Monthly, Quarterly OPEX & Vix expirations
OPEX Indicator:
The OPEX indicator is designed to provide traders with a visual representation of key options expiration dates, particularly for monthly, quarterly, and VIX options expirations. This indicator can be particularly helpful for market participants who focus on options-based strategies or those who track the impact of options expiration on price action.
The indicator overlays vertical lines and labels on the chart to highlight three key types of expiration events:
Monthly Equity and Index Expiration (OPEX): This marks the standard monthly options expiration dates for equity and index options.
Quarterly Index Expiration (Q): This indicates the quarterly expiration dates for index options, which tend to have a larger impact on the market.
Monthly VIX Expiration (VIXEX): This marks the monthly expiration of VIX options and futures, which are important for volatility traders.
How to Use the OPEX Indicator:
Expiration Dates on the Chart: The OPEX indicator marks expiration dates with vertical lines and labels that appear on the chart. These are customizable, allowing you to adjust the line and label colors to suit your preferences. The lines and labels will appear at specific times, such as the closing of the market on expiration days, allowing traders to prepare for potential volatility or other market dynamics associated with these events.
Customizable Colors and Label Positions: The indicator offers flexibility in customizing the appearance of expiration lines and labels. For each expiration type (OPEX, Quarterly, and VIXEX), you can adjust the line color, label color, and label text color. Additionally, the label text size and position can be customized (e.g., above the bar, below the bar, top or bottom of the chart). This allows for a tailored display that suits your trading style and chart layout.
Visualizing Impact of Expiration Events: Traders who track the influence of expiration events can use this indicator to spot potential market moves around expiration dates. For example, significant price swings often occur near expiration days as options traders adjust their positions. With this indicator, you can visualize these dates on your chart and analyze market behavior in the lead-up to, during, and after the expirations.
Input Options:
Expiration Types:
Monthly Equity, Index Expiration (OPEX): Turn on or off the monthly equity expiration markers.
Quarterly Index Expiration (Q): Turn on or off the quarterly expiration markers.
Monthly VIX Expiration (VIXEX): Turn on or off the VIX expiration markers.
Line and Label Customization:
Line Color: Adjust the color of the vertical lines marking the expiration events.
Label Color: Customize the color of the expiration labels.
Label Text Color: Adjust the color of the text inside the labels.
Label Position: Choose the position of the labels (e.g., top, bottom, above bar, below bar).
Use Cases:
Options Traders: Track options expiration dates to assess potential price swings or liquidity changes.
Volatility Traders: Watch for patterns around VIX options expirations.
Index Traders: Monitor quarterly expirations for potential market-moving events.
Example Use:
As a trader, you can apply this indicator to your chart and observe how price action reacts near expiration dates. For instance, on the monthly OPEX expiration day, you might notice increased volatility or an uptick in options-related price moves. By observing this trend over time, you can align your trades to capitalize on predictable movements around key expiration days.
Additionally, you may use the quarterly expiration markers to assess whether there’s typically a market shift during these periods, providing insights for long-term traders.
This indicator can be a helpful tool for preparing and managing trades around critical options expiration dates, helping to forecast potential market behavior based on historical patterns.
TradingView Community Guidelines Compliance: This script complies with TradingView's community guidelines by offering a clear and valuable function for traders, providing customizable inputs for enhanced usability. The script is focused on chart visualizations without manipulating or misrepresenting market data. It serves as an educational tool and a functional indicator, with no claims or misleading functionality. The indicator does not promote financial products or services and focuses solely on charting for better trading decision-making.
볼래틸리티
IU Trailing Stop Loss MethodsThe 'IU Trailing Stop Loss Methods' it's a risk management tool which allows users to apply 12 trailing stop-loss (SL) methods for risk management of their trades and gives live alerts when the trailing Stop loss has hit. Below is a detailed explanation of each input and the working of the Script.
Main Inputs:
- bar_time: Specifies the date from which the trade begins and entry price will be the open of the first candle.
- entry_type: Choose between 'Long' or 'Short' positions.
- trailing_method: Select the trailing stop-loss method. Options include ATR, Parabolic SAR, Supertrend, Point/Pip based, Percentage, EMA, Highest/Lowest, Standard Deviation, and multiple target-based methods.
- exit_after_close: If checked, exits the trade only after the candle closes.
Optional Inputs:
ATR Settings:
- atr_Length: Length for the ATR calculation.
- atr_factor: ATR multiplier for SL calculation.
Parabolic SAR Settings:
- start, increment, maximum: Parameters for the Parabolic SAR indicator.
Supertrend Settings:
- supertrend_Length, supertrend_factor: Length and factor for the Supertrend indicator.
Point/Pip Based:
- point_base: Set trailing SL in points/pips.
Percentage Based:
- percentage_base: Set SL as a percentage of entry price.
EMA Settings:
- ema_Length: Length for EMA calculation.
Standard Deviation Settings:
- std_Length, std_factor: Length and factor for standard deviation calculation.
Highest/Lowest Settings:
- highest_lowest_Length: Length for the highest/lowest SL calculation.
Target-Based Inputs:
- ATR, Point, Percentage, and Standard Deviation based target SL settings with customizable lengths and multipliers.
Entry Logic:
- Trades initiate based on the entry_type selected and the specified bar_time.
- If Long is selected, a long trade is initiated when the conditions match, and vice versa for Short.
Trailing Stop-Loss (SL) Methods Explained:
The strategy dynamically adjusts stop-loss based on the chosen method. Each method has its calculation logic:
- ATR: Stop-loss calculated using ATR multiplied by a user-defined factor.
- Parabolic SAR: Uses the Parabolic SAR indicator for trailing stop-loss.
- Supertrend: Utilizes the Supertrend indicator as the stop-loss line.
- Point/Pip Based: Fixed point-based stop-loss.
- Percentage Based: SL set as a percentage of entry price.
- EMA: SL based on the Exponential Moving Average.
- Highest/Lowest: Uses the highest high or lowest low over a specified period.
- Standard Deviation: SL calculated using standard deviation.
Exit Conditions:
- If exit_after_close is enabled, the position will only close after the candle confirms the stop-loss hit.
- If exit_after_close is disabled, the strategy will close the trade immediately when the SL is breached.
Visualization:
The script plots the chosen trailing stop-loss method on the chart for easy visualization.
Target-Based Trailing SL Logic:
- When a position is opened, the strategy calculates the initial stop-loss and progressively adjusts it as the price moves favorably.
- Each SL adjustment is stored in an array for accurate tracking and visualization.
Alerts and Labels:
- When the Entry or trailing stop loss is hit this scripts draws a label and give alert to the user that trailing stop has been hit for the trade.
Note - on the historical data The Script will show nothing if the entry and the exit has happened on the same candle, because we don't know what was hit first SL or TP (basically how the candle was formed on the lower timeframe).
Summary:
This script offers flexible trailing stop-loss options for traders who want dynamic risk management in their strategies. By offering multiple methods like ATR, SAR, Supertrend, and EMA, it caters to various trading styles and risk preferences.
Market Volatility Momentum + Trend Filter Pro @MaxMaserati# 📊 Market Volatility Momentum + Trend Filter Pro
## 🎯 Overview
An enhanced version of the Market Momentum Indicator, combining the power of momentum analysis with adaptive volatility bands and trend filtering. This professional tool helps traders identify market direction and potential momentum shifts with greater precision.
## 🔄 Core Momentum Components
### 📈 Momentum Line
- Calculated using the midpoint between highest and lowest prices over 14 periods
- Provides a clear reference for price direction
- Acts as a dynamic support/resistance level
### 📉 Momentum Signal
- Offset from the Momentum Line by 0.25 tick size
- Creates a precise visual guide for momentum shifts
- Standard increment compatible with most markets
## 💫 Enhanced Features
### 🌊 Trend Filter
- Dynamic color-coding system showing trend strength
- Customizable length and damping parameters
- Visual identification of neutral market conditions
### 📊 Volatility Bands
- Adaptive bands that expand and contract with market volatility
- Choice between short-term and long-term trend adaptation
- Provides additional confirmation of trend strength
## 📝 Trading Signals
### 📈 Bullish Momentum
- Both momentum lines below price
- Enhanced by trend filter color confirmation
- Supported by volatility band positioning
### 📉 Bearish Momentum
- Both momentum lines above price
- Confirmed by trend filter color signals
- Reinforced by volatility band context
### ⚖️ Consolidation
- Momentum lines within price range
- Neutral trend indication with deep blue area
- Potential breakout preparation phase
## ⚙️ Multi-Timeframe Analysis
- Dual timeframe capability for comprehensive market view
- Custom timeframe selection with current chart reference
- Real-time timeframe display in top-right corner
## 🎨 Visual Features
- Dynamic bar coloring system reflecting trend strength
- Clear trend visualization through color gradients
- Optional line smoothing for reduced noise
- Customizable color schemes
## 💡 Tips for Usage
1. Monitor the position of price relative to momentum lines
2. Use trend filter colors for confirmation
3. Watch for convergence with volatility bands
4. Pay attention to neutral market signals
5. Utilize multi-timeframe analysis for better context
## ⚠️ Important Notes
- Originally designed without smoothing (smoothing optional)
- Best used with multiple timeframe analysis
- Provides clearest signals in trending markets
- Works effectively across all tradable assets
Note: Past performance doesn't guarantee future results. Always practice proper risk management and develop your trading plan.
Uptrick: Oracle Metrics +
Introduction
Uptrick: Oracle Metrics + is a multi-dimensional trading indicator designed to consolidate various technical and risk-oriented signals into one accessible framework. It allows traders to observe market volatility, identify potential reversal points, and assess numerous performance metrics, all within a single interface.
Purpose
The main goal of this indicator is to simplify a broad array of market insights. It merges trend analysis, volatility indicators, on-chart signals, and risk-performance metrics to help traders quickly evaluate the state of a market and make more informed decisions.
