100 Point Scaled EMA100 Point Scaled EMA is a distinctive indicator that standardizes trend analysis by normalizing price data. Here’s a breakdown of its technical features:
Normalized Exponential Moving Averages (EMAs):
Dual EMAs: Configurable lengths (typically 9 and 21) are applied to calculate EMAs.
Scaling Mechanism: The EMAs are normalized to a fixed 0–100 range using the highest and lowest prices over the last 100 bars, enabling consistent analysis regardless of market volatility.
Integrated Relative Strength Index (RSI):
A 14-period RSI is incorporated to provide additional momentum and overbought/oversold insights.
Dynamic Visual Cues:
Gradient Fills: Visual gradients highlight overbought and oversold regions, enhancing the readability of trend shifts.
Crossover Signals:
The script detects EMA crossovers with specific conditions—crossover events occurring below 25 and above 75—to mark potential trade setups.
This technical approach makes the 100 Point Scaled EMA a powerful tool for traders, offering a simple unique and standardized perspective on market trends.
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Jumbalika BandsThis indicator is designed using several common technical analysis tools: Bollinger Bands, Exponential Moving Averages (EMAs), and the Parabolic SAR. I'll walk you through each section to explain how it works and how you can use it:
1. Bollinger Bands
Bollinger Bands are used to measure volatility and overbought/oversold conditions. It consists of three lines:
Basis (Middle Line): A simple moving average (SMA) of the price over a defined period (in this case, 20 periods).
Upper Band: The basis plus a certain number of standard deviations. It represents the upper boundary of expected price movement.
Lower Band: The basis minus the same number of standard deviations. It represents the lower boundary of expected price movement.
Interpretation:
Overbought: If the price moves above the upper band, it could signal that the asset is overbought.
Oversold: If the price moves below the lower band, it could signal that the asset is oversold.
Volatility: A wider band indicates higher volatility, and a narrower band indicates lower volatility.
2. Exponential Moving Averages (EMAs)
The indicator plots four different EMAs:
9-period EMA: This is a short-term trend indicator.
20-period EMA on Close: This is another medium-term trend indicator, based on the close price.
20-period EMA on High: A variation of the 20-period EMA, but based on the high prices.
20-period EMA on Low: A variation of the 20-period EMA, but based on the low prices.
Interpretation:
9 EMA: A faster-moving average that responds quicker to price changes. It can be used to identify short-term trends.
20 EMA: A slower-moving average that reacts more gradually to price changes. It helps identify the broader trend.
High/Low EMAs: These give additional insights into the extremes of price action, which can help identify possible support or resistance levels.
Trading signals (common usage):
Crossover: When a shorter EMA (like the 9 EMA) crosses above a longer EMA (like the 20 EMA), it could be a bullish signal. When it crosses below, it could be a bearish signal.
3. Parabolic SAR
The Parabolic SAR is a trend-following indicator that is used to identify potential price reversals. The Parabolic SAR is plotted as a series of dots either above or below the price, depending on the trend:
Below the price: The trend is up (bullish).
Above the price: The trend is down (bearish)
4. Background Coloring (Optional)
The background will change color when the price crosses the Bollinger Bands:
Green background when the price is above the upper Bollinger Band.
Red background when the price is below the lower Bollinger Band.
Adjust the values for Bollinger Bands, EMAs, and Parabolic SAR directly in the indicator settings to suit your trading preferences.
Bollinger Bands: If the price is above the upper band, it might indicate an overbought condition, while if it's below the lower band, it might indicate an oversold condition.
EMAs: The 9 EMA is often used to track short-term trends, while the 20-period EMAs (on the close, high, and low) help analyze the broader market trend.
Parabolic SAR: The Parabolic SAR is often used to identify trend reversals. If the SAR is below the price, the trend is up, and if it's above the price, the trend is down.
Background Color: The background coloring helps visually highlight potential market conditions when the price breaks out of the Bollinger Bands.
Example Use Case:
Decide the trend based on the parabolic SAR, when the bar touches the upper or lower Bollinger take a short or long position based on the price action using EMAs.
JMA Quantum Edge: Adaptive Precision Trading System JMA Quantum Edge: Adaptive Precision Trading System - Enhanced Visuals & Risk Management
Get ready to experience a groundbreaking trading strategy that adapts in real-time to market conditions! This powerful, open-source script combines advanced technical analysis with state-of-the-art risk management tools, designed to give you the edge you need in today's dynamic markets.
What It Does:
Adaptive JMA Indicator:
Utilizes a custom Jurik Moving Average (JMA) that adjusts its sensitivity based on market volatility, ensuring you get precise signals even in the most fluctuating environments.
Dynamic Risk Management:
Features built-in support for partial exits (scaling out) to secure profits, along with an optional Kelly Criterion-based position sizing that tailors your exposure based on historical performance metrics.
Robust Error Handling:
Incorporates market condition filters—like minimum volume and maximum allowed gap percentage—to ensure trades are only executed under favorable conditions.
Vivid Visual Enhancements:
Enjoy an animated background that reflects market momentum, dynamic pivot markers, and clearly drawn trend channels. Plus, interactive tables provide real-time performance analytics and detailed error metrics.
Fully Customizable:
With a comprehensive set of inputs, you can easily tailor the strategy to your personal trading style and market preferences. Adjust everything from JMA parameters to refresh intervals for tables and labels!
How to Use It:
Add the Script:
Copy and paste the script into the Pine Script Editor on TradingView and click “Add to Chart.”
Configure Your Settings:
Customize your risk management (capital, commission, position sizing, partial exits, etc.) and tweak the JMA settings to match your preferred trading style. Use the extensive input panel to adjust visuals, alerts, and more.
Backtest & Optimize:
Run the strategy in the Strategy Tester to analyze its historical performance. Monitor real-time analytics and error metrics via the interactive tables, and fine-tune your parameters for optimal performance.
Go Live with Confidence:
Once you're satisfied with the backtest results, use the generated signals for live trading, and let the system help you stay ahead in fast-paced markets!
How to use the imputs:
This cutting-edge strategy is designed to adapt to changing market conditions and offers you complete control over your trading parameters. Here’s a breakdown of what each group of inputs does and how you should use them:
Risk Management & Trade Settings
Recalculate on Every Tick:
What it does: When enabled, the strategy recalculates on every price update.
Recommendation: Leave it true for fast charts.
Initial Capital:
What it does: Sets your starting capital for backtesting, which influences position sizing and performance metrics.
Recommendation: Start with $10,000 (or adjust according to your trading capital).
Commission (%):
What it does: Simulates the cost per trade.
Recommendation: Use a realistic rate (e.g., 0.04%).
Position Size & Quantity Type:
What they do: Define how large each trade will be. Choose between a fixed unit amount or a percentage of equity.
Recommendation: For beginners, the default fixed value is a good start. Experiment later with percentage-based sizing if needed.
Order Comment:
What it does: Adds a label to your orders for easier tracking.
Allow Reverse Orders:
What it does: If disabled, the strategy will close opposing positions before entering a new trade, reducing conflicts.
Enable Dynamic Position Sizing:
What it does: Adjusts trade size based on current volatility.
Recommendation: Beginners may start with this disabled until they understand basic sizing.
Partial Exit Inputs:
What they do:
Enable Partial Exits: When turned on, you can scale out of your position to lock in profits.
Partial Exit Profit (%): The profit percentage that triggers a partial exit.
Partial Exit Percentage: The percentage of your current position to exit. Recommendation: Use defaults (e.g., 5% profit, 50% exit) to secure profits gradually.
Kelly Criterion Option:
What it does: When enabled, adjusts your position sizing using historical performance (win rate and profit factor).
Recommendation: Beginners might leave this disabled until comfortable with backtest performance metrics.
Market Condition Filters:
What they do:
Minimum Volume: Ensures trades occur only when there’s sufficient market activity.
Maximum Gap (%): Prevents trading if there’s an unusually large gap between the previous close and current open. Recommendation: Defaults work well for most markets. If trades seem erratic, consider tightening these limits.
JMA Settings
Price Source:
What it does: The input series for the JMA calculation, typically set to the closing price.
JMA Length:
What it does: Controls the smoothing period of the JMA. Lower values are more sensitive; higher values smooth out the noise. Recommendation: Start with 21.
JMA Phase & Power:
What they do: Adjust how responsive the JMA is. Phase controls timing; power adjusts the intensity. Recommendation: Default settings (63 phase and 3 power) are a balanced starting point.
Visual Settings & Style
Show JMA Line, Pivot Lines, and Pivot Labels:
What they do: Toggle visual elements on your chart for easier signal identification.
Pivot History Count:
What it does: Limits how many historical pivot markers are displayed.
Color Settings (Up/Down Neon Colors):
What they do: Set the visual cues for buy and sell signals.
Pivot Marker & Line Style:
What they do: Choose the style and thickness of your pivot markers and lines.
Show Stats Panel:
What it does: Displays real-time performance and error metrics.
Dynamic Background & Visual Enhancements
Animate Background:
What it does: Changes the background color based on market momentum.
Show Trend Channels & Volume Zones:
What they do: Draw trend channels and highlight areas of high volatility/volume.
Show Data-Rich Labels:
What it does: Displays key metrics like volume, error percentage, and momentum on the chart.
High Volatility Threshold:
What it does: Determines the multiplier for when the chart background should change due to high volatility.
