TICK Charting & DivergencesOverview
The TICK index measures the number of NYSE stocks making an uptick versus a downtick. This indicator identifies divergences between price action and TICK readings, potentially signaling trend reversals.
Key Features
Real-time TICK monitoring during market hours (9:30 AM - 4:00 PM ET)
Customizable smoothing factor for TICK values
Regular and hidden divergences detection
Reference lines at ±500 and ±1000 levels
Current TICK value display
TICK Internals Interpretation
Above +1000: Strong buying pressure, potential exhaustion
Above +500: Moderate buying pressure
Below -500: Moderate selling pressure
Below -1000: Strong selling pressure, potential exhaustion
Best Practices
Use in conjunction with support/resistance levels, market trend direction, and time of day.
Higher probability setups with multiple timeframe confirmation, divergence at key price levels, and extreme TICK readings (±1000).
Settings Optimization
Smoothing Factor: 1-3 (lower for faster signals)
Pivot Lookback: 5-10 bars (adjust based on timeframe)
Range: 5-60 bars (wider for longer-term signals)
Warning Signs
Multiple failed divergences
Choppy price action
Low volume periods
Major news events pending
Remember: TICK divergences are not guaranteed signals. Always use proper risk management and combine with other technical analysis tools.
Поиск скриптов по запросу "股价站上60月线"
Nimu Market on DemandNimu Market On Demand is an innovative tool designed to provide a visual representation of market demand levels on a scale of 1 to 100. This scale is displayed at specific intervals , making it easy for users to understand market demand fluctuations in real time.
To enhance analysis, Nimu Market On Demand also incorporates the Relative Strength Index (RSI) with key thresholds at . RSI is a widely-used technical indicator that measures market strength and momentum, offering insights into overbought (excessive buying) or oversold (excessive selling) conditions.
The combination of the Demand graph and RSI enables users to:
Identify the right time to buy when the RSI falls below 30, signaling an oversold condition.
Determine the optimal time to sell when the RSI rises above 70, indicating an overbought condition.
With an integrated visualization, users can effortlessly observe demand patterns and combine them with RSI signals to make smarter and more strategic trading decisions. This tool is designed to help traders and investors maximize opportunities in a dynamic market environment.
EMA Crossover with RSI and DistanceEMA Crossover with RSI and Distance Strategy
This strategy combines Exponential Moving Averages (EMA) with Relative Strength Index (RSI) and distance-based conditions to generate buy, sell, and neutral signals. It is designed to help traders identify entry and exit points based on multiple technical indicators.
Key Components:
Exponential Moving Averages (EMA):
The strategy uses four EMAs: EMA 5, EMA 13, EMA 40, and EMA 55.
A buy signal (long) is triggered when EMA 5 crosses above EMA 13 and EMA 40 crosses above EMA 55.
A sell signal (short) is generated when EMA 55 crosses above EMA 40.
The distance between EMAs (5 and 13) is also important. If the current distance between EMA 5 and EMA 13 is smaller than the average distance over the last 5 candles, a neutral condition is triggered, preventing a signal even if all other conditions are met.
Relative Strength Index (RSI):
The 14-period RSI is used to determine market strength and direction.
The strategy requires RSI to be above 50 and greater than the average RSI (over the past 14 periods) for a buy signal.
If the RSI is above 60, a green signal is given, indicating a strong bullish condition, even if the EMA conditions are not fully met.
If the RSI is below 40, a red signal is given, indicating a strong bearish condition, regardless of the EMA crossover.
Distance Conditions:
The strategy calculates the distance between EMA 5 and EMA 13 on each candle and compares it to the average distance of the last 5 candles.
If the current distance between EMA 5 and EMA 13 is lower than the average of the last 5 candles, a neutral signal is triggered. This helps avoid entering a trade when the market is losing momentum.
Additionally, if the distance between EMA 40 and EMA 13 is greater than the previous distance, the previous signal is kept intact, ensuring that the trend is still strong enough for the signal to remain valid.
Signal Persistence:
Once a buy (green) or sell (red) signal is triggered, it remains intact as long as the price is closing above EMA 5 for long trades or below EMA 55 for short trades.
If the price moves below EMA 5 for long trades or above EMA 55 for short trades, the signal is recalculated based on the most recent conditions.
Signal Display:
Green Signals: Represent a strong buy signal and are shown below the candle when the RSI is above 60.
Red Signals: Represent a strong sell signal and are shown above the candle when the RSI is below 40.
Neutral Signals: Displayed when the conditions for entry are not met, specifically when the EMA distance condition is violated.
Long and Short Signals: Additional signals are shown based on the EMA crossovers and RSI conditions. These signals are plotted below the candle for long positions and above the candle for short positions.
Trade Logic:
Long Entry: Enter a long trade when EMA 5 crosses above EMA 13, EMA 40 crosses above EMA 55, and the RSI is above 50 and greater than the average RSI. Additionally, the current distance between EMA 5 and EMA 13 should be larger than the average distance of the last 5 candles.
Short Entry: Enter a short trade when EMA 55 crosses above EMA 40 and the RSI is below 40.
Neutral Condition: If the distance between EMA 5 and EMA 13 is smaller than the average distance over the last 5 candles, the strategy will not trigger a signal, even if other conditions are met.
Zero Lag Signals For Loop [QuantAlgo]Elevate your trend-following investing and trading strategy with Zero Lag Signals For Loop by QuantAlgo , a simple yet effective technical indicator that merges advanced zero-lag mechanism with adaptive trend analysis to bring you a fresh take on market momentum tracking. Its aim is to support both medium- to long-term investors monitoring broader market shifts and precision-focused traders seeking quality entries through its dual-focused analysis approach!
🟢 Core Architecture
The foundation of this indicator rests on its zero-lag implementation and dynamic trend assessment. By utilizing a loop-driven scoring system alongside volatility-based filtering, each market movement is evaluated through multiple historical lenses while accounting for current market conditions. This multi-layered approach helps differentiate between genuine trend movements and market noise across timeframe and asset classes.
🟢 Technical Foundation
Three distinct components of this indicator are:
Zero Lag EMA : An enhanced moving average calculation designed to minimize traditional lag effects
For Loop Scoring System : A comprehensive scoring mechanism that weighs current price action against historical contexts
Dynamic Volatility Analysis : A sophisticated ATR-based filter that adjusts signal sensitivity to market conditions
🟢 Key Features & Signals
The Zero Lag Signals For Loop provides market insights through:
Color-coded Zero Lag line that adapts to trend direction
Dynamic fills between price and Zero Lag basis for enhanced visualization
Trend change markers (L/S) that highlight potential reversal points
Smart bar coloring that helps visualize market momentum
Background color changes with vertical lines at significant trend shifts
Customizable alerts for both bullish and bearish reversals
🟢 Practical Usage Tips
Here's how you can get the most out of the Zero Lag Signals For Loop :
1/ Setup:
Add the indicator to your TradingView chart by clicking on the star icon to add it to your favorites ⭐️
Start with the default Zero Lag length for balanced sensitivity
Use the standard volatility multiplier for proper filtering
Keep the default loop range for comprehensive trend analysis
Adjust threshold levels based on your investing and/or trading style
2/ Reading Signals:
Watch for L/S markers - they indicate validated trend reversals
Pay attention to Zero Lag line color changes - they confirm trend direction
Monitor bar colors for additional trend confirmation
Configure alerts for trend changes in both bullish and bearish directions, ensuring you can act on significant technical developments promptly.
🟢 Pro Tips
Fine-tune the Zero Lag length based on your timeframe:
→ Lower values (20-40) for more responsive signals
→ Higher values (60-100) for stronger trend confirmation
Adjust volatility multiplier based on market conditions:
→ Increase multiplier in volatile markets
→ Decrease multiplier in stable trending markets
Combine with:
→ Volume analysis for trade validation
→ Multiple timeframe analysis for broader context
→ Other technical tools for comprehensive analysis
ForecastPro by BinhMyco1. Overview:
This Pine Script implements a custom forecasting tool on TradingView, labeled "BinhMyco." It provides a method to predict future price movements based on historical data and a comparison with similar historical patterns. The script supports two types of forecasts: **Prediction** and **Replication**, where the forecasted price can be either based on price peaks/troughs or an average direction. The script also calculates a confidence probability, showing how closely the forecasted data aligns with historical trends.
2. Inputs:
- Source (`src`): The input data source for forecasting, which defaults to `open`.
- Length (`len`): The length of the training data used for analysis (fixed at 200).
