EMA Proximity AlertThe EMA Proximity Alert Indicator is designed to help traders identify when the price of an asset is close to a set of user-defined Exponential Moving Averages (EMAs). This indicator is particularly useful for those who use multiple EMAs as part of their trading strategy and want to receive alerts when the price approaches these key levels.
Features
Customizable EMAs:
The indicator supports four customizable EMAs with default periods of 9, 21, 55, and 100. Users can adjust the lengths of these EMAs according to their preferences.
Proximity Alerts:
Users can set a proximity percentage for each EMA individually. The indicator will generate an alert when the closing price is within the specified percentage of the EMA.
Visual Representation:
The EMAs are plotted on the chart with distinct colors:
EMA 1 (default 9) - Blue
EMA 2 (default 21) - Orange
EMA 3 (default 55) - Green
EMA 4 (default 100) - Red
Background Highlight:
The background of the chart will be highlighted in a semi-transparent color when the price is close to any of the monitored EMAs, making it easy to identify these areas at a glance.
Alert Conditions:
The indicator includes alert conditions that can be used to trigger notifications in TradingView. When the price is close to a monitored EMA, an alert is triggered with a message indicating which EMA is close.
Tooltip Symbols:
When the price is within the specified proximity to a monitored EMA, a small circular symbol is plotted above the bar. Hovering over this symbol displays a tooltip with information about the proximity, including the EMA length and the percentage.
Moving Averages
Pivot Points with MID LevelsThis indicator shows the Standard Pivot Points level based on daily values that can act as support and resistance. It is used by a variety of traders around the world. You can select which time frame Pivot Point Levels you'd like. Daily, weekly etc... Perfect for swing trading or day trading.
Pivot Points- Shows 3 levels of resistance, the Pivot Point and 3 levels of support
(R3, R2, R1, PIVOT POINT, S1, S2, S3
MID Levels- The MID levels are 50% retracement from the pivot point level above it and below
Example- R3, MID, R2, MID, R1, MID, PIVOT POINT, MID, S1, MID, S2, MID, S3
With this indicator you will also have the option to show the Previous days High and Low that are also important levels. On gap up/down days it is always interesting to see if price will close the gap, hence the important level to note.
PDH= Previous Days High
PDL= Previous Days Low
I have added a feature that you can now select specific color to each level and the line style for each level to help understand which levels are being show by personal needs.
Happy Trading
Nasan Moving Average with ForecastThe "Nasan Moving Average with Forecast" indicator is a technical analysis forecasting tool that combines the principles of historical data analysis and random walk theory. It calculates a customized moving average (Nasan Moving Average) by integrating price data and statistical measures and projects future price points by generating forecast values within calculated volatility bounds, creating a dynamic and insightful visualization of potential market movements. This indicator to blend past market behavior with probabilistic future trends to enhance forecasting.
Input Parameters:
len: Differencing length (default 21, Use a minimum of 5 and for lower time frames less than 15 min use values between 300 -3000)
len1: Correction Factor Length 1 (default 21, this determines the length of the MA you want , eg. 10 MA, 50 MA, 100 MA, )
len2: Correction Factor Length 2 (default 9, this works best if it is ~ </=1/2 of len1 )
len3: Smoothing Length (default 5, I would not change this and only use if I want to introduce lag where you want to use it for cross over strategies).
forecast_points: Number of points to forecast (default 30).
m: Multiplier for standard deviation (default 2.5).
bl: Block length for calculating max/min values (default 100).
use_calculated_max_min: Boolean to decide whether to use calculated max/min values.
Nasan Moving Average Calculation:
Calculates the simple moving average (mean) and standard deviation (sd) of the typical price (hlc3).
Computes intermediate variables (a, b, c, etc.) based on log transformation and cumulative sum.
Applies weighted moving averages (wma) to these intermediate variables to smooth them and derive the final value c6.
Plots c6 as the Nasan Moving Average if the bar is confirmed. To learn more see Nasan Moving Average.
Forecast Points Calculation:
Calculates maximum (max_val) and minimum (min_val) values for the forecast, either using a fixed value or based on standard deviation and a multiplier.
Initializes an array to store forecast values and creates polyline objects for plotting.
If the current bar is one of the last three bars and confirmed:
Clears and reinitializes the polyline.
Initializes the first forecast value from the cumulative sum c.
Generates subsequent forecast values using a random value within the range .
