BTC InsightThis script is a comprehensive tool for analyzing Bitcoin's daily price range, trend predictions, and significant volume-based order block levels. It combines multiple technical analysis concepts, including exponential moving averages (EMAs), logarithmic calculations, and custom indicators for advanced forecasting and visualization.
Key Features and Technical Details
1. Exponential Moving Averages (EMAs)
The script calculates two smoothed EMAs:
EMA1 and EMA2 are derived from the logarithmic price of Bitcoin (log(close)).
The smoothing periods and multipliers are user-configurable through inputs:
Smoothed EMA1 Period (default: 728)
Smoothed EMA2 Period (default: 728)
Initial EMA Multipliers (default: 1.0 for EMA1, 5.0 for EMA2)
A time decay factor is applied to the multipliers to adjust sensitivity over time, making the EMAs adaptive to market dynamics.
2. Logarithmic Domain Calculations
The script uses logarithmic transformations to enhance accuracy when dealing with large price changes.
Adjustments to EMAs are made in the logarithmic domain and converted back to the price domain for plotting.
3. EMA Forecasting
The script performs a linear regression analysis over a specified period (728 bars by default) to estimate future price trends for both EMAs.
Slope Adjustments:
RSI (Relative Strength Index) is incorporated to modify the forecast slope dynamically:
RSI > 70: Bearish adjustment (-0.5)
RSI < 30: Bullish adjustment (+0.5)
Forecasts are plotted as dashed lines, projecting future values of EMA1 (green) and EMA2 (red).
4. Order Block Detection
Detects order block levels based on high volume spikes relative to the average volume over a lookback period (default: 100 bars).
A volume multiplier (default: 1.5x) is applied to identify significant volume activity.
Two types of order blocks are identified:
Below EMA1: A price zone where significant buying occurred below EMA1.
Above EMA2: A price zone where significant selling occurred above EMA2.
Order blocks are visualized as shaded rectangles:
Green boxes represent order blocks below EMA1.
Red boxes represent order blocks above EMA2.
5. Customization Inputs
The script allows fine-tuning via the following parameters:
EMA Settings: Periods, multipliers, and time factors for both EMAs.
Volume Analysis Settings: Lookback period and volume multiplier for order block detection.
Order Block Box Settings: Height of the range as a percentage of the detected price.
6. Visualization
EMAs: Two smoothed exponential moving averages are plotted with configurable offsets.
Forecast Lines: Dashed lines project future EMA trends based on regression analysis.
Order Block Boxes: Highlight areas of high volume below EMA1 and above EMA2, indicating potential support or resistance zones.
How It Works in Practice
EMAs and Trend Analysis:
The EMAs represent long-term market trends, adjusted dynamically using custom multipliers and time decay.
The script forecasts the EMAs' future trajectories to anticipate potential price movements.
Order Blocks:
High-volume zones indicate areas where significant market activity occurred, providing insights into potential price reversal points or continuation zones.
RSI Integration:
RSI-based slope adjustment fine-tunes the EMA forecast, adding an extra layer of dynamic market context.
Comprehensive View:
By combining trend forecasts with volume-based zones, the script delivers a robust analysis tool for identifying potential entry/exit points, support/resistance levels, and long-term trend predictions.
Cerca negli script per "Exponential"
Machine Learning RSI [BackQuant]Machine Learning RSI
The Machine Learning RSI is a cutting-edge trading indicator that combines the power of Relative Strength Index (RSI) with Machine Learning (ML) clustering techniques to dynamically determine overbought and oversold thresholds. This advanced indicator adapts to market conditions in real-time, offering traders a robust tool for identifying optimal entry and exit points with increased precision.
Core Concept: Relative Strength Index (RSI)
The RSI is a well-known momentum oscillator that measures the speed and change of price movements, oscillating between 0 and 100. Typically, RSI values above 70 are considered overbought, and values below 30 are considered oversold. However, static thresholds may not be effective in all market conditions.
This script enhances the RSI by integrating a dynamic thresholding system powered by Machine Learning clustering, allowing it to adapt thresholds based on historical RSI behavior and market context.
Machine Learning Clustering for Dynamic Thresholds
The Machine Learning (ML) component uses clustering to calculate dynamic thresholds for overbought and oversold levels. Instead of relying on fixed RSI levels, this indicator clusters historical RSI values into three groups using a percentile-based initialization and iterative optimization:
Cluster 1: Represents lower RSI values (typically associated with oversold conditions).
Cluster 2: Represents mid-range RSI values.
Cluster 3: Represents higher RSI values (typically associated with overbought conditions).
Dynamic thresholds are determined as follows:
Long Threshold: The upper centroid value of Cluster 3.
Short Threshold: The lower centroid value of Cluster 1.
This approach ensures that the indicator adapts to the current market regime, providing more accurate signals in volatile or trending conditions.
Smoothing Options for RSI
To further enhance the effectiveness of the RSI, this script allows traders to apply various smoothing methods to the RSI calculation, including:
Simple Moving Average (SMA)
Exponential Moving Average (EMA)
Weighted Moving Average (WMA)
Hull Moving Average (HMA)
Linear Regression (LINREG)
Double Exponential Moving Average (DEMA)
Triple Exponential Moving Average (TEMA)
Adaptive Linear Moving Average (ALMA)
T3 Moving Average
Traders can select their preferred smoothing method and adjust the smoothing period to suit their trading style and market conditions. The option to smooth the RSI reduces noise and makes the indicator more reliable for detecting trends and reversals.
Long and Short Signals
The indicator generates long and short signals based on the relationship between the RSI value and the dynamic thresholds:
Long Signals: Triggered when the RSI crosses above the long threshold, signaling bullish momentum.
Short Signals: Triggered when the RSI falls below the short threshold, signaling bearish momentum.
These signals are dynamically adjusted to reflect real-time market conditions, making them more robust than static RSI signals.
Visualization and Clustering Insights
The Machine Learning RSI provides an intuitive and visually rich interface, including:
RSI Line: Plotted in real-time, color-coded based on its position relative to the dynamic thresholds (green for long, red for short, gray for neutral).
Dynamic Threshold Lines: The script plots the long and short thresholds calculated by the ML clustering process, providing a clear visual reference for overbought and oversold levels.
Cluster Plots: Each RSI cluster is displayed with distinct colors (green, orange, and red) to give traders insights into how RSI values are grouped and how the dynamic thresholds are derived.
Customization Options
The Machine Learning RSI is highly customizable, allowing traders to tailor the indicator to their preferences:
RSI Settings : Adjust the RSI length, source price, and smoothing method to match your trading strategy.
Threshold Settings : Define the range and step size for clustering thresholds, allowing you to fine-tune the clustering process.
Optimization Settings : Control the performance memory, maximum clustering steps, and maximum data points for ML calculations to ensure optimal performance.
UI Settings : Customize the appearance of the RSI plot, dynamic thresholds, and cluster plots. Traders can also enable or disable candle coloring based on trend direction.
Alerts and Automation
To assist traders in staying on top of market movements, the script includes alert conditions for key events:
Long Signal: When the RSI crosses above the long threshold.
Short Signal: When the RSI crosses below the short threshold.
These alerts can be configured to notify traders in real-time, enabling timely decisions without constant chart monitoring.
Trading Applications
The Machine Learning RSI is versatile and can be applied to various trading strategies, including:
Trend Following: By dynamically adjusting thresholds, this indicator is effective in identifying and following trends in real-time.
Reversal Trading: The ML clustering process helps identify extreme RSI levels, offering reliable signals for reversals.
Range-Bound Trading: The dynamic thresholds adapt to market conditions, making the indicator suitable for trading in sideways markets where static thresholds often fail.
Final Thoughts
The Machine Learning RSI represents a significant advancement in RSI-based trading indicators. By integrating Machine Learning clustering techniques, this script overcomes the limitations of static thresholds, providing dynamic, adaptive signals that respond to market conditions in real-time. With its robust visualization, customizable settings, and alert capabilities, this indicator is a powerful tool for traders seeking to enhance their momentum analysis and improve decision-making.
As always, thorough backtesting and integration into a broader trading strategy are recommended to maximize the effectiveness!
TEMA Crosses_AIT with Manual TEMA CalculationTitle: TEMA Crosses_AIT Indicator
Description:
The TEMA Crosses_AIT Indicator is designed for traders looking to leverage the Triple Exponential Moving Average (TEMA) to identify trend reversals and momentum shifts in the market. This indicator calculates both fast and slow TEMA lines and signals potential buy or sell opportunities based on crossovers between these two lines.
Key Features:
Fast TEMA (TEMAF):
Default period: 20 (adjustable)
Represents the short-term trend and reacts quickly to price changes.
Slow TEMA (TEMAS):
Default period: 200 (adjustable)
Represents the long-term trend, smoothing out price fluctuations to give a clearer view of the overall direction.
Signal Generation:
Long Signal: A long (buy) signal is generated when the fast TEMA crosses above the slow TEMA, indicating a potential upward trend.
Short Signal: A short (sell) signal is generated when the fast TEMA crosses below the slow TEMA, indicating a potential downward trend.
Color-coded Visualization:
The fast TEMA line is displayed in green when it is above the slow TEMA (bullish signal) and in red when below (bearish signal).
The slow TEMA line is displayed in white.
A yellow triangle appears below the price bar for long entries.
A fuchsia triangle appears above the price bar for short entries.
How It Works:
The indicator calculates the Triple Exponential Moving Average (TEMA) manually using exponential moving averages (EMA). The TEMA is calculated by subtracting the second EMA from three times the first EMA, then adding the third EMA. This provides a smoother trend line that reacts more quickly than a traditional EMA, making it ideal for spotting trend changes.
Customizable Inputs:
TEMAF Period: Adjust the period of the fast TEMA to fit your trading style.
TEMAS Period: Adjust the period of the slow TEMA to match the time frame you are analyzing.
