Killzones & Previous High-Low Liquidity [odnac]This indicator is designed for use in intraday trading to visualize key "Killzones" (specific time windows during different global market sessions) and highlight liquidity levels based on previous highs and lows from the previous day and week.
It helps traders identify potential market entry and exit points based on time-based trading zones and price action levels.
Key Features:
Killzone (Market Session Timeframes):
Asia (2000-0000 UTC): Displays a shaded box over the Asia trading session.
Europe (0200-0500 UTC): Highlights the European trading session.
New York AM (0830-1100 UTC): Represents the morning session of the NY market.
New York PM (1330-1600 UTC): Represents the afternoon session of the NY market.
Each of these timeframes can be customized in terms of session start and end times, and the shaded areas will help identify high liquidity periods when the market tends to be more active.
Previous High-Low Liquidity Zones:
Previous Week's High/Low: Displays lines at the high and low of the previous week.
These are important liquidity levels that can influence price action.
Previous Day's High/Low: Shows the high and low from the previous trading day.
These are also significant levels to watch for potential support and resistance.
Filters and Customization:
Position Filtering: The indicator allows users to filter out previous highs or lows if the current price doesn't align with those levels.
For example, it can filter out previous week highs if the current price is lower than that level.
Vertical Lines: Optional vertical lines to highlight key time points such as the start and end of the previous week and day.
How It Works:
The indicator visually draws "killzones" as shaded regions on the chart, indicating periods of increased market activity.
This can help traders align their strategies with the most liquid periods of the day.
The previous high and low lines (both for the previous week and the previous day) are drawn as solid lines and can be toggled on/off in the settings.
Labels are added to indicate the specific levels and periods.
The indicator provides clear visual cues, helping traders assess if the price is near important liquidity levels and whether the current market conditions align with those levels.
Customizable Settings:
You can control whether each Killzone and liquidity level is shown on the chart.
Color customization for the various zones and lines is also available.
The indicator also lets you decide whether to hide weekend data, set time-frame limits, and choose whether or not to show vertical lines at the beginning and end of each trading session.
This indicator is aimed at traders who want to trade based on high-liquidity periods and understand where key support and resistance levels are likely to emerge based on previous price action.
Komut dosyalarını "Cycle" için ara
Volatility Momentum Breakout StrategyDescription:
Overview:
The Volatility Momentum Breakout Strategy is designed to capture significant price moves by combining a volatility breakout approach with trend and momentum filters. This strategy dynamically calculates breakout levels based on market volatility and uses these levels along with trend and momentum conditions to identify trade opportunities.
How It Works:
1. Volatility Breakout:
• Methodology:
The strategy computes the highest high and lowest low over a defined lookback period (excluding the current bar to avoid look-ahead bias). A multiple of the Average True Range (ATR) is then added to (or subtracted from) these levels to form dynamic breakout thresholds.
• Purpose:
This method helps capture significant price movements (breakouts) while ensuring that only past data is used, thereby maintaining realistic signal generation.
2. Trend Filtering:
• Methodology:
A short-term Exponential Moving Average (EMA) is applied to determine the prevailing trend.
• Purpose:
Long trades are considered only when the current price is above the EMA, indicating an uptrend, while short trades are taken only when the price is below the EMA, indicating a downtrend.
3. Momentum Confirmation:
• Methodology:
The Relative Strength Index (RSI) is used to gauge market momentum.
• Purpose:
For long entries, the RSI must be above a mid-level (e.g., above 50) to confirm upward momentum, and for short entries, it must be below a similar threshold. This helps filter out signals during overextended conditions.
Entry Conditions:
• Long Entry:
A long position is triggered when the current closing price exceeds the calculated long breakout level, the price is above the short-term EMA, and the RSI confirms momentum (e.g., above 50).
• Short Entry:
A short position is triggered when the closing price falls below the calculated short breakout level, the price is below the EMA, and the RSI confirms momentum (e.g., below 50).
Risk Management:
• Position Sizing:
Trades are sized to risk a fixed percentage of account equity (set here to 5% per trade in the code, with each trade’s stop loss defined so that risk is limited to approximately 2% of the entry price).
• Stop Loss & Take Profit:
A stop loss is placed a fixed ATR multiple away from the entry price, and a take profit target is set to achieve a 1:2 risk-reward ratio.
• Realistic Backtesting:
The strategy is backtested using an initial capital of $10,000, with a commission of 0.1% per trade and slippage of 1 tick per bar—parameters chosen to reflect conditions faced by the average trader.
