Liquidity Zones [BigBeluga]This indicator is designed to detect liquidity zones on the chart by identifying significant pivot highs and lows filtered by volume strength. It plots these zones as boxes, highlighting areas where liquidity is likely to accumulate. The indicator also draws lines extending from these boxes, marking the levels where price may "grab" this liquidity. The size of these boxes can be dynamic, adjusting based on the volume size, offering a visual representation of market areas where traders might expect significant price reactions.
🔵 IDEA
The idea behind the Liquidity Zones indicator is to help traders identify key market levels where liquidity accumulates. Liquidity zones are areas where there are enough buy or sell orders that can potentially lead to significant price movements. By focusing on pivot points filtered by volume strength, the indicator aims to provide a clearer picture of where large players may have positioned their orders. This insight allows traders to anticipate potential market reactions, such as reversals or breakouts, when the price reaches these zones. The option for dynamic box height further refines the visualization, showing the extent of liquidity based on the volume's intensity.
🔵 KEY FEATURES & USAGE
◉ Volume-Filtered Pivot Highs and Lows:
The indicator scans for pivot highs and lows on the chart, filtering these points based on the volume strength setting (Low, Mid, High). This ensures that only the most significant liquidity zones, backed by notable trading volume, are highlighted. Traders can adjust the filter to focus on different levels of market activity, from small fluctuations to major volume spikes.
Low:
Mid:
High:
◉ Dynamic and Static Liquidity Zones:
Liquidity zones are plotted as boxes around pivot points, with an optional dynamic mode that adjusts the box height based on the normalized volume. This dynamic adjustment reflects the liquidity carried by the volume, making it easier to gauge the significance of each zone. In static mode, the boxes have a fixed height, providing a consistent visual reference for the zones.
◉ Color Intensity Based on Volume:
The indicator adjusts the color intensity of the liquidity zones based on the volume strength. Higher volume zones will be displayed with more intense colors, giving a visual cue to the strength of the liquidity present in that area. This makes it easier to differentiate between zones of varying importance at a glance, allowing traders to quickly identify where the market has the highest concentration of liquidity.
◉ Liquidity Grab Detection and Red Circles:
When the price interacts with a liquidity zone, the indicator detects whether liquidity has been "grabbed" at these levels. If the price moves into a zone and crosses a level, the box label changes to "Liquidity Grabbed," and the line marking the level becomes dashed.
Reversal Points:
The beginning of a trend:
Additionally marks these "liquidity grabs" with red circles, indicating both recent and past liquidity grabs. This feature helps traders identify areas where liquidity has been absorbed by the market, which may signal potential reversals or shifts in market direction.
◉ Dashboard Display:
A dashboard in the upper right corner of the chart provides an overview of the indicator's settings and status. It shows the number of plotted zones, as set in the input settings, and whether the dynamic mode is active. This quick reference helps traders stay informed about the indicator's configuration without needing to open the settings panel.
🔵 CUSTOMIZATION
Length & Zones Amount: Set the length for pivot detection and the maximum number of zones to be displayed on the chart. This allows you to control how many liquidity zones you want to monitor at any given time.
Volume Strength Filter: Adjust the filter to Low, Mid, or High to control the strength of volume required for a pivot to be considered a significant liquidity zone. Higher settings focus on zones with greater volume, indicating stronger liquidity.
Dynamic Distance Mode: Enable or disable the dynamic mode, which adjusts the box height based on the volume size. When dynamic mode is off, the boxes have a fixed height based on the ATR, offering a consistent visualization regardless of the volume size.
The Liquidity Zones indicator is a versatile tool for identifying areas of significant market activity, offering a clear view of where liquidity is likely to reside. By filtering these zones through volume strength and providing dynamic or static visualization options, it equips traders with insights into potential market reaction points, enhancing their ability to anticipate and respond to market movements. The varying color intensity based on volume further aids in quickly recognizing the most critical liquidity zones on the chart.
Trend Analysis
Optimized Comprehensive Analysis Table# Enhanced Comprehensive Analysis Table
This advanced indicator provides a holistic view of market sentiment by analyzing multiple technical indicators simultaneously. It's designed to give traders a quick, at-a-glance summary of market conditions across various timeframes and analysis methods.
## Key Features:
- Analyzes 9 popular technical indicators
- Weighted voting system for overall market sentiment
- Customizable indicator weights
- Clear, color-coded table display
## Indicators Analyzed:
1. MACD (Moving Average Convergence Divergence)
2. RSI (Relative Strength Index)
3. Moving Averages (50, 100, 200-period)
4. Stochastic Oscillator
5. Parabolic SAR
6. MFI (Money Flow Index)
7. CCI (Commodity Channel Index)
8. OBV (On Balance Volume)
9. ADX (Average Directional Index)
## How It Works:
Each indicator's signal is calculated and classified as bullish, bearish, or neutral. These signals are then weighted according to user-defined inputs. The weighted votes are summed to determine an overall market sentiment.
## Interpretation:
- The table displays the state of each indicator and the overall market sentiment.
- Green indicates bullish conditions, red bearish, and yellow neutral.
- The "Overall State" row at the bottom provides a quick summary of the combined analysis.
## Customization:
Users can adjust the weight of each indicator to fine-tune the analysis according to their trading strategy or market conditions.
This indicator is ideal for traders who want a comprehensive overview of market conditions without having to monitor multiple indicators separately. It's particularly useful for confirming trade setups, identifying potential trend reversals, and managing risk.
Note: This indicator is meant to be used as part of a broader trading strategy. Always combine with other forms of analysis and proper risk management.
FxASTLite [ALLDYN]This script, titled "FxASTLite " or "FxAST LX," is a Pine Script indicator designed for trading systems that use multiple technical analysis tools such as EMAs (Exponential Moving Averages) and PSAR (Parabolic Stop and Reverse). The script is overlaid on the price chart, providing insights into market trends and potential buy or sell signals.
### Key Features:
1. **EMA (Exponential Moving Averages)**
- The script plots several EMAs (5, 8, 13, 21, 50, and 200) based on the Heiken Ashi close price. EMAs are helpful in identifying trends, momentum, and potential entry/exit points.
- The script highlights key relationships between the EMAs, such as the crossover or crossunder of faster EMAs (like the 8 EMA) with slower ones (like the 21 EMA). These events often signal potential trend reversals or continuation.
2. **PSAR (Parabolic Stop and Reverse)**
- The script uses the PSAR indicator, which is a trend-following indicator that highlights potential points where the market might reverse direction.
- The script identifies bullish PSAR flips (when the PSAR value moves below the price, signaling a potential upward trend) and bearish PSAR flips (when the PSAR value moves above the price, signaling a downward trend).
- The PSAR flips are used to generate buy or sell signals.
3. **Heiken Ashi Candles**
- It uses Heiken Ashi candles to smooth out price action and better identify trends. Heiken Ashi candles help filter out market noise and make trends clearer compared to regular candlestick charts.
4. **Session Times**
- The script allows traders to track different market sessions (e.g., London, New York, Asia). It identifies and allows users to analyze price action during specific trading hours.
5. **Buy and Sell Signals**
- The script defines multiple conditions for buy and sell signals:
- **Buy Signals**: Generated when certain conditions are met, such as the price moving above key EMAs, bullish PSAR flips, and bullish Heiken Ashi candles.
- **Sell Signals**: Generated when conditions like bearish PSAR flips, bearish candles, and price moving below EMAs are met.
- These signals are designed to guide traders on when to enter or exit trades.
6. **Alerts**
- The script comes with alert conditions, which can be used to set automated alerts for when buy or sell signals occur. This allows the trader to stay informed without constantly monitoring the chart.
### How It Works:
1. **EMA-Based Trend Identification:**
- EMAs help identify the overall market trend. For example, if the 8-period EMA crosses above the 21-period EMA, it signals a potential bullish trend. Conversely, if the 8 EMA crosses below the 21 EMA, it may signal a bearish trend.
2. **PSAR for Trend Reversals:**
- PSAR values provide insight into potential trend reversals. When the PSAR flips (moving from above to below the price or vice versa), the script highlights these flips as potential buy/sell signals.
3. **Combining Signals:**
- The script combines multiple indicators (EMAs, PSAR, and Heiken Ashi candles) to provide stronger confirmations of potential entry and exit points. By using multiple indicators, the script reduces the likelihood of false signals.
4. **Visual Overlay:**
- The script overlays key information on the price chart, such as EMAs and PSAR dots, which makes it easy for traders to visualize market conditions in real-time.
### Benefits of Using This Script:
1. **Trend Identification:**
- The combination of EMAs and PSAR helps traders identify trends early. The visual display of these indicators directly on the chart makes it easier to detect shifts in market sentiment.
2. **Smoothed Candlesticks:**
- By using Heiken Ashi candles, the script smooths out noisy price action, making it easier to spot trends and reduce the likelihood of making impulsive decisions based on short-term volatility.
3. **Buy and Sell Signals:**
- The script generates clear buy and sell signals based on a combination of multiple technical factors (EMAs, PSAR, and Heiken Ashi). This can help traders time their entries and exits more effectively.
4. **Multi-Timeframe Alerts:**
- With the built-in alert functionality, traders can set up alerts for specific signals (like a PSAR flip or EMA crossover) across different timeframes. This helps traders stay informed without having to watch the chart constantly.
5. **Session Management:**
- The ability to track different market sessions allows traders to focus on times of high liquidity and volatility, which are often the best times to trade.
6. **Customizability:**
- The script allows traders to customize the settings for each indicator (e.g., EMA lengths, PSAR settings, session times) according to their trading preferences.
### Use Cases:
- **Trend Trading:**
- Traders who follow market trends can benefit from this script as it uses EMAs and PSAR to identify trending conditions and potential trend reversals.
- **Swing Trading:**
- Swing traders looking to capitalize on medium-term market moves can use the script to identify optimal entry and exit points based on momentum shifts.
- **Intraday Trading:**
- The inclusion of market sessions and real-time alerts makes the script useful for intraday traders who want to focus on specific trading hours, such as the opening of the London or New York sessions.
Overall, this script is designed for traders who rely on technical indicators to guide their trading decisions. The combination of EMAs, PSAR, and Heiken Ashi candles provides a well-rounded view of market trends and potential entry/exit points, making it a powerful tool for traders looking to improve their strategy.
Price Movement > Custom Points with Day of WeekThe code is a TradingView Pine Script indicator designed to track and visualize price movements in a financial market (like stocks or cryptocurrencies) based on a specific point threshold. Here’s a breakdown of its functionality:
Purpose of the Code:
Price Movement Calculation: It calculates the difference between the closing price and the opening price of each bar (or candle) to determine if the price has moved significantly.
Threshold Input: The user can set a threshold (e.g., 500 points) to determine what constitutes a significant movement.
Movement Conditions:
Positive Movement: If the price movement is greater than the threshold, it’s marked as a positive movement.
Negative Movement: If the price movement is less than the negative threshold (i.e., below -500 points), it’s marked as a negative movement.
Day of the Week Identification: The script identifies the day of the week for each bar (Monday through Sunday).
Visual Output:
It plots shapes (like labels) on the chart:
For positive movements, it shows "YES" in green, indicating the movement exceeded the threshold for that day.
For negative movements, it shows "YES" in red, indicating the movement fell below the negative threshold for that day.
Use Cases:
Traders: It helps traders quickly identify days where significant price movements occurred, allowing them to analyze trends and make informed trading decisions.
Market Analysis: The indicator can be used for backtesting strategies based on significant price movements.
Overall, this code serves as a visual tool for analyzing price volatility in a market based on user-defined thresholds and day-based observations. If you have any specific questions or need further clarification about any part of it, feel free to ask!
Demand and Supply Conditions with SignalsIntroduction:
This document outlines a trading strategy that utilizes price action analysis and color signals to make informed trading decisions. The strategy focuses on identifying demand and supply conditions, curve patterns, and generating signals based on historical price data. The colors associated with each condition and signal serve as visual indicators to assist in decision-making.
I. Strategy Overview:
Objective:
The objective of this trading strategy is to identify potential trading opportunities based on price action analysis and color signals.
Key Components:
Demand Condition: A green upward-facing triangle indicates a potential demand condition.
Supply Condition: A red downward-facing triangle indicates a potential supply condition.
