Swing Breakout System (SBS)The Swing Breakout Sequence (SBS) is a trading strategy that focuses on identifying high-probability entry points based on a specific pattern of price swings. This indicator will identify these patterns, then draw lines and labels to show confirmation.
How To Use:
The indicator will show both Bullish and Bearish SBS patterns.
Bullish Pattern is made up of 6 points: Low (0), HH (1), LL (2 | but higher than initial Low), New HH (3), LL (5), LL again (5)
Bearish Patten is made up of 6 points: High (0), LL (1), HH (2 | but lower than initial high), New LL (3), HH (5), HH again (5)
A label with an arrow will appear at the end, showing the completion of a successful sequence
Idea behind the strategy:
The idea behind this strategy, is the accumulation and then manipulation of liquidity throughout the sequence. For example, during SBS sequence, liquidity is accumulated during step (2), then price will push away to make a new high/low (step 3), after making a minor new high/low, price will retrace breaking the key level set up in step (2). This is price manipulating taking liquidity from behind high/low from step (2). After taking liquidity price the idea is price will continue in the original direction.
Step 0 - Setting up initial direction
Step 1 - Setting up initial direction
Step 2 - Key low/high establishing liquidity
Step 3 - Failed New high/low
Step 4 - Taking liquidity from step (2)
Step 5 - Taking liquidity from step 2 and 4
Pattern Detection:
- Uses pivot high/low points to identify swing patterns
- Stores 6 consecutive swing points in arrays
- Identifies two types of patterns:
1. Bullish Pattern: A specific sequence of higher lows and higher highs
2. Bearish Pattern: A specific sequence of lower highs and lower lows
Note: Because the indicator is identifying a perfect sequence of 6 steps, set ups may not appear frequently.
Visualization:
- Draws connecting lines between swing points
- Labels each point numerically (optional)
- Shows breakout arrows (↑ for bullish, ↓ for bearish)
- Generates alerts on valid breakouts
User Input Settings:
Core Parameters
1. Pivot Lookback Period (default: 2)
- Controls how many bars to look back/forward for pivot point detection
- Higher values create fewer but more significant pivot points
2. Minimum Pattern Height % (default: 0.1)
- Minimum required height of the pattern as a percentage of price
- Filters out insignificant patterns
3. Maximum Pattern Width (bars) (default: 50)
- Maximum allowed width of the pattern in bars
- Helps exclude patterns that form over too long a period
Wyszukaj w skryptach "the strat"
WAGMI LAB Trend Reversal Indicator HMA-Kahlman (m15)WAGMI HMA-Kahlman Trend Reversal Indicator
This indicator combines the Hull Moving Average (HMA) with the Kahlman filter to provide a dynamic trend reversal signal, perfect for volatile assets like Bitcoin. The strategy works particularly well on lower timeframes, making it ideal for intraday trading and fast-moving markets.
Key Features:
Trend Detection: It uses a blend of HMA and Kahlman filters to detect trend reversals, providing more accurate and timely signals.
Volatility Adaptability: Designed with volatile assets like Bitcoin in mind, this indicator adapts to rapid price movements, offering smoother trend detection during high volatility.
Easy Visualization: Buy (B) and Sell (S) signals are clearly marked with labels, helping traders spot trend shifts quickly and accurately.
Trendlines Module: The indicator plots trendlines based on pivot points, highlighting important support and resistance levels. This helps traders understand the market structure and identify potential breakout or breakdown zones.
Customizable: Adjust the HMA and Kahlman parameters to fit different assets or trading styles, making it flexible for various market conditions.
Usage Tips:
Best Timeframes: The indicator performs exceptionally well on lower timeframes (such as 15-minute to 1-hour charts), making it ideal for scalping and short-term trading strategies.
Ideal for Volatile Assets: This strategy is perfect for highly volatile assets like Bitcoin, but can also be applied to other cryptocurrencies and traditional markets with high price fluctuations.
Signal Confirmation: Use the trend signals (green for uptrend, red for downtrend) along with the buy/sell labels to help you confirm potential entries and exits. It's also recommended to combine the signals with other technical tools like volume analysis or RSI for enhanced confirmation.
Trendline Analysis: The plotted trendlines provide additional visual context to identify key market zones, supporting your trading decisions with a clear view of ongoing trends and possible reversal areas.
Risk Management: As with any strategy, always consider proper risk management techniques, such as stop-loss and take-profit levels, to protect against unforeseen market moves.
9-20 EMA Crossover with TP and SL9-20 EMA Crossover: This script tracks the crossover of the 9-period EMA and the 20-period EMA.
When the 9 EMA crosses above the 20 EMA, a buy signal is triggered.
When the 9 EMA crosses below the 20 EMA, a sell signal is triggered.
Take Profit and Stop Loss Levels:
The take profit for a long position is set at 3% above the entry price (close * 1.03).
The stop loss for a long position is set at 1% below the entry price (close * 0.99).
The take profit for a short position is set at 3% below the entry price (close * 0.97).
The stop loss for a short position is set at 1% above the entry price (close * 1.01).
Leverage: The strategy uses 20x leverage for both long and short positions (leverage=20).
Alerts: Alerts are set up for the buy signal when the 9 EMA crosses above the 20 EMA and the sell signal when the 9 EMA crosses below the 20 EMA. These alerts can be used with a webhook to trigger trades on Binance Futures.
Strategy:
For long trades: The strategy enters a long position and sets a take profit at 3% above the entry price and a stop loss at 1% below the entry price.
For short trades: The strategy enters a short position and sets a take profit at 3% below the entry price and a stop loss at 1% above the entry price.
200 EMA Breakout & Retest Strategy200 EMA Breakout & Retest Strategy
This script is designed for traders who rely on the 200 EMA as a key indicator for trend direction and trade setups. The strategy identifies potential buy and sell opportunities based on breakouts and subsequent retests of the 200 EMA.
How It Works
EMA Breakout Detection:
The script monitors when the price crosses and closes above or below the 200 EMA.
No signal is generated immediately upon the breakout.
Retest Confirmation:
After the breakout, the price must retrace to touch the 200 EMA.
A valid signal occurs only when the price touches the EMA and the candle closes above (for buy) or below (for sell).
Trade Signal Generation:
Once the retest is confirmed:
A Buy Signal is generated if the price closes above the 200 EMA after the retest.
A Sell Signal is generated if the price closes below the 200 EMA after the retest.
The script calculates:
Stop Loss: Placed at the low of the candle for a buy signal and at the high of the candle for a sell signal.
Take Profit: Based on a customizable Risk-Reward Ratio (default is 1:2).
Visual Indicators:
The 200 EMA is plotted on the chart for reference.
Buy/Sell signals are displayed as labels on the chart.
Stop loss and take profit levels are drawn using dotted lines.
Customization Options
EMA Length: Adjustable (default is 200).
Risk-Reward Ratio: Customizable to suit different trading styles.
Who Is This For?
This strategy is ideal for traders who:
Prefer trading with the trend using EMA-based strategies.
Look for precise entry points with confirmation from retests.
Require automated calculation of risk-reward levels.
One Shot One Kill ICT [TradingFinder] Liquidity MMXM + CISD OTE🔵 Introduction
The One Shot One Kill trading setup is one of the most advanced methods in the field of Smart Money Concept (SMC) and ICT. Designed with a focus on concepts such as Liquidity Hunt, Discount Market, and Premium Market, this strategy emphasizes precise Price Action analysis and market structure shifts. It enables traders to identify key entry and exit points using a structured Trading Model.
The core process of this setup begins with a Liquidity Hunt. Initially, the price targets areas like the Previous Day High and Previous Day Low to absorb liquidity. Once the Change in State of Delivery(CISD)is broken, the market structure shifts, signaling readiness for trade entry. At this stage, Fibonacci retracement levels are drawn, and the trader enters a position as the price retraces to the 0.618 Fibonacci level.
Part of the Smart Money approach, this setup combines liquidity analysis with technical tools, creating an opportunity for traders to enter high-accuracy trades. By following this setup, traders can identify critical market moves and capitalize on reversal points effectively.
Bullish :
Bearish :
🔵 How to Use
The One Shot One Kill setup is a structured and advanced trading strategy based on Liquidity Hunt, Fibonacci retracement, and market structure shifts (CISD). With a focus on precise Price Action analysis, this setup helps traders identify key market movements and plan optimal trade entries and exits. It operates in two scenarios: Bullish and Bearish, each with distinct steps.
🟣 Bullish One Shot One Kill
In the Bullish scenario, the process starts with the price moving toward the Previous Day Low, where liquidity is absorbed. At this stage, retail sellers are trapped as they enter short trades at lower levels. Following this, the market reverses upward and breaks the CISD, signaling a shift in market structure toward bullishness.
Once this shift is identified, traders draw Fibonacci levels from the lowest point to the highest point of the move. When the price retraces to the 0.618 Fibonacci level, conditions for a buy position are met. The target for this trade is typically the Previous Day High or other significant liquidity zones where major buyers are positioned, offering a high probability of price reversal.