Important Disclaimers:
• No Look-Ahead Bias:
All breakout levels are calculated using only past data (excluding the current bar) to ensure that the strategy does not “peek” into future data.
• Educational Purpose:
This strategy is experimental and provided solely for educational purposes. Past performance is not indicative of future results.
• User Responsibility:
Traders should thoroughly backtest and paper trade the strategy under various market conditions and adjust parameters to fit their own risk tolerance and trading style before live deployment.
Conclusion:
By integrating volatility-based breakout signals with trend and momentum filters, the Volatility Momentum Breakout Strategy offers a unique method to capture significant price moves in a disciplined manner. This publication provides a transparent explanation of the strategy’s components and realistic backtesting parameters, making it a useful tool for educational purposes and further customization by the TradingView community.
Kalman FilterKalman Filter Indicator Description
This indicator applies a Kalman Filter to smooth the selected price series (default is the close) and help reveal the underlying trend by filtering out market noise. The filter is based on a recursive algorithm consisting of two main steps:
Prediction Step:
The filter predicts the next state using the last estimated value and increases the uncertainty (error covariance) by adding the process noise variance (Q). This step assumes that the price follows a random walk, where the last known estimate is the best guess for the next value.
Update Step:
The filter computes the Kalman Gain, which determines the weight given to the new measurement (price) versus the prediction. It then updates the state estimate by combining the prediction with the measurement error (using the measurement noise variance, R). The error covariance is also updated accordingly.
Key Features:
Customizable Input:
Source: Choose any price series (default is the closing price) for filtering.
Measurement Noise Variance (R): Controls the sensitivity to new measurements (default is 0.1). A higher R makes the filter less responsive.
Process Noise Variance (Q): Controls the assumed level of inherent price variability (default is 0.01). A higher Q allows the filter to adapt more quickly to changes.
Visual Trend Indication:
The filtered trend line is plotted directly on the chart:
When enabled, the line is colored green when trending upward and red when trending downward.
If color option is disabled, the line appears in blue.
This indicator is ideal for traders looking to smooth price data and identify trends more clearly by reducing the impact of short-term volatility.
Daily Bubble Risk AdjustmentThis script calculates the ratio of the asset's closing price to its 20-week moving average (20W MA) and visualizes it as a color-coded line chart. The script also includes a customizable moving average (default: 111-day MA) to help smooth the ratio trend.
It identifies overbought and oversold conditions relative to the 20W MA, making it a valuable tool for long-term trend analysis.
High-Probability IndicatorExplanation of the Code
Trend Filter (EMA):
A 50-period Exponential Moving Average (EMA) is used to determine the overall trend.
trendUp is true when the price is above the EMA.
trendDown is true when the price is below the EMA.
Momentum Filter (RSI):
A 14-period RSI is used to identify overbought and oversold conditions.
oversold is true when RSI ≤ 30.
overbought is true when RSI ≥ 70.
Volatility Filter (ATR):
A 14-period Average True Range (ATR) is used to measure volatility.
ATR is multiplied by a user-defined multiplier (default: 2.0) to set a volatility threshold.
Ensures trades are only taken during periods of sufficient volatility.
Entry Conditions:
Long Entry: Price is above the EMA (uptrend), RSI is oversold, and the candle range exceeds the ATR threshold.
Short Entry: Price is below the EMA (downtrend), RSI is overbought, and the candle range exceeds the ATR threshold.
Exit Conditions:
Take Profit: A fixed percentage above/below the entry price.
Stop Loss: A fixed percentage below/above the entry price.
Visualization:
The EMA is plotted on the chart.
Background colors highlight uptrends and downtrends.
Buy and sell signals are displayed as labels on the chart.
Alerts:
Alerts are triggered for buy and sell signals.
How to Use the Indicator
Trend Filter:
Only take trades in the direction of the trend (e.g., long in an uptrend, short in a downtrend).
Momentum Filter:
Look for oversold conditions in an uptrend for long entries.
Look for overbought conditions in a downtrend for short entries.
Volatility Filter:
Ensure the candle range exceeds the ATR threshold to avoid low-volatility trades.
Risk Management:
Use the built-in take profit and stop loss levels to manage risk.
Optimization Tips
Backtesting:
Test the indicator on multiple timeframes and assets to evaluate its performance.
Adjust the input parameters (e.g., EMA length, RSI length, ATR multiplier) to optimize for specific markets.
Combination with Other Strategies:
Add additional filters, such as volume analysis or support/resistance levels, to improve accuracy.