Multi-Timeframe Settings
Higher Timeframe:
What it does: Uses a higher timeframe’s JMA for trend confirmation. Recommendation: Use Daily ('D') or Weekly ('W') for broader trend analysis.
Show HTF Trend Zone & Opacity:
What they do: Display a visual zone from the higher timeframe to help confirm trends.
6. Trailing Stop Settings
Trailing Stop ATR Factor & Offset Multiplier:
What they do: Calculate trailing stops based on the Average True Range (ATR), adjusting stop distances dynamically. Recommendation: Default settings are a good balance but can be fine-tuned based on asset volatility.
Alerts & Notifications
Alerts on Pivot Formation & JMA Crossover:
What they do: Notify you when key events occur.
Dynamic Power Threshold:
What it does: Sets the sensitivity for dynamic alerts.
8. Static Stop Loss / Take Profit
Static Stop Loss (%) & Take Profit (%):
What they do: Allow you to set fixed stop loss or take profit levels. Recommendation: Leave them at 0 to disable if you prefer dynamic risk management, or set them if you have strict risk/reward preferences.
Advanced Settings
ATR Length:
What it does: Determines the period for ATR calculation, impacting trailing stop sensitivity. Recommendation: Start with 14.
Optimization Feedback & Enhanced Error Analysis
Error Metric Length & Error Threshold (%):
What they do: Calculate error metrics (like average error, skewness, and kurtosis) to help you fine-tune the JMA. Recommendation: Use the defaults and adjust if the error metrics seem off during backtesting.
UI - User-Driven Tweaking & Table Customization
Parameter Tweaker Panel, Debug/Performance Table Settings:
What they do: Provide interactive tables that display real-time performance, error metrics, and allow you to monitor strategy parameters.
Refresh Frequency Options (Table & Label Refresh Intervals):
What they do: Set how often the tables and labels update.
Recommendation: Start with an interval of 1 bar; increase it if your chart is too busy.
Important for Beginners:
Default Settings:
All default values have been chosen for balanced performance across different markets. If you ever experience unexpected behavior, start by resetting the inputs to their defaults.
Step-by-Step Adjustments:
Experiment by changing one setting at a time while observing how the strategy’s signals and performance metrics change. This will help you understand the impact of each parameter.
Resetting to Defaults:
If things seem off or you’re not getting the expected results, you can always reset the indicator. Either reload the script or use the “Reset Inputs” option (if available) to revert to the default settings.
Jump in, experiment, and enjoy the power of adaptive precision trading. This strategy is built to grow with your skills—have fun exploring and refining your trading edge!
Happy trading!
RoGr75 - EMA Cross Signal with Buffer and Variable Distance**Overview**:
This script is designed to identify potential buy and sell signals based on the crossover of two Exponential Moving Averages (EMAs) – a short-term EMA (default: 8 periods) and a long-term EMA (default: 50 periods). To reduce noise and false signals, the script incorporates a customizable buffer percentage, ensuring that signals are only generated when the short-term EMA moves significantly above or below the long-term EMA. Additionally, the script allows users to adjust the distance of the signals from the candles using the Average True Range (ATR) for better visualization.
---
Improvements: Added Buffer Percentage for reduced noise in Signals
### **Key Features**:
1. **EMA Crossover Signals**:
Buy Signal: Generated when the short-term EMA crosses above the long-term EMA.
Sell Signal: Generated when the short-term EMA crosses below the long-term EMA.
2. **Buffer Percentage**:
A user-defined buffer percentage ensures that signals are only triggered when the short-term EMA moves a specified percentage above or below the long-term EMA, reducing false signals.
3. **Customizable Signal Distance**:
Signals are plotted at a user-defined distance from the candles, calculated using the ATR (Average True Range) for dynamic positioning.
4. **Visual Enhancements**:
Buy and sell signals are displayed as labels above or below the candles, with optional background highlighting for better visibility.
5. **Flexible Inputs**:
Users can customize the lengths of the short-term and long-term EMAs, the ATR period, the signal distance multiplier, and the buffer percentage.
6. **Alerts**:
Built-in alert conditions allow users to receive real-time notifications for buy and sell signals.
### **Input Parameters**:
**Short EMA Length**: Period for the short-term EMA (default: 8).
**Long EMA Length**: Period for the long-term EMA (default: 50).
**Signal Distance**: Multiplier for ATR to determine the distance of signals from the candles (default: 2.0).
**ATR Length**: Period for the ATR calculation (default: 14).
**Buffer Percentage**: Percentage buffer for reversal signals to reduce noise (default: 1.0%).
### **Ideal For**:
Traders who use EMA crossovers as part of their strategy.
Those looking to reduce false signals with a buffer mechanism.
Users who prefer dynamic signal positioning based on market volatility (ATR).
### **Notes**:
The buffer percentage ensures that signals are only generated when the price moves significantly, making it suitable for trend-following strategies.
The script is highly customizable, allowing traders to adapt it to different timeframes and instruments.
SPY/TLT Strategy█ STRATEGY OVERVIEW
The "SPY/TLT Strategy" is a trend-following crossover strategy designed to trade the relationship between TLT and its Simple Moving Average (SMA). The default configuration uses TLT (iShares 20+ Year Treasury Bond ETF) with a 20-period SMA, entering long positions on bullish crossovers and exiting on bearish crossunders. **This strategy is NOT optimized and performs best in trending markets.**
█ KEY FEATURES
SMA Crossover System: Uses price/SMA relationship for signal generation (Default: 20-period)
Dynamic Time Window: Configurable backtesting period (Default: 2014-2099)
Equity-Based Position Sizing: Default 100% equity allocation per trade
Real-Time Visual Feedback: Price/SMA plot with trend-state background coloring
Event-Driven Execution: Processes orders at bar close for accurate backtesting
█ SIGNAL GENERATION
1. LONG ENTRY CONDITION
TLT closing price crosses ABOVE SMA
Occurs within specified time window
Generates market order at next bar open
2. EXIT CONDITION
TLT closing price crosses BELOW SMA
Closes all open positions immediately
█ ADDITIONAL SETTINGS
SMA Period: Simple Moving Average length (Default: 20)
Start Time and End Time: The time window for trade execution (Default: 1 Jan 2014 - 1 Jan 2099)
Security Symbol: Ticker for analysis (Default: TLT)
█ PERFORMANCE OVERVIEW
Ideal Market Conditions: Strong trending environments
Potential Drawbacks: Whipsaws in range-bound markets
Backtesting results should be analyzed to optimize the MA Period and EMA Filter settings for specific instruments
Combined Multi-Timeframe EMA OscillatorThis script aims to visualize the strength of bullish or bearish trends by utilizing a mix of 200 EMA across multiple timeframes. I've observed that when the multi-timeframe 200 EMA ribbon is aligned and expanding, the uptrend usually lasts longer and is safer to enter at a pullback for trend continuation. Similarly, when the bands are expanding in reverse order, the downtrend holds longer, making it easier to sell the pullbacks.
In this script, I apply a purely empirical and experimental method: a) Ranking the position of each of the above EMAs and turning it into an oscillator. b) Taking each 200 EMA on separate timeframes, turning it into a stochastic-like oscillator, and then averaging them to compute an overall stochastic.
To filter a bullish signal, I use the bullish crossover between these two aggregated oscillators (default: yellow and blue on the chart) which also plots a green shadow area on the screen and I look for buy opportunities/ ignore sell opportunities while this signal is bullish. Similarly, a bearish crossover gives us a bearish signal which also plots a red shadow area on the screen and I only look for sell opportunities/ ignore any buy opportunities while this signal is bearish.
Note that directly buying the signal as it prints can lead to suboptimal entries. The idea behind the above is that these crossovers point on average to a stronger trend; however, a trade should be initiated on the pullbacks with confirmation from momentum and volume indicators and in confluence with key areas of support and resistance and risk management should be used in order to protect your position.
Disclaimer: This script does not constitute certified financial advice, the current work is purely experimental, use at your own discretion.
EMA/SMA + Multi-Timeframe Dashboard (Vertical)20/50 ema and 200 sma
The EMA SMA Trading Indicator combines the power of Exponential Moving Averages (EMA) and Simple Moving Averages (SMA) to help traders identify trends, reversals, and key entry/exit points.
Features:
Dual Moving Averages: Tracks both EMA and SMA to provide a balanced view of short-term and long-term market trends.
Customizable Periods: Allows users to set unique periods for EMA and SMA to suit their trading style and timeframe (e.g., day trading, swing trading, or investing).
Cross Alerts: Highlights EMA and SMA crossover points, which often indicate potential buy or sell signals.
Color-Coded Lines: Visual differentiation between EMA (dynamic and responsive) and SMA (smooth and lagging) for better readability.
Multi-Timeframe Compatibility: Suitable for scalping, intraday trading, and long-term analysis.
Usage:
Trend Confirmation: When the EMA is above the SMA, it signals a bullish trend; when it is below the SMA, it signals a bearish trend.
Crossover Strategy: Use crossovers as potential buy (EMA crosses above SMA) or sell (EMA crosses below SMA) signals.
Dynamic Support/Resistance: EMA can act as short-term support/resistance, while SMA represents long-term levels.