- Reference Length (`leng`): A fixed reference length for comparing similar historical patterns (set to 70).
- Forecast Length (`length`): The length of the forecast period (fixed at 60).
- Multiplier (`mult`): A constant multiplier for the forecast confidence cone (set to 4.0).
- Forecast Type (`typ`): Type of forecast, either **Prediction** or **Replication**.
- Direction Type (`dirtyp`): Defines how the forecast is calculated — either based on price **peaks/troughs** or an **average direction**.
- Forecast Divergence Cone (`divcone`): A boolean option to enable the display of a confidence cone around the forecast.
3. Color Constants:
- Green (`#00ffbb`): Color used for upward price movements.
- Red (`#ff0000`): Color used for downward price movements.
- Reference Data Color (`refcol`): Blue color for the reference data.
- Similar Data Color (`simcol`): Orange color for the most similar data.
- Forecast Data Color (`forcol`): Yellow color for forecasted data.
4. Error Checking:
- The script checks if the reference length is greater than half the training data length, and if the forecast length exceeds the reference length, raising errors if either condition is true.
5. Arrays for Calculation:
- Correlation Array (`c`): Holds the correlation values between the data source (`src`) and historical data points.
- Index Array (`index`): Stores the indices of the historical data for comparison.
6. Forecasting Logic:
- Correlation Calculation: The script calculates the correlation between the historical data (`src`) and the reference data over the given reference length. It then identifies the point in history most similar to the current data.
- Forecast Price Calculation: Based on the type of forecast (Prediction or Replication), the script calculates future prices either by predicting based on similar bars or by replicating past data. The forecasted prices are stored in the `forecastPrices` array.
- Forecast Line Drawing: The script draws lines to represent the forecasted price movements. These lines are color-coded based on whether the forecasted price is higher or lower than the current price.
7. Divergence Cone (Optional):
- If the **divcone** option is enabled, the script calculates and draws a confidence cone around the forecasted prices. The upper and lower bounds of the cone are calculated using a standard deviation factor, providing a visual representation of forecast uncertainty.
8. Probability Table:
- A table is displayed on the chart, showing the probability of the forecast being accurate. This probability is calculated using the correlation between the current data and the most similar historical pattern. If the probability is positive, the table background turns green; if negative, it turns red. The probability is presented as a percentage.
9. Key Functions:
- `highest_range` and `lowest_range`: Functions to find the highest and lowest price within a range of bars.
- `ftype`: Determines the forecast type (Prediction or Replication) and adjusts the forecasting logic accordingly.
- `ftypediff`: Computes the difference between the forecasted and actual prices based on the selected forecast type.
- `ftypelim`, `ftypeleft`, `ftyperight`: Additional functions to adjust the calculation of the forecast based on the forecast type.
10. Conclusion:
The "ForecastPro" script is a unique tool for forecasting future price movements on TradingView. It compares historical price data with similar historical trends to generate predictions. The script also offers a customizable confidence cone and displays the probability of the forecast's accuracy. This tool provides traders with valuable insights into future price action, potentially enhancing decision-making in trading strategies.
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This script provides advanced functionality for traders who wish to explore price forecasting, and can be customized to fit various trading styles.
[blackcat] L2 Six Round Positioning█ OVERVIEW
The script is an indicator designed to plot the direction (up, down, no change) of several moving averages (MA) on a separate chart, without overlaying the price data. It calculates Simple Moving Averages (SMA) for 3, 5, 8, 34, 60, 120, and 250 periods and uses conditional logic to determine the color and position of the plotted columns based on whether each MA is increasing, decreasing, or unchanged.
█ LOGICAL FRAMEWORK
The script is structured into three main sections:
1 — Input Parameters: None explicitly defined, but the script uses default settings for the indicator function.
2 — Calculations: Computes Simple Moving Averages (SMA) for seven different periods.
3 — Plotting: Uses conditional logic to plot columns representing the direction of each MA, with positions and colors indicating whether the MA is increasing, decreasing, or unchanged.
The flow of data is straightforward: the script calculates the SMAs, determines their direction, sets the appropriate color, and then plots the columns.
█ CUSTOM FUNCTIONS
• No custom functions are defined in this script. All calculations and plotting are done using built-in Pine Script functions such as ta.sma for SMA calculation and plot for plotting.
█ KEY POINTS AND TECHNIQUES
• Use of ta.sma: The script effectively uses the ta.sma function to calculate Simple Moving Averages for different periods.
• Conditional Logic: The script employs conditional logic (ternary operators) to determine the color and position of the plotted columns based on the direction of each MA.
• Plotting with plot: The plot function is used extensively to display the direction of each MA with different colors and positions.
• Color Transparency: The use of color.new with transparency (e.g., color.new(color.green, 50)) allows for visually distinct colors that are not too overpowering.
█ EXTENDED KNOWLEDGE AND APPLICATIONS
• Modifications: The script could be enhanced by adding input parameters to allow users to customize the periods of the moving averages, colors, and transparency levels.
• Extensions: Similar techniques could be applied to other types of moving averages (e.g., EMA, WMA) or to other technical indicators.
• Strategy Development: This indicator could serve as a component in a larger trading strategy by providing insights into the overall trend direction across multiple timeframes.
• Related Concepts: Understanding of moving averages, conditional logic, and plotting techniques in Pine Script would be beneficial for further development and customization of this script.
Three Moving Averages Strategythis is three moving averages strategy is good for day time frame best for swing trading , probability vary for 60 to 80 to increase the probability add other indictors . you can rsi or macd.
Austin MTF EMA Entry PointsAustin MTF EMA Entry Points
Overview
The Austin MTF EMA Entry Points is a custom TradingView indicator designed to assist traders in identifying high-probability entry points by combining multiple time frame (MTF) analysis. It leverages exponential moving averages (EMAs) from the daily, 1-hour, and 15-minute charts to generate buy and sell signals that align with the overall trend.
This indicator is ideal for traders who:
Want to trade in the direction of the broader daily trend.
Seek precise entry points on lower time frames (1H and 15M).
Prefer using EMAs as their main trend-following tool.
How It Works
Daily Trend Filter:
The indicator calculates the 50 EMA on the daily chart.
The daily EMA acts as the primary trend filter:
If the current price is above the daily 50 EMA, the trend is bullish.
If the current price is below the daily 50 EMA, the trend is bearish.
Lower Time Frame Entry Points:
The indicator calculates the 20 EMA on both the 1-hour (1H) and 15-minute (15M) time frames.
Buy and sell signals are generated when the price aligns with the trend on all three time frames:
Buy Signal: Price is above the daily 50 EMA and also above the 20 EMA on both the 1H and 15M charts.
Sell Signal: Price is below the daily 50 EMA and also below the 20 EMA on both the 1H and 15M charts.
Visual and Alert Features:
Plot Lines:
The daily 50 EMA is plotted in yellow for easy identification of the main trend.
The 20 EMA from the 1H chart is plotted in blue, and the 15M chart's EMA is in purple for comparison.
Buy/Sell Markers:
Green "Up" arrows appear for buy signals.
Red "Down" arrows appear for sell signals.
Alerts:
Alerts notify users when a buy or sell signal is triggered, making it easier to act on trading opportunities in real-time.
How to Use the Indicator
Identify the Main Trend:
Check the relationship between the price and the daily 50 EMA (yellow line):
Only look for buy signals if the price is above the daily 50 EMA.
Only look for sell signals if the price is below the daily 50 EMA.
Wait for Lower Time Frame Alignment:
For a valid signal, ensure that the price is also above or below the 20 EMA (blue and purple lines) on both the 1H and 15M time frames:
This alignment confirms short-term momentum in the same direction as the daily trend.
Act on Signals:
Use the arrows as visual cues for entry points:
Enter long trades on green "Up" arrows.
Enter short trades on red "Down" arrows.
The alerts will notify you of these signals, so you don’t have to monitor the chart constantly.
Exit Strategy:
Use your preferred stop-loss, take-profit, or trailing stop strategy.
You can also exit trades if the price crosses back below/above the daily 50 EMA, signaling a potential reversal.
Use Cases
Swing Traders: Use the daily trend filter to trade in the direction of the dominant trend, while using 1H and 15M signals to fine-tune entries.
Day Traders: Leverage the 1H and 15M time frames to capitalize on short-term momentum while respecting the broader daily trend.
Position Traders: Monitor the indicator to determine potential reversals or significant alignment across time frames.
Customizable Inputs
The indicator includes the following inputs:
Daily EMA Length: Default is 50. Adjust this to change the length of the trend filter EMA.