Updates the forecast array and plots the forecast points as an orange curved polyline.
Plotting Max/Min Values:
Plots max_val and min_val as green and red lines, respectively, to indicate the bounds of the forecast range.
Components of the Forecasting Model
Historical Dependence:
Nasan Moving Average Calculation: The script calculates a custom moving average (c6) that incorporates historical price data (hlc3), standard deviations (sd), and weighted moving averages (wma). This part of the code processes historical data to create a smoothed representation of the price trend.
Max/Min Value Calculation: The maximum (max_val) and minimum (min_val) values for the forecast can be calculated based on the historical standard deviation of a transformed variable b over a block length (bl). This introduces historical volatility into the bounds for the forecast.
Random Walk Model:
Random Value Generation: Within the forecast points calculation, a random value (random_val) is generated for each forecast point within the range . This random value introduces stochasticity into the model, characteristic of a random walk process.
Cumulative Sum for Forecasting: The script uses a cumulative sum (prev_f + random_val) to generate the next forecast point (next_f). This is a typical approach in random walk models where each new point is based on the previous point plus some random noise.
Explanation of the Forecast Model
Random Walk Characteristics: Each new forecast point is generated by adding a random value to the previous point, making the model a random walk with drift, where the drift is influenced by historical correction factors (c1, c4).
Historical and Statistical Dependence: The bounds of the random values and the initial conditions are derived from historical data, ensuring that the forecast respects historical volatility and trends.
The forecasting model in the script is a hybrid approach: It uses a random walk to generate future points, characterized by adding random values to the previous forecasted value.
The historical and statistical dependence is incorporated through initial conditions, scaling factors, and bounds derived from historical price data and its statistical properties.
This combination ensures that the forecasts are not purely stochastic but are grounded in historical price behavior, making the model more robust and potentially more accurate in reflecting market conditions.
Nasan Moving AverageNasan Moving Average belong to the group of moving average which provides a high degree of smoothness with very low lag.
The calculation process involves several steps to analyze the typical price of a financial asset over specific periods. It starts by computing a simple moving average and standard deviation of the typical price. Then, it standardizes (differencing TP - Average Typical price over previous n periods) the price and applies an inverse hyperbolic sine transformation to the standardized value. The transformed values are summed cumulatively, and various weighted moving averages are calculated to adjust and smooth the data. The final output is a smoothed signal with reduced lag.
Input Parameters:
len: Differencing length (default 21, Use a minimum of 5 and for lower time frames less than 15 min use values between 300 -3000)
len1: Correction Factor Length 1 (default 21, this determines the length of the MA you want , eg. 10 MA, 50 MA, 100 MA, )
len2: Correction Factor Length 2 (default 9, this works best if it is ~ </=1/2 of len1 )
len3: Smoothing Length (default 5, I would not change this and only use if I want to introduce lag where you want to use it for cross over strategies).
Differencing and Standardization:
The code calculates the standardized price a by differencing the typical price and normalizing it using the mean and standard deviation. This step standardizes the price changes.
Transformation:
The transformation using logarithms and square roots (b) aim to stabilize the variance and make the distribution more normal-like, improving the robustness of the cumulative sum c.
Cumulative Sum:
The cumulative sum c of the transformed series helps in integrating the series over time, capturing the overall trend and movement.
Correction Factors:
Correction factors c1 and c4 adjust the cumulative sum based on weighted averages, to correct any biases or to align it with the typical price.
Smoothing:
The final result c6 is smoothed using a weighted moving average, reducing noise and making it easier to interpret trends.
Moving average to price cloudHi all!
This indicator shows when the price crosses the defined moving average. It plots a green or red cloud (depending on trend) and the moving average. It also plots an arrow when the trend changes (this can be disabled in 'style'->'labels' in the settings).
The moving average itself can be used as dynamic support/resistance. The trend will change based on your settings (described below). By default the trend will change when the whole bar is above/below the moving average for 2 bars (that's closed). This can be changed by "Source" and "Bars".
Settings
• Length (choose the length of the moving average. Defaults to 21)
• Type (choose what type of moving average).
- "SMA" (Simple Moving Average)
- "EMA" (Exponential Moving Average)
- "HMA" (Hull Moving Average)
- "WMA" (Weighted Moving Average)
- "VWMA" (Volume Weighted Moving Average)
- "DEMA" (Double Exponential Moving Average)
Defaults to"EMA".