Features
1. Cloud Visualization
A colored cloud overlays the chart, indicating market conditions. When the cloud narrows, it can signal upcoming breakout scenarios, as volatility compresses and price movement may accelerate. In contrast, when the cloud is wide, this could hint at an extended trend that might be nearing a pullback or retracement. Observing shifts between narrow and wide phases helps anticipate shifts in momentum.
This can be seen here:
Simple Cloud Overlay
You can also use the cloud like this: when it turns purple you sell when it turns aqua color you buy. These signals are not very accurate in ranging markets but therefore they are usually better on almost all timeframes and assets in trending markets. :
Bounces of cloud. The cloud can also be used as a type of support/resistance. In the example below you can see how the trend bounces off of the cloud. For example, you could add up to your position every time it touches the cloud and then you could fully exit when the cloud turns purple or the trend breaks below the cloud:
An example of a way you could use this indicator as a confirmation is here. In the image below, a fake signal is generated, you can eliminate this signal by waiting for the cloud to turn purple in order to have confirmation for a potential downward move:
2. Bar Coloring for Volatility and System States
Traders can choose between two bar-coloring methods:
• Volatility: Bars change color intensity based on the level of current volatility relative to a historical average. This helps in spotting abrupt changes in market behavior, where bars become more pronounced when volatility is higher. You can see the volatility information in the volatility table.
• System Score: Bars receive a color gradient determined by the indicator’s final overall score. This simplifies spotting bullish, bearish, or neutral phases without needing to inspect multiple metrics separately. The closer the final score is to zero the less the color difference between bullish and bearish is.
3. Reversion Signals and Potential Reversal Alerts
Two sets of on-chart markers help in spotting sudden shifts in momentum:
• Reversion Signals marked with the letter R: These signals combine RSI thresholds, stochastic crossovers, and EMA confirmation to identify potential reversals. RSI highlights overbought (above 70) or oversold (below 30) conditions, while stochastic crossovers confirm shifts in momentum. The EMA ensures signals align with the broader trend, reducing false positives in volatile markets. Together, these components provide a reliable way to spot potential market corrections or reversals.
• Potential Reversal Signals marked with small circles: These signals detect subtle shifts in momentum using a smoothed RSI (via TEMA) and changes in its slope. When the slope turns positive or negative near key levels, it highlights early-stage reversals. This approach helps traders identify timely entry or exit opportunities by capturing potential trend changes before they fully develop.
4. Main Metrics Table
A primary dashboard shows detailed performance measures and market analytics. Next to each value, there is a bullish or bearish arrow to hint at the current direction of that metric. The table includes the following:
• Sharpe Ratio: Offers a view of risk-adjusted returns, hinting at whether rewards outweigh the variability in price.
• Sortino Ratio: A variation of risk-adjusted return focusing more on downside risk.
• Treynor Ratio: Displays returns relative to systematic risk, referencing a user-provided beta.
• Information Ratio: Shows how the instrument is outperforming or underperforming a benchmark, scaled by tracking error.
• ROC: Rate of change in price over a specified period, reflecting momentum.
• MACD Histogram: The difference between fast and slow moving average convergence, illustrating momentum shifts.
• CMF: Chaikin Money Flow, evaluating buying or selling pressure by combining price and volume.
• Ulcer Index: A measure of drawdown intensity to gauge how severe downtrends or pullbacks have been.
• Amihud Ratio: Assesses illiquidity by comparing price impact to volume.
• Market Depth Ratio: Looks at price ranges relative to volume activity, indicating how deeply the market can absorb trades.
• S2F Ratio: Incorporates the asset’s circulating supply relative to its yearly production, sometimes referenced in markets with a defined issuance schedule.
• NVT Ratio: A network value to transactions ratio, typically applied to on-chain data.
• MVRV Ratio: Compares the asset’s market value with its realized value, highlighting overall valuation conditions.
• Autocorrelation: Shows how current price movement may be echoing previous price changes.
• Alpha: Measures excess return over what might be expected from a risk-free rate plus systematic market exposure.
• Skewness: Reveals the asymmetry of the return distribution.
• Kurtosis: Looks at whether returns have heavier or lighter tails than typical distributions.
• Max Drawdown: The largest peak-to-trough drop within a lookback window, a key measure of downside risk.
• Calmar Ratio: Evaluates returns in light of drawdowns, relating performance to the severity of pullbacks.
• Omega Ratio: Considers gains versus losses around a threshold return level to measure reward-to-risk balance.
• January Performance: A snapshot of how price behaves in January over a lookback, connected to the idea of seasonality.
• Bid-Ask Spread: Reflects the percentage difference between highest and lowest price in a period, hinting at market liquidity costs.
5. Final Score Table
After analyzing individual metrics, the indicator calculates an overall score that determines if the broader environment appears bullish, bearish, or neutral. This final score then influences optional color schemes across the chart, allowing traders to see at a glance how multiple data points combine into one stance. For those who prefer a visual “gauge,” an additional grid table can be enabled, where boxes fill with varying color intensities based on the current score. The score calculation is complex and uses a similar technique to TPI. It assigns values to each metric and then divides the score by the amount of metrics. The score is then visualized in the System Generation bar coloring option according to how intense the signal is.
Grids (visualization of how much more the score needs to be a full signal.):
6. Volatility Table
A separate table focuses on how current volatility compares with an average measure. When current volatility differs significantly from historical norms, the bars become more vividly colored. If volatility nears its average, the bars are more subdued. This helps traders know when to be cautious of sudden moves or to adapt their position sizing.
Indicator Inputs
Users can tailor numerous inputs to suit the nature of each instrument:
• Risk-Free Rate (annualized rate used for risk calculations)
• Benchmark Return (expected return of the market benchmark)
• Beta (measure of systematic risk, particularly for Treynor Ratio calculations)
• Lookback Period (window of time used for many rolling calculations)
• ROC Period (time span for the rate of change calculation)
• CMF Period (window for the Chaikin Money Flow measure)
• Ulcer Index Period (depth for the Ulcer Index reading)
• Amihud Illiquidity Period (period for measuring price impact relative to volume)
• Market Depth Ratio Period (time range for examining price breadth versus volume)
• Circulating Supply (used for the stock-to-flow calculation)
• Yearly Production (helps update the stock-to-flow ratio)
• Market Cap (overall value of the instrument, often used in ratio metrics)
• Transaction Volume (on-chain or traded volume data for NVT ratio)
• Realized Value (alternative valuation data, used in MVRV calculation)
• Threshold Return for Omega (sets a custom threshold above which returns are considered favorable)
• Bar Coloring Method (choose between volatility-based or final-score-based color themes)
• Table Text Size (adjust the display size of table entries)
• Additional parameters related to internal signals (like RSI lengths or smoothing settings) can be fine-tuned for different market behaviors. It is important to customize these fields according to the characteristics of the specific asset you are trading.
Important!
Adjust the inputs according to your current asset! The inputs under the 'Vital' section have to be adjusted so that the metrics function properly. If not well adjusted to your asset, your final score will be mixed up and System Bar coloring as well! These inputs include: Circulating Supply, Yearly Production, Market Cap, Transaction Volume, and Realized Value!
Originality and Uniqueness
Uptrick: Oracle Metrics + stands out by combining complex metrics, including calculations similar to the Trend Probability Indicator (TPI), to provide a deeper analysis of market conditions. The indicator offers multiple signals tailored to different trading scenarios, allowing users to filter and customize them manually through a variety of features. This flexibility, combined with its advanced risk and trend analysis tools, makes it a versatile solution for both momentum and long-term trading strategies.
Warnings
In some scenarios, overlapping numbers or markers may crowd the chart. A practical fix for any visual overlap is removing the indicator and then reapplying it, which generally resets the tables and color overlays.
Summary
Uptrick: Oracle Metrics + merges cloud-based analytics, bar-coloring for volatility or system state, reversion alerts, and a detailed metrics dashboard into one seamless interface. This synergy of short-term signals and long-term performance metrics aims to give traders a fuller perspective on risk, trend changes, and valuation. By tuning the inputs to each asset, traders can capture more relevant data, while the color-coded approach simplifies quick decision-making in a dynamic market environment.
Disclaimer
The Uptrick: Oracle Metrics + indicator is a tool designed to assist traders in analyzing market conditions and making informed decisions. It is not a guarantee of future performance or a substitute for independent financial advice. Trading involves significant risk, and past results do not guarantee future outcomes. Users are advised to conduct their own research, consider their financial situation, and consult with a licensed financial professional if necessary. Uptrick and its affiliates are not responsible for any financial losses incurred while using this indicator. Use at your own discretion and risk.
Systematic Risk Aggregation ModelThe “Systematic Risk Aggregation Model” is a quantitative trading strategy implemented in Pine Script™ designed to assess and visualize market risk by aggregating multiple financial risk factors. This model uses a multi-dimensional scoring approach to quantify systemic risk, incorporating volatility, drawdowns, put/call ratios, tail risk, volume spikes, and the Sharpe ratio. It derives a composite risk score, which is dynamically smoothed and plotted alongside adaptive Bollinger Bands to identify trading opportunities. The strategy’s theoretical framework aligns with modern portfolio theory and risk management literature (Markowitz, 1952; Taleb, 2007).
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Key Components of the Model
1. Volatility as a Risk Proxy
The model calculates the standard deviation of the closing price over a specified period (volatility_length) to quantify market uncertainty. Volatility is normalized to a score between 0 and 100, using its historical minimum and maximum values.
Reference: Volatility has long been regarded as a critical measure of financial risk and uncertainty in capital markets (Hull, 2008).
2. Drawdown Assessment
The drawdown metric captures the relative distance of the current price from the highest price over the specified period (drawdown_length). This is converted into a normalized score to reflect the magnitude of recent losses.
Reference: Drawdown is a key metric in risk management, often used to measure potential downside risk in portfolios (Maginn et al., 2007).