Curve Pattern Condition: A blue upward-facing triangle indicates a potential curve pattern condition.
Signal Condition: A yellow upward-facing triangle indicates a potential buy signal.
II. Understanding the Colors:
* Green: Represents the demand condition, which suggests potential buying pressure in the market. A green upward-facing triangle is plotted on the chart when the demand condition is met at a specific candle or bar.
* Red: Represents the supply condition, which suggests potential selling pressure in the market. A red downward-facing triangle is plotted on the chart when the supply condition is met at a specific candle or bar.
* Blue: Represents the curve pattern condition, which suggests the presence of a specific pattern based on price action analysis. A blue upward-facing triangle is plotted on the chart when the curve pattern condition is met at a specific candle or bar.
* Yellow: Represents the signal condition, which is a combination of the demand condition and the curve pattern condition. A yellow upward-facing triangle is plotted on the chart when the signal condition is met at a specific candle or bar, indicating a potential buy signal.
III. Decision-Making Process:
* Demand and Supply Conditions: Identify potential buying opportunities when a green demand condition is present. Consider potential selling opportunities when a red supply condition is present. Use these conditions to assess the overall market sentiment and potential price reversals.
* Curve Patterns: Analyze the presence of blue curve pattern conditions to identify specific price patterns. These patterns can provide additional confirmation for potential trading decisions.
* Signal Condition: Pay attention to the yellow signal condition, which indicates a potential buy signal. Evaluate the overall market context and consider entering a buy position when the signal condition is met.
* Risk Management: Implement proper risk management techniques such as setting stop-loss orders and position sizing to protect against potential losses.
IV. Conclusion:
This trading strategy leverages price action analysis and color signals to identify potential trading opportunities. The colors associated with each condition and signal serve as visual aids to highlight specific points on the chart. It's important to thoroughly backtest and validate the strategy before applying it to real-world trading scenarios. Additionally, always consider market conditions, risk management, and individual trading preferences when making trading decisions.
Disclaimer: Trading involves risks, and this document does not guarantee profitable outcomes. Traders should exercise caution and perform their own due diligence before engaging in any trading activity.
Remember to continually review and adapt your trading strategy based on market conditions and personal experiences to enhance its effectiveness.
E9 ASIA Session
*note: Upon updating the script the conversion from V4 to v5 has lost the weekend extended lines and now prints an asia session for each day. It is recommended (esp for crypto) to extend these lines across the weekend like in the chart example above.
The E9 Asia Session Indicator is a valuable tool for traders aiming to track and analyze the Asia trading session on financial charts. This indicator provides insights into price behavior during the Asia session, which is crucial for making informed trading decisions. Here's an overview of its key functionalities and uses:
1. Session Highs and Lows
Purpose:
The indicator calculates and plots the high and low of the Asia session.
It helps identify key levels of support and resistance established during this trading period.
Importance:
These levels can act as significant reference points for future price movements.
Price action that occurs near these levels often provides clues about potential breakouts or reversals.
2. Session Background Color
Purpose:
The indicator can shade the background of the chart during the Asia session.
Importance:
This visual cue helps quickly identify the session's timeframe, enhancing the trader’s ability to observe price behavior within this specific period.
It aids in distinguishing between different trading sessions and understanding their influence on price action.
3. Start of Session Marker
Purpose:
A visual marker (such as a circle) is plotted at the beginning of each Asia session.
Importance:
This marker helps traders visually pinpoint the start of the session, making it easier to analyze how the price reacts from the session's opening.
4. End of Session Marker
Purpose:
A marker is plotted at the end of the Asia session, indicating where the session closes.
Importance:
This marker is useful for tracking the end of the session and observing price behavior around this critical juncture.
It helps in analyzing whether the session's high or low gets revisited or broken in subsequent sessions.
Practical Uses:
Strategic Planning: Traders can use the plotted high and low levels to set their trading strategies, stop-loss orders, and profit targets.
Market Analysis: Understanding how price interacts with the Asia session’s high and low levels can provide insights into market sentiment and potential price movements.
By incorporating the E9 Asia Session Indicator into your trading toolkit, you can gain a deeper understanding of the Asia session's impact on price dynamics, enhancing your overall trading strategy and decision-making process.
Disclaimer: The information contained in this article does not constitute financial advice or a solicitation to buy or sell any securities. All investments involve risk, and past performance does not guarantee future results. Always evaluate your financial circumstances and investment objectives before making trading decisions.
Gaussian SWMA For LoopGaussian SWMA For Loop Indicator
The "Gaussian SWMA For Loop" is a sophisticated indicator designed to identify potential trading opportunities by combining a Gaussian-weighted moving average (WMA) with a simple moving average (SMA), enhanced by a loop-based scoring system. This indicator is tailored for traders looking to capture trends and reversals with a refined approach, making use of advanced filtering techniques and custom thresholds for signal generation.
Key Features:
1. Gaussian Weighted Moving Average (WMA):
The indicator starts by applying a Gaussian filter to the input price data (default is the closing price). The Gaussian filter smooths the data by applying weights according to a Gaussian distribution, determined by the Gaussian Sigma parameter. This results in a smooth, noise-reduced WMA, which is more responsive to significant price movements while ignoring minor fluctuations.
2. Simple Moving Average (SMA) on Smoothed Data:
After the data is smoothed using the Gaussian filter, an SMA is calculated over this smoothed data. The length of this SMA can be adjusted via the SMA Length input, allowing users to control the level of additional smoothing applied to the already filtered data.
3. Loop-Based Scoring System:
Range Analysis: The core feature of this indicator is the loop-based scoring system. It evaluates the filtered SMA by comparing its current value to previous values over a specified range, defined by the From and To parameters.
Score Calculation: The loop iterates through each value within the defined range and adjusts a score based on whether the current filtered SMA is higher or lower than its historical values. This score is a measure of the trend's strength and direction.
Thresholds for Signal Generation: Users can define custom thresholds for long (Long Threshold) and short (Short Threshold) signals. The score is compared against these thresholds to generate buy and sell signals.
4. Signal Generation:
Buy Signal (L): Triggered when the score exceeds the user-defined Long Threshold.
Sell Signal (S): Triggered when the score falls below the Short Threshold.
5. Visual Enhancements:
The indicator plots the filtered SMA on the chart, with the line and bar colors changing based on the buy and sell signals:
Teal (color.rgb(0, 255, 187)) for a buy signal.
Magenta (color.rgb(255, 0, 157)) for a sell signal.
Gray for a neutral condition.
Additionally, the fill between the current and previous SMA values is colored based on the signal, providing a clear visual cue for trend direction and strength.
6. Alert Conditions:
The indicator includes customizable alerts that notify the user when a buy or sell signal is generated:
Long Alert: Notifies when a buy signal is triggered.
Short Alert: Notifies when a sell signal is triggered.
Configurable Inputs:
Main Group:
WMA Length (length): Sets the length of the Gaussian-weighted moving average.
SMA Length (len): Specifies the period for the SMA applied to the Gaussian-smoothed data.
Source (src): The price data used for calculations (default is the closing price).
Gaussian Sigma (sigma): Determines the standard deviation of the Gaussian distribution, influencing the smoothing effect.
For Loop Group:
From (a): The starting point for the loop-based score analysis.
To (b): The endpoint for the loop-based score analysis.
Threshold Group:
Long Threshold (threshold_L): Defines the score threshold above which a buy signal is triggered.
Short Threshold (threshold_S): Defines the score threshold below which a sell signal is triggered.
Practical Use:
This indicator is ideal for traders who want to identify trends and potential reversals with precision. The combination of Gaussian smoothing, SMA, and the loop-based scoring system offers a robust method to filter out noise and focus on significant market moves. The customizable thresholds and alert system further enhance its utility, making it a powerful tool for both manual and automated trading strategies.
Note: As with any trading indicator, it's recommended to backtest the "Gaussian SWMA For Loop" under various market conditions and use it in conjunction with other analysis techniques to confirm signals before making trading decisions.
Birdies [LuxAlgo]The Birdies indicator uses a unique technique to provide support/resistance curves based on a circle connecting the last swing high/low.
A specific, customizable part of this circle acts as a curve of interest, which can trigger visual breakout signals.
🔶 USAGE
The script projects a bird-like pattern when a valid Swing point is found. Multiple customization options are included.
🔹 Trend & Support/Resistance Tool
The color fill patterns and the wing boundaries can give insights into the current trend direction as well as serve as potential support/resistance areas.
In the example above, "Birdies" coincide with pullback and support/resistance zones.
🔹 Swing Length & Buffer
Besides the "Swing Length", with higher values returning longer-term Swing Levels, the script's behavior can be fine-tuned with filters ("Settings" - "Validation").
🔹 Validation
To minimize clutter, three filters are included:
Minimum X-Distance: The minimum amount of bars between subsequent Swings
Minimum Y-Distance: The minimum amount of bars between subsequent Swings
Buffer (Multiple of ATR)
The "Minimum X/Y-Distance" creates a zone where a new Swing is considered invalid. Only when the Swing is out of the zone, can it be considered valid.
In other words, in the example above, a Swing High can only be valid when enough bars/time have passed, and the difference between the last Swing and the previous is more than the ATR multiplied by the "Minimum Y-Distance" factor.
The "Buffer" creates a line above/below the "Birdy", derived from the measured ATR at the conception of the "Birdy" multiplied with a factor ("Buffer").
When the closing price crosses the "Birdy", it must also surpass this buffer line to produce a valid signal, lowering the risk of clutter as a result.
🔶 DETAILS
Birdies are derived from a circle that connects two Swing points. The left-wing curve originates from the most recent "Swing point" to the last value on the circle before crossing its midline. The mirror image of the left wing creates the right wing.
Enabling "Origine" will draw a line from the last Swing to the first.
🔹 Style
The publication includes a style setting with four options.
The first, "Birdy," shows a bird-like shape derived from a circle connecting the last Swing High and Swing Low.
The second option holds everything from the first option but connects both wingtips, providing potential horizontal levels of interest.
When setting "Birdy" to "None", the visual breakout signals will not defer from previous settings, but the focus is shifted towards the fill color, which can help detect potential trend shift.
A fourth setting, "Left Wing", will only show the left part of the "Birdy" pattern, removing the right part from the equation. This will change the visual breakout signals, providing alternative signals.
🔶 SETTINGS
Swing Length: The period used for swing detection, with higher values returning longer-term Swing Levels.
🔹 Validation
Minimum X-Distance: The minimum amount of bars between subsequent Swings
Minimum Y-Distance: The minimum amount of bars between subsequent Swings
Buffer (Multiple of ATR)
🔹 Style
Bullish Patterns: Enable / color
Bearish Patterns: Enable / color
Buffer Zone: Show / Color
Color Fill: Show color fill between two Birdies (if available)
Origine: Show the line between both Swing Points
🔹 Calculation
Calculated Bars: Allows the usage of fewer bars for performance/speed improvement
Absolute ZigZagThis ZigZag Indicator is a bit unique in it's kind.
It uses my own Absolute ZigZag Lib to calculate the pivots:
Instead of using percentages or looking more than 1 bar left or right, this Zigzag library calculates pivots by just looking at the current bar highs and lows and the ones of one bar earlier. This is a very fast and accurate way of calculating pivots.
The library also features a solution for bars that have both a higher high and a higher low like seen below.
You can also use your own colors for the labels and the lines:
You can also quickly select a one-colored theme without changing all colors at once:
MultiTimeFrame Trends and Candle Bias (by MC) v1This MultiTimeFrame Trends and Candle Bias provides the trader a quick glance on how each timeframe is trending and what the current candle bias is in each timeframe.
Interpreting Candle Bias : Green points to a bullish bias while red, a bearish bias for a given specific timeframe. For instance, if the current 1 hour candle bias is red, it means that the last hour, the bias has been bearish. If the Daily candle bias is red, it means that the day in question has been a bearish for this selected symbol.
Interpreting MTF Trends: Trends for each time frame follows the simple moving average of the closing prices for the X number of candles you enter in the input section. So for example, if you decide to enter 6 for the 1-hour time frame, the trend for the last 6 hours will be shown and tracked; if on the Daily time frame, you enter 7, the trend for the last 7 days or 1 week will be shown and tracked. I have provided below (as well as on tooltips in the input section of this indicator) recommendations of what numbers to use depending on what kind of trader you are.