• Source (Define the price source that must be above/below the moving average for the trend to change. Defaults to 'High/low (passive)')
- 'Open' The open of the bar has to cross the moving average
- 'Close' The close of the bar has to cross the moving average
- 'High/low (passive)' In a down trend: the low of the bar has to cross the moving average
- 'High/low (aggressive)' In a down trend: the high of the bar has to cross the moving average
• Source bar must be close. Defaults to 'true'.
• Bars (Define the number bars whose value (defined in 'Source') must be above/below the moving average. All the bars (defined by this number) must be above/below the moving average for the trend to change. Defaults to 2.)
Let me know if you have any questions.
Best of trading luck!
Uptrick: Complex WMA Indicator with Trend Transitions
The "Complex WMA Indicator with Trend Transitions" is a technical analysis tool designed to help traders identify and visualize market trends using three Weighted Moving Averages (WMAs) of varying lengths. The primary purpose of this indicator is to provide a clearer and more nuanced view of market trends by highlighting bullish and bearish phases and filtering out noise, thereby enabling more informed trading decisions.
Detailed Explanation
This indicator allows users to set the lengths of three WMAs through input parameters. The default lengths are set to 10, 20, and 50, but users can customize these values according to their trading strategy. The WMAs are calculated using the closing prices of the specified periods, and the results are plotted on the chart in red, green, and blue, corresponding to the first, second, and third WMAs, respectively.
The indicator defines two primary conditions for trend analysis: bullish and bearish trends. A bullish trend is identified when both the shorter WMAs (first and second) are above the longest WMA (third), indicating upward momentum. Conversely, a bearish trend is identified when both the shorter WMAs are below the longest WMA, signaling downward momentum.
Crossover Signals and Trend Transitions
The script also identifies crossover signals between the first and second WMAs. A bullish crossover occurs when the first WMA crosses above the second WMA, generating a buy signal. This event is marked on the chart with a green upward label. A bearish crossover, marked with a red downward label, occurs when the first WMA crosses below the second WMA, indicating a sell signal.
To track the trend transitions effectively, the indicator employs a state machine. It maintains two variables, currentTrend and prevTrend, to store the current and previous trend states. The trend state is updated based on the defined trend conditions. When the trend changes from one state to another (e.g., from a bullish trend to a bearish trend), the indicator creates a label at the beginning of the new trend to mark this transition. This helps traders quickly recognize significant changes in market direction.
Visual Enhancements
The indicator enhances visual clarity by coloring the background of the chart based on the identified trend. When a bullish trend is detected, the background turns green, and when a bearish trend is identified, it turns red. The script ensures that only clear bullish and bearish trends are highlighted by excluding the "No Clear Trend" state, which reduces noise and prevents false signals.
Alerts
To further aid traders, the indicator includes alert conditions for both bullish and bearish crossovers. These alerts notify traders when a crossover occurs, enabling them to take timely action based on the identified signals.
Purpose and Unique Features
The primary purpose of the "Complex WMA Indicator with Trend Transitions" is to provide traders with a more precise and actionable analysis of market trends. Unlike simple moving average indicators, this tool uses multiple WMAs and incorporates a state machine to track and highlight trend transitions more effectively. By focusing on clear trend signals and filtering out noise, it helps traders make more informed decisions.
This indicator differs from other moving average-based tools in several ways:
Multi-WMA Analysis: It uses three WMAs of different lengths, providing a more comprehensive view of the market trend.
State Machine for Trends: The use of a state machine to track trend transitions ensures that only significant trends are highlighted, reducing noise.
Visual Clarity: The combination of colored backgrounds and labeled transitions makes it easier for traders to identify and act on trends.
Customization: Users can adjust the lengths of the WMAs to suit their trading strategies, making the indicator versatile.
In summary, the "Complex WMA Indicator with Trend Transitions" offers a sophisticated and customizable approach to trend analysis, providing clear visual cues and alerts for significant market movements, which sets it apart from simpler moving average indicators.
Support and Resistance Breakouts By RICHIESupport and resistance are fundamental concepts in technical analysis used to identify price levels on charts that act as barriers, preventing the price of an asset from getting pushed in a certain direction. Here’s a detailed description of each and how breakout strategies are typically used:
Support
Support is a price level where a downtrend can be expected to pause due to a concentration of demand. As the price of an asset drops, it hits a level where buyers tend to step in, causing the price to rebound.