Lower Time Frame EMA Length: Default is 20. Adjust this to change the short-term EMA for the 1H and 15M charts.
Time Frames: Hardcoded to "D", "60", and "15", but you can modify the script for different time frames if needed.
Example Scenarios
Buy Signal:
Price is above the daily 50 EMA.
Price crosses above the 20 EMA on both the 1H and 15M time frames.
A green "Up" arrow is displayed, and an alert is triggered.
Sell Signal:
Price is below the daily 50 EMA.
Price crosses below the 20 EMA on both the 1H and 15M time frames.
A red "Down" arrow is displayed, and an alert is triggered.
Strengths and Limitations
Strengths:
Aligns trades with the higher time frame trend for increased probability.
Uses multiple time frame analysis to identify precise entry points.
Visual signals and alerts make it easy to use in real-time.
Limitations:
May produce fewer signals in choppy or ranging markets.
Requires discipline to avoid overtrading when conditions are unclear.
Lag in EMAs could result in late entries in fast-moving markets.
Final Notes
The Austin MTF EMA Entry Points indicator is a powerful tool for traders who value multiple time frame alignment and trend-following strategies. While it simplifies decision-making, it is always recommended to backtest and practice proper risk management before using it in live markets.
Try it out and make smarter, trend-aligned trades today! 🚀
[blackcat] L1 BS Line of Defense █ OVERVIEW
The Pine Script provided is an advanced technical indicator designed to generate reliable buy and sell signals by integrating momentum, moving averages, and price level analyses. It employs a custom weighted moving average (WMA) and exponential moving averages (EMAs) to compute key signals known as the "Buy/Sell Signal" and the "Short Line." These signals aim to pinpoint optimal entry and exit points for trades by evaluating their relationship with current market dynamics.
█ FEATURES
Key Components:
• Custom Weighted Moving Average ( WMA ): Provides enhanced flexibility compared to traditional moving averages.
• Exponential Moving Averages ( EMA ): Smooths the defense line and its short-term counterpart to filter out market noise.
• Momentum Indicators: Includes both short-term and long-term momentum adjusted via custom WMA and EMAs.
• Conditional Signal Generation: Signals are triggered based on precise crossovers and price conditions.
Logical Framework:
1 — Input Parameters:
No explicit user-defined inputs; defaults are used for internal calculations.
2 — Custom Functions:
• custom_wma : Calculates a custom WMA.
• calculate_buy_sell_signals : Generates buy and sell signals.
3 — Calculations:
• Momentum and Range Analysis over 9, 34, and 60-bar periods.
• Application of custom WMA and EMAs to smooth and refine data.
• Derivation of the "defense line" and "short_ema_defense."
4 — Plotting:
• Main signal lines ("Buy/Sell Signal" and "Short Line") are visualized.
• A horizontal zero line serves as a reference point.
█ HOW TO USE
To utilize this script effectively:
1 — Add the script to your TradingView chart.
2 — Observe the "Buy/Sell Signal" and "Short Line" relative to the zero line and each other.
3 — Look for crossovers and divergence patterns to identify potential trade opportunities.
4 — Combine the signals with additional technical indicators or fundamental analysis for better accuracy.
█ LIMITATIONS
While the script provides valuable insights, users should consider the following limitations:
• Default settings may not suit all markets or instruments; customization might be necessary.
• False signals can occur during volatile or ranging markets.
• Backtesting and optimization are recommended before live trading.
█ NOTES
For further enhancement and personalization:
• Introduce adjustable input parameters for WMA and EMA lengths and weights.
• Extend the script into a full-fledged trading strategy with entry and exit rules.
• Apply the script across multiple timeframes for comprehensive analysis.
• Incorporate risk management practices such as stop-loss and take-profit levels.
• Explore related Pine Script functions like security() for multi-timeframe analysis and [pine>alertcondition() for automated alerts.
Understanding core concepts like momentum, moving averages, and crossovers will aid in developing similar indicators or refining existing ones.
Logarithmic Regression AlternativeLogarithmic regression is typically used to model situations where growth or decay accelerates rapidly at first and then slows over time. Bitcoin is a good example.
𝑦 = 𝑎 + 𝑏 * ln(𝑥)
With this logarithmic regression (log reg) formula 𝑦 (price) is calculated with constants 𝑎 and 𝑏, where 𝑥 is the bar_index .
Instead of using the sum of log x/y values, together with the dot product of log x/y and the sum of the square of log x-values, to calculate a and b, I wanted to see if it was possible to calculate a and b differently.
In this script, the log reg is calculated with several different assumed a & b values, after which the log reg level is compared to each Swing. The log reg, where all swings on average are closest to the level, produces the final 𝑎 & 𝑏 values used to display the levels.
🔶 USAGE
The script shows the calculated logarithmic regression value from historical swings, provided there are enough swings, the price pattern fits the log reg model, and previous swings are close to the calculated Top/Bottom levels.
When the price approaches one of the calculated Top or Bottom levels, these levels could act as potential cycle Top or Bottom.
Since the logarithmic regression depends on swing values, each new value will change the calculation. A well-fitted model could not fit anymore in the future.
Swings are based on Weekly bars. A Top Swing, for example, with Swing setting 30, is the highest value in 60 weeks. Thirty bars at the left and right of the Swing will be lower than the Top Swing. This means that a confirmation is triggered 30 weeks after the Swing. The period will be automatically multiplied by 7 on the daily chart, where 30 becomes 210 bars.
Please note that the goal of this script is not to show swings rapidly; it is meant to show the potential next cycle's Top/Bottom levels.
🔹 Multiple Levels
The script includes the option to display 3 Top/Bottom levels, which uses different values for the swing calculations.
Top: 'high', 'maximum open/close' or 'close'
Bottom: 'low', 'minimum open/close' or 'close'
These levels can be adjusted up/down with a percentage.
Lastly, an "Average" is included for each set, which will only be visible when "AVG" is enabled, together with both Top and Bottom levels.
🔹 Notes
Users have to check the validity of swings; the above example only uses 1 Top Swing for its calculations, making the Top level unreliable.
Here, 1 of the Bottom Swings is pretty far from the bottom level, changing the swing settings can give a more reliable bottom level where all swings are close to that level.
Note the display was set at "Logarithmic", it can just as well be shown as "Regular"
In the example below, the price evolution does not fit the logarithmic regression model, where growth should accelerate rapidly at first and then slows over time.
Please note that this script can only be used on a daily timeframe or higher; using it at a lower timeframe will show a warning. Also, it doesn't work with bar-replay.
🔶 DETAILS
The code gathers data from historical swings. At the last bar, all swings are calculated with different a and b values. The a and b values which results in the smallest difference between all swings and Top/Bottom levels become the final a and b values.
The ranges of a and b are between -20.000 to +20.000, which means a and b will have the values -20.000, -19.999, -19.998, -19.997, -19.996, ... -> +20.000.
As you can imagine, the number of calculations is enormous. Therefore, the calculation is split into parts, first very roughly and then very fine.
The first calculations are done between -20 and +20 (-20, -19, -18, ...), resulting in, for example, 4.
The next set of calculations is performed only around the previous result, in this case between 3 (4-1) and 5 (4+1), resulting in, for example, 3.9. The next set goes even more in detail, for example, between 3.8 (3.9-0.1) and 4.0 (3.9 + 0.1), and so on.
1) -20 -> +20 , then loop with step 1 (result (example): 4 )
2) 4 - 1 -> 4 +1 , then loop with step 0.1 (result (example): 3.9 )
3) 3.9 - 0.1 -> 3.9 +0.1 , then loop with step 0.01 (result (example): 3.93 )
4) 3.93 - 0.01 -> 3.93 +0.01, then loop with step 0.001 (result (example): 3.928)
This ensures complicated calculations with less effort.
These calculations are done at the last bar, where the levels are displayed, which means you can see different results when a new swing is found.
Also, note that this indicator has been developed for a daily (or higher) timeframe chart.
🔶 SETTINGS
Three sets
High/Low
• color setting
• Swing Length settings for 'High' & 'Low'
• % adjustment for 'High' & 'Low'
• AVG: shows average (when both 'High' and 'Low' are enabled)
Max/Min (maximum open/close, minimum open/close)
• color setting
• Swing Length settings for 'Max' & 'Min'
• % adjustment for 'Max' & 'Min'
• AVG: shows average (when both 'Max' and 'Min' are enabled)
Close H/Close L (close Top/Bottom level)
• color setting
• Swing Length settings for 'Close H' & 'Close L'
• % adjustment for 'Close H' & 'Close L'
• AVG: shows average (when both 'Close H' and 'Close L' are enabled)
Show Dashboard, including Top/Bottom levels of the desired source and calculated a and b values.
