[SGM Ordinal Patterns]An ordinal pattern is a concept used in mathematics and time series analysis. It is a way of describing the relative order of values in a sequence. Rather than focusing on the exact values, we are interested in how they compare to each other.
An ordinal pattern will tell you how these values are positioned relative to each other.
We do not look at the exact values, but only their order.
Concrete Example
• 4 (position 1 in the original sequence) is in position 2 in the ordered sequence.
• 7 (position 2 in the original sequence) is in position 3 in the ordered sequence.
• 2 (position 3 in the original sequence) is in position 1 in the ordered sequence.
The ordinal pattern for this sequence is then (2,3,1)(2, 3, 1)(2,3,1).
Script Explanation
This script analyzes ordinal patterns based on the closing prices of the last three bars and calculates the future gains associated with each ordinal pattern.
The main elements of the script are:
1. ordinal_pattern Function:
o Determines the ordinal pattern based on three past closing values.
o Returns an index (from 0 to 5) corresponding to one of the six possible ordinal patterns.
2. Calculations and Storage:
o For each new bar, the last three closes are used to identify the ordinal pattern.
o Future gains are calculated and associated with the previous ordinal pattern.
o Return statistics (mean, standard deviation and Sharpe ratio) are calculated for each pattern.
3. Visualization:
o Draws lines connecting the last three closes.
o Tables displaying the number of occurrences, distributions, and return statistics for each ordinal pattern.
What the Script Shows:
• Table motifs_table : Number of occurrences and distribution of each ordinal pattern. An uneven distribution between patterns (different by one sixth for each pattern) can indicate market inefficiency.
• Table pattern_analysis : Analysis of returns (mean, standard deviation, Sharpe ratio) for each ordinal pattern.
• Table current_motif_table : Ordinal pattern of the last bar.
This script helps to understand and visualize how ordinal patterns influence future returns of financial asset prices. An uneven distribution of patterns can indicate market inefficiencies.
Statistics
Oscillator Scatterplot Analysis [Trendoscope®]In this indicator, we demonstrate how to plot oscillator behavior of oversold-overbought against price movements in the form of scatterplots and perform analysis. Scatterplots are drawn on a graph containing x and y-axis, where x represent one measure whereas y represents another. We use the library Graph to collect the data and plot it as scatterplot.
Pictorial explanation of components is defined in the chart below.
🎲 This indicator performs following tasks
Calculate and plot oscillator
Identify oversold and overbought areas based on various methods
Measure the price and bar movement from overbought to oversold and vice versa and plot them on the chart.
In our example,
The x-axis represents price movement. The plots found on the right side of the graph has positive price movements, whereas the plots found on the left side of the graph has negative price movements.
The y-axis represents the number of bars it took for reaching overbought to oversold and/or oversold to overbought. Positive bars mean we are measuring oversold to overbought, whereas negative bars are a measure of overbought to oversold.
🎲 Graph is divided into 4 equal quadrants
Quadrant 1 is the top right portion of the graph. Plots in this quadrant represent the instances where positive price movement is observed when the oscillator moved from oversold to overbought
Quadrant 2 is the top left portion of the graph. Plots in this quadrant represent the instances where negative price movement is observed when the oscillator moved from oversold to overbought.
Quadrant 3 is the bottom left portion of the chart. Plots in this quadrant represent the instances where negative price movement is observed when the oscillator moved from overbought to oversold.
Quadrant 4 is the bottom right portion of the chart. Plots in this quadrant represent the instances where positive price movement is observed when the oscillator moved from overbought to oversold.
🎲 Indicator components in Detail
Let's dive deep into the indicator.
🎯 Oscillator Selection
Select the Oscillator and define the overbought oversold conditions through input settings
Indicator - Oscillator base used for performing analysis
Length - Loopback length on which the oscillator is calculated
OB/OS Method - We use Bollinger Bands, Keltener Channel and Donchian channel to calculate dynamic overbought and oversold levels instead of static 80-10. This is also useful as other type of indicators may not be within 0-100 range.
Length and Multiplier are used for the bands for calculating Overbought/Oversold boundaries.
🎯 Define Graph Properties
Select different graph properties from the input settings that will instruct how to display the scatterplot.
Type - this can be either scatterplot or heatmap. Scatterplot will display plots with specific transparency to indicate the data, whereas heatmap will display background with different transparencies.
Plot Color - this is the color in which the scatterplot or heatmap is drawn
Plot Size - applicable mainly for scatterplot. Since the character we use for scatterplot is very tiny, the large at present looks optimal. But, based on the user's screen size, we may need to select different sizes so that it will render properly.
Rows and Columns - Number of rows and columns allocated per quadrant. This means, the total size of the chart is 2X rows and 2X columns. Data sets are divided into buckets based on the number of available rows and columns. Hence, changing this can change the appearance of the overall chart, even though they are representing the same data. Also, please note that tables can have max 10000 cells. If we increase the rows and columns by too much, we may get runtime errors.
Outliers - this is used to exclude the extreme data. 20% outlier means, the chart will ignore bottom 20% and top 20% when defining the chart boundaries. However, the extreme data is still added to the boundaries.
1000SATS and ORDI Market Cap RatioSure! Here is a detailed description and usage guide for your TradingView indicator:
### Indicator Description
**Title**: 1000SATS/ORDI Market Cap Ratio
**Description**: The "1000SATS/ORDI Market Cap Ratio" indicator calculates and visualizes the market capitalization ratio between 1000SATS and ORDI. This indicator allows traders and investors to analyze the relative market strength and valuation trends of 1000SATS compared to ORDI over time. By tracking this ratio, users can gain insights into market dynamics and potential trading opportunities between these two assets.
### Indicator Usage
**Purpose**:
- To compare the market capitalizations of 1000SATS and ORDI.
- To identify potential undervaluation or overvaluation of 1000SATS relative to ORDI.
- To assist in making informed trading and investment decisions based on market cap trends.
**How to Use**:
1. **Add the Indicator to Your Chart**:
- Open TradingView and navigate to your chart.
- Click on the "Indicators" button at the top of the chart.
- Select "Pine Editor" and paste the provided script.
- Click "Add to Chart" to apply the indicator.
2. **Interpret the Ratio**:
- The indicator will plot a line representing the ratio of the market capitalization of 1000SATS to ORDI.
- A rising ratio indicates that the market cap of 1000SATS is increasing relative to ORDI, suggesting stronger market performance or higher valuation of 1000SATS.