Support Level Identification: Support levels are identified by looking at historical data where prices have repeatedly fallen to a certain level but have then rebounded.
Strength of Support: The more times an asset price hits a support level without breaking below it, the stronger that support level is considered to be.
Resistance
Resistance is a price level where an uptrend can be expected to pause due to a concentration of selling interest. As the price of an asset increases, it hits a level where sellers tend to step in, causing the price to drop.
Resistance Level Identification: Resistance levels are identified by looking at historical data where prices have repeatedly risen to a certain level but have then fallen back.
Strength of Resistance: The more times an asset price hits a resistance level without breaking above it, the stronger that resistance level is considered to be.
Breakouts
A breakout occurs when the price moves above a resistance level or below a support level with increased volume. Breakouts can be significant because they suggest a change in supply and demand dynamics, often leading to strong price movements.
Breakout Above Resistance: Indicates a bullish market sentiment. Traders often interpret this as a sign to enter a long position (buy).
Breakout Below Support: Indicates a bearish market sentiment. Traders often interpret this as a sign to enter a short position (sell).
Breakout Trading Strategies
Confirmation: Wait for a candle to close beyond the support or resistance level to confirm the breakout.
Volume: Increased volume on a breakout adds credibility, suggesting that the price move is supported by strong buying or selling interest.
Retest: Sometimes, after a breakout, the price will return to the breakout level to test it as a new support or resistance. This retest offers another entry point.
Stop-Loss: Place stop-loss orders just below the resistance (for long positions) or above the support (for short positions) to limit potential losses in case of a false breakout.
Take-Profit: Identify target levels for taking profits. These can be set based on previous support/resistance levels or using tools like Fibonacci retracements.
MAHA Luxmi AI Candles [Overlay]The MAHA Luxmi AI Candles trading indicator is a sophisticated tool designed to assist traders in identifying potential trading opportunities by utilizing a combination of Moving Average (MA) and Heikin-Ashi (HA) techniques, further enhanced with a custom formula. Here’s a detailed breakdown of its functionalities:
1. Integration of MA and HA Techniques
MAHA stands for Moving Average and Heikin-Ashi. This indicator modifies these traditional techniques with a unique custom formula, aiming to provide more accurate and reliable signals for traders. The combination enhances the smoothing effect of Moving Averages with the trend indication of Heikin-Ashi candles.
2. Four-Colored Candles for Trend Indication
The indicator uses a color-coded system to denote different market conditions and potential trading opportunities:
- Green Candles: These candles indicate a potential long opportunity. The appearance of a green candle suggests that the market is showing bullish tendencies, prompting traders to consider entering a long position.
- Blue Candles: These candles signify an active pullback within a bullish trend. The blue candle warns traders of a possible temporary reversal within the overall bullish trend, suggesting caution and the need for confirmation before continuing with a long position or preparing for a potential reversal.
- Red Candles: These candles represent a potential short opportunity. A red candle indicates bearish market conditions, signaling traders to consider entering a short position.
- Yellow Candles: These candles denote an active pullback within a bearish trend. The presence of a yellow candle indicates a temporary reversal within the bearish trend, urging traders to be cautious with short positions and look for signs of continuation or reversal.
3. MAHA Bars for Distance and Area of Interest
In addition to the colored candles, the MAHA Luxmi AI Candles indicator also plots MAHA bars. These bars share the same color coding and usage as the candles, providing a consistent visual representation of market conditions:
- Green Bars: Indicate a potential long opportunity, aligning with green candles.
- Blue Bars: Show an active pullback in a bullish trend, aligning with blue candles.
- Red Bars: Represent a potential short opportunity, aligning with red candles.
- Yellow Bars: Indicate an active pullback in a bearish trend, aligning with yellow candles.
The MAHA bars help traders gauge the distance between the current price and the area of interest, enhancing their understanding of how close or far the price is from key levels identified by the MAHA formula. This aids in making better decisions regarding entry and exit points.
4. Trailing Stop Loss Feature
The base of the MAHA Bars can also be used as a trailing stop loss. This feature provides a dynamic stop loss level that adjusts with the market, helping traders lock in profits and limit losses by following the trend. When the price moves favorably, the trailing stop loss adjusts accordingly, ensuring that traders can capitalize on market movements while minimizing risk.