Show Swings + Dot size
Rate of Change of OBV with RSI ColorThis indicator combines three popular tools in technical analysis : On-Balance Volume (OBV), Rate of Change (ROC), and Relative Strength Index (RSI). It aims to monitor momentum and potential trend reversals based on volume and price changes.
Calculation:
ROC(OBV) = ((OBV(today) - OBV(today - period)) / OBV(today - period)) * 100
This calculates the percentage change in OBV over a specific period. A positive ROC indicates an upward trend in volume, while a negative ROC suggests a downward trend.
What it Monitors:
OBV: Tracks the volume flow associated with price movements. Rising OBV suggests buying pressure, while falling OBV suggests selling pressure.
ROC of OBV:
Measures the rate of change in the OBV, indicating if the volume flow is accelerating or decelerating.
RSI: Measures the strength of recent price movements, indicating potential overbought or oversold conditions.
How it can be Used:
Identifying Trend Continuation: Rising ROC OBV with a rising RSI might suggest a continuation of an uptrend, especially if the color is lime (RSI above 60).
Identifying Trend Reversal: Falling ROC OBV with a declining RSI might suggest a potential trend reversal, especially if the color approaches blue (RSI below 40).
Confirmation with Threshold: The horizontal line (threshold) can be used as a support or resistance level. Bouncing ROC OBV off the threshold with a color change could suggest a pause in the trend but not necessarily a reversal.
When this Indicator is Useful:
This indicator can be useful for assets with strong volume activity, where tracking volume changes provides additional insights.
It might be helpful during periods of consolidation or trend continuation to identify potential breakouts or confirmations.
Market Open Range Breakaway v1.2Script Name: Market Open Range Breakaway 1.2
This TradingView script, "Market Open Range Breakaway," highlights the market's opening range for a user-selected day of the week. It calculates the high and low prices during a specified period after the market opens, plots these levels, and tracks the opening price. The script dynamically adjusts for time zones and only displays data during market hours on the chosen day, with optional background shading for the defined range period.
Purpose: Identifies and highlights the market's opening range for a selected day of the week.
Features: Calculates and plots the high, low, and open price during the market's opening range.
Configurable range duration (e.g., 15, 30, or 60 minutes).
Automatically adjusts for different time zones.
Displays levels only during market hours on the target day.
Optional background shading for the opening range.
Inputs: Target day of the week.
Opening range duration.
Use Case: Ideal for traders looking to analyze breakout levels or price movements around the opening range.
Multi-Timeframe MACD, Signal & Histogram TableThis Pine Script is designed for the TradingView platform to create a multi-timeframe MACD (Moving Average Convergence Divergence), Signal, and Histogram table that displays values for different timeframes. The script uses the MACD indicator to assess market trends across various timeframes and display the results in a table format on the chart. Here's a breakdown of its components and functionality:
1. User Inputs for Timeframes:
The script allows the user to input five different timeframes for the analysis. These are configured using input.string, which enables the user to select from a list of timeframes (from seconds to months).
tf1 to tf5 represent the different timeframes (for example, 5 minutes, 15 minutes, 60 minutes, 240 minutes, and daily).
2. MACD Settings:
The script provides adjustable settings for the MACD calculation:
macdShortLength (default 12): The length of the short-term moving average for the MACD.
macdLongLength (default 26): The length of the long-term moving average for the MACD.
macdSignalLength (default 9): The length of the signal line, which is an EMA (Exponential Moving Average) of the MACD line.
3. MACD Calculation Function (calc_macd):
This function calculates the MACD, Signal, and Histogram values:
MACD Line: Difference between the fast and slow exponential moving averages.
Signal Line: EMA of the MACD line.
Histogram: Difference between the MACD line and Signal line.
4. Requesting Multi-Timeframe Data:
The script calculates the MACD, Signal, and Histogram for the selected timeframes (tf1 to tf5) using request.security, which retrieves data for those timeframes:
macd_tf1, signal_tf1, hist_tf1 for Timeframe 1 (and similar variables for the other timeframes).
5. Rounding Values:
A helper function roundDecimal is used to round MACD, Signal, and Histogram values to two decimal places for readability.
6. Color Assignment Based on Value:
The colors of the values in the table cells are dynamically set based on whether the value is positive or negative:
MACD, Signal, and Histogram: The script uses conditional color assignments (green for positive values, red for negative values).
For example, if the MACD value is greater than or equal to 0, it is colored green, otherwise red. The same logic applies to the Signal and Histogram values.
7. Populating the Table:
For each timeframe (tf1 to tf5), the script populates the table with the following data:
Timeframe (e.g., "5 min")
Rounded MACD value
Rounded Signal value
Rounded Histogram value
The respective color is applied to each value based on whether it is positive or negative.
8. Table Update:
The table is updated dynamically with new data on each new bar. Each timeframe’s values are populated into the table starting from row 1 through row 5.
RSI-EMA Signal by stock shooter## Strategy Description: 200 EMA Crossover with RSI, Green/Red Candles, Volume, and Exit Conditions
This strategy combines several technical indicators to identify potential long and short entry opportunities in a trading instrument. Here's a breakdown of its components:
1. 200-period Exponential Moving Average (EMA):
* The 200-period EMA acts as a long-term trend indicator.
* The strategy looks for entries when the price is above (long) or below (short) the 200 EMA.
2. Relative Strength Index (RSI):
* The RSI measures the momentum of price movements and helps identify overbought and oversold conditions.
* The strategy looks for entries when the RSI is below 40 (oversold) for long positions and above 60 (overbought) for short positions.
3. Green/Red Candles:
* This indicator filters out potential entries based on the current candle's closing price relative to its opening price.
* The strategy only considers long entries on green candles (closing price higher than opening) and short entries on red candles (closing price lower than opening).
4. Volume:
* This indicator adds a volume filter to the entry conditions.
* The strategy only considers entries when the current candle's volume is higher than the average volume of the previous 20 candles, aiming for stronger signals.
Overall:
This strategy aims to capture long opportunities during potential uptrends and short opportunities during downtrends, based on a combination of price action, momentum, and volume confirmation.
Important Notes:
Backtesting is crucial to evaluate the historical performance of this strategy before deploying it with real capital.
Consider incorporating additional risk management techniques like stop-loss orders.
This strategy is just a starting point and can be further customized based on your trading goals and risk tolerance.
Stoch RSI and RSI Buy/Sell Signals with MACD Trend FilterDescription of the Indicator
This Pine Script is designed to provide traders with buy and sell signals based on the combination of Stochastic RSI, RSI, and MACD indicators, enhanced by the confirmation of candle colors. The primary goal is to facilitate informed trading decisions in various market conditions by utilizing different indicators and their interactions. The script allows customization of various parameters, providing flexibility for traders to adapt it to their specific trading styles.
Usefulness
This indicator is not just a mashup of existing indicators; it integrates the functionality of multiple momentum and trend-detection methods into a cohesive trading tool. The combination of Stochastic RSI, RSI, and MACD offers a well-rounded approach to analyzing market conditions, allowing traders to identify entry and exit points effectively. The inclusion of color-coded signals (strong vs. weak) further enhances its utility by providing visual cues about the strength of the signals.
How to Use This Indicator
Input Settings: Adjust the parameters for the Stochastic RSI, RSI, and MACD to fit your trading style. Set the overbought/oversold levels according to your risk tolerance.
Signal Colors:
Strong Buy Signal: Indicated by a green label and confirmed by a green candle (close > open).
Weak Buy Signal: Indicated by a blue label and confirmed by a green candle (close > open).
Strong Sell Signal: Indicated by a red label and confirmed by a red candle (close < open).
Weak Sell Signal: Indicated by an orange label and confirmed by a red candle (close < open).
Example Trading Strategy Using This Indicator
To effectively use this indicator as part of your trading strategy, follow these detailed steps:
Setup:
Timeframe : Select a timeframe that aligns with your trading style (e.g., 15-minute for intraday, 1-hour for swing trading, or daily for longer-term positions).
Indicator Settings : Customize the Stochastic RSI, RSI, and MACD parameters to suit your trading approach. Adjust overbought/oversold levels to match your risk tolerance.
Strategy:
1. Strong Buy Entry Criteria :
Wait for a strong buy signal (green label) when the RSI is at or below the oversold level (e.g., ≤ 35), indicating a deeply oversold market. Confirm that the MACD shows a decreasing trend (bearish momentum weakening) to validate a potential reversal. Ensure the current candle is green (close > open) if candle color confirmation is enabled.
