ATR Trailing Stop by tactical trade 22 Oct 2024Description:
The ATR Dual Trailing Stop indicator is a versatile and powerful tool designed to help traders visualize dynamic support and resistance levels based on the Average True Range (ATR). This indicator plots two separate ATR-based trailing stops with customizable settings, providing a comprehensive view of potential market reversals and trend strength.
Key features:
Two ATR Trailing Stops: The first stop uses customizable ATR settings (default: 10-period ATR with a 3x multiplier), while the second stop uses an alternate configuration (default: 21-period ATR with a 7x multiplier).
Multi-Timeframe ATR Calculation: Regardless of the chart's time frame, the ATR is calculated based on a user-selected time frame (e.g., daily), allowing for consistent stop-loss levels even in lower time frames like 5-minute or 15-minute charts.
Visual Cues: The indicator clearly plots two trailing stop lines in different colors, making it easy to track the market’s volatility-based support and resistance areas.
No Buy/Sell Signals: This is purely a trailing stop indicator with no embedded buy/sell signals, giving traders the flexibility to use it with their preferred entry/exit strategies.
This indicator is especially useful in highly volatile markets where precise trailing stop levels are essential for managing risk and maximizing profit potential. The dual ATR configuration helps traders adapt to changing market conditions by providing two levels of stop placement: a shorter-term and a longer-term trailing stop.
Sentiment
Market Phases [OmegaTools]The Market Phases indicator utilizes the Detrended Price Oscillator (DPO) to assess various asset classes, bonds, or stock sectors across different market phases. It offers users the ability to monitor and compare trends in multiple markets through a normalized DPO approach, providing insights into relative overbought or oversold conditions. The indicator supports three distinct modes: "Asset Classes," "Bonds," and "Stock Sectors," allowing flexibility in market analysis based on user preference.
Key Features:
Detrended Price Oscillator (DPO) Calculation: The DPO is computed to remove longer-term trends and focus on shorter-term cyclical behavior. The indicator applies normalization using linear interpolation to smooth out the values for better comparison across different markets.
Three Analysis Modes:
Asset Classes: Compares the DPO for major asset classes, including stocks (S&P 500), bonds (US 10-Year), commodities (Gold), and the US Dollar Index (DXY).
Bonds: Analyzes the DPO across various bond categories such as investment-grade bonds (LQD), high-yield bonds (HYG), emerging market bonds (EMB), and corporate bonds.
Stock Sectors: Provides insight into key stock sectors, including Technology (XLK), Utilities (XLU), Financials (XLF), and Healthcare (XLV).
Real-Time Plotting:
The indicator plots the DPO values of the selected assets, bonds, or sectors on the chart. It provides a visual representation of the market phases, helping to identify potential market reversals or trends. Each plot is color-coded for clarity:
Blue: Asset/Sector 1
Red: Asset/Sector 2
Green: Asset/Sector 3
Orange: Asset/Sector 4
Table Display:
A dynamic table is displayed on the chart, showing the DPO values for the selected mode's assets or sectors. This allows quick comparison and evaluation of market trends.
Inputs:
DPO Length: Defines the lookback period for DPO calculation, adjustable between 10 and 500.
Normalization Length: Sets the length for normalizing the DPO values, with options ranging from 100 to 2000.
Mode: Choose between "Asset Classes," "Bonds," or "Stock Sectors" for tailored market analysis.
This tool is perfect for traders seeking to identify cyclical market phases, compare different asset classes, or monitor sector rotation dynamics. Use it to align your trading strategies with broader market trends and uncover potential trading opportunities across multiple markets.
ICT Professional Accumulation DistributionICT Professional Accumulation Distribution (ICT AD) provides a x-ray view into market accumulation and distribution. You can literally see the institutions at work.
The indicator consists of two cumulative lines derived from:
Cumulative change from open to close
Cumulative change from previous close to new open
By overlaying these two cumulative lines, you can detect real meaningful divergence that is narrative based not mathematically derived. You're seeing the real works of algorithms in play working in this area.
These divergences are only useful at extremes (topping or bottoming formations), not while trending. It will probably confirm your suspicion about making a important high or low.
This works on all timeframes but is most impactful on the daily.
How to use:
Method 1:
Enable the option for "Show Open vs Close."
Calculate the shift by subtracting the "Open vs Close" line value from the ICT Accumulation/Distribution (AD) line value.
Look for divergences between the two cumulative lines.
Method 2:
Switch the chart's display mode to "Line View" (representing the Open vs Close).
look for divergences between the line chart and the ICT AD line.
Chande Momentum Oscillator StrategyThe Chande Momentum Oscillator (CMO) Trading Strategy is based on the momentum oscillator developed by Tushar Chande in 1994. The CMO measures the momentum of a security by calculating the difference between the sum of recent gains and losses over a defined period. The indicator offers a means to identify overbought and oversold conditions, making it suitable for developing mean-reversion trading strategies (Chande, 1997).
Strategy Overview:
Calculation of the Chande Momentum Oscillator (CMO):
The CMO formula considers both positive and negative price changes over a defined period (commonly set to 9 days) and computes the net momentum as a percentage.
The formula is as follows:
CMO=100×(Sum of Gains−Sum of Losses)(Sum of Gains+Sum of Losses)
CMO=100×(Sum of Gains+Sum of Losses)(Sum of Gains−Sum of Losses)
This approach distinguishes the CMO from other oscillators like the RSI by using both price gains and losses in the numerator, providing a more symmetrical measurement of momentum (Chande, 1997).
Entry Condition:
The strategy opens a long position when the CMO value falls below -50, signaling an oversold condition where the price may revert to the mean. Research in mean-reversion, such as by Poterba and Summers (1988), supports this approach, highlighting that prices often revert after sharp movements due to overreaction in the markets.
Exit Conditions:
The strategy closes the long position when:
The CMO rises above 50, indicating that the price may have become overbought and may not provide further upside potential.
Alternatively, the position is closed 5 days after the buy signal is triggered, regardless of the CMO value, to ensure a timely exit even if the momentum signal does not reach the predefined level.
This exit strategy aligns with the concept of time-based exits, reducing the risk of prolonged exposure to adverse price movements (Fama, 1970).
Scientific Basis and Rationale:
Momentum and Mean-Reversion:
The strategy leverages the well-known phenomenon of mean-reversion in financial markets. According to research by Jegadeesh and Titman (1993), prices tend to revert to their mean over short periods following strong movements, creating opportunities for traders to profit from temporary deviations.
The CMO captures this mean-reversion behavior by monitoring extreme price conditions. When the CMO reaches oversold levels (below -50), it signals potential buying opportunities, whereas crossing overbought levels (above 50) indicates conditions for selling.
Market Efficiency and Overreaction:
The strategy takes advantage of behavioral inefficiencies and overreactions, which are often the drivers behind sharp price movements (Shiller, 2003). By identifying these extreme conditions with the CMO, the strategy aims to capitalize on the market’s tendency to correct itself when price deviations become too large.
Optimization and Parameter Selection:
The 9-day period used for the CMO calculation is a widely accepted timeframe that balances responsiveness and noise reduction, making it suitable for capturing short-term price fluctuations. Studies in technical analysis suggest that oscillators optimized over such periods are effective in detecting reversals (Murphy, 1999).
Performance and Backtesting:
The strategy's effectiveness is confirmed through backtesting, which shows that using the CMO as a mean-reversion tool yields profitable opportunities. The use of time-based exits alongside momentum-based signals enhances the reliability of the strategy by ensuring that trades are closed even when the momentum signal alone does not materialize.
Conclusion:
The Chande Momentum Oscillator Trading Strategy combines the principles of momentum measurement and mean-reversion to identify and capitalize on short-term price fluctuations. By using a widely tested oscillator like the CMO and integrating a systematic exit approach, the strategy effectively addresses both entry and exit conditions, providing a robust method for trading in diverse market environments.
References:
Chande, T. S. (1997). The New Technical Trader: Boost Your Profit by Plugging into the Latest Indicators. John Wiley & Sons.