3. Put/Call Ratio as a Sentiment Indicator
The strategy integrates the put/call ratio, sourced from an external symbol, to assess market sentiment. High values often indicate bearish sentiment, while low values suggest bullish sentiment (Whaley, 2000). The score is normalized similarly to other metrics.
4. Tail Risk via Modified Z-Score
Tail risk is approximated using the modified Z-score, which measures the deviation of the closing price from its moving average relative to its standard deviation. This approach captures extreme price movements and potential “black swan” events.
Reference: Taleb (2007) discusses the importance of considering tail risks in financial systems.
5. Volume Spikes as a Proxy for Market Activity
A volume spike is defined as the ratio of current volume to its moving average. This ratio is normalized into a score, reflecting unusual trading activity, which may signal market turning points.
Reference: Volume analysis is a foundational tool in technical analysis and is often linked to price momentum (Murphy, 1999).
6. Sharpe Ratio for Risk-Adjusted Returns
The Sharpe ratio measures the risk-adjusted return of the asset, using the mean log return divided by its standard deviation over the same period. This ratio is transformed into a score, reflecting the attractiveness of returns relative to risk.
Reference: Sharpe (1966) introduced the Sharpe ratio as a standard measure of portfolio performance.
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Composite Risk Score
The composite risk score is calculated as a weighted average of the individual risk factors:
• Volatility: 30%
• Drawdown: 20%
• Put/Call Ratio: 20%
• Tail Risk (Z-Score): 15%
• Volume Spike: 10%
• Sharpe Ratio: 5%
This aggregation captures the multi-dimensional nature of systemic risk and provides a unified measure of market conditions.
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Dynamic Bands with Bollinger Bands
The composite risk score is smoothed using a moving average and bounded by Bollinger Bands (basis ± 2 standard deviations). These bands provide dynamic thresholds for identifying overbought and oversold market conditions:
• Upper Band: Signals overbought conditions, where risk is elevated.
• Lower Band: Indicates oversold conditions, where risk subsides.
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Trading Strategy
The strategy operates on the following rules:
1. Entry Condition: Enter a long position when the risk score crosses above the upper Bollinger Band, indicating elevated market activity.
2. Exit Condition: Close the long position when the risk score drops below the lower Bollinger Band, signaling a reduction in risk.
These conditions are consistent with momentum-based strategies and adaptive risk control.
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Conclusion
This script exemplifies a systematic approach to risk aggregation, leveraging multiple dimensions of financial risk to create a robust trading strategy. By incorporating well-established risk metrics and sentiment indicators, the model offers a comprehensive view of market dynamics. Its adaptive framework makes it versatile for various market conditions, aligning with contemporary advancements in quantitative finance.
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References
1. Hull, J. C. (2008). Options, Futures, and Other Derivatives. Pearson Education.
2. Maginn, J. L., Tuttle, D. L., McLeavey, D. W., & Pinto, J. E. (2007). Managing Investment Portfolios: A Dynamic Process. Wiley.
3. Markowitz, H. (1952). Portfolio Selection. The Journal of Finance, 7(1), 77–91.
4. Murphy, J. J. (1999). Technical Analysis of the Financial Markets. New York Institute of Finance.
5. Sharpe, W. F. (1966). Mutual Fund Performance. The Journal of Business, 39(1), 119–138.
6. Taleb, N. N. (2007). The Black Swan: The Impact of the Highly Improbable. Random House.
7. Whaley, R. E. (2000). The Investor Fear Gauge. The Journal of Portfolio Management, 26(3), 12–17.
RSI + ADX + ATR 18-01-25Combining RSI (Relative Strength Index), ADX (Average Directional Index), and ATR (Average True Range) creates a synergistic approach to technical analysis. This powerful trio covers momentum, trend strength, and volatility, providing comprehensive insights into market conditions. Here's a deeper exploration of their combined results:
1. Momentum Assessment with RSI
Purpose: RSI measures the speed and magnitude of recent price changes to determine overbought or oversold levels.
Benefit in Combination:
When RSI indicates overbought (above 70) or oversold (below 30) levels, it signals a potential reversal or correction.
However, these signals can be false in strongly trending markets, which is why ADX is used alongside it.
2. Trend Strength Confirmation with ADX
Purpose: ADX confirms the presence and strength of a trend.
Benefit in Combination:
If RSI shows a potential reversal but ADX indicates a strong trend (above 25), the trend is likely to continue, and RSI signals may need to be approached with caution.
Conversely, if ADX is below 20 (weak trend), RSI signals are more likely to indicate genuine reversals, as the market lacks a strong directional push.
3. Volatility Analysis with ATR
Purpose: ATR evaluates the level of price volatility.
Benefit in Combination:
High ATR values indicate volatile conditions where prices can move significantly; this helps in setting wider stop-loss levels to avoid premature exits.
Low ATR values suggest quieter markets, where tighter stop-losses and profit targets are more suitable.
[LeonidasCrypto]Volume Force IndexVolume Force Index (VFI)
Overview
The Volume Force Index (VFI) is a technical indicator that measures the balance between buying and selling pressure in the market by analyzing volume patterns. It helps traders identify potential trend reversals and confirm trend strength.
What It Measures
Buying vs. selling volume pressure
Market momentum
Potential overbought/oversold conditions
Volume trend strength
How to Read the Indicator
Main Components:
Main Line (Green/Red)
Green: Buying pressure is dominant
Red: Selling pressure is dominant
The steeper the slope, the stronger the pressure
Signal Line (Yellow)
Fast EMA that helps identify trend changes
Acts as an early warning system for potential reversals
Dynamic Bands (Red/Green lines)
Adapt to market volatility
Help identify extreme conditions
Based on actual market volatility rather than fixed levels
Signals to Watch
Trend Direction:
Rising oscillator = Increasing buying pressure
Falling oscillator = Increasing selling pressure
Signal Line Crossovers:
Main line crosses above signal line = Potential bullish signal
Main line crosses below signal line = Potential bearish signal
Band Touches:
Touching upper band = Possible buying exhaustion
Touching lower band = Possible selling exhaustion
Color Changes:
Green to Red = Shift to selling pressure
Red to Green = Shift to buying pressure
Best Practices
When to Use:
Trend confirmation
Identifying potential reversals
Volume analysis
Market strength assessment
Tips:
Use in conjunction with price action
Look for divergences with price
More reliable on higher timeframes
Consider market context
Default Settings:
MA Period: 14 (volume calculation)
Smooth Length: 3 (noise reduction)
EMA Period: 4 (signal line)
Volatility Period: 20 (band calculation)
Volatility Multiplier: 1.5 (band width)
Best Markets to Apply
Any market with reliable volume data
Summary
The VFI is a powerful tool that combines volume analysis with trend identification. Its adaptive nature makes it suitable for various market conditions, but it should be used as part of a complete trading strategy, not in isolation.
Liquidity Trading Algorithm (LTA)
The Liquidity Trading Algorithm is an algorithm designed to provide trade signals based on
liquidity conditions in the market. The underlying algorithm is based on the Liquidity
Dependent Price Movement (LDPM) metric and the Liquidity Dependent Price Stability (LDPS)
algorithm.
Together, LDPM and LDPS demonstrate statistically significant forecasting capabilities for price-
action on equities, cryptocurrencies, and futures. LTA takes these liquidity measurements and
translates them into actionable insights by way of entering or exiting a position based
on the future outlooks, as measured by the current liquidity status.
The benefit of LTA is that it can incorporate these powerful liquidity measurements into
actionable insights with several features designed to help you tailor LTA's behavior and
measurements to your desired vantage point. These customizable features come by the way of determining LTA's assessment style, and additional monitoring systems for avoiding bear and bull traps, along with various other quality of life features, discussed in more detail below.
First, a few quick facts:
- LTA is compatible on a wide array of instruments, including Equities, Futures, Cryptocurrencies, and Forex.
- LTA is compatible on most intervals in so long as the data can be calculated appropriately,
(be sure to do a backtest on timescales less than 1-minue to ensure the data can be computed).
- LTA only measures liquidity at the end of the interval of the chart chosen, and does not respond to conditions during the candle interval, unless specified (such as with `Stops`).
- LTA is interval-dependent, this means it will measure and behave differently on different
intervals as the underlying algorithms are dependent on the interval chosen.
- LTA can utilize fractional share sizing for cryptocurrencies.
- LTA can be restricted to either bullish or bearish indications.
- Additional Monitoring Systems are available for additional risk mitigation.
In short, LTA is a widely applicable, unique algorithm designed to translate liquidity measurements into liquidity insights.
Before getting more into the details, here is a quick list of the main features and settings
available for customization:
- Backtesting Start Date: Manual selection of the start date for the algorithm during backtesting.
- Assessment Style: adjust how LDPM and LDPS measure and respond to changes in liquidity.
- Impose Wait: force LTA to wait before entering or exiting a position to ensure conditions have remained conducive.
- Trade Direction Allowance: Restrict LTA to only long or only short, if desired.
- Position Sizing Method: determine how LTA calculates position sizing.
- Fractional Share Sizing: allow LTA to calculate fractional share sizes for cryptocurrencies
- Max Size Limit: Impose a maximum size on LTA's positions.
- Initial Capital: Indicate how much capital LTA should stat with.
- Portfolio Allotment: Indicate to LTA how much (in percentages) of the available balance should be considered when calculating position size.
- Enact Additional Monitoring Systems: Indicate if LTA should impose additional safety criteria when monitoring liquidity.
- Configure Take Profit, Stop-Loss, Trailing Stop Loss
- Display Information tables on the current position, overall strategy performance, along
with a text output showing LTA's processes.
- Real-time text output and updates on LTA's inner workings.
Let's get into some more of the details.
LTA's Assessment Style
LTA's assessment style determines how LTA collects and responds to changing data. In traditional terms, this is akin to (but not quite exactly the same as) the sensitivity versus specificity spectrum, whereby on one end (the sensitive end), an algorithm responds to changes in data in a reactive manner (which tends to lower its specificity, or how often it is correct in its indications), and on the other end, the opposite one, the algorithm foresakes quick changes for longevity of outlook.
