simulation Integrity:
Independence: Each simulation path is generated independently, ensuring unbiased and diverse projections.
Randomness: Utilizes a Gaussian random number generator to introduce variability in diffusion terms, mimicking real market randomness.
Statistical Reliability:
Central Limit Theorem (CLT): By simulating a sufficient number of paths (e.g., 30), the sample mean (EV) converges to the population mean, ensuring reliable EV and confidence band calculations.
Variance Calculation: Accurate computation of variance from simulation data ensures precise confidence intervals.
Dynamic Projections:
Running Average (EV of EV): Provides a cumulative perspective, allowing traders to observe how the average expectation evolves as the projection progresses.
Customization and Enhancements
Adjustable Parameters:
Tailor the projection length and simulation count to match your trading style and analysis depth.
Visual Customization:
Modify line colors, styles, and transparency to enhance clarity and fit chart aesthetics.
Extended Statistical Metrics:
Future iterations can incorporate additional metrics like median projections, skewness, or alternative confidence intervals.
Dynamic Recalculation:
Implement logic to automatically update projections as new data becomes available, ensuring real-time relevance.
Performance Considerations
Object Count Management:
High simulation counts and extended projection periods can lead to a significant number of graphical objects, potentially slowing down chart performance.
Solution: Utilize display toggles effectively and optimize projection parameters to balance detail with performance.
Computational Efficiency:
The script employs efficient array handling and conditional plotting to minimize unnecessary computations and object creation.
Conclusion
The Anchored GBM Projections + EV & Confidence Bands indicator is a robust tool for traders seeking to forecast potential future price movements using statistical models. By integrating Geometric Brownian Motion simulations with expected value calculations and confidence intervals, it offers a comprehensive view of possible market scenarios. The addition of the "EV of EV" line further enhances analytical depth by providing a running average of expected values, aiding in trend identification and strategic decision-making.
Hope it helps!
Volume Volatility and Delta Indicator (HN)This Volume Volatility Indicator with Overall Average from Hossein.N helps you visualize the volatility of volume on different timeframes and compares it to the average volume over a given period. It includes several components:
Volume Volatility Indicator (Blue Line): This shows the volatility of volume relative to its moving average over a specified period. Higher values indicate more volatile trading conditions.
Long-Term Volatility Average (Orange Line): This line shows the moving average of the volume volatility indicator over a longer period. It acts as a benchmark for comparing the current volume volatility with historical trends.
Average Volume on Up Days (Green Line): Displays the average volume on days when the price is going up (green).
Average Volume on Down Days (Red Line): Displays the average volume on days when the price is going down (red).
Delta in Percentage (Blue Line): This shows the difference between the average volume of up days and down days, expressed as a percentage of the overall moving average of volume. It can be used to identify bullish or bearish volume imbalances. For example:
Positive values indicate that the volume on up days is stronger than on down days, which could suggest a bullish trend.
Negative values suggest that volume on down days is stronger than on up days, potentially indicating a bearish trend.
Zero Line (Gray Dotted Line): A reference line at 0 that helps you identify when the delta is positive or negative, and visualize the neutral point where volume is balanced between up and down days.
How to Use This Indicator:
Add to Your Chart: Copy the script above and paste it into TradingView's Pine Script editor. Click "Add to Chart" to visualize the indicator.
Interpret the Indicator:
Volume Volatility: A higher value suggests high market volatility. When volume is highly volatile, it may indicate more significant price movements or market uncertainty.
Long-Term Average of Volatility: Use this line as a reference to see whether current volatility is above or below average over a longer period.
Delta in Percentage: This is particularly useful to compare the strength of buying and selling volume. A positive delta percentage suggests strong buying pressure, while a negative delta suggests strong selling pressure. The closer the delta is to zero, the more balanced the volume between up and down days.
Use for Trend Confirmation: The indicator can help confirm trends. If the delta percentage is positive and increasing, and the volume volatility is above average, it could signal strong bullish momentum. Conversely, if the delta is negative and the volume volatility is rising, it may suggest bearish sentiment.