Fama, E. F. (1970). Efficient Capital Markets: A Review of Theory and Empirical Work. The Journal of Finance, 25(2), 383-417.
Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. The Journal of Finance, 48(1), 65-91.
Murphy, J. J. (1999). Technical Analysis of the Financial Markets: A Comprehensive Guide to Trading Methods and Applications. New York Institute of Finance.
Poterba, J. M., & Summers, L. H. (1988). Mean Reversion in Stock Prices: Evidence and Implications. Journal of Financial Economics, 22(1), 27-59.
Shiller, R. J. (2003). From Efficient Markets Theory to Behavioral Finance. Journal of Economic Perspectives, 17(1), 83-104.
Parent Session Sweeps + Alert Killzone Ranges with Parent Session Sweep
Key Features:
1. Multiple Session Support: The script tracks three major trading sessions - Asia, London, and New York. Users can customize the timing of these sessions.
2. Killzone Visualization: The strategy visually represents each session's range, either as filled boxes or lines, allowing traders to easily identify key price levels.
3. Parent Session Logic: The core of the strategy revolves around identifying a "parent" session - a session that encompasses the range of the following session. This parent session becomes the basis for potential trade setups.
4. Sweep and Reclaim Setups: The strategy looks for price movements that sweep (break above or below) the parent session's high or low, followed by a reclaim of that level. This price action often indicates a potential reversal.
5. Risk-Reward Filtering: Each potential setup is evaluated based on a user-defined minimum risk-reward ratio, ensuring that only high-quality trade opportunities are considered.
6. Candle Close Filter: An optional filter that checks the characteristics of the candle that reclaims the parent session level, adding an extra layer of confirmation to the setup.
7. Performance Tracking: The strategy keeps track of bullish and bearish setup success rates, providing valuable feedback on its performance over time.
8. Visual Aids: The script draws lines to mark the parent session's high and low, making it easy for traders to identify key levels.
How It Works:
1. The script continuously monitors price action across the defined sessions.
2. When a session fully contains the range of the next session, it's identified as a potential parent session.
3. The strategy then waits for price to sweep either the high or low of this parent session.
4. If a sweep occurs, it looks for a reclaim of the swept level within the parameters set by the user.
5. If a valid setup is identified, the script generates an alert and places a trade (if backtesting or running live).
6. The strategy continues to monitor the trade for either reaching the target (opposite level of the parent session) or hitting the stop loss.
Considerations for Signals:
- Sweep: A break of the parent session's high or low.
- Reclaim: A close back inside the parent session range after a sweep.
- Candle Characteristics: Optional filter for the reclaim candle (e.g., bullish candle for long setups).
- Risk-Reward: Each setup must meet or exceed the user-defined minimum risk-reward ratio.
- Session Timing: The strategy is sensitive to the defined session times, which should be set according to the trader's preferred time zone.
This strategy aims to capitalize on institutional order flow and liquidity patterns in the forex market, providing traders with a systematic approach to identifying potential reversal points with favorable risk-reward profiles.
Rolling VWAPGuide for Traders
What is the Rolling VWAP?
The Volume Weighted Average Price (VWAP) is a key indicator used by traders to assess the average price of an asset, weighted by volume over a specified period. Unlike a simple moving average, the VWAP accounts for trading volume, making it a more accurate reflection of price action and market sentiment.
The Rolling VWAP in this script dynamically updates based on a user-defined period, allowing traders to view the average price over a chosen number of bars. This is particularly useful for identifying trends and potential entry or exit points in the market.
Key Benefits of Using Rolling VWAP
Better Market Insight: VWAP provides insight into where most trading is occurring, helping you gauge the strength of a price move.
Support and Resistance Levels: It often acts as dynamic support or resistance, signaling areas where price might reverse.
Trend Confirmation: A rising VWAP suggests a bullish trend, while a falling VWAP indicates a bearish trend.
Informed Entry/Exit Decisions: Use the VWAP to find entry points below it in an uptrend or exit points above it in a downtrend.
How to Use this Script:
Custom Period Input:
You can modify the "VWAP Period" to adjust the number of bars considered in the rolling calculation.
The default period is 14 bars, but you can set it based on your strategy (e.g., shorter for intraday trading, longer for swing trading).
Chart Interpretation
Bullish Signals: When the price is above the VWAP line, it suggests upward momentum, and you may consider buying opportunities.
Bearish Signals: When the price is below the VWAP, it indicates downward momentum, and you may consider selling or shorting opportunities.
Reversion to VWAP: Prices often revert to the VWAP after extended moves away from it, offering potential trade setups.
Combine with Other Indicators:
Momentum Indicators: Use with RSI, MACD, or moving averages for confirmation.
Volume Analysis: VWAP works well when combined with volume indicators to assess if a breakout is supported by high trading volume.
Customization:
Traders can customize the script's period and plot color to fit their charting preferences.
Practical Tips:
Intraday Traders: Use shorter periods (e.g., 5 or 10) to capture VWAP trends in fast-moving markets.
Swing Traders: Use longer periods (e.g., 50 or 100) to assess longer-term price and volume trends.
By integrating this Rolling VWAP into your strategy, you can better understand where the majority of trading volume has occurred, allowing you to make more informed decisions in your trading process.
ATR Bands with ATR Cross + InfoTableOverview
This Pine Script™ indicator is designed to enhance traders' ability to analyze market volatility, trend direction, and position sizing directly on their TradingView charts. By plotting Average True Range (ATR) bands anchored at the OHLC4 price, displaying crossover labels, and providing a comprehensive information table, this tool offers a multifaceted approach to technical analysis.
Key Features:
ATR Bands Anchored at OHLC4: Visual representation of short-term and long-term volatility bands centered around the average price.
OHLC4 Dotted Line: A dotted line representing the average of Open, High, Low, and Close prices.
ATR Cross Labels: Visual cues indicating when short-term volatility exceeds long-term volatility and vice versa.
Information Table: Displays real-time data on market volatility, calculated position size based on risk parameters, and trend direction relative to the 20-period Smoothed Moving Average (SMMA).
Purpose
The primary purpose of this indicator is to:
Assess Market Volatility: By comparing short-term and long-term ATR values, traders can gauge the current volatility environment.
Determine Optimal Position Sizing: A calculated position size based on user-defined risk parameters helps in effective risk management.
Identify Trend Direction: Comparing the current price to the 20-period SMMA assists in determining the prevailing market trend.
Enhance Decision-Making: Visual cues and real-time data enable traders to make informed trading decisions with greater confidence.
How It Works
1. ATR Bands Anchored at OHLC4
Average True Range (ATR) Calculations
Short-Term ATR (SA): Calculated over a 9-period using ta.atr(9).
Long-Term ATR (LA): Calculated over a 21-period using ta.atr(21).
Plotting the Bands
OHLC4 Dotted Line: Plotted using small circles to simulate a dotted line due to Pine Script limitations.
ATR(9) Bands: Plotted in blue with semi-transparent shading.
ATR(21) Bands: Plotted in orange with semi-transparent shading.
Overlap: Bands can overlap, providing visual insights into changes in volatility.
2. ATR Cross Labels
Crossover Detection:
SA > LA: Indicates increasing short-term volatility.
Detected using ta.crossover(SA, LA).
A green upward label "SA>LA" is plotted below the bar.
SA < LA: Indicates decreasing short-term volatility.
Detected using ta.crossunder(SA, LA).
A red downward label "SA LA, then the market is considered volatile.
Display: Shows "Yes" or "No" based on the comparison.
b. Position Size Calculation
Risk Total Amount: User-defined input representing the total capital at risk.
Risk per 1 Stock: User-defined input representing the risk associated with one unit of the asset.
Purpose: Helps traders determine the appropriate position size based on their risk tolerance and current market volatility.
c. Is Price > 20 SMMA?
SMMA Calculation:
Calculated using a 20-period Smoothed Moving Average with ta.rma(close, 20).
Logic: If the current close price is above the SMMA, the trend is considered upward.
Display: Shows "Yes" or "No" based on the comparison.