While this is in part true, it is not a full view of the underlying mechanisms that changing the assessment style augments. A better analogy would be that the sensitive end of the spectrum (`Aggressive`) is in a state such that the algorithm wants to changing its outlooks, and as such, with changes in data, the algorithm has to be convinced as to why that is not a good idea to change outlooks, whereas the the more specific states (`Conservative`, `Diamond`) must be convinced that their view is no longer valid and that it needs to be changed.
This means the `Aggressive` and the `Diamond` settings fundamentally differ not just in their
data collection, but also in the data processing such that the `Aggressive` decision tree has to
be convinced that the data is the same (as its defualt is that it has changed),
and the `Diamond` decision tree has to be convinced that the data is not the same, and as such, the outlook need changed.
From there, the algorithm cooks through the data and determines to what the outlook should be changed to, given the current state of liquidity.
`Balanced` lies in the middle of this balance, attempting to balance being open to new ideas while not removing the wisdom of the past, as it were.
On a scale of most `sensitive` to most `specific`, it is as follows: `Aggressive`, `Balanced`,
`Conservative`, `Diamond`.
Functionally, these different modes can help in different liquidity environments, as certain
environments are more conducive to an eager approach (such as found near `Aggressive`) or are more conducive to a more conservative approach, where sudden changes in liquidity are known to be short-lived and unremarkable (such as many previously identified bull or bear traps).
For instance, on low interval views, it can often-times be beneficial to keep the algorithm towards the `Sensitive` end, since on the lower-timeframes, the crosswinds can change quite dramatically; whereas on the longer intervals, it may be useful to maintain a more `Specific` algorithm (such as found near `Diamond` mode) setting since longer intervals typically lend themselves to longer time-horizons, which themselves typically lend themselves to "weathering the storm", as it were.
LTA's Assessment Style is also supported by the Additional Monitoring Systems which works
to add sensitivity without sacrificing specificity by enacting a separate monitoring system, as described below.
Additional Monitoring Systems
The Additional Monitoring System (AMS) attempts to add more context to any changes in liquidity conditions as measured, such that LTA as a whole will have an expanded view into any rapidly changing liquidity conditions before these changes manifest in the traditional data streams. The ideal is that this allows for early exits or early entrances to positions "a head of time".
The traditional use of this system is to indicate when liquidity is suggestive of the end of a particular run (be it a bear run or a bull run), so an early exit can be initiated (and thus,
downside averted) even before the data officially showcase such changes. In such cases (when AMS becomes activated), the algorithm will signal to exit any open positions, and will restrict the opening of any new positions.
When a position is exited because of AMS, it is denoted as an `Early Exit` and if a position is prevented from being entered, the text output will display `AM prevented entry...` to indicate that conditions are not meeting AMS' additional standards.
The algorithm will wait to make any actions while `AMS` is `active` and will only enter into a new position once `AMS` has been `deactivated` and overall liquidity conditions are appropriate.
Functionally, the benefits of AMS translate to:
- Toggeling AMS on will typically see a net reduction in overall profitability, but
- AMS will typically (almost always) reduce max drawdown,
an increases in max runup, and increase return-over-maxdrawdown, and
- AMS can provide benefit for equities that experience a lot of "traps" by navigating early
entrance and early exits.
So in short, AMS is way of adding an additional level of liquidity monitoring that attempts to
exit positions if conditions look to be deteriorating, and to enter conditions if they look to be
improving. The cost of this additional monitoring, however, is a greater number of trades indicated, and a lower overall profitability.
Impose Wait
Note: `Impose Wait` will not force Take Profit, Stop Loss, or Trailing Stop Loss to
wait.
LTA can be indicated to `wait` before entering or exiting a position if desired. This means that if conditions change, whereas without a `wait` imposed, the algorithm would immediately indicate this change via a signal to alter the strategy's position, with a `wait` imposed, the algorithm will `wait` the indicated number of bars, and then re-check conditions before proceeding.
If, while waiting, conditions change to a state that is no longer compatible with the "order-in-
waiting", then the order-in-waiting is removed, and the counts reset (i.e.: conditions must remain favorable to the intended positional change throughout the wait period).
Since LTA works at the end-of-intervals, there is an inherently "built-in" wait of 1 bar when
switching directly from long to short (i.e.: if a full switch is indicated, then it is indicated as
conditions change -> exit new position -> wait until -> check conditions ->
enter new position as indicated). Thus, to impose a wait of `1 bar` would be to effectively have a total of two candles' ends prior to the entrance of the new position).
There are two main styles of `Impose Wait` that you can utilize:
- `Wait` : this mode will cause LTA to `wait` when both entering and exiting a position (in so long as it is not an exit signaled via a Take Profit, Stop Loss or Trailing Stop Loss).
- `Exit-Wait` : This mode will >not< cause LTA to `wait` if conditions require the closing of a position, but will force LTA to wait before entering into a position.
Position:
In addition to the availability to restrict LTA to either a long-only or short-only strategy, LTA
also comprises additional flexibility when deciding on how it should navigate the markets with
regards to sizing. Notably, this flexibility benefits several aspects of LTA's existence, namely the ability to determine the `Sizing Method`, or if `Fractional Share Sizing` should be employed, and more, as discussed below.
Position Sizing Method
There are two main ways LTA can determine the size of a position. Either via the `Fixed-Share` choice, or the `Fixed-Percentage` choice.
- `Fixed-Share` will use the amount indicated in the `Max Sizing Limit` field as the position size, always.
Note: With `Fixed-Share` sizing, LTA will >not< check if the balance is sufficient
prior to signaling an entrance.
- `Fixed-Percentage` will use the percentage amount indicated in the `Portfolio Allotment` field as the percentage of available funds to use when calculating the position size. Additionally, with the `Fixed-Percentage` choice, you can set the `Max Sizing Limit` if desired, which will ensure that no position will be entered greater than the amount indicated in the field.
Fractional Share Sizing
If the underlying instrument supports it (typically only cryptocurrencies), share sizing can be
fractionalized. If this is done, the resulting positin size is rounded to `4 digits`. This means any
position with a size less than `0.00005` will be rounded to `0.0000`
Note: Ensure that the underlying instrument supports fractional share sizing prior
to initiating.
Max Sizing Limit
As discussed above, the `Max Sizing Limit` will determine:
- The position size for every position, if `Sizing Method : Fixed-Share` is utilized, or
- The maximum allowed size, regardless of available capital, if `Sizing Method : Fixed-Percentage` is utilized.
Note: There is an internal maximum of 100,000 units.
Initial Capital
Note: There are 2 `Initial Capital` settings; one in LTA's settings and one in the
`Properties` tab. Ensure these two are the same when doing backtesting.
The initial capital field will be used to determine the starting balanace of the strategy, and
is used to calculate the internal data reporting (the data tables).
Portfolio Allotment
You can specify how much of the total available balance should be used when calculating the share size. The default is 100%.
Stops
Note: Stops over-ride `AMS` and `Impose Wait`, and are not restricted to only the
end-of-candle and will occur instantaneously upon their activation. Neither `AMS` nor `Impose Wait` can over-ride a signal from a `Take-Profit`, `Stop-Loss`, or a `Trailing-Stop Loss`.
LTA enhouses three stops that can be configured, a `Take-Profit`, a `Stop-Loss` and a `Trailing-Stop Loss`. The configurations can be set in the settings in percent terms. These exit signals will always over-ride AMS or any other restrictions on position exit.
Their configuration is rather standard; set the percentages you want the signal to be sent at and so it will be done.
Some quick notes on the `Trailing-Stop Loss`:
- The activation percentage must be reached (in profits) prior to the `Traililng-Stop Loss`
from activating the downside protection. For example, if the `Activation Percentage` is 10%, then unless the position reaches (at any point) a 10% profit, then it will not signal any exits on the downside, should it occur.
- The downside price-point is continuously updated and is calculated from the maximum profit reached in the given position and the loss percentage placed in the appropriate field.
Data Tables and Data Output
LTA provides real-time data output through a variety of mechanisms:
- `Position Table`
The `Position Table` displays information about the current position, including:
> Position Duration : how long the position has been open for.
> Indicates if the side is Long or Short, depending on if it is long or short.
> Entry Price: the price the position was entered at.
> Current Price (% Dif): the current price of the underlying and the %-difference between the entry price and the current price.
> Max Profit ($/%): the maximum profit reached in $ and % terms.
> Current PnL ($/%) : the current PnL for the open position.
- `Performance Table`
The `Performance Table` displays information regarding the overall performance of the algorithm since its `Start Date`. These data include:
> Initial Equity ($): The initial equity the algorithm started with.
> Current Equity ($): The current total equity of the account (including open positions)
> Net Profits ($|%) : The overall net profit in $ and % terms.
> Long / Short Trade Counts: The respective trade counts for the positions entered.
> Total Closed Trades: The running sum of the number of trades closed.
> Profitability: The calculation of the number of profitable trades over the total number of
trades.
> Avg. Profit / Trade: The calculation of the average profit per trade in both $ and % terms.
> Avg. Loss / Trade: The calculation of the average loss per trade in both $ and % terms.
> Max Run-Up: The maximum run-up the algorithm has seen in both $ and % terms.
> Max Drawdown: The maximum draw-down the algorithm has seen in both $ and % terms.
> Return-Over-Max-Drawdown: the ratio of the maximum drawdown against the current net profits.
- `Text Output`
LTA will output, if desired, signals to the text output field every time it analysis or performs and action. These messages can include information such as:
"
08:00:00 >> AM Protocol activated ... exiting position ...
08:00:00 >> Exit Order Created for qty: 2, profit: 380 (4.34%)
...
09:30:00 >> Checking conditions ...
09:30:00 >> AM protocol prevented entry ... waiting ...
"
This way, you can keep an eye out on what is happening "under the hood", as it were.