What is a best setup for MultiTimeFrame Trends?
Considerations Across All Timeframes:
- Trading Style : Scalpers and very short-term intraday traders may prefer fewer candles (like 12 to 20), which allow them to react quickly to price changes. Swing traders or those holding positions for a few hours to a couple of days might prefer more candles (like 50 to 120) to identify more stable trends.
- Market Conditions : In volatile markets, using more candles helps smooth out price fluctuations and provides a clearer trend signal. In trending markets, fewer candles might be sufficient to capture the trend.
- Session-Based Adjustments : Traders may adjust their settings depending on the time of day or session they are trading. For example, during high-volatility periods like market open or close, using fewer candles can help capture quick moves.
The number of preceding candles to use for estimating the recent trend can depend on various factors, including the type of market, the asset being traded, the timeframe, and the specific goals of your analysis. However, here are some general guidelines to help you decide:
### 1. **Short-Term Trends (Fast Moving Averages):**
- **5 to 20 Candles**: If you want to capture a short-term trend, typically in day trading or scalping strategies, you might use 5 to 20 candles. This is common for fast-moving averages like the 9-period or 15-period moving averages. It reacts quickly to price changes, but it can also give more false signals due to market noise.
### 2. **Medium-Term Trends (Moderate Moving Averages):**
- **20 to 50 Candles**: For a more balanced approach that reduces the impact of short-term volatility while still being responsive to trend changes, 20 to 50 candles are commonly used. This range is popular for swing trading strategies, where the goal is to capture trends that last several days to weeks.
### 3. **Long-Term Trends (Slow Moving Averages):**
- **50 to 200 Candles**: To identify long-term trends, such as those seen in position trading or for confirming major trend directions, you might use 50 to 200 candles. The 50-period and 200-period moving averages are particularly well-known and are often used by traders to identify significant trend reversals or confirmations.
### 4. **Adaptive Approach:**
- **Market Conditions**: In trending markets, fewer candles might be needed to identify a trend, while in choppy or range-bound markets, using more candles can help filter out noise.
- **Volatility**: In highly volatile markets, more candles might be necessary to smooth out price action and avoid false signals.
### **Experiment and Backtesting:**
The optimal number of candles can vary significantly based on the asset and strategy. It's often a good idea to backtest different periods to see which provides the best balance between responsiveness and reliability in identifying trends. You can use tools like the strategy tester in TradingView or other backtesting software to compare the performance of different settings.
### **General Recommendation:**
- **For Shorter Timeframes** (e.g., 5m, 15m): 10-20 candles might be effective.
- **For Medium Timeframes** (e.g., 1h, 4h): 20-50 candles are often a good starting point.
- **For Longer Timeframes** (e.g., Daily, Weekly): 50-200 candles help capture major trends.
If you're unsure, a common starting point for many traders is the 20-period moving average, which provides a balance between sensitivity and reliability.
Guidelines for 1-Minute Timeframe:
For the 1-minute (1M) timeframe, trend analysis typically focuses on very short-term price movements, which is crucial for scalping and ultra-short-term trading strategies. Here’s a breakdown of the number of preceding candles you might use:
1. **Very Short-Term Trend:**
- **10 to 20 Candles (10 to 20 Minutes):** Using 10 to 20 candles captures about 10 to 20 minutes of price action. This range is suitable for scalpers who need to identify very short-term trends and make quick trading decisions.
2. **Short-Term Trend:**
- **30 to 60 Candles (30 to 60 Minutes):** This period covers 30 to 60 minutes of trading, making it useful for traders looking to understand the trend over a full trading hour. It helps capture price movements and trends that develop within a single hour.
3. **Intraday Trend:**
- **120 Candles (2 Hours):** Using 120 candles provides a view of the trend over approximately 2 hours. This is useful for traders who want to see how the market is trending throughout a larger portion of the trading day.
4. **Extended Intraday Trend:**
- **240 to 480 Candles (4 to 8 Hours):** This longer period gives a broader view of the intraday trend, covering 4 to 8 hours. It’s helpful for identifying trends that span a significant portion of the trading day, which can be useful for traders looking to align with the broader intraday movement.
**Considerations:**
- **High Sensitivity:** The 1-minute timeframe is highly sensitive to market movements, so shorter periods (10 to 20 candles) can capture rapid price changes but may also generate noise.
- **Market Volatility:** In highly volatile markets, using more candles (like 30 to 60 or more) helps smooth out the noise and provides a clearer trend signal.
- **Trading Style:** Scalpers will typically use shorter periods to make very quick decisions. Traders holding positions for a bit longer, even within the same day, may use more candles to get a clearer picture of the trend.
**Common Approaches:**
- **5-Period Moving Average:** The 5-period moving average on a 1-minute chart can be used for extremely short-term trend signals, reacting quickly to price changes.
- **20-Period Moving Average:** The 20-period moving average is a good choice for capturing short-term trends and can help filter out some of the noise while still being responsive.
- **50-Period Moving Average:** The 50-period moving average provides a broader view of the trend and can help smooth out price movements over a longer intraday period.
**Recommendation:**
- **Start with 10 to 20 Candles:** For the most immediate and actionable signals, especially useful for scalping or very short-term trading.
- **Use 30 to 60 Candles:** For a clearer view of trends that develop over an hour, suitable for those looking to trade within a single trading hour.
- **Consider 120 Candles:** For observing broader intraday trends over 2 hours, helping align trades with more significant intraday movements.
- **Explore 240 to 480 Candles:** For a longer intraday perspective, covering up to 8 hours, which can be useful for strategies that span a larger portion of the trading day.
**Practical Example:**
- **Scalpers:** If you’re executing trades every few minutes, start with 10 to 20 candles to get rapid trend signals.
- **Short-Term Traders:** For trends that last an hour or so, 30 to 60 candles will provide a better sense of direction while still being responsive.
- **Intraday Traders:** For broader trends that span several hours, 120 candles will help you see the overall intraday movement.
Experimentation and backtesting with these settings on historical data will help you fine-tune your approach to the 1-minute timeframe for your specific trading strategy and asset.
Guidelines for 5, 15 and 30 min Timeframes:
For shorter timeframes like 5, 15, and 30 minutes, the number of preceding candles you use will depend on how quickly you want to react to changes in the trend and the specific trading style you’re employing. Here's a breakdown for each:
**5-Minute Timeframe:**
1. **Very Short-Term (Micro Trend):**
- **12 to 20 Candles (60 to 100 Minutes):** Using 12 to 20 candles on a 5-minute chart captures 1 to 1.5 hours of price action. This is ideal for very short-term trades, such as scalping, where quick entries and exits are key.
2. **Short-Term Trend:**
- **30 to 60 Candles (150 to 300 Minutes):** This period covers 2.5 to 5 hours, making it useful for intraday traders who want to identify the trend within a trading session. It helps capture the direction of the market during the most active parts of the day.
3. **Intra-Day Trend:**
- **120 Candles (10 Hours):** Using 120 candles gives you a broad view of the trend over two trading sessions. This is useful for traders who want to understand the trend throughout the entire trading day.
**15-Minute Timeframe:**
1. **Very Short-Term:**
- **12 to 20 Candles (3 to 5 Hours):** On a 15-minute chart, this period covers 3 to 5 hours, making it useful for capturing the morning or afternoon trend within a trading day. It’s often used by intraday traders who need to make quick decisions.
2. **Short-Term Trend:**
- **30 to 60 Candles (7.5 to 15 Hours):** This covers almost a full trading day to a day and a half. It’s popular among day traders who want to align their trades with the trend of the day or the previous trading session.
3. **Intra-Week Trend:**
- **120 Candles (30 Hours):** This period spans about two trading days and is useful for traders looking to capture trends that may extend beyond a single trading day but not necessarily for an entire week.
**30-Minute Timeframe:**
1. **Short-Term Trend:**
- **12 to 20 Candles (6 to 10 Hours):** This period captures the trend over a single trading session. It's useful for day traders who want to understand the market’s direction throughout the day.
2. **Medium-Term Trend:**
- **30 to 50 Candles (15 to 25 Hours):** This period covers about two trading days and is useful for short-term swing traders or intraday traders who are looking for trends that might last a couple of days.
3. **Intra-Week Trend:**
- **100 to 120 Candles (50 to 60 Hours):** This longer period captures about 4 to 5 trading days, making it useful for traders who want to understand the broader trend over the course of the week.
**Summary Recommendations:**
- **5-Minute Chart:**
- **12 to 20 candles** for very short-term trades.
- **30 to 60 candles** for intraday trends within a single session.
- **120 candles** for a broader view of the day’s trend.
- **15-Minute Chart:**
- **12 to 20 candles** for short-term trades within a few hours.
- **30 to 60 candles** for trends lasting a full day or more.
- **120 candles** for trends extending over a couple of days.
- **30-Minute Chart:**
- **12 to 20 candles** for understanding the daily trend.
- **30 to 50 candles** for trends over a couple of days.
- **100 to 120 candles** for an intra-week trend view.
Experimenting with these settings and backtesting on historical data will help you find the optimal number of candles for your specific trading style and the assets you trade.
Guidelines for 1H Timeframes:
When analyzing trends on a 1-hour (1H) timeframe, you're focusing on short to medium-term trends, often used by day traders and short-term swing traders. Here’s how you can approach selecting the number of preceding candles:
1. **Short-Term Trend:**
- **14 to 21 Candles (14 to 21 Hours):** Using 14 to 21 candles on a 1-hour chart captures roughly half a day to a full day of trading activity. This range is ideal for day traders who want to identify short-term momentum and trend changes within a single trading day.
2. **Medium-Term Trend:**
- **50 Candles (2 Days):** A 50-period moving average on a 1-hour chart covers about two days of trading. This period is popular for identifying trends that may last a couple of days, making it useful for short-term swing traders.
3. **Longer-Term Trend:**
- **100 Candles (4 Days):** Using 100 candles gives you a broader view of the trend over about four days of trading. This is helpful for traders who want to align their trades with a more sustained trend that spans the entire week.
4. **Very Short-Term (Micro Trend):**
- **7 to 10 Candles (7 to 10 Hours):** For traders looking to capture micro trends or very short-term price movements, using 7 to 10 candles can provide a quick look at recent price action. This is often used for scalping or very short-term intraday strategies.
**Considerations:**
- **Market Volatility:** In highly volatile markets, using more candles (like 50 or 100) helps smooth out noise and provides a clearer trend signal. In less volatile conditions, fewer candles may suffice to capture trends.
- **Trading Style:** If you are a day trader looking for quick moves, shorter periods (like 7 to 21 candles) might be more suitable. For those who hold positions for a day or two, longer periods (like 50 or 100 candles) can provide better trend confirmation.
- **Asset Class:** The optimal number of candles can vary depending on the asset
Guidelines for 4H Timeframes:
When analyzing trends on a 4-hour (4H) timeframe, you’re generally looking to capture short to medium-term trends. This timeframe is popular among swing traders and intraday traders who want to balance between catching more significant market moves and not being too sensitive to noise. Here's how you can approach selecting the number of preceding candles:
1. **Short-Term Trend:**
- **14 to 21 Candles (2 to 3 Days):** Using 14 to 21 candles on a 4-hour chart covers roughly 2 to 3 days of trading activity. This range is ideal for traders looking to capture short-term momentum, especially in markets where price action can move quickly within a few days.
2. **Medium-Term Trend:**
- **50 Candles (8 to 10 Days):** A 50-period moving average on a 4-hour chart represents approximately 8 to 10 days of trading (considering 6 trading periods per day). This period is popular among swing traders for identifying trends that develop over the course of one to two weeks.
3. **Longer-Term Trend:**
- **100 Candles (16 to 20 Days):** Using 100 candles gives you a broader view of the trend over about 3 to 4 weeks. This is useful for traders who want to align their trades with the more sustained market direction while still remaining responsive to recent changes.
**Considerations:**
- **Market Conditions:** In a trending market, fewer candles (like 14 or 21) may be enough to identify the trend, allowing for quicker responses to price movements. In a more volatile or range-bound market, using more candles (like 50 or 100) can help smooth out noise and avoid false signals.