This indicator is perfect for traders who want to combine EMA's speed with SMA's stability for improved decision-making in volatile markets. Customizable alerts and visual cues make it user-friendly for beginners and experienced traders.
Make informed decisions and take your trading to the next level with the EMA SMA Trading Indicator!
ANIL's OHCL, VWAP and EMA CrossPrevious Week High and Low:
This part calculates the previous week's high and low values and plots them as continuous blue lines. The plot.style_line ensures the lines are drawn continuously.
Previous Day Open, High, Low, Close:
The script uses request.security to get the previous day's open, high, low, and close values. These are plotted as continuous lines in different colors:
Open: Green
High: Red
Low: Orange
Close: Purple
VWAP (Volume Weighted Average Price):
The VWAP is calculated using ta.vwap(close) and plotted with a thick black line.
Exponential Moving Averages (EMAs):
The script calculates two EMAs: one with a 9-period (fast) and one with a 21-period (slow).
The EMAs are plotted as continuous lines:
Fast EMA: Blue
Slow EMA: Red
EMA Cross:
The script checks for EMA crossovers and crossunders:
A crossover (fast EMA crossing above slow EMA) triggers a buy signal (green label below the bar).
A crossunder (fast EMA crossing below slow EMA) triggers a sell signal (red label above the bar).
Customization:
You can adjust the fastLength and slowLength variables to change the period of the EMAs.
You can modify the line colors and line thickness to match your preferred style.
The buy and sell signals can be customized further with different shapes or additional conditions for signal generation.
This script provides a comprehensive and visually distinct indicator with the previous week's and day's levels, VWAP, and EMA crossover signals.
Binary Options Pro Helper By Himanshu AgnihotryThe Binary Options Pro Helper is a custom indicator designed specifically for one-minute binary options trading. This tool combines technical analysis methods like moving averages, RSI, Bollinger Bands, and pattern recognition to provide precise Buy and Sell signals. It also includes a time-based filter to ensure trades are executed only during optimal market conditions.
Features:
Moving Averages (EMA):
Uses short-term (7-period) and long-term (21-period) EMA crossovers for trend detection.
RSI-Based Signals:
Identifies overbought/oversold conditions for entry points.
Bollinger Bands:
Highlights market volatility and potential reversal zones.
Chart Pattern Recognition:
Detects double tops (sell signals) and double bottoms (buy signals).
Time-Based Filter:
Trades only within specified hours (e.g., 9:30 AM to 11:30 AM) to avoid unnecessary noise.
Visual Signals:
Plots buy and sell markers directly on the chart for ease of use.
How to Use:
Setup:
Add this script to your TradingView chart and select a 1-minute timeframe.
Signal Interpretation:
Buy Signal: Triggered when EMA crossover occurs, RSI is oversold (<30), and a double bottom pattern is detected.
Sell Signal: Triggered when EMA crossover occurs, RSI is overbought (>70), and a double top pattern is detected.
Timing:
Ensure trades are executed only during the specified time window for better accuracy.
Best Practices:
Use this indicator alongside fundamental analysis or market sentiment.
Test it thoroughly with historical data (backtesting) and in a demo account before live trading.
Adjust parameters (e.g., EMA periods, RSI thresholds) based on your trading style.
Bitcoin Pi Cycle TrackerThe Bitcoin Pi Cycle Tracker is based on the widely recognized Pi Cycle Top Indicator, a concept used to identify potential market cycle tops in Bitcoin's price. This implementation combines the 111-day Simple Moving Average (SMA) and the 350-day SMA (multiplied by 2) to detect key crossover points. When the 111-day SMA crosses above the 350-day SMA x2, it signals a potential market peak.
Key Features:
Plots the 111-day SMA (blue) and the 350-day SMA x2 (red) for clear visualization.
Displays visual markers and vertical lines at crossover points to highlight key moments.
Sends alerts for crossovers, helping traders stay ahead of market movements.
This tool is an implementation of the Pi Cycle concept originally popularized by Bitcoin market analysts. Use it to analyze historical price cycles and prepare for significant market events. Please note that while the Pi Cycle Indicator has been historically effective, it should be used alongside other tools for a comprehensive trading strategy.
MERCURY-PRO by DrAbhiramSivprasd“MERCURYPRO”
The MERCURYPRO indicator is a custom technical analysis tool designed to provide dynamic trend signals based on a combination of the Chande Momentum Oscillator (CMO) and Standard Deviation (StDev). This indicator helps traders identify trend reversals or continuation based on the behavior of the price and momentum.
Key Features:
• Source Input: The indicator works with any price data, with the default set to close, which represents the closing price of each bar.
• Length Input: A period (default value 9) is used to determine the calculation window for the Chande Momentum Oscillator and Standard Deviation.
• Fixed CMO Length Option: Users can choose whether to use a fixed CMO length of 9 or adjust the length to the user-defined pds value.
• Calculation Method: The indicator allows switching between using the Chande Momentum Oscillator (CMO) or Standard Deviation (StDev) for the momentum calculation.
• Alpha: The smoothing factor used in the calculation of the MERCURYPRO value, which is based on the length of the period input (pds).
Core Calculation:
1. Momentum Calculation: The script calculates the momentum by determining the change in the source price (e.g., close) from one period to the next.
2. Chande Momentum Oscillator (CMO): The positive and negative momentum components are calculated and then summed over the specified period. This value is normalized to a percentage to determine the momentum strength.
3. K Value Calculation: The script selects either the CMO or Standard Deviation (depending on the user setting) to calculate the k value, which represents the dynamic price momentum.
4. MERCURYPRO Line: The final output of the indicator, MERCURYPRO, is computed using a weighted average of the k value and the previous MERCURYPRO value. The line is smoothed using the Alpha parameter.
Plot and Signal Generation:
• Color Coding: The line is color-coded based on the direction of MERCURYPRO:
• Blue: The trend is bullish (MERCURYPRO is rising).
• Maroon: The trend is bearish (MERCURYPRO is falling).
• Default Blue: Neutral or sideways market conditions.
• Plotting: The MERCURYPRO line is plotted with varying colors depending on the trend direction.
Alerts:
• Color Change Alert: The indicator has an alert condition based on when the MERCURYPRO line crosses its previous value. This helps traders stay informed about potential trend reversals or continuation signals.
Use Case:
• Trend Confirmation: Traders can use the MERCURYPRO indicator to identify whether the market is in a strong trend or not.
• Signal for Entries/Exits: The color change and crossovers of the MERCURYPRO line can be used as entry or exit signals, depending on the trader’s strategy.
Overall Purpose:
The MERCURYPRO indicator combines momentum analysis with smoothing techniques to offer a dynamic, responsive tool for identifying market trends and potential reversals. It is particularly useful in conjunction with other technical indicators to provide confirmation for trade setups.
How to Use the MERCURYPRO Indicator:
The MERCURYPRO indicator is designed to help traders identify trend reversals and market conditions. Here are a few ways you can use it:
1. Trend Confirmation (Bullish or Bearish)
• Bullish Trend: When the MERCURYPRO line is colored Blue, it indicates a rising trend, suggesting that the market is bullish.
• Action: You can consider entering long positions when the line turns blue, or holding your existing positions if you’re already long.
• Bearish Trend: When the MERCURYPRO line is colored Maroon, it signals a downward trend, indicating a bearish market.
• Action: You may consider entering short positions or closing any long positions when the line turns maroon.
2. Trend Reversal Alerts
• Color Change: The MERCURYPRO indicator changes color when there’s a trend reversal. The alert condition triggers when the MERCURYPRO crosses above or below its previous value, signaling a potential shift in the trend.
• Action: You can use this alert as a signal to monitor potential entry or exit points for trades. For example, a crossover from maroon to blue could indicate a potential buying opportunity, while a crossover from blue to maroon could suggest a selling opportunity.
3. Use with Other Indicators for Confirmation
• While the MERCURYPRO provides valuable trend insights, it’s often more effective when used in combination with other indicators like RSI (Relative Strength Index), MACD, or moving averages to confirm signals.
• Example: If MERCURYPRO turns blue and RSI is above 50, it may signal a strong bullish trend, enhancing the confidence to enter a long trade.
4. Divergence
• Watch for divergence between the MERCURYPRO line and the price chart:
• Bullish Divergence: If the price makes new lows while MERCURYPRO is showing higher lows, it suggests a potential bullish reversal.
• Bearish Divergence: If the price makes new highs while MERCURYPRO is showing lower highs, it suggests a potential bearish reversal.
Example of Use:
• Example 1: If the MERCURYPRO line changes from maroon to blue, you might enter a long position. After the MERCURYPRO line turns blue, use an alert to monitor the price action. If other indicators (like RSI) also suggest strength, your confidence in the trade will increase.
• Example 2: If the MERCURYPRO line shifts from blue to maroon, it could be a signal to close long positions and consider shorting the market if other conditions align (e.g., moving averages also turn bearish).
Warning for Using the MERCURYPRO Indicator:
1. Lagging Indicator:
• The MERCURYPRO is a lagging indicator, meaning it responds to price changes after they have occurred. This may delay entry and exit signals, and it’s crucial to combine it with other leading indicators to get timely information.
2. False Signals in Range-bound Markets:
• In choppy or sideways markets, the MERCURYPRO line can produce false signals, flipping between blue and maroon frequently without showing a clear trend. It’s important to avoid trading based on these false signals when the market is not trending.