- A falling ratio indicates that the market cap of 1000SATS is decreasing relative to ORDI, suggesting weaker market performance or lower valuation of 1000SATS.
3. **Analyze Trends**:
- Use the indicator to spot trends and potential reversal points in the market cap ratio.
- Combine the ratio analysis with other technical indicators and chart patterns to enhance your trading strategy.
4. **Set Alerts**:
- Set custom alerts on the ratio to notify you of significant changes or specific thresholds being reached, enabling timely decision-making.
**Example**:
- If the ratio is consistently rising, it may indicate a good opportunity to consider 1000SATS as a stronger investment relative to ORDI.
- Conversely, if the ratio is falling, it may be a signal to reevaluate the strength of 1000SATS compared to ORDI.
**Note**: Always conduct thorough analysis and consider other market factors before making trading decisions based on this indicator.
### Script
```pinescript
//@version=4
study("1000SATS and ORDI Market Cap Ratio", shorttitle="1000SATS/ORDI Ratio", overlay=true)
// Define the circulating supply for ORDI and 1000SATS
ORDI_supply = 21000000 // Circulating supply of ORDI
SATS_1000_supply = 2100000000000 // Circulating supply of 1000SATS
// Fetch the price data for ORDI
ordi_price = security("BINANCE:ORDIUSDT", timeframe.period, close)
// Fetch the price data for 1000SATS
sats_1000_price = security("BINANCE:1000SATSUSDT", timeframe.period, close)
// Calculate the market capitalizations
ordi_market_cap = ordi_price * ORDI_supply
sats_1000_market_cap = sats_1000_price * SATS_1000_supply
// Calculate the market cap ratio
ratio = sats_1000_market_cap / ordi_market_cap
// Plot the ratio
plot(ratio, title="1000SATS/ORDI Market Cap Ratio", color=color.blue, linewidth=2)
```
This description and usage guide should help users understand the purpose and functionality of your indicator, as well as how to effectively apply it in their trading activities on TradingView.
Ethereum ETF Tracker (EET)Get all the information you need about all the different Ethereum ETF.
With the Ethereum ETF Tracker, you can observe all possible Ethereum ETF data:
ETF name.
Ticker.
Price.
Volume.
Share of total ETF volume.
Fees.
Exchange.
Custodian.
At the bottom of the table, you'll find the ETHE Premium (and ETH per Share), and day's total volume.
In addition, you can see the volume for the different Exchanges, as well as for the different Custodians.
If you don't want to display these lines to save space, you can uncheck "Show Additional Data" in the indicator settings.
The Idea
The goal is to provide the community with a tool for tracking all Ethereum ETF data in a synthesized way, directly in your TradingView chart.
How to Use
Simply read the information in the table. You can hover above the Fees and Exchanges cells for more details.
The table takes space on the chart, you can remove the extra lines by unchecking "Show Additional Data" in the indicator settings or reduce text size by changing the "Table Text Size" parameter.
Aggregate volume can be displayed directly on the graph (this volume can be displayed on any asset, such as Ethereum itself). The display can be disabled in the settings.
Coinbase vs Binance Spot Premium for All coins🔶 Coinbase Premium
This indicator allows you to track the premiums for various coins listed on Coinbase relative to Binance. The buying strength of US markets tend to be a good indicator for up trending markets.
The moving average crosses shown as ribbons can be used to time entries and exits
🔶 Available Pairs
Currently, the indicator includes 31 coins as listed below:
BTC, ETH, SOL, BONK, DOGE, XRP, SHIB, ONDO, AVAX, LINK, ENS, LTC, RNDR, INJ, BCH, ARB, OP, ADA, DOT, TIA, ICP, MATIC, LDO, NEAR, CVX, AERO, ORCA, SEI, STX, MKR, SUI
🔶 Key Features
Select Coin: You can select any of the 31 supported coins to track its premium.
Show Ribbons: Option to enable or disable the display of ribbon trend lines between two moving averages.
Adjust MA Lengths: Customizable lengths for the short and long moving averages to fine-tune the trend analysis.
🔶 Calculations
The premium is a simple nominal difference between the Coinbase price and the Binance price.
eg) Coinbase ETHUSD - Binance ETHUSDT = Premium
🔶 Disclaimer
This indicator is for informational purposes only and should not be considered financial advice.
Always conduct your own research and due diligence before making any trading decisions. Past performance is not necessarily indicative of future results.
[SGM Markov Chain]Introduction
A Markov chain is a mathematical model that describes a system evolving over time among a finite number of states. This model is based on the assumption that the future state of the system depends only on the current state and not on previous states, the so-called Markov property. In the context of financial markets, Markov chains can be used to model transitions between different market conditions, for example, the probability of a price going up after going up, or going down after going down.
Script Description
This script uses a Markov chain to calculate closing price transition probabilities across the entire accessible chart. It displays the probabilities of the following transitions:
- Up after Up (HH): Probability that the price rises after going up.
- Down after Down (BB): Probability that the price will go down after going down.
- Up after Down (HB): Probability that the price goes up after going down.
- Down after Up (BH): Probability that the price will go down after going up.
Features
- Color customization: Choose colors for each transition type.
- Table Position: Select the position of the probability display table (top/left, top/right, bottom/left, bottom/right).
Position Size CalculatorThe Position Size Calculator (PSC) is a comprehensive tool designed to assist traders in managing their trades risk by accurately calculating the optimal position size based on account settings, trade levels, and risk management parameters. This indicator helps traders make informed decisions by providing critical information about potential profit and loss , risk-reward ratio (RRR) , and position size (PS) .
█ Key Features
• Customizable Account Settings: Define your account size , currency , risk tolerance , and commission structure to personalize the calculations.
• Real-Time Trade Levels: Easily input your entry , stop loss , and take profit prices directly on the chart for immediate calculations.
• Visual Indicators: Clearly see your entry, stop loss, and take profit levels with customizable colors and labels.
• Comprehensive Position Information: View detailed information about your position, including potential profit and loss , risk-reward ratio , and position size .
• Currency Conversion: Automatically convert prices to your account currency, making it easy to manage trades in different markets.
• Hide Metrics : Choose which metrics to display to avoid emotional influence on your trading decisions (e.g., hiding PnL).
█ Conclusion
The Position Size Calculator is an essential tool for traders looking to optimize their trading strategies and manage risk effectively . By providing detailed calculations and visual indicators, this tool helps you make informed decisions, improving your overall trading performance.