- **Trading Style:** If you are an intraday trader, shorter periods (14 to 21 candles) may be preferable, as they allow for quick entries and exits. Swing traders might lean towards the 50 to 100 candle range to capture trends that last several days to a few weeks.
- **Volatility:** The higher the volatility of the asset, the more candles you might want to use to ensure that the trend signal is not too erratic.
**Common Approaches:**
- **20-Period Moving Average:** A 20-period moving average on a 4-hour chart is often used by traders to capture short-term trends that align with momentum over the past few days.
- **50-Period Moving Average:** The 50-period moving average is widely used on the 4-hour chart to track medium-term trends. It provides a good balance between reacting to new trends and avoiding too many whipsaws.
- **100-Period Moving Average:** The 100-period moving average offers insight into the longer-term trend on the 4-hour chart, helping to filter out short-term noise and confirm the overall market direction.
**Recommendation:**
- **Start with 20 Candles for Short-Term Trends:** This period is useful for capturing quick movements and short-term trends over a couple of days.
- **Use 50 Candles for Medium-Term Trends:** This is a standard setting that provides a balanced view of the market over about 1 to 2 weeks.
- **Consider 100 Candles for Longer-Term Trends:** This helps to identify more significant trends that have persisted for a few weeks.
**Practical Example:**
- **Intraday Traders:** If you’re focused on shorter-term trades and need to react quickly, using 14 to 21 candles will help you capture the most recent momentum.
- **Swing Traders:** If you’re looking to hold positions for several days to a few weeks, starting with 50 candles will give you a clearer picture of the trend over that period.
- **Position Traders:** For those holding positions for a longer duration within a month, using 100 candles helps to align with the broader trend while still being responsive enough for 4-hour price movements.
Backtesting these settings on your chosen asset and strategy will help refine the optimal number of candles for your specific needs.
Guidelines for Daily Timeframes:
When analyzing trends on a daily timeframe, you're typically focusing on short to medium-term trends. Here’s how you can determine the optimal number of preceding candles:
1. **Short-Term Trend:**
- **10 to 20 Candles (2 to 4 Weeks):** Using 10 to 20 daily candles captures about 2 to 4 weeks of price action. This is commonly used for identifying short-term trends, ideal for swing traders or those looking for quick entries and exits within a month.
2. **Medium-Term Trend:**
- **50 Candles (2 to 3 Months):** The 50-day moving average is a classic choice for capturing medium-term trends. This period covers about 2 to 3 months of trading days and is often used by swing traders and investors to identify the trend over a quarter or a season.
3. **Long-Term Trend:**
- **100 to 200 Candles (4 to 9 Months):** For longer-term trend analysis, using 100 to 200 daily candles gives you a broader perspective, covering approximately 4 to 9 months of price action. The 200-day moving average, in particular, is widely used by investors to determine the overall long-term trend and to assess market health.
**Considerations:**
- **Market Volatility:** In more volatile markets, using a larger number of candles (e.g., 50 or 200) helps smooth out noise and provides a more reliable trend signal. In less volatile markets, fewer candles might be sufficient to capture trends effectively.
- **Trading Style:** Day traders might prefer shorter periods (like 10 or 20 candles) for quicker signals, while position traders and longer-term swing traders might opt for 50 to 200 candles to focus on more sustained trends.
- **Asset Class:** The optimal number of candles can also depend on the asset class. For example, equities might have different optimal settings compared to forex or cryptocurrencies due to different volatility characteristics.
**Common Approaches:**
- **20-Period Moving Average:** The 20-day moving average is a popular choice for short-term trend analysis. It’s widely used by traders to identify the short-term direction and to make quick trading decisions.
- **50-Period Moving Average:** The 50-day moving average is a staple for medium-term trend analysis, often used as a key indicator for both entry and exit points in swing trading.
- **200-Period Moving Average:** The 200-day moving average is crucial for long-term trend identification. It's commonly used by investors and is often seen as a major support or resistance level. When the price is above the 200-day moving average, the market is generally considered to be in a long-term uptrend, and vice versa.
**Recommendation:**
- **Start with 20 Candles for Short-Term Trends:** This period is commonly used for identifying recent trends within the last few weeks.
- **Use 50 Candles for Medium-Term Trends:** This provides a good balance between responsiveness and stability, making it a good fit for most swing trading strategies.
- **Use 200 Candles for Long-Term Trends:** This period is ideal for long-term analysis and is particularly useful for investors looking at the overall market trend.
**Practical Example:**
- If you’re trading equities and want to catch short-term trends, start with 20 candles to identify trends that have developed over the past month.
- If you’re more focused on medium to long-term trends, consider using 50 or 200 candles to ensure you’re aligned with the broader market direction.
Experimenting with these periods and backtesting on historical data will help you determine the best setting for your particular strategy and the asset you're analyzing.
Guidelines for Weekly Timeframes:
When analyzing trends on a weekly timeframe, you're typically looking at intermediate to long-term trends. Here's how you might approach selecting the number of preceding candles:
1. **Intermediate-Term Trend:**
- **13 to 26 Candles (3 to 6 Months):** Using 13 to 26 weekly candles corresponds to a period of 3 to 6 months. This range is effective for identifying intermediate-term trends, which is suitable for swing traders or those looking to hold positions for several weeks to a few months.
2. **Medium-Term Trend:**
- **26 to 52 Candles (6 Months to 1 Year):** For a broader view, you might use 26 to 52 weekly candles. This represents 6 months to 1 year of price data, which is helpful for understanding the market’s behavior over a medium-term period. This range is commonly used by swing traders and position traders who are interested in capturing trends lasting several months.
3. **Long-Term Trend:**
- **104 Candles (2 Years):** Using 104 weekly candles gives you a 2-year perspective. This can be useful for long-term trend analysis, particularly for investors or those looking to identify major trend reversals or continuations over a more extended period.
**Considerations:**
- **Market Type:** In trending markets, fewer candles (like 13 or 26) may work well, capturing the trend more quickly. In choppier or range-bound markets, using more candles can help reduce noise and avoid false signals.
- **Asset Class:** The optimal number of candles can vary depending on the asset class. For example, equities might benefit from a slightly shorter lookback period compared to more volatile assets like commodities or cryptocurrencies.
- **Volatility:** If the market or asset you're analyzing is highly volatile, using a higher number of candles (like 52 or 104) can help smooth out price fluctuations and provide a more stable trend signal.
**Common Approaches:**
- **20-Period Moving Average:** A 20-week moving average is popular among traders for identifying the intermediate trend. It’s responsive enough to capture significant trend changes while filtering out short-term noise.
- **50-Period Moving Average:** The 50-week moving average is often used to identify longer-term trends and is commonly referenced in both technical analysis and by longer-term traders.
- **200-Period Moving Average:** Although less common on weekly charts compared to daily charts, a 200-week moving average can be used to identify very long-term trends, such as multi-year market cycles.
**Recommendation:**
- **Start with 26 Candles:** This gives you a half-year perspective and is a good starting point for most analyses on a weekly timeframe. It balances sensitivity to recent trends with the ability to capture more significant, sustained movements.
- **Adjust Based on Backtesting:** You can increase the number of candles to 52 if you find that you need more stability in the trend signal, or decrease to 13 if you're looking for a more responsive signal.
Experimenting with different periods and backtesting on historical data can help determine the best setting for your specific strategy and asset class.
Guidelines for Monthly Timeframes:
For analyzing trends on monthly timeframes, you would generally be looking at much longer periods to capture the broader, long-term trend. Here's how you can approach it:
1. **Long-Term Trend (Primary Trend):**
- **12 to 24 Candles (1 to 2 Years):** Using 12 to 24 monthly candles corresponds to a period of 1 to 2 years. This is typically sufficient to identify long-term trends and is commonly used by long-term investors or position traders who are interested in the overall direction of the market or asset over multiple years.
2. **Very Long-Term Trend (Secular Trend):**
- **36 to 60 Candles (3 to 5 Years):** To capture very long-term secular trends, you might use 36 to 60 monthly candles. This would represent a time frame of 3 to 5 years and is often used for understanding macroeconomic trends or very long-term investment strategies.
3. **Ultra Long-Term Trend:**
- **120 Candles (10 Years):** In some cases, especially for assets like indices or commodities that are analyzed over decades, using 120 monthly candles can help in identifying ultra long-term trends. This would be appropriate for strategic investors or those looking at generational market cycles.
**Considerations:**
- **Volatility and Stability:** Monthly timeframes generally smooth out short-term volatility, but they can also be slow to react to changes. Using a larger number of candles (e.g., 24 or more) can help ensure that the trend signal is robust and not prone to frequent whipsaws.
- **Asset Class:** The choice of period might also depend on the asset class. For instance, equities might require fewer candles compared to commodities or currencies, which can exhibit different trend dynamics.
- **Market Phases:** In different market phases (bullish, bearish, or sideways), the number of candles might need to be adjusted. For instance, in a strongly trending market, fewer candles might still provide a reliable trend indication, whereas in a more volatile or ranging market, more candles might be needed to smooth out the data.
**Common Approaches:**
- **50-Period Moving Average:** A 50-month moving average is popular among long-term traders and investors for identifying the primary trend. It offers a balance between capturing the overall trend and being responsive enough to significant changes.
- **200-Period Moving Average:** Although rarely used on a monthly chart due to the long timeframe it represents (over 16 years), it can be useful for identifying very long-term secular trends, especially for broad market indices or in macroeconomic analysis.
**Recommendation:**
- **Start with 24 Candles:** This gives you a 2-year perspective on the trend and is a good starting point for most long-term analyses on monthly charts. Adjust upwards if you need a broader trend view, depending on the stability and nature of the asset you're analyzing.
Experimentation and backtesting with your specific asset and strategy can help fine-tune the exact number of candles that work best for your analysis on a monthly timeframe.
Time based Insights [Digit23]Description:
The NSE Trading Time Insights indicator is a powerful tool designed for traders on the National Stock Exchange (NSE) of India. It provides a comprehensive overview of different trading sessions throughout the day, offering valuable insights into market characteristics and potential trading strategies for each time period.
Key Features:
1. Dynamic Session Display: The indicator automatically detects the current trading session and highlights it in the table.
2. Customizable Table: Users can choose to display either a full table showing all sessions or focus on the current session only.
3. User-Editable Content: Time ranges, session characteristics, and trading insights are fully customizable by the user.
4. Visual Customization: Table position and color scheme can be adjusted to suit individual preferences.
5. Market Status Indicator: Clearly shows when the market is closed.
Sessions Covered:
1. Opening Bell
2. Mid-Morning
3. Lunch Hour
4. Early Afternoon
5. Power Hour
For each session, the indicator displays:
- Time Range
- Session Name
- Market Characteristics
- Trading Insights
Customization Options:
- Table Position: Choose from top-left, top-right, bottom-left, or bottom-right of the chart.
- Color Scheme: Customize colors for header, cells, highlighting, and market closed status.
- Session Details: Edit time ranges, characteristics, and trading insights for each session.
Usage:
This indicator is particularly useful for:
1. New traders learning about intraday market dynamics on the NSE.
2. Experienced traders looking for a quick reference of session characteristics.
3. Traders developing or refining time-based trading strategies.
4. Anyone seeking to understand the typical flow of the trading day on the NSE.
Note:
The indicator uses the chart's time to determine the current session. Ensure your chart is set to the correct time zone for accurate results.
Disclaimer:
This indicator is for informational purposes only. The provided insights and characteristics are general in nature and may not reflect current market conditions. Always conduct your own analysis and risk assessment before making trading decisions.
Dynamic Resistance and Support LinesThis script is designed to dynamically plot support and resistance lines based on full-dollar and half-dollar price levels relative to the close price on a chart. The script is particularly useful for day traders and scalpers, as it helps visualize key psychological price levels that often act as support and resistance zones in volatile and fast-moving markets in real time.
Key Features:
Dynamic Resistance and Support Levels:
Full-dollar levels: These are calculated by rounding the close price to the nearest full dollar and then extending the levels by adding and subtracting increments of 1 (e.g., $1, $2, $3).
Half-dollar levels: These are calculated by adding and subtracting 0.5 increments to the nearest full-dollar price, providing additional reference points. The historical full-dollar levels remain where support and resistance may have occurred in the past.