3. Overreliance on One Indicator:
• Relying solely on MERCURYPRO can be risky. Always confirm signals with additional tools like volume analysis, price action, or other indicators to increase the accuracy of your trades.
4. Market Conditions Matter:
• The indicator may work well in trending markets, but in highly volatile or news-driven environments, it may provide misleading signals. Ensure that you take market fundamentals and external news events into consideration before acting on the indicator’s signals.
5. Risk Management:
• As with any technical indicator, MERCURYPRO is not infallible. Always use appropriate risk management techniques such as stop-loss orders to protect your capital. Never risk more than you can afford to lose on a trade.
6. Backtest First:
• Before implementing MERCURYPRO in live trading, make sure to backtest it on historical data. Test the strategy with various market conditions to assess its effectiveness and identify any potential weaknesses.
By considering these guidelines and warnings, you can use the MERCURYPRO indicator more effectively and mitigate potential risks in your trading strategy.
Support/Resistance
Custom Moving Average Indicator with MACD, RSI, and Support/Resistance
This indicator is designed to help traders make informed trading decisions by integrating several technical indicators, including moving averages, the Relative Strength Index (RSI), and the Moving Average Convergence Divergence (MACD).
Key Features:
Moving Averages:
This indicator uses simple moving averages (SMAs) for several periods (4, 18, 66, 89, 632, 1000, 1500, 2000, and 3000 bars). This helps to identify the overall trend of the price and potential support and resistance levels.
The color of each moving average line is dynamically changed based on the closing price's position relative to the average; it turns red if the price is above the average and green if the price is below.
Relative Strength Index (RSI):
The RSI is calculated for a 14-bar period, which is a measure of overbought or oversold conditions.
An RSI value above 70 indicates an overbought condition, while a value below 30 indicates an oversold condition.
MACD:
The MACD is calculated using a fast length of 12, a slow length of 26, and a signal length of 9. Crossovers between the MACD line and the signal line indicate momentum shifts.
A crossover of the MACD line above the signal line suggests a potential buy signal, while a crossover below indicates a potential sell signal.
Buy and Sell Signals:
Buy Signal: Triggered when the MACD line crosses above the signal line, the RSI is below 30, the MACD is above 0, and there is high volume.
Sell Signal: Triggered when the MACD line crosses below the signal line, the RSI is above 70, the MACD is below 0, and there is high volume.
Alerts:
The indicator includes alerts that are triggered when buy and sell signals occur, helping traders respond quickly to market opportunities.
How to Trade Using the Indicator (continued):
Trading on Buy Signals:
Look for buy signals when the MACD line crosses above the signal line. Ensure that the RSI is below 30, indicating there is a potential for price recovery from an oversold condition.
Confirm that the volume is above the average, which indicates strong market participation and adds validity to the trade.
Trading on Sell Signals:
Search for sell signals when the MACD line crosses below the signal line. Check that the RSI is above 70 to confirm an overbought condition, implying the price may decline.
As with buy signals, ensure that volume is high to validate the strength of the sell signal.
Risk Management:
Use stop-loss orders to protect your capital. Establish an initial loss threshold based on your risk management strategy.
Continuously monitor the market and new signals and adjust your approach according to your market analysis.
Conclusion:
This combined indicator helps traders make informed decisions by relying on a set of technical tools. To achieve the best results, ensure you integrate the analysis from these indicators with your trading strategies and other techniques.
Feel free to use this explanation as an introduction or guide to inform traders on how to effectively use the indicator. If you have any more questions or need further details, don't hesitate to ask!
Volume-MACD-RSI Integrated StrategyDescription:
This script integrates three well-known technical analysis tools—Volume, MACD, and RSI—into a single signal meant to help traders identify potential turning points under strong market conditions.
Concept Overview:
Volume Filter: We compare the current bar’s volume to a 20-period volume average and require it to exceed a specified multiplier. This ensures that signals occur only during periods of heightened market participation. The logic is that moves on low volume are less reliable, so we wait for increased activity to confirm potential trend changes.
MACD Momentum Shift:
We incorporate MACD crossovers to determine when momentum is changing direction. MACD is a popular momentum indicator that identifies shifts in trend by comparing short-term and long-term EMAs. A bullish crossover (MACD line crossing above the signal line) may suggest upward momentum is building, while a bearish crossunder can indicate momentum turning downward.
RSI Market Condition Check:
RSI helps us identify overbought or oversold conditions. By requiring that RSI be oversold on buy signals and overbought on sell signals, we attempt to pinpoint entries where price could be at an extreme. The idea is to position entries or exits at junctures where price may be due for a reversal.
How the Script Works Together:
Volume Confirmation: No signals fire unless there’s strong volume. This reduces false positives.
MACD Momentum Check: Once volume confirms market interest, MACD crossover events serve as a trigger to initiate consideration of a trade signal.
RSI Condition: Finally, RSI determines whether the market is at an extreme. This final layer helps ensure we only act on signals that have both momentum shift and a price at an extreme level, potentially increasing the reliability of signals.
Intended Use:
This script can help highlight potential reversal points or trend shifts during active market periods.
Traders can use these signals as a starting point for deeper analysis. For instance, a “BUY” arrow may prompt a trader to investigate the market context, confirm with other methods, or look for patterns that further support a long entry.
The script is best used on markets with reliable volume data, such as stocks or futures, and can be experimented with across different timeframes. Adjusting the RSI thresholds, MACD parameters, and volume multiplier can help tailor it to specific instruments or trading styles.
Chart Setup:
When adding this script to your chart, it should be the only indicator present, so you can clearly see the red “BUY” arrows and green “SELL” arrows at the candle closes where signals occur.
The chart should be kept clean and uncluttered for clarity. No other indicators are necessary since the logic is already integrated into this single script.
Trend Stability Index (TSI)Overview
The Trend Stability Index (TSI) is a technical analysis tool designed to evaluate the stability of a market trend by analyzing both price movements and trading volume. By combining these two crucial elements, the TSI provides traders with insights into the strength and reliability of ongoing trends, assisting in making informed trading decisions.
Key Features
• Dual Analysis: Integrates price changes and volume fluctuations to assess trend stability.
• Customizable Periods: Allows users to set evaluation periods for both trend and volume based on their trading preferences.
• Visual Indicators: Displays the Trend Stability Index as a line chart, highlights neutral zones, and uses background colors to indicate trend stability or instability.
Configuration Settings
1. Trend Length (trendLength)
• Description: Determines the number of periods over which the price stability is evaluated.
• Default Value: 15
• Usage: A longer trend length smooths out short-term volatility, providing a clearer picture of the overarching trend.
2. Volume Length (volumeLength)
• Description: Sets the number of periods over which trading volume changes are assessed.
• Default Value: 15
• Usage: Adjusting the volume length helps in capturing significant volume movements that may influence trend strength.
Calculation Methodology
The Trend Stability Index is calculated through a series of steps that analyze both price and volume changes:
1. Price Change Rate (priceChange)
• Calculation: Utilizes the Rate of Change (ROC) function on the closing prices over the specified trendLength.
• Purpose: Measures the percentage change in price over the trend evaluation period, indicating the direction and momentum of the price movement.
2. Volume Change Rate (volumeChange)
• Calculation: Applies the Rate of Change (ROC) function to the trading volume over the specified volumeLength.
• Purpose: Assesses the percentage change in trading volume, providing insight into the conviction behind price movements.
3. Trend Stability (trendStability)
• Calculation: Multiplies priceChange by volumeChange.
• Purpose: Combines price and volume changes to gauge the overall stability of the trend. A higher positive value suggests a strong and stable trend, while negative values may indicate trend weakness or reversal.
4. Trend Stability Index (TSI)
• Calculation: Applies a Simple Moving Average (SMA) to the trendStability over the trendLength period.
• Purpose: Smooths the trend stability data to create a more consistent and interpretable index.
Trend/Ranging Determination
• Stable Trend (isStable)
• Condition: When the TSI value is greater than 0.
• Interpretation: Indicates that the current trend is stable and likely to continue in its direction.
• Unstable Trend / Range-bound Market
• Condition: When the TSI value is less than or equal to 0.
• Interpretation: Suggests that the trend may be weakening, reversing, or that the market is moving sideways without a clear direction.
Visualization
The TSI indicator employs several visual elements to convey information effectively:
1. TSI Line
• Representation: Plotted as a blue line.
• Purpose: Displays the Trend Stability Index values over time, allowing traders to observe trend stability dynamics.
2. Neutral Horizontal Line
• Representation: A gray horizontal line at the 0 level.
• Purpose: Serves as a reference point to distinguish between stable and unstable trends.
3. Background Color
• Stable Trend: Green background with 80% transparency when isStable is true.
• Unstable Trend: Red background with 80% transparency when isStable is false.
• Purpose: Provides an immediate visual cue about the current trend’s stability, enhancing the interpretability of the indicator.
Usage Guidelines
• Identifying Trend Strength: Utilize the TSI to confirm the strength of existing trends. A consistently positive TSI suggests strong trend momentum, while a negative TSI may signal caution or a potential reversal.
• Volume Confirmation: The integration of volume changes helps in validating price movements. Significant price changes accompanied by corresponding volume shifts can reinforce the reliability of the trend.