🟣 Bearish One Shot One Kill
In the Bearish scenario, the price initially moves toward the Previous Day High to absorb liquidity. Retail buyers are trapped as they enter long trades near the highs. After the liquidity hunt, the market reverses downward, breaking the CISD, which signals a bearish shift in market structure. Following this confirmation, Fibonacci levels are drawn from the highest point to the lowest point of the move.
When the price retraces to the 0.618 Fibonacci level, a sell position is initiated. The target for this trade is usually the Previous Day Low or other key liquidity zones where major sellers are active.
This setup provides a precise and logical framework for traders to identify market movements and enter trades at critical reversal points.
🔵 Settings
🟣 CISD Logical settings
Bar Back Check : Determining the return of candles to identify the CISD level.
CISD Level Validity : CISD level validity period based on the number of candles.
🟣 LIQUIDITY Logical settings
Swing period : You can set the swing detection period.
Max Swing Back Method : It is in two modes "All" and "Custom". If it is in "All" mode, it will check all swings, and if it is in "Custom" mode, it will check the swings to the extent you determine.
Max Swing Back : You can set the number of swings that will go back for checking.
🟣 CISD Display settings
Displaying or not displaying swings and setting the color of labels and lines.
🟣 LIQUIDITY Display settings
Displaying or not displaying swings and setting the color of labels and lines.
🔵 Conclusion
The One Shot One Kill setup is one of the most effective and well-structured trading strategies for identifying and capitalizing on key market movements. By incorporating concepts such as Liquidity Hunt, CISD, and Fibonacci retracement, this setup allows traders to enter trades with high precision at optimal points.
The strategy emphasizes detailed Price Action analysis and the identification of Smart Money behavior, helping traders to execute successful trades against the general market trend.
With a focus on identifying liquidity in the Previous Day High and Low and aligning it with Fibonacci retracement levels, this setup provides a robust framework for entering both bullish and bearish trades.
The combination of liquidity analysis and Fibonacci retracement at the 0.618 level enables traders to minimize risk and exploit major market moves effectively.
Ultimately, success with the One Shot One Kill setup requires practice, patience, and strict adherence to its rules. By mastering its concepts and focusing on high-probability setups, traders can enhance their decision-making skills and build a sustainable and professional trading approach.
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.
[blackcat] L3 Bullish Grab SignalOVERVIEW
The " L3 Bullish Grab Signal" indicator is designed to identify bullish trends and potential buying opportunities in the market. It uses a combination of moving averages and custom calculations to generate signals. The indicator is set to not overlay on the price chart, meaning it will have its own panel below the main chart, and it updates based on the specified timeframe.
FEATURES
Input Parameters:
shortEmaPeriod: Default value is 13, used for the shorter-term EMA.
longEmaPeriod: Default value is 34, used for the longer-term EMA.
signalEmaPeriod: Default value is 5, used to smooth the difference between the short and long EMAs.
lookbackPeriod: Default value is 60, used to look back over a certain number of bars for specific calculations.
Variable Calculations:
priceWeightedAverage: Calculated as (close * 2 + high + low) / 4 * 10, a custom price point.
shortEma: EMA of priceWeightedAverage over the short period.
longEma: EMA of priceWeightedAverage over the long period.
signalEma: EMA of the difference between shortEma and longEma, smoothed over the signalEmaPeriod.
oscillatorValue: Calculated as 2 * (shortEma - longEma - signalEma) * 5.5, a custom oscillator.
positiveOscillatorValue: Positive part of oscillatorValue, setting negative values to zero.
bullishSignal: True when positiveOscillatorValue increases and was previously negative.
confirmedBullishSignal: True when the bullish signal is confirmed by certain conditions involving the oscillator values and price increases.
priceIncreaseThreshold: Checks if the close price increased by more than 7% from the previous bar.
strongBullishSignal: Combines the bullish signal with the confirmed signal and the price increase threshold.
confirmedStrongBullishSignal: When all conditions for a strong bullish signal are met.
weakBullishSignal: Bullish signal that doesn't meet the strong criteria but still shows some strength.
Plotting:
Oscillator Value: Plots the raw oscillator value in white.
Positive Oscillator Value: Plots only the positive part of the oscillator value in white.
Strong Bullish Signal Stick: Plots a red candlestick when a strong bullish signal is confirmed, using the highest positive oscillator value over the lookback period.
Bullish Signal Stick: Plots a white candlestick for a bullish signal that isn't necessarily strong.
Weak Bullish Signal Stick: Plots a green candlestick for a weak bullish signal.
Positive Trend: Plots yellow candlesticks when the oscillator value is positive.
Negative Trend: Plots fuchsia candlesticks when the oscillator value is negative.
Numbers on Candles: Represents the breakout strength as a percentage change in price.
HOW TO USE
Install the Script: Add the script to your TradingView chart.
Customize Inputs:
Adjust the shortEmaPeriod, longEmaPeriod, signalEmaPeriod, and lookbackPeriod as needed.
Interpret the Charts:
Red Candles: Indicate a strong bullish trend, suggesting a potential buying opportunity.
White Candles: Indicate bullish signals that are not as strong but still suggest a buying opportunity.
Green Candles: Indicate weak bullish signals, suggesting a possible buying opportunity but with less confidence.
Yellow Candles: Indicate a positive trend, suggesting the market is in an uptrend.
Fuchsia Candles: Indicate a negative trend, suggesting the market is in a downtrend.
Numbers on Candles: Show the breakout strength as a percentage change in price.
Analyze Trends and Signals:
Use red candles to identify strong bullish signals, especially if the price has increased by more than 7% from the previous bar.
Monitor white and green candles for potential entries with lower confidence.
Avoid trading during fuchsia candles, as the market is in a downtrend.
MARKET MEANING AND TRADING USAGE
Strong Bullish Signal (Red Candles): Indicates a significant price increase and momentum, suggesting a strong buying opportunity.
Bullish Signal (White Candles): Suggests a buying opportunity but with less confidence compared to strong signals.
Weak Bullish Signal (Green Candles): Indicates a possible buying opportunity with even lower confidence.
Positive Trend (Yellow Candles): Suggests the market is in an uptrend.
Negative Trend (Fuchsia Candles): Suggests the market is in a downtrend.
Trading Strategy:
Buy: When a strong bullish signal is confirmed (red candle), especially if the price has increased by more than 7% from the previous bar.
Monitor: Watch for bullish signals (white candles) and weak bullish signals (green candles) for potential entries with lower confidence.
Avoid: During negative trends (fuchsia candles), as the market is in a downtrend.
LIMITATIONS
Simplicity: The implementation is based on a combination of moving averages and custom calculations, which might not capture all aspects of market dynamics.
Close Price Dependency: Uses close prices to determine trends and signals, which might not reflect intrabar price movements and trade imbalances accurately.
Historical Data: The script is based on historical data and does not guarantee future performance.
NOTES
Educational Tool: The script is designed for educational purposes and should not be considered financial advice.
Backtesting: Users are encouraged to backtest the strategy on a demo account before applying it to live trades.
Complementary Use: Best used in conjunction with other indicators and analysis methods for more accurate trading decisions.
THANKS
Special thanks to the TradingView community for their support and feedback.
Weekly Trading StrategyStrategy Overview:
This trading strategy is designed for short-term trades over weekly intervals, utilizing the combination of Simple Moving Averages (SMA) for trend identification and the Relative Strength Index (RSI) for overbought/oversold conditions. It aims to capitalize on momentum shifts while mitigating the risk of entering a market at extreme points.
Key Components:
Fast SMA (9 periods): Acts as a short-term trend indicator, providing insights into quick price changes.
Slow SMA (21 periods): Represents a longer-term trend, smoothing out price fluctuations to show a more stable trend line.
RSI (14 periods): An oscillator that measures the speed and change of price movements, helping to identify potential reversal points.
Entry Signals:
Buy Signal:
Condition 1: The fast SMA (9 periods) crosses above the slow SMA (21 periods), indicating a potential upward trend shift.
Condition 2: RSI falls below 30, suggesting the asset is potentially oversold and due for a correction upwards.
Sell Signal:
Condition 1: The fast SMA crosses below the slow SMA, signaling a possible downward trend shift.
Condition 2: RSI climbs above 70, indicating the asset might be overbought and could pull back.
Strategy Execution:
Timeframe: This strategy is optimized for a weekly chart (W), where each bar or candle represents one week of trading data.
Alert System: Alerts can be set up for buy and sell signals, allowing traders to react promptly to market conditions without constant chart monitoring.
Risk Management:
This strategy includes inherent risk management by avoiding trades when the market shows extreme conditions via RSI. However, traders should also consider:
Position sizing based on account size and risk tolerance.
Setting stop-loss orders to manage potential losses if the market moves against the position.
Considering additional market analysis or indicators for confirmation before executing trades.
Considerations:
Backtesting: Before live trading, backtest the strategy on historical data to assess performance across different market conditions.
Adaptation: Market dynamics change, so periodic review and adjustment of SMA periods and RSI thresholds might be necessary.
Complementary Analysis: Enhance this strategy with fundamental analysis or other technical indicators for a more robust trading approach.