Risk Disclaimer:
Important: This indicator is a tool designed to help analyze market conditions. It does not guarantee success in trading and should not be used as the sole basis for making trading decisions. Always do your own research, consider other factors (e.g., price action, market news, fundamentals), and manage your risk appropriately. Trading involves significant risk, and you should only trade with money you can afford to lose. Always ensure you understand the risks involved in trading and use risk management strategies.
By using this tool, you accept full responsibility for any trading decisions and the outcomes thereof. The information presented is for educational and informational purposes only.
Entropy Volatility Index [CHE]I Entropy Volatility Index (EVI)
II An Experimental Script for Measuring Market Volatility
III Introduction
The Entropy Volatility Index (EVI) is an experimental indicator based on concepts from thermodynamics and information theory. The goal of the EVI is to quantify market uncertainty and volatility by calculating the entropy of price changes.
IV Basic Concepts
Entropy in Thermodynamics
Entropy is a measure of disorder or randomness in a system.
The second law of thermodynamics states that entropy in a closed system tends to increase over time.
Entropy in Information Theory
In information theory, entropy measures the uncertainty or information content of a random variable.
The entropy H of a random variable X with probability distribution P(x) is calculated as:
H(X) = -∑ P(x) log P(x)
V Derivation of the EVI
Calculation of Price Changes
Absolute price changes are calculated to serve as the basis for probability calculations.
Creation of the Histogram
A histogram is created and initialized to count the frequency of price changes.
Updating the Histogram
The histogram is updated by counting the frequency of each price change.
Calculation of Probabilities
The probabilities of the price changes are calculated based on their frequencies in the histogram.
Calculation of Entropy
Entropy is calculated using the probabilities of price changes. Higher entropy indicates higher uncertainty or disorder in the market.
Plotting the Indicator
The EVI is plotted to visually represent market volatility and uncertainty.
VI Interpretation of the EVI
High EVI Values
High Volatility: Strong and irregular price movements.
High Uncertainty: Increased market uncertainty.
Possible Market Turning Points: Indicators of potential trend changes.
Low EVI Values
Low Volatility: More consistent and predictable price movements.
Stability: More stable market phases.
Trend Consistency: Indicators of stable trends or sideways movements.
VII Conclusion
The Entropy Volatility Index (EVI) is an experimental script that applies concepts from thermodynamics and information theory to measure market volatility. It offers a new perspective on market uncertainty and can be used as an additional tool for traders.
VIII Example Use Cases
Identifying Volatile Phases: Use the EVI to identify periods of high volatility and prepare for potential rapid price movements.
Risk Management: Adjust your risk management strategy based on the EVI. During high EVI periods, consider hedging positions or adjusting position sizes.
Complementing Other Indicators: Combine the EVI with other technical indicators (e.g., RSI, MACD) for a more comprehensive view of market conditions.
I hope this experimental script provides valuable insights. Thank you for your feedback and suggestions for improvement.
Best regards,
Chervolino
ATR by Time [QuantVue]"ATR by Time" incorporates time-specific volatility patterns by calculating the Average True Range (ATR) over a customizable period and comparing it to historical ATR values
at specific times of the day.
The Average True Range (ATR) is a popular technical indicator that measures market volatility by decomposing the entire range of an asset price for that period.
By taking the ATR at certain times of the day and comparing it to the current bar's ATR, traders can gain several potential advantages:
Volatility Pattern Recognition: Different times of the trading day often exhibit different levels of volatility. For instance, markets might be more volatile at the open and close compared to midday. By tracking ATR at specific times, traders can recognize these patterns and better predict periods of high or low volatility.
Risk Management: Understanding volatility trends throughout the day helps in better risk management. During periods of high expected volatility (indicated by higher ATR compared to the historical average), traders can adjust their stop-loss levels and position sizes accordingly to protect their capital.
Trend Confirmation and Divergence: This indicator can help confirm trends or identify potential reversals. For example, if the current ATR consistently exceeds the average ATR at specific times, it may confirm a strong trend. Conversely, if the current ATR falls below the historical average, it could signal a potential slowdown or reversal.
This indicator will work on all markets on all time frames. User can customize ATR length as well as the lookback period.