█ Important
• Ensure that your stop loss and take profit levels are correctly set relative to your entry price to avoid errors.
• The default commission setting considers both entry and exit commissions. Adjust accordingly if only one commission is applicable.
Consider using this tool to manage every trade risk correctly and prevent significant drawdowns.
Hope you like it. Happy trading!
[SGM Return Distribution]Code Description
This Pine Script™ is designed to analyze the distribution of historical returns of a financial asset and project future confidence levels. It uses statistical techniques to estimate the probability of winning and losing as well as displaying confidence bands and distribution statistics.
User Entries
Length (252): The number of days used to calculate statistics.
Offset (20): Offset used to project future values.
Projection Days (10): Number of days projected into the future.
Smoothing Confidence Levels (10): Smoothing confidence bands.
Display Settings
Plot Distribution: Shows the distribution of returns.
Show Probabilities: Shows winning and losing probabilities.
Show Distribution Stats: Shows distribution statistics.
Show Confidence Bands: Shows confidence bands.
Show Confidence Lines: Shows confidence lines.
Calculations and Features
Distribution of Yields:
Calculates logarithmic returns and their statistics (average, volatility, skewness, kurtosis).
Projects the average and volatility over the projected number of days.
Displays the distribution of returns as a histogram.
Confidence Interval:
Uses the inv_norm function to calculate Z scores for different confidence levels.
Calculates the upper and lower bounds of the confidence bands.
Probability Display:
Calculates and displays win and loss probabilities based on the distribution of returns.
Statistics Display:
Shows key statistics such as mean, volatility, skewness and kurtosis.
Trust Bands and Lines:
Shows confidence bands and lines based on calculated confidence levels.
Mathematical Assumptions Used
Logarithmic Returns: Returns are calculated using the logarithm of prices, which is common for financial time series because it makes returns independent of price level.
Normal Distribution for Confidence Bands: Confidence interval calculations are based on the assumption that returns follow a normal distribution.
Average and Volatility Projection: Average returns and volatility are projected over a future period assuming they remain constant.
Skewness and Kurtosis: Although these measures are calculated for understanding the distribution of returns, they are not used in box projections but can provide additional information about the distribution of historical returns.
Use in Trading
Risk Estimation: Confidence bands can help estimate likely future price levels, which is crucial for determining strike levels and risk management.
Risk Management: Use confidence bands to set stop-loss and take-profit levels.
Probability Analysis: Win and loss probabilities can help assess a position's likelihood of success.
Potential Problems
Assumption of Normality for Confidence Bands: Financial returns do not always follow a normal distribution, especially in the presence of extreme events (fat tails).
Stationarity: Assuming that return statistics (average, volatility) remain constant over time can be erroneous in volatile market periods.
Limited Historical Data: Using a limited history (252 days) may not capture all possible behaviors of the asset.
Input Parameters: Results can be sensitive to the input parameters chosen (length, offset, etc.).
9:30 Opening Price MarkerIndicator Name: 9:30 Opening Price Marker
Description:
The "9:30 Opening Price Marker" is a custom indicator for TradingView that highlights the opening price at 9:30 AM in the UTC-4 time zone (Eastern Daylight Time) on the chart. It helps traders and analysts easily identify and track the price level at which the market opens each day.
Features:
Timezone Conversion: The indicator converts the current time to the UTC-4 timezone (Eastern Daylight Time) to accurately determine the 9:30 AM opening price.
Visual Marker: It visually marks the opening price with a dotted line on the chart, making it prominent for quick reference.
Label: Additionally, it includes a label next to the opening price line, indicating "9:30 Opening Price", enhancing clarity and usability.
Overlay: The indicator is designed to overlay on the price chart, ensuring it doesn't clutter other technical analysis tools or indicators.
Usage:
Day-to-Day Analysis: Traders can use this indicator to quickly gauge market sentiment at the daily opening, which can influence intraday trading strategies.
Reference Point: Acts as a reference point for identifying price movements and potential trading opportunities relative to the day's opening price.
Time-Specific Insights: Provides insights into price action immediately following the market open, aiding in decision-making based on early trading activity.
Installation: Copy the provided Pine Script code into TradingView's Pine Editor, save the script as an indicator, and apply it to your chart.
Disclaimer : This indicator is intended for informational purposes only and should not be solely relied upon for trading decisions. Always consider multiple sources of information and perform thorough analysis before executing trades.
Curved Smart Money Concepts Probability (Zeiierman)█ Overview
The Curved Smart Money Concepts Probability indicator, developed by Zeiierman, is a sophisticated trading tool designed to leverage the principles of Smart Money trading. This indicator identifies key market structure points and adapts to changing market conditions, providing traders with actionable insights into market trends and potential reversals. The trading tool stands out due to its unique curved structure and advanced probability features, which enhance its effectiveness and usability for traders.
█ How It Works
The indicator operates by analyzing market data to identify pivotal moments where institutional investors might be influencing price movements. It employs a combination of adaptive trend lengths, multipliers for sensitivity adjustments, and pivot periods to accurately capture market structure shifts. The indicator calculates upper and lower bands based on adaptive sizes and identifies zones of overbought (premium) and oversold (discount) conditions.
Key Features of Probability Calculations
The Curved Smart Money Concepts Probability indicator integrates sophisticated probability calculations to enhance trading decision-making:
Win/Loss Tracking: The indicator tracks the number of successful (win) and unsuccessful (loss) trades based on the identified market structure points (ChoCH, SMS, BMS). This provides a historical context of the indicator's performance.
Probability Percentages: For each market structure point (ChoCH, SMS, BMS), the indicator calculates the probability of the next move being successful or not. This is presented as a percentage, giving traders a quantifiable measure of confidence in the signals.
Dynamic Adaptation: The probability calculations adapt to market conditions by considering the frequency and success rate of the signals, allowing traders to adjust their strategies based on the indicator’s historical accuracy.
Visual Representation: Probabilities are displayed on the chart, helping traders quickly assess the likelihood of future price movements based on past performance.
Key benefits of the Curved Structure
The Curved Smart Money Concepts Probability indicator features a unique curved structure that offers several advantages over traditional linear structures:
Noise Reduction: The curved structure smooths out short-term market fluctuations, reducing the noise often seen in linear structures. This helps traders focus on the true trend direction rather than getting distracted by minor price movements.
Adaptive Sensitivity: The curved structure adjusts its sensitivity based on market conditions. This means it can effectively capture both short-term and long-term trends by dynamically adapting to changes in market volatility, something linear structures struggle with.