• Entry and Exit Signals: Traders can use crossovers of the TSI with the neutral line (0 level) as potential entry or exit points. For instance, a crossover from below to above 0 may indicate a bullish trend initiation, while a crossover from above to below 0 could suggest bearish momentum.
• Combining with Other Indicators: To enhance trading strategies, consider using the TSI in conjunction with other technical indicators such as Moving Averages, RSI, or MACD for comprehensive market analysis.
Example Scenario
Imagine analyzing a stock with the following observations using the TSI:
• The TSI has been consistently above 0 for the past 30 periods, accompanied by increasing trading volume. This scenario indicates a strong and stable uptrend, suggesting that buying opportunities may be favorable.
• Conversely, if the TSI drops below 0 while the price remains relatively flat and volume decreases, it may imply that the current trend is losing momentum, and the market could be entering a consolidation phase or preparing for a trend reversal.
Conclusion
The Trend Stability Index is a valuable tool for traders seeking to assess the reliability and strength of market trends by integrating price and volume dynamics. Its customizable settings and clear visual indicators make it adaptable to various trading styles and market conditions. By incorporating the TSI into your trading analysis, you can enhance your ability to identify and act upon stable and profitable trends.
RSI Difference (Fast and Slow)Introduction
Oscillators like the RSI are fundamental tools for identifying trends in financial markets. Their ability to measure price momentum allows traders to detect overbought, oversold levels, and divergences, anticipating trend changes. Are there ways to improve the use of traditional RSI? How can we obtain more detailed information about current trends? This indicator answers these questions by expanding the functionalities of the traditional RSI and offering an additional tool for analysis.
How does it work?
This indicator provides a framework for trend analysis based on the following setup:
Fast RSI
Slow RSI
SMA of the fast RSI
SMA of the slow RSI
Histogram
Custom Indicator Settings
My preferred configuration is based on the 13 and 55 moving averages. The rest of the setup is as follows:
I typically use the 13 and 55 moving averages to configure both the RSI and short- and long-term moving averages.
Interpretation and Signals: Including a Long-Period RSI
Including a long-period RSI helps identify key patterns in market behavior. Crossovers between the two can be used to establish entry patterns:
If the fast RSI crosses above the slow RSI, this could indicate a long-entry pattern.
If the fast RSI crosses below the slow RSI, this could indicate a short-entry pattern.
Interpretation and Signals: Including Moving Averages
Including moving averages for both the short- and long-period RSI can help identify the base trend of the movement and, consequently:
Avoid false signals.
Trade in favor of the trend.
A simple way to start working with these is to use the crossover of the moving averages to identify the current trend:
If the short-period SMA is above the long-period SMA, the trend is bullish.
If the short-period SMA is below the long-period SMA, the trend is bearish.
Interpretation and Signals: The Histogram
The histogram represents the difference between the moving averages. If the histogram is positive, the short average is above the long average. If the histogram is below zero, the short average is below the long average. Divergences with price provide signals of potential exhaustion in the movement, indicating a possible reversal.
Indicator Details
This indicator builds upon the traditional RSI by integrating additional features that enhance its utility for traders. Here’s how each component is calculated and how they contribute to the originality of the script:
Fast RSI and Slow RSI: The fast RSI is calculated using a shorter lookback period, allowing it to capture rapid changes in momentum. The slow RSI uses a longer period to smooth out fluctuations and provide a broader view of the trend. These two RSIs work together to identify significant momentum shifts.
SMA of RSI values: The simple moving averages (SMA) of the fast and slow RSI help filter out noise and provide clear crossover signals. The SMAs are calculated using standard formulas but applied to the RSI values rather than price data, which adds a layer of insight into momentum trends.
Histogram calculation: The histogram represents the difference between the SMA of the fast RSI and the SMA of the slow RSI. This value gives a visual representation of the convergence or divergence of momentum. When the histogram crosses zero, it signifies a potential shift in the underlying trend.
This indicator combines multiple layers of analysis: fast and slow momentum, trend confirmation through SMAs, and divergence detection via the histogram. This multi-dimensional approach provides traders with a more comprehensive tool for trend analysis and decision-making.
Conclusion
This article has explored how to use this indicator to identify trends, leverage entry patterns, and analyze divergences by combining the fast RSI, slow RSI, their moving averages, and a histogram. Additionally, I’ve detailed how I usually interpret this indicator:
Identifying RSI patterns to anticipate momentum changes.
Using SMAs to confirm base trends.
Leveraging the histogram to detect divergences and potential price reversals.
Dual Strategy Selector V2 - CryptogyaniOverview:
This script provides traders with a dual-strategy system that they can toggle between using a simple dropdown menu in the input settings. It is designed to cater to different trading styles and needs, offering both simplicity and advanced filtering techniques. The strategies are built around moving average crossovers, enhanced by configurable risk management tools like take profit levels, trailing stops, and ATR-based stop-loss.
Key Features:
Two Strategies in One Script:
Strategy 1: A classic moving average crossover strategy for identifying entry signals based on trend reversals. Includes user-defined take profit and trailing stop-loss options for profit locking.
Strategy 2: An advanced trend-following system that incorporates:
A higher timeframe trend filter to confirm entry signals.
ATR-based stop-loss for dynamic risk management.
Configurable partial take profit to secure gains while letting the trade run.
Highly Customizable:
All key parameters such as SMA lengths, take profit levels, ATR multiplier, and timeframe for the trend filter are adjustable via the input settings.
Dynamic Toggle:
Traders can switch between Strategy 1 and Strategy 2 with a single dropdown, allowing them to adapt the strategy to market conditions.
How It Works:
Strategy 1:
Entry Logic: A long trade is triggered when the fast SMA crosses above the slow SMA.
Exit Logic: The trade exits at either a user-defined take profit level (percentage or pips) or via an optional trailing stop that dynamically adjusts based on price movement.
Strategy 2:
Entry Logic: Builds on the SMA crossover logic but adds a higher timeframe trend filter to align trades with the broader market direction.
Risk Management:
ATR-Based Stop-Loss: Protects against adverse moves with a volatility-adjusted stop-loss.
Partial Take Profit: Allows traders to secure a percentage of gains while keeping some exposure for extended trends.
How to Use:
Select Your Strategy:
Use the dropdown in the input settings to choose Strategy 1 or Strategy 2.
Configure Parameters:
Adjust SMA lengths, take profit, and risk management settings to align with your trading style.
For Strategy 2, specify the higher timeframe for trend filtering.
Deploy and Monitor:
Apply the script to your preferred asset and timeframe.
Use the backtest results to fine-tune settings for optimal performance.
Why Choose This Script?:
This script stands out due to its dual-strategy flexibility and enhanced features:
For beginners: Strategy 1 provides a simple yet effective trend-following system with minimal setup.
For advanced traders: Strategy 2 includes powerful tools like trend filters and ATR-based stop-loss, making it ideal for challenging market conditions.
By combining simplicity with advanced features, this script offers something for everyone while maintaining full transparency and user customization.
Default Settings:
Strategy 1:
Fast SMA: 21, Slow SMA: 49
Take Profit: 7% or 50 pips
Trailing Stop: Optional (disabled by default)
Strategy 2:
Fast SMA: 20, Slow SMA: 50
ATR Multiplier: 1.5
Partial Take Profit: 50%
Higher Timeframe: 1 Day (1D)
TechniTrend: Volatility and MACD Trend Highlighter🟦 Overview
The "Candle Volatility with Trend Prediction" indicator is a powerful tool designed to identify market volatility based on candle movement relative to average volume while also incorporating trend predictions using the MACD. This indicator is ideal for traders who want to detect volatile market conditions and anticipate potential price movements, leveraging both price changes and volume dynamics.
It not only highlights candles with significant price movements but also integrates a trend analysis based on the MACD (Moving Average Convergence Divergence), allowing traders to gauge whether the market momentum aligns with or diverges from the detected volatility.
🟦 Key Features
🔸Volatility Detection: Identifies candles that exceed normal price fluctuations based on average volume and recent price volatility.
🔸Trend Prediction: Uses the MACD indicator to overlay trend analysis, signaling potential market direction shifts.
🔸Volume-Based Analysis: Integrates customizable moving averages (SMA, EMA, WMA, etc.) of volume, providing a clear visualization of volume trends.
🔸Alert System: Automatically notifies traders of high-volatility situations, aiding in timely decision-making.
🔸Customizability: Includes multiple settings to tailor the indicator to different market conditions and timeframes.
🟦 How It Works
The indicator operates by evaluating the price volatility in relation to average volume and identifying when a candle's volatility surpasses a threshold defined by the user. The key calculations include:
🔸Average Volume Calculation: The user selects the type of moving average (SMA, EMA, etc.) to calculate the average volume over a set period.
🔸Volatility Measurement: The indicator measures the body change (difference between open and close) and the high-low range of each candle. It then calculates recent price volatility using a standard deviation over a user-defined length.
🔸Weighted Index: A unique index is created by dividing price change by average volume and recent volatility.
🔸Highlighting Volatility: If the weighted index exceeds a customizable threshold, the candle is highlighted, indicating potential trading opportunities.
🔸Trend Analysis with MACD: The MACD line and signal line are plotted and adjusted with a user-defined multiplier to visualize trends alongside the volatility signals.
🟦 Recommended Settings
🔸Volume MA Length: A default of 14 periods for the average volume calculation is recommended. Adjust to higher periods for long-term trends and shorter periods for quick trades.