Usage and Benefits
- Trend Identification: The color-coded system simplifies the identification of market trends and potential reversals, making it easier for traders to understand market dynamics at a glance.
- Pullback and Reversal Alerts: The blue and yellow candles/bars alert traders to potential pullbacks and reversals, providing crucial information for managing trades and avoiding false signals.
- Distance Measurement: The MAHA bars help traders measure the distance between the current price and the areas of interest, enhancing their ability to assess the risk and potential reward of trades.
- Trailing Stop Loss: The base of the MAHA Bars can be used as a trailing stop loss, providing a dynamic risk management tool that adapts to market conditions.
Overall, the MAHA Luxmi AI Candles trading indicator is a powerful tool for traders looking to leverage the combined strengths of Moving Averages and Heikin-Ashi techniques. The intuitive color-coded system, additional MAHA bars, and the trailing stop loss feature make it an essential component of a trader’s toolkit for identifying trends, managing risk, and identifying trading opportunities.
IsAlgo - Support & Resistance Strategy► Overview:
The Support & Resistance Strategy is designed to identify critical support and resistance levels and execute trades when the price crosses these levels. Utilizing a combination of a moving average, ATR indicator, and the highest and lowest prices, this strategy aims to accurately pinpoint entry and exit points for trades based on market movements.
► Description:
The Support & Resistance Strategy leverages the ATR (Average True Range) and a moving average to identify key support and resistance levels. The strategy calculates these levels by measuring the distance between the current market price and the moving average. This distance is continuously compared with each new candle to provide an estimate of the support and resistance levels.
The ATR is utilized to determine the width of these levels, ensuring they adjust to market volatility. To validate these levels, the strategy counts how often a candle’s low or high touches the estimated support or resistance and then bounces back. A higher frequency of such touches indicates a stronger, more reliable level.
Once the levels are confirmed, the strategy waits for a candle to close above the resistance level or below the support level. A candle closing above the resistance triggers a long entry, while a candle closing below the support triggers a short entry.
The strategy incorporates multiple stop-loss options to manage risk effectively. These options include setting stop-loss levels based on fixed pips, ATR calculations, or the highest/lowest prices of previous candles. Up to three take-profit levels can be set using fixed pips, ATR, or risk-to-reward ratios. A trailing stop feature adjusts the stop loss as the trade moves into profit, and a break-even feature moves the stop loss to the entry price once a certain profit level is reached.
Additionally, the strategy can close trades if the price crosses the opposite support or resistance level or if a candle moves significantly against the trade direction.
↑ Long Entry Example:
↓ Short Entry Example:
► Features & Settings:
⚙︎ Levels: Configure the length, width, and ATR period for support and resistance levels.
⚙︎ Moving Average: Use an Exponential Moving Average (EMA) to confirm trend direction. This can be enabled or disabled.
⚙︎ Entry Candle: Define the minimum and maximum body size and the body-to-candle size ratio for entry candles.
⚙︎ Trading Session: Specify the trading hours during which the strategy operates.
⚙︎ Trading Days: Select which days of the week the strategy is active.
⚙︎ Backtesting: Set a backtesting period with start and end dates. This feature can be deactivated.
⚙︎ Trades: Customize trade direction (long, short, or both), position sizing (fixed or percentage-based), maximum open trades, and daily trade limits.
⚙︎ Trades Exit: Choose from various exit methods, including profit/loss limits, trade duration, or crossing the opposite support/resistance level.
⚙︎ Stop Loss: Set stop-loss levels using fixed pips, ATR-based calculations, or the highest/lowest price within a specified number of previous candles.
⚙︎ Break Even: Adjust the stop loss to break-even once certain profit conditions are met.
⚙︎ Trailing Stop: Automatically adjust the stop loss as the trade moves into profit.
⚙︎ Take Profit: Define up to three take-profit levels using fixed pips, ATR, or risk-to-reward ratios based on the stop loss.
⚙︎ Alerts: Receive alerts for significant actions such as trade openings and closings, with support for dynamic values.
⚙︎ Dashboard: A visual display on the chart providing detailed information about ongoing and past trades.
► Backtesting Details:
Timeframe: 1-hour US30 chart
Initial Balance: $10,000
Order Size: 5 Units
Commission: $0.5 per contract
Slippage: 5 ticks
Stop Loss: Based on the opposite support/resistance level or break-even adjustments
Median Moving Average @shrilssThe "Median Moving Average" (MMA) It allows users to select from two moving average lengths—short and long—and plots the median moving average, which is the midpoint between these two averages. Colored green for upward trends and red for downward trends, enhancing visual analysis.