How to Use
Step 1: Add the Indicator to Your Chart
Copy the Script: Copy the entire Pine Script code into the TradingView Pine Editor.
Save and Apply: Save the script and click "Add to Chart."
Step 2: Configure Inputs
Risk Parameters: Adjust the "Risk Total Amount" and "Risk per 1 Stock" in the indicator settings to match your personal risk management strategy.
Step 3: Interpret the Visuals
ATR Bands
Width of Bands: Wider bands indicate higher volatility; narrower bands indicate lower volatility.
Band Overlap: Pay attention to areas where the blue and orange bands diverge or converge.
OHLC4 Dotted Line
Serves as a central reference point for the ATR bands.
Helps visualize the average price around which volatility is measured.
ATR Cross Labels
"SA>LA" Label:
Indicates short-term volatility is increasing relative to long-term volatility.
May signal potential breakout or trend acceleration.
"SA 20 SMMA?
Use this to confirm trend direction before entering or exiting trades.
Practical Example
Imagine you are analyzing a stock and notice the following:
ATR(9) Crosses Above ATR(21):
A green "SA>LA" label appears.
The info table shows "Yes" for "Is ATR-based price volatile."
Position Size:
Based on your risk parameters, the position size is calculated.
Price Above 20 SMMA:
The info table shows "Yes" for "Is price > 20 SMMA."
Interpretation:
The market is experiencing increasing short-term volatility.
The trend is upward, as the price is above the 20 SMMA.
You may consider entering a long position, using the calculated position size to manage risk.
Customization
Colors and Transparency:
Adjust the colors of the bands and labels to suit your preferences.
Risk Parameters:
Modify the default values for risk amounts in the inputs.
Moving Average Period:
Change the SMMA period if desired.
Limitations and Considerations
Lagging Indicators: ATR and SMMA are lagging indicators and may not predict future price movements.
Market Conditions: The effectiveness of this indicator may vary across different assets and market conditions.
Risk of Overfitting: Relying solely on this indicator without considering other factors may lead to suboptimal trading decisions.
Conclusion
This indicator combines essential elements of technical analysis to provide a comprehensive tool for traders. By visualizing ATR bands anchored at the OHLC4, indicating volatility crossovers, and providing real-time data on position sizing and trend direction, it aids in making informed trading decisions.
Whether you're a novice trader looking to understand market volatility or an experienced trader seeking to refine your strategy, this indicator offers valuable insights directly on your TradingView charts.
Code Summary
The script is written in Pine Script™ version 5 and includes:
Calculations for OHLC4, ATRs, Bands, SMMA:
Uses built-in functions like ta.atr() and ta.rma() for calculations.
Plotting Functions:
plotshape() for the OHLC4 dotted line.
plot() and fill() for the ATR bands.
Crossover Detection:
ta.crossover() and ta.crossunder() for detecting ATR crosses.
Labeling Crossovers:
label.new() to place informative labels on the chart.
Information Table Creation:
table.new() to create the table.
table.cell() to populate it with data.
Acknowledgments
ATR and SMMA Concepts: Built upon standard technical analysis concepts widely used in trading.
Pine Script™: Leveraged the capabilities of Pine Script™ version 5 for advanced charting and analysis.
Note: Always test any indicator thoroughly and consider combining it with other forms of analysis before making trading decisions. Trading involves risk, and past performance is not indicative of future results.
Happy Trading!
Enhanced Economic Composite with Dynamic WeightEnhanced Economic Composite with Dynamic Weight
Overview of the Indicator :
The "Enhanced Economic Composite with Dynamic Weight" is a comprehensive tool that combines multiple economic indicators, technical signals, and dynamic weighting to provide insights into market and economic health. It adjusts based on current volatility and recession risk, offering a detailed view of market conditions.
What This Indicator Does :
Tracks Economic Health: Uses key economic and market indicators to assess overall market conditions.
Dynamic Weighting: Adjusts the importance of components like stock indices, gold, and bonds based on volatility (VIX) and yield curve inversion.
Technical Signals: Identifies market momentum shifts through key crossovers like the Golden Cross, Death Cross, Silver Cross, and Hospice Cross.
Recession Shading: Marks known recessions for historical context.
Economic Factors Considered :
TIP (Treasury Inflation-Protected Securities): Reflects inflation expectations.
Gold: A safe-haven asset, increases in weight during volatility or rising momentum.
US Dollar Index (DXY): Measures USD strength, fixed weight of 10%, smoothed with EMA.
Commodities (DBC): Indicates global demand; weight increases with momentum or volatility.
Volatility Index (VIX): Reflects market risk, inversely related to market confidence.
Stock Indices (S&P 500, DJIA, NASDAQ, Russell 2000): Represent market performance, with weights reduced during high volatility or negative yield spread.
Yield Spread (10Y - 2Y Treasuries): Predicts recessions; negative spread reduces stock weighting.
Credit Spread (HYG - TLT): Indicates market risk through corporate vs. government bond yields.
How and Why Factors are Weighted:
Stock Indices get more weight in stable markets (low VIX, positive yield spread), while safe-haven assets like gold and bonds gain weight in volatile markets or during yield curve inversions. This dynamic adjustment ensures the composite reflects current market sentiment.
Technical Signals:
Golden Cross: 50 EMA crossing above 200 SMA, signaling bullish momentum.
Death Cross: 50 EMA below 200 SMA, indicating bearish momentum.
Silver Cross: 21 EMA crossing above 50 EMA, plotted only if below the 200-day SMA, signaling potential upside in downtrend conditions.
Hospice Cross: 50 EMA crosses below 21 EMA, plotted only if 21 EMA is below 200 SMA, a leading bearish signal.
Recession Shading:
Recession periods like the Great Recession, Early 2000s Recession, and COVID-19 Recession are shaded to provide historical context.
Benefits of Using This Indicator:
Comprehensive Analysis: Combines economic fundamentals and technical analysis for a full market view.
Dynamic Risk Adjustment: Weights shift between growth and safe-haven assets based on volatility and recession risk.
Early Signals: The Silver Cross and Hospice Cross provide early warnings of potential market shifts.
Recession Forecasting: Helps predict downturns through the yield curve and recession indicators.
Who Can Benefit:
Traders: Identify market momentum shifts early through crossovers.
Long-term Investors: Use recession warnings and dynamic adjustments to protect portfolios.
Analysts: A holistic tool for analyzing both economic trends and market movements.
This indicator helps users navigate varying market conditions by dynamically adjusting based on economic factors and providing early technical signals for market momentum shifts.
US Recessions based on James Hamilton's JHDUSRGDPBRThis simple script uses James Hamilton's JHDUSRGDPBR indicator to colour areas representing recession periods in the US. Best used in conjunction with other macroeconomics indicators, like –as in the example– unemployment rates
Every $5 (3 Up, 3 Down) GOLD onlyDescription :
This indicator plots customizable horizontal lines spaced every $5 on the XAUUSD chart, with exactly 3 lines above and 3 lines below the nearest $5 level from the current price.
Key Features :
Line Spacing: The lines are plotted at $5 intervals starting from the nearest whole $5 price below the current price (e.g., $1900, $1905, etc.).
Customizable Line Color : Users can select the color of the lines via the indicator settings, making it adaptable to different chart themes and styles.
Customizable Line Style : The indicator allows you to choose from the following line styles:
Solid : Continuous line.
Dashed: Dashed line for a more discrete visual.
Dotted: Dotted line for minimalistic visibility.
Visibility Control : The indicator limits the number of lines to 3 above and 3 below the current price, keeping the chart clean and uncluttered while providing key levels of interest.
Use Cases :
Support and Resistance Identification: Easily spot key psychological levels in $5 increments, useful for identifying potential support or resistance zones in XAUUSD trading.
Price Action Monitoring : Traders can visually track how XAUUSD interacts with specific price levels spaced by $5 increments.
Customization Options :
Color Selection: Modify the line color to match your chart theme or highlight important levels.
Line Style: Select between solid, dashed, or dotted lines to customize the look of your chart.