🔸Volatility Threshold Multiplier: Set at 1.2 by default to capture moderately significant movements. Increase for fewer but stronger signals or decrease for more frequent signals.
🔸MACD Settings: Default MACD parameters (12, 26, 9) are suggested. Tweak based on your trading strategy and asset volatility.
🔸MACD Multiplier: Adjust based on how the MACD should visually compare to the average volume. A multiplier of 1 works well for most cases.
🟦 How to Use
🔸Volatile Market Detection:
Look for highlighted candles that suggest a deviation from typical price behavior. These candles often signify an entry point for short-term trades.
🔸Trend Confirmation:
Use the MACD trend analysis to verify if the highlighted volatile candles align with a bullish or bearish trend.
For example, a bullish MACD crossover combined with a highlighted candle suggests a potential uptrend, while a bearish crossover with volatility signals may indicate a downtrend.
🔸Volume-Driven Strategy:
Observe how volume changes impact candle volatility. When volume rises significantly and candles are highlighted, it can suggest strong market moves influenced by big players.
🟦 Best Use Cases
🔸Trend Reversals: Detect potential trend reversals early by spotting divergences between price and MACD within volatile conditions.
🔸Breakout Strategies: Use the indicator to confirm price breakouts with significant volume changes.
🔸Scalping or Day Trading: Customize the indicator for shorter timeframes to capture rapid market movements based on volatility spikes.
🔸Swing Trading: Combine volatility and trend insights to optimize entry and exit points over longer periods.
🟦 Customization Options
🔸Volume-Based Inputs: Choose from SMA, EMA, WMA, and more to define how average volume is calculated.
🔸Threshold Adjustments: Modify the volatility threshold multiplier to increase or decrease sensitivity based on your trading style.
🔸MACD Tuning: Adjust MACD settings and the multiplier for trend visualization tailored to different asset classes and market conditions.
🟦 Indicator Alerts
🔸High Volatility Alerts: Automatically triggered when candles exceed user-defined volatility levels.
🔸Bullish/Bearish Trend Alerts: Alerts are activated when highlighted volatile candles align with bullish or bearish MACD crossovers, making it easier to spot opportunities without constantly monitoring the chart.
🟦 Examples of Use
To better understand how this indicator works, consider the following scenarios:
🔸Example 1: In a strong uptrend, observe how volume surges and volatility highlight candles right before price consolidations, indicating optimal exit points.
🔸Example 2: During a downtrend, see how the MACD aligns with volume-driven volatility, signaling potential short-selling opportunities.
Fibonacci ATR Fusion - Strategy [presentTrading]Open-script again! This time is also an ATR-related strategy. Enjoy! :)
If you have any questions, let me know, and I'll help make this as effective as possible.
█ Introduction and How It Is Different
The Fibonacci ATR Fusion Strategy is an advanced trading approach that uniquely integrates Fibonacci-based weighted averages with the Average True Range (ATR) to identify and capitalize on significant market trends.
Unlike traditional strategies that rely on single indicators or static parameters, this method combines multiple timeframes and dynamic volatility measurements to enhance precision and adaptability. Additionally, it features a 4-step Take Profit (TP) mechanism, allowing for systematic profit-taking at various levels, which optimizes both risk management and return potential in long and short market positions.
BTCUSD 6hr Performance
█ Strategy, How It Works: Detailed Explanation
The Fibonacci ATR Fusion Strategy utilizes a combination of technical indicators and weighted averages to determine optimal entry and exit points. Below is a breakdown of its key components and operational logic.
🔶 1. Enhanced True Range Calculation
The strategy begins by calculating the True Range (TR) to measure market volatility accurately.
TR = max(High - Low, abs(High - Previous Close), abs(Low - Previous Close))
High and Low: Highest and lowest prices of the current trading period.
Previous Close: Closing price of the preceding trading period.
max: Selects the largest value among the three calculations to account for gaps and limit movements.
🔶 2. Buying Pressure (BP) Calculation
Buying Pressure (BP) quantifies the extent to which buyers are driving the price upwards within a period.
BP = Close - True Low
Close: Current period's closing price.
True Low: The lower boundary determined in the True Range calculation.
🔶 3. Ratio Calculation for Different Periods
To assess the strength of buying pressure relative to volatility, the strategy calculates a ratio over various Fibonacci-based timeframes.
Ratio = 100 * (Sum of BP over n periods) / (Sum of TR over n periods)
n: Length of the period (e.g., 8, 13, 21, 34, 55).
Sum of BP: Cumulative Buying Pressure over n periods.
Sum of TR: Cumulative True Range over n periods.
This ratio normalizes buying pressure, making it comparable across different timeframes.
🔶 4. Weighted Average Calculation
The strategy employs a weighted average of ratios from multiple Fibonacci-based periods to smooth out signals and enhance trend detection.
Weighted Avg = (w1 * Ratio_p1 + w2 * Ratio_p2 + w3 * Ratio_p3 + w4 * Ratio_p4 + Ratio_p5) / (w1 + w2 + w3 + w4 + 1)
w1, w2, w3, w4: Weights assigned to each ratio period.
Ratio_p1 to Ratio_p5: Ratios calculated for periods p1 to p5 (e.g., 8, 13, 21, 34, 55).
This weighted approach emphasizes shorter periods more heavily, capturing recent market dynamics while still considering longer-term trends.
🔶 5. Simple Moving Average (SMA) of Weighted Average
To further smooth the weighted average and reduce noise, a Simple Moving Average (SMA) is applied.
Weighted Avg SMA = SMA(Weighted Avg, m)
- m: SMA period (e.g., 3).
This smoothed line serves as the primary signal generator for trade entries and exits.
🔶 6. Trading Condition Thresholds
The strategy defines specific threshold values to determine optimal entry and exit points based on crossovers and crossunders of the SMA.
Long Condition = Crossover(Weighted Avg SMA, Long Entry Threshold)
Short Condition = Crossunder(Weighted Avg SMA, Short Entry Threshold)
Long Exit = Crossunder(Weighted Avg SMA, Long Exit Threshold)
Short Exit = Crossover(Weighted Avg SMA, Short Exit Threshold)
Long Entry Threshold (T_LE): Level at which a long position is triggered.
Short Entry Threshold (T_SE): Level at which a short position is triggered.
Long Exit Threshold (T_LX): Level at which a long position is exited.
Short Exit Threshold (T_SX): Level at which a short position is exited.
These conditions ensure that trades are only executed when clear trends are identified, enhancing the strategy's reliability.
Previous local performance
🔶 7. ATR-Based Take Profit Mechanism
When enabled, the strategy employs a 4-step Take Profit system to systematically secure profits as the trade moves in the desired direction.
TP Price_1 Long = Entry Price + (TP1ATR * ATR Value)
TP Price_2 Long = Entry Price + (TP2ATR * ATR Value)
TP Price_3 Long = Entry Price + (TP3ATR * ATR Value)
TP Price_1 Short = Entry Price - (TP1ATR * ATR Value)
TP Price_2 Short = Entry Price - (TP2ATR * ATR Value)
TP Price_3 Short = Entry Price - (TP3ATR * ATR Value)
- ATR Value: Calculated using ATR over a specified period (e.g., 14).
- TPxATR: User-defined multipliers for each take profit level.
- TPx_percent: Percentage of the position to exit at each TP level.
This multi-tiered exit strategy allows for partial position closures, optimizing profit capture while maintaining exposure to potential further gains.
█ Trade Direction
The Fibonacci ATR Fusion Strategy is designed to operate in both long and short market conditions, providing flexibility to traders in varying market environments.
Long Trades: Initiated when the SMA of the weighted average crosses above the Long Entry Threshold (T_LE), indicating strong upward momentum.
Short Trades: Initiated when the SMA of the weighted average crosses below the Short Entry Threshold (T_SE), signaling robust downward momentum.
Additionally, the strategy can be configured to trade exclusively in one direction—Long, Short, or Both—based on the trader’s preference and market analysis.
█ Usage
Implementing the Fibonacci ATR Fusion Strategy involves several steps to ensure it aligns with your trading objectives and market conditions.
1. Configure Strategy Parameters:
- Trading Direction: Choose between Long, Short, or Both based on your market outlook.
- Trading Condition Thresholds: Set the Long Entry, Short Entry, Long Exit, and Short Exit thresholds to define when to enter and exit trades.
2. Set Take Profit Levels (if enabled):
- ATR Multipliers: Define how many ATRs away from the entry price each take profit level is set.
- Take Profit Percentages: Allocate what percentage of the position to close at each TP level.
3. Apply to Desired Chart:
- Add the strategy to the chart of the asset you wish to trade.
- Observe the plotted Fibonacci ATR and SMA Fibonacci ATR indicators for visual confirmation.
4. Monitor and Adjust:
- Regularly review the strategy’s performance through backtesting.
- Adjust the input parameters based on historical performance and changing market dynamics.
5. Risk Management:
- Ensure that the sum of take profit percentages does not exceed 100% to avoid over-closing positions.
- Utilize the ATR-based TP levels to adapt to varying market volatilities, maintaining a balanced risk-reward ratio.