This strategy is suited for traders looking for weekly swings in the market, balancing between following the trend and spotting potential reversals. However, like all trading strategies, it should not be used in isolation but as part of a broader trading plan.
Enhanced VIP-like IndicatorSettings Breakdown Tutorial: Optimizing a Trading Strategy
This guide explains the key trading strategy settings and how to customize them based on your trading style and goals. Each parameter is essential for tailoring the strategy to market conditions and your risk appetite.
1. Short Moving Average Length (Default: 9)
• Purpose: Tracks short-term trends using a small number of candles.
• Settings Tips:
• Smaller Values (e.g., 9): Quickly react to price changes, useful for fast-moving markets.
• Larger Values (e.g., 12-15): Generate smoother signals for less volatile trades.
2. Long Moving Average Length (Default: 21)
• Purpose: Identifies long-term trends.
• Settings Tips:
• Higher Values (e.g., 50): Spot broader trends at the expense of slower signals.
• Trend Analysis: The interaction of short and long MAs helps determine bullish or bearish trends (e.g., bullish when short MA crosses above long MA).
3. Higher Timeframe MA Length (Default: 200)
• Purpose: Filters long-term trends on a higher timeframe (e.g., daily).
• Settings Tips:
• 200 Periods: Standard for defining bullish (price above) or bearish (price below) markets.
• Adjustable: Use 100 for faster responses or stick with 200 for reliability.
4. Higher Timeframe (Default: 1 Day)
• Purpose: Defines the timeframe for the higher moving average.
• Settings Tips:
• Shorter Timeframes (e.g., 4 Hours): More frequent trading signals.
• Daily Timeframe: Best for swing trading and identifying macro trends.
5. RSI Length (Default: 14)
• Purpose: Measures momentum over a specific number of candles.
• Settings Tips:
• Lower Values (e.g., 7): More sensitive to price changes, ideal for quick trades.
• Higher Values (e.g., 20): Smooth signals for more stable markets.
6. RSI Overbought (70) and Oversold (30) Levels
• Purpose: Marks thresholds for overbought and oversold conditions.
• Settings Tips:
• Stricter Levels (e.g., 80/20): Fewer, higher-quality signals.
• Looser Levels (e.g., 65/35): More frequent signals, suitable for active trading.
7. Pivot Left Bars (5) and Pivot Right Bars (5)
• Purpose: Confirms pivot points (support/resistance) based on surrounding candles.
• Settings Tips:
• Higher Values (e.g., 10): Stronger but less frequent pivot points.
• Lower Values: More responsive, for traders seeking quick pivots.
8. Take Profit Percentage (Default: 2%)
• Purpose: Defines the profit level to exit trades.
• Settings Tips:
• Higher Values (e.g., 5%): For swing traders holding positions longer.
• Lower Values (e.g., 1%): For scalpers focusing on quick trades.
9. Minimum Volume (Default: 1,000,000)
• Purpose: Ensures sufficient liquidity for trading.
• Settings Tips:
• Lower Values: For lower-volume markets.
• Higher Values: Reduces risk in high-liquidity assets.
10. Stop Loss Percentage (Default: 1%)
• Purpose: Sets the maximum acceptable loss per trade.
• Settings Tips:
• Lower Values (e.g., 0.5%): Reduces risk, suited for conservative trading.
• Higher Values (e.g., 2%): Allows more price fluctuation, ideal for volatile markets.
11. Entry Conditions
• Options:
• MA Crossover & RSI: Combines trend-following and momentum for well-rounded signals.
• Pivot Breakout: Focuses on support/resistance breakouts for high-impact trades.
• Settings Tips:
• Trend-Following Traders: Use MA Crossover & RSI.
12. Exit Conditions
• Options:
• Opposite Signal: Exits when the trade’s opposite condition occurs (e.g., bullish to bearish).
• Fixed Take Profit/Stop Loss: Exits based on predefined profit/loss thresholds.
• Settings Tips:
• Opposite Signal: Ideal for trend-following strategies.
Summary
Customizing these settings aligns the strategy with your trading goals. Test configurations in a demo environment before live trading to refine the approach and optimize results. Always balance profit potential with risk management.
• Fixed Levels: Better for strict risk management.
• Breakout Traders: Opt for Pivot Breakout.
[blackcat] L3 Top and Bottom Divine JudgmentOVERVIEW
The "Top and Bottom Divine Judgment" indicator is designed to identify potential tops and bottoms in the market using a combination of EMAs, SMAs, and custom calculations based on high and low prices. It provides multiple lines and plots to help traders visualize different market conditions and potential turning points.
FEATURES
Customizable EMA and SMA periods for various calculations.
Identification of bullish and bearish trends using EMAs.
Detection of overbought and oversold conditions.
Multiple lines and histograms to indicate specific market conditions and potential reversals.
Visual alerts with colored lines and shapes.
HOW TO USE
Add the script to your TradingView chart.
Customize Settings:
Adjust the short_ema_period, long_ema_period, sma_period, high_period, low_period, and other period inputs in the "Inputs" section.
Bullish and Bearish EMAs:
bullish_ema (yellow) and bearish_ema (fuchsia) are plotted to assess the overall market trend.
When bullish_ema is above bearish_ema, it suggests an uptrend.
When bullish_ema is below bearish_ema, it suggests a downtrend.
High-Low Boundary Line:
A horizontal line at 50 (yellow) represents a midpoint in the normalized price range, helping to identify overbought or oversold conditions.
Danger and Caution, Sell Signal, etc.:
These lines indicate specific conditions where the market might be overextended or due for a reversal.
Histograms for CZS1 and CZS4:
These histograms (aqua and purple) represent changes in certain indicators, possibly related to momentum or volatility, helping traders gauge the strength of trends.
Support Line Cross:
A shape ("●") is plotted when the close price crosses above a calculated support line, which could be a buy signal.
Generate Trading Signals:
Bullish and Bearish Trends:
Use the crossover of bullish_ema and bearish_ema to identify potential trend changes.
Overbought/Oversold Conditions:
Use the High-Low Boundary Line to identify overbought or oversold levels.
Specific Market Conditions:
Use the lines for "Danger and Caution," "Sell Signal," "Weak Out Strong Stay," "Opportunity," "Low Suck," and "High Sell" to identify specific market conditions and potential reversals.
Support Line Cross:
Use the plotted shape to identify potential buy signals when the close price crosses above the support line.
Risk Management:
Use the indicator in conjunction with other tools and risk management strategies to confirm trading signals and manage positions effectively.
LIMITATIONS
The script is based on historical data and does not guarantee future performance.
It is recommended to use the script in conjunction with other analysis tools.
The effectiveness of the strategy may vary depending on the market conditions and asset being traded.
NOTES
The script is designed for educational purposes and should not be considered financial advice.
Users are encouraged to backtest the strategy on a demo account before applying it to live trades.
THANKS
Special thanks to the TradingView community for their support and feedback.
Enhanced SMA Strategy with Trend Lines & S&R by DaxThe Enhanced SMA Strategy with Trend Lines & Support/Resistance (S&R) by Dax indicator is a technical analysis tool designed to improve trading decisions by combining the simplicity of the Simple Moving Average (SMA) with the insight provided by trend lines and support/resistance levels. This hybrid approach aims to create a more robust and reliable trading strategy.
Key Components:
Simple Moving Average (SMA):
SMA is a basic trend-following indicator that calculates the average of a set of price data over a specified period. It helps identify the direction of the market, such as whether an asset is in an uptrend or downtrend.
The Enhanced SMA Strategy may use multiple SMAs, such as short-term (e.g., 20-period) and long-term (e.g., 50-period), to detect crossovers that signal buy or sell opportunities. For example, a bullish crossover occurs when a short-term SMA crosses above a long-term SMA, indicating a potential buying signal, while a bearish crossover signals a potential sell.
Trend Lines:
Trend lines are drawn on the price chart to visually identify the direction of the market, acting as dynamic support and resistance levels. A trend line is drawn by connecting two or more price points that demonstrate the overall price movement.
Trend lines can help traders see potential breakout or breakdown points. A price breaking above a downtrend line or below an uptrend line often signals a trend reversal.
Support and Resistance (S&R):
Support levels are price levels where an asset tends to find buying interest and stop falling, while Resistance levels are points where selling pressure emerges and prevent the price from rising further.
These levels are critical in determining where price reversals or consolidations are likely to occur. Enhanced S&R indicators can automatically identify these levels and draw horizontal lines at these critical points on the chart.
Combining S&R with SMA can help traders decide whether a breakout or bounce is likely at these levels, increasing the odds of a successful trade.
How It Works:
Trend Identification: The SMA is used to determine the trend direction. A rising SMA indicates an uptrend, while a falling SMA suggests a downtrend.
Signal Generation: The strategy often uses a combination of SMA crossovers (bullish or bearish) along with the confirmation of price action near trend lines and support/resistance levels. For example:
If a price breaks above resistance and the short-term SMA crosses above the long-term SMA, a buy signal is confirmed.
Conversely, if the price breaks below support and the short-term SMA crosses below the long-term SMA, a sell signal is given.