This script utilizes TradingView's RelativeValue library and averageAtTime function, which is used to compare a current data point in a time interval to an average of data points with corresponding time offsets across historical periods. Its purpose is to assess the significance of a value by considering the historical context within past time intervals.
Give this indicator a BOOST and COMMENT your thoughts!
We hope you enjoy.
Cheers!
HV-RV Oscillator by DINVESTORQ(PRABIR DAS)Description:
The HV-RV Oscillator is a powerful tool designed to help traders track and compare two types of volatility measures: Historical Volatility (HV) and Realized Volatility (RV). This indicator is useful for identifying periods of market volatility and can be employed in various trading strategies. It plots both volatility measures on a normalized scale (0 to 100) to allow easy comparison and analysis.
How It Works:
Historical Volatility (HV):
HV is calculated by taking the log returns of the closing prices and finding the standard deviation over a specified period (default is 14 periods).
The value is then annualized assuming 252 trading days in a year.
Realized Volatility (RV):
RV is based on the True Range, which is the maximum of the current high-low range, the difference between the high and the previous close, and the difference between the low and the previous close.
Like HV, the standard deviation of the True Range over a specified period is calculated and annualized.
Normalization:
Both HV and RV values are normalized to a 0-100 scale, making it easy to see their relative magnitude over time.
The highest and lowest values within the period are used to normalize the data, which smooths out short-term volatility spikes.
Smoothing:
The normalized values of both HV and RV are then smoothed using a Simple Moving Average (SMA) to reduce noise and provide a clearer trend.
Crossover Signals:
Buy Signal : When the Normalized HV crosses above the Normalized RV, it indicates that the historical volatility is increasing relative to the realized volatility, which could be interpreted as a buy signal.
Sell Signal : When the Normalized HV crosses below the Normalized RV, it suggests that the historical volatility is decreasing relative to the realized volatility, which could be seen as a sell signal.
Features:
Two Volatility Lines: The blue line represents Normalized HV, and the orange line represents Normalized RV.
Neutral Line: A gray dashed line at the 50 level indicates a neutral state between the two volatility measures.
Buy/Sell Markers: Green upward arrows are shown when the Normalized HV crosses above the Normalized RV, and red downward arrows appear when the Normalized HV crosses below the Normalized RV.
Inputs:
HV Period: The number of periods used to calculate Historical Volatility (default = 14).
RV Period: The number of periods used to calculate Realized Volatility (default = 14).
Smoothing Period: The number of periods used for smoothing the normalized values (default = 3).
How to Use:
This oscillator is designed for traders who want to track the relationship between Historical Volatility and Realized Volatility.
Buy signals occur when HV increases relative to RV, which can indicate increased market movement or potential breakout conditions.
Sell signals occur when RV is greater than HV, signaling reduced volatility or potential trend exhaustion.
Example Use Cases:
Breakout/Trend Strategy: Use the oscillator to identify potential periods of increased volatility (when HV crosses above RV) for breakout trades.
Mean Reversion: Use the oscillator to detect periods of low volatility (when RV crosses above HV) that might signal a return to the mean or consolidation.
This tool can be used on any asset class such as stocks, forex, commodities, or indices to help you make informed decisions based on the comparison of volatility measures.
NOTE: FOR INTRDAY PURPOSE USE 30/7/9 AS SETTING AND FOR DAY TRADE USE 14/7/9
Machine Learning Adaptive SuperTrend [AlgoAlpha]📈🤖 Machine Learning Adaptive SuperTrend - Take Your Trading to the Next Level! 🚀✨
Introducing the Machine Learning Adaptive SuperTrend , an advanced trading indicator designed to adapt to market volatility dynamically using machine learning techniques. This indicator employs k-means clustering to categorize market volatility into high, medium, and low levels, enhancing the traditional SuperTrend strategy. Perfect for traders who want an edge in identifying trend shifts and market conditions.
What is K-Means Clustering and How It Works
K-means clustering is a machine learning algorithm that partitions data into distinct groups based on similarity. In this indicator, the algorithm analyzes ATR (Average True Range) values to classify volatility into three clusters: high, medium, and low. The algorithm iterates to optimize the centroids of these clusters, ensuring accurate volatility classification.