Enhanced Trend Detection: By providing a more gradual transition between market phases, the curved structure helps in identifying trends more accurately. This is particularly useful in volatile markets where linear structures might give false signals due to their rigid nature.
Improved Market Structure Analysis: The curved structure's ability to adapt and smooth out irregularities provides a clearer picture of the overall market structure. This clarity is essential for identifying premium and discount zones, as well as mid-range support and resistance levels, which are crucial for effective ICT Smart Money Trading.
█ Terminology
ChoCH (Change of Character): Indicates a potential reversal in market direction. It is identified when the price breaks a significant high or low, suggesting a shift from a bullish to bearish trend or vice versa.
SMS (Smart Money Shift): Represents the transition phase in market structure where smart money begins accumulating or distributing assets. It typically follows a BMS and indicates the start of a new trend.
BMS (Bullish/Bearish Market Structure): Confirms the trend direction. Bullish Market Structure (BMS) confirms an uptrend, while Bearish Market Structure (BMS) confirms a downtrend. It is characterized by a series of higher highs and higher lows (bullish) or lower highs and lower lows (bearish).
Premium: A zone where the price is considered overbought. It is calculated as the upper range of the current market structure and indicates a potential area for selling or shorting.
Mid Range: The midpoint between the high and low of the market structure. It often acts as a support or resistance level, helping traders identify potential reversal or continuation points.
Discount: A zone where the price is considered oversold. It is calculated as the lower range of the current market structure and indicates a potential area for buying or going long.
█ How to Use
Identifying Trends and Reversals: Traders can use the indicator to identify the overall market trend and potential reversal points. By observing the ChoCH, SMS, and BMS signals, traders can gauge whether the market is transitioning into a new trend or continuing the current trend.
Example Strategies
⚪ Trend Following Strategy:
Identify the current market trend using BMS signals.
Enter a trade in the direction of the trend when the price retraces to the mid-range zone.
Set a stop-loss just below the mid-range (for long trades) or above the mid-range (for short trades).
Take profit in the premium/discount zone or when a ChoCH signal indicates a potential reversal.
⚪ Reversal Strategy:
Wait for a ChoCH signal to identify a potential market reversal.
Enter a trade in the direction of the new trend as indicated by the SMS signal.
Set a stop-loss just beyond the recent high (for short trades) or low (for long trades).
Take profit when the price reaches the premium or discount zone opposite to the entry.
█ Settings
Curved Trend Length: Determines the length of the trend used to calculate the adaptive size of the structure. Adjusting this length allows traders to capture either longer-term trends (for smoother curves) or short-term trends (for more reactive curves).
Curved Multiplier: Scales the adjustment factors for the upper and lower bands. Increasing the multiplier widens the bands, reducing sensitivity to price changes. Decreasing it narrows the bands, making the structure more responsive.
Pivot Period: Sets the period for capturing trends. A higher period captures broader trends, while a lower period focuses on short-term trends.
Response Period: Adjusts the structure’s responsiveness. A low value focuses on short-term changes, while a high value smoothens the structure.
Premium/Discount Range: Allows toggling between displaying the active range or previous range to analyze real-time or historical levels.
Structure Candles: Enables the display of curved structure candles on the chart, providing a modified view of price action.
-----------------
Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Moving Average Z-Score Suite [BackQuant]Moving Average Z-Score Suite
1. What is this indicator
The Moving Average Z-Score Suite is a versatile indicator designed to help traders identify and capitalize on market trends by utilizing a variety of moving averages. This indicator transforms selected moving averages into a Z-Score oscillator, providing clear signals for potential buy and sell opportunities. The indicator includes options to choose from eleven different moving average types, each offering unique benefits and characteristics. It also provides additional features such as standard deviation levels, extreme levels, and divergence detection, enhancing its utility in various market conditions.
2. What is a Z-Score
A Z-Score is a statistical measurement that describes a value's relationship to the mean of a group of values. It is measured in terms of standard deviations from the mean. For instance, a Z-Score of 1.0 means the value is one standard deviation above the mean, while a Z-Score of -1.0 indicates it is one standard deviation below the mean. In the context of financial markets, Z-Scores can be used to identify overbought or oversold conditions by determining how far a particular value (such as a moving average) deviates from its historical mean.
3. What moving averages can be used
The Moving Average Z-Score Suite allows users to select from the following eleven moving averages:
Simple Moving Average (SMA)
Hull Moving Average (HMA)
Exponential Moving Average (EMA)
Weighted Moving Average (WMA)
Double Exponential Moving Average (DEMA)
Running Moving Average (RMA)
Linear Regression Curve (LINREG) (This script can be found standalone )
Triple Exponential Moving Average (TEMA)
Arnaud Legoux Moving Average (ALMA)
Kalman Hull Moving Average (KHMA)
T3 Moving Average
Each of these moving averages has distinct properties and reacts differently to price changes, allowing traders to select the one that best fits their trading style and market conditions.
4. Why Turning a Moving Average into a Z-Score is Innovative and Its Benefits
Transforming a moving average into a Z-Score is an innovative approach because it normalizes the moving average values, making them more comparable across different periods and instruments. This normalization process helps in identifying extreme price movements and mean-reversion opportunities more effectively. By converting the moving average into a Z-Score, traders can better gauge the relative strength or weakness of a trend and detect potential reversals. This method enhances the traditional moving average analysis by adding a statistical perspective, providing clearer and more objective trading signals.
5. How It Can Be Used in the Context of a Trading System
In a trading system, it can be used to generate buy and sell signals based on the Z-Score values. When the Z-Score crosses above zero, it indicates a potential buying opportunity, suggesting that the price is above its mean and possibly trending upward. Conversely, a Z-Score crossing below zero signals a potential selling opportunity, indicating that the price is below its mean and might be trending downward. Additionally, the indicator's ability to show standard deviation levels and extreme levels helps traders set profit targets and stop-loss levels, improving risk management and trade planning.
6. How It Can Be Used for Trend Following
For trend-following strategies, it can be particularly useful. The Z-Score oscillator helps traders identify the strength and direction of a trend. By monitoring the Z-Score and its rate of change, traders can confirm the persistence of a trend and make informed decisions to enter or exit trades. The indicator's divergence detection feature further enhances trend-following by identifying potential reversals before they occur, allowing traders to capitalize on trend shifts. By providing a clear and quantifiable measure of trend strength, this indicator supports disciplined and systematic trend-following strategies.