Example Use : On a 1-hour chart, if the RSI drops below 35, MACD shows three consecutive bars of decreasing negative momentum, and a green candle forms, enter a buy position. This setup signals a robust entry with strong momentum backing it.
2. Weak Buy Entry Criteria :
Monitor for weak buy signals (blue label) when RSI is above the oversold level but still below the neutral (e.g., between 36 and 50). This indicates a market recovering from an oversold state but not fully reversing yet. These signals can be used for early entries with additional confirmations, such as support levels or higher timeframe trends.
Example Use : On the same 1-hour chart, if RSI is at 45, the MACD shows momentum stabilizing (not necessarily negative), and a green candle appears, consider a partial or cautious entry. Use this as an early warning for a potential bullish move, especially when higher timeframe indicators align.
3. Strong Sell Entry Criteria :
Look for a strong sell signal (red label) when RSI is at or above the overbought level (e.g., ≥ 65), signaling a strong overbought condition. The MACD should show three consecutive bars of increasing positive momentum to indicate that the bullish trend is weakening. Ensure the current candle is red (close < open) if candle color confirmation is enabled.
Example Use : If RSI reaches 70, MACD shows increasing momentum that starts to level off, and a red candle forms on a 1-hour chart, initiate a short position with a stop loss set above recent resistance. This is a high-confidence signal for potential price reversal or pullback.
4. Weak Sell Entry Criteria :
Use weak sell signals (orange label) when RSI is between the neutral and overbought levels (e.g., between 50 and 64). These can indicate potential short opportunities that might not yet be fully mature but are worth monitoring. Look for other confirmations like resistance levels or trendline touches to strengthen the signal.
Example Use : If RSI reads 60 on a 1-hour chart, and the MACD shows slight positive momentum with signs of slowing down, place a cautious sell position or scale out of existing long positions. This setup allows you to prepare for a possible downtrend.
Trade Management:
Stop Loss : For buy trades, place stop losses below recent swing lows. For sell trades, set stops above recent swing highs to manage risk effectively.
Take Profit : Target nearby resistance or support levels, apply risk-to-reward ratios (e.g., 1:2), or use trailing stops to lock in profits as price moves in your favor.
Confirmation : Align these signals with broader trends on higher timeframes. For example, if you receive a weak buy signal on a 15-minute chart, check the 1-hour or daily chart to ensure the overall trend is not bearish.
Real-World Example: Imagine trading on a 15-minute chart :
For a buy:
A strong buy signal (green) appears when the RSI dips to 32, MACD shows declining bearish momentum, and a green candle forms. Enter a buy position with a stop loss below the most recent support level.
Alternatively, a weak buy signal (blue) appears when RSI is at 47. Use this as a signal to start monitoring the market closely or enter a smaller position if other indicators (like support and volume analysis) align.
For a sell:
A strong sell signal (red) with RSI at 72 and a red candle signals to short with conviction. Place your stop loss just above the last peak.
A weak sell signal (orange) with RSI at 62 might prompt caution but can still be acted on if confirmed by declining volume or touching a resistance level.
These strategies show how to blend both strong and weak signals into your trading for more nuanced decision-making.
Technical Analysis of the Code
1. Stochastic RSI Calculation:
The script calculates the Stochastic RSI (stochRsiK) using the RSI as input and smooths it with a moving average (stochRsiD).
Code Explanation : ta.stoch(rsi, rsi, rsi, stochLength) computes the Stochastic RSI, and ta.sma(stochRsiK, stochSmoothing) applies smoothing.
2. RSI Calculation :
The RSI is computed over a user-defined period and checks for overbought or oversold conditions.
Code Explanation : rsi = ta.rsi(close, rsiLength) calculates RSI values.
3. MACD Trend Filter :
MACD is calculated with fast, slow, and signal lengths, identifying trends via three consecutive bars moving in the same direction.
Code Explanation : = ta.macd(close, macdLengthFast, macdLengthSlow, macdSignalLength) sets MACD values. Conditions like macdLine < macdLine confirm trends.
4. Buy and Sell Conditions :
The script checks Stochastic RSI, RSI, and MACD values to set buy/sell flags. Candle color filters further confirm valid entries.
Code Explanation : buyConditionMet and sellConditionMet logically check all conditions and toggles (enableStochCondition, enableRSICondition, etc.).
5. Signal Flags and Confirmation :
Flags track when conditions are met and ensure signals only appear on appropriate candle colors.
Code Explanation : Conditional blocks (if statements) update buyFlag and sellFlag.
6. Labels and Alerts :
The indicator plots "BUY" or "SELL" labels with the RSI value when signals trigger and sets alerts through alertcondition().
Code Explanation : label.new() displays the signal, color-coded for strength based on RSI.
NOTE : All strategies can be enabled or disabled in the settings, allowing traders to customize the indicator to their preferences and trading styles.
Options Series - Technical Analysis Chart➤ Simple Technical Chart Only:
➤ With MA-20 Overlay and Volatility background bars:
➤ With RSI Candles:
⭐ Overview and How It Works:
This script provides a multi-asset analysis tool to assess various market conditions across four symbols simultaneously. It combines several indicators such as daily price change, Moving Averages (MA), Bollinger Bands (BB), Parabolic SAR, RSI, and VWAP to generate buy/sell signals and trend indicators. Its strength lies in the layered use of indicators to enhance signal reliability, making it valuable for traders needing cross-validation in decision-making.
⭐ Key Features and Functionality:
The script evaluates each symbol's price against various indicators and conditions:
Daily Price Conditions: It checks if each symbol’s close price is above or below the previous day’s open, close, and intra-day ranges, forming a foundational bullish/bearish condition.
Range Breakout 1st 5min Candle (ORB): Opening Range Breakout levels are calculated and compared with current close prices, detecting breakout/breakdown conditions.
ORB Body: This basically calculates the previous day Daily candle body size, if todays Daily candle body size is greater than previous day, then we can say that we are having good momentum else its likely to be in-sidebar trading.
Moving Averages (MA): It leverages EMA-20, 2-day, and 3-day exponential moving averages to gauge short to medium-term trends.
RSI and VWAP: Relative Strength Index (RSI) determines overbought or oversold conditions, while VWAP compares prices to volume-weighted levels.
Bollinger Bands and Trend Analysis: Detects volatility and potential breakout conditions.
Concept of ORB Body:
Current_PrevDay_Body = (math.max(var_Current_PrevD_Open, var_Current_PrevD_Close) - math.min(var_Current_PrevD_Open, var_Current_PrevD_Close))
Current_Upper_ORB = var_Current_D_Open + Current_PrevDay_Body
Current_Lower_ORB = var_Current_D_Open - Current_PrevDay_Body
Current_TodayDay_Body = math.max(var_Current_D_Open, var_Current_Close) - math.min(var_Current_D_Open, var_Current_Close)
Current_ORBBody = Current_TodayDay_Body > Current_PrevDay_Body
Current_Upper_ORB_bull = (var_Current_Close > Current_Upper_ORB)
Current_Lower_ORB_bear = (var_Current_Close < Current_Lower_ORB)
🎨 Visualizations and User Experience:
The script can dynamically display colored backgrounds indicating trends when conditions are met. For example, the bgcolor function changes the background when certain trend-based criteria are satisfied, offering visual cues to users. Additionally, the checkbox input toggles trend bar visualizations, enhancing user experience by providing a quick visual reference without needing to interpret individual data points manually.
RSI-Based Candle Coloring:
➤ The script customizes candle colors based on RSI thresholds, specifically defining upper (60) and lower (40) RSI levels. When the RSI value exceeds the upper threshold, candles are colored as bullish (green), and if it falls below the lower threshold, candles are colored as bearish (red). Neutral RSI values result in a default color (gray).
➤ This setup offers a visually intuitive way to identify potential trend directions based on RSI levels, making it ideal for traders looking to gauge momentum visually.
⭐ Settings and Customization:
With multiple user-configurable inputs, the script allows for tailored analysis. Customizable parameters, such as enabling/disabling trend bars and setting various look-back periods for indicators like Bollinger Bands and Moving Averages, make it adaptable to various trading styles and preferences. It also allows users to modify visual elements like colors and styles, improving flexibility.