Use Cases:
Trend Reversals: The crossovers between the fast and slow TEMA provide clear signals for potential trend reversals, which can be used to enter or exit trades.
Momentum Confirmation: The color-coded TEMA lines allow traders to easily identify whether the short-term momentum is aligned with the long-term trend, helping to confirm the strength of a move.
Recommendations:
This indicator works well with other momentum-based tools like RSI or MACD for confirming signals and identifying overbought or oversold conditions. It is suitable for use across different asset classes, including stocks, cryptocurrencies, forex, and commodities.
Disclaimer:
The TEMA Crosses_AIT indicator should not be used as a standalone trading strategy. It is recommended to combine this indicator with other forms of analysis and risk management techniques. Always backtest the indicator on historical data before applying it to live trades.
TEMA For Loop [Mattes]The TEMA For Loop indicator is a powerful tool designed for technical analysis, combining the Triple Exponential Moving Average (TEMA) with a custom scoring mechanism based on a for loop. It evaluates price trends over a specified period, allowing traders to identify potential entry and exit points in the market. This indicator enhances decision-making by providing visual cues through dynamic candle coloring, reflecting market sentiment and trends effectively.
Technical Details:
Triple Exponential Moving Average (TEMA):
- TEMA is known for its responsiveness to price changes, as it reduces lag compared to traditional moving averages. The TEMA calculation employs three nested Exponential Moving Averages (EMAs) to produce a smoother trend line, which helps traders identify the direction and momentum of the market.
Scoring Mechanism:
- The scoring mechanism is based on a custom for loop that compares the current TEMA value to previous values over a specified range. The loop counts how many previous values are less than the current value, generating a score that reflects the strength of the trend:
- A higher score indicates a stronger upward trend.
- A lower (negative) score suggests a downward trend.
Threshold Levels:
- Upper Threshold: A score above this level signals a potential long entry, indicating strong bullish momentum.
- Lower Threshold: A score below this level indicates a potential short entry, suggesting bearish sentiment.
>>>These thresholds are adjustable, allowing traders to fine-tune their strategy according to their risk tolerance and market conditions.
Signal Logic:
- The indicator provides clear signals for entering long or short positions based on the score crossing the defined thresholds.
>>Long Entry Signal: When the smoothed score crosses above the upper threshold.
>>Short Entry Signal: When the smoothed score crosses below the lower threshold.
Why This Indicator Is Useful:
>>> Enhanced Decision-Making: The TEMA For Loop indicator offers traders a clear and objective view of market trends, reducing the emotional aspect of trading. By visualizing bullish and bearish conditions, it assists traders in making timely decisions.
>>> Customizable Parameters: The ability to adjust TEMA period, thresholds, and other settings allows traders to tailor the indicator to their specific trading strategies and market conditions.
Visual Clarity: The integration of dynamic candle coloring provides immediate visual cues about the prevailing trend, making it easier for traders to spot potential trade opportunities at a glance.
The TEMA For Loop - Smoothed with Candle Colors indicator is a sophisticated trading tool that utilizes TEMA and a custom scoring mechanism to identify and visualize market trends effectively. By employing dynamic candle coloring, traders gain immediate insights into market sentiment, enabling informed decision-making for entry and exit strategies. This indicator is designed for traders seeking a systematic approach to trend analysis, enhancing their trading performance through clear, actionable signals.
Larry Williams Valuation Index [tradeviZion]Larry Williams Valuation Index
Welcome to the Larry Williams Valuation Index by tradeviZion! This script is an interpretation of Larry Williams' famous WillVal (Valuation) Index, originally developed in 1990 to help traders determine whether a market or asset is overvalued or undervalued. We've extended it to support multiple securities and offer alerts for different valuation levels, helping you make more informed trading decisions.
What is the Valuation Index?
The Valuation Index measures how a security's current price compares to its historical price action. It helps identify whether the security is overvalued (priced too high), undervalued (priced too low), or in a normal range.
This version supports multiple securities and uses valuation parameters to help you assess the relative valuation of three securities simultaneously. It can help you determine the best times to enter (buy) or exit (sell) the market.
Key Features
Multi-Security Analysis: Analyze up to three securities simultaneously to get a broader view of market conditions.
Valuation Levels: Automatically calculate overvaluation and undervaluation levels or set manual levels for consistent analysis.
Custom Alerts: Create custom alerts when securities move between overvalued, undervalued, or normal ranges.
Customizable Table Display: Display a table with valuation values and their status on the chart.
Getting Started
Step 1: Adding the Script to Your Chart
First, add the Larry Williams Valuation Index script to your chart on TradingView. The script is designed to work with any timeframe, but for best results, use weekly or daily timeframes for a longer-term perspective.
Step 2: Configuring Securities
The script allows you to analyze up to three different securities :
Security 1 (Default: DXY)
Security 2 (Default: GC1!)
Security 3 (Default: ZB1!)
You can enable or disable each security individually.
Custom Timeframe Option: You have the option to select a custom timeframe for analysis. This allows you to see whether the security is overvalued or undervalued in lower or higher timeframes. Note that this feature is experimental and has not been extensively tested. Larry Williams originally used the weekly timeframe to determine if a stock was overvalued or undervalued. By default, the indicator compares the current price with the security based on the selected timeframe, except if you choose to use a custom timeframe.
Pro Tip : New users can start with the default securities to understand the concept before using other assets.
Step 3: Valuation Index Settings
Short EMA Length : This is the short-term average used for calculations. A lower value makes it more responsive to recent price changes.
Long EMA Length : This is the long-term average, used to smooth the valuation over time.
Valuation Length (Default: 156) : Represents approximately three years of daily bars (as recommended by Larry Williams).
How is the Valuation Index Calculated?
The valuation calculation is done using a method called WVI (WillVal Index), which compares the current price of a security to the price of another correlated security. Here’s a step-by-step explanation:
1. Data Collection: The script takes the closing price of the security you are analyzing and the closing price of the correlated security.
2. Ratio Calculation : The ratio of the two prices is calculated:
Price Ratio = (Price of your security) / (Price of correlated security) * 100.
This ratio helps determine how expensive or cheap your security is compared to the correlated one.
3. Exponential Moving Averages (EMAs) : The price ratio is used to calculate short-term and long-term EMAs (Exponential Moving Averages). EMAs are used to create smooth lines that represent the average price of a security over a specific period of time, with more weight given to recent data. By calculating both short-term and long-term EMAs, we can identify the trend direction and how the security is performing compared to its historical averages.
4. Valuation Index Calculation:
The Valuation Index is calculated as the difference between the short-term EMA and the long-term EMA. This difference helps to determine if the security is currently overvalued or undervalued:
A positive value indicates that the price is above its longer-term trend, suggesting potential overvaluation.
A negative value indicates that the price is below its longer-term trend, suggesting potential undervaluation.
5. Normalization:
To make the valuation easier to interpret, the calculated valuation index is then normalized using the highest and lowest values over the selected valuation length (e.g., 156 bars).
This normalization process converts the index into a percentage between 0 and 100, where higher values indicate overvaluation and lower values indicate undervaluation.
Step 4: Understanding Valuation Levels
The valuation levels indicate whether a security is currently undervalued, overvalued, or in a normal range.
Manual Levels : You can manually set the overvaluation and undervaluation thresholds (default is 85 for overvalued and 15 for undervalued).
Auto Levels : The script can automatically calculate these levels based on recent price action, allowing you to adapt to changing market conditions.
Auto Levels Calculation Explained:
The Auto Levels are calculated by taking the average of the valuation indices for all three securities (e.g., index1, index2, and index3).
The script then looks at the highest and lowest values of this average over a selected number of recent bars (e.g., 50 bars).
The overvaluation level is determined by taking the highest value and multiplying it by a multiplier (e.g., 5). Similarly, the undervaluation level is calculated using the lowest value and the multiplier.
These dynamic levels adjust according to recent price action, providing an adaptive approach to identifying overvalued and undervalued conditions.
Step 5: How to Use the Script to Make Trading Decisions
For new users, here's a step-by-step trading strategy you can use with the Valuation Index:
1. Identify Undervalued Opportunities
When two or more securities are in the undervalued range (below 15 for manual or below automatically calculated undervalue levels), wait for at least two of these securities to turn from undervalued to normal .
This transition indicates a potential buy opportunity .
2. Buying Signal
When at least two securities transition from undervalued to normal, you can consider buying the asset.
This indicates that the market may be recovering from undervalued conditions and could be moving into a growth phase.
3. Selling Signal
Exit when the price high closes below the EMA 21 (21-day exponential moving average).
Alternatively, if the valuation index reaches overvalued levels (above 85 manually or auto-calculated), wait for it to drop back to normal . This can be another point to exit the trade .
You can also use any other sell condition based on your r isk management strategy .
Alerts for Valuation Levels
The script includes alerts to notify you of changing market conditions:
To activate these alerts, follow these steps, referring to the provided screenshot with detailed steps:
1. Enable Alerts : Click on the settings gear icon on the script title in your chart. In the settings menu, scroll to the section labeled Alerts Settings .
Enable Alerts by checking the Enable Alerts box.
Set the Required Securities for Alert (default is 2 securities).
Choose the Alert Frequency : Selecting Once Per Bar Close will trigger alerts only at the close of each bar, ensuring you receive confirmed signals rather than potentially noisy intermediate signals.
2. Select Alert Type : Choose the type of alert you want to activate, such as Alert on Overvalued, Alert on Undervalued, Alert on Over to Normal , or Alert on Under to Normal .
3. Save Settings : Click OK to save your alert settings.
4. Add Alert on Indicator : Click the "..." (More button) next to the indicator name on the chart and select " Add alert on tradeviZion - WillVal ".
5. Create Alert : In the Create Alert window:
Set Condition to tradeviZion - WillVal .
Ensure Any alert() function call is selected.
Set the Alert Name and select your Expiration preferences.