Risk Management:
Use proper position sizing and risk-reward ratios to maximize profitability.
Disclaimer
No indicator can guarantee an 85% win ratio due to the inherent unpredictability of financial markets. This script is provided for educational purposes only. Always conduct thorough backtesting and paper trading before using any strategy in live trading.
Let me know if you need further assistance or enhancements!
High Volume Time (HVT) Auto-DisplayThis Indicator displays the upcoming HVT for the NasDaq on a table. The HVT is also displayed on the chart in real-time in order to help accentuate the best times to trade and a clear picture for the daily directional move. This times were found manually and bear as much significance as I bring it to have. These are not guaranteed times for the market to move, but rather High Probability Times based on my own backtesting on NQ.
Average Price in Time PeriodsThis Pine Script calculates and displays average prices for two specific time ranges during a trading day: from 09:00 to 22:30 and from 22:30 to 09:00. It updates the average prices by summing the closing prices in each time frame and then plots them as green and red lines, respectively. The script also displays black lines outside these specific time ranges to prevent "gaps" in the chart during off-peak hours. The displayed lines are dynamically adjusted based on the current time, with the green line for 09:00-22:30 and the red line for 22:30-09:00.
Daily COC Strategy with SHERLOCK WAVESThis indicator implements a unique trading strategy known as the "Daily COC (Candle Over Candle) Strategy" enhanced with "SHERLOCK WAVES" for pattern recognition. It's designed for traders looking to capitalize on specific candlestick formations with a negative risk-reward ratio, with the aim of achieving a high win rate (over 70%) through numerous trading opportunities, despite each trade having a higher risk relative to the reward.
Key Features:
Pattern Recognition: Identifies a setup based on three consecutive candles - a red candle followed by a shooting star, then an entry candle that does not break below the shooting star's low.
Negative Risk/Reward Trade Selection: Focuses on entries where the potential stop loss is greater than the take profit, banking on a high win rate to offset the individual trade's negative risk-reward ratio.
Visual Signals:
Green Label: Marks potential entry points at the high of the candle before the entry.
Green Dot: Indicates a winning trade closure.
Red Dot: Signals a losing trade closure.
Blue Circle: Warns when the current candle is within 2% of breaking above the previous candle's high, suggesting a potential setup is developing.
Green Circle: Plots the take profit level.
Red Circle: Plots the stop loss level.
Dynamic Statistics: A live updating label showing the number of trades, wins, losses, open trades, current account balance, and win percentage.
Customizable Parameters:
Risk % per Trade: Adjust the percentage of your account balance you're willing to risk on each trade.
Initial Account Balance: Set your starting balance for tracking performance.
Start Date for Strategy: Define when the strategy should start calculating from, allowing for backtesting.
Alerts:
An alert condition is set for when a potential trade setup is developing, helping traders prepare for entries.
Usage Tips:
This strategy is predicated on the idea that a high win rate can compensate for the negative risk-reward ratio of individual trades. It might not suit all market conditions or traders' risk profiles.
Use this strategy in conjunction with other analysis methods to validate trade setups.
Note: Always backtest thoroughly before applying to live markets. Consider this tool as part of a broader trading strategy, not a standalone solution. Monitor your win rate and adjust your risk management accordingly to ensure the strategy remains profitable over time.
This description now correctly explains the purpose behind the negative risk-reward ratio in the context of your trading strategy.
Auto Last Earnings AVWAP
This script provides an automated approach to tracking critical post-earnings price levels. You can add it to a chart and then flip through your watchlist to see the anchored AVWAPs without the need to do it manually one by one.
Core Features:
Automatically detects earnings dates and anchors VWAP calculations without manual input
Calculates volume-weighted average price specifically from the last earnings release
Identifies and visualizes significant earnings gaps between reporting periods
Volume-Based Signal Detection:
Monitors VWAP crosses with volume confirmation (requires 1.5x normal volume)
Labels high-volume breakouts with clear directional signals
Uses a 6-bar adaptive volume baseline to filter out noise
Practical Applications:
AVWAP anchored at earnings offers a great price support level that should be considered when deciding to buy/sell the stock. This script eliminates manual VWAP anchoring and reduces chart management time
Key Differentiators:
First note: coding VWAP anchoring in pine is more challenging that one would think. The source code is open to help other users and hopefully inspire different applications.
No need to manually anchor the VWAP
Draws earnings gap from earnings to earnings (if auto mode)
Detects breakouts through the AVWAP line
Multi-Timeframe RSI Grid Strategy with ArrowsKey Features of the Strategy
Multi-Timeframe RSI Analysis:
The strategy calculates RSI values for three different timeframes:
The current chart's timeframe.