No backtests for this indicator due to the many options and ways it can be used,
Enjoy
Trend Forecasting - The Quant Science🌏 Trend Forecasting | ENG 🌏
This plug-in acts as a statistical filter, adding new information to your chart that will allow you to quickly verify the direction of a trend and the probability with which the price will be above or below the average in the future, helping you to uncover probable market inefficiencies.
🧠 Model calculation
The model calculates the arithmetic mean in relation to positive and negative events within the available sample for the selected time series. Where a positive event is defined as a closing price greater than the average, and a negative event as a closing price less than the average. Once all events have been calculated, the probabilities are extrapolated by relating each event.
Example
Positive event A: 70
Negative event B: 30
Total events: 100
Probabilities A: (100 / 70) x 100 = 70%
Probabilities B: (100 / 30) x 100 = 30%
Event A has a 70% probability of occurring compared to Event B which has a 30% probability.
🔍 Information Filter
The data on the graph show the future probabilities of prices being above average (default in green) and the probabilities of prices being below average (default in red).
The information that can be quickly retrieved from this indicator is:
1. Trend: Above-average prices together with a constant of data in green greater than 50% + 1 indicate that the observed historical series shows a bullish trend. The probability is correlated proportionally to the value of the data; the higher and increasing the expected value, the greater the observed bullish trend. On the other hand, a below-average price together with a red-coloured data constant show quantitative data regarding the presence of a bearish trend.
2. Future Probability: By analysing the data, it is possible to find the probability with which the price will be above or below the average in the future. In green are classified the probabilities that the price will be higher than the average, in red are classified the probabilities that the price will be lower than the average.
🔫 Operational Filter .
The indicator can be used operationally in the search for investment or trading opportunities given its ability to identify an inefficiency within the observed data sample.
⬆ Bullish forecast
For bullish trades, the inefficiency will appear as a historical series with a bullish trend, with high probability of a bullish trend in the future that is currently below the average.
⬇ Bearish forecast
For short trades, the inefficiency will appear as a historical series with a bearish trend, with a high probability of a bearish trend in the future that is currently above the average.
📚 Settings
Input: via the Input user interface, it is possible to adjust the periods (1 to 500) with which the average is to be calculated. By default the periods are set to 200, which means that the average is calculated by taking the last 200 periods.
Style: via the Style user interface it is possible to adjust the colour and switch a specific output on or off.
🇮🇹Previsione Della Tendenza Futura | ITA 🇮🇹
Questo plug-in funge da filtro statistico, aggiungendo nuove informazioni al tuo grafico che ti permetteranno di verificare rapidamente tendenza di un trend, probabilità con la quale il prezzo si troverà sopra o sotto la media in futuro aiutandoti a scovare probabili inefficienze di mercato.
🧠 Calcolo del modello
Il modello calcola la media aritmetica in relazione con gli eventi positivi e negativi all'intero del campione disponibile per la serie storica selezionata. Dove per evento positivo si intende un prezzo alla chiusura maggiore della media, mentre per evento negativo si intende un prezzo alla chiusura minore della media. Calcolata la totalità degli eventi le probabilità vengono estrapolate rapportando ciascun evento.
Esempio
Evento positivo A: 70
Evento negativo B: 30
Totale eventi : 100
Formula A: (100 / 70) x 100 = 70%
Formula B: (100 / 30) x 100 = 30%
Evento A ha una probabilità del 70% di realizzarsi rispetto all' Evento B che ha una probabilità pari al 30%.
🔍 Filtro informativo
I dati sul grafico mostrano le probabilità future che i prezzi siano sopra la media (di default in verde) e le probabilità che i prezzi siano sotto la media (di default in rosso).
Le informazioni che si possono rapidamente reperire da questo indicatore sono:
1. Trend: I prezzi sopra la media insieme ad una costante di dati in verde maggiori al 50% + 1 indicano che la serie storica osservata presenta un trend rialzista. La probabilità è correlata proporzionalmente al valore del dato; tanto più sarà alto e crescente il valore atteso e maggiore sarà la tendenza rialzista osservata. Viceversa, un prezzo sotto la media insieme ad una costante di dati classificati in colore rosso mostrano dati quantitativi riguardo la presenza di una tendenza ribassista.
2. Probabilità future: analizzando i dati è possibile reperire la probabilità con cui il prezzo si troverà sopra o sotto la media in futuro. In verde vengono classificate le probabilità che il prezzo sarà maggiore alla media, in rosso vengono classificate le probabilità che il prezzo sarà minore della media.
🔫 Filtro operativo
L' indicatore può essere utilizzato a livello operativo nella ricerca di opportunità di investimento o di trading vista la capacità di identificare un inefficienza all'interno del campione di dati osservato.
⬆ Previsione rialzista
Per operatività di tipo rialzista l'inefficienza apparirà come una serie storica a tendenza rialzista, con alte probabilità di tendenza rialzista in futuro che attualmente si trova al di sotto della media.
⬇ Previsione ribassista
Per operatività di tipo short l'inefficienza apparirà come una serie storica a tendenza ribassista, con alte probabilità di tendenza ribassista in futuro che si trova attualmente sopra la media.
📚 Impostazioni
Input: tramite l'interfaccia utente Input è possibile regolare i periodi (da 1 a 500) con cui calcolare la media. Di default i periodi sono impostati sul valore di 200, questo significa che la media viene calcolata prendendo gli ultimi 200 periodi.
Style: tramite l'interfaccia utente Style è possibile regolare il colore e attivare o disattivare un specifico output.
ARIMA Indicator with Optional SmoothingOverview
The ARIMA (AutoRegressive Integrated Moving Average) Indicator is a powerful tool used to forecast future price movements by combining differencing, autoregressive, and moving average components. This indicator is designed to help traders identify trends and potential reversal points by analyzing the historical price data.
Key Features
AutoRegressive Component (AR): Utilizes past values to predict future prices.
Moving Average Component (MA): Averages past price differences to smooth out noise.
Differencing: Reduces non-stationarity in the time series data.
Optional Smoothing: Applies EMA to the ARIMA output for a smoother signal.
Customizable Parameters: Allows users to adjust AR and MA orders, differencing periods, and smoothing lengths.
Concepts Underlying the Calculations
Differencing: Subtracts previous prices from current prices to remove trends and seasonality, making the data stationary.
AutoRegressive Component (AR): Predicts future prices based on a linear combination of past values.