Dynamic Support/Resistance: Trend lines are drawn automatically or manually to spot areas where price might reverse. The Enhanced SMA Strategy checks if the price is close to these levels, providing a more precise entry/exit point based on the broader market context.
Advantages of the Enhanced SMA Strategy with Trend Lines & S&R:
Improved Accuracy: By combining trend-following (SMA) with key levels like trend lines and S&R, the strategy filters out false signals, leading to more reliable trade setups.
Trend Confirmation: The use of trend lines and S&R confirms the broader market context, reducing the risk of trading against the trend or entering at weak price points.
Flexible: This strategy can be applied to various timeframes, from short-term day trading to longer-term swing trading.
Visual Clarity: The combination of trend lines, S&R, and moving averages provides a clear and visually intuitive strategy for identifying key price levels and trend shifts.
How to Use It:
Draw Trend Lines: Identify the most recent price peaks and troughs to draw trend lines, marking the potential resistance and support levels.
Use SMAs: Apply two different-period SMAs to detect the trend (e.g., 20-period and 50-period). Pay attention to crossovers for buy/sell signals.
Watch for Breakouts or Reversals: Monitor how the price behaves at support or resistance levels and the trend lines. A price move beyond these levels, accompanied by a confirming SMA crossover, can signal a strong trade opportunity.
Conclusion:
The Enhanced SMA Strategy with Trend Lines & S&R by Dax is a powerful, multi-layered approach to technical analysis. It enhances the basic SMA strategy by incorporating additional tools like trend lines and support/resistance levels, which help traders make more informed decisions with higher accuracy. This method is suitable for both novice and experienced traders, offering clear trade signals while reducing the risk of false entries.
EMA Crossover Strategy with 50 & 200 EMAs - Faisal AnwarThis indicator uses 50 and 200-day Exponential Moving Averages (EMAs) to identify significant trend directions and potential trading opportunities through golden crossovers and death crosses. It highlights the role of EMAs as dynamic support in uptrends and downtrends, enhancing trend-following strategies.
Detailed Explanation:
EMAs Used:
The strategy utilizes two key EMAs — the 50-day EMA and the 200-day EMA. The 50-day EMA is often seen as a medium-term trend indicator, while the 200-day EMA is regarded as a benchmark for the long-term market trend.
Golden Crossover:
This occurs when the 50-day EMA crosses above the 200-day EMA, traditionally considered a bullish signal indicating potential long positions.
Death Cross:
This event is marked by the 50-day EMA crossing below the 200-day EMA, typically viewed as a bearish signal suggesting potential short positions.
Trend Support Identification:
The script also identifies when the price is above the 50-day EMA during an uptrend (indicating ongoing support) and when the price is above the 200-day EMA during a downtrend, suggesting the EMA is acting as resistance turning into support.
Visual Tools:
The indicator plots these EMAs on the chart with distinct colors for easy differentiation and uses background color changes to visually indicate when these EMAs act as support. Buy and sell signals are clearly marked with shapes and text directly on the chart for actionable insights.
Usage Tips:
Trading Decisions:
This indicator is best used in markets with clear trends, where EMAs can effectively identify shifts in momentum and serve as reliable support or resistance levels.
Complementary Tools:
Consider combining this EMA strategy with other technical analysis tools like RSI or MACD for confirmation of signals to enhance the reliability of the trading signals.
Ideal for:
Traders looking for a visual tool to assist in identifying trend directions and optimal points for entering or exiting trades based on established technical analysis principles.
MERCURY-PRO by DrAbhiramSivprasd“MERCURYPRO”
The MERCURYPRO indicator is a custom technical analysis tool designed to provide dynamic trend signals based on a combination of the Chande Momentum Oscillator (CMO) and Standard Deviation (StDev). This indicator helps traders identify trend reversals or continuation based on the behavior of the price and momentum.
Key Features:
• Source Input: The indicator works with any price data, with the default set to close, which represents the closing price of each bar.
• Length Input: A period (default value 9) is used to determine the calculation window for the Chande Momentum Oscillator and Standard Deviation.
• Fixed CMO Length Option: Users can choose whether to use a fixed CMO length of 9 or adjust the length to the user-defined pds value.
• Calculation Method: The indicator allows switching between using the Chande Momentum Oscillator (CMO) or Standard Deviation (StDev) for the momentum calculation.
• Alpha: The smoothing factor used in the calculation of the MERCURYPRO value, which is based on the length of the period input (pds).
Core Calculation:
1. Momentum Calculation: The script calculates the momentum by determining the change in the source price (e.g., close) from one period to the next.
2. Chande Momentum Oscillator (CMO): The positive and negative momentum components are calculated and then summed over the specified period. This value is normalized to a percentage to determine the momentum strength.
3. K Value Calculation: The script selects either the CMO or Standard Deviation (depending on the user setting) to calculate the k value, which represents the dynamic price momentum.
4. MERCURYPRO Line: The final output of the indicator, MERCURYPRO, is computed using a weighted average of the k value and the previous MERCURYPRO value. The line is smoothed using the Alpha parameter.
Plot and Signal Generation:
• Color Coding: The line is color-coded based on the direction of MERCURYPRO:
• Blue: The trend is bullish (MERCURYPRO is rising).
• Maroon: The trend is bearish (MERCURYPRO is falling).
• Default Blue: Neutral or sideways market conditions.
• Plotting: The MERCURYPRO line is plotted with varying colors depending on the trend direction.
Alerts:
• Color Change Alert: The indicator has an alert condition based on when the MERCURYPRO line crosses its previous value. This helps traders stay informed about potential trend reversals or continuation signals.
Use Case:
• Trend Confirmation: Traders can use the MERCURYPRO indicator to identify whether the market is in a strong trend or not.
• Signal for Entries/Exits: The color change and crossovers of the MERCURYPRO line can be used as entry or exit signals, depending on the trader’s strategy.
Overall Purpose:
The MERCURYPRO indicator combines momentum analysis with smoothing techniques to offer a dynamic, responsive tool for identifying market trends and potential reversals. It is particularly useful in conjunction with other technical indicators to provide confirmation for trade setups.
How to Use the MERCURYPRO Indicator:
The MERCURYPRO indicator is designed to help traders identify trend reversals and market conditions. Here are a few ways you can use it:
1. Trend Confirmation (Bullish or Bearish)
• Bullish Trend: When the MERCURYPRO line is colored Blue, it indicates a rising trend, suggesting that the market is bullish.
• Action: You can consider entering long positions when the line turns blue, or holding your existing positions if you’re already long.
• Bearish Trend: When the MERCURYPRO line is colored Maroon, it signals a downward trend, indicating a bearish market.
• Action: You may consider entering short positions or closing any long positions when the line turns maroon.
2. Trend Reversal Alerts
• Color Change: The MERCURYPRO indicator changes color when there’s a trend reversal. The alert condition triggers when the MERCURYPRO crosses above or below its previous value, signaling a potential shift in the trend.
• Action: You can use this alert as a signal to monitor potential entry or exit points for trades. For example, a crossover from maroon to blue could indicate a potential buying opportunity, while a crossover from blue to maroon could suggest a selling opportunity.
3. Use with Other Indicators for Confirmation
• While the MERCURYPRO provides valuable trend insights, it’s often more effective when used in combination with other indicators like RSI (Relative Strength Index), MACD, or moving averages to confirm signals.
• Example: If MERCURYPRO turns blue and RSI is above 50, it may signal a strong bullish trend, enhancing the confidence to enter a long trade.
4. Divergence
• Watch for divergence between the MERCURYPRO line and the price chart:
• Bullish Divergence: If the price makes new lows while MERCURYPRO is showing higher lows, it suggests a potential bullish reversal.
• Bearish Divergence: If the price makes new highs while MERCURYPRO is showing lower highs, it suggests a potential bearish reversal.
Example of Use:
• Example 1: If the MERCURYPRO line changes from maroon to blue, you might enter a long position. After the MERCURYPRO line turns blue, use an alert to monitor the price action. If other indicators (like RSI) also suggest strength, your confidence in the trade will increase.
• Example 2: If the MERCURYPRO line shifts from blue to maroon, it could be a signal to close long positions and consider shorting the market if other conditions align (e.g., moving averages also turn bearish).
Warning for Using the MERCURYPRO Indicator:
1. Lagging Indicator:
• The MERCURYPRO is a lagging indicator, meaning it responds to price changes after they have occurred. This may delay entry and exit signals, and it’s crucial to combine it with other leading indicators to get timely information.
2. False Signals in Range-bound Markets:
• In choppy or sideways markets, the MERCURYPRO line can produce false signals, flipping between blue and maroon frequently without showing a clear trend. It’s important to avoid trading based on these false signals when the market is not trending.
3. Overreliance on One Indicator:
• Relying solely on MERCURYPRO can be risky. Always confirm signals with additional tools like volume analysis, price action, or other indicators to increase the accuracy of your trades.
4. Market Conditions Matter:
• The indicator may work well in trending markets, but in highly volatile or news-driven environments, it may provide misleading signals. Ensure that you take market fundamentals and external news events into consideration before acting on the indicator’s signals.