Two higher timeframes (configurable via higher_tf1 and higher_tf2 inputs).
It uses these RSI values to identify overbought (sell) and oversold (buy) conditions.
Grid Trading System:
The strategy uses a grid-based approach to scale into trades. It adds positions at predefined intervals (grid_space) based on the ATR (Average True Range) and a grid multiplication factor (grid_factor).
The grid system allows for pyramiding (adding to positions) up to a maximum number of grid levels (max_grid).
Daily Profit Target:
The strategy has a daily profit target (daily_target). Once the target is reached, it closes all open positions and stops trading for the day.
Drawdown Protection:
If the open drawdown exceeds 2% of the account equity, the strategy closes all positions to limit losses.
Reverse Signals:
If the RSI conditions reverse (e.g., from buy to sell or vice versa), the strategy closes all open positions and resets the grid.
Visualization:
The script plots buy and sell signals as arrows on the chart.
It also plots the RSI values for the current and higher timeframes, along with overbought and oversold levels.
How It Works
Inputs:
The user can configure parameters like RSI length, overbought/oversold levels, higher timeframes, grid spacing, lot size multiplier, maximum grid levels, daily profit target, and ATR length.
RSI Calculation:
The RSI is calculated for the current timeframe and the two higher timeframes using ta.rsi().
Grid System:
The grid system uses the ATR to determine the spacing between grid levels (grid_space).
When the price moves in the desired direction, the strategy adds positions at intervals of grid_space, increasing the lot size by a multiplier (lot_multiplier) for each new grid level.
Entry Conditions:
A buy signal is generated when the RSI is below the oversold level on all three timeframes.
A sell signal is generated when the RSI is above the overbought level on all three timeframes.
Position Management:
The strategy scales into positions using the grid system.
It closes all positions if the daily profit target is reached or if a reverse signal is detected.
Visualization:
Buy and sell signals are plotted as arrows on the chart.
RSI values for all timeframes are plotted, along with overbought and oversold levels.
Example Scenario
Suppose the current RSI is below 30 (oversold), and the RSI on the 60-minute and 240-minute charts is also below 30. This triggers a buy signal.
The strategy enters a long position with a base lot size.
If the price moves against the position by grid_space, the strategy adds another long position with a larger lot size (scaled by lot_multiplier).
This process continues until the maximum grid level (max_grid) is reached or the daily profit target is achieved.
Key Variables
grid_level: Tracks the current grid level (number of positions added).
last_entry_price: Tracks the price of the last entry.
base_size: The base lot size for the initial position.
daily_profit_target: The daily profit target in percentage terms.
target_reached: A flag to indicate whether the daily profit target has been achieved.
Potential Use Cases
This strategy is suitable for traders who want to combine RSI-based signals with a grid trading approach to capitalize on mean-reverting price movements.
It can be used in trending or ranging markets, depending on the RSI settings and grid parameters.
Limitations
The grid trading system can lead to significant drawdowns if the market moves strongly against the initial position.
The strategy relies heavily on RSI, which may produce false signals in strongly trending markets.
The daily profit target may limit potential gains in highly volatile markets.
Customization
You can adjust the input parameters (e.g., RSI length, overbought/oversold levels, grid spacing, lot multiplier) to suit your trading style and market conditions.
You can also modify the drawdown protection threshold or add additional filters (e.g., volume, moving averages) to improve the strategy's performance.