Key Features
🎨 Customizable Appearance: Adjust colors for bullish and bearish trends.
🔧 Flexible Settings: Configure ATR length, SuperTrend factor, and initial volatility guesses.
📊 Volatility Classification: Uses k-means clustering to adapt to market conditions.
📈 Dynamic SuperTrend Calculation: Applies the classified volatility level to the SuperTrend calculation.
🔔 Alerts: Set alerts for trend shifts and volatility changes.
📋 Data Table Display: View cluster details and current volatility on the chart.
Quick Guide to Using the Machine Learning Adaptive SuperTrend Indicator
🛠 Add the Indicator: Add the indicator to favorites by pressing the star icon. Customize settings like ATR length, SuperTrend factor, and volatility percentiles to fit your trading style.
📊 Market Analysis: Observe the color changes and SuperTrend line for trend reversals. Use the data table to monitor volatility clusters.
🔔 Alerts: Enable notifications for trend shifts and volatility changes to seize trading opportunities without constant chart monitoring.
How It Works
The indicator begins by calculating the ATR values over a specified training period to assess market volatility. Initial guesses for high, medium, and low volatility percentiles are inputted. The k-means clustering algorithm then iterates to classify the ATR values into three clusters. This classification helps in determining the appropriate volatility level to apply to the SuperTrend calculation. As the market evolves, the indicator dynamically adjusts, providing real-time trend and volatility insights. The indicator also incorporates a data table displaying cluster centroids, sizes, and the current volatility level, aiding traders in making informed decisions.
Add the Machine Learning Adaptive SuperTrend to your TradingView charts today and experience a smarter way to trade! 🌟📊
Volumetric Volatility Blocks [UAlgo]The Volumetric Volatility Blocks indicator is designed to identify significant volatility blocks based on price and volume data. It utilizes a combination of the Average True Range (ATR) and Simple Moving Average (SMA) to determine the volatility level and identify periods of heightened market activity. The indicator highlights these volatility blocks, providing traders with visual cues for potential trading opportunities. It differentiates between bullish and bearish volatility by analyzing price movement and volume, offering a nuanced view of market sentiment. This tool is particularly useful for traders looking to capitalize on periods of high volatility and momentum shifts.
🔶 Key Features
Volatility Measurement Length: Controls the period used to calculate the ATR.
Smooth Length of Volatility: Defines the period for the SMA used to smooth the ATR.
Multiplier of SMA: Sets the minimum threshold for the ATR to be considered a "high volatility" block.
Show Last X Volatility Blocks: Determines how many of the most recent volatility blocks are displayed on the chart.
Mitigation Method: Choose between "Close" or "Wick" price to filter volatility blocks based on price action. This helps avoid highlighting blocks broken by the chosen price level.
Volume Info: Displaying the volume associated with each block.
Up/Down Block Color: Sets the color for bullish and bearish volatility blocks.
🔶 Usage
The Volumetric Volatility Blocks indicator visually represents periods of high volatility with blocks on the chart. Green blocks indicate bullish volatility, while red blocks indicate bearish volatility.
Bullish Volatility Blocks: When the ATR surpasses the smoothed ATR multiplied by the set multiplier, and the price closes higher than it opened, a bullish block is formed. These blocks are generally used to identify potential buying opportunities as they indicate upward momentum.
Bearish Volatility Blocks: Conversely, bearish blocks form under the same conditions, but when the price closes lower than it opened. These blocks can signal potential selling opportunities as they highlight downward momentum.
Volume Information: Each block can display volume data, providing insight into the strength of the market movement. The percentage shown on the block indicates the relative volume contribution of that block, helping traders assess the significance of the volatility.
The volume percentages in the Volumetric Volatility Blocks indicator are calculated based on the total volume of the most recent volatility blocks. For each of the most recent volatility blocks, the percentage of the total volume is calculated by dividing the block's volume by the total volume:
🔶 Disclaimer
Use with Caution: This indicator is provided for educational and informational purposes only and should not be considered as financial advice. Users should exercise caution and perform their own analysis before making trading decisions based on the indicator's signals.