Extend Lines:
You can toggle whether the support and resistance lines are extended to the right, left, or both directions. This allows flexibility in projecting potential future areas of support or resistance.
Custom Line Extension:
The user can set the number of bars (or time periods) that the support and resistance lines will extend, giving control over how long the levels remain on the chart.
Color-Coded Lines:
Red lines represent full-dollar resistance and support levels.
Blue lines represent half-dollar levels, making it easy to differentiate between key psychological price zones.
Line Flexibility:
The script allows the lines to extend both left and right on the chart, making it useful for analyzing historical price action or projecting future price movements. The number of bars for extension is customizable, allowing for tailored setups.
Nearest Full Dollar Plot:
The nearest full-dollar price level is plotted as a yellow circle on the chart. This serves as a quick visual cue for traders to monitor price proximity to critical levels.
Benefits in Day Trading, Scalping, and Volatile Markets:
Visualizing Key Psychological Levels:
Full-dollar and half-dollar price levels often act as psychological barriers for traders. This script helps traders easily identify these levels, which are important in both fast-moving markets and during sideways consolidation.
Improved Decision-Making:
By automatically drawing these support and resistance levels, the script helps day traders and scalpers make quicker and more informed decisions, especially in volatile markets where every second counts.
Adaptability to Market Conditions:
The flexibility of extending lines based on trader preferences allows the user to adapt the script to various market conditions, such as high volatility or trend-based trading, providing a clear view of potential breakout or reversal areas.
Better Risk Management:
Having predefined support and resistance levels helps traders better manage risk, as these levels can act as logical areas for setting stop losses or taking profits.
This script is especially valuable for traders looking to capitalize on quick market movements or identify key entry and exit points during market volatility.
Institutional Levels (Whole, Half, Quarter) By CapitalwithcalebThis Pine Script indicator is designed to plot institutional levels, which are key price levels that traders often monitor. These levels include whole numbers (like 12000, 12500), half levels (like 12250), and quarter levels (like 12375). The script allows full customization of colors, line styles, and line widths for each type of level (whole, half, and quarter).
Key Features:
Range of Levels:
The user defines a minimum (minLevel) and maximum (maxLevel) price level, and the script plots levels in increments of 50 points (step size of 50 covers quarter, half, and whole levels).
Customizable Appearance:
Color Customization: You can choose separate colors for whole, half, and quarter levels.
Line Style Customization: You can choose between solid, dashed, or dotted lines for each level type (whole, half, and quarter).
Line Width Customization: You can adjust the width of the lines (1 to 5).
Automatic Level Detection:
The script automatically determines whether a level is a whole, half, or quarter level based on whether it is a multiple of 1000 (whole), 500 (half), or 250 (quarter).
Plotting of Lines:
It draws horizontal lines across the entire chart (extend.both) at the calculated levels.
For each level, it determines its type (whole, half, quarter) and plots it using the user-specified colors, line styles, and widths.
Functions:
getLineStyle(styleStr): A functional helper that converts the string input from the user ("Solid", "Dashed", "Dotted") into Pine Script's corresponding line style constants.
plotLevel(level, color, width, style): Another functional helper that plots a line at the given price level with the provided color, width, and line style.
Execution Flow:
User Input: The user specifies the minimum and maximum levels to display on the chart. They also configure the appearance of the lines (color, style, width).
Level Calculation: The script iterates over all levels between the minLevel and maxLevel with a step size of 50, checking if the level is a whole, half, or quarter level.
Line Plotting: The appropriate lines are drawn on the chart, based on the type of level and user settings.
Example Use Case:
If a user sets the minLevel to 12000 and maxLevel to 13000, the script will automatically plot lines at key institutional levels like:
12000 (whole), 12250 (quarter), 12500 (whole), 12750 (quarter), etc.
H-Infinity Volatility Filter [QuantAlgo]Introducing the H-Infinity Volatility Filter by QuantAlgo 📈💫
Enhance your trading/investing strategy with the H-Infinity Volatility Filter , a powerful tool designed to filter out market noise and identify clear trend signals in volatile conditions. By applying an advanced H∞ filtering process, this indicator assists traders and investors in navigating uncertain market conditions with improved clarity and precision.
🌟 Key Features:
🛠 Customizable Noise Parameters: Adjust worst-case noise and disturbance settings to tailor the filter to various market conditions. This flexibility helps you adapt the indicator to handle different levels of market volatility and disruptions.
⚡️ Dynamic Trend Detection: The filter identifies uptrends and downtrends based on the filtered price data, allowing you to quickly spot potential shifts in the market direction.
🎨 Color-Coded Visuals: Easily differentiate between bullish and bearish trends with customizable color settings. The indicator colors the chart’s candles according to the detected trend for immediate clarity.
🔔 Custom Alerts: Set alerts for trend changes, so you’re instantly informed when the market transitions from bullish to bearish or vice versa. Stay updated without constantly monitoring the charts.
📈 How to Use:
✅ Add the Indicator: Add the H-Infinity Volatility Filter to your favourites and apply it to your chart. Customize the noise and disturbance parameters to match the volatility of the asset you are trading/investing. This allows you to optimize the filter for your specific strategy.
👀 Monitor Trend Shifts: Watch for clear visual signals as the filter detects uptrends or downtrends. The color-coded candles and line plots help you quickly assess market conditions and potential reversals.
🔔 Set Alerts: Configure alerts to notify you when the trend changes, allowing you to react quickly to potential market shifts without needing to manually track price movements.
🌟 How It Works and Academic Background:
The H-Infinity Volatility Filter is built on the foundations of H∞ (H-infinity) control theory , a mathematical framework originating from the field of engineering and control systems. Developed in the 1980s by notable engineers such as George Zames and John C. Doyle , this theory was designed to help systems perform optimally under uncertain and noisy conditions. H∞ control focuses on minimizing the worst-case effects of disturbances and noise, making it a powerful tool for managing uncertainty in complex environments.
In financial markets, where unpredictable price fluctuations and noise often obscure meaningful trends, this same concept can be applied to price data to filter out short-term volatility. The H-Infinity Volatility Filter adopts this approach, allowing traders and investors to better identify potential trends by reducing the impact of random price movements. Instead of focusing on precise market predictions, the filter increases the probability of highlighting significant trends by smoothing out market noise.
This indicator works by processing historical price data through an H∞ filter that continuously adjusts based on worst-case noise levels and disturbances. By considering several past states, it estimates the current price trend while accounting for potential external disruptions that might influence price behavior. Parameters like "worst-case noise" and "disturbance" are user-configurable, allowing traders to adapt the filter to different market conditions. For example, in highly volatile markets, these parameters can be adjusted to manage larger price swings, while in more stable markets, they can be fine-tuned for smoother trend detection.
The H-Infinity Volatility Filter also incorporates a dynamic trend detection system that classifies price movements as bullish or bearish. It uses color-coded candles and plots—green for bullish trends and red for bearish trends—to provide clear visual cues for market direction. This helps traders and investors quickly interpret the trend and act on potential signals. While the indicator doesn’t guarantee accuracy in trend prediction, it significantly reduces the likelihood of false signals by focusing on meaningful price changes rather than random fluctuations.
How It Can Be Applied to Trading/Investing:
By applying the principles of H∞ control theory to financial markets, the H-Infinity Volatility Filter provides traders and investors with a sophisticated tool that manages uncertainty more effectively. Its design makes it suitable for use in a wide range of markets—whether in fast-moving, volatile environments or calmer conditions.
The indicator is versatile and can be used in both short-term trading and medium to long-term investing strategies. Traders can tune the filter to align with their specific risk tolerance, asset class, and market conditions, making it an ideal tool for reducing the effects of market noise while increasing the probability of detecting reliable trend signals.
For investors, the filter can help in identifying medium to long-term trends by filtering out short-term price swings and focusing on the broader market direction. Whether applied to stocks, forex, commodities, or cryptocurrencies, the H-Infinity Volatility Filter helps traders and investors interpret market behavior with more confidence by offering a more refined view of price movements through its noise reduction techniques.
Disclaimer:
The H-Infinity Volatility Filter is designed to assist in market analysis by filtering out noise and volatility. It should not be used as the sole tool for making trading or investment decisions. Always incorporate other forms of analysis and risk management strategies. No statements or signals from this indicator or us should be considered financial advice. Past performance is not indicative of future results.
Advanced Volume-Driven Breakout SignalsThe "Advanced Volume-Driven Breakout Signals" indicator is a cutting-edge tool designed to help traders identify high-potential trading opportunities through sophisticated volume analysis techniques. This indicator integrates volume flow analysis, moving averages, and Relative Volume (RVOL) to provide a comprehensive view of market conditions, going beyond traditional Volume Spread Analysis (VSA) methods.
Key Features:
Volume Flow Analysis: Distinguishes bullish and bearish volume flows with distinct colors, making it easier to visualize market sentiment and potential breakout points.
Volume Flow Moving Averages: Calculates moving averages for volume using various methods (SMA, EMA, WMA, HMA, VWMA), accommodating different trading strategies. This includes settings for adjusting the type of moving average and its period, as well as thresholds for high, medium, and low volume levels.
Volume Spikes Detection: Identifies significant volume spikes based on user-defined multipliers and moving averages, highlighting unusual trading activity.
Volume MA Cloud Settings: Computes general moving averages of volume to track trends and detect deviations. This feature includes options to select different moving average types and adjust thresholds for detecting high volume activity.
Relative Volume (RVOL): Measures current volume relative to historical averages, triggering signals when RVOL exceeds predefined thresholds, indicating notable changes in trading activity.
Entry Conditions: Provides clear long and short entry signals based on combined volume flow conditions and RVOL, offering actionable trading opportunities.
Volume Visualization:
— Bullish Volume Flow: Light and dark green bars indicate bullish volume flow.
— Bearish Volume Flow: Light and dark red bars denote bearish volume flow.
— High Volume Bars: Highlighted in yellow, and extreme volume bars in orange for additional context. These bars are plotted for visual aid and do not directly influence trade signals, focusing instead on the quality and strength of the volume flow.
Alerts: Allows users to create alert notifications for long and short entry signals when the criteria are met, enabling traders to respond promptly to trading opportunities.
Usage:
Overlay: Apply the indicator directly to your price chart to visualise real-time signals and volume conditions.
Customisable: Adjust settings for moving averages, RVOL, and other parameters to match your trading strategy and preferences.
Comparison to VSA Scripts: The "Advanced Volume-Driven Breakout Signals" indicator extends beyond traditional VSA scripts by incorporating a wider range of analytical features. While VSA primarily focuses on volume spread patterns and price action, this indicator offers enhanced functionality with advanced RVOL metrics, customizable moving averages, and detailed volume spike detection, making it a more versatile tool for identifying breakout opportunities and managing trades. It is particularly effective when used alongside key levels and order blocks.
Acknowledgements: Special thanks to @oh92 and @goofoffgoose for their invaluable scripts, which served as inspiration in the development of this advanced trading indicator.
Notes: The script is continually evolving, with ongoing refinements aimed at enhancing accuracy and performance.
Ichimoku Cloud Crosses_AITIchimoku Cloud Crosser_AIT
The "Ichimoku Cloud Crosses_AIT" indicator is designed to leverage the Ichimoku Cloud components, focusing on the crossovers between the Tenkan-sen and Kijun-sen lines. This indicator visually displays these crossovers on the price chart to help traders identify potential long and short trading opportunities.
1. Indicator Components
Ichimoku Cloud Elements
Tenkan-sen (Conversion Line): A short-term trend indicator. It is the midpoint of the highest high and the lowest low over a specified period (tenkanLength). In this indicator, the default period is set to 21.
Kijun-sen (Base Line): A medium-term trend indicator. It is the midpoint of the highest high and the lowest low over the specified period (kijunLength). In this indicator, the default period is set to 120.
Senkou Span A and B: These components are part of the traditional Ichimoku Cloud, but they are not directly plotted in this version of the indicator.
Chikou Span (Lagging Span): This component is included in the calculation but is not plotted in this indicator version.
2. Signal Conditions
Long Signal
Condition: A long signal is generated when the Tenkan-sen crosses above the Kijun-sen.
Visual Representation: Displayed as a yellow triangle below the price bar.
Short Signal
Condition: A short signal is generated when the Tenkan-sen crosses below the Kijun-sen.