This indicator is ideal for XAUUSD traders looking for clear, customizable visual levels on their charts to aid in decision-making, whether you're tracking price action or setting targets for entry and exit.
Expanding Volume Range with Anchored VWAPExpanding Volume Range with Anchored VWAP Indicator Summary
This Pine Script indicator is designed for intraday trading, particularly for timeframes of 60 minutes or less. It combines several technical analysis concepts to provide traders with a comprehensive view of price action, volume, and potential support/resistance levels.
## Key Features
1. **Anchored VWAP (Volume Weighted Average Price)**
- Calculates and displays an Anchored VWAP line
- Resets at the start of each new day or when a new highest volume bar is detected
2. **Expanding Volume Range (EVR)**
- Identifies and highlights high volume bars
- Creates a box around the price range of the last three high volume bars
- Generates additional support/resistance lines based on this range
3. **Custom Multiplier Calculations**
- Allows users to customize the calculation of support/resistance levels
- Includes options for separate top and bottom multipliers
- Provides an exponential adjustment for fine-tuning
4. **Volume-Based Candle Coloring**
- Colors candles differently based on their volume relative to recent history
- Highlights the first candle of each session in a distinct color
5. **VWAP-Based Line and Fill Colors**
- Changes colors of lines and fills based on price position relative to VWAP
6. **Alert Generation**
- Creates alerts when price breaks above or below the EVR high and low levels
## User Inputs
The indicator offers several customizable inputs grouped into categories:
1. **Volume Colors**
- Customize colors for various elements (lines, fills, candles) based on volume and VWAP relationship
2. **Target Levels**
- Set multipliers for calculating target levels
3. **Multiplier Calculations**
- Enable/disable custom multiplier calculations
- Set base multipliers and exponents for top and bottom levels
## Functionality Breakdown
1. The indicator tracks the highest volume bars for the current and previous day.
2. It creates an Expanding Volume Range (EVR) based on the last three high volume bars.
3. Using the EVR, it calculates and draws support and resistance levels.
4. The levels can be calculated using either simple multipliers or a more complex exponential formula, depending on user preference.
5. Candles are colored based on their volume and whether they're the first candle of a session.
6. An Anchored VWAP is calculated and displayed, resetting at the start of each day or on new highest volume bars.
7. Alerts are generated when price moves beyond the EVR high or low levels.
## Use Cases
This indicator can be particularly useful for:
- Identifying potential support and resistance levels based on high volume price action
- Spotting changes in volume patterns throughout the trading session
- Recognizing price action relative to the Anchored VWAP
- Setting up potential entry and exit points based on the expanding volume range
Traders should use this indicator in conjunction with other forms of analysis and risk management strategies for best results.
Commitment of Trader %R StrategyThis Pine Script strategy utilizes the Commitment of Traders (COT) data to inform trading decisions based on the Williams %R indicator. The script operates in TradingView and includes various functionalities that allow users to customize their trading parameters.
Here’s a breakdown of its key components:
COT Data Import:
The script imports the COT library from TradingView to access historical COT data related to different trader groups (commercial hedgers, large traders, and small traders).
User Inputs:
COT data selection mode (e.g., Auto, Root, Base currency).
Whether to include futures, options, or both.
The trader group to analyze.
The lookback period for calculating the Williams %R.
Upper and lower thresholds for triggering trades.
An option to enable or disable a Simple Moving Average (SMA) filter.
Williams %R Calculation: The script calculates the Williams %R value, which is a momentum indicator that measures overbought or oversold levels based on the highest and lowest prices over a specified period.
SMA Filter: An optional SMA filter allows users to limit trades to conditions where the price is above or below the SMA, depending on the configuration.
Trade Logic: The strategy enters long positions when the Williams %R value exceeds the upper threshold and exits when the value falls below it. Conversely, it enters short positions when the Williams %R value is below the lower threshold and exits when the value rises above it.
Visual Elements: The script visually indicates the Williams %R values and thresholds on the chart, with the option to plot the SMA if enabled.
Commitment of Traders (COT) Data
The COT report is a weekly publication by the Commodity Futures Trading Commission (CFTC) that provides a breakdown of open interest positions held by different types of traders in the U.S. futures markets. It is widely used by traders and analysts to gauge market sentiment and potential price movements.
Data Collection: The COT data is collected from futures commission merchants and is published every Friday, reflecting positions as of the previous Tuesday. The report categorizes traders into three main groups:
Commercial Traders: These are typically hedgers (like producers and processors) who use futures to mitigate risk.
Non-Commercial Traders: Often referred to as speculators, these traders do not have a commercial interest in the underlying commodity but seek to profit from price changes.
Non-reportable Positions: Small traders who do not meet the reporting threshold set by the CFTC.
Interpretation:
Market Sentiment: By analyzing the positions of different trader groups, market participants can gauge sentiment. For instance, if commercial traders are heavily short, it may suggest they expect prices to decline.
Extreme Positions: Some traders look for extreme positions among non-commercial traders as potential reversal signals. For example, if speculators are overwhelmingly long, it might indicate an overbought condition.
Statistical Insights: COT data is often used in conjunction with technical analysis to inform trading decisions. Studies have shown that analyzing COT data can provide valuable insights into future price movements (Lund, 2018; Hurst et al., 2017).
Scientific References
Lund, J. (2018). Understanding the COT Report: An Analysis of Speculative Trading Strategies.
Journal of Derivatives and Hedge Funds, 24(1), 41-52. DOI:10.1057/s41260-018-00107-3
Hurst, B., O'Neill, R., & Roulston, M. (2017). The Impact of COT Reports on Futures Market Prices: An Empirical Analysis. Journal of Futures Markets, 37(8), 763-785.
DOI:10.1002/fut.21849
Commodity Futures Trading Commission (CFTC). (2024). Commitment of Traders. Retrieved from CFTC Official Website.
Indices Tracker and VOLD-Market BreadthThis is an overlay displaying DOW, Nasdaq and S&P performance for the day in real-time along with NQ and NYSE market breadth display.
Overview of the Script:
The Dow, Nasdaq, S&P Tracker section is at the top, displaying the current index values, changes, and colors.
The VOLD-Market Breadth section is below, providing the market breadth information.
Helpful to get a market view while trading stocks or options directionally.
Custom Text BoxThis is an indicator to have text anchored in any symbol or chart, keep your ules at sight so is easy for you to follow, have your Bias too.
Dynamic Supply and Demand Zones [AlgoAlpha]Introducing the Dynamic Supply and Demand Zones by AlgoAlpha. This indicator is designed to automatically identify and visualize dynamic supply and demand zones on your chart, helping traders pinpoint potential reversal areas and assess market sentiment with enhanced clarity. It adapts to market conditions using a dynamic look-back mechanism, making it more responsive to recent price movements. 📈💡
Key Features
📊 Dynamic Look-Back : Automatically adjusts the look-back period based on the most recent pivot point, ensuring the most relevant data is analyzed.
🎯 Pivot Point Detection : Utilizes a user-defined period to detect significant pivot highs and lows, marking potential reversal points with precision.
🛠 Customizable Parameters : Offers extensive customization options including look-back period, pivot detection sensitivity, resolution, and zone tolerance.
🗺 Visual Display : Shows supply and demand zones as boxes on the chart, with optional profiles and background highlighting to differentiate between bullish and bearish zones.
🖍 Color-Coded Zones : Zones are color-coded for easy identification: green for bullish, red for bearish, and gray for neutral levels.
🔔 Alert Conditions : Triggers alerts when new pivot points are detected, ensuring you never miss a key market movement.
How to Use
🚀 Adding the Indicator : Press the star icon and add the indicator to favorites. Add it to your chart and adjust settings to fit your trading strategy.
🔍 Zone Analysis : Observe the color-coded zones on the chart. Bullish zones indicate potential support areas, while bearish zones suggest resistance. Monitor price interactions with these zones for potential entry and exit signals.
🔔 Alerts : Activate alert conditions for new pivot detections to stay ahead of market reversals.