Not Financial Advice: The information provided by this indicator does not constitute financial advice, and the creator (UAlgo) shall not be held responsible for any trading losses incurred as a result of using this indicator.
Backtesting Recommended: Traders are encouraged to backtest the indicator thoroughly on historical data before using it in live trading to assess its performance and suitability for their trading strategies.
Risk Management: Trading involves inherent risks, and users should implement proper risk management strategies, including but not limited to stop-loss orders and position sizing, to mitigate potential losses.
No Guarantees: The accuracy and reliability of the indicator's signals cannot be guaranteed, as they are based on historical price data and past performance may not be indicative of future results.
STD-Filtered Jurik Volty Adaptive TEMA [Loxx]The STD-Filtered Jurik Volty Adaptive TEMA is an advanced moving average overlay indicator that incorporates adaptive period inputs from Jurik Volty into a Triple Exponential Moving Average (TEMA). The resulting value is further refined using a standard deviation filter to minimize noise. This adaptation aims to develop a faster TEMA that leads the standard, non-adaptive TEMA. However, during periods of low volatility, the output may be noisy, so a standard deviation filter is employed to decrease choppiness, yielding a highly responsive TEMA without the noise typically caused by low market volatility.
█ What is Jurik Volty?
Jurik Volty calculates the price volatility and relative price volatility factor.
The Jurik smoothing includes 3 stages:
1st stage - Preliminary smoothing by adaptive EMA
2nd stage - One more preliminary smoothing by Kalman filter
3rd stage - Final smoothing by unique Jurik adaptive filter
Here's a breakdown of the code:
1. volty(float src, int len) => defines a function called volty that takes two arguments: src, which represents the source price data (like close price), and len, which represents the length or period for calculating the indicator.
2. int avgLen = 65 sets the length for the Simple Moving Average (SMA) to 65.
3. Various variables are initialized like volty, voltya, bsmax, bsmin, and vsum.
4. len1 is calculated as math.max(math.log(math.sqrt(0.5 * (len-1))) / math.log(2.0) + 2.0, 0); this expression involves some mathematical transformations based on the len input. The purpose is to create a dynamic factor that will be used later in the calculations.
5. pow1 is calculated as math.max(len1 - 2.0, 0.5); this variable is another dynamic factor used in further calculations.
6. del1 and del2 represent the differences between the current src value and the previous values of bsmax and bsmin, respectively.
7. volty is assigned a value based on a conditional expression, which checks whether the absolute value of del1 is greater than the absolute value of del2. This step is essential for determining the direction and magnitude of the price change.
8. vsum is updated based on the previous value and the difference between the current and previous volty values.
9. The Simple Moving Average (SMA) of vsum is calculated with the length avgLen and assigned to avg.
10. Variables dVolty, pow2, len2, and Kv are calculated using various mathematical transformations based on previously calculated variables. These variables are used to adjust the Jurik Volty indicator based on the observed volatility.
11. The bsmax and bsmin variables are updated based on the calculated Kv value and the direction of the price change.
12. inally, the temp variable is calculated as the ratio of avolty to vsum. This value represents the Jurik Volty indicator's output and can be used to analyze the market trends and potential reversals.
Jurik Volty can be used to identify periods of high or low volatility and to spot potential trade setups based on price behavior near the volatility bands.
█ What is the Triple Exponential Moving Average?
The Triple Exponential Moving Average (TEMA) is a technical indicator used by traders and investors to identify trends and price reversals in financial markets. It is a more advanced and responsive version of the Exponential Moving Average (EMA). TEMA was developed by Patrick Mulloy and introduced in the January 1994 issue of Technical Analysis of Stocks & Commodities magazine. The aim of TEMA is to minimize the lag associated with single and double exponential moving averages while also filtering out market noise, thus providing a smoother, more accurate representation of the market trend.
To understand TEMA, let's first briefly review the EMA.