In summary, this script is a sophisticated trading strategy that combines RSI-based signals with a grid trading system to manage entries, exits, and position sizing. It includes features like daily profit targets, drawdown protection, and multi-timeframe analysis to enhance its robustnes
[COG]MTF RZP Heatmap MTF RZP Heatmap (Range Zone Pulse)
What It Does
This indicator creates three visual heatmaps that show how current price movement compares to the average range of different timeframes. It helps traders:
Identify when price moves are overextended
Compare momentum across different timeframes
Spot potential reversal points
Understand the relative strength of price movements
How It Works
Range Calculation:
For each selected timeframe, it calculates an average range based on the specified number of periods
The range is measured from high to low for each period
A moving average of these ranges creates a dynamic "normal" range for that timeframe
Position Calculation:
Measures how far price has moved from the period's opening price
Compares this movement to the average range
Converts the movement into a percentage (-100% to +100%)
Visual Display:
Shows three vertical heatmaps, one for each timeframe
Colors graduate from bearish (typically red) to bullish (typically green)
A dot indicator shows the current position within each range
Percentage labels show exact movement relative to average range
Trading Applications
Trend Trading:
Multiple timeframes aligned in the same color suggest strong trend
Use larger timeframes (Daily/Weekly) for trend direction
Use smaller timeframes (4H/1H) for entry timing
Mean Reversion:
Extreme readings (near +100% or -100%) suggest overextended moves
Look for divergences between timeframes
Use when shorter timeframes show extremes but larger timeframes don't
Volatility Trading:
Compare current moves to average ranges
Identify when markets are more volatile than usual
Adjust position sizes based on range expansion/contraction
Multi-Timeframe Analysis:
Compare price action across different time horizons
Identify conflicting signals between timeframes
Use for timeframe alignment in trading decisions
Best Practices for Usage
Timeframe Selection:
Set the first timeframe to your trading timeframe
Set the second timeframe to your trend timeframe
Set the third timeframe to your entry timeframe
Range Period Settings:
Default is 5 periods
Increase for more stable readings
Decrease for more responsive readings
Color Interpretation:
Darker colors indicate stronger moves
Look for alignment across timeframes
Watch for extremes in any timeframe
Trading Setups:
Wait for alignment in multiple timeframes
Use extreme readings for counter-trend trades
Combine with other indicators for confirmation
AllDay Session TimesIndicator: Custom Session Times
This indicator is designed to assist traders by visualizing specific trading session times on the TradingView platform. It highlights two important trading sessions: the Day Session and the Evening Session, providing a visual aid that helps traders navigate the markets with greater accuracy.
Day Session Time Range:
Starts: 10:55 UTC+2
Ends: 13:30 UTC+2
Evening Session Time Range:
Starts: 16:55 UTC+2
Ends: 18:30 UTC+2
How It Works:
Colors and Backgrounds: This indicator uses background colors to differentiate the sessions. The green background appears during the Day Session, while the blue background indicates the Evening Session.
Lines: Session time ranges are also marked with clear lines on the chart, making it easier to identify the specific session periods.
Time Zone: The time zone is set to UTC+2 (Europe/Helsinki), but it can easily be adjusted to match your local time zone.
Why Use This Indicator?
This indicator is especially useful for traders who focus on specific market sessions. For example:
The Day Session might be when the market is more active, and trends are clearer.
The Evening Session could be a good time to observe market adjustments based on the events of the day and find potential trading opportunities.
By visualizing these specific time frames, the indicator helps reduce distractions and enables a more focused approach to trading.
Use Cases:
This indicator is ideal for:
Day traders and swing traders who want to focus on certain market sessions.
Technical analysts who prefer to visualize market behavior within specific time frames.
Strategy optimization and a more precise assessment of market conditions.
Features:
Visual session markers that help traders focus on key trading periods.
Easy customization of time zone and session time ranges.
Background colors and lines that improve chart readability and session tracking.
Made By AllDayEsa
Buy/Sell Break and RetestThis script is a Pine Script indicator for TradingView titled **"Buy/Sell Break and Retest"**. Here's a description of its functionality:
### Purpose:
The script identifies potential **buy** and **sell entry levels** based on break-and-retest patterns in the market. It works by analyzing higher timeframe data (e.g., 1-hour) and marking entries on a lower timeframe (e.g., 1-minute).
### Key Features:
1. **Configurable Timeframes**:
- `Analysis Timeframe`: Used for identifying break-and-retest signals (default: 1-hour).
- `Entry Timeframe`: Used for marking and plotting entries (default: 1-minute).
2. **Buy and Sell Signals**:
- A **sell entry** is triggered when a bearish candle (close < open) is identified in the analysis timeframe.
- A **buy entry** is triggered when a bullish candle (close > open) is identified in the analysis timeframe.
3. **Retest Logic**:
- For sell signals: The retest is validated when the price breaks below the identified sell level.
- For buy signals: The retest is validated when the price breaks above the identified buy level.
4. **Visual Indicators**:
- Entry levels are marked with labels:
- **Buy Entry**: Green labels are placed at bullish candle opens.
- **Sell Entry**: Red labels are placed at bearish candle closes.
- Plots the levels for easy reference:
- **Sell Level**: Displayed as red circles on the chart.
- **Buy Level**: Displayed as green circles on the chart.
5. **Dynamic Updates**:
- Levels are cleared when invalidated by the price action.