⭐ Uniqueness of the Concept:
The unique aspect of this script is its multi-symbol approach combined with complex conditions. By comparing not only one but four symbols simultaneously, it provides a broader market view and allows traders to correlate signals across different assets, offering a potential edge for diversified or comparative strategies. Additionally, the incorporation of ORB and multi-timeframe MAs gives it a robustness often lacking in simpler single-symbol scripts.
🚀 Conclusion:
This script is a powerful multi-indicator tool suited for traders looking for a comparative, multi-symbol analysis. With features like ORB, Bollinger Band-based trend detection, and MA cross-verification, it can assist traders in identifying and validating trend signals across assets. The user-friendly visualizations and customizable settings further enhance its usability, making it versatile for various trading strategies and preferences.
Hinton Map█ HINTON MAP
This script displays a Hinton Map visualization of market data for user-defined tickers and timeframes. It uses color gradients to represent the magnitude and direction of price change, RSI, and a combination of both.
This is one example. You can modify and try other values as you wish, but do keep the incoming values between -1 and 1.
In the Example Usage:
Users can input up to 5 symbols and 5 timeframes. For each ticker/timeframe combination:
The box size represents the relative magnitude of the 2-bar percentage change.
The box fill color represents the direction and magnitude of the 2-bar percentage change.
The box border color and thickness represent the RSI deviation from 50.
The inner box color represents a combination of price change magnitude and RSI deviation from 50.
Hovering over each box displays a tooltip with the ticker, timeframe, percentage change, and RSI.
Inputs:
• Unit Size (bars):
The size of each Hinton unit in bars.
Type: int
Default Value: 10
• Border Width:
The base width of the inner box border.
Type: int
Default Value: 3
• Negative Hue (0-360):
The hue value for negative price changes (0-360).
Type: float
Default Value: 100
• Positive Hue (0-360):
The hue value for positive price changes (0-360).
Type: float
Default Value: 180
• Ticker 1-5:
The tickers to display on the Hinton map.
Type: string
Default Value: AAPL
• Timeframes (comma separated):
The timeframes to display on the Hinton map (comma-separated).
Type: string
Default Value: 1, 5, 60, 1D, 1W
(Fun Note: My Home town is named `Hinton`)
Advanced Multi-Seasonality StrategyThe Multi-Seasonality Strategy is a trading system based on seasonal market patterns. Seasonality refers to recurring market trends driven by predictable calendar-based events. These patterns emerge due to economic cycles, corporate activities (e.g., earnings reports), and investor behavior around specific times of the year. Studies have shown that such effects can influence asset prices over defined periods, leading to opportunities for traders who exploit these patterns (Hirshleifer, 2001; Bouman & Jacobsen, 2002).
How the Strategy Works:
The strategy allows the user to define four distinct periods within a calendar year. For each period, the trader selects:
Entry Date (Month and Day): The date to enter the trade.
Holding Period: The number of trading days to remain in the trade after the entry.
Trade Direction: Whether to take a long or short position during that period.
The system is designed with flexibility, enabling the user to activate or deactivate each of the four periods. The idea is to take advantage of seasonal patterns, such as buying during historically strong periods and selling during weaker ones. A well-known example is the "Sell in May and Go Away" phenomenon, which suggests that stock returns are higher from November to April and weaker from May to October (Bouman & Jacobsen, 2002).
Seasonality in Financial Markets:
Seasonal effects have been documented across different asset classes and markets:
Equities: Stock markets tend to exhibit higher returns during certain months, such as the "January effect," where prices rise after year-end tax-loss selling (Haugen & Lakonishok, 1987).
Commodities: Agricultural commodities often follow seasonal planting and harvesting cycles, which impact supply and demand patterns (Fama & French, 1987).
Forex: Currency pairs may show strength or weakness during specific quarters based on macroeconomic factors, such as fiscal year-end flows or central bank policy decisions.
Scientific Basis:
Research shows that market anomalies like seasonality are linked to behavioral biases and institutional practices. For example, investors may respond to tax incentives at the end of the year, and companies may engage in window dressing (Haugen & Lakonishok, 1987). Additionally, macroeconomic factors, such as monetary policy shifts and holiday trading volumes, can also contribute to predictable seasonal trends (Bouman & Jacobsen, 2002).
Risks of Seasonal Trading:
While the strategy seeks to exploit predictable patterns, there are inherent risks:
Market Changes: Seasonal effects observed in the past may weaken or disappear as market conditions evolve. Increased algorithmic trading, globalization, and policy changes can reduce the reliability of historical patterns (Lo, 2004).
Overfitting: One of the risks in seasonal trading is overfitting the strategy to historical data. A pattern that worked in the past may not necessarily work in the future, especially if it was based on random chance or external factors that no longer apply (Sullivan, Timmermann, & White, 1999).
Liquidity and Volatility: Trading during specific periods may expose the trader to low liquidity, especially around holidays or earnings seasons, leading to slippage and larger-than-expected price swings.
Economic and Geopolitical Shocks: External events such as pandemics, wars, or political instability can disrupt seasonal patterns, leading to unexpected market behavior.
Conclusion:
The Multi-Seasonality Strategy capitalizes on the predictable nature of certain calendar-based patterns in financial markets. By entering and exiting trades based on well-established seasonal effects, traders can potentially capture short-term profits. However, caution is necessary, as market dynamics can change, and seasonal patterns are not guaranteed to persist. Rigorous backtesting, combined with risk management practices, is essential to successfully implementing this strategy.
References:
Bouman, S., & Jacobsen, B. (2002). The Halloween Indicator, "Sell in May and Go Away": Another Puzzle. American Economic Review, 92(5), 1618-1635.
Fama, E. F., & French, K. R. (1987). Commodity Futures Prices: Some Evidence on Forecast Power, Premiums, and the Theory of Storage. Journal of Business, 60(1), 55-73.
Haugen, R. A., & Lakonishok, J. (1987). The Incredible January Effect: The Stock Market's Unsolved Mystery. Dow Jones-Irwin.
Hirshleifer, D. (2001). Investor Psychology and Asset Pricing. Journal of Finance, 56(4), 1533-1597.
Lo, A. W. (2004). The Adaptive Markets Hypothesis: Market Efficiency from an Evolutionary Perspective. Journal of Portfolio Management, 30(5), 15-29.
Sullivan, R., Timmermann, A., & White, H. (1999). Data-Snooping, Technical Trading Rule Performance, and the Bootstrap. Journal of Finance, 54(5), 1647-1691.
This strategy harnesses the power of seasonality but requires careful consideration of the risks and potential changes in market behavior over time.
Ultimate Fibonacci Trading Tool [CHE]Ultimate Fibonacci Trading Tool – Your Key to More Precise Trading Decisions!
Description:
Discover the Ultimate Fibonacci Trading Tool , a powerful instrument designed to revolutionize your technical analysis. This tool is crafted to assist traders of all experience levels in better understanding market movements and making informed decisions. By utilizing a higher reference period from the past, it provides you with a clear advantage in identifying critical support and resistance levels.
🌟 Key Features in Detail:
1. Automatic Timeframe Selection:
- Auto Timeframe: The tool automatically detects the optimal higher reference period based on your current chart, providing more precise analysis without additional effort.
- Multiplier Mode: Define the higher timeframe using a multiplier. By default set to 5, this can be adjusted to suit your individual needs.
- Manual Selection: For maximum control, you can manually select the desired timeframe.
2. Customizable Fibonacci Levels:
- Enable/Disable Levels: Toggle specific Fibonacci levels (e.g., 0.236, 0.382, 0.5, 0.618, etc.) on or off to personalize your analysis.
- User-Defined Values: Input custom numerical values for each level to support specialized Fibonacci calculations.
- Color Customization: Choose individual colors for each level to keep your charts clear and visually appealing.
3. Automatic Trend Detection:
- The tool automatically identifies whether the market is in a bullish or bearish trend and adjusts the Fibonacci calculations accordingly, ensuring you always have the most relevant information at hand.
4. Period Separators with Start and Stop Labels:
- Customizable Separator Lines: Visualize the beginning of new time periods with lines that you can customize in style, color, and width.
- Start/Stop Labels: Clear markers help you instantly recognize critical time points and potential trend changes.
5. Flexible Label Management:
- Display Styles: Decide how Fibonacci levels are presented—percentage, price level, or both—so you get the information most important to you.
- Size Adjustment: Modify the size of the labels to optimize readability on your chart.
- Positioning: Place labels where they make the most sense for your analysis.
6. Informative Time Period Display:
- Customizable Info Box: Keep track of the reference period used with a customizable information box displayed directly on your chart.
- Layout Options: Determine the size, position, background, and text colors for seamless integration into your chart environment.