How It Works
The indicator starts by detecting pivot highs and lows over a specified period. These pivots serve as reference points for determining the analysis range. If the Dynamic Look-Back feature is enabled, the look-back range dynamically adjusts from the most recent pivot to the current bar. Otherwise, a fixed look-back period is used. The price range is divided into multiple bins based on a specified resolution, and each bin’s volume is calculated by accumulating the volume of candles that fall within its price range. A zone is defined as significant if its volume is less than the adjacent bins, and the difference meets the Zone Tolerance criteria, indicating a potential area of support or resistance. These zones are then plotted on the chart as boxes. Bullish zones are shown in green, and bearish zones in red, helping traders visually identify key levels where supply and demand imbalances may cause price reversals.
Distance From moving averageDistance From Moving Average is designed to help traders visualize the deviation of the current price from a specified moving average. Users can select from four different types of moving averages: Simple Moving Average (SMA), Exponential Moving Average (EMA), Weighted Moving Average (WMA), and Hull Moving Average (HMA).
Key Features:
User-Friendly Input Options:
Choose the type of moving average from a dropdown menu.
Set the length of the moving average, with a default value of 200.
Custom Moving Average Calculations:
The script computes the selected moving average using the appropriate mathematical formula, allowing for versatile analysis based on individual trading strategies.
Distance Calculation:
The indicator calculates the distance between the current price and the chosen moving average, providing insight into market momentum. A positive value indicates that the price is above the moving average, while a negative value shows it is below.
Visual Representation:
The distance is plotted on the chart, with color coding:
Lime: Indicates that the price is above the moving average (bullish sentiment).
Red: Indicates that the price is below the moving average (bearish sentiment).
Customization:
Users can further customize the appearance of the plotted line, enhancing clarity and visibility on the chart.
This indicator is particularly useful for traders looking to gauge market conditions and make informed decisions based on the relationship between current prices and key moving averages.
LiquidityFlow Dominance+Alerts (btc.d, T3, Stables)LiquidityFlow Dominance+Alerts: Overview & Usage Guide
Overview
The LiquidityFlow Dominance+Alerts indicator provides a dynamic view of liquidity flow across Bitcoin, Altcoins, and Stablecoins, helping track liquidity shifts and identify market sentiment. By integrating moving averages, custom alerts, and thresholds for extreme outliers, this indicator helps to anticipate bullish and bearish shifts in liquidity and alert market tops and bottoms.
Key features include:
1. Liquidity Flow Monitoring : Track liquidity flow across Bitcoin (BTC), Altcoins (TOTAL3), and Stablecoins (USDT, USDC, DAI).
2. Custom Alerts : Set alerts for key liquidity shifts and extreme conditions in Stablecoin dominance, both with static and moving average (MA)-based calculations.
3. Moving Averages : Use Simple, Exponential, or Weighted Moving Averages to smooth out market data for more reliable signals.
4. Outlier Detection : Identify potential tops and bottoms using thresholds for Stablecoin dominance, with alerts for extreme movements.
Functionality
Data Inputs and Key Metrics
- Symbols Monitored:
- Bitcoin Dominance (BTC.D)
- Altcoin Market Cap (TOTAL3)
- Stablecoins (USDT.D, USDC.D, DAI.D)
- Liquidity Flow Conditions:
- Track percentage changes in dominance across sectors to detect liquidity flow into Bitcoin, Altcoins, or Stablecoins.
- Custom Metrics:
- Liquidity Flow Index: BTC Dominance minus Stablecoin Dominance.
- Liquidity Flow Ratio: BTC Dominance divided by the combined dominance of Stablecoins and Altcoins.
Moving Average Integration
- Select from SMA, EMA, or WMA to apply moving averages to the dominance metrics. Moving averages help smooth out short-term volatility and provide more consistent signals.
- Moving averages are applied to each sector (BTC, Altcoins, and Stablecoins) and compared to their previous period values to determine shifts in liquidity.
Alerts and Thresholds
- % Change Lookback Period: Adjust the lookback period to align with the timeframe of your chart. Shorter timeframes may require a lower lookback period, while higher timeframes may benefit from longer periods.
- Stables Bull/Bear % for Alerts: Set a threshold for when Stablecoin dominance becomes a bullish or bearish signal relative to BTC and Altcoins. A higher threshold may be used in volatile markets to filter out noise.
- Extreme Outliers Detection: Use the **Stables Up/Down Extreme Threshold** to identify potential market tops or bottoms when Stablecoin dominance deviates significantly from historical trends. The **Extreme Lookback Period** controls the time window for detecting these anomalies.
How to Use the Indicator
Adjusting the % Change Lookback Period
- The `% Change Lookback Period` should be adjusted based on your chart’s timeframe. For example, a shorter period (e.g., 7) works well for intraday charts, while longer periods (e.g., 14) might be more suitable for daily or weekly charts.
Setting Thresholds for Alerts
- Stables Bull/Bear % for Alerts: Adjust this setting to define when Stablecoin dominance triggers bullish or bearish alerts. A value like 1% could be a good starting point for most market conditions but can be fine-tuned based on volatility.
- Extreme Lookback Period: Define the lookback period for detecting extreme moves in Stablecoin dominance. This will help identify major tops and bottoms in the market. For shorter-term trades, consider using a shorter extreme lookback (e.g., 7-10 periods).
Alerts for Liquidity Shifts
- The indicator supports alerts for key liquidity shifts, which are useful for staying ahead of market movements. Alerts can be set to notify you when liquidity moves into:
- Bitcoin: Indicating a potential bullish trend for Bitcoin.
- Altcoins: Signaling altcoins are bullish.
- Stablecoins: Suggesting a risk-off environment or market correction.
Extreme Alerts for Stables
- Extreme Up/Down Alerts: These are triggered when Stablecoin dominance crosses extreme thresholds. For example, if Stablecoin dominance rises more than 14% over a set period, it could signal a market top, while a significant drop could indicate a market bottom.
Moving Average Calculations
- In addition to static percentage changes, moving averages can be applied to smooth out dominance values. The type and length of the moving average can be customized:
- SMA (Simple Moving Average): Best for smoothing out volatility in a linear way.
- EMA (Exponential Moving Average): More responsive to recent data, making it useful in faster markets.
- WMA (Weighted Moving Average): Emphasizes more recent data, but less reactive than the EMA.
Additional Usage Tips:
- Background Colors: The indicator visually highlights the dominant liquidity flow:
- Orange: Liquidity is shifting toward Bitcoin.
- Aqua: Liquidity is flowing into Altcoins.
- Red: Liquidity is moving into Stablecoins.
Bitcoin CME-Spot Z-Spread - Strategy [presentTrading]This time is a swing trading strategy! It measures the sentiment of the Bitcoin market through the spread of CME Bitcoin Futures and Bitfinex BTCUSD Spot prices. By applying Bollinger Bands to the spread, the strategy seeks to capture mean-reversion opportunities when prices deviate significantly from their historical norms
█ Introduction and How it is Different
The Bitcoin CME-Spot Bollinger Bands Strategy is designed to capture mean-reversion opportunities by exploiting the spread between CME Bitcoin Futures and Bitfinex BTCUSD Spot prices. The strategy uses Bollinger Bands to detect when the spread between these two correlated assets has deviated significantly from its historical norm, signaling potential overbought or oversold conditions.
What sets this strategy apart is its focus on spread trading between futures and spot markets rather than price-based indicators. By applying Bollinger Bands to the spread rather than individual prices, the strategy identifies price inefficiencies across markets, allowing traders to take advantage of the natural reversion to the mean that often occurs in these correlated assets.
BTCUSD 8hr Performance
█ Strategy, How It Works: Detailed Explanation
The strategy relies on Bollinger Bands to assess the volatility and relative deviation of the spread between CME Bitcoin Futures and Bitfinex BTCUSD Spot prices. Bollinger Bands consist of a moving average and two standard deviation bands, which help measure how much the spread deviates from its historical mean.