Exponential Moving Average (EMA):
EMA is a weighted moving average that gives more importance to recent price data. The formula for EMA is:
EMA_t = (Price_t * α) + (EMA_(t-1) * (1 - α))
Where:
EMA_t: EMA at time t
Price_t: Price at time t
α: Smoothing factor (α = 2 / (N + 1))
N: Length of the moving average period
EMA_(t-1): EMA at time t-1
Triple Exponential Moving Average (TEMA):
Triple Exponential Moving Average (TEMA):
TEMA combines three exponential moving averages to provide a more accurate and responsive trend indicator. The formula for TEMA is:
TEMA = 3 * EMA_1 - 3 * EMA_2 + EMA_3
Where:
EMA_1: The first EMA of the price data
EMA_2: The EMA of EMA_1
EMA_3: The EMA of EMA_2
Here are the steps to calculate TEMA:
1. Choose the length of the moving average period (N).
2. Calculate the smoothing factor α (α = 2 / (N + 1)).
3. Calculate the first EMA (EMA_1) using the price data and the smoothing factor α.
4. Calculate the second EMA (EMA_2) using the values of EMA_1 and the same smoothing factor α.
5. Calculate the third EMA (EMA_3) using the values of EMA_2 and the same smoothing factor α.
5. Finally, compute the TEMA using the formula: TEMA = 3 * EMA_1 - 3 * EMA_2 + EMA_3
The Triple Exponential Moving Average, with its combination of three EMAs, helps to reduce the lag and filter out market noise more effectively than a single or double EMA. It is particularly useful for short-term traders who require a responsive indicator to capture rapid price changes. Keep in mind, however, that TEMA is still a lagging indicator, and as with any technical analysis tool, it should be used in conjunction with other indicators and analysis methods to make well-informed trading decisions.
Extras
Signals
Alerts
Bar coloring
Loxx's Expanded Source Types (see below):
vol_coneDraws a volatility cone on the chart, using the contract's realized volatility (rv). The inputs are:
- window: the number of past periods to use for computing the realized volatility. VIX uses 30 calendar days, which is 21 trading days, so 21 is the default.
- stdevs: the number of standard deviations that the cone will cover.
- periods to project: the length of the volatility cone.
- periods per year: the number of periods in a year. for a daily chart, this is 252. for a thirty minute chart on a contract that trades 23 hours a day, this is 23 * 2 * 252 = 11592. for an accurate cone, this input must be set correctly, according to the chart's time frame.
- history: show the lagged projections. in other words, if the cone is set to project 21 periods in the future, the lines drawn show the top and bottom edges of the cone from 23 periods ago.
- rate: the current interest or discount rate. this is used to compute the forward price of the underlying contract. using an accurate forward price allows you to compare the realized volatility projection to the implied volatility projections derived from options prices.
Example settings for a 30 minute chart of a contract that trades 23 hours per day, with 1 standard deviation, a 21 day rv calculation, and half a day projected:
- stdevs: 1
- periods to project: 23
- window: 23 * 2 * 21 = 966
- periods per year: 23 * 2 * 252 = 11592
Additionally, a table is drawn in the upper right hand corner, with several values:
- rv: the contract's current realized volatility.
- rnk: the rv's percentile rank, compared to the rv values on past bars.
- acc: the proportion of times price settled inside, versus outside, the volatility cone, "periods to project" into the future. this should be around 65-70% for most contracts when the cone is set to 1 standard deviation.
- up: the upper bound of the cone for the projection period.
- dn: the lower bound of the cone for the projection period.
Limitations:
- pinescript only seems to be able to draw a limited distance into the future. If you choose too many "periods to project", the cone will start drawing vertically at some limit.
- the cone is not totally smooth owing to the facts a) it is comprised of a limited number of lines and b) each bar does not represent the same amount of time in pinescript, as some cross weekends, session gaps, etc.
TVMC - Composite Indicator with Technical RatingsDescription:
The TVMC (Trend, Volume, Momentum, Composite) indicator is a powerful multi-component tool designed to provide traders with a comprehensive understanding of market conditions. By combining four essential technical analysis components—trend, momentum, volume, and volatility—this indicator offers clear and actionable insights to assist in decision-making.