🔧 Detailed Settings Options:
- Timeframe Selection:
- Timeframe Type: Choose between "Auto Timeframe," "Multiplier," or "Manual" to control how the reference period is calculated.
- Multiplier: Set the multiplier when using the "Multiplier" mode; this value determines how many units of the current timeframe are used as the reference.
- Manual Resolution: If "Manual" is selected, you can input the exact timeframe (e.g., "60," "1D," "1W").
- Fibonacci Level Settings:
- Enabling Individual Levels: Toggle each Fibonacci level on or off according to your preference.
- Adjusting Level Values: Enter custom numerical values for each level to perform specialized calculations.
- Color Selection: Choose a unique color for each level to ensure clear differentiation.
- Period Separator Settings:
- Separator Color: Define the color of the separator lines to make them distinctly visible.
- Separator Style: Choose between "Solid," "Dashed," or "Dotted" to adjust the style of the separator lines.
- Separator Width: Set the width of the separator lines to match your chart aesthetics.
- Label Management:
- Label Style: Select how labels are displayed:
- Default: Shows both percentage and price.
- None: No labels are displayed.
- Percentage: Shows only the Fibonacci level percentage.
- Price: Shows only the price at the Fibonacci level.
- Label Size: Adjust the size of the labels (tiny, small, normal, large, huge) for optimal readability.
- Time Period Display:
- Show Time Period: Enable or disable the information box displaying the reference period.
- Size: Choose the size of the information box (tiny, small, normal, large, huge, auto).
- Positioning: Set the vertical (top, middle, bottom) and horizontal (left, center, right) position of the box.
- Color Customization: Select the background and text color of the information box to integrate it into your chart design.
📈 Why Is the Higher Reference Period Important?
The Ultimate Fibonacci Trading Tool leverages a higher reference period from the past to calculate Fibonacci levels. This approach offers several advantages:
- Deeper Market Analysis: By considering longer timeframes, you can uncover major market movements and trends that might be hidden in shorter periods.
- More Accurate Support and Resistance Levels: Higher timeframes provide more robust Fibonacci levels that are observed by many market participants.
- Better Decision-Making Foundation: With a comprehensive view of the market, you can make more informed trading decisions and minimize potential risks.
🎯 How This Tool Enhances Your Trading Strategy:
- Increased Efficiency: Automate complex calculations and save valuable time.
- Personalized Analysis: Adapt the tool to your individual needs and strategies.
- Enhanced Precision: Utilize precise Fibonacci levels to better determine entry and exit points.
- Improved Market Insight: Gain deeper understanding of market trends and structures by using higher timeframes.
🚀 Get Started Now!
Don't miss the opportunity to revolutionize your chart analysis. Integrate the Ultimate Fibonacci Trading Tool into your trading routine and benefit from more precise analyses and improved trading decisions.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Best regards
Chervolino
Fibonacci BandsDescription
This indicator dynamically calculates Fibonacci retracement levels based on the highest high and lowest low over a specified lookback period. The key Fibonacci levels (0.236, 0.382, 0.5, 0.618, and 0.786) are plotted on the chart, with shaded areas between these levels for visual guidance.
How it works
The script computes the highest high (hh) and the lowest low (ll) over the defined length.
It calculates the price range (delta) as the difference between the highest high and the lowest low.
Fibonacci levels are then determined using the formula: ℎℎ − (delta × Fibonacci ratio)
Each Fibonacci level is then plotted as a line with a specific color.
Key Features
Customizable Length: Users can adjust the lookback period to suit their trading strategy.
Multiple Fibonacci Levels: Includes common Fibonacci retracement levels, providing traders with a comprehensive view of potential support and resistance areas.
Visual Fillings: The script includes customizable shading between levels, which helps traders quickly identify key zones (like the "Golden Zone" between 0.5 and 0.618).
Unique Points
Fibonacci Focus: This script is specifically designed around Fibonacci retracement levels, which are popular among technical traders for identifying potential reversal points.
Dynamic Range Calculation: The use of the highest high and lowest low within a user-defined period offers a dynamic approach to adapting to changing market conditions.
How to use it
Adjust the length parameter (default is 60) to determine how many bars back the indicator will calculate the highest high and lowest low. A longer length may provide a broader perspective of price action, while a shorter length may react more quickly to recent price changes.
Observe the plotted Fibonacci levels: 0.236, 0.382, 0.5, 0.618, and 0.786. These levels often act as potential support and resistance points. Pay attention to how price interacts with these levels.
When the price approaches a Fibonacci level, consider it a potential reversal point. The filled areas between the Fibonacci levels indicate zones where price might consolidate or reverse. The "Golden Zone" (between 0.5 and 0.618) is particularly significant; many traders watch this area closely for potential entry points in an uptrend or exit points in a downtrend.
First Heikin-Ashi Candle Tracker [CHE] First Heikin-Ashi Candle Tracker
"A Heikin-Ashi Candle Rarely Comes Alone"
1. Introduction
Fundamental Observation
- "A Heikin-Ashi Candle Rarely Comes Alone"
- This principle highlights the tendency of Heikin-Ashi candles to appear in sequences, indicating sustained trends rather than isolated movements.
- Recognizing these patterns can significantly enhance trading strategies by identifying stronger and more reliable entry points.
2. Understanding Heikin-Ashi Candles
What Are Heikin-Ashi Candles?
- Heikin-Ashi is a type of candlestick chart used to identify market trends more clearly.
- Calculation Method:
- Ha_Close: (Open + High + Low + Close) / 4
- Ha_Open: (Previous Ha_Open + Previous Ha_Close) / 2
- Ha_High: Maximum of High, Ha_Open, Ha_Close
- Ha_Low: Minimum of Low, Ha_Open, Ha_Close
- Visual Differences:
- Smoother appearance compared to traditional candlesticks.
- Helps in filtering out market noise and highlighting the prevailing trend.
Benefits of Heikin-Ashi Candles
- Trend Clarity: Easier identification of uptrends and downtrends.
- Reduced Noise: Minimizes the impact of insignificant price movements.
- Visual Appeal: Cleaner charts enhance decision-making processes.
3. Introducing the First Heikin-Ashi Candle Tracker [CHE ]
Purpose of the Indicator
- Track First Heikin-Ashi Candles: Identifies the initial appearance of Heikin-Ashi candles across multiple timeframes.
- Enhance Trading Decisions: Provides visual cues for potential long and short entries based on trend confirmations.
Key Features
- Multi-Timeframe Support: Monitor Heikin-Ashi candles across different timeframes (e.g., 240, 60, 30, 15 minutes).
- Customizable Visuals: Adjustable colors and line widths for better chart integration.
- User-Friendly Interface: Easy-to-configure settings tailored to individual trading preferences.
- Max Line Management: Controls the number of displayed lines to maintain chart clarity.
4. How to Use the First Heikin-Ashi Candle Tracker
Step-by-Step Guide
1. Enable Desired Groups:
- Activate up to four groups, each representing a different timeframe.
- Customize each group's settings according to your trading strategy.
2. Configure Timeframes:
- Select timeframes that align with your trading style (e.g., short-term vs. long-term).
3. Set Candle Types to Track:
- Choose to monitor Both, Green (Bullish), or Red (Bearish) Heikin-Ashi candles.
- Focus on specific candle types to streamline entry signals.
4. Customize Visual Indicators:
- Adjust Green Line Color and Red Line Color for clear distinction.
- Modify Line Width to ensure visibility without cluttering the chart.
5. Manage Line Limits:
- Set the Max Number of Lines to prevent overcrowding.
- The indicator will automatically remove the oldest lines when the limit is exceeded.
6. Interpret Signals:
- Green Lines: Indicate potential Long entry points.
- Red Lines: Indicate potential Short entry points.
- Observe the sequence and frequency of candles to assess trend strength.
Practical Example
- Uptrend Identification:
- Consecutive green Heikin-Ashi candles with corresponding green lines signal a strong upward trend.
- Consider entering a Long position when the first green candle appears.
- Downtrend Identification:
- Consecutive red Heikin-Ashi candles with corresponding red lines signal a strong downward trend.
- Consider entering a Short position when the first red candle appears.
5. Benefits and Utility
Enhanced Trend Detection
- Early Signals: Identify the beginning of new trends promptly.
- Confirmation: Multiple timeframes provide robust confirmation of trend direction.
Improved Entry Points
- Precision: Pinpoint optimal moments to enter trades, reducing the risk of false signals.
- Flexibility: Suitable for both Long and Short strategies across various markets.