6. Set Notification Preferences : Go to the Notifications tab and select how you want to receive notifications, such as via app notification, toast notification, email , or sound alert . Adjust these preferences to best suit your needs.
7. Click Create : Finally, click Create to activate the alert.
These alerts will help you stay informed about key market conditions and take action accordingly, ensuring you do not miss critical trading opportunities.
Understanding the Table Display
The script includes an interactive table on the chart to show the valuation status of each security:
Security : The name of the security being analyzed.
Value : The current valuation index value.
Status : Indicates whether the security is overvalued, undervalued , or in a normal range.
Color: Displays a color code for easy identification of status:
Red for overvalued.
Green for undervalued.
Other colors represent normal valuation levels.
Empowering Messages : Motivational messages are displayed to encourage disciplined trading. These messages will change periodically, helping keep a positive trading mindset.
Acknowledgment
This tool builds upon the foundational work of Larry Williams, who developed the WillVal (Valuation) Index concept. It also incorporates enhancements to extend multi-security analysis, valuation normalization, and advanced alerting features, providing a more versatile and powerful indicator. The Larry Williams Valuation Index [ tradeviZion ] helps traders make informed decisions by assessing overvalued and undervalued conditions for multiple securities simultaneously.
Note : Always practice proper risk management and thoroughly test the indicator to ensure it aligns with your trading strategy. Past performance is not indicative of future results.
Trade smarter with TradeVizion—unlock your trading potential today!
[ROC3] Rate of Change Candle ColorROC is a statistical indicator which tracks how much a security's price has changed over a certain period, showing whether momentum is picking up or slowing down. It’s a handy tool because it helps traders spot trend changes and understand how strong a trend is.
My ROC3 indicator will color the candlesticks based on the Rate of Change (ROC) and its Exponential Moving Average (EMA). This indicator helps traders visually identify bullish and bearish trends by applying color to the candles, making it easier to spot momentum shifts and trend changes.
How It Works:
Rate of Change (ROC): Calculates the percentage change in the price over a specified number of bars. This indicator measures the speed at which price changes.
EMA of ROC: Applies an Exponential Moving Average to the ROC values to provide a smoothed benchmark. The EMA helps to reduce noise and make trend identification more reliable.
Coloring Logic:
Bullish Candles (Green): When the current ROC is higher than the EMA of the ROC.
Bearish Candles (Red): When the current ROC is lower than the EMA of the ROC.
Settings:
ROC Length (Default: 60): The number of bars used to calculate the Rate of Change. Adjust this parameter to change the sensitivity of the ROC calculation.
ROC EMA Length (Default: 7): The number of bars used to calculate the Exponential Moving Average of the ROC. This length determines how smooth the EMA is. A shorter length reacts faster to price changes, while a longer length provides a smoother, slower response.
How to Use:
Apply the Indicator: Add the Rate of Change Candle Color indicator to your TradingView chart.
Interpret the Colors:
Green Candles: Indicate bullish momentum. The current ROC is greater than its EMA, suggesting upward pressure.
Red Candles: Indicate bearish momentum. The current ROC is less than its EMA, suggesting downward pressure.
Adjust Settings: Customize the ROC Length and ROC EMA Length based on your trading strategy. Shorter ROC lengths may capture more short-term trends, while longer lengths provide a broader view.
Combine with Other Indicators: Use the in conjunction with other technical indicators or chart patterns to enhance your trading analysis.
Example Use Case:
Trend Confirmation: Use the color changes to confirm bullish or bearish trends. Green candles can confirm uptrends, while red candles may signal downtrends or potential reversals.
Momentum Analysis: Monitor how frequently the ROC crosses above or below its EMA to gauge momentum strength and make informed trading decisions.
Note:
This indicator is designed to assist with trend analysis and should be used as part of a broader trading strategy. Always conduct your own research and analysis before making trading decisions.
Cherio...
Dema Ema Crossover | viResearchDema Ema Crossover | viResearch
Conceptual Foundation and Innovation
The "Dema Ema Crossover" indicator combines the strengths of the Double Exponential Moving Average (DEMA) with an Exponential Moving Average (EMA) crossover strategy. The DEMA is well-known for its ability to reduce lag compared to standard moving averages, offering smoother trend-following signals. In this script, the DEMA is used as the foundation, with two EMAs applied on top of it to further refine the trend detection and crossover points. This combination provides traders with a robust tool for identifying trend shifts and potential entry or exit points.
By leveraging the faster responsiveness of the DEMA and using EMA crossovers, the "Dema Ema Crossover" indicator helps traders detect and act on trend reversals more efficiently, making it a powerful solution for capturing both short- and long-term market movements.
Technical Composition and Calculation
The "Dema Ema Crossover" script consists of three main components: the Double Exponential Moving Average (DEMA), the fast EMA, and the slow EMA. The DEMA is calculated based on the selected length and source price, providing a smooth representation of market trends. Two EMAs are then applied to the DEMA, with one being faster (shorter period) and the other slower (longer period). The crossover between these two EMAs generates the signals for trend changes.
For the DEMA, the calculation uses the ta.dema function, which reduces lag while maintaining smoothness in the moving average. The fast and slow EMAs are calculated using the ta.ema function, with the fast EMA responding more quickly to price changes, while the slow EMA captures broader trends. The crossover between these two EMAs is used to generate buy and sell signals based on the direction of the crossover.
Features and User Inputs
The "Dema Ema Crossover" script offers several customizable inputs that allow traders to tailor the indicator to their trading strategies. The DEMA Length controls how smooth the DEMA is, with a longer length creating a slower-moving average and a shorter length providing a more responsive one. The Fast EMA Length and Slow EMA Length are also customizable, allowing traders to adjust the sensitivity of the crossover signals based on their market outlook and preferred trading timeframe.
Practical Applications
The "Dema Ema Crossover" indicator is designed for traders looking for a reliable crossover strategy that combines the responsiveness of the DEMA with the precision of EMA crossovers. This tool is particularly effective for:
Identifying Trend Reversals: The crossover between the fast and slow EMAs applied to the DEMA provides early signals of potential trend reversals, allowing traders to position themselves in the market more effectively. Confirming Trend Direction: The combined effect of the DEMA and EMA crossovers helps confirm the strength of a trend, improving decision-making around trade entries and exits. Adapting to Different Market Conditions: The customizable parameters allow traders to adjust the sensitivity of the crossover signals, making the indicator suitable for both fast-moving markets and slower, trending environments.
Advantages and Strategic Value
The "Dema Ema Crossover" script offers a significant advantage by combining the smoothness of the DEMA with the accuracy of EMA crossovers. The DEMA’s ability to reduce lag while maintaining responsiveness makes it ideal for trend-following strategies, while the crossover between the fast and slow EMAs provides precise entry and exit points. This combination reduces false signals and helps traders adapt to changing market conditions, resulting in a more reliable and efficient trend-following system.
Alerts and Visual Cues
The script includes alert conditions to notify traders of key crossover events. The "Dema Ema Crossover Long" alert is triggered when the fast EMA crosses above the slow EMA, signaling a potential upward trend. Conversely, the "Dema Ema Crossover Short" alert signals a possible downward trend when the fast EMA crosses below the slow EMA. Visual cues such as colored fills between the two EMAs highlight these crossover points on the chart, helping traders quickly identify trend shifts.
Summary and Usage Tips
The "Dema Ema Crossover | viResearch" indicator provides traders with a powerful combination of the DEMA and EMA crossovers, offering a smooth yet responsive tool for detecting trend reversals and confirming trend direction. By incorporating this script into your trading strategy, you can improve your ability to capture trend changes with greater accuracy, reducing the impact of market noise. Whether you are focused on short-term market moves or long-term trends, the "Dema Ema Crossover" indicator offers a flexible and reliable solution for traders at all levels.
Note: Backtests are based on past results and are not indicative of future performance.
Dema Supertrend | viResearchDema Supertrend | viResearch
Conceptual Foundation and Innovation
The "Dema Supertrend" indicator by viResearch combines the benefits of the Double Exponential Moving Average (DEMA) with the popular Supertrend method to provide an advanced tool for trend detection and volatility management. By integrating DEMA into the Supertrend calculation, the indicator reduces lag while enhancing responsiveness to market changes. This results in more accurate trend identification and a refined method for capturing directional movements.
Technical Composition and Calculation
The "Dema Supertrend" builds on the core principles of the Supertrend indicator by incorporating DEMA for smoother and more responsive trend detection. The key innovation lies in replacing the raw price data with the DEMA-smoothed values, allowing traders to identify trends with reduced noise and enhanced precision.
DEMA and ATR-Based Supertrend Calculation:
DEMA Calculation (demalen): The Double Exponential Moving Average is applied to the price data (hlc3 by default) over a user-defined length, providing a smoothed representation of the market trend. DEMA minimizes lag compared to simple or exponential moving averages, allowing for more timely trend identification.
Supertrend Bands (u, l): The Supertrend upper and lower bands are calculated by adding or subtracting a multiple of the Average True Range (ATR) from the DEMA value. These bands dynamically adjust to market volatility, acting as support and resistance levels to guide trading decisions.
Trend Logic (L, S): The script determines whether the price is above or below the bands to signal an uptrend (L) or downtrend (S). Crosses above or below these bands trigger visual alerts and trend changes, with alerts built in for potential long or short positions.
Trend Continuation and Reversal:
The indicator ensures that once a trend is identified, it persists until clear reversal criteria are met. This is achieved through a comparison of the current and previous values of the Supertrend bands, reducing the occurrence of false signals in volatile markets.
Features and User Inputs
The "Dema Supertrend" script offers a range of customizable options, allowing traders to tailor the indicator to different market conditions and trading strategies:
Supertrend Length: The length of the Supertrend period can be adjusted, allowing traders to control the sensitivity of the trend detection.
Multiplier: The ATR multiplier adjusts the distance between the DEMA and the Supertrend bands. A higher multiplier reduces the frequency of trend changes, while a lower multiplier increases sensitivity to price movements.