5. Risk Management:
• As with any technical indicator, MERCURYPRO is not infallible. Always use appropriate risk management techniques such as stop-loss orders to protect your capital. Never risk more than you can afford to lose on a trade.
6. Backtest First:
• Before implementing MERCURYPRO in live trading, make sure to backtest it on historical data. Test the strategy with various market conditions to assess its effectiveness and identify any potential weaknesses.
By considering these guidelines and warnings, you can use the MERCURYPRO indicator more effectively and mitigate potential risks in your trading strategy.
TearRepresentative's Rule-Based Dip Buying Strategy Rule-Based Dip Buying Strategy Indicator
This TradingView indicator, inspired by TearRepresentative [ , is a refined tool designed to assist traders in implementing a rule-based dip buying strategy. The indicator automates the identification of optimal buy and sell points, helping traders stay disciplined and minimize emotional biases. It is tailored to index trading, specifically leveraged ETFs like SPXL, to capture opportunities in market pullbacks and recoveries.
Key Features
Dynamic Buy Levels:
Tracks the local high over a customizable lookback period and calculates three buy levels based on percentage drops from the high:
Buy Level 1: First entry point (e.g., 15% drop).
Buy Level 2: Second entry point (e.g., additional 10% drop).
Buy Level 3: Third entry point (e.g., additional 7% drop).
Average Price Tracking:
Dynamically calculates the average price for entered positions when multiple buy levels are triggered.
Sell Level:
Computes a take-profit level (e.g., 20% above the average price) to automate profit-taking when the market rebounds.
Signal Visualization:
Buy Signals: Displayed as green triangles at each buy level.
Sell Signals: Displayed as red triangles at the sell level.
Alerts:
Configurable alerts notify traders when buy or sell signals are triggered, ensuring no opportunity is missed.
Visual Aids:
Semi-transparent and dynamic lines represent buy and sell levels for clear visualization.
Labels provide additional clarity for active levels, helping traders quickly identify actionable signals.
How It Works
The indicator analyzes market movements to identify dips based on predefined thresholds.
Buy signals are triggered when the market price reaches specified levels below the local high.
Once a position is taken, the indicator dynamically adjusts the average entry price and calculates the corresponding sell level.
A sell signal is generated when the market price rises above the calculated take-profit level.
Why Use This Indicator?
Discipline: Automates decision-making, removing emotional factors from trading.
Clarity: Provides clear entry and exit points to simplify complex market dynamics.
Versatility: Suitable for all market conditions, especially during pullbacks and rebounds.
Customization: Allows traders to tailor parameters to their preferred trading style and risk tolerance.
Acknowledgment
This indicator is based on the strategy and insights provided by TearRepresentative, whose expertise in rule-based trading has inspired countless traders. TearRepresentative's approach emphasizes simplicity, reliability, and consistency, offering a robust framework for long-term success.
MCP Stop Strategy [JARUTIR]The MCP Stop Strategy is a trading tool designed to help traders lock in profits and manage risks. It is based on the concept of setting a MCP (Mental Capacity Preservation) Stop explained in the book "The Lifecycle Trade". I call it Maximum Controllable Profit Stop which helps protect profits once a stock or asset reaches a new peak. The MCP Stop is dynamically calculated based on the Buy Price and the All Time High Price (Peak Price), and is adjusted using a customizable percentage (MCP%) to retain a portion of the gains from the peak price during a drawdown.
Key Features :
MCP Stop Calculation: The script calculates the MCP Stop as:
MCP Stop = Buy Price + (Peak Price - Buy Price) x MCP%
This helps you protect a portion of your gains (defined by MCP%) as the price moves in your favor.
Flexible Buy Date Option:
You can either manually input a Buy Date or let the script automatically detect the Buy Date when the price first meets or exceeds the user-defined Buy Price.
After the Buy Date, the MCP Stop, Buy Price, and Peak Price are plotted on the chart for easy visualization.
Customizable Parameters:
Buy Price: The price at which the asset was bought.
MCP Percentage: The percentage of profit from the peak that you want to retain in case of a drawdown.
Lookback Length: The number of bars to consider when calculating the Peak Price (All Time High).
How to Use the Script :
Set the Buy Price: Enter the price at which you bought the asset.
Set the MCP%: Enter the percentage of profits you want to protect from the peak. For example, if you want to retain 10% of the gain from the peak, set this to 10.
Choose the Buy Date Method:
Automated Buy Date: The script will automatically detect the first bar where the price meets or exceeds the Buy Price.
Manual Buy Date: If you prefer to specify a particular Buy Date, input the desired date and time.
View the MCP Stop and Peak Price: After the Buy Date (either manually or automatically detected), the MCP Stop, Buy Price, and Peak Price will be plotted on the chart.
Monitor the MCP Stop Trigger: The script will alert you when the price falls below the MCP Stop, indicating a potential exit point to protect profits.
Frequently Asked Questions (FAQs):
1. What is the MCP Stop?
The MCP Stop is a dynamic stop-loss level that adjusts based on your Buy Price and the All Time High Price (Peak Price). It protects a portion of your gains from the peak, which is defined by the MCP%. For example, if you set the MCP% to 10%, the script will retain 10% of the gains from the peak and use this as a stop-loss.
2. How does the Buy Date work?
The Buy Date is the date when you entered the position:
If you choose Automated Buy Date, the script will automatically set the Buy Date to the first bar when the price meets or exceeds the Buy Price.
If you choose Manual Buy Date, you can specify a particular date and time when you want the strategy to start calculating and plotting the MCP Stop and Peak Price.
3. What happens if the price falls below the MCP Stop?
If the price drops below the MCP Stop, the script will mark this as a potential exit point, helping you protect profits. A visual alert (MCP STOP) will be shown on the chart when the price reaches or falls below the MCP Stop.
4. Can I adjust the Lookback Length for Peak Price?
Yes, you can customize the Lookback Length (the number of bars the script considers when calculating the Peak Price) by entering a value in the input field. By default, it is set to 1000 bars, which represents a few months of historical data, but you can increase or decrease this based on your trading strategy.
5. Why would I want to use the automated Buy Date?
The Automated Buy Date is useful for traders who want the script to automatically track the Buy Date when the price first reaches or exceeds the Buy Price. This is helpful when you're unsure of the exact entry date but know the price at which you bought the asset. It simplifies the process by eliminating the need for manual input.
6. Can I use this strategy for long and short positions?
The current version of this script is designed for long positions, where you buy an asset and want to protect your profits as the price increases. If you're interested in applying it to short positions, you would need to adjust the logic accordingly (e.g., tracking the lowest price instead of the peak price).
7. Can I modify the script to fit my trading strategy?
Yes, this script is highly customizable. You can adjust parameters such as Buy Price, MCP%, and Lookback Length to suit your specific trading style. You can also tweak the visual appearance of the plotted lines and alerts.
Disclaimer:
This strategy is intended for educational purposes only. It should not be considered financial advice. Always perform your own research and consult with a professional before making any trading decisions. Trading involves significant risk, and you should never trade with money you cannot afford to lose.
RSI and Bollinger Bands Screener [deepakks444]Indicator Overview
The indicator is designed to help traders identify potential long signals by combining the Relative Strength Index (RSI) and Bollinger Bands across multiple timeframes. This combination allows traders to leverage the strengths of both indicators to make more informed trading decisions.
Understanding RSI
What is RSI?
The Relative Strength Index (RSI) is a momentum oscillator that measures the speed and change of price movements. Developed by J. Welles Wilder Jr. for stocks and forex trading, the RSI is primarily used to identify overbought or oversold conditions in an asset.
How RSI Works:
Calculation: The RSI is calculated using the average gains and losses over a specified period, typically 14 periods.
Range: The RSI oscillates between 0 and 100.
Interpretation:
Key Features of RSI:
Momentum Indicator: RSI helps identify the momentum of price movements.
Divergences: RSI can show divergences, where the price makes a higher high, but the RSI makes a lower high, indicating potential reversals.
Trend Identification: RSI can also help identify trends. In an uptrend, the RSI tends to stay above 50, and in a downtrend, it tends to stay below 50.
Understanding Bollinger Bands
What is Bollinger Bands?
Bollinger Bands are a type of trading band or envelope plotted two standard deviations (positively and negatively) away from a simple moving average (SMA) of a price. Developed by financial analyst John Bollinger, Bollinger Bands consist of three lines:
Upper Band: SMA + (Standard Deviation × Multiplier)
Middle Band (Basis): SMA
Lower Band: SMA - (Standard Deviation × Multiplier)
How Bollinger Bands Work:
Volatility Measure: Bollinger Bands measure the volatility of the market. When the bands are wide, it indicates high volatility, and when the bands are narrow, it indicates low volatility.
Price Movement: The price tends to revert to the mean (middle band) after touching the upper or lower bands.
Support and Resistance: The upper and lower bands can act as dynamic support and resistance levels.
Key Features of Bollinger Bands:
Volatility Indicator: Bollinger Bands help traders understand the volatility of the market.
Mean Reversion: Prices tend to revert to the mean (middle band) after touching the bands.