LTA will produce a message at the end of its assessment at the end of each candle interval, as well as when a position is exited due to a `Stop` or due to `AMS` being activated.
Additionally, the `Text Output` includes a initial message, but for space-constraints, this
can be toggled off with the `Blank Text Output` option within LTA's configurations.
For additional information, please refer to the Author's Instructions below.
Volume profile [Signals] - By Leviathan [Mindyourbuisness]Market Sessions and Volume Profile with Sweep Signals - Based on Leviathan's Volume Profile
This indicator is an enhanced version of Leviathan's Volume Profile indicator, adding session-based value area analysis and sweep detection signals. It combines volume profile analysis with market structure concepts to identify potential reversal opportunities.
Features
- Session-based volume profiles (Daily, Weekly, Monthly, Quarterly, Yearly)
- Forex sessions support (Tokyo, London, New York)
- Value Area analysis with POC, VAH, and VAL levels
- Extended level visualization for the last completed session
- Sweep detection signals for key value area levels
Sweep Signals Explanation
The indicator detects two types of sweeps at VAH, VAL, and POC levels:
Bearish Sweeps (Red Triangle Down)
Conditions:
- Price makes a high above the level (VAH/VAL/POC)
- Closes below the level
- Closes below the previous candle's low
- Previous candle must be bullish
Trading Implication: Suggests a failed breakout and potential reversal to the downside. These sweeps often indicate stop-loss hunting above key levels followed by institutional selling.
Bullish Sweeps (Green Triangle Up)
Conditions:
- Price makes a low below the level (VAH/VAL/POC)
- Closes above the level
- Closes above the previous candle's high
- Previous candle must be bearish
Trading Implication: Suggests a failed breakdown and potential reversal to the upside. These sweeps often indicate stop-loss hunting below key levels followed by institutional buying.
Trading Guidelines
1. Use sweep signals in conjunction with the overall trend
2. Look for additional confirmation like:
- Volume surge during the sweep
- Price action patterns
- Support/resistance levels
3. Consider the session's volatility and time of day
4. More reliable signals often occur at VAH and VAL levels
5. POC sweeps might indicate stronger reversals due to their significance as fair value levels
Notes
- The indicator works best on higher timeframes (1H and above)
- Sweep signals are more reliable during active market hours
- Consider using multiple timeframe analysis for better confirmation
- Past performance is not indicative of future results
Credits: Original Volume Profile indicator by Leviathan
Sunil BB Blast Heikin Ashi StrategySunil BB Blast Heikin Ashi Strategy
The Sunil BB Blast Heikin Ashi Strategy is a trend-following trading strategy that combines Bollinger Bands with Heikin-Ashi candles for precise market entries and exits. It aims to capitalize on price volatility while ensuring controlled risk through dynamic stop-loss and take-profit levels based on a user-defined Risk-to-Reward Ratio (RRR).
Key Features:
Trading Window:
The strategy operates within a user-defined time window (e.g., from 09:20 to 15:00) to align with market hours or other preferred trading sessions.
Trade Direction:
Users can select between Long Only, Short Only, or Long/Short trade directions, allowing flexibility depending on market conditions.
Bollinger Bands:
Bollinger Bands are used to identify potential breakout or breakdown zones. The strategy enters trades when price breaks through the upper or lower Bollinger Band, indicating a possible trend continuation.
Heikin-Ashi Candles:
Heikin-Ashi candles help smooth price action and filter out market noise. The strategy uses these candles to confirm trend direction and improve entry accuracy.
Risk Management (Risk-to-Reward Ratio):
The strategy automatically adjusts the take-profit (TP) level and stop-loss (SL) based on the selected Risk-to-Reward Ratio (RRR). This ensures that trades are risk-managed effectively.
Automated Alerts and Webhooks:
The strategy includes automated alerts for trade entries and exits. Users can set up JSON webhooks for external execution or trading automation.
Active Position Tracking:
The strategy tracks whether there is an active position (long or short) and only exits when price hits the pre-defined SL or TP levels.
Exit Conditions:
The strategy exits positions when either the take-profit (TP) or stop-loss (SL) levels are hit, ensuring risk management is adhered to.
Default Settings:
Trading Window:
09:20-15:00
This setting confines the strategy to the specified hours, ensuring trading only occurs during active market hours.
Strategy Direction:
Default: Long/Short
This allows for both long and short trades depending on market conditions. You can select "Long Only" or "Short Only" if you prefer to trade in one direction.
Bollinger Band Length (bbLength):
Default: 19
Length of the moving average used to calculate the Bollinger Bands.
Bollinger Band Multiplier (bbMultiplier):
Default: 2.0
Multiplier used to calculate the upper and lower bands. A higher multiplier increases the width of the bands, leading to fewer but more significant trades.
Take Profit Multiplier (tpMultiplier):
Default: 2.0
Multiplier used to determine the take-profit level based on the calculated stop-loss. This ensures that the profit target aligns with the selected Risk-to-Reward Ratio.
Risk-to-Reward Ratio (RRR):
Default: 1.0
The ratio used to calculate the take-profit relative to the stop-loss. A higher RRR means larger profit targets.
Trade Automation (JSON Webhooks):
Allows for integration with external systems for automated execution:
Long Entry JSON: Customizable entry condition for long positions.
Long Exit JSON: Customizable exit condition for long positions.
Short Entry JSON: Customizable entry condition for short positions.
Short Exit JSON: Customizable exit condition for short positions.
Entry Logic:
Long Entry:
The strategy enters a long position when:
The Heikin-Ashi candle shows a bullish trend (green close > open).
The price is above the upper Bollinger Band, signaling a breakout.
The previous candle also closed higher than it opened.
Short Entry:
The strategy enters a short position when:
The Heikin-Ashi candle shows a bearish trend (red close < open).
The price is below the lower Bollinger Band, signaling a breakdown.
The previous candle also closed lower than it opened.
Exit Logic:
Take-Profit (TP):
The take-profit level is calculated as a multiple of the distance between the entry price and the stop-loss level, determined by the selected Risk-to-Reward Ratio (RRR).
Stop-Loss (SL):
The stop-loss is placed at the opposite Bollinger Band level (lower for long positions, upper for short positions).
Exit Trigger:
The strategy exits a trade when either the take-profit or stop-loss level is hit.
Plotting and Visuals:
The Heikin-Ashi candles are displayed on the chart, with green candles for uptrends and red candles for downtrends.
Bollinger Bands (upper, lower, and basis) are plotted for visual reference.
Entry points for long and short trades are marked with green and red labels below and above bars, respectively.
Strategy Alerts:
Alerts are triggered when:
A long entry condition is met.
A short entry condition is met.
A trade exits (either via take-profit or stop-loss).
These alerts can be used to trigger notifications or webhook events for automated trading systems.
Notes:
The strategy is designed for use on intraday charts but can be applied to any timeframe.
It is highly customizable, allowing for tailored risk management and trading windows.
The Sunil BB Blast Heikin Ashi Strategy combines two powerful technical analysis tools (Bollinger Bands and Heikin-Ashi candles) with strong risk management, making it suitable for both beginners and experienced traders.
Feebacks are welcome from the users.
Advanced Options Trading Indicator: Buy & Sell Signal Generator This powerful custom indicator combines the Relative Strength Index (RSI) and Moving Average (MA) to help traders identify optimal entry and exit points in the options market. The indicator generates real-time buy and sell signals based on RSI crossovers and price positioning relative to the moving average, providing actionable insights for traders seeking to make informed decisions. Additionally, it calculates potential call and put option strike prices with a buffer for added flexibility and precision, ensuring a well-rounded approach to options trading.
Machine Learning Price Target Prediction Signals [AlgoAlpha]Introducing the Machine Learning Price Target Predictions, a cutting-edge trading tool that leverages kernel regression to provide accurate price targets and enhance your trading strategy. This indicator combines trend-based signals with advanced machine learning techniques, offering predictive insights into potential price movements. Perfect for traders looking to make data-driven decisions with confidence.
What is Kernel Regression and How It Works
Kernel regression is a non-parametric machine learning technique that estimates the relationship between variables by weighting data points based on their similarity to a given input. The similarity is determined using a kernel function, such as the Gaussian (RBF) kernel, which assigns higher weights to closer data points and progressively lower weights to farther ones. This allows the model to make smooth and adaptive predictions, balancing recent data and historical trends.
Key Features
🎯 Predictive Price Targets : Uses kernel regression to estimate the magnitude of price movements.
📈 Dynamic Trend Analysis : Multiple trend detection methods, including EMA crossovers, Hull Moving Average, and SuperTrend.
🔧 Customizable Settings : Adjust bandwidth for kernel regression and tweak trend indicator parameters to suit your strategy.
📊 Visual Trade Levels : Displays take-profit and stop-loss levels directly on the chart with customizable colors.
📋 Performance Metrics : Real-time win rate, recommended risk-reward ratio, and training data size displayed in an on-chart table.
🔔 Alerts : Get notified for new trends, take-profit hits, and stop-loss triggers.
How to Use
🛠 Add the Indicator : Add it to your favorites and apply it to your chart. Configure the trend detection method (SuperTrend, HMA, or EMA crossover) and other parameters based on your preferences.
📊 Analyze Predictions : Observe the predicted move size, recommended risk-reward ratio, and trend direction. Use the displayed levels for trade planning.
🔔 Set Alerts : Enable alerts for trend signals, take-profit hits, or stop-loss triggers to stay informed without constant monitoring.
How It Works
The indicator calculates features such as price volatility, relative strength, and trend signals, which are stored during training periods. When a trend change is detected, the kernel regression model predicts the likely price move based on these features. Predictions are smoothed using the specified bandwidth to avoid overfitting while ensuring timely responses to feature changes. Visualized take-profit and stop-loss levels help traders optimize risk management. Real-time metrics like win rate and recommended risk-reward ratios provide actionable insights for decision-making.