Visual Representation: Displayed as a fuchsia triangle above the price bar.
3. How to Use the Indicator
Add the Indicator: Apply the "Ichimoku Cloud Crosses_AIT" indicator to your chart in TradingView.
Adjust Parameters: You can customize the periods for the Tenkan-sen, Kijun-sen, Senkou Span A, Senkou Span B, and Chikou Span in the indicator's settings.
Interpret the Signals:
Long Signal: Look for a yellow triangle below the bar, indicating a potential bullish crossover (Tenkan-sen crossing above Kijun-sen).
Short Signal: Look for a fuchsia triangle above the bar, indicating a potential bearish crossover (Tenkan-sen crossing below Kijun-sen).
Conclusion
The "Ichimoku Cloud Crosses_AIT" indicator provides a clear visualization of the crossovers between the Tenkan-sen and Kijun-sen lines on the price chart. This tool helps traders quickly identify potential bullish and bearish signals, making it a valuable addition to any trading strategy. Adjust the settings and parameters as needed to fit your specific trading style and market conditions.
Ichimoku Crosses_RSI_AITIchimoku Crosser_RSI_AIT
Overview
The "Ichimoku Cloud Crosses_AIT" strategy is a technical trading strategy that combines the Ichimoku Cloud components with the Relative Strength Index (RSI) to generate trade signals. This strategy leverages the crossovers of the Tenkan-sen and Kijun-sen lines of the Ichimoku Cloud, along with RSI levels, to identify potential entry and exit points for long and short trades. This guide explains the strategy components, conditions, and how to use it effectively in your trading.
1. Strategy Parameters
User Inputs
Tenkan-sen Period (tenkanLength): Default value is 21. This is the period used to calculate the Tenkan-sen line (conversion line) of the Ichimoku Cloud.
Kijun-sen Period (kijunLength): Default value is 120. This is the period used to calculate the Kijun-sen line (base line) of the Ichimoku Cloud.
Senkou Span B Period (senkouBLength): Default value is 52. This is the period used to calculate the Senkou Span B line (leading span B) of the Ichimoku Cloud.
RSI Period (rsiLength): Default value is 14. This period is used to calculate the Relative Strength Index (RSI).
RSI Long Entry Level (rsiLongLevel): Default value is 60. This level indicates the minimum RSI value for a long entry signal.
RSI Short Entry Level (rsiShortLevel): Default value is 40. This level indicates the maximum RSI value for a short entry signal.
2. Strategy Components
Ichimoku Cloud
Tenkan-sen: A short-term trend indicator calculated as the simple moving average (SMA) of the highest high and the lowest low over the Tenkan-sen period.
Kijun-sen: A medium-term trend indicator calculated as the SMA of the highest high and the lowest low over the Kijun-sen period.
Senkou Span A: Calculated as the average of the Tenkan-sen and Kijun-sen, plotted 26 periods ahead.
Senkou Span B: Calculated as the SMA of the highest high and lowest low over the Senkou Span B period, plotted 26 periods ahead.
Chikou Span: The closing price plotted 26 periods behind.
Relative Strength Index (RSI)
RSI: A momentum oscillator that measures the speed and change of price movements. It ranges from 0 to 100 and is used to identify overbought or oversold conditions.
3. Entry and Exit Conditions
Entry Conditions
Long Entry:
The Tenkan-sen crosses above the Kijun-sen (bullish crossover).
The RSI value is greater than or equal to the rsiLongLevel.
Short Entry:
The Tenkan-sen crosses below the Kijun-sen (bearish crossover).
The RSI value is less than or equal to the rsiShortLevel.
Exit Conditions
Exit Long Position: The Tenkan-sen crosses below the Kijun-sen.
Exit Short Position: The Tenkan-sen crosses above the Kijun-sen.
4. Visual Representation
Tenkan-sen Line: Plotted on the chart. The color changes based on its relation to the Kijun-sen (green if above, red if below) and is displayed with a line width of 2.
Kijun-sen Line: Plotted as a white line with a line width of 1.
Entry Arrows:
Long Entry: Displayed as a yellow triangle below the bar.
Short Entry: Displayed as a fuchsia triangle above the bar.
5. How to Use
Apply the Strategy: Apply the "Ichimoku Cloud Crosses_AIT" strategy to your chart in TradingView.
Configure Parameters: Adjust the strategy parameters (Tenkan-sen, Kijun-sen, Senkou Span B, and RSI settings) according to your trading preferences.
Interpret the Signals:
Long Entry: A yellow triangle appears below the bar when a long entry signal is generated.
Short Entry: A fuchsia triangle appears above the bar when a short entry signal is generated.
Monitor Open Positions: The strategy automatically exits positions based on the defined conditions.
Backtesting and Live Trading: Use the strategy for backtesting and live trading. Adjust risk management settings in the strategy properties as needed.
Conclusion
The "Ichimoku Cloud Crosses_AIT" strategy uses Ichimoku Cloud crossovers and RSI to generate trading signals. This strategy aims to capture market trends and potential reversals, providing a structured way to enter and exit trades. Make sure to backtest and optimize the strategy parameters to suit your trading style and market conditions before using it in a live trading environment.
Multi-Scale Adaptive MAs (Hurst, CVaR, Fractal) // AlgoFyreThe Multi-Scale Adaptive MAs (Hurst, CVaR, Fractal) indicator adjusts moving averages based on market conditions, using Hurst Exponent for trend persistence, CVaR for extreme risk assessment, and Fractal Dimension for market complexity. It enhances trend detection and risk management across various timeframes.
TABLE OF CONTENTS
🔶 ORIGINALITY 🔸Adaptive Mechanisms
🔸Multi-Faceted Analysis
🔸Versatility Across Timeframes
🔸Multi-Scale Combination
🔶 FUNCTIONALITY 🔸Hurst Exponent (H)
🞘 How it works
🞘 How to calculate
🞘 Code extract
🔸Conditional Value at Risk (CVaR)
🞘 How it works
🞘 How to calculate
🞘 Code extract
🔸Fractal Dimension (FD)
🞘 How it works
🞘 How to calculate
🞘 Code extract
🔶 INSTRUCTIONS 🔸Step-by-Step Guidelines
🞘 Setting Up the Indicator
🞘 Understanding What to Look For on the Chart
🞘 Possible Entry Signals
🞘 Possible Take Profit Strategies
🞘 Possible Stop-Loss Levels
🞘 Additional Tips
🔸Customize settings
🔶 CONCLUSION
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🔶 ORIGINALITY The Multi-Scale Adaptive MAs (Hurst, CVaR, Fractal) indicator stands out due to its unique approach of dynamically adjusting moving averages based on advanced statistical measures, making it highly responsive to varying market conditions. Unlike traditional moving averages that rely on static periods, this indicator adapts in real-time using three distinct adaptive methods: Hurst Exponent, CVaR, and Fractal Dimension.
🔸Adaptive Mechanisms
Traditional MA indicators use fixed lengths, which can lead to lagging signals or over-sensitivity in volatile markets. The Multi-Scale Adaptive MAs employ adaptive methods to adjust the MA length dynamically, providing a more accurate reflection of current market conditions.
🔸Multi-Faceted Analysis
By integrating Hurst Exponent, CVaR, and Fractal Dimension, the indicator offers a comprehensive market analysis. It captures different aspects of market behavior, including trend persistence, risk of extreme movements, and complexity, which are often missed by standard MAs.
🔸Versatility Across Timeframes
The indicator’s ability to switch between different adaptive methods based on market conditions allows traders to analyze short-term, medium-term, and long-term trends with enhanced precision.
🔸Multi-Scale Combination
Utilizing multiple adaptive MAs in combination provides a more nuanced view of the market, allowing traders to see how short, medium, and long-term trends interact. This layered approach helps in identifying the strength and consistency of trends across different scales, offering more reliable signals and aiding in complex decision-making processes. When combined, these MAs can also signal key market shifts when they converge or diverge, offering deeper insights than a single MA could provide.
🔶 FUNCTIONALITY The indicator adjusts moving averages based on a variety of different choosable adaptives. The Hurst Exponent to identify trend persistence or mean reversion, adapting to market conditions for both short-term and long-term trends. Using CVaR, it evaluates the risk of extreme price movements, ensuring the moving average is more conservative during high-risk periods, protecting against potential large losses. By incorporating the Fractal Dimension, the indicator adapts to market complexity, adjusting to varying levels of price roughness and volatility, which allows it to respond more accurately to different market structures and patterns.
Let's dive into the details:
🔸Hurst Exponent (H)
Measures the degree of trend persistence or mean reversion.
By using the Hurst Exponent, the indicator adjusts to capture the strength and duration of trends, helping traders to stay in profitable trades longer and avoid false reversals in ranging markets.
It enhances the detection of trends, making it suitable for both short-term scalping and identifying long-term trends.
🞘 How it works Rescaled Range (R/S) Analysis Calculate the mean of the closing prices over a set window.
Determine the deviation of each price from the mean.
Compute the cumulative sum of these deviations over the window.
Calculate the range (R) of the cumulative deviations (maximum minus minimum).
Compute the standard deviation (S) of the price series over the window.
Obtain the R/S ratio as R/S.
Linear Regression for Hurst Exponent Calculate the logarithm of multiple window sizes and their corresponding R/S values.
Use linear regression to determine the slope of the line fitting the log(R/S) against log(window size).
The slope of this line is an estimate of the Hurst Exponent.
🞘 How to calculate Range (R)
Calculate the maximum cumulative deviation:
R=max(sum(deviation))−min(sum(deviation))
Where deviation is the difference between each price and the mean.
Standard Deviation (S)
Calculate the standard deviation of the price series:
S=sqrt((1/(n−1))∗sum((Xi−mean)2))
Rescaled Range (R/S)
Divide the range by the standard deviation:
R/S=R/S
Hurst Exponent
Perform linear regression to estimate the slope of:
log(R/S) versus log(windowsize)
The slope of this line is the Hurst Exponent.
🞘 Code extract // Hurst Exponent
calc_hurst(source_, adaptive_window_) =>
window_sizes = array.from(adaptive_window_/10, adaptive_window_/5, adaptive_window_/2, adaptive_window_)
float hurst_exp = 0.5
// Calculate Hurst Exponent proxy
rs_list = array.new_float()
log_length_list = array.new_float()
for i = 0 to array.size(window_sizes) - 1
len = array.get(window_sizes, i)
// Ensure we have enough data
if bar_index >= len * 2
mean = adaptive_sma(source_, len)
dev = source_ - mean
// Calculate cumulative deviations over the window
cum_dev = ta.cum(dev) - ta.cum(dev )
r = ta.highest(cum_dev, len) - ta.lowest(cum_dev, len)
s = ta.stdev(source_, len)
if s != 0
rs = r / s
array.push(rs_list, math.log(rs))
array.push(log_length_list, math.log(len))
// Linear regression to estimate Hurst Exponent
n = array.size(log_length_list)
if n > 1
mean_x = array.sum(log_length_list) / n
mean_y = array.sum(rs_list) / n
sum_num = 0.0
sum_den = 0.0
for i = 0 to n - 1
x = array.get(log_length_list, i)
y = array.get(rs_list, i)
sum_num += (x - mean_x) * (y - mean_y)
sum_den += (x - mean_x) * (x - mean_x)
hurst_exp := sum_den != 0 ? sum_num / sum_den : 0.5
else
hurst_exp := 0.5 // Default to 0.5 if not enough data
hurst_exp
🔸Conditional Value at Risk (CVaR)
Assesses the risk of extreme losses by focusing on tail risk.
This method adjusts the moving average to account for market conditions where extreme price movements are likely, providing a more conservative approach during periods of high risk.
Traders benefit by better managing risk and avoiding major losses during volatile market conditions.
🞘 How it works Calculate Returns Determine the returns as the percentage change between consecutive closing prices over a specified window.
Percentile Calculation Identify the percentile threshold (e.g., the 5th percentile) for the worst returns in the dataset.
Average of Extreme Losses Calculate the average of all returns that are less than or equal to this percentile, representing the CVaR.
🞘 How to calculate Return Calculation
Calculate the return as the percentage change between consecutive prices:
Return = (Pt − Pt−1) / Pt−1
Where Pt is the price at time t.