DEMA Length: The length of the DEMA calculation can be customized to smooth price data over different timeframes, helping traders capture long-term trends or short-term movements more effectively.
Practical Applications
The "Dema Supertrend" is an ideal tool for traders who seek to follow trends while minimizing the impact of market noise. Its combination of DEMA and Supertrend provides a clear, dynamic view of the market's direction, making it especially effective in volatile environments.
Key Uses:
- Trend Following: The Dema Supertrend helps traders align their positions with the prevailing market trend by providing clear signals for uptrends and downtrends based on DEMA-smoothened price action.
- Volatility Management: The integration of ATR ensures that the Supertrend bands adapt to changes in market volatility, allowing traders to avoid entering trades during choppy, unpredictable price movements.
- Signal Confirmation: The script includes visual and alert-based signals for trend continuation and reversal, enabling traders to confirm entries and exits with greater accuracy.
Advantages and Strategic Value
The "Dema Supertrend" offers several strategic advantages:
- Reduced Lag: By integrating DEMA into the Supertrend calculation, the indicator responds more quickly to price changes, reducing the lag inherent in traditional moving averages.
- Noise Reduction: The use of DEMA filters out short-term fluctuations, providing a clearer signal for traders looking to capture significant market trends.
- Dynamic Adjustments: The combination of ATR and DEMA allows the indicator to adapt to both trending and ranging markets, making it suitable for a variety of trading strategies.
Summary and Usage Tips
The "Dema Supertrend" is a powerful tool for trend-following traders, offering a precise and adaptive method for identifying and confirming market direction. Traders can experiment with different settings for the Supertrend and DEMA lengths, as well as the ATR multiplier, to optimize the indicator for various trading environments. For best results, use the "Dema Supertrend" in conjunction with other technical analysis tools to confirm trends and manage risk. Whether you're seeking to capture long-term market moves or react to short-term volatility, the "Dema Supertrend" provides a reliable and flexible solution for your trading strategy.
DSL Oscillator [BigBeluga]DSL Oscillator BigBeluga
The DSL (Discontinued Signal Lines) Oscillator is an advanced technical analysis tool that combines elements of the Relative Strength Index (RSI), Discontinued Signal Lines, and Zero-Lag Exponential Moving Average (ZLEMA). This versatile indicator is designed to help traders identify trend direction, momentum, and potential reversal points in the market.
What are Discontinued Signal Lines (DSL)?
Discontinued Signal Lines are an extension of the traditional signal line concept used in many indicators. While a standard signal line compares an indicator's value to its smoothed (slightly lagging) state, DSL takes this idea further by using multiple adaptive lines that respond to the indicator's current value. This approach provides a more nuanced view of the indicator's state and momentum, making it easier to determine trends and desired states of the indicator.
🔵 KEY FEATURES
● Discontinued Signal Lines (DSL)
Uses multiple adaptive lines that respond to the indicator's value
Provides a more nuanced view of the indicator's state and momentum
Helps determine trends and desired states of the indicator more effectively
Available in "Fast" and "Slow" modes for different responsiveness
Acts as dynamic support and resistance levels for the oscillator
● DSL Oscillator
Based on a combination of RSI and Discontinued Signal Lines
// Discontinued Signal Lines
dsl_lines(src, length)=>
UP = 0.
DN = 0.
UP := (src > ta.sma(src, length)) ? nz(UP ) + dsl_mode / length * (src - nz(UP )) : nz(UP )
DN := (src < ta.sma(src, length)) ? nz(DN ) + dsl_mode / length * (src - nz(DN )) : nz(DN )
Smoothed using Zero-Lag Exponential Moving Average for reduced lag
// Zero-Lag Exponential Moving Average function
zlema(src, length) =>
lag = math.floor((length - 1) / 2)
ema_data = 2 * src - src
ema2 = ta.ema(ema_data, length)
ema2
Oscillates between 0 and 100
Color-coded for easy interpretation of market conditions
● Signal Generation
Generates buy signals when the oscillator crosses above the lower DSL line below 50
Generates sell signals when the oscillator crosses below the upper DSL line above 50
Signals are visualized on both the oscillator and the main chart
● Visual Cues
Background color changes on signal occurrences for easy identification
Candles on the main chart are colored based on the latest signal
Oscillator line color changes based on its position relative to the DSL lines
🔵 HOW TO USE
● Trend Identification
Use the color and position of the DSL Oscillator relative to its Discontinued Signal Lines to determine the overall market trend
● Entry Signals
Look for buy signals (green circles) when the oscillator crosses above the lower DSL line
Look for sell signals (blue circles) when the oscillator crosses below the upper DSL line
Confirm signals with the triangles on the main chart and background color changes
● Exit Signals
Consider exiting long positions on exit signals and short positions on Entery signals
Watch for the oscillator crossing back between the DSL lines as a potential early exit signal
● Momentum Analysis
Strong momentum is indicated when the oscillator moves rapidly towards extremes and away from the DSL lines
Weakening momentum can be spotted when the oscillator struggles to reach new highs or lows, or starts converging with the DSL lines
The space between the DSL lines can indicate potential momentum strength - wider gaps suggest stronger trends
● Confirmation
Use the DSL lines as dynamic support/resistance levels for the oscillator
Look for convergence between oscillator signals and price action on the main chart
Combine signals with other technical indicators or chart patterns for stronger confirmation
🔵 CUSTOMIZATION
The DSL Oscillator offers several customization options:
Adjust the main calculation length for the DSL lines
Choose between "Fast" and "Slow" modes for the DSL lines calculation
By fine-tuning these settings, traders can adapt the DSL Oscillator to various market conditions and personal trading strategies.
The DSL Oscillator provides a multi-faceted approach to market analysis, combining trend identification, momentum assessment, and signal generation in one comprehensive tool. Its dynamic nature and visual cues make it suitable for both novice and experienced traders across various timeframes and markets. The integration of RSI, Discontinued Signal Lines, and ZLEMA offers traders a sophisticated yet intuitive tool to inform their trading decisions.
The use of Discontinued Signal Lines sets this oscillator apart from traditional indicators by providing a more adaptive and nuanced view of market conditions. This can potentially lead to more accurate trend identification and signal generation, especially in markets with varying volatility.
Traders can use the DSL Oscillator to identify trends, spot potential reversals, and gauge market momentum. The combination of the oscillator, dynamic signal lines, and clear visual signals provides a holistic view of market conditions. As with all technical indicators, it's recommended to use the DSL Oscillator in conjunction with other forms of analysis and within the context of a well-defined trading strategy.
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
Directional Movement Index DEThis script uses the existing built-in DMI indicator but adds two lines indicating strength of the ADX trend. The original author J. Welles Wilder, indicated a ADX trending strongly above 25 (yellow by default), and ADX trending weaker at a threshold of 20 or below (dashed yellow by default).
The default colours have been changed so that ADX is yellow, +DI is green, and -DI is red.
Calculation
Calculating the DMI can actually be broken down into two parts. First, calculating the +DI and -DI, and second, calculating the ADX. To calculate the +DI and -DI you need to find the +DM and -DM (Directional Movement). +DM and -DM are calculated using the High, Low and Close for each period. You can then calculate the following:
Current High - Previous High = UpMove
Previous Low - Current Low = DownMove
If UpMove > DownMove and UpMove > 0, then +DM = UpMove, else +DM = 0
If DownMove > Upmove and Downmove > 0, then -DM = DownMove, else -DM = 0
Once you have the current +DM and -DM calculated, the +DM and -DM lines can be calculated and plotted based on the number of user defined periods.
+DI = 100 times Exponential Moving Average of (+DM / Average True Range)
-DI = 100 times Exponential Moving Average of (-DM / Average True Range)
Now that -+DX and -DX have been calculated, the last step is calculating the ADX.
ADX = 100 times the Exponential Moving Average of the Absolute Value of (+DI - -DI) / (+DI + -DI)
The basics
DMI has a value between 0 and 100 and is used to measure the strength of the current trend. +DI and -DI are then used to measure direction. When combined, the indicator can provide some valuable insight. A general interpretation would be that during a strong trend (ADX above 25 but dependent on the analyst's interpretation), when the +DI is above the -DI, then a Bullish Market is defined. When -DI is above +DI, then a Bearish Market is at hand.
One thing to be considered is that what DMI values determine, strength or a potential signal, is up to the trader's interpretation. Acceptable values may change depending on the financial instrument being examined, therefore some historical analysis of the instrument in question would be prudent. A technical analyst can make better decisions based on what has occurred in historical examples.
All credit goes to the original script .
Median Moving Average @shrilssThe "Median Moving Average" (MMA) It allows users to select from two moving average lengths—short and long—and plots the median moving average, which is the midpoint between these two averages. Colored green for upward trends and red for downward trends, enhancing visual analysis.
Additionally, users can choose from a range of moving average types including Simple (SMA), Exponential (EMA), Weighted (WMA), Double Exponential (DEMA), Triple Exponential (TEMA), Hull (HMA), and Volume Weighted (VWMA).
Moving Average Bands with Signals [UAlgo]The "Moving Average Bands with Signals combines various moving average types with ATR-based bands to help traders identify potential support and resistance levels.
It plots moving average bands with upper and lower support/resistance levels based on the Average True Range (ATR) and user-defined settings.Additionally, the script generates buy/sell signals based on price crossing above or below the bands.
🔶 Key Features
Multiple Moving Average Types:
Supports various moving average calculations including Arnaud Legoux Moving Average (ALMA), Exponential Moving Average (EMA), Double Exponential Moving Average (DEMA), Triple Exponential Moving Average (TEMA), Kaufman Adaptive Moving Average (KAMA), Hull Moving Average (HMA), Least Squares Moving Average (LSMA), Simple Moving Average (SMA), Triangular Moving Average (TMA), Volume-Weighted Moving Average (VWMA), Weighted Moving Average (WMA), and Zero-Lag Moving Average (ZLMA).