Moving Average Component (MA): Uses past forecast errors to refine future predictions.
Exponential Moving Average (EMA): Applies more weight to recent prices, providing a smoother and more responsive signal.
How It Works
The ARIMA Indicator first calculates the differenced series to achieve stationarity. Then, it computes the simple moving average (SMA) of this differenced series. The indicator uses the AR and MA components to adjust the SMA, creating an approximation of the ARIMA model. Finally, an optional smoothing step using EMA can be applied to the ARIMA approximation to produce a smoother signal.
How Traders Can Use It
Traders can use the ARIMA Indicator to:
Identify Trends: Detect emerging trends by observing the direction of the ARIMA line.
Spot Reversals: Look for divergences between the ARIMA line and the price to identify potential reversal points.
Generate Trading Signals: Use crossovers between the ARIMA line and the price to generate buy or sell signals.
Filter Noise: Enable the optional smoothing to filter out market noise and focus on significant price movements.
Example Usage Instructions
Add the ARIMA Indicator to your chart.
Adjust the input parameters to suit your trading strategy:
Set the SMA Length (e.g., 14).
Choose the Differencing Period (e.g., 1).
Define the AR Order (p) and MA Order (q) (e.g., 1).
Configure the Smoothing Length if smoothing is desired (e.g., 5).
Enable or disable smoothing as needed.
Observe the ARIMA line (blue) and compare it to the price chart.
Use the ARIMA line to identify trends and potential reversals.
Implement trading decisions based on the ARIMA line’s behavior relative to the price.
Markov Chain Trend IndicatorOverview
The Markov Chain Trend Indicator utilizes the principles of Markov Chain processes to analyze stock price movements and predict future trends. By calculating the probabilities of transitioning between different market states (Uptrend, Downtrend, and Sideways), this indicator provides traders with valuable insights into market dynamics.
Key Features
State Identification: Differentiates between Uptrend, Downtrend, and Sideways states based on price movements.
Transition Probability Calculation: Calculates the probability of transitioning from one state to another using historical data.
Real-time Dashboard: Displays the probabilities of each state on the chart, helping traders make informed decisions.
Background Color Coding: Visually represents the current market state with background colors for easy interpretation.
Concepts Underlying the Calculations
Markov Chains: A stochastic process where the probability of moving to the next state depends only on the current state, not on the sequence of events that preceded it.
Logarithmic Returns: Used to normalize price changes and identify states based on significant movements.
Transition Matrices: Utilized to store and calculate the probabilities of moving from one state to another.
How It Works
The indicator first calculates the logarithmic returns of the stock price to identify significant movements. Based on these returns, it determines the current state (Uptrend, Downtrend, or Sideways). It then updates the transition matrices to keep track of how often the price moves from one state to another. Using these matrices, the indicator calculates the probabilities of transitioning to each state and displays this information on the chart.
How Traders Can Use It
Traders can use the Markov Chain Trend Indicator to:
Identify Market Trends: Quickly determine if the market is in an uptrend, downtrend, or sideways state.
Predict Future Movements: Use the transition probabilities to forecast potential market movements and make informed trading decisions.
Enhance Trading Strategies: Combine with other technical indicators to refine entry and exit points based on predicted trends.
Example Usage Instructions
Add the Markov Chain Trend Indicator to your TradingView chart.
Observe the background color to quickly identify the current market state:
Green for Uptrend, Red for Downtrend, Gray for Sideways
Check the dashboard label to see the probabilities of transitioning to each state.
Use these probabilities to anticipate market movements and adjust your trading strategy accordingly.
Combine the indicator with other technical analysis tools for more robust decision-making.
SD Distance Mean BetaThe "SD Distance Mean Indicator" is a currently a developing tool designed to enhance trading precision by dynamically adjusting to market conditions. This indicator provides insights into price deviations from the mean, helping traders make inf OANDA:XAUUSD ormed decisions based on significant price movements.
Key Features:
Adaptive Length Adjustment:
The indicator dynamically adjusts the calculation period based on the Average True Range (ATR). This allows it to respond to different market conditions, using a shorter length during consolidations and a longer length during trends.
Standardized Distance Calculation:
The indicator calculates the distance of the current price from the mean and standardizes it using the standard deviation. This standardized distance is then smoothed to reduce noise and provide clearer signals.
Dynamic Standard Deviation (SD) Levels:
SD levels are adjusted dynamically based on ATR, providing a more accurate representation of price volatility. These levels are further smoothed to minimize wiggling on shorter timeframes like the 30-minute chart.
Visual Cues for Trading Signals:
The indicator plots multiple SD levels (+1, +2, +3, +4 and their negatives) and highlights significant price movements. When the standardized distance line hits or exceeds these levels, it signals potential overbought or oversold conditions.
Customizable Smoothing: The smoothing length for both the standardized distance and SD levels can be customized to suit different trading strategies and timeframes. Default values are set to provide a balance between responsiveness and stability.
Usage:
Identifying Reversals : The indicator helps in spotting potential reversal points. When the smoothed standardized distance line hits +2 SD or -2 SD and rebounds, it signals a possible price reversal back towards the mean.
Confirming Trends: Dynamic SD levels provide a clear visual representation of price volatility, helping traders confirm trend strength and potential breakout points.
Enhancing Precision: By dynamically adjusting to market conditions, the indicator enhances trading precision, making it suitable for various market environments.
This script is an essential addition to any trader's toolkit, offering a blend of adaptability, precision, and visual clarity to support more informed trading decisions.
Settings:
Short Length: Period length used during consolidations.
Long Length: Period length used during trends.
ATR Length: Length for ATR calculation.
ATR Threshold: Threshold value to switch between short and long lengths.
Smoothing Length: Length for smoothing the standardized distance.
SD Smoothing Length: Length for smoothing the dynamic SD levels.
By using this indicator, traders can leverage its adaptive capabilities to navigate various market conditions effectively and enhance their trading performance on XAUUSD and other assets.
Consecutive Closes Above/Below 3 SMA with Z-Score BandsA simple indicator that measures consecutive closes above & below the 3-period simple moving average. An upper and lower Z-score has been calculated to indicate where the 4 standard deviations of the last 60 bars sits.
Useful for identifying directional runs in price.
PEV Price BandThe PEV Price Band shows prices calculated using the high and low P/FQ EV of the previous period. (price to enterprise value per share for the last quarter) multiplied by FQ's current EVPS (similar to comparing marketcap to enterprise value but edit equations that are close to the theory of P/E)
If the current price is lower than the minimum P/EVPS, it is considered cheap. In other words, a current price is above the maximum is considered expensive.