Additionally, users can choose from a range of moving average types including Simple (SMA), Exponential (EMA), Weighted (WMA), Double Exponential (DEMA), Triple Exponential (TEMA), Hull (HMA), and Volume Weighted (VWMA).
Color Hull Moving AverageDescription:
The Color Hull Moving Average (CHMA) is a technical indicator designed to smooth and remove lag from traditional moving averages, making it more responsive to price movements. This indicator automatically adjusts the color of the moving average to green when it is rising and red when it is falling, helping to identify trends in a more visual and sophisticated way.
Characteristics:
Period: User configurable (default: 20)
Data Source: Can be applied to any price series, such as closing, opening, high, low, etc.
Dynamic Colors: The HMA line changes color based on its direction, making it easy to see trends.
Green: Uptrend
Red: Downtrend
How to use:
Period Configuration: Adjust the period to improve improvements and reactivity according to the asset and timeframe analyzed.
Color Interpretation: Use color changes to identify inflection points in the market.
Combination with Other Indicators: The HMA can be combined with other technical indicators to validate entry and exit signals.
Warning: Although HMA is a powerful tool, we recommend using it in conjunction with other forms of analysis for best results.
Combined IndicatorSummary
This custom Pine Script combines three main indicators into one, each with its own functionalities and visual cues. It provides a comprehensive approach to trend analysis by integrating short-term, medium-term, and long-term indicators. Each part of the indicator can be toggled on or off independently to suit the trader’s needs.
Part 1: EMA 14 and EMA 200
Purpose: This part of the indicator is designed to identify short-term and long-term trends using Exponential Moving Averages (EMA). It helps traders spot potential entry and exit points based on the relationship between short-term and long-term moving averages.
Visuals:
• EMA 14: Plotted in blue (#2962ff)
• EMA 200: Plotted in red (#f23645)
Signals:
• Long Signal: Generated when EMA 14 crosses above EMA 200, indicating a potential upward trend.
• Short Signal: Generated when EMA 14 crosses below EMA 200, indicating a potential downward trend.
Usage: Toggle this part on or off using the checkbox input to focus on short-term vs. long-term trends.
Part 2: EMA 9 and SMA 20
Purpose: This part combines Exponential and Simple Moving Averages to provide a medium-term trend analysis. It helps smooth out price data and identify potential trend reversals and continuation patterns.
Visuals:
• EMA 9: Plotted in green
• SMA 20: Plotted in dark red
Usage: Toggle this part on or off using the checkbox input to focus on medium-term trends and price smoothing.
Part 3: Golden Cross and Death Cross
Purpose: This part identifies long-term bullish and bearish market conditions using the 50-day and 200-day Simple Moving Averages (SMA). It highlights major trend changes that can inform long-term investment decisions.
Visuals:
• 50-day SMA: Plotted in gold (#ffe600)
• 200-day SMA: Plotted in black
Signals:
• Golden Cross: Generated when the 50-day SMA crosses above the 200-day SMA, indicating a potential long-term upward trend.
• Death Cross: Generated when the 50-day SMA crosses below the 200-day SMA, indicating a potential long-term downward trend.
Usage: Toggle this part on or off using the checkbox input to focus on long-term trend changes.
How to Use
1. Enable/Disable Indicators: Use the checkboxes provided in the input settings to enable or disable each part of the indicator according to your analysis needs.
2. Interpret Signals: Look for crossover events to determine potential entry and exit points based on the relationship between the moving averages.
3. Visual Confirmation: Use the color-coded lines and shape markers on the chart to visually confirm signals and trends.
4. Customize Settings: Adjust the lengths of the EMAs and SMAs in the input settings to suit your trading strategy and the specific asset you are analyzing.
Practical Application
• Short-Term Trading: Use the EMA 14 and EMA 200 signals to identify quick trend changes.
• Medium-Term Trading: Use the EMA 9 and SMA 20 to capture medium-term trends and reversals.
• Long-Term Investing: Monitor the Golden Cross and Death Cross signals to make decisions based on long-term trend changes.
Example of Unique Features
• Integrated Toggle System: Allows users to enable or disable specific parts of the indicator to customize their analysis.
• Multi-Tier Trend Analysis: Combines short-term, medium-term, and long-term indicators to provide a comprehensive view of the market.