Optimized Engulfing StrategyOptimized Engulfing Strategy
The Optimized Engulfing Strategy is a trend-following system designed to capitalize on bullish and bearish engulfing patterns in the market. It uses a combination of price action, trend direction, and volatility-based risk management to execute high-probability trades.
Key Components:
Bullish Engulfing Pattern:
A bullish engulfing candle is identified when:
The current candle closes above its open (bullish).
The previous candle closes below its open (bearish).
The current candle's close is higher than the previous candle's open.
The current candle's open is lower than the previous candle's close.
This pattern signals potential bullish momentum.
Bearish Engulfing Pattern:
A bearish engulfing candle is identified when:
The current candle closes below its open (bearish).
The previous candle closes above its open (bullish).
The current candle's close is lower than the previous candle's open.
The current candle's open is higher than the previous candle's close.
This pattern signals potential bearish momentum.
Trend Confirmation:
Trades are only taken in the direction of the trend:
Buy: When the 50-period SMA (simple moving average) is above the 200-period SMA, indicating an uptrend.
Sell: When the 50-period SMA is below the 200-period SMA, indicating a downtrend.
Risk Management:
Stop Loss: Placed below the low of the engulfing candle (for buys) or above the high (for sells), with an additional buffer based on the ATR (Average True Range) multiplied by a user-defined factor (default: 1.5).
Take Profit: Calculated using a fixed risk-to-reward ratio (default: 1:2), ensuring a potential reward that is double the risk.
Session Filtering:
Trades can be limited to specific trading hours using a customizable session filter (default: 24 hours).
Trade Execution:
Separate logic is implemented for buy and sell trades, allowing independent toggling of long or short positions via user inputs.
Visualization:
Bullish and bearish engulfing candles are highlighted on the chart for clarity.
The ATR value is displayed in the top-right corner of the chart for reference.
How It Works:
Identify a bullish or bearish engulfing pattern.
Confirm the direction of the trend using the 50 SMA and 200 SMA.
Ensure the market is within the allowed session filter (e.g., London or New York sessions).
Enter a trade if all conditions are met:
Long trades for bullish engulfing patterns in an uptrend.
Short trades for bearish engulfing patterns in a downtrend.
Manage the trade using a stop loss and take profit based on ATR and the risk-reward ratio.
Adaptive Fourier Transform Supertrend [QuantAlgo]Discover a brand new way to analyze trend with Adaptive Fourier Transform Supertrend by QuantAlgo , an innovative technical indicator that combines the power of Fourier analysis with dynamic Supertrend methodology. In essence, it utilizes the frequency domain mathematics and the adaptive volatility control technique to transform complex wave patterns into clear and high probability signals—ideal for both sophisticated traders seeking mathematical precision and investors who appreciate robust trend confirmation!
🟢 Core Architecture
At its core, this indicator employs an adaptive Fourier Transform framework with dynamic volatility-controlled Supertrend bands. It utilizes multiple harmonic components that let you fine-tune how market frequencies influence trend detection. By combining wave analysis with adaptive volatility bands, the indicator creates a sophisticated yet clear framework for trend identification that dynamically adjusts to changing market conditions.
🟢 Technical Foundation
The indicator builds on three innovative components:
Fourier Wave Analysis: Decomposes price action into primary and harmonic components for precise trend detection
Adaptive Volatility Control: Dynamically adjusts Supertrend bands using combined ATR and standard deviation
Harmonic Integration: Merges multiple frequency components with decreasing weights for comprehensive trend analysis
🟢 Key Features & Signals
The Adaptive Fourier Transform Supertrend transforms complex wave calculations into clear visual signals with:
Dynamic trend bands that adapt to market volatility
Sophisticated cloud-fill visualization system
Strategic L/S markers at key trend reversals
Customizable bar coloring based on trend direction
Comprehensive alert system for trend shifts
🟢 Practical Usage Tips
Here's how you can get the most out of the Adaptive Fourier Transform Supertrend :
1/ Setup:
Add the indicator to your favorites, then apply it to your chart ⭐️
Start with close price as your base source
Use standard Fourier period (14) for balanced wave detection
Begin with default harmonic weight (0.5) for balanced sensitivity
Start with standard Supertrend multiplier (2.0) for reliable band width
2/ Signal Interpretation:
Monitor trend band crossovers for potential signals
Watch for convergence of price with Fourier trend
Use L/S markers for trade entry points
Monitor bar colors for trend confirmation
Configure alerts for significant trend reversals
🟢 Pro Tips
Fine-tune Fourier parameters for optimal sensitivity:
→ Lower Base Period (8-12) for more reactive analysis
→ Higher Base Period (15-30) to filter out noise
→ Adjust Harmonic Weight (0.3-0.7) to control shorter trend influence
Customize Supertrend settings:
→ Lower multiplier (1.5-2.0) for tighter bands
→ Higher multiplier (2.0-3.0) for wider bands
→ Adjust ATR length based on market volatility
Strategy Enhancement:
→ Compare signals across multiple timeframes
→ Combine with volume analysis
→ Use with support/resistance levels
→ Integrate with other momentum indicators
India VIXThe VIX chart represents the Volatility Index, commonly referred to as the "Fear Gauge" of the stock market. It measures the market's expectations of future volatility over the next 30 days, based on the implied volatility of NSE index options. The VIX is often used as an indicator of investor sentiment, reflecting the level of fear or uncertainty in the market.
Here’s a breakdown of what you might observe on a typical VIX chart:
VIX Value: The y-axis typically represents the VIX index value, with higher values indicating higher levels of expected market volatility (more fear or uncertainty), and lower values signaling calm or stable market conditions.
VIX Spikes: Large spikes in the VIX often correspond to market downturns or periods of heightened uncertainty, such as during financial crises or major geopolitical events. A high VIX is often associated with a drop in the stock market.
VIX Drops: A decline in the VIX indicates a reduction in expected market volatility, usually linked with periods of market calm or rising stock prices.
Trend Analysis: Technical traders might use moving averages or other indicators on the VIX chart to assess the potential for future market movements.
Inverse Relationship with the Stock Market: Typically, there is an inverse correlation between the VIX and the stock market. When stocks fall sharply, volatility increases, and the VIX tends to rise. Conversely, when the stock market rallies or remains stable, the VIX tends to fall.
A typical interpretation would be that when the VIX is low, the market is relatively stable, and when the VIX is high, the market is perceived to be uncertain or volatile.
VWAP Fibonacci Bands (Zeiierman)█ Overview
The VWAP Fibonacci Bands is a sophisticated yet user-friendly indicator designed to assist traders in visualizing market trends, volatility, and potential support/resistance levels. Developed by Zeiierman, this tool integrates the MIDAS (Market Interpretation Data Analysis System) methodology with Standard Deviation Bands and user-defined Fibonacci levels to provide a comprehensive market analysis framework.
This indicator is built for traders who want a dynamic and customizable approach to understanding market movements, offering features that adapt to varying market conditions. Whether you're a scalper, swing trader, or long-term investor.
█ How It Works
⚪ Anchor Point System
The indicator begins its calculations based on an anchor point, which can be set to:
A specific date for historical analysis or alignment with significant market events.
A timeframe-based reset, dynamically restarting calculations at the beginning of each selected period (e.g., daily, weekly, or monthly).
This dual-anchor method ensures flexibility, allowing the indicator to align with various trading strategies.
⚪ MIDAS Calculation
The MIDAS calculation is central to this indicator. It uses cumulative price and volume data to compute a volume-weighted average price (VWAP), offering a trendline that reflects the true value weighted by trading activity.
⚪ Standard Deviation Bands
The upper and lower bands are calculated using the standard deviation of price movements around the MIDAS line.
⚪ Fibonacci Levels
User-defined Fibonacci ratios are used to plot additional support and resistance levels between the bands. These levels provide visual cues for potential price reversals or trend continuations.
█ How to Use
⚪ Trend Identification
Uptrend: The price remains above the MIDAS line.
Downtrend: The price stays below the MIDAS line and aligns with the lower bands.
⚪ Support and Resistance
The upper and lower bands act as support and resistance levels.
Fibonacci levels provide intermediate zones for potential price reversals.
⚪ Volatility Analysis
Wider bands indicate periods of high volatility.
Narrower bands suggest low-volatility conditions, often preceding breakouts.
⚪ Overbought/Oversold Conditions
Look for the price beyond the upper or lower bands to identify extreme conditions.
█ Settings
Set Anchor Method
Anchor Method: Choose between Timeframe or Date to define the starting point of calculations.
Anchor Timeframe: For Timeframe mode, specify the interval (e.g., Daily, Weekly).
Anchor Date: For Date mode, set the exact starting date for historical alignment.
Set Std Dev Multiplier
Controls the width of the bands:
Higher values widen the bands, filtering out minor fluctuations.
Lower values tighten the bands for more responsive analysis.
Set Fibonacci Levels
Define custom Fibonacci ratios (e.g., 0.236, 0.382) to plot intermediate levels between the bands.
█ Tips for Fine-Tuning
⚪ For Trend Trading:
Use higher Std Dev Multipliers to focus on long-term trends and avoid noise. Adjust Anchor Timeframe to Weekly or Monthly for broader trend analysis.
⚪ For Reversal Trading:
Tighten the bands with a lower Std Dev Multiplier.
Use shorter anchor timeframes for intraday reversals (e.g., Hourly).
⚪ For Volatile Markets:
Increase the Std Dev Multiplier to accommodate wider price swings.
⚪ For Quiet Markets:
Decrease the Std Dev Multiplier to highlight smaller fluctuations.
-----------------
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!
Risk-Adjusted Trend IndicatorThe Risk-Adjusted Trend Indicator is a comprehensive tool designed to evaluate market trends while factoring in risk levels. By combining trend strength, volatility, and dynamic scaling, this indicator provides traders with clear, actionable signals for optimal entries and exits. Its focus on risk-adjusted metrics ensures that signals are both reliable and contextually informed by prevailing market conditions.