PEV Price Band consists of 2 parts.
- First of all, the current P/EVPS value is "green" (if the markecap is less than the enterprise value) or "red" (if the marketcap is more than the enterprise value) or "gold" (if the market value is less than the enterprise value and less than equity)
- Second, the blue line is the closing price.
Easy Scalping Lot Calculator for ForexThe calculator was created to make it easier to calculate the lot size on Forex. I planned to use it for the following pairs: AUDCAD, AUDCHF, AUDJPY, AUDUSD, EURAUD, EURCAD, EURCHF, EURGBP, EURJPY, EURNZD, EURUSD, GBPCHF, GBPJPY, GBPUSD, NZDUSD, USDCAD, USDCHF, USDJPY, XAUUSD.
The indicator is a table that shows the calculation of the lot for a predetermined stop loss.
For example, you are planning a trade, have calculated a stop loss of 15 points, and by checking the table you understand approximately what lot you need to use to limit your risk.
In the settings you can change the risk and also determine the stop loss value in points.
The calculator does not take into account the spread in the calculations.
There are websites where you can accurately calculate the lot, but if you trade on small time frames this is not suitable for you.
The calculator uses the formula:
Lot size = maximum risk / stop loss (in pips) / minimum pip value x minimum trading lot.
Holding ValueTrading view requires me to add a larger description:
Short done by me: Show your holding value at each candlestick
Chatgpt:
This Pine Script plugin is designed to help traders and investors visualize the current value of their holdings in USD directly on TradingView charts. The plugin calculates the total value of the specified holdings based on the closing price of each candle and displays this value dynamically, formatted to show in thousands (k) or millions (m) with a maximum of two decimal places.
Features
Holdings Input: Allows the user to input the amount of the asset they hold.
Dynamic Calculation: Calculates the current value of holdings based on the closing price of each candle.
Formatted Display: Formats the value in thousands or millions with up to two decimal places.
Chart Label: Displays the formatted value as a label on the chart.
Data Window Display: Uses plotchar to display the current value in the data window without plotting it directly on the chart.
Scaled Historical ATR [SS]Hello again everyone,
This is the Scaled ATR Range indicator. This was done in response to an article/analysis I posted regarding the expected high and range on SPX. I would encourage you to read it here:
Essentially, I took SPX data, scaled it to correct for inflation, then calculated the ATR for Bullish years to get our average range to expect and our close range to expected.
I accomplished this analysis using Excel; however, I figured Pinescript would handle this type of task more elegantly, and I was correct!
This indicator is the result.
What it does:
This indicator permits the analyst to select a historic period in time. The indicator will then scale the period into returns and convert the range to a corrected range based on the current position of the ticker. How it does this is by converting the returns of the historic period selected, then multiplying the returns by the current period open, to ensure that the range amounts are corrected for inflation and natural growth of a ticker.
I say analyst because this indicator is intended to be used by both professional and recreational analysts, to give them an easy way to:
a) Scale historic data and correct it based on the current rate; and
b) Offer insight into a ticker’s ATR and behaviour during bullish and bearish periods.
Prior to this indicator, the only way to do this would be manually or the use of statistical software.
How to use?
The indicator’s use is quite simple. Once launched, the indicator will ask the user to input a timeframe period that the user is interested in assessing. In the main chart above, I chose SPX between 1995 and 2001.
The user can further filter down the data using the settings menu. In the settings menu, there is an option to filter by “All”, “Bullish Periods” or “Bearish Periods”.
Filtering by “All”
Filtering by “All” will include all candles selected within the timeframe. This includes both bearish and bullish candles. It will give you the averaged out range for the entire period of time, including both bearish and bullish instances.
Filtering by “Bullish”
Filtering by “Bullish” will omit any red candles from the analysis. It will only return the ATR ranges for green, bullish candles.
Filtering by “Bearish”
Inverse to filtering by Bullish, if you filter by Bearish, it will only include the red, bearish candles in the analysis.
My suggestion? If you are trying to determine t he likely outcome of a bullish year, filter by Bullish instances. If you want the likely outcome of a bearish year, filter by Bearish.
Other features of the Indicator:
The indicator will display the current period statistics. In the main chart above, you can see that the current ranges for this year are displayed. This allows you to do a side by side comparison of the current period vs. the historic period you are looking at. This can alert you to further upside, further downside and the anticipated close range. It can also alert you to whether or not we are following a similar trajectory as the historical periods you are looking at.
As well, the indicator will list target prices for the current period based on the historical periods you are looking at. This helps to put things into perspective.
Concluding Remarks
And that is the indicator in a nutshell! I encourage you to read the article I linked above to see how you may use it in an analysis. This would be the best example of a real world application of this indicator!
Otherwise, I hope you enjoy and, as always, safe trades!
MVRV-Z adjusted EN version (by ilyaevp95)Descriptions:
The MVRV Z-Score indicator is a powerful tool designed by original authors Murad Mahmudov and David Puell for BTC to help traders make informed decisions about their cryptocurrency investments. It is based on the MVRV (Market Value to Realized Value) metric, which measures the relationship between the market capitalization and the realized capitalization of a cryptocurrency. The indicator provides signals for accumulating or selling an asset based on deviations in market capitalization from realized capitalization.
How it works:
Market Capitalization : This is the total value of coins that have been issued at a given point in time. Market capitalization is calculated by multiplying the current price of the asset by the number of coins that have been issued.
Realized Capitalization (Realized Price) : This is the amount of money that has been spent on purchasing a particular asset. In the context of cryptocurrencies, it represents the sum of all transaction values for a specific blockchain. Realized capitalization can be calculated using historical data on transaction prices.
MVRV Metric : The MVRV metric compares market capitalization with realized capitalization, providing a measure of how overvalued or undervalued a cryptocurrency is relative to its historical transaction data. A high MVRV value indicates that the market is overvaluing the asset, while a low MVRV suggests undervaluation.
Z-Score Calculation : The Z-score is a statistical measure that normalizes the deviation of market capitalization from its mean value (realized capitalization) to a standard deviation. This makes it possible to compare assets that have different values and time periods, as it takes into account the volatility of the market.
Note: For accurate Z-score calculation, you need to use the indicator on a chart with a mostly complete historical data set for a specific cryptocurrency.