█ Default Settings
Understanding the default settings is crucial for optimizing the Fibonacci ATR Fusion Strategy's performance. Here's a precise and simple overview of the key parameters and their effects:
🔶 Key Parameters and Their Effects
1. Trading Direction (`tradingDirection`)
- Default: Both
- Effect: Determines whether the strategy takes both long and short positions or restricts to one direction. Selecting Both allows maximum flexibility, while Long or Short can be used for directional bias.
2. Trading Condition Thresholds
Long Entry (long_entry_threshold = 58.0): Higher values reduce false positives but may miss trades.
Short Entry (short_entry_threshold = 42.0): Lower values capture early short trends but may increase false signals.
Long Exit (long_exit_threshold = 42.0): Exits long positions early, securing profits but potentially cutting trends short.
Short Exit (short_exit_threshold = 58.0): Delays short exits to capture favorable movements, avoiding premature exits.
3. Take Profit Configuration (`useTakeProfit` = false)
- Effect: When enabled, the strategy employs a 4-step TP mechanism to secure profits at multiple levels. By default, it is disabled to allow users to opt-in based on their trading style.
4. ATR-Based Take Profit Multipliers
TP1 (tp1ATR = 3.0): Sets the first TP at 3 ATRs for initial profit capture.
TP2 (tp2ATR = 8.0): Targets larger trends, though less likely to be reached.
TP3 (tp3ATR = 14.0): Optimizes for extreme price moves, seldom triggered.
5. Take Profit Percentages
TP Level 1 (tp1_percent = 12%): Secures 12% at the first TP.
TP Level 2 (tp2_percent = 12%): Exits another 12% at the second TP.
TP Level 3 (tp3_percent = 12%): Closes an additional 12% at the third TP.
6. Weighted Average Parameters
Ratio Periods: Fibonacci-based intervals (8, 13, 21, 34, 55) balance responsiveness.
Weights: Emphasizes recent data for timely responses to market trends.
SMA Period (weighted_avg_sma_period = 3): Smoothens data with minimal lag, balancing noise reduction and responsiveness.
7. ATR Period (`atrPeriod` = 14)
Effect: Sets the ATR calculation length, impacting TP sensitivity to volatility.
🔶 Impact on Performance
- Sensitivity and Responsiveness:
- Shorter Ratio Periods and Higher Weights: Make the weighted average more responsive to recent price changes, allowing quicker trade entries and exits but increasing the likelihood of false signals.
- Longer Ratio Periods and Lower Weights: Provide smoother signals with fewer false positives but may delay trade entries, potentially missing out on significant price moves.
- Profit Taking:
- ATR Multipliers: Higher multipliers set take profit levels further away, targeting larger price movements but reducing the probability of reaching these levels.
- Fixed Percentages: Allocating equal percentages at each TP level ensures consistent profit realization and risk management, preventing overexposure.
- Trade Direction Control:
- Selecting Specific Directions: Restricting trades to Long or Short can align the strategy with market trends or personal biases, potentially enhancing performance in trending markets.
- Risk Management:
- Take Profit Percentages: Dividing the position into smaller percentages at multiple TP levels helps lock in profits progressively, reducing risk and allowing the remaining position to ride further trends.
- Market Adaptability:
- Weighted Averages and ATR: By combining multiple timeframes and adjusting to volatility, the strategy adapts to different market conditions, maintaining effectiveness across various asset classes and timeframes.
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If you want to know more about ATR, can also check "SuperATR 7-Step Profit".
Enjoy trading.
Price Movement Predictor (PMP)The Price Movement Predictor (PMP) is a versatile trading indicator designed to assist traders in identifying potential buy and sell opportunities in the market. This indicator utilizes a combination of technical analysis tools to generate signals based on the relative strength index (RSI) and moving averages, ensuring a robust and strategic approach to trading.
Key Features:
RSI-Based Signal Generation:
The indicator monitors the RSI to identify overbought and oversold conditions in the market.
A buy signal is generated when the RSI drops below a predefined oversold threshold, indicating potential upward price movement.
Conversely, a sell signal is triggered when the RSI exceeds a specified overbought level, suggesting a possible price decline.
Moving Average Confirmation:
The indicator employs two moving averages: a short-term and a long-term moving average.
Buy and sell signals are confirmed only after a crossover event occurs, ensuring that trades are entered in alignment with market trends.
The short moving average crossing above the long moving average confirms a buy signal, while a crossover below confirms a sell signal.
Take Profit and Stop Loss Management:
The PMP includes adjustable take profit and stop loss levels, which are automatically calculated based on user-defined percentages.
Labels indicating the take profit (TP) and stop loss (SL) levels are plotted on the chart, helping traders manage their risk effectively.
Alerts are available for both TP and SL conditions, allowing traders to stay informed about their trade outcomes.
User-Friendly Interface:
The indicator provides an intuitive setup with adjustable parameters for moving average lengths, RSI levels, and TP/SL ratios.
Clear buy and sell signals are displayed directly on the chart, making it easy for traders to act on potential opportunities.
Usage:
The Price Movement Predictor is ideal for traders who seek a systematic approach to identify trading opportunities and manage risk. By combining RSI signals with moving average crossovers, the indicator helps filter out false signals and enhances the accuracy of trade entries. It is suitable for various trading styles, including day trading, swing trading, and long-term investing.
Z-Score RSI StrategyOverview
The Z-Score RSI Indicator is an experimental take on momentum analysis. By applying the Relative Strength Index (RSI) to a Z-score of price data, it measures how far prices deviate from their mean, scaled by standard deviation. This isn’t your traditional use of RSI, which is typically based on price data alone. Nevertheless, this unconventional approach can yield unique insights into market trends and potential reversals.
Theory and Interpretation
The RSI calculates the balance between average gains and losses over a set period, outputting values from 0 to 100. Typically, people look at the overbought or oversold levels to identify momentum extremes that might be likely to lead to a reversal. However, I’ve often found that RSI can be effective for trend-following when observing the crossover of its moving average with the midline or the crossover of the RSI with its own moving average. These crossovers can provide useful trend signals in various market conditions.
By combining RSI with a Z-score of price, this indicator estimates the relative strength of the price’s distance from its mean. Positive Z-score trends may signal a potential for higher-than-average prices in the near future (scaled by the standard deviation), while negative trends suggest the opposite. Essentially, when the Z-Score RSI indicates a trend, it reflects that the Z-score (the distance between the average and current price) is likely to continue moving in the trend’s direction. Generally, this signals a potential price movement, though it’s important to note that this could also occur if there’s a shift in the mean or standard deviation, rather than a meaningful change in price itself.
While the Z-Score RSI could be an insightful addition to a comprehensive trading system, it should be interpreted carefully. Mean shifts may validate the indicator’s predictions without necessarily indicating any notable price change, meaning it’s best used in tandem with other indicators or strategies.
Recommendations
Before putting this indicator to use, conduct thorough backtesting and avoid overfitting. The added parameters allow fine-tuning to fit various assets, but be careful not to optimize purely for the highest historical returns. Doing so may create an overly tailored strategy that performs well in backtests but fails in live markets. Keep it balanced and look for robust performance across multiple scenarios, as overfitting is likely to lead to disappointing real-world results.
DSL Strategy [DailyPanda]
Overview
The DSL Strategy by DailyPanda is a trading strategy that synergistically combines the idea from indicators to create a more robust and reliable trading tool. By integrating these indicators, the strategy enhances signal accuracy and provides traders with a comprehensive view of market trends and momentum shifts. This combination allows for better entry and exit points, improved risk management, and adaptability to various market conditions.
Combining ideas from indicators adds value by:
Enhancing Signal Confirmation : The strategy requires alignment between trend and momentum before generating trade signals, reducing false entries.
Improving Accuracy : By integrating price action with momentum analysis, the strategy captures more reliable trading opportunities.
Providing Comprehensive Market Insight : The combination offers a better perspective on the market, considering both the direction (trend) and the strength (momentum) of price movements.
How the Components Work Together
1. Trend Identification with DSL Indicator
Dynamic Signal Lines : Calculates upper and lower DSL lines based on a moving average (SMA) and dynamic thresholds derived from recent highs and lows with a specified offset. These lines adapt to market conditions, providing real-time trend insights.
ATR-Based Bands : Adds bands around the DSL lines using the Average True Range (ATR) multiplied by a width factor. These bands account for market volatility and help identify potential stop-loss levels.
Trend Confirmation : The relationship between the price, DSL lines, and bands determines the current trend. For example, if the price consistently stays above the upper DSL line, it indicates a bullish trend.
2. Momentum Analysis
RSI Calculation : Computes the RSI over a specified period to measure the speed and change of price movements.
Zero-Lag EMA (ZLEMA) : Applies a ZLEMA to the RSI to minimize lag and produce a more responsive oscillator.
DSL Application on Oscillator : Implements the DSL concept on the oscillator by calculating dynamic upper and lower levels. This helps identify overbought or oversold conditions more accurately.
Signal Generation : Detects crossovers between the oscillator and its DSL lines. A crossover above the lower DSL line signals potential bullish momentum, while a crossover below the upper DSL line signals potential bearish momentum.
3. Integrated Signal Filtering
Confluence Requirement : A trade signal is generated only when both the DSL indicator and oscillator agree. For instance, a long entry requires both an uptrend confirmation from the DSL indicator and a bullish momentum signal from the oscillator.