Squeeze: A Bollinger Band Squeeze occurs when the bands narrow significantly, indicating low volatility and a potential breakout.
Combining RSI and Bollinger Bands
Strategy Overview:
The strategy aims to identify potential long signals by combining RSI and Bollinger Bands across multiple timeframes. The key conditions are:
RSI Crossing Above 60: The RSI should cross above 60 on the 15-minute timeframe.
RSI Above 60 on Higher Timeframes: The RSI should already be above 60 on the hourly and daily timeframes.
Price Above 20MA or Walking on Upper Bollinger Band: The price should be above the 20-period moving average of the Bollinger Bands or walking on the upper Bollinger Band.
Strategy Details:
RSI Calculation:
Calculate the RSI for the 15-minute, 1-hour, and 1-day timeframes.
Check if the RSI crosses above 60 on the 15-minute timeframe.
Ensure the RSI is above 60 on the 1-hour and 1-day timeframes.
Bollinger Bands Calculation:
Calculate the Bollinger Bands using a 20-period moving average and 2 standard deviations.
Check if the price is above the 20-period moving average or walking on the upper Bollinger Band.
Entry and Exit Signals:
Long Signal: When all the above conditions are met, consider a long entry.
Exit: Exit the trade when the price crosses below the 20-period moving average or the stop-loss is hit.
Example Usage
Setup:
Add the indicator to your TradingView chart.
Configure the inputs as per your requirements.
Monitoring:
Look for the long signal on the chart.
Ensure that the RSI is above 60 on the 15-minute, 1-hour, and 1-day timeframes.
Check that the price is above the 20-period moving average or walking on the upper Bollinger Band.
Trading:
Enter a long position when the criteria are met.
Set a stop-loss below the low of the recent 15-minute candle or based on your risk management rules.
Monitor the trade and exit when the RSI returns below 60 on any of the timeframes or when the price crosses below the 20-period moving average.
House Rules Compliance
No Financial Advice: This strategy is for educational purposes only and should not be construed as financial advice.
Risk Management: Always use proper risk management techniques, including stop-loss orders and position sizing.
Past Performance: Past performance is not indicative of future results. Always conduct your own research and analysis.
TradingView Guidelines: Ensure that any shared scripts or strategies comply with TradingView's terms of service and community guidelines.
Conclusion
This strategy combines RSI and Bollinger Bands across multiple timeframes to identify potential long signals. By ensuring that the RSI is above 60 on higher timeframes and that the price is above the 20-period moving average or walking on the upper Bollinger Band, traders can make more informed decisions. Always remember to conduct thorough research and use proper risk management techniques.
[blackcat] L1 Simple Dual Channel Breakout█ OVERVIEW
The script " L1 Simple Dual Channel Breakout" is an indicator designed to plot dual channel breakout bands and their long-term EMAs on a chart. It calculates short-term and long-term moving averages and deviations to establish upper, lower, and middle bands, which traders can use to identify potential breakout opportunities.
█ LOGICAL FRAMEWORK
Structure:
The script is structured into several main sections:
• Input Parameters: The script does not explicitly define input parameters for the user to adjust, but it uses default values for short_term_length (5) and long_term_length (181).
• Calculations: The calculate_dual_channel_breakout function performs the core calculations, including the blast condition, typical price, short-term and long-term moving averages, and dynamic moving averages.
• Plotting: The script plots the short-term bands (upper, lower, and middle) and their long-term EMAs. It also plots conditional line breaks when the short-term bands cross the long-term EMAs.
Flow of Data and Logic:
1 — The script starts by defining the calculate_dual_channel_breakout function.
2 — Inside the function, it calculates various moving averages and deviations based on the input prices and lengths.
3 — The function returns the calculated bands and EMAs.
4 — The script then calls this function with predefined lengths and plots the resulting bands and EMAs on the chart.
5 — Conditional plots are added to highlight breakouts when the short-term bands cross the long-term EMAs.
█ CUSTOM FUNCTIONS
The script defines one custom function:
• calculate_dual_channel_breakout(close_price, high_price, low_price, short_term_length, long_term_length): This function calculates the short-term and long-term bands and EMAs. It takes five parameters: close_price, high_price, low_price, short_term_length, and long_term_length. It returns an array containing the upper band, lower band, middle band, long-term upper EMA, long-term lower EMA, and long-term middle EMA.
█ KEY POINTS AND TECHNIQUES
• Typical Price Calculation: The script uses a modified typical price calculation (2 * close_price + high_price + low_price) / 4 instead of the standard (high_price + low_price + close_price) / 3.
• Short-term and Long-term Bands: The script calculates short-term bands using a simple moving average (SMA) of the typical price and long-term bands using a relative moving average (RMA) of the close price.
• Conditional Plotting: The script uses conditional plotting to highlight breakouts when the short-term bands cross the long-term EMAs, enhancing visual identification of trading signals.
• EMA for Long-term Trends: The use of Exponential Moving Averages (EMAs) for long-term bands helps in smoothing out short-term fluctuations and focusing on long-term trends.
█ EXTENDED KNOWLEDGE AND APPLICATIONS
• Modifications: Users can add input parameters to allow customization of short_term_length and long_term_length, making the indicator more flexible.
• Enhancements: The script could be extended to include alerts for breakout conditions, providing traders with real-time notifications.
• Alternative Bands: Users might experiment with different types of moving averages (e.g., WMA, HMA) for the short-term and long-term bands to see if they yield better results.
• Additional Indicators: Combining this indicator with other technical indicators (e.g., RSI, MACD) could provide a more comprehensive trading strategy.
• Backtesting: Users can backtest the strategy using Pine Script's strategy functions to evaluate its performance over historical data.
Hybrid Triple Exponential Smoothing🙏🏻 TV, I present you HTES aka Hybrid Triple Exponential Smoothing, designed by Holt & Winters in the US, assembled by me in Saint P. I apply exponential smoothing individually to the data itself, then to residuals from the fitted values, and lastly to one-point forecast (OPF) errors, hence 'hybrid'. At the same time, the method is a closed-form solution and purely online, no need to make any recalculations & optimize anything, so the method is O(1).
^^ historical OPFs and one-point forecasting interval plotted instead of fitted values and prediction interval
Before the How-to, first let me tell you some non-obvious things about Triple Exponential smoothing (and about Exponential Smoothing in general) that not many catch. Expo smoothing seems very straightforward and obvious, but if you look deeper...
1) The whole point of exponential smoothing is its incremental/online nature, and its O(1) algorithm complexity, making it dope for high-frequency streaming data that is also univariate and has no weights. Consequently:
- Any hybrid models that involve expo smoothing and any type of ML models like gradient boosting applied to residuals rarely make much sense business-wise: if you have resources to boost the residuals, you prolly have resources to use something instead of expo smoothing;
- It also concerns the fashion of using optimizers to pick smoothing parameters; honestly, if you use this approach, you have to retrain on each datapoint, which is crazy in a streaming context. If you're not in a streaming context, why expo smoothing? What makes more sense is either picking smoothing parameters once, guided by exogenous info, or using dynamic ones calculated in a minimalistic and elegant way (more on that in further drops).
2) No matter how 'right' you choose the smoothing parameters, all the resulting components (level, trend, seasonal) are not pure; each of them contains a bit of info from the other components, this is just how non-sequential expo smoothing works. You gotta know this if you wanna use expo smoothing to decompose your time series into separate components. The only pure component there, lol, is the residuals;
3) Given what I've just said, treating the level (that does contain trend and seasonal components partially) as the resulting fit is a mistake. The resulting fit is level (l) + trend (b) + seasonal (s). And from this fit, you calculate residuals;
4) The residuals component is not some kind of bad thing; it is simply the component that contains info you consciously decide not to include in your model for whatever reason;
5) Forecasting Errors and Residuals from fitted values are 2 different things. The former are deltas between the forecasts you've made and actual values you've observed, the latter are simply differences between actual datapoints and in-sample fitted values;
6) Residuals are used for in-sample prediction intervals, errors for out-of-sample forecasting intervals;
7) Choosing between single, double, or triple expo smoothing should not be based exclusively on the nature of your data, but on what you need to do as well. For example:
- If you have trending seasonal data and you wanna do forecasting exclusively within the expo smoothing framework, then yes, you need Triple Exponential Smoothing;
- If you wanna use prediction intervals for generating trend-trading signals and you disregard seasonality, then you need single (simple) expo smoothing, even on trending data. Otherwise, the trend component will be included in your model's fitted values → prediction intervals.
8) Kind of not non-obvious, but when you put one smoothing parameter to zero, you basically disregard this component. E.g., in triple expo smoothing, when you put gamma and beta to zero, you basically end up with single exponential smoothing.