Signals : Based on the Z-score, the indicator generates signals for accumulation or sale. If the Z-score falls below a certain threshold (negative), it may indicate an opportunity to accumulate the asset. Conversely, if the Z-score rises above a positive threshold, it could suggest a potential sell signal.
The indicator uses a color-coded system to provide traders with visual cues:
Green background indicates a signal to accumulate.
Orange (Red) background indicates a signal to sell.
Deviations exceeding the specified thresholds by 1 and 2 Z (positive direction), 0.5 and 1 Z (negative direction) are highlighted in a brighter color, indicating more extreme deviations.
Note: The signals provided by this indicator should not be considered financial advice. Traders should conduct their own research (DYOR) before making any investment decisions.
Parameters: The indicator provides several parameters for customization:
Blockchain : The blockchain for which the analysis is performed. This allows the user to select the specific blockchain they are interested in analyzing. The default value is BTC.
Z threshold for positive deviations : This parameter sets the threshold above which the deviation will be considered positive. A higher value will result in fewer signals, while a lower value may generate more false signals. The default value is 3.0.
Z threshold for negative deviations : Similar to the previous parameter, this sets the threshold below which the deviation will be considered negative. The default value is 0.
Market Capitalization : There are two types of market capitalization available: Standard and Free float coin capitalization. Free float is calculated by multiplying its current price by the total number of units in free circulation - the number that are not locked in any contracts or other forms of restriction. For DASH, ZEC, BAT and ALGO available only Free float capitalization. The default value is "Standard"
Negative Deviation Filter Mode : When enabled, if the deviation has been positive for a certain number of previous weeks (the default value is 40 weeks), the indicator will not generate a signal to accumulate. This helps to avoid false signals during the start of a bearish market. This may be helpful for volatile coins, whose price can drastically fall below the realized price after the end of a bull market. The default setting is "disabled".
Display Options:
MVRV plot : Displays the MVRV metric for the selected blockchain.
Z-Score plot : Shows the Z-score calculated by the indicator.
Realized Price plot : Provides a visual representation of the realized price of the cryptocurrency on main chart.
S ignal Display : Choose whether to display signals on the main chart or in a separate panel.
Historical mode : Choose whether to show signals for all historical data on the chart or for a certain number of periods. The default setting is "disabled".
Groupings [SS]Hey everyone,
Releasing this indicator called groupings.
If you watch/read my analyses on Tradingview, you will have heard me talk about groups. Groups is something I invented. What it is, is just taking the Euclidean Distance (ED) of the previous 5 candles in a specified period (i.e. daily timeframe, weekly, 1 minute, 5 minute, etc.) and rounding the ED up to a whole number.
I have had great success in this approach because the information provided is broad enough to give leniency in interpretation but narrow enough to hone in on potential moves and target prices.
This indicator is a simplified version of how I do groupings in other software, however it is no less powerful!
What do groups tell us?
A "group" takes into account the previous 5 candles, using the ED. This gives Pinescript a general idea of what the short term trend looks like mathematically. From there, Pinescript can look for other groups that looked similar to how this current trend looks. From there, it can offer us insights into what tends to happen in candles subsequent to this group. For example, the ATR range, the close range and whether it is bearish or bullish.
And that is precisely how this indicator operates, Pinescript will calculate the group of the previous 5 canndles in the timeframe period you are looking at. It will then lookback over the designated "train" length and identify previous groups, and what happened in those groups. It looks specifically at:
- What is that average High ATR associated with that group,
- What is the average Low ATR associated with that group,
- What is the average close range associated with that group,
- What is the sentiment associated with that group.
How to use the indicator?
In terms of use, the indicator is relatively simple to use. It will plot three lines, a red for the anticipated low range, a green for the anticipated high range and purple for the opening range (where the current candle opened at).
In addition, it will plot a dot for the anticipated close area. When the dot is green, it expects a bullish close. When the dot is red, it expects a bearish close.
The indicator is going to give you a heads up as to whether we are in a bullish group, what you can anticipate the high and low range to be and where you can anticipate the close.
Of course, its not always exact, as in the image above you can see it underestimated the high range and over-estimated the low range; however, we did close within the anticipate range.
The indicator is meant to help you with your bias. I will reference this indicator on the daily timeframe at open to see what the expectations are for the day.
However, you can use it on any timeframe you wish.
Other functions:
The indicator can plot the EMA 9, 21 and 5. These are the 3 indicators I like and I find them helpful for both intraday and swing trading. However, they can be toggled off if you do not wish to view them.
In addition, the EMAs will be green if the ticker is trending above the EMA 21 (which is a critical EMA for me to determine the immediate sentiment). If the ticker is below, they will turn red.
There is also the ability to adjust the train time. The default is 1,000 candles back, but I usually have it on 1500. If you have a lot of indicators and a lot going on, on your chart, you may find that 1500 is too much and it will lag/error. That’s okay, 500 candles is sufficient and will not put a lot of stress on Pinescript.
Concluding remarks
Its overall a fairly simple concept and indicator, but it has been a neat and helpful / insightful invention. I originally developed this using R and happy to have now brought it into Pinescript.
I hope you enjoy!
Safe trades everyone!
Frequency and Volume ProfileFREQUENCY & VOLUME PROFILE
⚪ OVERVIEW
The Frequency and Volume Profile indicator plots a frequency or volume profile based on the visible bars on the chart, providing insights into price levels with significant trading activity.
⚪ USAGE
● Market Structure Analysis:
Identify key price levels where significant trading activity occurred, which can act as support and resistance zones.
● Volume Analysis:
Use the volume mode to understand where the highest trading volumes have occurred, helping to confirm strong price levels.
● Trend Confirmation:
Analyze the distribution of trading activity to confirm or refute trends, mark important levels as support and resistance, aiding in making more informed trading decisions.
● Frequency Distribution:
In statistics, a frequency distribution is a list of the values that a variable takes in a sample. It is usually a list. Displayed as a histogram.
⚪ SETTINGS
Source: Select the price data to use for the profile calculation (default: hl2).
Move Profile: Set the number of bars to offset the profile from the current bar (default: 100).
Mode: Choose between "Frequency" and "Volume" for the profile calculation.
Profile Color: Customize the color of the profile lines.
Lookback Period: Uses 5000 bars for daily and higher timeframes, otherwise 10000 bars.
The Frequency Profile indicator is a powerful tool for visualizing price levels with significant trading activity, whether in terms of frequency or volume. Its dynamic calculation and customizable settings make it a versatile addition to any trading strategy.