Percentile Threshold
Identify the return value at the specified percentile (e.g., 5th percentile):
PercentileValue=percentile(returns,percentile_threshold)
CVaR Calculation
Compute the average of all returns below the percentile threshold:
CVaR = (1/n)∗sum(Return) for all Return≤PercentileValue
Where n is the total number of returns.
🞘 Code extract // Percentile
calc_percentile(data, percentile, window) =>
arr = array.new_float(0)
for i = 0 to window - 1
array.push(arr, data )
array.sort(arr)
index = math.floor(percentile / 100 * (window - 1))
array.get(arr, index)
// Conditional Value at Risk
calc_cvar(percentile_value, returns, window) =>
// Collect returns worse than the threshold
cvar_sum = 0.0
cvar_count = 0
for i = 0 to window - 1
ret = returns
if ret <= percentile_value
cvar_sum += ret
cvar_count += 1
// Calculate CVaR
cvar = cvar_count > 0 ? cvar_sum / cvar_count : 0.0
cvar
🔸Fractal Dimension (FD)
Evaluates market complexity and roughness by analyzing how price movements behave across different scales.
It enables the moving average to adapt based on the level of market noise or structure, allowing for smoother MAs during complex, volatile periods and more sensitive MAs during clear trends.
This adaptability is crucial for traders dealing with varying market states, improving the indicator's responsiveness to price changes.
🞘 How it works Total Distance (L) Calculation Sum the absolute price movements between consecutive periods over a given window.
Maximum Distance (D) Calculation Calculate the maximum displacement from the first to the last price point within the window.
Calculate Fractal Dimension Use Katz's method to estimate the Fractal Dimension as the ratio of the logarithms of L and D, divided by the logarithm of the number of steps (N).
🞘 How to calculate Total Distance (L)
Sum the absolute price changes over the window:
L=sum(abs(Pt−Pt−1)) for t from 2 to n
Where Pt is the price at time t.
Maximum Distance (D)
Find the maximum absolute displacement from the first to the last price in the window:
D=max(abs(Pn-P1))
Fractal Dimension Calculation
Use Katz's method to estimate fractal dimension:
FD=log(L/D)/log(N)
Where N is the number of steps in the window.
🞘 Code extract // Fractal Dimension
calc_fractal(source_, adaptive_window_) =>
// Calculate the total distance (L) traveled by the price
L = 0.0
for i = 1 to adaptive_window_
L += math.abs(source_ - source_ )
// Calculate the maximum distance between first and last price
D = math.max(math.abs(source_ - source_ ), 1e-10) // Avoid division by zero
// Calculate the number of steps (N)
N = adaptive_window_
// Estimate the Fractal Dimension using Katz's formula
math.log(L / D) / math.log(N)
🔶 INSTRUCTIONS The Multi-Scale Adaptive MAs indicator can be set up by adding it to your TradingView chart and configuring the adaptive method (Hurst, CVaR, or Fractal) to match current market conditions. Look for price crossovers and changes in the slope for potential entry signals. Set take profit and stop-loss levels based on dynamic changes in the moving average, and consider combining it with other indicators for confirmation. Adjust settings and use adaptive strategies for enhanced trend detection and risk management.
🔸Step-by-Step Guidelines 🞘 Setting Up the Indicator Adding the Indicator to the Chart: Go to your TradingView chart.
Click on the "Indicators" button at the top.
Search for "Multi-Scale Adaptive MAs (Hurst, CVaR, Fractal)" in the indicators list.
Click on the indicator to add it to your chart.
Configuring the Indicator: Open the indicator settings by clicking on the gear icon next to its name on the chart.
Adaptive Method: Choose between "Hurst," "CVaR," and "Fractal" depending on the market condition and your trading style.
Length: Set the base length for the moving average (e.g., 20, 50, or 100). This length will be adjusted dynamically based on the selected adaptive method.
Other Parameters: Adjust any other parameters as needed, such as window sizes or scaling factors specific to each adaptive method.
Chart Setup: Ensure you have an appropriate timeframe selected (e.g., 1-hour, 4-hour, daily) based on your trading strategy.
Consider using additional indicators like volume or RSI to confirm signals.
🞘 Understanding What to Look For on the Chart Indicator Behavior: Observe how the adaptive moving average (AMA) behaves compared to standard moving averages, e.g. notice how it might change direction with strength (Hurst).
For example, the AMA may become smoother during high market volatility (CVaR) or more responsive during strong trends (Hurst).
Crossovers: Look for crossovers between the price and the adaptive moving average.
A bullish crossover occurs when the price crosses above the AMA, suggesting a potential uptrend.
A bearish crossover occurs when the price crosses below the AMA, indicating a possible downtrend.
Slope and Direction: Pay attention to the slope of the AMA. A rising slope suggests a bullish trend, while a declining slope indicates a bearish trend.
The slope’s steepness can give you clues about the trend's strength.
🞘 Possible Entry Signals Bullish Entry: Crossover Entry: Enter a long position when the price crosses above the AMA and the AMA has a positive slope.
Confirmation Entry: Combine the crossover with other indicators like RSI (above 50) or increasing volume for confirmation.
Bearish Entry: Crossover Entry: Enter a short position when the price crosses below the AMA and the AMA has a negative slope.
Confirmation Entry: Use additional indicators like RSI (below 50) or decreasing volume to confirm the bearish trend.
Adaptive Method Confirmation: Hurst: Enter when the AMA indicates a strong trend (steeper slope). Suitable for trend-following strategies.
CVaR: Be cautious during high-risk periods. Enter only if confirmed by other indicators, as the AMA may become more conservative.
Fractal: Ideal for capturing reversals in complex markets. Look for crossovers in volatile markets.
🞘 Possible Take Profit Strategies Static Take Profit Levels: Set take profit levels based on predefined ratios (e.g., 1:2 or 1:3 risk-reward ratio).
Place take profit orders at recent swing highs (for long positions) or swing lows (for short positions).
Trailing Stop Loss: Use a trailing stop based on a percentage of the AMA value to lock in profits as the trend progresses.
Adjust the trailing stop dynamically to follow the AMA, allowing profits to run while protecting gains.
Adaptive Method Based Exits: Hurst: Exit when the AMA begins to flatten or turn in the opposite direction, signaling a potential trend reversal.
CVaR: Consider taking profits earlier during high-risk periods when the AMA suggests caution.
Fractal: Use the AMA to exit in complex markets when it smooths out, indicating reduced volatility.
🞘 Possible Stop-Loss Levels Initial Stop Loss: Place an initial stop loss below the AMA (for long positions) or above the AMA (for short positions) to protect against adverse movements.
Use a buffer (e.g., ATR value) to avoid being stopped out by normal price fluctuations.
Adaptive Stop Loss: Adjust the stop loss dynamically based on the AMA. Move the stop loss along the AMA as the trend progresses to minimize risk.
This helps in adapting to changing market conditions and avoiding premature exits.
Adaptive Method-Specific Stop Loss: Hurst: Use wider stops during trending markets to allow for minor pullbacks.
CVaR: Adjust stops in high-risk periods to avoid being stopped out prematurely during price fluctuations.
Fractal: Place stops at recent support/resistance levels in highly volatile markets.
🞘 Additional Tips Combine with Other Indicators: Enhance your strategy by combining the AMA with other technical indicators like MACD, RSI, or Bollinger Bands for better signal confirmation.
Backtesting and Practice: Backtest the indicator on historical data to understand how it performs in different market conditions.
Practice using the indicator on a demo account before applying it to live trading.
Market Awareness: Always be aware of market conditions and fundamental events that might impact price movements, as the AMA reacts to price action and may not account for sudden news-driven events.
🔸Customize settings 🞘 Time Override: Enables or disables the ability to override the default time frame for the moving averages. When enabled, you can specify a custom time frame for the calculations.
🞘 Time: Specifies the custom time frame to use when the Time Override setting is enabled.
🞘 Enable MA: Enables or disables the moving average. When disabled, MA will not be displayed on the chart.
🞘 Show Smoothing Line: Enables or disables the display of a smoothing line for the moving average. The smoothing line helps to reduce noise and provide a clearer trend.
🞘 Show as Horizontal Line: Displays the moving average as a horizontal line instead of a dynamic line that follows the price.
🞘 Source: Specifies the data source for the moving average calculation (e.g., close, open, high, low).
🞘 Length: Sets the period length for the moving average. A longer length will result in a smoother moving average, while a shorter length will make it more responsive to price changes.
🞘 Time: Specifies a custom time frame for the moving average, overriding the default time frame if Time Override is enabled.
🞘 Method: Selects the calculation method for the moving average (e.g., SMA, EMA, SMMA, WMA, VWMA).
🞘 Offset: Shifts the moving average forward or backward by the specified number of bars.
🞘 Color: Sets the color for the moving average line.
🞘 Adaptive Method: Selects the adaptive method to dynamically adjust the moving average based on market conditions (e.g., Hurst, CVaR, Fractal).
🞘 Window Size: Sets the window size for the adaptive method, determining how much historical data is used for the calculation.
🞘 CVaR Scaling Factor: Adjusts the influence of CVaR on the moving average length, controlling how much the length changes based on calculated risk.
🞘 CVaR Risk: Specifies the percentile cutoff for the worst-case returns used in the CVaR calculation to assess extreme losses.
🞘 Smoothing Method: Selects the method for smoothing the moving average (e.g., SMA, EMA, SMMA, WMA, VWMA).
🞘 Smoothing Length: Sets the period length for smoothing the moving average.
🞘 Fill Color to Smoothing Moving Average: Enables or disables the color fill between the moving average and its smoothing line.
🞘 Transparency: Sets the transparency level for the color fill between the moving average and its smoothing line.
🞘 Show Label: Enables or disables the display of a label for the moving average on the chart.
🞘 Show Label for Smoothing: Enables or disables the display of a label for the smoothing line of the moving average on the chart.
🔶 CONCLUSION The Multi-Scale Adaptive MAs indicator offers a sophisticated approach to trend analysis and risk management by dynamically adjusting moving averages based on Hurst Exponent, CVaR, and Fractal Dimension. This adaptability allows traders to respond more effectively to varying market conditions, capturing trends and managing risks with greater precision. By incorporating advanced statistical measures, the indicator goes beyond traditional moving averages, providing a nuanced and versatile tool for both short-term and long-term trading strategies. Its unique ability to reflect market complexity and extreme risks makes it an invaluable asset for traders seeking a deeper understanding of market dynamics.
Universal Trend Following Valuation | viResearch Universal Trend Following Valuation | viResearch
Conceptual Foundation and Innovation
The "Universal Trend Following Valuation" script represents a comprehensive approach to trend-following systems. It combines multiple technical indicators and methods to assess market trends, integrating Sharpe, Sortino, and Omega ratios with various moving averages and Z-score calculations. By utilizing advanced statistical tools, the script provides traders with a well-rounded evaluation of trend strength, direction, and potential reversals. The inclusion of Z-scores and custom ratios allows for a more in-depth and accurate market analysis, making it a valuable tool for trend valuation.
Technical Composition and Calculation
This script is built on various performance metrics and trend-following methods. It features ratio calculations, such as Sharpe, Sortino, and Omega, which provide insight into the risk-adjusted performance of assets, helping traders gauge the strength of market trends. Weekly RSI values are smoothed using dema, ema, and median methods to offer a clearer view of trend momentum. Additionally, Z-scores are applied to these ratios and the weekly RSI, offering a standardized assessment of trend deviations from historical performance. A custom scoring system is used to generate a cumulative trend score, highlighting potential market reversals or confirmations.
Key Indicators and Features
The script uses weekly RSI and EMA/Dema smoothing to reduce market noise and produce clearer trend signals. The Sharpe, Sortino, and Omega ratio calculations help assess market performance and volatility, with Z-scores adding another analytical layer. Different moving averages (HMA, DEMA, SMMA) are incorporated to evaluate both short-term and long-term trends, making the script adaptable to various market conditions. Furthermore, the script provides trend confirmation through multiple layers by using indicators like the Supertrend and the Average True Range (ATR) factor to cross-check trends for increased reliability.
Practical Applications
This script is ideal for traders looking to systematically evaluate market trends and effectively position themselves. The combination of advanced statistical tools and customizable moving averages and ratios ensures that the script remains both flexible and powerful. It is particularly useful for confirming trends and highlighting potential reversals, giving traders a reliable signal for either trend continuation or reversals. The inclusion of Sharpe and Sortino ratios allows traders to focus on trends that offer a favorable risk-reward profile.