Key Features:
1. Exponential Moving Average (EMA):
• The EMA serves as the foundation for trend detection, offering a smoothed representation of price movement over a user-defined period.
• Aids in distinguishing bullish and bearish trends effectively.
2. Average True Range (ATR):
• ATR is used to gauge market volatility, ensuring that the indicator adapts to changing market conditions.
• Facilitates the normalization of trend strength relative to current market volatility.
3. Risk-Adjusted Trend Score:
• Computes the difference between the price and EMA and normalizes it using the ATR to account for risk.
• This metric allows traders to focus on trends with favorable risk-reward ratios, filtering out weak or high-risk setups.
4. Dynamic Scaling:
• Adjusts the risk-adjusted score to fit within the chart’s price range, making the visualization intuitive and easy to interpret.
5. Buy/Sell Signals:
• Buy signals are triggered when the risk-adjusted score crosses above a positive threshold.
• Sell signals are triggered when the score crosses below a negative threshold.
• Signals are plotted directly on the chart with intuitive markers for quick decision-making.
6. Background Color Zones:
• Highlights bullish and bearish trend zones using subtle background shading, enhancing visual clarity.
Reason for Combining These Elements
The Risk-Adjusted Trend Indicator blends elements of trend analysis, volatility measurement, and risk assessment to address a fundamental challenge in trading: identifying high-confidence trades that align with a trader’s risk tolerance. Here’s why these components were chosen and how they work together:
1. EMA (Trend Detection):
• Provides a reliable baseline for trend direction, ensuring that the indicator aligns with the market’s prevailing trend.
2. ATR (Volatility Normalization):
• Adjusts trend strength calculations based on market volatility, allowing the indicator to adapt to varying market conditions and avoid false signals in high-volatility environments.
3. Risk-Adjusted Score:
• By factoring in both trend strength and volatility, this score ensures that only trends with favorable risk-reward dynamics are highlighted.
• This approach minimizes overtrading and reduces exposure to high-risk setups.
4. Dynamic Scaling:
• Ensures that the indicator’s outputs remain visually accessible, regardless of the asset or timeframe being analyzed.
• Enhances usability by aligning the score with price action on the chart.
5. Visual Aids (Signals and Background Zones):
• The inclusion of visual signals and background zones simplifies decision-making, making the tool suitable for both novice and experienced traders.
Simple Trend Strength & MomentumThis indicator will show a combination of Trend Strength, Volatility using an Adaptive Moving Average (AMA), and Market Momentum.
You can use this indicator to identify trends, volatility, and momentum shifts in real-time, making it an excellent tool for both trend-following and breakout strategies.
The three main features of this indicator are:
Adaptive Moving Average (AMA): Tracks the trend direction with a dynamic smoothing factor that adjusts based on market volatility. The AMA line changes color based on trend strength (green for bullish, red for bearish). I manually compute the Adaptive Moving Average (AMA) using a smoothing factor derived from the market's efficiency ratio. I have used fastLength and slowLength to control the responsiveness of the AMA.
Volatility Bands: Plots upper and lower bands around the AMA line, indicating price volatility. These bands dynamically adjust based on ATR, with a color gradient that changes intensity based on market volatility.
Momentum Circles: Positive momentum (ROC above the threshold) is shown as a green circle below the bar, while negative momentum is marked by a red circle above the bar. This makes it easy to spot momentum shifts.
The green dots in the indicator represent positive momentum. Specifically, they are displayed when the Rate of Change (ROC) of the price exceeds a predefined threshold (set as threshold in the input). This indicates that the market is experiencing upward price movement at a rate faster than the defined threshold.
How it works:
Rate of Change (ROC) measures the percentage change in price over a specified period (in this case, 14 periods).
When the ROC is greater than the set threshold (1.5 by default), a green circle (dot) is plotted below the price bar to signal that there is significant positive momentum.
This can be seen as an indicator of bullish momentum, where price is increasing at a relatively fast pace compared to previous periods.
The green dots help you spot when the price is moving upward rapidly, potentially signaling a good time to enter a long position or watch for further price action.
NOTE: It is vice versa for red dots.
Multi-Timeframe Volatility ATR - [by Oberlunar]This script (for now in beta release) is specifically designed for scalping or traders operating on lower timeframes (if you are in a timeframe of one minute wait one minute to collect statistics). Its primary purpose is to provide detailed insights into market volatility by calculating the ATR (Average True Range) and its percentage changes, allowing traders to quickly identify shifts in market conditions.
The ATR is calculated across six user-defined timeframes, which can include very short intervals such as 5 or 15 seconds. This setup enables real-time monitoring of volatility, which is critical for scalping strategies. The script collects a rolling history of the last five ATR values for each timeframe. These historical values are used to calculate percentage changes by comparing the current ATR with the oldest value in the history, offering a clear view of how volatility is evolving over time.
Percentage changes are displayed dynamically in a table, with color-coded feedback to indicate the direction of the change: green for increases, red for decreases, and gray for stability or insufficient data. This visual representation makes it easy to spot whether market volatility is rising or falling at a glance.
By progressively collecting data, the script becomes increasingly effective as more ATR values are accumulated. This functionality is especially useful for traders on lower timeframes, where rapid changes in volatility can signal breakout opportunities or shifts in market dynamics.
Soon I will update personalized ATR parameters, and lookback strategies for statistics.
Choppiness Index (levels)This Pine Script is a Choppiness Index Indicator with gradient visual enhancements. The Choppiness Index is a technical analysis tool that measures the "choppiness" or sideways movement of the market. It ranges from 0 to 100, where higher values indicate a more consolidated or sideways market, and lower values suggest a trending market.
Key Features:
Choppiness Index Calculation:
The script calculates the Choppiness Index based on the Average True Range (ATR) and the highest and lowest prices over a user-defined period (length).
Visual Bands:
Horizontal dashed lines are drawn at levels 55 (Upper Band), 50 (Middle Band), and 45 (Lower Band) to define key levels for interpreting the indicator.
Gradient Fills:
A blue fill is applied between the upper and lower bands (45–55) for visual clarity.
Dynamic gradients are applied to the areas:
Above the Upper Band (55–100): A green gradient fill where the color intensity increases with higher values.
Below the Lower Band (0–45): A red gradient fill where the color intensity increases with lower values.
Offset Option:
The offset input allows users to shift the Choppiness Index plot horizontally for visualization or alignment purposes.
Usage:
This indicator helps traders quickly assess market conditions:
Values above 55 indicate a choppy, non-trending market.
Values below 45 indicate a trending market.
The gradient fills make it easier to spot extreme conditions visually.
Customization:
Users can adjust:
length: The calculation period for the Choppiness Index.
offset: Horizontal shift of the Choppiness Index plot.
The gradient colors (green and red) and transparency levels are customizable in the script.
This enhanced visualization is ideal for traders who want a clear and intuitive representation of market choppiness, combined with visually striking gradient fills for quick analysis of market conditions.
US Treasury Yields ROC1. Motivation and Context
The yield curve, which represents the relationship between bond yields and their maturities, plays a pivotal role in macroeconomic analysis and market forecasting. Changes in the slope or curvature of the yield curve are often indicative of investor expectations about economic growth, inflation, and monetary policy. For example:
• Steepening curves may indicate economic optimism and rising inflation expectations.
• Flattening curves are often associated with slower growth or impending recessions.
Analyzing these dynamics with quantitative tools such as the rate of change (ROC) enables traders and analysts to identify actionable patterns in the market. As highlighted by Gürkaynak, Sack, and Wright (2007), the term structure of interest rates embeds significant economic information, and understanding its movements is crucial for both policy makers and market participants.
2. Methodology
2.1 Input Parameters
The script takes the following key input:
• ROC Period (roc_length): Determines the number of bars over which the rate of change is calculated. This is an adjustable parameter (14 by default), allowing users to adapt the analysis to different timeframes.
2.2 Data Sources
The yields of the US Treasury securities for different maturities are fetched from TradingView using the request.security() function:
• 2-Year Yield (TVC:US02Y)
• 5-Year Yield (TVC:US05Y)
• 10-Year Yield (TVC:US10Y)
• 30-Year Yield (TVC:US30Y)
These yields are central to identifying trends in short-term versus long-term rates.
2.3 Visualization
Plots: The ROC values for each maturity are plotted in distinct colors for clarity:
• 2Y: Blue
• 5Y: Yellow
• 10Y: Green
• 30Y: Red
Background Highlight: The script uses color-coded backgrounds to visualize the identified curve regimes:
• Bull Steepener: Neon Green
• Bear Steepener: Bright Red
• Bull Flattener: Blue
• Bear Flattener: Orange
2.4 Zero Line
A horizontal zero line is included as a reference point, allowing users to easily identify transitions from negative to positive ROC values, which may signal shifts in the yield curve dynamics.
3. Implications for Financial Analysis
By automating the identification of yield curve dynamics, this script aids in:
• Macroeconomic Forecasting:
Steepeners and flatteners are associated with growth expectations and monetary policy changes. For instance, Bernanke and Blinder (1992) emphasize the predictive power of the yield curve for future economic activity.
• Trading Strategies:
Yield curve steepening or flattening can inform bond market strategies, such as long/short duration trades or curve positioning.
4. References
1. Bernanke, B. S., & Blinder, A. S. (1992). “The Federal Funds Rate and the Channels of Monetary Transmission.” American Economic Review, 82(4), 901–921.
2. Gürkaynak, R. S., Sack, B., & Wright, J. H. (2007). “The U.S. Treasury Yield Curve: 1961 to the Present.” Journal of Monetary Economics, 54(8), 2291–2304.
3. TradingView Documentation. “request.security Function.” Retrieved from TradingView.
Multi-Band Comparison (Uptrend)Multi-Band Comparison
Overview:
The Multi-Band Comparison indicator is engineered to reveal critical levels of support and resistance in strong uptrends. In a healthy upward market, the price action will adhere closely to the 95th percentile line (the Upper Quantile Band), effectively “riding” it. This indicator combines a modified Bollinger Band (set at one standard deviation), quantile analysis (95% and 5% levels), and power‑law math to display a dynamic picture of market structure—highlighting a “golden channel” and robust support areas.