### Use Case:
This indicator helps traders spot break-and-retest opportunities by:
- Allowing higher timeframe analysis to determine trend direction and key levels.
- Providing actionable buy and sell entry points on lower timeframes for precision.
Let me know if you'd like further clarification or improvements!
Global Relevant Events MarkerThe Global Relevant Events Marker script is designed to mark significant global events on a chart, such as economic crises or major geopolitical events. It uses vertical lines to indicate the exact dates of these events and places labels (optional) near the lines to provide a description of the event.
Vertical & Open Lines - Yearly [MsF]Yearly Vertical & Open Lines Indicator
This indicator helps traders visualize yearly boundaries and track previous year's price levels. It draws:
- Vertical lines at the start of each year
- Horizontal lines showing previous year's open and close prices
- Optional labels with price information
Features:
- Customizable line colors and styles
- Toggle yearly vertical lines
- Show/hide previous year's price levels
- Optional price labels
- Next year line preview
Usage:
1. Add indicator to your chart
2. Adjust Base Time to match your market's yearly reset time
3. Customize colors and styles using input options
4. Toggle features as needed
Countdown Candle RRS// Countdown Candle RRS Indicator
//
// This indicator displays a countdown timer for the current candle on the chart.
// It shows the remaining time until the current candle closes, providing traders
// with a visual reference for time-based decision making.
//
// Features:
// - Customizable countdown display (size, position, and color)
// - Adapts to different timeframes (daily, hourly, and minute-based)
// - Displays time in appropriate format based on the chart timeframe
// - Daily or higher: XdHH:MM:SS (e.g., 2d05:30:15)
// - Hourly: HH:MM:SS
// - Minute or lower: MM:SS
// - Updates in real-time on the last candle
//
// Usage:
// - Add this indicator to your chart to see the countdown timer
// - Use the input options to customize the appearance and position of the timer
// - The timer will update on each tick, showing the time remaining until the current candle closes
//
// Note: This indicator is particularly useful for traders who need precise timing
// for entry or exit decisions, especially in fast-moving markets or when using
// specific time-based strategies.
//
// Author: reza rashidi
// Version: 1.0
Internal Bar Strength (IBS) Strategy█ STRATEGY DESCRIPTION
The "Internal Bar Strength (IBS) Strategy" is a mean-reversion strategy designed to identify trading opportunities based on the closing price's position within the daily price range. It enters a long position when the IBS indicates oversold conditions and exits when the IBS reaches overbought levels. This strategy was designed to be used on the daily timeframe.
█ WHAT IS INTERNAL BAR STRENGTH (IBS)?
Internal Bar Strength (IBS) measures where the closing price falls within the high-low range of a bar. It is calculated as:
IBS = (Close - Low) / (High - Low)
- **Low IBS (≤ 0.2)**: Indicates the close is near the bar's low, suggesting oversold conditions.
- **High IBS (≥ 0.8)**: Indicates the close is near the bar's high, suggesting overbought conditions.
█ SIGNAL GENERATION
1. LONG ENTRY
A Buy Signal is triggered when:
The IBS value drops below the Lower Threshold (default: 0.2).
The signal occurs within the specified time window (between `Start Time` and `End Time`).
2. EXIT CONDITION
A Sell Signal is generated when the IBS value rises to or above the Upper Threshold (default: 0.8). This prompts the strategy to exit the position.
█ ADDITIONAL SETTINGS
Upper Threshold: The IBS level at which the strategy exits trades. Default is 0.8.
Lower Threshold: The IBS level at which the strategy enters long positions. Default is 0.2.
Start Time and End Time: The time window during which the strategy is allowed to execute trades.
█ PERFORMANCE OVERVIEW
This strategy is designed for ranging markets and performs best when prices frequently revert to the mean.
It is sensitive to extreme IBS values, which help identify potential reversals.
Backtesting results should be analyzed to optimize the Upper/Lower Thresholds for specific instruments and market conditions.
Buy on 5 day low Strategy█ STRATEGY DESCRIPTION
The "Buy on 5 Day Low Strategy" is a mean-reversion strategy designed to identify potential buying opportunities when the price drops below the lowest low of the previous five days. It enters a long position when specific conditions are met and exits when the price exceeds the high of the previous day. This strategy is optimized for use on daily or higher timeframes.
█ WHAT IS THE 5-DAY LOW?
The 5-Day Low is the lowest price observed over the last five days. This level is used as a reference to identify potential oversold conditions and reversal points.
█ SIGNAL GENERATION
1. LONG ENTRY
A Buy Signal is triggered when:
The close price is below the lowest low of the previous five days (`close < _lowest `).