Customizable ATR Bands:
Integrates the Average True Range (ATR) to calculate dynamic support and resistance bands around the moving average. The multiplier for the bands is user-adjustable, allowing for finer control over the sensitivity and width of the bands.
Signal Generation:
Provides visual signals on the chart when the price interacts with the support or resistance bands. Users can choose between using the wick or the close price to generate these signals, adding an extra layer of customization based on their trading style.
Flexible Input Parameters:
Allows users to input parameters for moving average length, ATR length, band multiplier, and signal type. Additional settings are available for specific moving average types, such as ALMA's offset and sigma, KAMA's fast and slow periods, and LSMA's offset.
🔶 Disclaimer
This script is provided for educational purposes only and should not be considered financial advice.
Trading financial instruments involves substantial risk and can result in significant financial losses.
The script’s performance in the past is not indicative of future results, and no guarantees are made regarding its accuracy, reliability, or performance.
GM-8 and ADX Strategy with Second EMADescription:
This TradingView script implements a trading strategy based on the Moving Average (GM-8), the Average Directional Index (ADX), and the second Exponential Moving Average (EMA). The strategy utilizes these indicators to identify potential buy and sell signals on the chart.
Indicators:
GM-8 (Moving Average 8): This indicator calculates the average price of the last 8 periods and is used to identify trends.
ADX (Average Directional Index): The ADX measures the strength of a trend and is used to determine whether the market is moving in a particular direction or not.
Second EMA (Exponential Moving Average): This is an additional EMA line with a period of 59, which is used to provide additional confirmation signals for the trend.
Trading Conditions:
Buy Condition: A buy signal is generated when the closing price is above the GM-8 and the second EMA, and the ADX value is above the specified threshold.
Sell Condition: A sell signal is generated when the closing price is below the GM-8 and the second EMA, and the ADX value is above the specified threshold.
Trading Logic:
If a buy condition is met, a long position is opened with a user-defined lot size.
If a sell condition is met, a short position is opened with the same user-defined lot size.
Positions are closed when the opposite conditions are met.
User Parameters:
Users can adjust the periods for the GM-8, the second EMA, and the ADX, as well as the threshold for the ADX and the lot size according to their preferences.
Note:
This script has been developed for use on a $100,000 account with FTMO, therefore the account size is set to $100,000. Please ensure that the strategy parameters and settings meet the requirements of your trading strategy and carefully review the results before committing real capital.
--------------------------------------------------------------------------------------------------------------
Beschreibung:
Dieses TradingView-Skript implementiert eine Handelsstrategie, die auf dem gleitenden Mittelwert (GM-8), dem Average Directional Index (ADX) und der zweiten exponentiellen gleitenden Durchschnittslinie (EMA) basiert. Die Strategie verwendet diese Indikatoren, um potenzielle Kauf- und Verkaufssignale auf dem Chart zu identifizieren.
Indikatoren:
GM-8 (Gleitender Mittelwert 8): Dieser Indikator berechnet den Durchschnittspreis der letzten 8 Perioden und wird verwendet, um Trends zu identifizieren.
ADX (Average Directional Index): Der ADX misst die Stärke eines Trends und wird verwendet, um festzustellen, ob sich der Markt in eine bestimmte Richtung bewegt oder nicht.
Zweite EMA (Exponential Moving Average): Dies ist eine zusätzliche EMA-Linie mit einer Periode von 59, die verwendet wird, um zusätzliche Bestätigungssignale für den Trend zu liefern.
Handelsbedingungen:
Kaufbedingung: Es wird ein Kaufsignal generiert, wenn der Schlusskurs über dem GM-8 und der zweiten EMA liegt und der ADX-Wert über dem angegebenen Schwellenwert liegt.
Verkaufsbedingung: Es wird ein Verkaufssignal generiert, wenn der Schlusskurs unter dem GM-8 und der zweiten EMA liegt und der ADX-Wert über dem angegebenen Schwellenwert liegt.
Handelslogik:
Wenn eine Kaufbedingung erfüllt ist, wird eine Long-Position mit einer benutzerdefinierten Losgröße eröffnet.
Wenn eine Verkaufsbedingung erfüllt ist, wird eine Short-Position mit derselben benutzerdefinierten Losgröße eröffnet.
Positionen werden geschlossen, wenn die Gegenbedingungen erfüllt sind.
Benutzerparameter:
Benutzer können die Perioden für den GM-8, die zweite EMA und den ADX sowie den Schwellenwert für den ADX und die Losgröße nach ihren eigenen Präferenzen anpassen.
Hinweis:
Dieses Skript wurde für die Verwendung auf einem $100.000-Konto bei FTMO entwickelt, daher ist die Kontogröße auf $100.000 festgelegt. Bitte stellen Sie sicher, dass die Strategieparameter und -einstellungen den Anforderungen Ihrer Handelsstrategie entsprechen und dass Sie die Ergebnisse sorgfältig überprüfen, bevor Sie echtes Kapital einsetzen.
EMA 9/13/18/25 + Bollinger BandThe indicator combines two components: Exponential Moving Averages (EMAs) and Bollinger Bands.
Exponential Moving Averages (EMAs): The indicator calculates four EMAs with different periods: 9, 13, 18, and 25. An Exponential Moving Average is a type of moving average that places a greater weight and significance on the most recent data points. As the name suggests, it's an average of the asset's price over a certain period, with recent prices given more weight in the calculation, making it more responsive to recent price changes.
Bollinger Bands: Bollinger Bands consist of a simple moving average (the basis) and two standard deviations plotted away from it. The standard deviations are multiplied by a factor (usually 2) to determine the distance from the basis. These bands dynamically adjust themselves based on recent price movements. The upper band represents the highest price level reached in the given period, while the lower band represents the lowest price level.
Combining these components provides traders with insights into both trend direction and volatility. The EMAs help identify trends by smoothing out price data, while the Bollinger Bands offer insights into volatility and potential price reversal points. Traders often use the crossovers of EMAs and interactions with Bollinger Bands to make trading decisions. For example, when the price touches the upper Bollinger Band, it may indicate overbought conditions, while touching the lower band may suggest oversold conditions. Additionally, crossovers of EMAs (such as the shorter-term EMA crossing above or below the longer-term EMA) may signal changes in trend direction.
Fine-tune Inputs: Fourier Smoothed Volume zone oscillator WFSVZ0Use this Strategy to Fine-tune inputs for the (W&)FSVZ0 Indicator.
Strategy allows you to fine-tune the indicator for 1 TimeFrame at a time; cross Timeframe Input fine-tuning is done manually after exporting the chart data.
I suggest using "Close all" input False when fine-tuning Inputs for 1 TimeFrame. When you export data to Excel/Numbers/GSheets I suggest using "Close all" input as True, except for the lowest TimeFrame.
MEANINGFUL DESCRIPTION:
The Volume Zone oscillator breaks up volume activity into positive and negative categories. It is positive when the current closing price is greater than the prior closing price and negative when it's lower than the prior closing price. The resulting curve plots through relative percentage levels that yield a series of buy and sell signals, depending on level and indicator direction.
The Wavelet & Fourier Smoothed Volume Zone Oscillator (W&)FSVZO is a refined version of the Volume Zone Oscillator, enhanced by the implementation of the Discrete Fourier Transform . Its primary function is to streamline price data and diminish market noise, thus offering a clearer and more precise reflection of price trends.
By combining the Wavalet and Fourier aproximation with Ehler's white noise histogram, users gain a comprehensive perspective on volume-related market conditions.
HOW TO USE THE INDICATOR:
The default period is 2 but can be adjusted after backtesting. (I suggest 5 VZO length and NoiceR max length 8 as-well)
The VZO points to a positive trend when it is rising above the 0% level, and a negative trend when it is falling below the 0% level. 0% level can be adjusted in setting by adjusting VzoDifference. Oscillations rising below 0% level or falling above 0% level result in a natural trend.
HOW TO USE THE STRATEGY:
Here you fine-tune the inputs until you find a combination that works well on all Timeframes you will use when creating your Automated Trade Algorithmic Strategy. I suggest 4h, 12h, 1D, 2D, 3D, 4D, 5D, 6D, W and M.
When I ndicator/Strategy returns 0 or natural trend , Strategy Closes All it's positions.
ORIGINALITY & USFULLNESS:
Personal combination of Fourier and Wavalet aproximation of a price which results in less noise Volume Zone Oscillator.
The Wavelet Transform is a powerful mathematical tool for signal analysis, particularly effective in analyzing signals with varying frequency or non-stationary characteristics. It dissects a signal into wavelets, small waves with varying frequency and limited duration, providing a multi-resolution analysis. This approach captures both frequency and location information, making it especially useful for detecting changes or anomalies in complex signals.
The Discrete Fourier Transform (DFT) is a mathematical technique that transforms discrete data from the time domain into its corresponding representation in the frequency domain. This process involves breaking down a signal into its individual frequency components, thereby exposing the amplitude and phase characteristics inherent in each frequency element.
This indicator utilizes the concept of Ehler's Universal Oscillator and displays a histogram, offering critical insights into the prevailing levels of market noise. The Ehler's Universal Oscillator is grounded in a statistical model that captures the erratic and unpredictable nature of market movements. Through the application of this principle, the histogram aids traders in pinpointing times when market volatility is either rising or subsiding.
DETAILED DESCRIPTION:
My detailed description of the indicator and use cases which I find very valuable.
What is oscillator?
Oscillators are chart indicators that can assist a trader in determining overbought or oversold conditions in ranging (non-trending) markets.
What is volume zone oscillator?
Price Zone Oscillator measures if the most recent closing price is above or below the preceding closing price.
Volume Zone Oscillator is Volume multiplied by the 1 or -1 depending on the difference of the preceding 2 close prices and smoothed with Exponential moving Average.
What does this mean?