🔶 Spread Calculation:
The spread is calculated by subtracting the Bitfinex spot price from the CME Bitcoin futures price:
Spread = CME Price - Bitfinex Price
This spread represents the difference between the futures and spot markets, which may widen or narrow based on supply and demand dynamics in each market. By analyzing the spread, the strategy can detect when prices are too far apart (potentially overbought or oversold), indicating a trading opportunity.
🔶 Bollinger Bands Calculation:
The Bollinger Bands for the spread are calculated using a simple moving average (SMA) and the standard deviation of the spread over a defined period.
1. Moving Average (SMA):
The simple moving average of the spread (mu_S) over a specified period P is calculated as:
mu_S = (1/P) * sum(S_i from i=1 to P)
Where S_i represents the spread at time i, and P is the lookback period (default is 200 bars). The moving average provides a baseline for the normal spread behavior.
2. Standard Deviation:
The standard deviation (sigma_S) of the spread is calculated to measure the volatility of the spread:
sigma_S = sqrt((1/P) * sum((S_i - mu_S)^2 from i=1 to P))
3. Upper and Lower Bollinger Bands:
The upper and lower Bollinger Bands are derived by adding and subtracting a multiple of the standard deviation from the moving average. The number of standard deviations is determined by a user-defined parameter k (default is 2.618).
- Upper Band:
Upper Band = mu_S + (k * sigma_S)
- Lower Band:
Lower Band = mu_S - (k * sigma_S)
These bands provide a dynamic range within which the spread typically fluctuates. When the spread moves outside of these bands, it is considered overbought or oversold, potentially offering trading opportunities.
Local view
🔶 Entry Conditions:
- Long Entry: A long position is triggered when the spread crosses below the lower Bollinger Band, indicating that the spread has become oversold and is likely to revert upward.
Spread < Lower Band
- Short Entry: A short position is triggered when the spread crosses above the upper Bollinger Band, indicating that the spread has become overbought and is likely to revert downward.
Spread > Upper Band
🔶 Risk Management and Profit-Taking:
The strategy incorporates multi-step take profits to lock in gains as the trade moves in favor. The position is gradually reduced at predefined profit levels, reducing risk while allowing part of the trade to continue running if the price keeps moving favorably.
Additionally, the strategy uses a hold period exit mechanism. If the trade does not hit any of the take-profit levels within a certain number of bars, the position is closed automatically to avoid excessive exposure to market risks.
█ Trade Direction
The trade direction is based on deviations of the spread from its historical norm:
- Long Trade: The strategy enters a long position when the spread crosses below the lower Bollinger Band, signaling an oversold condition where the spread is expected to narrow.
- Short Trade: The strategy enters a short position when the spread crosses above the upper Bollinger Band, signaling an overbought condition where the spread is expected to widen.
These entries rely on the assumption of mean reversion, where extreme deviations from the average spread are likely to revert over time.
█ Usage
The Bitcoin CME-Spot Bollinger Bands Strategy is ideal for traders looking to capitalize on price inefficiencies between Bitcoin futures and spot markets. It’s especially useful in volatile markets where large deviations between futures and spot prices occur.
- Market Conditions: This strategy is most effective in correlated markets, like CME futures and spot Bitcoin. Traders can adjust the Bollinger Bands period and standard deviation multiplier to suit different volatility regimes.
- Backtesting: Before deployment, backtesting the strategy across different market conditions and timeframes is recommended to ensure robustness. Adjust the take-profit steps and hold periods to reflect the trader’s risk tolerance and market behavior.
█ Default Settings
The default settings provide a balanced approach to spread trading using Bollinger Bands but can be adjusted depending on market conditions or personal trading preferences.
🔶 Bollinger Bands Period (200 bars):
This defines the number of bars used to calculate the moving average and standard deviation for the Bollinger Bands. A longer period smooths out short-term fluctuations and focuses on larger, more significant trends. Adjusting the period affects the responsiveness of the strategy:
- Shorter periods (e.g., 100 bars): Makes the strategy more reactive to short-term market fluctuations, potentially generating more signals but increasing the risk of false positives.
- Longer periods (e.g., 300 bars): Focuses on longer-term trends, reducing the frequency of trades and focusing only on significant deviations.
🔶 Standard Deviation Multiplier (2.618):
The multiplier controls how wide the Bollinger Bands are around the moving average. By default, the bands are set at 2.618 standard deviations away from the average, ensuring that only significant deviations trigger trades.
- Higher multipliers (e.g., 3.0): Require a more extreme deviation to trigger trades, reducing trade frequency but potentially increasing the accuracy of signals.
- Lower multipliers (e.g., 2.0): Make the bands narrower, increasing the number of trade signals but potentially decreasing their reliability.
🔶 Take-Profit Levels:
The strategy has four take-profit levels to gradually lock in profits:
- Level 1 (3%): 25% of the position is closed at a 3% profit.
- Level 2 (8%): 20% of the position is closed at an 8% profit.
- Level 3 (14%): 15% of the position is closed at a 14% profit.
- Level 4 (21%): 10% of the position is closed at a 21% profit.
Adjusting these take-profit levels affects how quickly profits are realized:
- Lower take-profit levels: Capture gains more quickly, reducing risk but potentially cutting off larger profits.
- Higher take-profit levels: Let trades run longer, aiming for bigger gains but increasing the risk of price reversals before profits are locked in.
🔶 Hold Days (20 bars):
The strategy automatically closes the position after 20 bars if none of the take-profit levels are hit. This feature prevents trades from being held indefinitely, especially if market conditions are stagnant. Adjusting this:
- Shorter hold periods: Reduce the duration of exposure, minimizing risks from market changes but potentially closing trades too early.
- Longer hold periods: Allow trades to stay open longer, increasing the chance for mean reversion but also increasing exposure to unfavorable market conditions.
By understanding how these default settings affect the strategy’s performance, traders can optimize the Bitcoin CME-Spot Bollinger Bands Strategy to their preferences, adapting it to different market environments and risk tolerances.
US Sentiment Index [CryptoSea]The US Sentiment Index is an advanced analytical tool designed for traders seeking to uncover patterns, correlations, and potential leading signals across key market tickers. This indicator surpasses traditional sentiment measures, providing a data-driven approach that offers deeper insights compared to conventional indices like the Fear and Greed Index.
Key Features
Multi-Ticker Analysis: Integrates data from a diverse set of market indicators, including gold, S&P 500, U.S. Dollar Index, Volatility Index, and more, to create a comprehensive view of market sentiment.
Customisable Sensitivity Settings: Allows users to adjust the moving average period to fine-tune the sensitivity of sentiment calculations, adapting the tool to various market conditions and trading strategies.
Detailed Sentiment Scaling: Utilises a 0-100 scale to quantify sentiment strength, with colour gradients that visually represent bearish, neutral, and bullish conditions, aiding in quick decision-making.
Below is an example where the sentiment index can give leading signals. We see a first sign of wekaness in the index as it drops below its moving average. Shortly after we see it dip below our median 50 level, another sign of weakeness. We see the SPX price action to take a hit following the sentiment index decrease.
Tickers Used and Their Impact on Sentiment
The impact of each ticker on sentiment can be bullish or bearish, depending on their behaviour:
Gold (USGD): Typically seen as a safe-haven asset, rising gold prices often indicate increased market fear or bearish sentiment. Conversely, falling gold prices can signal reduced fear and a shift towards bullish sentiment in riskier assets.
S&P 500 (SPX): A rising S&P 500 is usually a sign of bullish sentiment, reflecting confidence in economic growth and market stability. A decline, however, suggests bearish sentiment and a potential move towards risk aversion.
U.S. Dollar Index (DXY): A strengthening U.S. Dollar can be a sign of fear as investors seek safety in the dollar, which is bearish for risk assets. A weakening dollar, on the other hand, can signal bullish sentiment as capital flows into riskier assets.
Volatility Index (VIX): Known as the "fear gauge," a rising VIX indicates increased market fear and bearish sentiment. A falling VIX suggests a calm, bullish market environment.
Junk Bonds (JNK): Rising junk bond prices often reflect bullish sentiment as investors take on more risk for higher returns. Conversely, falling junk bond prices signal increased fear and bearish sentiment.