^^ data smoothing, beta and gamma zeroed out, forecasting steps = 0
About the implementation
* I use a simple power transform that results in a log transform with lambda = 0 instead of the mainstream-used transformers (if you put lambda on 2 in Box-Cox, you won't get a power of 2 transform)
* Separate set of smoothing parameters for data, residuals, and errors smoothing
* Separate band multipliers for residuals and errors
* Both typical error and typical residuals get multiplied by math.sqrt(math.pi / 2) in order to approach standard deviation so you can ~use Z values and get more or less corresponding probabilities
* In script settings → style, you can switch on/off plotting of many things that get calculated internally:
- You can visualize separate components (just remember they are not pure);
- You can switch off fit and switch on OPF plotting;
- You can plot residuals and their exponentially smoothed typical value to pick the smoothing parameters for both data and residuals;
- Or you might plot errors and play with data smoothing parameters to minimize them (consult SAE aka Sum of Absolute Errors plot);
^^ nuff said
More ideas on how to use the thing
1) Use Double Exponential Smoothing (data gamma = 0) to detrend your time series for further processing (Fourier likes at least weakly stationary data);
2) Put single expo smoothing on your strategy/subaccount equity chart (data alpha = data beta = 0), set prediction interval deviation multiplier to 1, run your strat live on simulator, start executing on real market when equity on simulator hits upper deviation (prediction interval), stop trading if equity hits lower deviation on simulator. Basically, let the strat always run on simulator, but send real orders to a real market when the strat is successful on your simulator;
3) Set up the model to minimize one-point forecasting errors, put error forecasting steps to 1, now you're doing nowcasting;
4) Forecast noisy trending sine waves for fun.
^^ nuff said 2
All Good TV ∞
Structure Pilot Vision [Wang Indicators]Built and refined with Dave Teaches, the HTF Vision Pro supercharges the trader, providing them with the tools to approach price with a layered analysis.
Providing the trader the instruments to put on the spotlight significant zones to anticipate price deliveries
HTF CANDLE VISION
Displays up to 3 series of HTF Candles
Shows candlesticks from a higher time frame (e.g., daily, 4-hour, weekly) on a lower time frame chart (e.g., 1-hour, 15-minute). This allows traders to simultaneously observe both short-term and long-term market dynamics.
Customizable Time Frames: Users can select any higher time frame to overlay on the current chart. Common time frames include daily, weekly, and monthly candles, but other custom time frames can also be used.
Color Coding: The HTF candles are color-coded for easy differentiation from the lower time frame candles. Users can customize colors to suit their preferences.
Open, High, Low, Close (OHLC) Representation: The indicator displays the full candlestick pattern for the chosen HTF, including the open, high, low, and close values. This helps traders easily identify key price levels and trends.
Settings :
Number of candles
Space between the chart and the HTF candles
Space between candles sets
Size : from Tiny (2x regular candle size) to Large (x8 regular candle size)
Space between candles
Colors of candles, borders and wicks
Incorporating a Higher Time Frame (HTF) candle into your Lower Time Frame (LTF) chart can be immensely beneficial for traders looking to enhance their analysis and decision-making process.
Use Cases for HTF Candles on LTF Charts:
Trend Confirmation:
Use Case: A trader might be looking at a 15-minute chart (LTF) but wants to confirm if the short-term trends align with the daily trend (HTF). Plotting a daily candle on the 15-minute chart helps visualize whether the short-term movements are part of a broader, longer-term trend.
Support and Resistance Identification:
Use Case: By plotting a weekly candle on a daily chart, traders can quickly identify levels that have acted as significant support or resistance in the past on the higher time frame, which might not be as visible or influential on the daily chart alone.
Entry and Exit Points Enhancement:
Use Case: When preparing to enter a trade based on a 1-hour chart, overlaying a 4-hour candle can provide insights into potential reversal points or continuation patterns that are more significant on the higher time frame, thus refining entry and exit strategies.
Volatility and Breakout Analysis:
Use Case: Seeing how a single HTF candle (like a monthly candle on a weekly chart) closes can give traders an idea of the market's volatility or the strength behind breakouts. A long wick on the HTF candle might suggest a rejected breakout or a potential reversal.
Risk Management:
Use Case: Using an HTF candle can help set more informed stop-loss levels. For instance, if a trader uses a 4-hour candle on a 1-hour chart, they might place their stop-loss just beyond the low of the HTF candle, assuming this represents a significant level of support or resistance.
Contextual Trading Decisions:
Use Case: For scalpers or day traders, understanding where the current price action sits within the context of a higher timeframe can lead to better decision-making. For instance, trading within an HTF consolidation range might suggest less aggressive moves, while being near the top or bottom of such a range might indicate potential for larger movements.
Market Sentiment Analysis:
Use Case: The color (red for bearish, green for bullish) and size of the HTF candle can give a quick visual cue of the market sentiment over that period, helping traders assess whether they are going with or against the broader market flow.
Swing Trading:
Use Case: Swing traders might plot a weekly candle on a daily chart to align their trades with the direction of the weekly trend, ensuring they're not fighting the broader market momentum.
Educational and Visual Reference:
Use Case: For educational purposes, having an HTF candle overlay can serve as a visual reminder for students or new traders about how price movements on different time frames can influence each other, aiding in teaching concepts like "the trend is your friend."
Wang use cases :
The way it is intended to be used is as follow
If you trade the 1 min chart and have a set of 5 min HTF candles plotted on your charts it could be used as follow :
As long as the 5 min keep providing close below the last 5 min candle if you're short you're safe ... if the 5 min candle stop closing below the last ones and start giving up-close you should consider closing your trade
Another use of HTF Candle is to find fractals responsible (up or down internal mouv before the breakout that creates a new zone). This fractal acts as supply and demand zone responsible for maintening the trend or for a reversal.
See examples below :
These fractals are interesting zones because they often cause the price to react, so following a flip in the fractal, you can take a short in bearish zones and a long in bullish zones. Fractals are easier to detect thanks to the HTF candles function, and allow you to enter positions with greater confidence. They can be used in the same way as the 70%, 50% and 30% interest zones, or they can be used simultaneously.
Use with zones :
▫️ VERTICAL BARS VISION ▫️
The vertical bars provide a view of market fractality: on a low time frame chart, they show the size of a candle in a higher time frame, and thus give a better understanding of the price fractality essential to the strategy we use.
Example :
For your information, when you modify data in the vertical bars or HTF candles parameters, the two are synchronized automatically.
The Vertical HTF Candle Closures Indicator is a simple yet effective tool that helps traders visually track the closing times of higher time frame (HTF) candles (such as 4H, 1H, 15M) on a lower time frame chart (e.g., 1-minute).
This feature plots vertical lines on the chart at the exact closure time of each selected HTF, allowing traders to quickly recognize key moments when the HTF candles close, or better yet when we trade above / below the last one and reverse ''sweepy sweepy'' .
Its more like a vertical and more micro visualisation than the HTF Candles.
Wang usage :
its a great tool to be able to reverse engineer what's in a HTFcandle precisely its a good combination with HTF candle projections to train the eyes of the traders about Whats is inside a candle that formed on the higher time frame
Limitation & know issues :
The chart may become cluttered with too many lines if multiple time frames are selected. Adjusting the line style or disabling certain time frames can help reduce visual noise.
On low time frame (<30s), some bar may notshow exactly on time (e.g : in 10sec timeframe, the 15min bar can be displayed at 01:15:10 instead of 01:15:00).
Because of the data provider and the interpreter of Trading View, if there is not data for a candle, Trading view just "skip" the candle. Sometime, those skip are on the candle that goes to 15min, 1 hour or 4 hour. As this is a Trading View issue. There is pretty much nothing we can do.
Some users may experience vertical bars at 1am, 5am, 9am ... instead of 0am, 4am, 8am ... That is because of the difference between the Timezone set on the chart and the timezone of the market they trade. Vertical bar will always refer to the symbol displayed
Previous Day High and Low Count with Probabilities
Indicator Explanation
This indicator displays the number of days on which the previous day's high or low prices were not reached and calculates probabilities for future price movements based on this information. It stores the high and low values of the last 45 days and checks daily whether these levels were touched. Based on the number of days without touching either the high or the low, the indicator calculates the probability of future price movements in either direction (Up or Down).
The indicator offers customization options for label placement and color on the chart. The counts for the high and low touches, along with the calculated probabilities (in percentages), are displayed as labels on the chart. These labels can be shifted along the X-axis by up to 50 bars and can be customized in color and size. Additionally, the text for the labels can be freely chosen, giving the user improved flexibility and overview.
In summary, this indicator helps to:
- Track how often previous day's high and low levels were not reached.
- Estimate probabilities for future price movements based on this information.
- Customize the chart display for easier interpretation.
Strategy Concept
Probability and Touch Conditions:
A long position is entered only if:
The probability of reaching the high is at least 60%.
The price has not touched the previous day’s high in the last three days.
Similarly, for short positions:
The probability of reaching the low is at least 60%.
The price has not touched the previous day’s low in the last three days.
Incremental Position Size Increase:
On the 3rd consecutive day without a high/low touch and with the probability condition met, an initial position of 0.01 lots is opened.
On the 4th day, an additional position of 0.01 lots is added.
On the 5th day, an extra position of 0.02 lots is opened.
After a two-day pause, the situation is re-evaluated, and if conditions are still met, a 0.04-lot position is considered.
Trend Reversal Detection:
The strategy also includes a simple trend reversal check. If the market shows clear reversal signals, no new positions will be opened.