IsAlgo - Reverse Candle Strategy► Overview:
The Reverse Candle Strategy leverages a customizable moving average to identify the start of a trend. It utilizes the highest and lowest prices to define the trend and its corrections, executing trades based on custom candlestick patterns to capitalize on the main trend's continuation.
► Description:
The Reverse Candle Strategy is designed to effectively identify and trade market trends by combining moving averages and custom candlestick patterns. The core of the strategy is a single, customizable moving average, which helps determine the trend direction. When the market price crosses above the moving average, this signifies the beginning of an uptrend. The strategy then tracks the highest price reached during the uptrend and waits for a correction. A specific custom candlestick pattern signals the end of the correction, at which point the strategy executes a long trade.
In the case of a downtrend, the market price crossing below the moving average marks the trend’s start. The strategy monitors the lowest price during the downtrend and awaits a correction. The end of this correction is identified by another custom candlestick pattern, prompting the strategy to execute a short trade. This combination of a moving average with precise candlestick patterns ensures that trades are made at optimal moments, improving the likelihood of successful trades.
The integration of the moving average and candlestick patterns is critical. The moving average smooths out price data to highlight the trend direction, while the custom candlestick patterns provide specific entry signals after a correction, ensuring the trend’s resumption is genuine. This synergy enhances the strategy’s ability to filter out false signals and improve trade accuracy.
↑ Long Entry Example:
When the price is moving above the moving average and the highest price has been detected, the strategy will wait for the entry candle to execute the long trade.
↓ Short Entry Example:
When the price is moving below the moving average and the lowest price has been detected, the strategy will wait for the entry candle to execute the short trade.
✕ Exit Conditions:
To manage risk effectively, the strategy provides multiple stop-loss options. Traders can set stop-loss levels using fixed pips, ATR-based calculations, or the higher/lower price of past candles. Additionally, trades can be closed if a candle moves against the trade direction. Up to three take-profit levels can be set using fixed pips, ATR, or risk-to-reward ratios, allowing traders to secure profits at different stages. The trailing stop feature adjusts the stop loss as the trade moves into profit, locking in gains while allowing for continued potential upside. Furthermore, a break-even feature moves the stop loss to the entry price once a certain profit level is reached, protecting against losses. Trades can also be closed when the price crosses the moving average.
► Features & Settings:
⚙︎ Moving Average: Users can choose between various types of moving averages (e.g., SMA, EMA) to confirm the trend direction.
⚙︎ Trend & Corrections: Set minimum and maximum pips for trends and corrections, with an option to define correction percentages relative to the trend.
⚙︎ Entry Candle: Define the entry candle by specifying the minimum and maximum size of the candle's body and the ratio of the body to the entire candle size, ensuring significant breakouts trigger trades.
⚙︎ Trading Session: This feature allows users to define specific trading hours during which the strategy should operate, ensuring trades are executed only during preferred market periods.
⚙︎ Trading Days: Users can specify which days the strategy should be active, offering the flexibility to avoid trading on specific days of the week.
⚙︎ Backtesting: Enables a backtesting period during which the strategy can be tested over a selected start and end date. This feature can be deactivated if not needed.
⚙︎ Trades: Configure trade direction (long, short, or both), position sizing (fixed or percentage-based), maximum number of open trades, and daily trade limits.
⚙︎ Trades Exit: Various exit methods, such as setting profit or loss limits, trade duration, or closing trades on moving average crossings.
⚙︎ Stop Loss: Various stop-loss methods are available, including a fixed number of pips, ATR-based, or using the highest or lowest price points within a specified number of previous candles. Additionally, trades can be closed after a specific number of candles move in the opposite direction of the trade.
⚙︎ Break Even: This feature adjusts the stop loss to a break-even point once certain conditions are met, such as reaching predefined profit levels, to protect gains.
⚙︎ Trailing Stop: The trailing stop feature adjusts the stop loss as the trade moves into profit, securing gains while potentially capturing further upside.
⚙︎ Take Profit: up to three take-profit levels using fixed pips, ATR, or risk-to-reward ratios based on the stop loss. Alternatively, specify a set number of candles moving in the trade direction.
⚙︎ Alerts: The strategy includes a comprehensive alert system that informs the user of all significant actions, such as trade openings and closings. It supports placeholders for dynamic values like take-profit levels and stop-loss prices.