Long-Term Treasury Bonds (TLT): Higher prices for long-term treasuries usually indicate a flight to safety, reflecting bearish sentiment. Lower prices suggest a shift towards riskier assets, indicating bullish sentiment.
Financial Sector ETF (XLF): Strength in the financial sector is typically bullish, indicating confidence in economic conditions. Weakness in this sector can reflect bearish sentiment and concerns about financial stability.
Unemployment Rate (USUR): A rising unemployment rate is a bearish signal, indicating economic weakness. A declining unemployment rate is bullish, reflecting economic strength and job growth.
U.S. Interest Rates (USINTR, USIRYY): Higher interest rates can be bearish, as they increase borrowing costs and reduce spending. Lower rates are generally bullish, promoting economic growth and risk-taking.
How it Works
Sentiment Calculation: The US Sentiment Index combines data from multiple tickers, calculating sentiment by scaling the distance from their respective moving averages. Each asset's behaviour is interpreted within the context of market fear or greed, providing a refined sentiment reading that adjusts dynamically.
Market Strength Analysis: When the index is above 50 and also above its moving average, it indicates particularly strong or bullish market conditions, driven by greed. Conversely, when the index is below 50 and under its moving average, it signals bearish or weak market conditions, associated with fear.
Correlation and Pattern Detection: The indicator analyses correlations among the included assets to detect patterns that might signal potential market movements, giving traders a leading edge over simpler sentiment measures.
Adaptive Background Colouring: Utilises a colour gradient that dynamically adjusts based on sentiment values, highlighting extreme fear, neutral, and extreme greed levels directly on the chart.
Flexible Display Options: Offers settings to toggle the moving average plot and adjust its period, giving users the ability to tailor the indicator's sensitivity and display to their specific needs.
In this example below, we can see the Sentiment rise above the Moving Average (MA). Price action goes on to follow this, although there is an instance where it dips below the MA, it quickly rises back above again as a sign of strength.
Another way you can use this index is by simply using the MA, if its trending up, we know the macro sentiment is bullish.
Application
Data-Driven Insights: Offers traders a detailed, data-driven approach to sentiment analysis, incorporating a broad spectrum of market indicators to deliver actionable insights.
Pattern Recognition: Helps identify patterns and correlations that may lead to market reversals or continuations, providing a nuanced view that goes beyond simple sentiment gauges.
Enhanced Decision-Making: Equips traders with a robust tool to validate trading strategies and make informed decisions based on comprehensive sentiment analysis.
The US Sentiment Index by is an essential addition to the toolkit of any trader looking to navigate market complexities with precision and confidence. Its advanced features and data-driven approach offer unparalleled insights into market sentiment, setting it apart from conventional sentiment indicators.
Momentum Cloud.V33🌟 Introducing MomentumCloud.V33 🌟
MomentumCloud.V33 is a cutting-edge indicator designed to help traders capture market momentum with clarity and precision. This versatile tool combines moving averages, directional movement indexes (DMI), and volume analysis to provide real-time insights into trend direction and strength. Whether you’re a scalper, day trader, or swing trader, MomentumCloud.V33 adapts to your trading style and timeframe, making it an essential addition to your trading toolkit. 📈💡
🔧 Customizable Parameters:
• Moving Averages: Adjust the periods of the fast (MA1) and slow (MA2) moving averages to fine-tune your trend analysis.
• DMI & ADX: Customize the DMI length and ADX smoothing to focus on strong, actionable trends.
• Volume Multiplier: Modify the cloud thickness based on trading volume, emphasizing trends with significant market participation.
📊 Trend Detection:
• Color-Coded Clouds:
• Green Cloud: Indicates a strong uptrend, suggesting buying opportunities.
• Red Cloud: Indicates a strong downtrend, signaling potential short trades.
• Gray Cloud: Reflects a range-bound market, helping you avoid low-momentum periods.
• Dynamic Volume Integration: The cloud thickness adjusts dynamically with trading volume, highlighting strong trends supported by high market activity.
📈 Strength & Momentum Analysis:
• Strength Filtering: The ADX component ensures that only strong trends are highlighted, filtering out market noise and reducing false signals.
• Visual Momentum Gauge: The cloud color and thickness provide a quick visual representation of market momentum, enabling faster decision-making.
🔔 Alerts:
• Custom Alerts: Set up alerts for when the trend shifts or reaches critical levels, keeping you informed without needing to constantly monitor the chart.
🎨 Visual Enhancements:
• Gradient Cloud & Shadows: The indicator features a gradient-filled cloud with shadowed moving averages, enhancing both aesthetics and clarity on your charts.
• Adaptive Visual Cues: MomentumCloud.V33’s color transitions and dynamic thickness provide an intuitive feel for the market’s rhythm.
🚀 Quick Guide to Using MomentumCloud.V33
1. Add the Indicator: Start by adding MomentumCloud.V33 to your chart. Customize the settings such as MA periods, DMI length, and volume multiplier to match your trading style.
2. Analyze the Market: Observe the color-coded cloud and its thickness to gauge market momentum and trend direction. The thicker the cloud, the stronger the trend.
3. Set Alerts: Activate alerts for trend changes or key levels to capture trading opportunities without needing to watch the screen continuously.
⚙️ How It Works:
MomentumCloud.V33 calculates market momentum by combining moving averages, DMI, and volume. The cloud color changes based on the trend direction, while its thickness reflects the strength of the trend as influenced by trading volume. This integrated approach ensures you can quickly identify robust market movements, making it easier to enter and exit trades at optimal points.
Settings Overview:
• Moving Averages: Define the lengths for the fast and slow moving averages.
• DMI & ADX: Adjust the DMI length and ADX smoothing to focus on significant trends.
• Volume Multiplier: Customize the multiplier to control cloud thickness, highlighting volume-driven trends.
📚 How to Use MomentumCloud.V33:
• Trend Identification: The direction and color of the cloud indicate the prevailing trend, while the cloud’s thickness suggests the trend’s strength.
• Trade Execution: Use the green cloud to look for long entries and the red cloud for short positions. The gray cloud advises caution, as it represents a range-bound market.
• Alerts: Leverage the custom alerts to stay on top of market movements and avoid missing critical trading opportunities.
Unleash the power of trend and momentum analysis with MomentumCloud.V33! Happy trading! 📈🚀✨
Multi-Step FlexiSuperTrend - Indicator [presentTrading]This version of the indicator is built upon the foundation of a strategy version published earlier. However, this indicator version focuses on providing visual insights and alerts for traders, rather than executing trades. This one is mostly for @thorcmt.
█ Introduction and How it is Different
The **Multi-Step FlexiSuperTrend Indicator** is a versatile tool designed to provide traders with a highly customizable and flexible approach to trend analysis. Unlike traditional supertrend indicators, which focus on a single factor or threshold, the **FlexiSuperTrend** allows users to define multiple levels of take-profit targets and incorporate different trend normalization methods.
It comes with several advanced customization features, including multi-step take profits, deviation plotting, and trend normalization, making it suitable for both novice and expert traders.
BTCUSD 6hr Performance
█ Strategy, How It Works: Detailed Explanation
The **Multi-Step FlexiSuperTrend** works by calculating a supertrend based on multiple factors and incorporating oscillations from trend deviations. Here’s a breakdown of how it functions:
🔶 SuperTrend Calculation
At the heart of the indicator is the SuperTrend formula, which dynamically adjusts based on price movements.
🔶 Normalization of Deviations
To enhance accuracy, the **FlexiSuperTrend** calculates multiple deviations from the trend and normalizes them.
🔶 Multi-Step Take Profit Levels
The indicator allows setting up to three take profit levels, which are displayed via price level alerts. lows traders to exit part of their position at various profit intervals.
For more detail, please check the strategy version - Multi-Step-FlexiSuperTrend-Strategy:
and 'FlexiSuperTrend-Strategy'
█ Trade Direction
The **Multi-Step FlexiSuperTrend Indicator** supports both long and short trade directions.
This flexibility allows traders to adapt to trending, volatile, or sideways markets.