The signal occurs within the specified time window (between `Start Time` and `End Time`).
2. EXIT CONDITION
A Sell Signal is generated when the current closing price exceeds the high of the previous day (`close > high `). This indicates that the price has shown strength, potentially confirming the reversal and prompting the strategy to exit the position.
█ ADDITIONAL SETTINGS
Start Time and End Time: The time window during which the strategy is allowed to execute trades.
█ PERFORMANCE OVERVIEW
This strategy is designed for mean-reverting markets and performs best when the price frequently oscillates around key support levels.
It is sensitive to oversold conditions, as indicated by the 5-Day Low, and overbought conditions, as indicated by the previous day's high.
Backtesting results should be analyzed to optimize the strategy for specific instruments and market conditions.
Bollinger Bands Reversal + IBS Strategy█ STRATEGY DESCRIPTION
The "Bollinger Bands Reversal Strategy" is a mean-reversion strategy designed to identify potential buying opportunities when the price deviates below the lower Bollinger Band and the Internal Bar Strength (IBS) indicates oversold conditions. It enters a long position when specific conditions are met and exits when the IBS indicates overbought conditions. This strategy is suitable for use on various timeframes.
█ WHAT ARE BOLLINGER BANDS?
Bollinger Bands consist of three lines:
- **Basis**: A Simple Moving Average (SMA) of the price over a specified period.
- **Upper Band**: The basis plus a multiple of the standard deviation of the price.
- **Lower Band**: The basis minus a multiple of the standard deviation of the price.
Bollinger Bands help identify periods of high volatility and potential reversal points.
█ WHAT IS INTERNAL BAR STRENGTH (IBS)?
Internal Bar Strength (IBS) is a measure of where the closing price is relative to the high and low of the bar. It is calculated as:
IBS = (Close - Low) / (High - Low)
A low IBS value (e.g., below 0.2) indicates that the close is near the low of the bar, suggesting oversold conditions. A high IBS value (e.g., above 0.8) indicates that the close is near the high of the bar, suggesting overbought conditions.
█ SIGNAL GENERATION
1. LONG ENTRY
A Buy Signal is triggered when:
The IBS value is below 0.2, indicating oversold conditions.
The close price is below the lower Bollinger Band.
The signal occurs within the specified time window (between `Start Time` and `End Time`).
2. EXIT CONDITION
A Sell Signal is generated when the IBS value exceeds 0.8, indicating overbought conditions. This prompts the strategy to exit the position.
█ ADDITIONAL SETTINGS
Length: The lookback period for calculating the Bollinger Bands. Default is 20.
Multiplier: The number of standard deviations used to calculate the upper and lower Bollinger Bands. Default is 2.0.
Start Time and End Time: The time window during which the strategy is allowed to execute trades.
█ PERFORMANCE OVERVIEW
This strategy is designed for mean-reverting markets and performs best when the price frequently deviates from the Bollinger Bands.
It is sensitive to oversold and overbought conditions, as indicated by the IBS, which helps to identify potential reversals.
Backtesting results should be analyzed to optimize the Length and Multiplier parameters for specific instruments.
Turn of the Month Strategy on Steroids█ STRATEGY DESCRIPTION
The "Turn of the Month Strategy on Steroids" is a seasonal mean-reversion strategy designed to capitalize on price movements around the end of the month. It enters a long position when specific conditions are met and exits when the Relative Strength Index (RSI) indicates overbought conditions. This strategy is optimized for use on daily or higher timeframes.
█ WHAT IS THE TURN OF THE MONTH EFFECT?
The Turn of the Month effect refers to the observed tendency of stock prices to rise around the end of the month. This strategy leverages this phenomenon by entering long positions when the price shows signs of a reversal during this period.
█ SIGNAL GENERATION
1. LONG ENTRY
A Buy Signal is triggered when:
The current day of the month is greater than or equal to the specified `dayOfMonth` threshold (default is 25).
The close price is lower than the previous day's close (`close < close `).
The previous day's close is also lower than the close two days ago (`close < close `).
The signal occurs within the specified time window (between `Start Time` and `End Time`).
There is no existing open position (`strategy.position_size == 0`).
2. EXIT CONDITION
A Sell Signal is generated when the 2-period RSI exceeds 65, indicating overbought conditions. This prompts the strategy to exit the position.
█ ADDITIONAL SETTINGS
Day of Month: The day of the month threshold for triggering a Buy Signal. Default is 25.