If the VZO is above 0 and VZO is rising. We have a bullish trend. Most likely.
If the VZO is below 0 and VZO is falling. We have a bearish trend. Most likely.
Rising means that VZO on close is higher than the previous day.
Falling means that VZO on close is lower than the previous day.
What if VZO is falling above 0 line?
It means we have a high probability of a bearish trend.
Thus the indicator returns 0 and Strategy closes all it's positions when falling above 0 (or rising bellow 0) and we combine higher and lower timeframes to gauge the trend.
In the next Image you can see that trend is negative on 4h, negative on 12h and positive on 1D. That means trend is negative.
I am sorry, the chart is a bit messy. The idea is to use the indicator over more than 1 Timeframe.
What is approximation and smoothing?
They are mathematical concepts for making a discrete set of numbers a
continuous curved line.
Fourier and Wavelet approximation of a close price are taken from aprox library.
Key Features:
You can tailor the Indicator/Strategy to your preferences with adjustable parameters such as VZO length, noise reduction settings, and smoothing length.
Volume Zone Oscillator (VZO) shows market sentiment with the VZO, enhanced with Exponential Moving Average (EMA) smoothing for clearer trend identification.
Noise Reduction leverages Euler's White noise capabilities for effective noise reduction in the VZO, providing a cleaner and more accurate representation of market dynamics.
Choose between the traditional Fast Fourier Transform (FFT) , the innovative Double Discrete Fourier Transform (DTF32) and Wavelet soothed Fourier soothed price series to suit your analytical needs.
Image of Wavelet transform with FAST settings, Double Fourier transform with FAST settings. Improved noice reduction with SLOW settings, and standard FSVZO with SLOW settings:
Fast setting are setting by default:
VZO length = 2
NoiceR max Length = 2
Slow settings are:
VZO length = 5 or 7
NoiceR max Length = 8
As you can see fast setting are more volatile. I suggest averaging fast setting on 4h 12h 1d 2d 3d 4d W and M Timeframe to get a clear view on market trend.
What if I want long only when VZO is rising and above 15 not 0?
You have set Setting VzoDifference to 15. That reduces the number of trend changes.
Example of W&FSVZO with VzoDifference 15 than 0:
VZO crossed 0 line but not 15 line and that's why Indicator returns 0 in one case an 1 in another.
What is Smooth length setting?
A way of calculating Bullish or Bearish (W&)FSVZO .
If smooth length is 2 the trend is rising if:
rising = VZO > ta.ema(VZO, 2)
Meaning that we check if VZO is higher that exponential average of the last 2 elements.
If smooth length is 1 the trend is rising if:
rising = VZO_ > VZO_
Use this Strategy to fine-tune inputs for the (W&)FSVZO Indicator.
(Strategy allows you to fine-tune the indicator for 1 TimeFrame at a time; cross Timeframe Input fine-tuning is done manually after exporting the chart data)
I suggest using " Close all " input False when fine-tuning Inputs for 1 TimeFrame . When you export data to Excel/Numbers/GSheets I suggest using " Close all " input as True , except for the lowest TimeFrame . I suggest using 100% equity as your default quantity for fine-tune purposes. I have to mention that 100% equity may lead to unrealistic backtesting results. Be avare. When backtesting for trading purposes use Contracts or USDT.
200 EMA Trend Strategy Anti meanDescription:
The "200 EMA Trend Strategy" is a versatile technical analysis tool designed for day trading and long-term investing. It aims to identify potential trend reversal points in the market based on the interaction between the price and the 200-period Exponential Moving Average (EMA). This strategy utilizes the 200 EMA, standard deviation bands, and basic trend analysis to generate buy and sell signals.
Key Features:
200-period Exponential Moving Average (EMA): The indicator plots the 200-period Exponential Moving Average, a reliable trend-following indicator that smooths out price data to identify the underlying trend direction.
Standard Deviation Bands: Upper and lower bands around the 200 EMA are calculated based on a specified standard deviation multiplier. These bands help identify potential overbought and oversold levels in the market.
Trend Signals: Buy signals are generated when the price crosses above the 200 EMA, indicating a potential bullish trend, while sell signals are generated when the price crosses below the 200 EMA, indicating a potential bearish trend.
Exit Signals: Exit signals are triggered when the price moves beyond the standard deviation bands in the opposite direction of the current trend. Most trades will be exited with minimal losses, aiming to grow the trading account over time. Multiple exit signals may be displayed, but only the first signal will be considered, ignoring subsequent signals to minimize drawdown.
Usage:
Day Trading: For intraday trading, traders can use a one-minute chart and fix the indicator's timeframe to five minutes. This allows for quick decision-making and minimizes drawdown by focusing on short-term price movements.
Long-Term Investing: For long-term investing, traders can utilize a four-hour or two-hour chart and fix the indicator's timeframe to daily or one-day timeframe. This provides a broader perspective of the market trends and allows for strategic positioning over longer time horizons.
Risk Management: Employ proper risk management techniques and position sizing strategies to mitigate losses and maximize profits. Use the indicator's exit signals to exit trades with minimal losses and allow profitable trades to grow the trading account over time.
Risk Disclosure: Trading involves risks, and this indicator should be used as part of a comprehensive trading strategy. It is essential to consider risk management principles and employ proper position sizing techniques when trading based on the signals generated by this indicator.
Composite Trend Oscillator [ChartPrime]CODE DUELLO:
Have you ever stopped to wonder what the underlying filters contained within complex algorithms are actually providing for you? Wouldn't it be nice to actually visually inspect for that? Those would require some kind of wild west styled quick draw duel or some comparison method as a proper 'code duello'. Then it can be determined which filter can 'draw' the quickest from it's computational holster with the least amount of lag and smoothness.
In Pine we can do so, discovering how beneficial that would be. This can be accomplished by quickly switching from one filter to another by input() back and forth, requiring visual memory. A better way could be done by placing two indicators added to the chart and then eventually placed into one indicator pane on top of each other.
By adding a filter() helper function that calls other moving average functions chosen for comparison, it can put to the test which moving average is the best drawing filter suited to our expected needs. PhiSmoother was formerly debuted and now it is utilized in a more complex environment in a multitude of ways along side other commonly utilized filters. Now, you the reader, get to judge for yourself...
FILTER VERSATILITY:
Having the capability to adjust between various smoothing methods such as PhiSmoother, TEMA, DEMA, WMA, EMA, and SMA on historical market data within the code provides an advantage. Each of these filter methods offers distinct advantages and hinderances. PhiSmoother stands out often by having superb noise rejection, while also being able to manipulate the fine-tuning of the phase or lag of the indicator, enhancing responsiveness to price movements.
The following are more well-known classic filters. TEMA (Triple Exponential Moving Average) and DEMA (Double Exponential Moving Average) offer reduced transient response times to price changes fluctuations. WMA (Weighted Moving Average) assigns more weight to recent data points, making it particularly useful for reduced lag. EMA (Exponential Moving Average) strikes a balance between responsiveness and computational efficiency, making it a popular choice. SMA (Simple Moving Average) provides a straightforward calculation based on the arithmetic mean of the data. VWMA and RMA have both been excluded for varying reasons, both being unworthy of having explanation here.
By allowing for adjustment refinements between these filter methods, traders may garner the flexibility to adapt their analysis to different market dynamics, optimizing their algorithms for improved decision-making and performance on demand.
INDICATOR INTRODUCTION:
ChartPrime's Composite Trend Oscillator operates as an oscillator based on the concept of a moving average ribbon. It utilizes up to 32 filters with progressively longer periods to assess trend direction and strength. Embedded within this indicator is an alternative view that utilizes the separation of the ribbon filaments to assess volatility. Both versions are excellent candidates for trend and momentum, both offering visualization of polarity, directional coloring, and filter crossings. Anyone who has former experience using RSI or stochastics may have ease of understanding applying this to their chart.
COMPOSITE CLUSTER MODES EXPLAINED:
In Trend Strength mode, the oscillator behavior signifies market direction and movement strength. When the oscillator is rising and above zero, the market is within a bullish phase, and visa versa. If the signal filter crosses the composite trend, this indicates a potential dynamic shift signaling a possible reversal. When the oscillator is teetering on its extremities, the market is more inclined to reverse later.
With Volatility mode, the oscillator undergoes a transformation, displaying an unbounded oscillator driven by market volatility. While it still employs the same scoring mechanism, it is now scaled according to the strength of the market move. This can aid with identification of ranging scenarios. However, one side effect is that the oscillator no longer has minimum or maximum boundaries. This can still be advantageous when considering divergences.
NOTEWORTHY SETTINGS FEATURES:
The following input settings described offer comprehensive control over the indicator's behavior and visualization.
Common Controls:
Price Source Selection - The indicator offers flexibility in choosing the price source for analysis. Traders can select from multiple options.
Composite Cluster Mode - Choose between "Trend Strength" and "Volatility" modes, providing insights into trend directionality or volatility weighting.
Cluster Filter and Length - Selects a filter for the cluster composition. This includes a length parameter adjustment.
Cluster Options:
Cluster Dispersion - Users can adjust the separation between moving averages in the cluster, influencing the sensitivity of the analysis.
Cluster Trimming - By modifying upper and lower trim parameters, traders can adjust the sensitivity of the moving averages within the cluster, enhancing its adaptability.
PostSmooth Filter and Length - Choose a filter to refine the composite cluster's post-smoothing with a length parameter adjustment.
Signal Filter and Length - Users can select a filter for the lagging signal plot, also having a length parameter adjustment.
Transition Easing - Sensitivity adjustment to influence the transition between bullish and bearish colors.
Enjoy
Wavelet & Fourier Smoothed Volume zone oscillator (W&)FSVZO Indicator id:
USER;e7a774913c1242c3b1354334a8ea0f3c
(only relevant to those that use API requests)
MEANINGFUL DESCRIPTION:
The Volume Zone oscillator breaks up volume activity into positive and negative categories. It is positive when the current closing price is greater than the prior closing price and negative when it's lower than the prior closing price. The resulting curve plots through relative percentage levels that yield a series of buy and sell signals, depending on level and indicator direction.