Risk Management Integration : The strategy uses the DSL indicator's bands for setting stop-loss levels and calculates take-profit levels based on a user-defined risk-reward ratio. This ensures that every trade has a predefined risk management plan.
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Originality and Value Added to the Community
Unique Synergy : While both indicators are available individually, this strategy is original in how it combines them to enhance their strengths and mitigate their weaknesses, offering a novel approach not present in existing scripts.
Enhanced Reliability : By requiring confirmation from both trend and momentum indicators, the strategy reduces false signals and increases the likelihood of successful trades.
Versatility : The customizable parameters allow traders to adapt the strategy to different instruments, timeframes, and trading styles, making it a valuable tool for a wide range of trading scenarios.
Educational Contribution : The script demonstrates an effective method of combining indicators for improved trading performance, providing insights that other traders can learn from and apply to their own strategies.
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How to Use the Strategy
Adding the Strategy to Your Chart
Apply the DSL Strategy to your desired trading instrument and timeframe on TradingView.
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Configuring Parameters
DSL Indicator Settings :
Length (len) : Adjusts the sensitivity of the DSL lines (default is 34).
Offset : Determines the look-back period for threshold calculations (default is 30).
Bands Width (width) : Changes the distance of the ATR-based bands from the DSL lines (default is 1).
DSL-BELUGA Oscillator Settings :
Beluga Length (len_beluga) : Sets the period for the RSI calculation in the oscillator (default is 10).
DSL Lines Mode (dsl_mode) : Chooses between "Fast" (more responsive) and "Slow" (smoother) modes for the oscillator's DSL lines.
Risk Management :
Risk Reward (risk_reward) : Defines your desired risk-reward ratio for calculating take-profit levels (default is 1.5).
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Interpreting Signals
Long Entry Conditions :
Trend Confirmation : Price is above the upper DSL line and the upper DSL band (dsl_up1 > dsl_dn).
Price Behavior : The last three candles have both their opens and closes above the upper DSL line.
Momentum Signal : The DSL-BELUGA oscillator crosses above its lower DSL line (up_signal), indicating bullish momentum.
Short Entry Conditions :
Trend Confirmation : Price is below the lower DSL line and the lower DSL band (dsl_dn < dsl_up1).
Price Behavior : The last three candles have both their opens and closes below the lower DSL band.
Momentum Signal : The DSL-BELUGA oscillator crosses below its upper DSL line (dn_signal), indicating bearish momentum.
Exit Conditions :
Stop-Loss : Automatically set at the DSL indicator's band level (upper band for longs, lower band for shorts).
Take-Profit : Calculated based on the risk-reward ratio and the initial risk determined by the stop-loss distance.
Visual Aids
Signal Arrows : Upward green arrows for long entries and downward blue arrows for short entries appear on the chart when conditions are met.
Stop-Loss and Take-Profit Lines : Red and green lines display the calculated stop-loss and take-profit levels for active trades.
Background Highlighting : The chart background subtly changes color to indicate when a signal has been generated.
Backtesting and Optimization
Use TradingView's strategy tester to backtest the strategy over historical data.
Adjust parameters to optimize performance for different instruments or market conditions.
Regularly review backtesting results to ensure the strategy remains effective.
VOLUME DIRECTION INDICATORDesigned for the 1-hour chart, this indicator shows:
Green Line: Volume when price rises, suggesting buying.
Red Line: Volume when price falls, indicating selling.
How to Use:
Watch for Crossover: When the Green Line moves above the Red, it might signal a budding uptrend.
Check Retracement: If the Green Line pulls back but stays above the Red, the uptrend could be strengthening.
Price Check: Look for a small price drop but not a reversal.
Trade Entry:
Enter at the high of the retracement candle.
Or wait for the Green Line to rise again.
For Precision: Draw a line at the retracement peak and switch to a shorter timeframe to find entry patterns above this line.
Remember: Use this with other tools for better trading decisions.
The Volume Direction Indicator provides a visual representation of market activity by assuming volume can be attributed to buying or selling based on price action within each bar. When the price closes higher than it opened, the volume for that period is considered as 'Bought Shares', plotted in green. Conversely, if the price closes lower, the volume is treated as 'Sold Shares', shown in red. This indicator resets daily to give a fresh perspective on trading activity each day.
Key Features:
Buying Pressure: Green line represents the cumulative volume during periods where the price increased.
Selling Pressure: Red line indicates the cumulative volume during price decreases.
Daily Reset: Accumulated values reset at the start of each new trading day, focusing on daily market sentiment.
Note: This indicator simplifies market dynamics by linking volume directly to price changes. It does not account for complex trading scenarios like short selling or market manipulations. Use this indicator as a tool to gauge general market direction and activity, not for precise transaction data.
Cosine-Weighted MA ATR [InvestorUnknown]The Cosine-Weighted Moving Average (CWMA) ATR (Average True Range) indicator is designed to enhance the analysis of price movements in financial markets. By incorporating a cosine-based weighting mechanism , this indicator provides a unique approach to smoothing price data and measuring volatility, making it a valuable tool for traders and investors.
Cosine-Weighted Moving Average (CWMA)
The CWMA is calculated using weights derived from the cosine function, which emphasizes different data points in a distinctive manner. Unlike traditional moving averages that assign equal weight to all data points, the cosine weighting allocates more significance to values at the edges of the data window. This can help capture significant price movements while mitigating the impact of outlier values.
The weights are shifted to ensure they remain non-negative, which helps in maintaining a stable calculation throughout the data series. The normalization of these weights ensures they sum to one, providing a proportional contribution to the average.
// Function to calculate the Cosine-Weighted Moving Average with shifted weights
f_Cosine_Weighted_MA(series float src, simple int length) =>
var float cosine_weights = array.new_float(0)
array.clear(cosine_weights) // Clear the array before recalculating weights
for i = 0 to length - 1
weight = math.cos((math.pi * (i + 1)) / length) + 1 // Shift by adding 1
array.push(cosine_weights, weight)
// Normalize the weights
sum_weights = array.sum(cosine_weights)
for i = 0 to length - 1
norm_weight = array.get(cosine_weights, i) / sum_weights
array.set(cosine_weights, i, norm_weight)
// Calculate Cosine-Weighted Moving Average
cwma = 0.0
if bar_index >= length
for i = 0 to length - 1
cwma := cwma + array.get(cosine_weights, i) * close
cwma
Cosine-Weighted ATR Calculation
The ATR is an essential measure of volatility, reflecting the average range of price movement over a specified period. The Cosine-Weighted ATR uses a similar weighting scheme to that of the CWMA, allowing for a more nuanced understanding of volatility. By emphasizing more recent price movements while retaining sensitivity to broader trends, this ATR variant offers traders enhanced insight into potential price fluctuations.
// Function to calculate the Cosine-Weighted ATR with shifted weights
f_Cosine_Weighted_ATR(simple int length) =>
var float cosine_weights_atr = array.new_float(0)
array.clear(cosine_weights_atr)
for i = 0 to length - 1
weight = math.cos((math.pi * (i + 1)) / length) + 1 // Shift by adding 1
array.push(cosine_weights_atr, weight)
// Normalize the weights
sum_weights_atr = array.sum(cosine_weights_atr)
for i = 0 to length - 1
norm_weight_atr = array.get(cosine_weights_atr, i) / sum_weights_atr
array.set(cosine_weights_atr, i, norm_weight_atr)
// Calculate Cosine-Weighted ATR using true ranges
cwatr = 0.0
tr = ta.tr(true) // True Range
if bar_index >= length
for i = 0 to length - 1
cwatr := cwatr + array.get(cosine_weights_atr, i) * tr
cwatr
Signal Generation
The indicator generates long and short signals based on the relationship between the price (user input) and the calculated upper and lower bands, derived from the CWMA and the Cosine-Weighted ATR. Crossover conditions are used to identify potential entry points, providing a systematic approach to trading decisions.
// - - - - - CALCULATIONS - - - - - //{
bar b = bar.new()
float src = b.calc_src(cwma_src)
float cwma = f_Cosine_Weighted_MA(src, ma_length)
// Use normal ATR or Cosine-Weighted ATR based on input
float atr = atr_type == "Normal ATR" ? ta.atr(atr_len) : f_Cosine_Weighted_ATR(atr_len)
// Calculate upper and lower bands using ATR
float cwma_up = cwma + (atr * atr_mult)
float cwma_dn = cwma - (atr * atr_mult)
float src_l = b.calc_src(src_long)
float src_s = b.calc_src(src_short)
// Signal logic for crossovers and crossunders
var int signal = 0
if ta.crossover(src_l, cwma_up)
signal := 1
if ta.crossunder(src_s, cwma_dn)
signal := -1
//}
Backtest Mode and Equity Calculation
To evaluate its effectiveness, the indicator includes a backtest mode, allowing users to test its performance on historical data:
Backtest Equity: A detailed equity curve is calculated based on the generated signals over a user-defined period (startDate to endDate).
Buy and Hold Comparison: Alongside the strategy’s equity, a Buy-and-Hold equity curve is plotted for performance comparison.
Visualization and Alerts
The indicator features customizable plots, allowing users to visualize the CWMA, ATR bands, and signals effectively. The colors change dynamically based on market conditions, with clear distinctions between long and short signals.
Alerts can be configured to notify users of crossover events, providing timely information for potential trading opportunities.