Key Features:
1. Trend Component (TC):
* Based on MACD (Moving Average Convergence Divergence), this component analyzes the relationship between two exponential moving averages (fast and slow) to determine the prevailing market trend.
* The MACD signal is normalized to a range of -1 to +1 for consistency and clarity.
2. Momentum Component (MC):
* Utilizes RSI (Relative Strength Index) to measure the strength and speed of price movements.
* This component highlights overbought or oversold conditions, which may indicate potential market reversals.
3. Volume Confirmation (VC):
* Compares the current trading volume to its moving average over a specified period.
* High volume relative to the average confirms the validity of the current trend.
4. Volatility Filter (VF):
* Uses ATR (Average True Range) to gauge market volatility.
* Adjusts and smooths signals to reduce noise during periods of high volatility.
5. Technical Ratings Integration:
* Incorporates TradingView’s Technical Ratings, allowing users to validate signals using moving averages, oscillators, or a combination of both.
* Users can choose their preferred source of ratings for enhanced signal confirmation.
How It Works:
The TVMC indicator combines the weighted contributions of the Trend, Momentum, and Volume components, further refined by the Volatility Filter. Each component plays a specific role:
* Trend: Identifies whether the market is bullish, bearish, or neutral.
* Momentum: Highlights the strength of price action.
* Volume: Confirms whether the current price action is supported by sufficient trading activity.
* Volatility: Filters out excessive noise in volatile market conditions, providing a smoother and more reliable output.
Visualization:
1. Bullish Signals:
* The indicator line turns green and remains above the zero line, indicating upward momentum.
2. Bearish Signals:
* The indicator line turns red and falls below the zero line, signaling downward momentum.
3. Neutral Signals:
* The line is orange and stays near zero, indicating a lack of strong trend or momentum.
4. Zones:
* Horizontal lines at +30 and -30 mark strong bullish and bearish zones, respectively.
* A zero line is included for clear separation between bullish and bearish signals.
Recommended Usage:
* Best Timeframes: The indicator is optimized for higher timeframes such as 4-hour (H4) and daily (D1) charts.
* Trading Style: Suitable for swing and positional trading.
* Customization: The indicator allows users to adjust all major parameters (e.g., MACD, RSI, volume, and ATR settings) to fit their trading preferences.
Customization Options:
* Adjustable weights for Trend, Momentum, and Volume components.
* Fully configurable settings for MACD, RSI, Volume SMA, and ATR periods.
* Timeframe selection for multi-timeframe analysis.
Important Notes:
1. Originality: The TVMC indicator combines multiple analysis methods into a unique framework. It does not replicate or minimally modify existing indicators.
2. Transparency: The description is detailed enough for users to understand the methodology without requiring access to the code.
3. Clarity: The indicator is explained in a way that is accessible even to users unfamiliar with complex technical analysis tools.
Compliance with TradingView Rules:
* The indicator is written in Pine Script version 5, adhering to TradingView’s language standards.
* The description is written in English to ensure accessibility to the global community, with a clear explanation of all components and functionality.
* No promotional content, links, or unrelated references are included.
* The chart accompanying the indicator is clean and demonstrates its intended use clearly, with no additional indicators unless explicitly explained.
VIX Statistical Sentiment Index [Nasan]** THIS IS ONLY FOR US STOCK MARKET**
The indicator analyzes market sentiment by computing the Rate of Change (ROC) for the VIX and S&P 500, visualizing the data as histograms with conditional coloring. It measures the correlation between the VIX, the specific stock, and the S&P 500, displaying the results on the chart. The reliability measure combines these correlations, offering an overall assessment of data robustness. One can use this information to gauge the inverse relationship between VIX and S&P 500, the alignment of the specific stock with the market, and the overall reliability of the correlations for informed decision-making based on the inverse relationship of VIX and price movement.