The Wavelet & Fourier Smoothed Volume Zone Oscillator (W&)FSVZO is a refined version of the Volume Zone Oscillator, enhanced by the implementation of the Discrete Fourier Transform. Its primary function is to streamline price data and diminish market noise, thus offering a clearer and more precise reflection of price trends.
By combining the Wavalet and Fourier aproximation with Ehler's white noise histogram, users gain a comprehensive perspective on volume-related market conditions.
HOW TO USE THE INDICATOR:
The default period is 2 but can be adjusted after backtesting. (I suggest 5 VZO length and NoiceR max length 8 as-well)
The VZO points to a positive trend when it is rising above the 0% level, and a negative trend when it is falling below the 0% level. 0% level can be adjusted in setting by adjusting VzoDifference. Oscillations rising below 0% level or falling above 0% level result in natural trend.
ORIGINALITY & USFULLNESS:
Personal combination of Fourier and Wavalet aproximation of a price which results in less noise Volume Zone Oscillator.
The Wavelet Transform is a powerful mathematical tool for signal analysis, particularly effective in analyzing signals with varying frequency or non-stationary characteristics. It dissects a signal into wavelets, small waves with varying frequency and limited duration, providing a multi-resolution analysis. This approach captures both frequency and location information, making it especially useful for detecting changes or anomalies in complex signals.
The Discrete Fourier Transform (DFT) is a mathematical technique that transforms discrete data from the time domain into its corresponding representation in the frequency domain. This process involves breaking down a signal into its individual frequency components, thereby exposing the amplitude and phase characteristics inherent in each frequency element.
This indicator utilizes the concept of Ehler's Universal Oscillator and displays a histogram, offering critical insights into the prevailing levels of market noise. The Ehler's Universal Oscillator is grounded in a statistical model that captures the erratic and unpredictable nature of market movements. Through the application of this principle, the histogram aids traders in pinpointing times when market volatility is either rising or subsiding.
DETAILED DESCRIPTION:
My detailed description of the indicator and use cases which I find very valuable.
What is oscillator?
Oscillators are chart indicators that can assist a trader in determining overbought or oversold conditions in ranging (non-trending) markets.
What is volume zone oscillator?
Price Zone Oscillator measures if the most recent closing price is above or below the preceding closing price.
Volume Zone Oscillator is Volume multiplied by the 1 or -1 depending on the difference of the preceding 2 close prices and smoothed with Exponential moving Average.
What does this mean?
If the VZO is above 0 and VZO is rising. We have a bullish trend. Most likely.
If the VZO is below 0 and VZO is falling. We have a bearish trend. Most likely.
Rising means that VZO on close is higher than the previous day.
Falling means that VZO on close is lower than the previous day.
What if VZO is falling above 0 line?
It means we have a high probability of a bearish trend.
Thus the indicator returns 0 when falling above 0 (or rising bellow 0) and we combine higher and lower timeframes to gauge the trend.
In the next Image you can see that trend is positive on 4h, neutral on 12h and positive on 1D. That means trend is positive.
I am sorry, the chart is a bit messy. The idea is to use the indicator over more than 1 Timeframe.
What is approximation and smoothing?
They are mathematical concepts for making a discrete set of numbers a
continuous curved line.
Fourier and Wavelet approximation of a close price are taken from aprox library.
Key Features:
You can tailor the indicator to your preferences with adjustable parameters such as VZO length, noise reduction settings, and smoothing length.
Volume Zone Oscillator (VZO) shows market sentiment with the VZO, enhanced with Exponential Moving Average (EMA) smoothing for clearer trend identification.
Noise Reduction leverages Euler's White noise capabilities for effective noise reduction in the VZO, providing a cleaner and more accurate representation of market dynamics.
Choose between the traditional Fast Fourier Transform (FFT), the innovative Double Discrete Fourier Transform (DTF32) and Wavelet soothed Fourier soothed price series to suit your analytical needs.
Image of Wavelet transform with FAST settings, Double Fourier transform with FAST settings. Improved noice reduction with SLOW settings, and standard FSVZO with SLOW settings:
Fast setting are setting by default:
VZO length = 2
NoiceR max Length = 2
Slow settings are:
VZO length = 5 or 7
NoiceR max Length = 8
As you can see fast setting are more volatile. I suggest averaging fast setting on 4h 12h 1d 2d 3d 4d W and M Timeframe to get a clear view on market trend.
What if I want long only when VZO is rising and above 15 not 0?
You have set Setting VzoDifference to 15. That reduces the number of trend changes.
Example of W&FSVZO with VzoDifference 15 than 0:
VZO crossed 0 line but not 15 line and that's why Indicator returns 0 in one case an 1 in another.
What is Smooth length setting?
A way of calculating Bullish or Bearish FSVZO.
If smooth length is 2 the trend is rising if:
rising = VZO > ta.ema(VZO, 2)
Meaning that we check if VZO is higher that exponential average of the last 2 elements.
If smooth length is 1 the trend is rising if:
rising = VZO_ > VZO_
Rising is boolean value, meaning TRUE if rising and FALSE if falling.
Mathematical equations presented in Pinescript:
Fourier of the real (x axis) discrete:
x_0 = array.get(x, 0) + array.get(x, 1) + array.get(x, 2)
x_1 = array.get(x, 0) + array.get(x, 1) * math.cos( -2 * math.pi * _dir / 3 ) - array.get(y, 1) * math.sin( -2 * math.pi * _dir / 3 ) + array.get(x, 2) * math.cos( -4 * math.pi * _dir / 3 ) - array.get(y, 2) * math.sin( -4 * math.pi * _dir / 3 )
x_2 = array.get(x, 0) + array.get(x, 1) * math.cos( -4 * math.pi * _dir / 3 ) - array.get(y, 1) * math.sin( -4 * math.pi * _dir / 3 ) + array.get(x, 2) * math.cos( -8 * math.pi * _dir / 3 ) - array.get(y, 2) * math.sin( -8 * math.pi * _dir / 3 )
Euler's Noice reduction with both close and Discrete Furrier approximated price.
w = (dft1*src - dft1 *src ) / math.sqrt(math.pow(math.abs(src- src ),2) + math.pow(math.abs(dft1 - dft1 ),2))
filt := na(filt ) ? 0 : c1 * (w*dft1 + nz(w *dft1 )) / 2.0 /math.abs(dft1 -dft1 ) + c2 * nz(filt ) - c3 * nz(filt )
Usecase:
First option:
Select the preferred version of DFT and noise reduction settings based on your analysis requirements.
Leverage the script to identify Bullish and Bearish trends, shown with green and red triangle.
Combine Different Timeframes to accurately determine market trend.
Second option:
Pull the data with API sockets to automate your trading journey.
plot(close, title="ClosePrice", display=display.status_line)
plot(open, title="OpenPrice", display=display.status_line)
plot(greencon ? 1 : redcon ? -1 : 0, title="position", display=display.status_line)
Use ClosePrice, OpenPrice and "position" titles to easily read and backtest your strategy utilising more than 1 Time Frame.
Indicator id:
USER;e7a774913c1242c3b1354334a8ea0f3c
(only relevant to those that use API requests)
Trend Deviation strategy - BTC [IkkeOmar]Intro:
This is an example if anyone needs a push to get started with making strategies in pine script. This is an example on BTC, obviously it isn't a good strategy, and I wouldn't share my own good strategies because of alpha decay.
This strategy integrates several technical indicators to determine market trends and potential trade setups. These indicators include:
Directional Movement Index (DMI)
Bollinger Bands (BB)
Schaff Trend Cycle (STC)
Moving Average Convergence Divergence (MACD)
Momentum Indicator
Aroon Indicator
Supertrend Indicator
Relative Strength Index (RSI)
Exponential Moving Average (EMA)
Volume Weighted Average Price (VWAP)
It's crucial for you guys to understand the strengths and weaknesses of each indicator and identify synergies between them to improve the strategy's effectiveness.
Indicator Settings:
DMI (Directional Movement Index):
Length: This parameter determines the number of bars used in calculating the DMI. A higher length may provide smoother results but might lag behind the actual price action.
Bollinger Bands:
Length: This parameter specifies the number of bars used to calculate the moving average for the Bollinger Bands. A longer length results in a smoother average but might lag behind the price action.
Multiplier: The multiplier determines the width of the Bollinger Bands. It scales the standard deviation of the price data. A higher multiplier leads to wider bands, indicating increased volatility, while a lower multiplier results in narrower bands, suggesting decreased volatility.
Schaff Trend Cycle (STC):
Length: This parameter defines the length of the STC calculation. A longer length may result in smoother but slower-moving signals.
Fast Length: Specifies the length of the fast moving average component in the STC calculation.
Slow Length: Specifies the length of the slow moving average component in the STC calculation.
MACD (Moving Average Convergence Divergence):
Fast Length: Determines the number of bars used to calculate the fast EMA (Exponential Moving Average) in the MACD.
Slow Length: Specifies the number of bars used to calculate the slow EMA in the MACD.
Signal Length: Defines the number of bars used to calculate the signal line, which is typically an EMA of the MACD line.
Momentum Indicator:
Length: This parameter sets the number of bars over which momentum is calculated. A longer length may provide smoother momentum readings but might lag behind significant price changes.
Aroon Indicator:
Length: Specifies the number of bars over which the Aroon indicator calculates its values. A longer length may result in smoother Aroon readings but might lag behind significant market movements.
Supertrend Indicator:
Trendline Length: Determines the length of the period used in the Supertrend calculation. A longer length results in a smoother trendline but might lag behind recent price changes.
Trendline Factor: Specifies the multiplier used in calculating the trendline. It affects the sensitivity of the indicator to price changes.