Key Components & Calculations:
The Golden Channel: Upper Bollinger Band & Upper Std Dev Band of the Upper Quantile
Upper Bollinger Band:
Calculation:
boll_upper=SMA(close,length)+(boll_mult×stdev)
boll_upper=SMA(close,length)+(boll_mult×stdev) Here, the 20-period SMA is used along with one standard deviation of the close, where the multiplier (boll_mult) is 1.0.
Role in an Uptrend:
In a healthy uptrend, price rides near the 95th percentile line. When price crosses above this Upper Bollinger Band, it confirms strong bullish momentum.
Upper Std Dev Band of the Upper Quantile (95th Percentile) Band:
Calculation:
quant_upper_std_up=quant_upper+stdev
quant_upper_std_up=quant_upper+stdev The Upper Quantile Band, quant_upperquant_upper, is calculated as the 95th percentile of recent price data. Adding one standard deviation creates an extension that accounts for normal volatility around this extreme level.
The Golden Channel:
When the price crosses above the Upper Bollinger Band, the Upper Std Dev Band of the Upper Quantile immediately shifts to gold (yellow) and remains gold until price falls below the Bollinger level. Together, these two lines form the “golden channel”—a visual hallmark of a healthy uptrend where the price reliably hugs the 95th percentile level.
Upper Power‑Law Band
Calculation:
The Upper Power‑Law Band is derived in two steps:
Determine the Extreme Return Factor:
power_upper=Percentile(returns,95%)
power_upper=Percentile(returns,95%) where returns are computed as:
returns=closeclose −1.
returns=close close−1.
Scale the Current Price:
power_upper_band=close×(1+power_upper)
power_upper_band=close×(1+power_upper)
Rationale and Correlation:
By focusing on the upper 5% of returns (reflecting “fat tails”), the Upper Power‑Law Band captures extreme but statistically expected movements. In an uptrend, its value often converges with the Upper Std Dev Band of the Upper Quantile because both measures reflect heightened volatility and extreme price levels. When the Upper Power‑Law Band exceeds the Upper Std Dev Band, it can signal a temporary overextension.
Upper Quantile Band (95% Percentile)
Calculation:
quant_upper=Percentile(price,95%)
quant_upper=Percentile(price,95%) This level represents where 95% of past price data falls below, and in a robust uptrend the price action practically rides this line.
Color Logic:
Its color shifts from a neutral (blackish) tone to a vibrant, bullish hue when the Upper Power‑Law Band crosses above it—signaling extra strength in the trend.
Lower Quantile and Its Support
Lower Quantile Band (5% Percentile):
Calculation:
quant_lower=Percentile(price,5%)
quant_lower=Percentile(price,5%)
Behavior:
In a healthy uptrend, price remains well above the Lower Quantile Band. It turns red only when price touches or crosses it, serving as a warning signal. Under normal conditions it remains bright green, indicating the market is not nearing these extreme lows.
Lower Std Dev Band of the Lower Quantile:
This line is calculated by subtracting one standard deviation from quant_lowerquant_lower and typically serves as absolute support in nearly all conditions (except during gap or near-gap moves). Its consistent role as support provides traders with a robust level to monitor.
How to Use the Indicator:
Golden Channel and Trend Confirmation:
As price rides the Upper Quantile (95th percentile) perfectly in a healthy uptrend, the Upper Bollinger Band (1 stdev above SMA) and the Upper Std Dev Band of the Upper Quantile form a “golden channel” once price crosses above the Bollinger level. When this occurs, the Upper Std Dev Band remains gold until price dips back below the Bollinger Band. This visual cue reinforces trend strength.
Power‑Law Insights:
The Upper Power‑Law Band, which is based on extreme (95th percentile) returns, tends to align with the Upper Std Dev Band. This convergence reinforces that extreme, yet statistically expected, price moves are occurring—indicating that even though the price rides the 95th percentile, it can only stretch so far before a correction or consolidation.
Support Indicators:
Primary and Secondary Support in Uptrends:
The Upper Bollinger Band and the Lower Std Dev Band of the Upper Quantile act as support zones for minor retracements in the uptrend.
Absolute Support:
The Lower Std Dev Band of the Lower Quantile serves as an almost invariable support area under most market conditions.
Conclusion:
The Multi-Band Comparison indicator unifies advanced statistical techniques to offer a clear view of uptrend structure. In a healthy bull market, price action rides the 95th percentile line with precision, and when the Upper Bollinger Band is breached, the corresponding Upper Std Dev Band turns gold to form a “golden channel.” This, combined with the Power‑Law analysis that captures extreme moves, and the robust lower support levels, provides traders with powerful, multi-dimensional insights for managing entries, exits, and risk.
Disclaimer:
Trading involves risk. This indicator is for educational purposes only and does not constitute financial advice. Always perform your own analysis before making trading decisions.
majikal78
Custom Volume Ratio Indicator
The Custom Volume Ratio Indicator is a unique tool designed for traders to analyze price movements in relation to trading volume. This indicator calculates the ratio of the price range (the difference between the highest and lowest prices of a candle) to the volume of that candle. By visualizing this ratio, traders can gain insights into market dynamics and potential price movements.
Key Features:
1. Price Range Calculation: The indicator computes the price range for each candle by subtracting the lowest price from the highest price. This gives traders an understanding of how much price fluctuated during that specific time frame.
2. Volume Measurement: It utilizes the trading volume of each candle, which reflects the number of shares or contracts traded during that period. Volume is a critical factor in confirming trends and reversals in the market.
3. Ratio Visualization: The primary output of the indicator is the ratio of price range to volume. A higher ratio may indicate increased volatility relative to volume, suggesting potential trading opportunities. Conversely, a lower ratio could imply a more stable market environment.
4. Color-Coded Bars: The bars representing the ratio are color-coded based on the candle's closing price relative to its opening price. Green bars indicate bullish candles (where the close is higher than the open), while red bars indicate bearish candles (where the close is lower than the open). This visual cue helps traders quickly assess market sentiment.
5. Background Highlighting: The indicator also features a subtle background color to enhance visibility, making it easier for traders to focus on key areas of interest on the chart.
Use Cases:
• Trend Confirmation: Traders can use the volume ratio to confirm existing trends. A rising ratio alongside increasing volume may suggest a strong bullish trend, while a declining ratio could indicate weakening momentum.
• Volatility Assessment: By analyzing the price range relative to volume, traders can identify periods of high volatility. This information can be crucial for setting stop-loss orders or determining entry points.
• Market Sentiment Analysis: The color-coded bars provide immediate insight into market sentiment, allowing traders to make informed decisions based on recent price action.
Overall, the Custom Volume Ratio Indicator serves as a valuable addition to any trader's toolkit, providing essential insights into market behavior and helping to inform trading strategies.
CandelaCharts - OHLC Volatility Range Map 📝 Overview
Unlock the power of volatility analysis with the OHLC Volatility Range Map!
Volatility reveals the intensity and speed of price movements, often accompanied by manipulative wicks extending in the opposite direction of a candle’s close.
These sharp moves, common in volatile markets, are designed to mislead traders into taking positions against the prevailing trend. Such manipulation signals potential volatility spikes and offers key insights into market dynamics.
By analyzing these patterns, traders can anticipate the candle's distribution phase, where the price expands to new highs or lows during heightened volatility.
This phase provides crucial clues for spotting liquidity draws, retracement opportunities, and potential reversals, making the OHLC Volatility Range Map an indispensable tool for navigating fast-moving markets.
📦 Features
This tool offers a range of powerful features to enhance your trading analysis:
Real-time Data Feed : Stay updated with live candlestick stats, with each new candle updating OHLC data and performing ongoing historical calculations, even on sub-minute timeframes.
User-Friendly Interface : Designed for advanced traders, the intuitive interface allows easy navigation and customization of display settings, offering a personalized experience for data-driven analysis.
⚙️ Settings
Method: Sets the desired calculation algorithm.
Visualization: Controls the display modes.
Current volatility: Display the current-day volatility.
Use NY Midnight Open: Sets the day start
⚡️ Showcase
Here’s a visual showcase of the tool in action, highlighting its key features and capabilities:
Histogram
Barchart
📒 Usage
Here’s how you can use the OHLC Volatility Range Map to enhance your analysis:
Add OHLC Volatility Range Map to your Tradingview chart.
Watch at high-volatility zones that align with your analysis.
Combine this data with other models and insights to strengthen your trading strategy.
Example 1
By following these steps, you'll unlock powerful insights to refine and elevate your trading strategies.
🔹 Notes
Available calculation methods:
Mean
Median
🚨 Alerts
The indicator does not provide any alerts!
⚠️ Disclaimer
These tools are exclusively available on the TradingView platform.
Our charting tools are intended solely for informational and educational purposes and should not be regarded as financial, investment, or trading advice. They are not designed to predict market movements or offer specific recommendations. Users should be aware that past performance is not indicative of future results and should not rely on these tools for financial decisions. By using these charting tools, the purchaser agrees that the seller and creator hold no responsibility for any decisions made based on information provided by the tools. The purchaser assumes full responsibility and liability for any actions taken and their consequences, including potential financial losses or investment outcomes that may result from the use of these products.
By purchasing, the customer acknowledges and accepts that neither the seller nor the creator is liable for any undesired outcomes stemming from the development, sale, or use of these products. Additionally, the purchaser agrees to indemnify the seller from any liability. If invited through the Friends and Family Program, the purchaser understands that any provided discount code applies only to the initial purchase of Candela's subscription. The purchaser is responsible for canceling or requesting cancellation of their subscription if they choose not to continue at the full retail price. In the event the purchaser no longer wishes to use the products, they must unsubscribe from the membership service, if applicable.
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