█ Usage
To use the **FlexiSuperTrend Indicator**, traders can set up their preferences for the following key features:
- **Trading Direction**: Choose whether to focus on long, short, or both signals.
- **Indicator Source**: The price source to calculate the trend (e.g., close, hl2).
- **Indicator Length**: The number of periods to calculate the ATR and trend (the larger the value, the smoother the trend).
- **Starting and Increment Factor**: These adjust how reactive the trend is to price movements. The starting factor dictates how far the initial trend band is from the price, and the increment factor adjusts subsequent trend deviations.
The indicator then displays buy and sell signals on the chart, along with alerts for each take-profit level.
Local picture
█ Default Settings
The default settings of the **Multi-Step FlexiSuperTrend** are carefully designed to provide an optimal balance between sensitivity and accuracy. Let’s examine these default parameters and their effect on performance:
🔶 Indicator Length (Default: 10)
The **Indicator Length** determines the lookback period for the ATR calculation. A smaller value makes the indicator more reactive to price changes, but may generate more false signals. A longer length smooths the trend and reduces noise but may delay signals.
Effect on performance: Shorter lengths perform better in volatile markets, while longer lengths excel in trending markets.
🔶 Starting Factor (Default: 0.618)
This factor adjusts the starting distance of the SuperTrend from the current price. The smaller the starting factor, the closer the trend is to the price, making it more sensitive. Conversely, a larger factor allows more distance, reducing sensitivity but filtering out false signals.
Effect on performance: A smaller factor provides quicker signals but can lead to frequent false positives. A larger factor generates fewer but more reliable signals.
🔶 Increment Factor (Default: 0.382)
The **Increment Factor** controls how the trend bands adjust as the price moves. It increases the distance of the bands from the price with each iteration.
Effect on performance: A higher increment factor can result in wider stop-loss or trend reversal bands, allowing for longer trends to develop without frequent exits. A lower factor keeps the bands closer to the price and is more suited for shorter-term trades.
🔶 Take Profit Levels (Default: 2%, 8%, 18%)
The default take-profit levels are set at 2%, 8%, and 18%. These values represent the thresholds at which the trader can partially exit their positions. These multi-step levels are highly customizable depending on the trader’s risk tolerance and strategy.
Effect on performance: Lower take-profit levels (e.g., 2%) capture small, quick profits in volatile markets, while higher levels (8%-18%) allow for a more gradual exit in strong trends.
🔶 Normalization Method (Default: None)
The default normalization method is **None**, meaning the deviations are not normalized. However, enabling normalization (e.g., **Max-Min**) can improve the clarity of the indicator’s signals in volatile or choppy markets by smoothing out the noise.
Effect on performance: Using a normalization method can reduce the effect of extreme deviations, making signals more stable and less prone to false positives.
MCDX+RSI+SMA[THANHCONG]### Detailed Analysis of the MCDX+RSI+SMA Indicator
The MCDX+RSI+SMA indicator is designed to help investors conduct a deeper analysis of market trends by combining multiple technical factors into a single chart. This integration of popular indicators such as RSI, SMA, and Stochastic RSI provides investors with a comprehensive view of market movements, particularly in distinguishing between "Banker" and "Hot Money"—representing large and small capital flows.
#### Key Components of the Indicator:
1. **RSI for Banker and Hot Money:**
- **RSI (Relative Strength Index)** is a momentum oscillator that measures the speed and change of price movements, indicating overbought or oversold conditions. In this indicator, there are two distinct RSI lines configured for Banker (large capital) and Hot Money (small capital).
- Investors can adjust parameters like the RSI calculation period, baseline levels, and sensitivity for each type of capital flow, providing flexibility to adapt to varying market conditions.
2. **Moving Average (MA) of RSI:**
- The indicator employs two common types of Moving Averages: **SMA (Simple Moving Average)** and **EMA (Exponential Moving Average)**. These help smooth the RSI signals for Banker, offering a clearer view of the long-term trend of large capital in the market.
- Investors can select the type and period of the MA, allowing them to optimize the indicator for their trading style.
3. **Stochastic RSI:**
- The **Stochastic RSI** is incorporated to monitor overbought and oversold conditions over a specified timeframe. Parameters related to %K and %D of the Stochastic can also be adjusted to refine the accuracy of market signal analysis.
- A notable feature is the normalization of %K and %D on a 0-20 scale, making these lines compatible with other RSI charts, thus providing consistency in evaluating market strength.
4. **Overbought and Oversold Levels:**
- The indicator includes reference lines for overbought and oversold levels, aiding investors in identifying potential reversal zones in the market. This helps to avoid buying at excessively high prices or selling at excessively low prices.
#### Benefits for Investors:
- **Comprehensive View:** The indicator combines insights from both large (Banker) and small (Hot Money) capital flows, enabling investors to analyze not just trends but also the participation of each type of capital in the market.
- **Enhanced Technical Analysis:** By integrating multiple technical indicators within a single chart, investors can track important factors such as market momentum, overbought/oversold conditions, and capital flow shifts without needing to switch between various charts.
- **Flexibility and Customization:** The indicator allows adjustment of key parameters like the RSI period, sensitivity, type of MA, and Stochastic RSI settings, enabling investors to tailor the indicator to their trading strategy and timeframe.
- **Higher Reliability:** The combination of indicators like RSI, Stochastic RSI, and MA helps investors confirm trading signals more confidently. For instance, when both RSI and Stochastic RSI indicate overbought conditions, the likelihood of a reversal may be higher, reducing risk for investors.
#### Unique Features of the Indicator:
The MCDX+RSI+SMA indicator is a unique tool that integrates various market analysis factors into a single framework. This not only provides investors with a complete view of capital flows but also aids in optimizing decision-making based on multiple market aspects. Furthermore, its customizable parameters make it suitable for various trading strategies, from short-term to long-term.
S&R Precision Cloud by Dr. Abiram Sivprasad -4 directional biasDescription of the Script
**Script Name:** S&R Precision Cloud by Dr. Abhiram Sivprasad
**Overview:**
This script is designed to identify key support and resistance levels using the Central Pivot Range (CPR) methodology along with daily, weekly, and monthly pivots. It incorporates the Lagging Span from the Ichimoku Cloud to enhance decision-making in trading strategies for intraday, swing, and long-term positions mainly for directional bias.
---
### Key Components:
1. **Central Pivot Range (CPR):**
- **Central Pivot (CP):** Calculated as the average of the high, low, and close prices. This serves as a reference point for price action.
- **Below Central Pivot (BC) and Top Central Pivot (TC):** Derived to create a range that aids in identifying support and resistance levels.
2. **Support and Resistance Levels:**
- The script computes three support (S1, S2, S3) and resistance (R1, R2, R3) levels based on the Central Pivot.
- These levels are plotted for daily, weekly, and monthly time frames, providing traders with multiple reference points.
3. **Lagging Span:**
- The Lagging Span is plotted as the closing price shifted backward by 26 periods (as per Ichimoku settings).
- This serves as a filter for trade entries, where positions should only be taken in the direction opposite to where the price is relative to this line.
4. **User Inputs:**
- The script allows customization through checkboxes to plot daily, weekly, and monthly support and resistance levels as needed.
- Users can choose whether to display CPR and various support/resistance levels for better visual clarity.
5. **Color Coding:**
- The support and resistance lines are color-coded to distinguish between different levels (green for support, red for resistance, and blue for pivots).
---
### Trading Strategies:
- **Intraday Trading:**
- Utilize price movements around the Lagging Span and support/resistance levels for quick trades.
- **Swing Trading:**
- Identify potential reversal points at S2 and R2 levels, confirmed by divergences in price movement.
- **Long-Term Trading:**
- Monitor price behavior against the Lagging Span and significant pivot levels to capture longer trends.
---
### Summary:
This script equips traders with essential tools for technical analysis by clearly defining critical price levels and incorporating the Lagging Span for directional bias. It is suitable for various trading styles, including intraday, swing, and long-term strategies, making it a versatile addition to any trader’s toolkit.