RSI (Relative Strength Index):
Length: This parameter sets the number of bars over which RSI calculates its values. A longer length may result in smoother RSI readings but might lag behind significant price changes.
EMA (Exponential Moving Average):
Fast EMA: Specifies the number of bars used to calculate the fast EMA. A shorter period results in a more responsive EMA to recent price changes.
Slow EMA: Determines the number of bars used to calculate the slow EMA. A longer period results in a smoother EMA but might lag behind recent price changes.
VWAP (Volume Weighted Average Price):
Default settings are typically used for VWAP calculations, which consider the volume traded at each price level over a specific period. This indicator provides insights into the average price weighted by trading volume.
backtest range and rules:
You can specify the start date for backtesting purposes.
You can can select the desired trade direction: Long, Short, or Both.
Entry and Exit Conditions:
LONG:
DMI Cross Up: The Directional Movement Index (DMI) indicates a bullish trend when the positive directional movement (+DI) crosses above the negative directional movement (-DI).
Bollinger Bands (BB): The price is below the upper Bollinger Band, indicating a potential reversal from the upper band.
Momentum Indicator: Momentum is positive, suggesting increasing buying pressure.
MACD (Moving Average Convergence Divergence): The MACD line is above the signal line, indicating bullish momentum.
Supertrend Indicator: The Supertrend indicator signals an uptrend.
Schaff Trend Cycle (STC): The STC indicates a bullish trend.
Aroon Indicator: The Aroon indicator signals a bullish trend or crossover.
When all these conditions are met simultaneously, the strategy considers it a favorable opportunity to enter a long trade.
SHORT:
DMI Cross Down: The Directional Movement Index (DMI) indicates a bearish trend when the negative directional movement (-DI) crosses above the positive directional movement (+DI).
Bollinger Bands (BB): The price is above the lower Bollinger Band, suggesting a potential reversal from the lower band.
Momentum Indicator: Momentum is negative, indicating increasing selling pressure.
MACD (Moving Average Convergence Divergence): The MACD line is below the signal line, signaling bearish momentum.
Supertrend Indicator: The Supertrend indicator signals a downtrend.
Schaff Trend Cycle (STC): The STC indicates a bearish trend.
Aroon Indicator: The Aroon indicator signals a bearish trend or crossover.
When all these conditions align, the strategy considers it an opportune moment to enter a short trade.
Disclaimer:
THIS ISN'T AN OPTIMAL STRATEGY AT ALL! It was just an old project from when I started learning pine script!
The backtest doesn't promise the same results in the future, always do both in-sample and out-of-sample testing when backtesting a strategy. And make sure you forward test it as well before implementing it!
Furthermore this strategy uses both trend and mean-reversion systems, that is usually a no-go if you want to build robust trend systems .
Don't hesitate to comment if you have any questions or if you have some good notes for a beginner.
CPR by JBISIncludes CPR, Pivot Points and an EMA. This advanced technical indicator amalgamates critical components essential for robust market analysis: CPR (Central Pivot Range), Pivot Points, and EMA (Exponential Moving Average). Designed to empower traders with comprehensive insights, this indicator serves as a dynamic tool for chart analysis across various timeframes and markets.
CPR (Central Pivot Range):
Central Pivot Range, often abbreviated as CPR, represents a pivotal zone delineating critical support and resistance levels within a given trading session. Calculated from the previous session's high, low, and close, CPR helps identify potential reversal points and areas of price consolidation.
Pivot Points:
Pivot Points are key price levels derived from the previous session's high, low, and close. These levels serve as significant reference points for traders to anticipate potential price movements, gauge market sentiment, and formulate strategic entry and exit points.
EMA (Exponential Moving Average):
EMA, or Exponential Moving Average, is a widely-used trend-following indicator that places greater emphasis on recent price data. By smoothing out price fluctuations, EMA provides traders with a clearer depiction of market trends, facilitating timely decision-making and trend identification.
Key Features:
Customizable Parameters: Tailor the indicator settings to align with your trading strategy and risk tolerance.
Multi-Timeframe Analysis: Seamlessly analyze price action across different timeframes, enabling comprehensive market assessment and strategy formulation.
Visual Clarity: Intuitive chart visualization ensures easy interpretation of key levels and trend dynamics.
Real-Time Updates: Stay informed with real-time updates as market conditions evolve, empowering proactive decision-making and trade execution.
Advanced Volume Analytics and Distribution IndicatorThe Advanced Volume Analytics and Distribution Indicator is a sophisticated tool designed for financial analysts and traders who seek in-depth insights into market volume dynamics. This Pine Script-based indicator is a comprehensive solution, offering a rich set of features that analyze volume data using various statistical methods and theories. It's tailored for those who require a deeper understanding of market movements and volume distribution.
Key Features:
Volume Distribution Analysis: Utilizes standard deviation and mean calculations to analyze the distribution of trading volume. Employs z-scores to measure the standard deviations of volume from its mean, offering insights into volume anomalies.
Bell Curve Modeling: Constructs a bell curve (normal distribution) based on volume data, enabling users to visualize and assess the distribution of volume in a standard statistical format.
Provides a z-score based bell curve, offering a normalized view of volume deviations.
Exponential Smoothing: Applies exponential smoothing to volume data, giving more weight to recent observations. This feature is crucial for analyzing trending behaviors in volume data.
Stress Metric Calculation: Introduces a unique 'stress' metric, calculated using a custom formula. This metric is designed to evaluate the volatility or variability in the volume data over a specified period.
Central Limit Theorem (CLT) Mean Estimation: Implements CLT for estimating the mean of volume data. The CLT states that the distribution of sample means approximates a normal distribution as the sample size becomes larger.
Variance Point Estimation: Calculates the variance of volume data, providing insights into its variability and consistency over time.
Chi-Squared Test (Commented): Although not active in the initial release, the script includes a framework for a Chi-Squared Test to compare observed and expected volume frequencies, offering potential for future statistical comparisons.
Percentile Calculations and Convolution: Performs percentile calculations on volume data and employs convolution to these percentiles, enabling a more nuanced analysis of volume distribution.
Customizability: Users can input various parameters like anchor period, degrees of freedom, and smoothing preferences, making the tool adaptable to different analysis needs.
Visualization and Plotting: Features multiple plots for easy visualization of volume metrics, including stress, bell curves, point estimators, and smoothed data.
Theoretical Foundations:
This indicator is grounded in established statistical theories and methods, including the Central Limit Theorem, Chi-Squared Test (for future implementations), and convolution techniques. These foundations ensure that the indicator not only provides practical insights but also maintains a high standard of statistical rigor.
Intended Users:
This indicator is ideal for technical analysts, traders, and financial professionals who require a deep and statistically sound understanding of market volume behavior.
Release Notes:
This tool is designed a theoretical test of established statistical models and requires familiarity with Pine Script for customization. Future updates may include activation and expansion of the Chi-Squared Test functionality and additional statistical modules based on user feedback. It should be noted that it is advisable to use a logarithmic-inverted scale; when combined, these scales can provide a unique perspective that neither could offer alone. This combination might be particularly useful in highlighting exponential growth or decay trends, or in cases where the most significant data points are in the lower range of the dataset.
Notes of Stress Calculations:
The "stress metric" in the script is a custom-designed feature intended to measure the level of variability or volatility in the volume data over a given time period. This metric is calculated using a novel approach with concepts similar to those used in the field of engineering , particularly in stress analysis and finite element analysis (FEA).
Segmentation of Time Frame:
The script divides the given time frame (timeFrame) into smaller segments based on a specified number of units (units). This segmentation essentially breaks down the entire period into smaller, more manageable intervals for analysis. For each segment, the script calculates a 'stress' value. This involves iterating through each segment and performing calculations based on the source data (src), the default src is the volume data.
Calculation per Segment:
For each segment, the script identifies two points: the starting point (x1) and the ending point (x2). It then retrieves the corresponding values of the source data at these points (y1 and y2).
It calculates the difference in the x-axis (delta_x, the length of the segment) and the difference in the y-axis (delta_y, the change in volume over that segment).
Stress Calculation:
The script then calculates the 'stress' for each segment as the ratio of delta_y to delta_x. This ratio gives a measure of how much the volume has changed per unit of time within each segment. The stress values for each segment are then summed up to provide a cumulative measure of stress over the entire time frame.
The stress metric is essentially a measure of the volatility or variability in volume data. High stress values indicate larger changes in volume over shorter periods, suggesting more volatile market conditions. For traders and analysts, understanding the level of volatility is crucial. It can inform decision-making processes, risk management strategies, and provide insights into market sentiment. By comparing stress levels across different time frames or different securities, analysts can gain insights into relative market dynamics.
{Gunzo} Trend Sniper (Multiple MAs with coefficient)Updated GUNZO's Trend Sniper script by adding in different MA types to choose from. This can help reduce false signals and sharpen the trend reversal points.
Here's a summary of the key changes:
1. Multiple Moving Average Types: The original script was focused solely on the Weighted Moving Average (WMA) with a coefficient. The updated script introduces flexibility by allowing users to choose from a variety of Moving Average types, including WMA, VWMA (Volume Weighted Moving Average), EMA (Exponential Moving Average), SMA (Simple Moving Average), HullMA (Hull Moving Average), TEMA (Triple Exponential Moving Average), DEMA (Double Exponential Moving Average), T3, and RMA (Running Moving Average).
2. Coefficient Integration: In the original script, the coefficient was specifically designed for the WMA calculation. The updated script extends this concept to all the selected Moving Average types. This coefficient is applied differently depending on the type of MA, often affecting the length of the MA calculation.
3. Dynamic Length Calculation: For MAs that traditionally use an integer length (like SMA, EMA, etc.), the updated script calculates this length dynamically by multiplying the user-defined length by the coefficient and then rounding it to the nearest integer. This ensures compatibility with Pine Script's requirements for these functions.
All credits to GUNZO
original script: