Moving Average CyclesMoving Average Cycles Indicator
Description:
The Moving Average Cycles indicator is a versatile tool designed to help traders identify and analyze bullish and bearish cycles based on price movements relative to a moving average. This indicator offers valuable insights into market trends and potential reversal points.
Key Features:
Customizable Moving Average: Users can adjust the MA period and resolution (Daily, Weekly, Monthly) to suit their trading style.
Cycle Identification: The indicator tracks bull and bear cycles, providing visual cues through color-coded histograms.
Comprehensive Metrics: A detailed table displays crucial cycle statistics, including:
Current cycle information (candles and % distance from MA)
Maximum and average cycle lengths (in candles)
Maximum and average percentage distances from the MA
How to Use:
Apply the indicator to your chart and adjust the MA period and resolution as needed.
Green histograms represent bullish cycles, while red histograms indicate bearish cycles.
Use the metrics table to gain insights into historical cycle behavior and current market positioning.
This indicator is designed to complement your existing trading strategy by providing a clear visual representation of market cycles and detailed statistical information. It can be particularly useful for identifying potential trend reversals and gauging the strength of current trends compared to the past.
Note: Past performance does not guarantee future results. This indicator is meant for informational purposes only and should not be considered as financial advice. Always combine multiple analysis tools and conduct your own research before making trading decisions.
This script is published as open-source under the Mozilla Public License 2.0. Feel free to use and modify it, but please provide appropriate credit if you build upon this work.
I hope you find this Moving Average Cycles indicator helpful in your trading journey. If you have any questions or suggestions for improvement, please feel free to leave a comment below.
Cycles
Asset Drawdown & Drawdown HeatMap [InvestorUnknown]Overview
The "Asset Drawdown & Drawdown HeatMap" indicator is designed for educational purposes to help users visualize and analyze the drawdowns of various assets. It highlights both recent and historical drawdowns, offering valuable insights into the performance and risk of different investments. Additionally, it can serve as a complementary analysis tool for trading and investing decisions.
Features
Drawdown Calculation:
Computes the drawdown from the highest value (ATH) to the current value, showing the percentage decline.
Displays both the current drawdown and the maximum historical drawdown for the selected assets.
HeatMap Visualization:
Uses a gradient color scheme to represent the magnitude of drawdowns over a specified lookback period.
Helps identify periods of significant decline and recovery visually.
Multiple Assets:
Supports up to 10 different assets (adding more would make it harder to see the drawdowns of different assets), allowing users to compare drawdowns across various symbols.
Each asset can be individually plotted and color-coded for clarity.
Customizable Settings:
User inputs for high and low value calculations, color preferences, and lookback periods.
Option to color bars based on the drawdown heatmap.
Detailed Functionality
Drawdown Calculation:
The DD() function calculates the current drawdown and the maximum historical drawdown based on the high and low values.
The drawdown is calculated as 100 - (lowvalue / ATH * 100), where ATH is the highest value observed so far.
// - - - - - Custom Function - - - - - //{
DD() =>
ATH = highvalue
ATH := na(ATH ) ? highvalue : math.max(highvalue, ATH )
Drawdown = 100 - lowvalue / ATH * 100
MaxDrawdown = Drawdown
MaxDrawdown := na(MaxDrawdown ) ? Drawdown : math.max(Drawdown, MaxDrawdown )
//}
Security Request:
Uses the request.security() function to fetch drawdown data for each specified asset on a daily timeframe.
Computes both current drawdown (TnDD) and maximum drawdown (TnMDD) for each asset.
// - - - - - Create Variables - - - - - //{
= request.security("", "1D", DD()) // Chart
= request.security(t1, "1D", DD())
= request.security(t2, "1D", DD())
= request.security(t3, "1D", DD())
= request.security(t4, "1D", DD())
= request.security(t5, "1D", DD())
= request.security(t6, "1D", DD())
= request.security(t7, "1D", DD())
= request.security(t8, "1D", DD())
= request.security(t9, "1D", DD())
= request.security(t10, "1D", DD())
//}
Plotting:
Plots the drawdown values for each asset on the chart, with the option to enable or disable plotting for individual assets.
Colors the plotted lines and labels based on user-specified preferences.
HeatMap:
Creates a heatmap color gradient based on the drawdown values over the lookback period.
Colors the bars on the chart according to the heatmap to visualize drawdown severity over time.
// - - - - - HeatMap - - - - - //{
heatcol = color.from_gradient(T0DD, ta.lowest(T0DD,lookback), ta.highest(T0DD,lookback), topcol, botcol)
barcolor(colbars ? heatcol : na)
//}
Labels:
Displays labels for each asset's drawdown value at the end of the chart for quick reference.
This indicator is an excellent tool for educational purposes, helping users understand drawdown dynamics and their implications on asset performance. It also provides a visual aid for monitoring and comparing drawdowns across multiple assets, which can be beneficial for making informed trading and investment decisions.
US Presidential Elections (Names & Dates)US Presidential Elections (Names & Dates)
Description :
This indicator marks key dates in US presidential history, highlighting both election days and inauguration dates. It's designed to provide historical context to your charts, allowing you to see how major political events align with market movements.
Key Features:
• Displays US presidential elections from 1936 to 2052
• Shows inauguration dates for each president
• Customizable colors and styles for both election and inauguration markers
• Toggle visibility of election and inauguration labels separately
• Adapts to different timeframes (daily, weekly, monthly)
• Includes president names for historical context
The indicator uses yellow labels for election days and blue labels for inauguration dates. Election labels show the year and "Election", while inauguration labels display the name of the incoming president.
Customization options include:
• Colors for election and inauguration labels and text
• Line widths for both types of events
• Label placement styles
This tool is perfect for traders and analysts who want to correlate political events with market trends over long periods. It provides a unique perspective on how presidential cycles might influence financial markets.
Note: Future elections (2024 onwards) are marked with a placeholder (✅) as the presidents are not yet known.
Use this indicator to:
• Identify potential market patterns around election cycles
• Analyze historical market reactions to specific presidencies
• Add political context to your long-term chart analysis
Enhance your chart analysis with this comprehensive view of US presidential history!
Non-Sinusoidal Multi-Layered Moving Average OscillatorThis indicator utilizes multiple moving averages (MAs) of different lengths their difference and its rate of change to provide a comprehensive view of both short-term and long-term market trends. The output signal is characterized by its non-sinusoidal nature, offering distinct advantages in trend analysis and market forecasting.
Combining the difference between two moving averages with the ROC allows to assess not only the direction and strength of the trend but also the momentum behind it. Transforming these signal in to non-sinusoidal output enhances its utility.
The indicator allows traders to select any one or more of seven moving average options. Larger timeframes (e.g., MA89/MA144) provide a broader identification of the overall trend, helping to understand the general market direction. Smaller timeframes (e.g., MA5/MA8) are more sensitive to price changes and can indicate better entry and exit points, aiding in the identification of retracements and pullbacks. By combining multiple timeframes, traders can get a comprehensive view of the market, enabling more precise and informed trading decisions.
Key Features:
Multiple Moving Averages:
The indicator calculates several exponential moving averages (EMAs) based on different lengths: MA5, MA8, MA13, MA21, MA34, MA55, MA89, and MA144.
These MAs are further smoothed using a secondary exponential moving average, with the smoothing length customizable by the user.
Percentage Differences:
The indicator computes the percentage differences between successive MAs (e.g., (MA5 - MA8) / MA8 * 100). These differences highlight the relative movement of prices over different periods, providing insights into market momentum and trend strength.
Short-term MA differences (e.g., MA5/MA8) are more sensitive to recent price changes, making them useful for detecting quick market movements.
Long-term MA differences (e.g., MA89/MA144) smooth out short-term fluctuations, helping to identify major trends.
Rate of Change (ROC):
The indicator applies the Rate of Change (ROC) to the percentage differences of the MAs. ROC measures the speed at which the percentage differences are changing over time, providing an additional layer of trend analysis.
ROC helps in understanding the acceleration or deceleration of market trends, indicating the strength and potential reversals.
Transformations:
The percentage differences undergo a series of mathematical transformations (either inverse hyperbolic sine transformation or inverse fisher transformation) to refine the signal and enhance its interpretability. These transformations include adjustments to stabilize the values and highlight significant movements.
checkbox allows users to select which mathematical transformations to use.
Non-Sinusoidal Nature:
The output signal of this indicator is non-sinusoidal, characterized by abrupt changes and distinct patterns rather than smooth, wave-like oscillations.
The non-sinusoidal signal provides clearer demarcations of trend changes and is more responsive to sudden market shifts.
This nature reduces the lag typically associated with sinusoidal indicators, allowing for more timely and accurate trading decisions.
Customizable Options:
Users can select which MA pairs to include in the analysis using checkboxes. This flexibility allows the indicator to adapt to different trading strategies, whether focused on short-term movements or long-term trends.
Visual Representation:
The indicator plots the transformed values on a separate panel, making it easy for traders to visualize the trends and potential entry or exit points.
Usage Scenarios:
Short-Term Trading: By focusing on shorter MAs (e.g., MA5/MA8), traders can capture quick market movements and identify short-term trends.
Long-Term Analysis: Utilizing longer MAs (e.g., MA89/MA144) helps in identifying major market trends.
Combination of MAs: The ability to mix different MA lengths provides a balanced view, helping traders make decisions based on both immediate price actions and overall market direction.
Practical Benefits:
Early Signal Detection: The sensitivity of short-term MAs provides early signals for potential trend changes, assisting traders in timely decision-making.
Trend Confirmation: Long-term MAs offer stable trend confirmation, reducing the likelihood of false signals in volatile markets.
Noise Reduction: The mathematical transformations and ROC applied to the percentage differences help in filtering out market noise, focusing on meaningful price movements.
Improved Responsiveness: The non-sinusoidal nature of the signal allows the indicator to react more quickly to market changes, providing more accurate and timely trading signals.
Clearer Trend Demarcations: Non-sinusoidal signals make it easier to identify distinct phases of market trends, aiding in better interpretation and decision-making.
MA Optimizer Simplified [CHE]Introduction:
The MA Optimizer Simplified is a powerful tool for traders and analysts who want to compare and optimize various moving averages (MA). This tool is specifically designed to identify the best or worst performers among a variety of moving averages based on their cumulative performance.
Features and Benefits:
1. Versatility:
- Supports multiple types of moving averages, including:
- Simple Moving Average (SMA): A basic MA calculated by averaging the closing prices over a specified period.
- Exponential Moving Average (EMA): Gives more weight to recent prices, making it more responsive to new information.
- Weighted Moving Average (WMA): Assigns more weight to recent data, but in a linear fashion.
- Volume-Weighted Moving Average (VWMA): Averages prices based on volume, giving more importance to periods with higher trading volume.
- Hull Moving Average (HMA): Designed to reduce lag while improving smoothness.
- Smoothed Moving Average (SMMA or RMA): Averages prices over a longer period, providing a smoother line.
- Bollinger Bands: Uses SMA as a basis and adds upper and lower bands based on standard deviations.
- T3: A smoother and less lagging MA that reduces market noise.
- Allows users to easily switch between MA types and test different periods.
2. Performance Evaluation:
- Calculates the cumulative performance of up to ten different MAs.
- Automatically identifies the best or worst performer based on user selection (Best or Worst).
3. Crossover Detection:
- Detects crossovers of prices and MAs to measure performance.
- Provides clear visual signals when the price crosses a moving average.
4. Visual Representation:
- Plots the best MA indicator on the chart, dynamically changing its color based on price movement relative to the MA.
- Table functionality to display the performance of each MA, including the length and achieved performance in percentage.
5. Customizable Settings:
- Customizable settings for table size and position as well as colors for better visualization and user-friendliness.
- Flexibility in selecting the number of candles that must be above or below the MA before a signal is triggered.
Special Features:
1. T3 Indicator:
- The T3 indicator provides a smoother representation and reduces market noise, leading to more precise signals.
2. Crossover and Crossunder Logic:
- The script includes advanced logic for detecting crossover and crossunder events to identify accurate entry points.
3. Dynamic Color Change:
- The best MA indicator changes color based on the number of candles above or below the MA, helping to quickly recognize market sentiment.
4. Comprehensive Performance Analysis:
- The calculation of cumulative performance for each MA allows for detailed analysis and helps identify the most effective trading strategies.
Conclusion:
The MA Optimizer Simplified is an essential tool for any trader looking to analyze and optimize the performance of various moving averages. With its versatile features and user-friendly settings, it offers a comprehensive and efficient solution for technical analysis.
Best regards, Chervolino
Fourier Extrapolation of PriceOverview
The "Fourier Extrapolation of Price" indicator utilizes Fourier Transform methods to analyze and predict future price movements based on historical data. By decomposing price series into their frequency components, this indicator provides a forecast of future price trends, making it a powerful tool for traders seeking advanced analytical techniques.
Key Features
Fourier Transform Analysis: Applies Discrete Fourier Transform (DFT) to the price series to identify frequency components.
Price Prediction: Forecasts future prices based on the dominant frequencies detected in the historical data.
Customizable Parameters: Allows users to set the length of historical data for analysis and the forecast period.
Visual Representation: Plots historical and forecasted prices for easy comparison.
How It Works
The indicator first normalizes the price series by subtracting the mean. It then applies the Discrete Fourier Transform (DFT) to the normalized data, extracting the real and imaginary parts. The magnitude and phase of these components are used to forecast future prices through an inverse DFT. Finally, the forecasted prices are denormalized and plotted alongside the historical prices on the chart.
Usage Instructions
Configure Parameters: Set the length of the historical data (DFT Length) and the forecast period (Forecast Length) to suit your analysis.
Apply to Chart: Add the indicator to your chart to start the analysis. Note that the computation may take a minute to complete due to the complexity of the Fourier Transform.
Analyze Results: Review the plotted forecasted prices (in red) alongside the historical prices (in blue) to identify potential future trends.
Trading Decisions: Use the forecasted price trends to inform your trading decisions, such as identifying potential entry and exit points based on predicted market movements.
Note : Due to the computational complexity of the Fourier Transform, the prediction may take a minute to load. Please be patient as the indicator processes the data to provide accurate forecasts.
This indicator is useful for traders who:
Advanced Analysis: Seek advanced mathematical techniques for market analysis.
Trend Prediction: Want to forecast future price movements based on historical data.
Customizable Analysis: Prefer customizable parameters for tailored analysis.
Visual Insights: Appreciate visual representation of historical and forecasted prices for better decision-making.
[MAD] Custom Session VWAP BandsOverview
This indicator helps visualize the Volume Weighted Average Price (VWAP) and its associated standard deviation bands over specified time periods, providing traders with a clear understanding of price trends, volatility, and potential support/resistance levels.
Inputs
Deviation
StDev mult 1: Multiplier for the first standard deviation band (Default: 1.0)
StDev mult 2: Multiplier for the second standard deviation band (Default: 2.0)
StDev mult 3: Multiplier for the third standard deviation band (Default: 3.0)
StDev mult 4: Multiplier for the fourth standard deviation band (Default: 4.0)
Line width: Width of the lines for the bands (Default: 2)
Custom Vwap session reset settings
Many different options are considered when a session is going to be reset.
Plot and Fill Options
Enable Fills: Enable/disable filling between bands.
Plot +4: Enable/disable plotting the +4 standard deviation band.
Plot +3: Enable/disable plotting the +3 standard deviation band.
Plot +2: Enable/disable plotting the +2 standard deviation band.
Plot +1: Enable/disable plotting the +1 standard deviation band.
Plot VWAP: Enable/disable plotting the VWAP line.
Plot -1: Enable/disable plotting the -1 standard deviation band.
Plot -2: Enable/disable plotting the -2 standard deviation band.
Plot -3: Enable/disable plotting the -3 standard deviation band.
Plot -4: Enable/disable plotting the -4 standard deviation band.
How to Use the Indicator
Adding the Indicator
Add the indicator to your chart through your trading platform's indicator menu.
Configuring the VWAP Reset
Specify reset intervals based on time, days of the week, or specific dates.
Adjust the time zone if necessary.
Customizing Standard Deviation Bands
Set the multipliers for the standard deviation bands.
Choose line width for better visualization.
Enabling Plots and Fills
Select which bands to display.
Enable or disable fills between the bands.
Practical Application of VWAP Bands
Understanding VWAP
VWAP is a trading benchmark that calculates the average price a security has traded at throughout the day based on volume and price. It is primarily used for intraday trading but can also offer insights during end-of-day reviews.
Using VWAP for Trading
Intraday Trading
Entry and Exit Points: VWAP can help identify optimal buy and sell points. Buy when the price is above VWAP and sell when it's below.
Support and Resistance: VWAP often acts as a dynamic support/resistance level. Prices tend to revert to VWAP, making it a crucial level for intraday traders.
Trend Confirmation
Uptrends and Downtrends: In an uptrend, the price will generally stay above VWAP. Conversely, in a downtrend, it will stay below. Use this to confirm market direction.
Combining with Other Indicators
Moving Averages and Bollinger Bands: Combining VWAP with these indicators can provide a more robust trading signal, confirming trends and potential reversals.
Setting Stop-Loss and Profit Targets
Conservative Stop Orders: Place stop orders at recent lows for pullback trades.
Profit Targets: Use daily highs or Fibonacci extension levels to set profit targets.
Strategies for Using VWAP
Pullback Strategy
Buy during pullbacks to VWAP in an uptrend, and sell during rallies to VWAP in a downtrend.
Breakout Strategy
Look for breakouts above/below VWAP after the market open to capitalize on new trends.
Momentum Trading
Use VWAP to confirm the strength of a trend. Buy when the price is consistently above VWAP and sell when it's consistently below.
Institutional Strategies
Institutional traders use VWAP to execute large orders without causing significant market impact, ensuring trades are made around the average price.
By incorporating these strategies, traders can better understand market dynamics, make informed trading decisions, and manage their risk effectively.
Some setup possibilities
MTF Regime Filter II [CHE]Regime Filter II - Comprehensive Guide
Introduction
The "Regime Filter II " indicator is a tool designed to help traders identify market trends by smoothing price data and applying a color scheme to visualize bullish and bearish conditions. This guide provides a detailed explanation of the script's functionality, benefits, and how to use it effectively in TradingView.
Key Benefits
1. Trend Identification: Smooths price data to highlight underlying trends, making it easier for traders to spot potential buying or selling opportunities.
2. Visual Clarity: Uses distinct color schemes to differentiate between bullish and bearish market conditions, enhancing visual analysis.
3. Customization: Offers various settings to adjust smoothing and averaging lengths, choose between different color schemes, and set visibility for different timeframes.
4. Neutral Candle Option: Provides an option to display neutral candles for clearer visual representation when market conditions are neither strongly bullish nor bearish.
5. Timeframe Adaptability: Includes functions to determine appropriate step sizes based on different timeframes, ensuring the indicator remains accurate across various trading periods.
Script Breakdown
1. Indicator Declaration
The script starts by declaring itself as a TradingView indicator using the latest version of Pine Script. This sets up the framework for the indicator's functionality.
2. User Inputs for Smoothing and Averaging Lengths
The script allows users to input specific lengths for smoothing and averaging intervals. These inputs are crucial for determining how the price data is processed to identify trends. By adjusting these lengths, users can fine-tune the sensitivity of the indicator to market movements.
3. Color Scheme Selection
Users can choose between two color schemes: "Traditional" and "WT1 0 Rule". The selected color scheme will determine how the indicator colors the candles to represent bullish and bearish conditions. This customization enhances the visual appeal and usability of the indicator according to personal preferences.
4. Settings for Timeframe Visibility
The script includes settings that allow users to specify which timeframes the indicator should be visible on. This feature helps traders focus on the most relevant timeframes for their trading strategies. Additionally, users can set the number of recent candles to display, providing a clear view of the most recent market trends.
5. Color Definitions
The indicator defines specific colors for bearish and bullish candles. Bearish candles are colored red, while bullish candles are green. These color definitions are applied based on the selected color scheme and the calculated trend, providing a quick visual reference for market conditions.
6. Time Constants
To manage different timeframes effectively, the script uses constants that represent various time intervals in milliseconds, such as minutes, hours, and days. These constants are used to convert timeframes into a format that the script can work with to determine the appropriate step size for calculations.
7. Step Size Determination
The script includes a function that determines the step size based on the selected timeframe. This function ensures that the indicator adapts to different timeframes, maintaining its accuracy and relevance across various trading periods. The step size is calculated based on time intervals, and appropriate labels (like "60", "240", "1D") are assigned.
- For timeframes less than or equal to 1 minute, the step size is set to "60".
- For timeframes less than or equal to 5 minutes, the step size is set to "240".
- For timeframes less than or equal to 1 hour, the step size is set to "1D" (daily).
- For timeframes less than or equal to 4 hours, the step size is set to "3D" (three days).
- For timeframes less than or equal to 12 hours, the step size is set to "7D" (weekly).
- For timeframes less than or equal to 1 day, the step size is set to "1M" (monthly).
- For timeframes less than or equal to 1 week, the step size is set to "3M" (three months).
- For all other timeframes, the step size is set to "12M" (yearly).
8. Trend Calculation
The core of the indicator is its ability to calculate market trends. Here's a detailed breakdown of how the `calculateTrend` function works:
- Initialization: Variables for the middle price and scale, and summations of high/low prices and ranges, are initialized.
- Summation Loop: A loop runs over the smoothing length to calculate the sum of high and low prices and their range.
- Middle and Scale Calculation: The middle price is determined as the average of high/low sums, and the scale is calculated as a fraction of the average range.
- Normalization: The high, low, and close prices are normalized based on the middle price and scale.
- HT Calculation: The normalized prices are smoothed using a simple moving average (SMA).
- Frequency and Exponential Calculations: The frequency and related constants (a, c1, c2, c3) are calculated for further smoothing.
- Smoothed Moving Average (SMA): A smoothed moving average is computed using the HT values and exponential constants.
- WT1 and WT2 Calculation: The final smoothed values (WT1) and their average (WT2) are derived.
9. Color Application Based on Trend
Once the trend is calculated, the script applies the appropriate color to the candles based on the selected color scheme. This function ensures that the visual representation of the trend is consistent with the user’s preferences.
10. Label Plotting for Timeframes
If the option to display timeframe labels is enabled, the script plots labels on the chart to indicate the current timeframe. This feature helps users quickly identify which timeframe they are analyzing.
11. Shape Plotting Based on Trend and Color Scheme
The indicator plots shapes (squares) on the chart based on the calculated trend and selected color scheme. These shapes provide an additional visual cue for market conditions, enhancing the overall clarity of the indicator.
12. Neutral Candle Color Option
The script includes an option to set the color of neutral candles when market conditions are neither strongly bullish nor bearish. This option helps traders better visualize periods of market indecision.
Summary
The "Regime Filter II " is a powerful and customizable tool for traders, offering clear visual cues for market trends and adaptability to various timeframes. By smoothing price data and applying intuitive color schemes, it helps traders make more informed decisions. With features like adjustable smoothing lengths, multiple color schemes, and optional neutral candle displays, this indicator enhances market analysis and trading strategy development. By following this comprehensive guide, traders can effectively utilize the "Regime Filter II " indicator to enhance their market analysis and make more informed trading decisions.
Best regards
Weighted Global Liquidity Index (WGLI) ROCThe Weighted Global Liquidity Index (WGLI) ROC indicator calculates the rate of change (ROC) of the WGLI, providing valuable insights into the dynamics of global liquidity. The WGLI consolidates major central bank balance sheets and key financial indicators, such as Foreign Exchange Reserves, Interbank Rates, and Interest Rates, converted to USD and expressed in trillions. Specific US accounts like the Treasury General Account (TGA) and Reverse Repurchase Agreements (RRP) are subtracted from the Federal Reserve's balance sheet for a more detailed view of US liquidity.
Using both the WGLI and the WGLI ROC together allows users to track changes in global liquidity and understand policy trajectories and economic conditions. This dual approach offers insights into asset pricing and helps investors make informed decisions about capital allocation.
Feel free to explore and customize the WGLI ROC script to suit your analysis needs!
Weighted Global Liquidity Index (WGLI)The Weighted Global Liquidity Index (WGLI) provides a comprehensive view of major central bank balance sheets from around the world, using data converted to USD for consistency and expressed in trillions. This indicator includes specific US accounts like the Treasury General Account (TGA) and Reverse Repurchase Agreements (RRP), which are subtracted from the Federal Reserve's balance sheet to offer a more detailed perspective on US liquidity.
The WGLI incorporates not only the balance sheets but also additional key financial indicators such as Foreign Exchange Reserves, Interbank Rates, and Interest Rates, weighted by their global liquidity importance. The regions and central banks included are:
Federal Reserve System (FED) - Treasury General Account (TGA) - Reverse Repurchase Agreements (RRP)
European Central Bank (ECB)
People's Bank of China (PBC)
Bank of Japan (BOJ)
Bank of England (BOE)
Bank of Canada (BOC)
Reserve Bank of Australia (RBA)
Reserve Bank of India (RBI)
Swiss National Bank (SNB)
Central Bank of the Russian Federation (CBR)
Central Bank of Brazil (BCB)
Bank of Korea (BOK)
Reserve Bank of New Zealand (RBNZ)
Sweden's Central Bank (Riksbank)
Central Bank of Malaysia (BNM)
This tool is designed for anyone interested in gaining a snapshot of global liquidity to interpret macroeconomic trends. By examining these balance sheets and additional indicators, users can understand policy trajectories and evaluate the global economic climate. It also offers insights into asset pricing and helps investors make informed capital allocation decisions.
Feel free to explore and customize the WGLI script on Trading View to suit your analysis needs!
US M2### Relevance and Functionality of the "US M2" Indicator
#### Relevance
The "US M2" indicator is relevant for several reasons:
1. **Macro-Economic Insight**: The M2 money supply is a critical indicator of the amount of liquidity in the economy. Changes in M2 can significantly impact financial markets, including equities, commodities, and cryptocurrencies.
2. **Trend Identification**: By analyzing the M2 money supply with moving averages, the indicator helps identify long-term and short-term trends, providing insights into economic conditions and potential market movements.
3. **Trading Signals**: The indicator generates bullish and bearish signals based on moving average crossovers and the difference between current M2 values and their moving averages. These signals can be useful for making informed trading decisions.
#### How It Works
1. **Data Input**:
- **US M2 Money Supply**: The indicator fetches the US M2 money supply data using the "USM2" symbol with a monthly resolution.
2. **Moving Averages**:
- **50-Period SMA**: Calculates the Simple Moving Average (SMA) over 50 periods (months) to capture short-term trends.
- **200-Period SMA**: Calculates the SMA over 200 periods to identify long-term trends.
3. **Difference Calculation**:
- **USM2 Difference**: Computes the difference between the current M2 value and its 50-period SMA to highlight deviations from the short-term trend.
4. **Amplification**:
- **Amplified Difference**: Multiplies the difference by 100 to make the deviations more visible on the chart.
5. **Bullish and Bearish Conditions**:
- **Bullish Condition**: When the current M2 value is above the 50-period SMA, indicating a positive short-term trend.
- **Bearish Condition**: When the current M2 value is below the 50-period SMA, indicating a negative short-term trend.
6. **Short-Term SMA of Amplified Difference**:
- **14-Period SMA**: Applies a 14-period SMA to the amplified difference to smooth out short-term fluctuations and provide a clearer trend signal.
7. **Plots and Visualizations**:
- **USM2 Plot**: Plots the US M2 data for reference.
- **200-Period SMA Plot**: Plots the long-term SMA to show the broader trend.
- **Amplified Difference Histogram**: Plots the amplified difference as a histogram with green bars for bullish conditions and red bars for bearish conditions.
- **SMA of Amplified Difference**: Plots the 14-period SMA of the amplified difference to track the trend of deviations.
8. **Moving Average Cross Signals**:
- **Bullish Cross**: Plots an upward triangle when the 50-period SMA crosses above the 200-period SMA, signaling a potential long-term uptrend.
- **Bearish Cross**: Plots a downward triangle when the 50-period SMA crosses below the 200-period SMA, signaling a potential long-term downtrend.
### Summary
The "US M2" indicator provides a comprehensive view of the US M2 money supply, highlighting significant trends and deviations. By combining short-term and long-term moving averages with amplified difference analysis, it offers valuable insights and trading signals based on macroeconomic liquidity conditions.
BTC x M2 Divergence (Weekly)### Why the "M2 Money Supply vs BTC Divergence with Normalized RSI" Indicator Should Work
IMPORTANT
- Weekly only indicator
- Combine it with BTC Halving Cycle Profit for better results
The "M2 Money Supply vs BTC Divergence with Normalized RSI" indicator leverages the relationship between macroeconomic factors (M2 money supply) and Bitcoin price movements, combined with technical analysis tools like RSI, to provide actionable trading signals. Here's a detailed rationale on why this indicator should be effective:
1. **Macroeconomic Influence**:
- **M2 Money Supply**: Represents the total money supply, including cash, checking deposits, and easily convertible near money. Changes in M2 reflect liquidity in the economy, which can influence asset prices, including Bitcoin.
- **Bitcoin Sensitivity to Liquidity**: Bitcoin, being a digital asset, often reacts to changes in liquidity conditions. An increase in money supply can lead to higher asset prices as more money chases fewer assets, while a decrease can signal tightening conditions and lower prices.
2. **Divergence Analysis**:
- **Economic Divergence**: The indicator calculates the divergence between the percentage changes in M2 and Bitcoin prices. This divergence can highlight discrepancies between Bitcoin's price movements and broader economic conditions.
- **Market Inefficiencies**: Large divergences may indicate inefficiencies or imbalances that could lead to price corrections or trends. For example, if M2 is increasing (indicating more liquidity) but Bitcoin is not rising proportionately, it might suggest a potential upward correction in Bitcoin's price.
3. **Normalization and Smoothing**:
- **Normalized Divergence**: Normalizing the divergence to a consistent scale (-100 to 100) allows for easier comparison and interpretation over time, making the signals more robust.
- **Smoothing with EMA**: Applying Exponential Moving Averages (EMAs) to the normalized divergence helps to reduce noise and identify the underlying trend more clearly. This double-smoothed divergence provides a clearer signal by filtering out short-term volatility.
4. **RSI Integration**:
- **RSI as a Momentum Indicator**: RSI measures the speed and change of price movements, indicating overbought or oversold conditions. Normalizing the RSI and incorporating it into the divergence analysis helps to confirm the strength of the signals.
- **Combining Divergence with RSI**: By using RSI in conjunction with divergence, the indicator gains an additional layer of confirmation. For instance, a bullish divergence combined with an oversold RSI can be a strong buy signal.
5. **Dynamic Zones and Sensitivity**:
- **Good DCA Zones**: Highlighting zones where the divergence is significantly positive (good DCA zones) indicates periods where Bitcoin might be undervalued relative to economic conditions, suggesting good buying opportunities.
- **Red Zones**: Marking zones with extremely negative divergence, combined with RSI confirmation, identifies potential market tops or bearish conditions. This helps traders avoid buying into overbought markets or consider selling.
- **Peak Detection**: The sensitivity setting for detecting upside down peaks allows for early identification of potential market bottoms, providing timely entry points for traders.
6. **Visual Cues and Alerts**:
- **Clear Visualization**: The plots and background colors provide immediate visual feedback, making it easier for traders to spot significant conditions without deep analysis.
- **Alerts**: Built-in alerts for key conditions (good DCA zones, red zones, sell signals) ensure traders can act promptly based on the indicator's signals, enhancing the practicality of the tool.
### Conclusion
The "M2 Money Supply vs BTC Divergence with Normalized RSI" indicator integrates macroeconomic data with technical analysis to offer a comprehensive view of Bitcoin's market conditions. By analyzing the divergence between M2 money supply and Bitcoin prices, normalizing and smoothing the data, and incorporating RSI for momentum confirmation, the indicator provides robust signals for identifying potential buying and selling opportunities. This holistic approach increases the likelihood of capturing significant market movements and making informed trading decisions.
Percentile Nearest Rank Without Arrays [CHE] Presentation of the "Percentile Nearest Rank Without Arrays " Indicator
The "Percentile Nearest Rank Without Arrays " is a robust trading indicator designed to calculate the percentile value of a specific price within a defined time frame. This indicator provides traders with a visual representation that helps identify market trends and potential turning points.
Key Features and Functions:
- Percentile Calculation: The indicator calculates the percentile of the closing price within a specified period (default length is 15 periods). This allows traders to view the current price in the context of its historical distribution.
- Customizable Parameters: Traders can adjust the length of the observed period and the desired percentile value, making the analysis more tailored to their trading strategies.
- Color-Coded Visualization: The indicator uses color coding to signal whether the current closing price is above (green) or below (red) the calculated percentile value, providing visual clarity and quick decision-making.
- Efficiency Without Arrays: By avoiding the use of arrays, the indicator is more efficient in terms of computation and memory usage. This results in faster performance, especially when dealing with large datasets or real-time data.
Importance for Traders:
1. Trend Identification: By analyzing whether the current price is above or below a specific percentile value, traders can identify trends early and act accordingly.
2. Risk Management: The indicator helps traders better understand volatility and price distribution, leading to more effective risk management.
3. Trading Strategies: It can be used as part of trading strategies to identify entry and exit points based on statistical distributions.
4. Simplicity and Efficiency: As the indicator operates without the use of arrays, it is more efficient and simpler to implement, reducing computation time and improving the performance of the trading platform.
Scientific Explanation of Percentile Nearest Rank:
The Percentile Nearest Rank method is a statistical technique used to determine the relative standing of a value within a data set. For a given dataset of length \( n \) and a desired percentile \( p \), the method follows these steps:
1. Index Calculation: The index corresponding to the desired percentile is calculated using the formula:
index = ( p / 100 n ) -1
where "ceiling" denotes rounding up to the nearest integer.
2. Value Sorting: The values in the dataset are conceptually sorted from smallest to largest.
3. Count Comparison: For each value in the dataset, count how many values are smaller. When the count matches the calculated index, the value at this position is the percentile value.
4. Result Assignment: The value identified as the percentile value is then used for further analysis or plotting.
This method is advantageous for trading because it provides a non-parametric way to understand price distributions, making it less sensitive to outliers and more robust in volatile markets.
Scientific Context and Utility:
- Statistical Robustness: Unlike mean and median, the percentile provides a robust measure of the data distribution, less influenced by extreme values. This robustness is crucial for traders dealing with volatile markets.
- Non-Parametric Analysis: Percentiles do not assume any underlying distribution (e.g., normal distribution) of the data, making the analysis more flexible and broadly applicable.
- Quantitative Decision Making: By using percentiles, traders can make data-driven decisions based on the relative standing of current prices within historical data, enhancing the objectivity of their strategies.
- Efficiency Without Arrays: Avoiding the use of arrays reduces memory consumption and computational overhead, making the indicator more suitable for real-time applications and large datasets. This improves overall performance and responsiveness on trading platforms, which is crucial for making timely trading decisions.
In summary, the "Percentile Nearest Rank Without Arrays " indicator is a powerful tool for traders seeking to integrate statistical price distribution insights into their trading strategies. It provides a robust, non-parametric, and visually intuitive method to analyze market trends and volatility, while offering enhanced computational efficiency by avoiding the use of arrays.
MTF WaveTrend [CryptoSea]The MTF WaveTrend Indicator is a sophisticated tool designed to enhance market analysis through multi-timeframe WaveTrend calculations. This tool is built for traders who seek to identify market momentum and potential reversals with higher accuracy.
In the example below, we can see all the choosen timeframes agree on bearish momentum.
Key Features
Multi-Timeframe WaveTrend Analysis: Tracks WaveTrend values across multiple timeframes to provide a comprehensive view of market momentum.
Customizable Colour Rules: Offers three different colour rules (Traditional, WT1 0 Rule, WT1 & WT2 0 Rule) to suit various trading strategies.
Timeframe Visibility Control: Allows users to enable or disable specific timeframes, providing flexibility in analysis.
Clear Visual Indicators: Uses color-coded squares and labels to clearly display WaveTrend status across different timeframes.
Candle Colouring Option: Includes a setting for neutral candle coloring to enhance chart readability.
This example shows what can happen when all timeframes start alligning with eachother.
How it Works
WaveTrend Calculation: Computes the WaveTrend oscillator by applying a series of exponential moving averages and scaling calculations.
Multi-Timeframe Data Aggregation: Utilizes the `request.security` function to gather and display WaveTrend values from various timeframes without repainting issues.
Conditional Plotting: Displays visual cues only when higher timeframes align with the selected timeframe, ensuring relevant and reliable signals.
Dynamic Colour Rules: Adjusts the indicator colors based on the chosen rule, whether it's a traditional crossover, WT1 crossing zero, or both WT1 & WT2 crossing zero.
Traditional: Colors are determined by the relationship between WT1 and WT2. If WT1 is greater than WT2, it is bullish (bullColour), otherwise bearish (bearColour).
WT1 0 Rule: Colors are based on whether WT1 is above or below zero. WT1 above zero is bullish (bullColour), below zero is bearish (bearColour).
WT1 & WT2 0 Rule: A more complex rule where both WT1 and WT2 need to be above zero for a bullish signal (bullColour) or both below zero for a bearish signal (bearColour). If WT1 and WT2 are not in agreement, a neutral color (neutralColour) is displayed.
This indicator will make sure that the lowest timeframe you can see data from will be the timeframe you are on. This is to avoid false signals as you cannot display 3 x 5 minute candles whilst looking at the 15 minute candle.
Application
Strategic Decision-Making: Assists traders in making informed decisions by providing detailed analysis of WaveTrend movements across different timeframes.
Trend Confirmation: Reinforces trading strategies by confirming potential reversals with multi-timeframe WaveTrend analysis.
Customized Analysis: Adapts to various trading styles with extensive input settings that control the display and sensitivity of WaveTrend data.
The MTF WaveTrend Indicator by is an invaluable addition to a trader's toolkit, offering depth and precision in market trend analysis to navigate complex market conditions effectively.
RSI Sector analysis
Screening tool that produces a table with the various sectors and their RSI values. The values are shown in 3 rows, each with a user-defined length, and can be averaged out and displayed as a single value. The chart is color coded as well. Each ETF representing a sector can be looked at individually, with the top holdings in each preprogrammed, but users can define their own if they wish. The left most ticker is the "benchmark"; SPY is the benchmark for the various sectors, and the ETF is the benchmark for the tickers within.
Symbols are color coded: light blue text indicates that a symbol has greater RSI values in all three timeframes than the benchmark (the leftmost symbol). Orange text indicates that a symbol has a lower RSI value for all three timeframes. In the first row, light blue text indicates the largest RSI increase from the third row to the first row. Orange text indicates the largest RSI decrease from the third row to the first row.
A blue highlight indicates that the value is the highest among the tickers, excluding the benchmark, and an orange highlight indicates that the value is the lowest among the tickers, also excluding the benchmark. A blue highlight on the ticker indicates that it has the highest average value of the 3 rows, and a orange highlight on the ticker indicates that it has the lowest average value of the 3 rows.
HTF Dynamic EMA Smoothing Indicator [CHE] with Kernel SelectionThe Dynamic EMA Smoothing Indicator with Kernel Selection is a powerful Pine Script indicator for TradingView designed to smooth moving averages and identify market trends more clearly. Here is a detailed description of its functionalities and settings:
Main Functions:
1. Time Period Display:
- Option to show or hide an info box displaying the current time period.
- Customizable info box: Users can adjust the size, position, and colors of the info box to suit their preferences.
2. Timeframe Type Selection:
- Auto Timeframe: Automatically calculates the best timeframe based on the current resolution.
- Multiplier: Allows using an alternate timeframe as a multiple of the current resolution.
- Manual Resolution: Users can manually set a specific timeframe.
3. Colors:
- Custom colors for various graphical elements, including EMA lines and signals.
4. Basic Settings:
- EMA and Signal Periods: Defines the periods for the exponential moving averages (EMA) and signal lines.
- Smoothing Length and Kernel Type: Allows selecting the smoothing length and the type of kernel used for weighting the EMAs.
- ATR Multiplier: Defines the multiplier for the ATR (Average True Range) to identify relevant price ranges.
5. EMA Calculations:
- The indicator calculates a weighted EMA using several methods like Linear, Exponential, Epanechnikov, Triangular, and Cosine kernels.
- Smoothing is achieved by adding and removing values in a float array that stores the EMA values.
6. Plotting EMA and Signal Lines:
- The indicator plots the smoothed EMA and signal lines on the chart. The line colors change according to the trend direction (green for uptrend, red for downtrend).
7. Trading Signals:
- Long Signals: An upward arrow is displayed when the smoothed EMA indicates an uptrend.
- Short Signals: A downward arrow is displayed when the smoothed EMA indicates a downtrend.
- Alert Conditions: Alerts are triggered when long or short signals are detected.
8. ATR Bands:
- The indicator shows upper and lower ATR bands to identify potential support and resistance zones.
9. Time Period Display on Chart:
- A table is used to display the selected time period on the chart when the corresponding option is enabled.
This indicator offers extensive customization and allows traders to conduct complex market analyses using smoothed EMAs and custom timeframes. The integration of various kernels for smoothing makes it a versatile tool adaptable to different trading strategies.
Prometheus Polarized Fractal Efficiency (PFE)This indicator uses market data to calculate Polarized Fractal Efficiency (PFE) on an asset, so traders can have a better idea of which direction it may go.
Users can control the lookback length for the fractal calculation, the lookback length for the Exponential Moving Average (EMA), and whether or not to display lines at the -50 and 50 level, or -25 and 25 level.
Polarized Fractal Efficiency:
The Polarized Fractal Efficiency (PFE) indicator is a value between -100 and 100 with 0 as a midpoint.
A PFE above 0 indicates the asset may trend higher, a PFE below 0 indicates the asset may trend lower.
There are many ways to trade with PFE, the intuitive trend riding as described above, or reversals.
Even when the PFE is above 0, if it gets high enough, it may also be an indication of a reversal. A PFE of 90 - 100, or -100 - -90, may indicate price is ready to revert the other direction. Furthermore, traders already in a position may look to breaks of other levels to be their take profit or stop out spot.
Calculation:
Pi = 100 x (Price - Price )2 + N2 / Summation, j= 0, to N-2 (Price - Price )2 + 1
If Close < Close Pi = -Pi
PFEi = EMA(Pi, M)
Where:
N = period of indicator
M = smoothing period
Citation: www.investopedia.com
Scenarios:
Inputs are (9, 5) and every display option is on.
Trend example
Step 1: A short trade appears as PFE crosses below -25. We reach a safe take profit as PFE crosses below -50. Traders can use these levels to exit as well as enter.
Step 2: On the cross above 25 there is a safe long. As the PFE value breaks 0 a safe, early take profit could be appropriate for this trade. No guarantee we would see 50.
Step 3: Long scenario at break of 25, straight to 50. Simple, straightforward setup.
Step 4: This long results in a stop loss. Once again entry as PFE crosses 25, but as we cross the 0 line it is for a loss.
Step 5: The last trade in this example is reminiscent of step 3. This is a short trade entry at break of 25 and exit at break of 50.
Traders have liberty to use the PFE value to determine spots to enter and exit trades, long or short. 25 and 50 were chosen arbitrarily, values like 10 and 60 may work as well, we encourage traders to use their own discretion along with tools.
Reversal example
Step 1: PFE is around -100, crossing below it at one point! Strong zone for a potential reversal.
Step 2: PFE crosses above 25 adding conviction.
Step 3: Option to exit at 70.
Step 4: Option to exit at 90.
There is no “one size fits all method”, this approach may be more intuitive for some users and is just as feasible as the first.
Longer trend example
Step 1: Using -50 and 50 this time instead of -25 and 25 to be safer on our entries we see a short here. Was a good entry and as the value gets closer to -70 we can safely close.
Step 2: On this candle we see a long for the break of 50. On the next candle we break the 0 line, but because of our safe entry at 50, we could hold this and only stop out at a break of -25. We get close but stay in it and close at 70.
Step 3: Break of 50 for a long once again. This time the break of 0 line occurs as we are in profit, not letting a green trade go red is a golden rule of trading, so an early exit here.
Step 4: Same at step 2, break of 50 to long and stay in it, not stopping out at break of 0 line. The PFE value eventually reaches 70 and there is a good exit.
Quicker Reversal example
Step 1: Notice a close with PFE below -90, enter long for the reversal. Then close for profit when the PFE crosses above 70.
Step 2: When the PFE breaks above 90 we have a short entry. Like the long closing it when it crosses below -70.
Step 3: This step is the same setup as step 2. As PFE breaks above 90 we have a short entry. Closing it when it crosses below -70.
Recap:
Described above are 4 different examples with many different trades. Both trend and reversal trades. The PFE value is an indicator that can be used by traders in many different ways and Prometheus encourages traders to use their own discretion along with tools and not follow indicators blindly.
Options:
Users can control the input for the lookback of the indicator. The default is 9.
The smoothing factor for the EMA is also changeable, default is 5.
Users have options to display lines at -50, -25, 25, and 50.
New day started with DSTNew Day Started with DST Indicator
Description:
The "New Day Started with DST" indicator is designed for intraday charts and highlights the first bar of each new trading day, accounting for Germany's timezone and daylight saving time (DST) adjustments. This is particularly useful for traders who follow the German market or need precise day start indications based on Central European Time (CET) and Central European Summer Time (CEST).
Features:
- Timezone Adjustment: Automatically adjusts the time to CET (UTC+1) during standard time and CEST (UTC+2) during daylight saving time.
- Daylight Saving Time (DST) Handling: Correctly identifies the start and end of DST based on the last Sunday in March and October.
- New Day Highlight: Highlights the first bar of each new day, allowing traders to easily identify the start of a new trading day.
How It Works:
- Timezone Calculation: The script calculates the current time in Germany by adding the appropriate timezone offset to the UTC time.
- DST Rules: The script manually checks the conditions to determine if the current date falls within the DST period.
- New Day Detection: By checking the hour and minute of the corrected German time, the script determines if a new day has started and highlights the first bar accordingly.
Benefits:
- Enhanced Accuracy: Ensures that the start of a new day is accurately reflected according to German trading hours, considering both CET and CEST.
- Visual Aid: Provides a clear visual indication of the start of a new trading day, improving chart readability and trading precision.
- Customizable: Can be easily modified to adjust for other timezones and DST rules if needed.
Usage:
Apply this indicator to your intraday charts to automatically highlight the first bar of each new trading day, taking into account the timezone and DST adjustments for Germany. This tool is essential for traders operating in or tracking the German market, offering a reliable and precise method to monitor daily trading activity.
Example:
! (URL-to-your-screenshot)
This indicator ensures that you never miss the start of a new trading day, helping you to make timely and informed trading decisions.
---
How the Script Works:
1. Timezone Offset Calculation:
- The script begins by setting the base offset to 1 hour (CET is UTC+1).
- It initializes the DST offset to 0.
2. Determining the Current Month and Day:
- It retrieves the current month and day of the month from the `time` variable.
3. Checking DST Conditions:
- For months between April and September (inclusive), the DST offset is set to 1 hour (CEST is UTC+2).
- For March, it checks if the current date is after the last Sunday of March and if the time is past 2:00 AM to determine if DST should start.
- For October, it checks if the current date is before the last Sunday of October and if the time is before 2:00 AM to determine if DST should end.
4. Adjusting the Time for Germany:
- The script calculates the corrected German time by adding the base offset and DST offset to the UTC time.
5. Detecting the Start of a New Day:
- It checks if the hour and minute of the corrected German time are both zero (00:00), indicating the start of a new day.
6. Highlighting the First Bar:
- If the script detects a new day, it highlights the first bar of the new day with a green background color.
This approach ensures that the script accurately reflects the start of a new trading day according to German trading hours, including adjustments for daylight saving time.
Daye's Quarterly TheoryDaye's Quarterly Theory Indicator
Description
The Daye's Quarterly Theory Indicator divides trading time into smaller units to help traders identify potential accumulation, manipulation, distribution, and reversal/continuation phases within a day. It applies these time divisions to your charts, offering visual guidance aligned with ICT's PO3 concept:
Accumulation (A): The phase where positions are accumulated.
Manipulation (M): The phase where the market moves against the prevailing trend to trap traders.
Distribution (D): The phase where accumulated positions are distributed.
Reversal/Continuation (X): The phase indicating either a reversal or continuation of the trend.
This indicator breaks down time into quarters at different levels:
Daily Quarters:
Q1: 18:00 - 00:00 (Asia)
Q2: 00:00 - 06:00 (London)
Q3: 06:00 - 12:00 (NY AM)
Q4: 12:00 - 18:00 (NY PM)
90-Minute Quarters:
Q1: 18:00 - 19:30
Q2: 19:30 - 21:00
Q3: 21:00 - 22:30
Q4: 22:30 - 00:00
Micro Quarters (22.5 minutes) (Displayed on 7-minute TF or lower):
Q1: 18:00 - 18:22:30
Q2: 18:22:30 - 18:45
Q3: 18:45 - 19:07:30
Q4: 19:07:30 - 19:30
Features
Time Box Visualization: Highlights different quarters of the trading day to help visualize market phases.
Customizable Colors: Allows users to set different colors for daily, 90-minute, and micro quarters.
Flexible Settings: Designed to work out-of-the-box on both light and dark background charts.
ICT PO3 Alignment: Helps traders align their strategies with ICT's Accumulation, Manipulation, Distribution, and Reversal/Continuation phases.
Usage
Apply this indicator to your NQ1! or ES1! charts and observe the confluence with ICT's macro times. Use it to predict potential market phases and optimize your trading strategy by buying after manipulation down or selling after manipulation up.
Note: The indicator's display may vary based on the timeframe viewed and broker feeds. Back-test and research for best results on your preferred assets.
Strong Support and Resistance with EMAs @viniciushadek
### Strategy for Using Continuity Points with 20 and 9 Period Exponential Moving Averages, and Support and Resistance
This strategy involves using two exponential moving averages (EMA) - one with a 20-period and another with a 9-period - along with identifying support and resistance levels on the chart. Combining these tools can help determine trend continuation points and potential entry and exit points in market operations.
### 1. Setting Up the Exponential Moving Averages
- **20-Period EMA**: This moving average provides a medium-term trend view. It helps smooth out price fluctuations and identify the overall market direction.
- **9-Period EMA**: This moving average is more sensitive and reacts more quickly to price changes, providing short-term signals.
### 2. Identifying Support and Resistance
- **Support**: Price levels where demand is strong enough to prevent the price from falling further. These levels are identified based on previous lows.
- **Resistance**: Price levels where supply is strong enough to prevent the price from rising further. These levels are identified based on previous highs.
### 3. Continuity Points
The strategy focuses on identifying trend continuation points using the interaction between the EMAs and the support and resistance levels.
### 4. Buy Signals
- When the 9-period EMA crosses above the 20-period EMA.
- Confirm the entry if the price is near a support level or breaking through a resistance level.
### 5. Sell Signals
- When the 9-period EMA crosses below the 20-period EMA.
- Confirm the exit if the price is near a resistance level or breaking through a support level.
### 6. Risk Management
- Use appropriate stops below identified supports for buy operations.
- Use appropriate stops above identified resistances for sell operations.
### 7. Validating the Trend
- Check if the trend is validated by other technical indicators, such as the Relative Strength Index (RSI) or Volume.
### Conclusion
This strategy uses the combination of exponential moving averages and support and resistance levels to identify continuity points in the market trend. It is crucial to confirm the signals with other technical analysis tools and maintain proper risk management to maximize results and minimize losses.
Implementing this approach can provide a clearer view of market movements and help make more informed trading decisions.
Prometheus Analytics Hurst ExponentThis indicator uses market data to calculate the Hurst Exponent so traders can have knowledge of the long memory of the asset.
Users can control the lookback length for the H value (Hurst Exponent), lookback length for the SMA (Simple Moving Average) of the Hurst Exponent, to show either, and what to calculate the H value and SMA on.
Hurst Exponent:
The Hurst Exponent is a value between 0 and 1 with 0.5 as a midline.
An H value(Hurst Exponent) above 0.5 indicates a trending market, and a market that should have larger, longer moves.
An H value below 0.5 indicates a mean reverting market, and a market that should have smaller, shorter moves.
An H value of0.5 indicates a random walk. This would mean the price would follow a Brownian Motion model and future prices would be independent from past prices.
Just because the H value is above 0.5 does not indicate that there should be an UP trend, just as a value below 0.5 does not indicate a DOWN trend. It indicates that there should be a trend, up or down.
Scenarios:
An intuitive way to use the Hurst Exponent is as an asset is trending in whatever direction, as the H value crosses below 0.5 it indicates a reversal. It indicates that what was happening before isn’t impacting what is happening now as much.
Steps explained from picture:
Step 1: Strong uptrend is identified with the asset moving up aggressively with H above 0.5.
Step 2: The H value crosses below 0.5 and prices stay elevated.
Step 3: Price reverts back down as the H value stays below 0.5
Just because the H value is above 0.5 doesn’t mean the asset has to be uptrending. In this example we see the asset fall as the H value is above 0.5. Not only that, but every time it crosses below 0.5, the asset takes a breather on the way down
Step 1: As the H value crosses above 0.5, we can expect trends to appear in the asset.
Step 2: After the trend switches to down, we only see a breather and some chop after the H value crosses back below 0.5.
Step 3: Once The H value crosses back over we see the downtrend continue and new lows be made.
Step 4: We see it once again, simply the area of chop is bigger. We don’t see a higher high, breaking the overall downtrend, but once the H value crosses over again the downturn continues and we see a lower low.
It may occur when no strong trend is made in either direction. The H value above 0.5 does indeed sometimes correlate with an uptrend sometimes.
Step 1: After the strong downtrend we see a break below 0.5 with some consolidation.
Step 2: No clear big move on the asset or H value.
Step 3: H value above 0.5 leads to a break of highs and a new uptrend.
Users have the option to decide what to calculate the H value on. Close is the default, or dollar return per bar are the options. Dollar return per bar and offer an H value that may give a better indication of when price moves will be small and sporadic.
Using dollar move per bar.
Step 1: H value cross above 0.5, we see large candles and fast moves.
Step 2: H value crosses below 0.5, the candles immediately following are shorter. The big red candles come right before the cross back above.
Step 3: H value cross back above 0.5, after some chop, large move down.
Similar story
Step 1: H value above 0.5, big trends either direction
Step 2: After the H value crosses below, the moves are short and choppy.
Settings:
Options to show or remove either the H value or it’s SMA.
Options to adjust the period uses, default is (32, 16)
Master Accumulation Weekly Buy SignalsMaster Accumulation Weekly Buy Signals
The Master Accumulation Weekly Buy Signals indicator is designed to help traders identify potential buy opportunities based on the accumulation and distribution of volume, with a primary focus on weekly timeframes. This indicator combines the On Balance Volume (OBV) and the Accumulation/Distribution (AD) indicators to generate buy signals when both metrics show a decline.
Key Features:
Percentage Change Calculation: Calculates the percentage change in OBV and AD over a specified length tailored to weekly timeframes.
Timeframe Adaptability: While optimized for weekly timeframes, the indicator can also adjust to daily and monthly charts.
Volume Validation: Ensures that volume data is available and valid for accurate calculations.
Buy Signals: Generates buy signals when both OBV and AD percentage changes are negative, indicating potential accumulation by informed traders.
Visual Alerts: Plots buy signal triangles below the price bars on the main chart for easy identification.
How It Works:
On Balance Volume (OBV): Tracks the cumulative volume, considering the direction of price changes, and calculates the percentage change over the specified period, primarily for weekly analysis.
Accumulation/Distribution (AD): Measures the flow of volume into or out of a security, considering the relationship between the closing price and the high-low range, and calculates the percentage change over the specified period, primarily for weekly analysis.
Buy Signal Generation: A buy signal is generated when both OBV and AD show a negative percentage change, suggesting a potential buying opportunity.
How to Use:
Apply the indicator to your chart and select the weekly timeframe for optimal performance.
Look for buy signal triangles that appear below the price bars on the main chart.
Use the buy signals as part of your broader trading strategy, confirming them with other technical analysis tools and indicators.
Important Note:
This indicator is a tool to assist in identifying potential buy signals based on volume accumulation patterns. It is primarily designed for weekly timeframes and should not be used as a standalone trading strategy. Always perform comprehensive analysis and consider risk management practices before making any trading decisions.
This description highlights the indicator's primary focus on weekly timeframes while providing comprehensive information about its features and usage.
THIS IS TEST ONLY*******
Rolling Correlation with Bitcoin V1.1 [ADRIDEM]Overview
The Rolling Correlation with Bitcoin script is designed to offer a comprehensive view of the correlation between the selected ticker and Bitcoin. This script helps investors understand the relationship between the performance of the current ticker and Bitcoin over a rolling period, providing insights into their interconnected behavior. Below is a detailed presentation of the script and its unique features.
Unique Features of the New Script
Bitcoin Comparison : Allows users to compare the correlation of the current ticker with Bitcoin, providing an analysis of their relationship.
Customizable Rolling Window : Enables users to set the length for the rolling window, adapting to different market conditions and timeframes. The default value is 252 bars, which approximates one year of trading days, but it can be adjusted as needed.
Smoothing Option : Includes an option to apply a smoothing simple moving average (SMA) to the correlation coefficient, helping to reduce noise and highlight trends. The smoothing length is customizable, with a default value of 4 bars.
Visual Indicators : Plots the smoothed correlation coefficient between the current ticker and Bitcoin, with distinct colors for easy interpretation. Additionally, horizontal lines help identify key levels of correlation.
Dynamic Background Color : Adds dynamic background colors to highlight areas of strong positive and negative correlations, enhancing visual clarity.
Originality and Usefulness
This script uniquely combines the analysis of rolling correlation for a current ticker with Bitcoin, providing a comparative view of their relationship. The inclusion of a customizable rolling window and smoothing option enhances its adaptability and usefulness in various market conditions.
Signal Description
The script includes several features that highlight potential insights into the correlation between the assets:
Rolling Correlation with Bitcoin : Plotted as a red line, this represents the smoothed rolling correlation coefficient between the current ticker and Bitcoin.
Horizontal Lines and Background Color : Lines at -0.5, 0, and 0.5 help to quickly identify regions of strong negative, weak, and strong positive correlations.
These features assist in identifying the strength and direction of the relationship between the current ticker and Bitcoin.
Detailed Description
Input Variables
Length for Rolling Window (`length`) : Defines the range for calculating the rolling correlation coefficient. Default is 252.
Smoothing Length (`smoothing_length`) : The number of periods for the smoothing SMA. Default is 4.
Bitcoin Ticker (`bitcoin_ticker`) : The ticker symbol for Bitcoin. Default is "BINANCE:BTCUSDT".
Functionality
Correlation Calculation : The script calculates the daily returns for both Bitcoin and the current ticker and computes their rolling correlation coefficient.
```pine
bitcoin_close = request.security(bitcoin_ticker, timeframe.period, close)
bitcoin_dailyReturn = ta.change(bitcoin_close) / bitcoin_close
current_dailyReturn = ta.change(close) / close
rolling_correlation = ta.correlation(current_dailyReturn, bitcoin_dailyReturn, length)
```
Smoothing : A simple moving average is applied to the rolling correlation coefficient to smooth the data.
```pine
smoothed_correlation = ta.sma(rolling_correlation, smoothing_length)
```
Plotting : The script plots the smoothed rolling correlation coefficient and includes horizontal lines for key levels.
```pine
plot(smoothed_correlation, title="Rolling Correlation with Bitcoin", color=color.rgb(255, 82, 82, 50), linewidth=2)
h_neg1 = hline(-1, "-1 Line", color=color.gray)
h_neg05 = hline(-0.5, "-0.5 Line", color=color.red)
h0 = hline(0, "Zero Line", color=color.gray)
h_pos05 = hline(0.5, "0.5 Line", color=color.green)
h1 = hline(1, "1 Line", color=color.gray)
fill(h_neg1, h_neg05, color=color.rgb(255, 0, 0, 90), title="Strong Negative Correlation Background")
fill(h_neg05, h0, color=color.rgb(255, 165, 0, 90), title="Weak Negative Correlation Background")
fill(h0, h_pos05, color=color.rgb(255, 255, 0, 90), title="Weak Positive Correlation Background")
fill(h_pos05, h1, color=color.rgb(0, 255, 0, 90), title="Strong Positive Correlation Background")
```
How to Use
Configuring Inputs : Adjust the rolling window length and smoothing length as needed. Ensure the Bitcoin ticker is set to the desired asset for comparison.
Interpreting the Indicator : Use the plotted correlation coefficient and horizontal lines to assess the strength and direction of the relationship between the current ticker and Bitcoin.
Signal Confirmation : Look for periods of strong positive or negative correlation to identify potential co-movements or divergences. The background colors help to highlight these key levels.
This script provides a detailed comparative view of the correlation between the current ticker and Bitcoin, aiding in more informed decision-making by highlighting the strength and direction of their relationship.