**WHEN THE VIX ROC IS ABOVE ZERO (RED COLOR) AND RASING ONE CAN EXPECT THE PRICE TO MOVE DOWNWARDS, WHEN THE VIX ROC IS BELOW ZERO (GREEN)AND DECREASING ONE CAN EXPECT THE PRICE TO MOVE UPWARDS"
Understanding the VIX Concept:
The VIX, or Volatility Index, is a widely used indicator in finance that measures the market's expectation of volatility over the next 30 days. Here are key points about the VIX:
Fear Gauge:
Often referred to as the "fear gauge," the VIX tends to rise during periods of market uncertainty or fear and fall during calmer market conditions.
Inverse Relationship with Market:
The VIX typically has an inverse relationship with the stock market. When the stock market experiences a sell-off, the VIX tends to rise, indicating increased expected volatility.
Implied Volatility:
The VIX is derived from the prices of options on the S&P 500. It represents the market's expectations for future volatility and is often referred to as "implied volatility."
Contrarian Indicator:
Extremely high VIX levels may indicate oversold conditions, suggesting a potential market rebound. Conversely, very low VIX levels may signal complacency and a potential reversal.
VIX vs. SPX Correlation:
This correlation measures the strength and direction of the relationship between the VIX (Volatility Index) and the S&P 500 (SPX).
A negative correlation indicates an inverse relationship. When the VIX goes up, the SPX tends to go down, and vice versa.
The correlation value closer to -1 suggests a stronger inverse relationship between VIX and SPX.
Stock vs. SPX Correlation:
This correlation measures the strength and direction of the relationship between the closing price of the stock (retrieved using src1) and the S&P 500 (SPX).
This correlation helps assess how closely the stock's price movements align with the broader market represented by the S&P 500.
A positive correlation suggests that the stock tends to move in the same direction as the S&P 500, while a negative correlation indicates an opposite movement.
Reliability Measure:
Combines the squared values of the VIX vs. SPX and Stock vs. SPX correlations and takes the square root to create a reliability measure.
This measure provides an overall assessment of how reliable the correlation information is in guiding decision-making.
Interpretation:
A higher reliability measure implies that the correlations between VIX and SPX, as well as between the stock and SPX, are more robust and consistent.
One can use this reliability measure to gauge the confidence they can place in the correlations when making decisions about the specific stock based on VIX data and its correlation with the broader market.
TrendCylinder (Expo)█ Overview
The TrendCylinder is a dynamic trading indicator designed to capture trends and volatility in an asset's price. It provides a visualization of the current trend direction and upper and lower bands that adapt to volatility changes. By using this indicator, traders can identify potential breakouts or support and resistance levels. While also gauging the volatility to generate trading ranges. The indicator is a comprehensive tool for traders navigating various market conditions by providing a sophisticated blend of trend-following and volatility-based metrics.
█ How It Works
Trend Line: The trend line is constructed using the closing prices with the influence of volatility metrics. The trend line reacts to sudden price changes based on the trend factor and step settings.
Upper & Lower Bands: These bands are not static; they are dynamically adjusted with the calculated standard deviation and Average True Range (ATR) metrics to offer a more flexible, real-world representation of potential price movements, offering an idea of the market's likely trading range.
█ How to Use
Identifying Trends
The trend line can be used to identify the current market trend. If the price is above the trend line, it indicates a bullish trend. Conversely, if the price is below the trend line, it indicates a bearish trend.
Dynamic Support and Resistance
The upper and lower bands (including the trend line) dynamically change with market volatility, acting as moving targets of support and resistance. This helps set up stop-loss or take-profit levels with a higher degree of accuracy.
Breakout vs. Reversion Strategies
Price movements beyond the bands could signify strong trends, making it ideal for breakout strategies.
Fakeouts
If the price touches one of the bands and reverses direction, it could be a fakeout. Traders may choose to trade against the breakout in such scenarios.
█ Settings
Volatility Period: Defines the look-back period for calculating volatility. Higher values adapt the bands more slowly, whereas lower values adapt them more quickly.
Trend Factor: Adjusts the sensitivity of the trend line. Higher values produce a smoother line, while lower values make it more reactive to price changes.
Trend Step: Controls the pace at which the trend line adjusts to sudden price movements. Higher values lead to a slower adjustment and a smoother line, while lower values result in quicker adjustments.
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