Advantages and Strategic Value
The "Universal Trend Following Valuation" script offers a detailed, multifaceted approach to trend analysis. Its use of advanced statistical tools provides a more precise evaluation of market trends, making it valuable for both novice and experienced traders. The script reduces noise while ensuring that the core trend signals remain accurate, helping traders make more informed decisions in volatile market conditions.
Summary and Usage Tips
Incorporating the "Universal Trend Following Valuation" into your trading system can significantly enhance your ability to follow and confirm trends. With its customizable parameters and alerts, this script offers a powerful and reliable tool for navigating market volatility and optimizing trade entries and exits. By combining trend-following signals with performance metrics, traders can refine their strategies with increased confidence.
Disclaimer: Backtests are based on past results and are not indicative of future performance.
Relative Vigor Index [MTF] with MACD, Divergence and AlertsThis advanced indicator integrates the Normalized Relative Vigor Index (RVGI) with Multi-Timeframe (MTF) analysis, MACD, divergence detection, and customizable alert features. It provides a comprehensive toolkit for traders to analyze market momentum, identify trend changes, and react to significant technical signals.
Key Features:
Normalized Relative Vigor Index (RVGI):
Calculation: Computes the RVGI and its signal line using various smoothing methods (SWMA, EMA, SMA). The RVGI measures the strength of price movement relative to its historical volatility, providing insights into market momentum.
Plotting: Visualizes the RVGI and signal line on the chart. Users can customize the colors and transparency of the plots and the ribbon that fills the area between them.
Overbought/Oversold Levels: Displays horizontal lines to mark overbought and oversold zones, helping to identify potential reversal points.
Multi-Timeframe (MTF) Analysis:
Timeframe Selection: Allows users to select different timeframes for RVGI analysis, providing a broader perspective on market trends and signals.
Integration: Combines MTF data with the main indicator calculations to offer a more comprehensive view of market conditions.
MACD Integration:
Calculation: Computes MACD, MACD signal line, and MACD histogram with options for different moving average types (SMA, EMA) and a customizable scaling factor.
Plotting: Plots the MACD histogram, zero line, and signal line, with color and transparency settings to distinguish between positive and negative values.
Divergence Detection:
Bullish Divergence: Identifies and plots bullish divergence when the price makes a lower low while the RVGI makes a higher low, suggesting potential upward reversals.
Bearish Divergence: Identifies and plots bearish divergence when the price makes a higher high while the RVGI makes a lower high, indicating potential downward reversals.
Alerts:
Divergence Alerts: Configurable alerts for bullish and bearish divergences, notifying traders of significant potential reversals.
RVGI Alerts: Alerts for RVGI crossovers, overbought/oversold conditions, and trend changes based on RVGI and signal line crossovers.
MACD Alerts: Alerts for MACD line crossovers, histogram crossovers, and MACD zero line crossovers, helping traders stay informed of key MACD signals.
Customization Options:
Ribbon Colors and Transparency: Users can adjust the colors and transparency of the RVGI ribbon, enhancing visual clarity.
MACD Histogram Colors and Transparency: Customizable colors and transparency settings for the MACD histogram improve visibility and differentiation of positive and negative values.
Smoothing Methods: Choose between different smoothing methods for RVGI, tailoring the indicator to specific trading strategies.
Use Cases:
Trend Analysis: Utilize RVGI and MACD signals to analyze market trends, identify potential trend reversals, and assess momentum.
Divergence Identification: Detect and act on divergences between price and RVGI to spot potential trading opportunities.
Alert Management: Customize and receive alerts based on various conditions, ensuring timely responses to market signals.
Conclusion:
This indicator is designed for traders who seek a comprehensive tool combining momentum analysis, divergence detection, and signal alerts. By integrating RVGI, MACD, and MTF analysis, it provides a powerful suite of features to enhance market analysis and trading decisions
Chronos Sequential Compass (CSC)The Chronos Sequential Compass (CSC) is an advanced technical analysis tool used to identify potential price exhaustion points, trend reversals, and provide a framework for understanding market structure.
Key Components:
Setup Phase:
Bullish Setup: 9 consecutive closes lower than the close 4 bars earlier.
Bearish Setup: 9 consecutive closes higher than the close 4 bars earlier.
Visualized by green (bullish) or red (bearish) triangles on the chart.
Countdown Phase:
Starts after a Setup is completed.
Counts from 1 to 13(D), comparing the close to the low (for bullish) or high (for bearish) two bars earlier.
Displayed as numbers below (bullish) or above (bearish) the price bars.
Setups:
A Setup is complete when the low of bars 6 and 7 in a bullish Setup are exceeded by the low of bar 9.
For bearish Setups, the high of bars 6 and 7 must be exceeded by the high of bar 9.
Risk Levels:
Established when a Countdown reaches 13(D).
Acts as a reference point for potential trend reversals.
Countdown Delayed:
Indicated by a '+' symbol.
Occurs when a Countdown reaches 13(D) but doesn't meet specific criteria for completion.
Recycling:
Resets the Countdown if a strong opposite trend emerges during the Countdown phase.
How to Use the CSC:
Trend Identification:
Consecutive Setups in one direction indicate a strong trend.
Look for potential trend exhaustion when Setups start appearing in the opposite direction.
Potential Reversal Points:
Pay attention when a Countdown reaches 13, especially if it coincides with other technical factors (support/resistance, chart patterns, etc.).
A completed Countdown doesn't guarantee a reversal but suggests increased probability.
Risk Management:
Use Risk Levels as potential stop-loss points or profit-taking levels.
Be cautious of trades against the trend when price is far from the Risk Level.
Confluence with Price Action:
Look for candlestick patterns or chart formations at key Sequential levels for higher probability setups.
Timeframe Coordination:
Consider using CSC on multiple timeframes for a more comprehensive market view.
Higher timeframe signals often carry more weight.
Delayed Countdowns:
A delayed Countdown (indicated by '+') suggests the trend might continue.
It can provide opportunities for trend continuation trades.
Setup:
Setups often provide stronger signals and may lead to more significant moves.
Reversals should occur within 4 bars of setup signals
Completed Countdowns:
Reversals should occur within 12 bars of completed countdowns
EMA Volume [MacroGlide]EMA Volume is a versatile tool designed to track and analyze market volumes by calculating the Exponential Moving Averages (EMAs) of total, bullish, and bearish volumes. This indicator helps traders visualize volume dynamics, identify buying and selling pressure, and make informed trading decisions based on volume activity.
Key Features:
• Volume EMAs: The indicator calculates the EMAs of total, bullish, and bearish volumes, allowing users to observe how volume trends evolve over time. This helps identify shifts in market sentiment and potential reversals.
• Separation of Bullish and Bearish Volumes: By separating bullish and bearish volumes, the indicator provides a clear view of buying versus selling activity. This distinction is valuable for understanding the market's underlying momentum and direction.
• Customizable Visuals: Users can customize the line style and color for each volume type, allowing them to tailor the display of the indicator to their personal preferences and enhance the visual interpretation of the data.
How to Use:
• Add the indicator to your chart and adjust the EMA settings and display parameters according to your needs.
• Use the difference between bullish and bearish volumes to assess current market sentiment and analyze potential trend changes.
• Monitor the EMA of total volume to identify overall volume trends that can serve as additional signals for entering or exiting positions.
Methodology:
The indicator calculates the EMAs for total, bullish, and bearish volumes based on the trading volumes associated with price increases or decreases. This tool helps evaluate the strength of buying and selling at different times, making it especially useful for volume and market dynamics analysis.
Originality and Usefulness:
EMA Volume stands out for its ability to separate buying and selling volumes and present them in a clear visual format, significantly simplifying the analysis of market activity and decision-making in trading.
Charts:
The indicator displays clean and clear charts, where each type of volume is represented by its own line and color, making visual interpretation easier. The charts focus solely on key information for analysis: EMAs of total, bullish, and bearish volumes. These features make the charts highly useful for quick analysis and trading decision-making.
Enjoy the game!
Opening Range with Breakouts & Targets [LuxAlgo]Opening Range with Breakouts & Targets is based on the long-standing Opening Range Breakout strategy popularized by traders such as Toby Crabel and Mark Fisher.
This indicator measures and displays the price range created from the first period within a new trading session, along with price breakouts from that range and targets associated with the range width.
🔶 USAGE
The Opening Range (OR) can be a powerful tool for making a clear distinction between ranging and trending trading days. Using a rigid structure for drawing a range, provides a consistent basis to make judgments and comparisons that will better assist the user in determining a hypothesis for the day's price action.
NOTE: During a suspected "Range Day", the Opening Range can be used for reversion strategies, typically targeting the opposite extreme of the range or the mean of the range. However, more commonly the Opening Range is used for breakouts on suspected "Trend Days", targeting further upward or downward market movement.
The common Opening Range Breakout Strategy (ORB) outlines a structure to enter and exit positions based on rigid points determined by the Opening Range. This methodology can be adjusted based on markets or trading styles.
Determine Opening Range High & Low: These are the high and low price within a chosen period of time after the market opens. This can be customized to the user's trading style and preference. Common Ranges are from 5-60 mins.
Watch for a Breakout with Volume: A Breakout occurs when price crosses the OR High (ORH) or OR Low (ORL), an increase in volume is typically desired when witnessing these breakouts to confirm a stronger movement.
Manage Risk: Based on user preference and the appropriately determined amount of risk, multiple ways can be determined to manage risk by using Opening Range.
For Example: A stop-loss could be set at OR Mean (ORM) or the opposite side of the range, while a profit target could optionally be set at the first price target generated by the script.
Alternatively, a user might want to use a Moving Average (MA) as an adaptive stop-loss and use price targets to scale out. These are just 2 examples of the possible options, both capable with this tool.
🔹 Signals
Signals will fire based on the break of the opening range, this is indicated by arrows above and below the range boundaries.
Optionally, a bias can be added to these signals to aid in mitigating false signals by using a directional filter based on the current day's OR relative to the previous day's OR.
Regardless of the signal bias being enabled, the Opening Range Zone will always be colored directionally according to this.
If the current day's OR is above the previous day's OR, the Zone will be Green.
If the current day's OR is below the previous day's OR, the Zone will be Red.
By enabling the signal bias, signals in the opposite direction of the daily bias will fire on the cross of the first target in that direction.
🔹 Targets
In this indicator, targets are not limited and will generate infinitely based on a % width of the Opening Range.
Additionally, there are 2 display methods for these targets.
Extended: Extends the targets to the current bar and displays all targets that have been crossed so far within the session.
Adaptive: Extends only the 2 closest targets surrounding price, allowing for a display consisting of fewer lines at one time.
🔶 DETAILS
🔹 Historical Display
This indicator can be utilized in multiple ways, for use in real-time, and for historical analysis to form methods. Because of this, the indicator has an option to display only the current day's data or the entire historical data. This can also help clean up the chart when it is in use.
🔹 Time Period
The specific time period to create the opening range is entirely up to each user's preference, by default it is set to 30 mins; however, this time period can be edited with full control if desired.
Simply toggle on the "Custom Range" and input a range of time to create the range.
🔹 Session Moving Average
The Session Moving Average is a common Moving Average, which resets at the beginning of a new session. This allows for an unbiased MA that was created entirely from the current session's price action.
Note: The start of the session is determined by the start of the Opening Range if using a custom range of time.
🔶 SETTINGS
Show Historical Data: Choose to display only the current session's data or the full history of data.
Opening Range Time Period: Select the time period to form the opening range from. This operates on Session Start, so it will change with the chart.
Custom Range: Opt for a custom Range by enabling this and inputting your range times as well as your needed timezone.
Breakout Signal Bias: Select if the Breakout Signals will use a Daily Directional Bias for firing.
Target % of Range: Sets the % of the Range width that will be used as an increment for the Targets to display in.
Target Cross Source: Choose to use the Close price or High/Low price as the crossing level for Target displays. When this source crosses a target it will generate more targets.
Target Display: Choose which style of display to use for targets.
Session Moving Average: Optionally enable a Moving average of your choice that resets at the beginning of each session (start of opening range).