Adjustments and Risk Management
This strategy can be adjusted by modifying the probability values, the number of days without a high/low touch, and the lot sizes. Additionally, stop-loss and take-profit levels can be added to further control the risk and secure profits.
Strategy Concept
Probability and Touch Conditions:
A long position is entered only if:
The probability of reaching the high is at least 60%.
The price has not touched the previous day’s high in the last three days.
Similarly, for short positions:
The probability of reaching the low is at least 60%.
The price has not touched the previous day’s low in the last three days.
Incremental Position Size Increase:
On the 3rd consecutive day without a high/low touch and with the probability condition met, an initial position of 0.01 lots is opened.
On the 4th day, an additional position of 0.01 lots is added.
On the 5th day, an extra position of 0.02 lots is opened.
After a two-day pause, the situation is re-evaluated, and if conditions are still met, a 0.04-lot position is considered.
Trend Reversal Detection:
The strategy also includes a simple trend reversal check. If the market shows clear reversal signals, no new positions will be opened.
Risk Disclaimer
The author of this strategy does not assume any liability for potential losses or gains that may arise from the use of this strategy. Trading involves significant risk, and it is important to only trade with capital that you can afford to lose. The strategy presented is for educational purposes only and should not be considered as financial advice. Always conduct your own research and consider seeking advice from a professional financial advisor before making any trading decisions.
RBF Kijun Trend System [InvestorUnknown]The RBF Kijun Trend System utilizes advanced mathematical techniques, including the Radial Basis Function (RBF) kernel and Kijun-Sen calculations, to provide traders with a smoother trend-following experience and reduce the impact of noise in price data. This indicator also incorporates ATR to dynamically adjust smoothing and further minimize false signals.
Radial Basis Function (RBF) Kernel Smoothing
The RBF kernel is a mathematical method used to smooth the price series. By calculating weights based on the distance between data points, the RBF kernel ensures smoother transitions and a more refined representation of the price trend.
The RBF Kernel Weighted Moving Average is computed using the formula:
f_rbf_kernel(x, xi, sigma) =>
math.exp(-(math.pow(x - xi, 2)) / (2 * math.pow(sigma, 2)))
The smoothed price is then calculated as a weighted sum of past prices, using the RBF kernel weights:
f_rbf_weighted_average(src, kernel_len, sigma) =>
float total_weight = 0.0
float weighted_sum = 0.0
// Compute weights and sum for the weighted average
for i = 0 to kernel_len - 1
weight = f_rbf_kernel(kernel_len - 1, i, sigma)
total_weight := total_weight + weight
weighted_sum := weighted_sum + (src * weight)
// Check to avoid division by zero
total_weight != 0 ? weighted_sum / total_weight : na
Kijun-Sen Calculation
The Kijun-Sen, a component of Ichimoku analysis, is used here to further establish trends. The Kijun-Sen is computed as the average of the highest high and the lowest low over a specified period (default: 14 periods).
This Kijun-Sen calculation is based on the RBF-smoothed price to ensure smoother and more accurate trend detection.
f_kijun_sen(len, source) =>
math.avg(ta.lowest(source, len), ta.highest(source, len))
ATR-Adjusted RBF and Kijun-Sen
To mitigate false signals caused by price volatility, the indicator features ATR-adjusted versions of both the RBF smoothed price and Kijun-Sen.
The ATR multiplier is used to create upper and lower bounds around these lines, providing dynamic thresholds that account for market volatility.
Neutral State and Trend Continuation
This indicator can interpret a neutral state, where the signal is neither bullish nor bearish. By default, the indicator is set to interpret a neutral state as a continuation of the previous trend, though this can be adjusted to treat it as a truly neutral state.
Users can configure this setting using the signal_str input:
simple string signal_str = input.string("Continuation of Previous Trend", "Treat 0 State As", options = , group = G1)
Visual difference between "Neutral" (Bottom) and "Continuation of Previous Trend" (Top). Click on the picture to see it in full size.
Customizable Inputs and Settings:
Source Selection: Choose the input source for calculations (open, high, low, close, etc.).
Kernel Length and Sigma: Adjust the RBF kernel parameters to change the smoothing effect.
Kijun Length: Customize the lookback period for Kijun-Sen.
ATR Length and Multiplier: Modify these settings to adapt to market volatility.
Backtesting and Performance Metrics
The indicator includes a Backtest Mode, allowing users to evaluate the performance of the strategy using historical data. In Backtest Mode, a performance metrics table is generated, comparing the strategy's results to a simple buy-and-hold approach. Key metrics include mean returns, standard deviation, Sharpe ratio, and more.
Equity Calculation: The indicator calculates equity performance based on signals, comparing it against the buy-and-hold strategy.
Performance Metrics Table: Detailed performance analysis, including probabilities of positive, neutral, and negative returns.
Alerts
To keep traders informed, the indicator supports alerts for significant trend shifts:
// - - - - - ALERTS - - - - - //{
alert_source = sig
bool long_alert = ta.crossover (intrabar ? alert_source : alert_source , 0)
bool short_alert = ta.crossunder(intrabar ? alert_source : alert_source , 0)
alertcondition(long_alert, "LONG (RBF Kijun Trend System)", "RBF Kijun Trend System flipped ⬆LONG⬆")
alertcondition(short_alert, "SHORT (RBF Kijun Trend System)", "RBF Kijun Trend System flipped ⬇Short⬇")
//}
Important Notes
Calibration Needed: The default settings provided are not optimized and are intended for demonstration purposes only. Traders should adjust parameters to fit their trading style and market conditions.
Neutral State Interpretation: Users should carefully choose whether to treat the neutral state as a continuation or a separate signal.
Backtest Results: Historical performance is not indicative of future results. Market conditions change, and past trends may not recur.
HBK Price Action Strategy HBKPrice Action Strategy for XAUUSD with a Favorable Risk-Reward Ratio
Understanding the Strategy:
This strategy leverages price action principles to identify potential entry and exit points for XAUUSD on a 5-minute timeframe. The core idea is to identify price action patterns that suggest a high probability of a particular direction, and then to set stop-loss and take-profit levels to manage risk and reward.
Key Price Action Patterns to Watch:
Pin Bar: A pin bar is a candlestick with a long wick in one direction and a small body in the opposite direction. It often signals a reversal in the current trend.
Inside Bar: An inside bar forms when the current candle's high is lower than the previous candle's high, and the current candle's low is higher than the previous candle's low. It often indicates indecision or a potential breakout.
Engulfing Pattern: An engulfing pattern occurs when the current candle completely engulfs the previous candle. A bullish engulfing pattern signals a potential uptrend, while a bearish engulfing pattern signals a potential downtrend.
Risk-Reward Ratio:
A favorable risk-reward ratio is crucial for long-term trading success. Aim for a minimum risk-reward ratio of 1:2, meaning you risk $1 to potentially gain $2.
Entry and Exit Signals:
Long Entry:
Identify a bullish pin bar or engulfing pattern.
Wait for a confirmation candle to close above the pin bar's high or the engulfing pattern's high.
Place a stop-loss below the recent swing low.
Set a take-profit target at a key resistance level or a multiple of the stop-loss distance.
Short Entry:
Identify a bearish pin bar or engulfing pattern.
Wait for a confirmation candle to close below the pin bar's low or the engulfing pattern's low.
Place a stop-loss above the recent swing high.
Set a take-profit target at a key support level or a multiple of the stop-loss distance.
Additional Tips:
Use Support and Resistance Levels: Identify key support and resistance levels to set your stop-loss and take-profit targets.
Consider Market Sentiment: Pay attention to market sentiment and news events that may impact gold prices.
Manage Risk: Always use stop-loss orders to limit potential losses.
Be Patient: Don't force trades. Wait for high-probability setups.
Practice Discipline: Stick to your trading plan and avoid impulsive decisions.
Remember:
Price action trading requires practice and patience.
Backtest your strategy on historical data to refine your approach.
Always adapt to changing market conditions.
By following these guidelines and practicing disciplined risk management, you can increase your chances of success in trading XAUUSD on a 5-minute timeframe.
Custom Fibonacci StrategyCustom Fibonacci Strategy:
This strategy relies on analyzing Fibonacci levels to identify entry points for trades. It works by identifying peaks and troughs over a specified time period (50 bars in this code). Here are the steps of the strategy:
Identifying Peaks and Troughs:
The highest peak and lowest trough over the last 50 bars are identified.
If the price exceeds the previous peak, it is considered a break of the peak.
If the price falls below the previous trough after breaking the peak, it is considered a break of the trough.
Calculating Fibonacci Levels:
The 50% level (midway point) between the identified peak and trough is calculated.
Buy Signals:
When a trough is broken, and the price trades at or below the 50% level, the risk-to-reward ratio is evaluated.
If the risk-to-reward ratio is greater than or equal to 2, a buy signal is generated.
Displaying Levels:
Horizontal lines are displayed on the chart to illustrate the peak, trough, and Fibonacci level.
Summary
This strategy provides a systematic approach to trading based on Fibonacci retracement levels and price action, allowing traders to make informed decisions about entry points and manage risk effectively.