User-Friendly Operation
- Intuitive Settings: Easily configurable to match individual trading preferences.
- Visual Clarity: Clear lines and color-coding facilitate quick decision-making.
Time Efficiency
- Automated Tracking: Saves time by automatically identifying and marking relevant candles.
- Multi-Timeframe Analysis: Consolidates information from different timeframes into a single view.
6. Why Use the First Heikin-Ashi Candle Tracker ?
Strategic Advantages
- Market Insight: Gain deeper understanding of market dynamics through Heikin-Ashi analysis.
- Risk Management: Improved entry points contribute to better risk-reward ratios.
- Versatility: Applicable to various trading instruments, including stocks, forex, and cryptocurrencies.
Why Heikin-Ashi for Entries?
- Trend Reliability: Heikin-Ashi candles smooth out price data, providing more reliable trend indicators.
- Reduced Whipsaws: Fewer false signals compared to traditional candlestick charts.
- Clarity in Decision-Making: Simplifies the process of identifying and acting on market trends.
Conclusion
- The First Heikin-Ashi Candle Tracker is an essential tool for traders seeking to enhance their trend analysis and improve entry strategies.
- By leveraging the power of Heikin-Ashi candles, this indicator offers a clear, user-friendly approach to identifying profitable trading opportunities.
7. Getting Started
Installation
1. Add the Indicator:
- Open TradingView and navigate to the Pine Script editor.
- Paste the translated Pine Script code for the First Heikin-Ashi Candle Tracker .
- Save and add the indicator to your chart.
2. Configure Settings:
- Enable desired groups and set appropriate timeframes.
- Customize colors and line widths as per your preference.
- Adjust the maximum number of lines to maintain chart clarity.
3. Start Trading:
- Monitor the chart for green and red lines indicating potential Long and Short entries.
- Combine with other analysis tools for enhanced trading decisions.
Support and Resources
- Documentation: Refer to the included comments within the Pine Script for detailed explanations.
- Community Forums: Join TradingView communities for tips and shared experiences.
- Customer Support: Reach out for assistance with installation or configuration issues.
8. Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Happy Trading!
Best regards
Chervolino (Volker)
Stochastics Confluences 4 in 1Description of the Pine Script:
This script plots the Full Stochastic indicator for four different time periods, and highlights conditions where potential buy or sell signals can be identified. The Stochastic indicator measures the position of the current closing price relative to the range of high and low prices over a defined period, helping traders identify overbought and oversold conditions.
Key Features:
Stochastic Calculation for 4 Different Periods:
The script calculates the Stochastic for four separate lookback periods: 9, 14, 40, and 60 bars.
Each Stochastic value is smoothed by a Simple Moving Average (SMA) to reduce noise and provide a clearer signal.
Visual Representation:
It plots each Stochastic value on the chart using different colors, allowing the user to see how the different periods of the indicator behave relative to each other.
Horizontal lines are drawn at 80 (Upper Bound) and 20 (Lower Bound), commonly used to identify overbought and oversold regions.
Highlighting Buy and Sell Conditions:
Green Highlight (Potential Buy Signal):
When all four Stochastic values (for the four different periods) are below 20, this suggests that the asset is in an oversold condition across multiple timeframes. The green background highlight appears when the Stochastic lines converge below 20, indicating a potential buy signal, as the price may be preparing to move upward from an oversold state.
Red Highlight (Potential Sell Signal):
When all four Stochastic values are above 80, the asset is in an overbought condition across multiple timeframes. The red background highlight appears when the Stochastic lines converge above 80, indicating a potential sell signal, as the price may soon reverse downward from an overbought state.
How to Interpret the Signals:
Buy Signals (Green Highlight):
When the chart is highlighted in green, it means the Stochastic indicators for all four periods are below 20, signaling that the asset is oversold and may be nearing a potential upward reversal. This condition suggests a possible buying opportunity, especially when other indicators confirm the potential for an upward trend.
Sell Signals (Red Highlight):
When the chart is highlighted in red, it indicates that the Stochastic indicators for all four periods are above 80, meaning the asset is overbought. This condition signals a possible downward reversal, suggesting a potential selling opportunity if the price begins to show signs of weakness.
By using this script, traders can visually identify periods of strong confluence across different timeframes when the Stochastic indicators are in extreme oversold or overbought conditions, which are traditionally seen as strong buy or sell signals.
This approach helps filter out weaker signals and focuses on moments when all timeframes align, increasing the probability of a successful trade.
Futures Beta Overview with Different BenchmarksBeta Trading and Its Implementation with Futures
Understanding Beta
Beta is a measure of a security's volatility in relation to the overall market. It represents the sensitivity of the asset's returns to movements in the market, typically benchmarked against an index like the S&P 500. A beta of 1 indicates that the asset moves in line with the market, while a beta greater than 1 suggests higher volatility and potential risk, and a beta less than 1 indicates lower volatility.
The Beta Trading Strategy
Beta trading involves creating positions that exploit the discrepancies between the theoretical (or expected) beta of an asset and its actual market performance. The strategy often includes:
Long Positions on High Beta Assets: Investors might take long positions in assets with high beta when they expect market conditions to improve, as these assets have the potential to generate higher returns.
Short Positions on Low Beta Assets: Conversely, shorting low beta assets can be a strategy when the market is expected to decline, as these assets tend to perform better in down markets compared to high beta assets.
Betting Against (Bad) Beta
The paper "Betting Against Beta" by Frazzini and Pedersen (2014) provides insights into a trading strategy that involves betting against high beta stocks in favor of low beta stocks. The authors argue that high beta stocks do not provide the expected return premium over time, and that low beta stocks can yield higher risk-adjusted returns.
Key Points from the Paper:
Risk Premium: The authors assert that investors irrationally demand a higher risk premium for holding high beta stocks, leading to an overpricing of these assets. Conversely, low beta stocks are often undervalued.
Empirical Evidence: The paper presents empirical evidence showing that portfolios of low beta stocks outperform portfolios of high beta stocks over long periods. The performance difference is attributed to the irrational behavior of investors who overvalue riskier assets.
Market Conditions: The paper suggests that the underperformance of high beta stocks is particularly pronounced during market downturns, making low beta stocks a more attractive investment during volatile periods.
Implementation of the Strategy with Futures
Futures contracts can be used to implement the betting against beta strategy due to their ability to provide leveraged exposure to various asset classes. Here’s how the strategy can be executed using futures:
Identify High and Low Beta Futures: The first step involves identifying futures contracts that have high beta characteristics (more sensitive to market movements) and those with low beta characteristics (less sensitive). For example, commodity futures like crude oil or agricultural products might exhibit high beta due to their price volatility, while Treasury bond futures might show lower beta.
Construct a Portfolio: Investors can construct a portfolio that goes long on low beta futures and short on high beta futures. This can involve trading contracts on stock indices for high beta stocks and bonds for low beta exposures.
Leverage and Risk Management: Futures allow for leverage, which means that a small movement in the underlying asset can lead to significant gains or losses. Proper risk management is essential, using stop-loss orders and position sizing to mitigate the inherent risks associated with leveraged trading.
Adjusting Positions: The positions may need to be adjusted based on market conditions and the ongoing performance of the futures contracts. Continuous monitoring and rebalancing of the portfolio are essential to maintain the desired risk profile.
Performance Evaluation: Finally, investors should regularly evaluate the performance of the portfolio to ensure it aligns with the expected outcomes of the betting against beta strategy. Metrics like the Sharpe ratio can be used to assess the risk-adjusted returns of the portfolio.
Conclusion
Beta trading, particularly the strategy of betting against high beta assets, presents a compelling approach to capitalizing on market inefficiencies. The research by Frazzini and Pedersen emphasizes the benefits of focusing on low beta assets, which can yield more favorable risk-adjusted returns over time. When implemented using futures, this strategy can provide a flexible and efficient means to execute trades while managing risks effectively.
References
Frazzini, A., & Pedersen, L. H. (2014). Betting against beta. Journal of Financial Economics, 111(1), 1-25.
Fama, E. F., & French, K. R. (1992). The cross-section of expected stock returns. Journal of Finance, 47(2), 427-465.
Black, F. (1972). Capital Market Equilibrium with Restricted Borrowing. Journal of Business, 45(3), 444-454.
Ang, A., & Chen, J. (2010). Asymmetric volatility: Evidence from the stock and bond markets. Journal of Financial Economics, 99(1), 60-80.
By utilizing the insights from academic literature and implementing a disciplined trading strategy, investors can effectively navigate the complexities of beta trading in the futures market.