Start Time and End Time: The time window during which the strategy is allowed to execute trades.
█ PERFORMANCE OVERVIEW
This strategy is designed to exploit seasonal price patterns around the end of the month.
It performs best in markets where the Turn of the Month effect is pronounced.
Backtesting results should be analyzed to optimize the `dayOfMonth` threshold and RSI parameters for specific instruments.
Rosiz Support 2### **Indicator Name**: Custom RSI, Stochastic, and ADX
### **Description**:
This is a multi-functional indicator that combines three popular technical analysis tools—**RSI (Relative Strength Index)**, **Stochastic Oscillator**, and **ADX (Average Directional Index)**—into a single, customizable pane. This indicator helps traders analyze momentum, overbought/oversold conditions, and trend strength simultaneously, making it a powerful tool for making informed trading decisions.
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### **Features**:
1. **RSI (Relative Strength Index)**:
- Measures the speed and change of price movements.
- Helps identify overbought (>70) and oversold (<30) conditions.
- Includes customizable length and source options.
- Background shading visually highlights overbought and oversold zones.
2. **Stochastic Oscillator**:
- Determines momentum by comparing a security's closing price to its price range over a specific period.
- Includes %K and %D lines for crossovers, which signal potential entry or exit points.
- Highlights overbought (>80) and oversold (<20) zones with background fill.
3. **ADX (Average Directional Index)**:
- Measures trend strength (higher values indicate stronger trends).
- Includes customizable smoothing and DI (Directional Indicator) length.
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### **How to Use**:
- **RSI**: Look for overbought or oversold conditions for potential reversal points. Divergences between price and RSI may signal weakening trends.
- **Stochastic Oscillator**: Watch for %K and %D crossovers near overbought or oversold zones to confirm buy or sell signals.
- **ADX**: Use ADX values to assess trend strength:
- **ADX > 25**: Strong trend.
- **ADX < 20**: Weak or ranging market.
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### **Customization Options**:
- **RSI Settings**: Adjust length, source, and visual parameters.
- **Stochastic Settings**: Modify %K and %D lengths and smoothing factors.
- **ADX Settings**: Fine-tune smoothing and directional index lengths.
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### **Advantages**:
- Combines three indicators into one, reducing chart clutter.
- Customizable inputs for flexibility in various trading strategies.
- Visual enhancements (background fills and lines) for better readability.
This indicator is perfect for traders looking to combine momentum analysis, overbought/oversold signals, and trend strength in a single tool!
Month Separator
Month Separator Indicator
This Pine Script indicator separates each month on the chart by visually marking the change between months.
Features:
The indicator detects when the month changes.
It highlights the background with a semi-transparent blue color to differentiate the months.
A small red triangle is plotted at the top of the chart at the beginning of each new month, providing a clear visual cue.
Customization:
You can easily adjust the colors or styles in the script by modifying the bgcolor and plotshape functions.
The indicator works on all timeframes, but it is especially useful on higher timeframes (like daily or weekly charts) to track monthly transitions.
This script is ideal for traders who want a clear visual representation of month boundaries to analyze trends and key levels more effectively.
Ultra Disparity IndexGain insights into price movements across multiple timeframes with the Ultra Disparity Index . This indicator highlights overbought/oversold levels based on price disparities from moving averages.
Introduction
The Ultra Disparity Index is designed for traders who seek a deeper understanding of price movements and trends across various timeframes. By analyzing the disparity between the current price and its moving averages, the indicator helps identify overbought and oversold conditions.
Detailed Description
The indicator works by calculating the percentage difference between the current price and its moving averages over four user-defined lengths. It operates on multiple timeframes monthly, weekly, daily, 4-hour, and 1-hour giving traders a comprehensive view of market dynamics.
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Disparity Calculation
The indicator computes how far the current price is from moving averages to reveal the degree of disparity.
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Overbought/Oversold Zones
By normalizing disparities into percentages relative to the overbought/oversold range, the indicator represents overbought (100%) and oversold (-100%).
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Timeframe Flexibility
The user can visualize data from monthly to hourly intervals, ensuring adaptability to different trading strategies.
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Customizable Inputs
Users can configure moving average lengths and toggle visibility for specific timeframes and levels.
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Summary
The indicator uses simple moving averages (SMAs) as a benchmark for calculating disparity. This disparity is then analyzed using statistical tools, such as standard deviation, to derive meaningful levels. Finally, the results are visualized in a table, providing traders with an easy-to-read summary of disparity values and their respective normalized percentages.