⚙︎ Dashboard: Visual display providing detailed information about ongoing and past trades on the chart, helping users monitor performance and make informed decisions.
► Backtesting Details:
Timeframe: 30-minute NAS100 chart
Initial Balance: $10,000
Order Size: 5 Units
Commission: $0.5 per contract
Slippage: 5 ticks
Stop Loss: MA Crossing or by break even
Guppy Wave [UkutaLabs]█ OVERVIEW
The Guppy Wave Indicator is a collection of Moving Averages that provide insight on current market strength. This is done by plotting a series of 12 Moving Averages and analysing where each one is positioned relative to the others.
In doing this, this script is able to identify short-term moves and give an idea of the current strength and direction of the market.
The aim of this script is to simplify the trading experience of users by automatically displaying a series of useful Moving Averages to provide insight into short-term market strength.
█ USAGE
The Guppy Wave is generated using a series of 12 total Moving Averages composed of 6 Small-Period Moving Averages and 6 Large Period Moving Averages. By measuring the position of each moving average relative to the others, this script provides unique insight into the current strength of the market.
Rather than simply plotting 12 Moving Averages, a color gradient is instead drawn between the Moving Averages to make it easier to visualise the distribution of the Guppy Wave. The color of this gradient changes depending on whether the Small-Period Averages are above or below the Large-Period Averages, allowing traders to see current short-term market strength at a glance.
When the gradient fans out, this indicates a rapid short-term move. When the gradient is thin, this indicates that there is no dominant power in the market.
█ SETTINGS
• Moving Average Type: Determines the type of Moving Average that get plotted (EMA, SMA, WMA, VWMA, HMA, RMA)
• Moving Average Source: Determines the source price used to calculate Moving Averages (open, high, low, close, hl2, hlc3, ohlc4, hlcc4)
• Bearish Color: Determines the color of the gradient when Small-Period MAs are above Large-Period MAs.
• Bullish Color: Determines the color of the gradient when Small-Period MAs are below Large-Period MAs.
Fibonacci Moving Averages [UkutaLabs]█ OVERVIEW
The Fibonacci Moving Averages are a toolkit which allows the user to configure different types of Moving Averages based on key Fibonacci numbers.
Moving Averages are used to visualise short-term and long-term support and resistance which can be used as a signal where price might continue or retrace. Moving Averages serve as a simple yet powerful tool that can help traders in their decision-making and help foster a sense of where the price might be moving next.
The aim of this script is to simplify the trading experience of users by automatically displaying a series of useful Moving Averages, allowing the user to easily configure multiple at once depending on their trading style.
█ USAGE
This script will automatically plot 5 Moving Averages, each with a period of a key Fibonacci Level (5, 8, 13, 21 and 34).
Both the Source and Type of the Moving Averages can be configured by the user (see all options below under SETTINGS), making this a versatile trading tool that can provide value in a wide variety of trading styles.
█ SETTINGS
Configuration
• MA Source: Determines the source of the Moving Averages (open, high, low, close, hl2, hlc3, ohlc4, hlcc4)
• MA Source: Determines the type of the Moving Averages (SMA, EMA, VWMA, WMA, HMA, RMA)
Colors
• 5: Determines the color of the 5 period Moving Average
• 8: Determines the color of the 8 period Moving Average
• 13: Determines the color of the 13 period Moving Average
• 21: Determines the color of the 21 period Moving Average
• 34: Determines the color of the 34 period Moving Average
High Probability OS/OB {DCAquant}DCAquant - High Probability OS/OB
The DCAquant - High Probability OS/OB Pine Script is a sophisticated indicator that provides insights into overbought (OB) and oversold (OS) conditions based on Hull Moving Averages (HMA) and Volume Weighted Moving Averages (VWMA). Here's a detailed breakdown of its functionality:
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THIS INDICATOR IS ONLY WRITTEN FOR BTC, ETH and TOTAL!!!!!!!!!!!!!
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Functionality
The script identifies high-probability OB and OS zones by combining multiple moving averages (MAs).
1. Volume Weighted Moving Average (VWMA)
The VWMA function computes the VWMA over a specified length, incorporating both the price and volume.
2. Hull Moving Average with Volume Weight (HMA-VW)
The hullma_vw function calculates the HMA using the VWMA. This involves:
Computing VWMAs over the full length and half-length.
Using these VWMAs to derive the HMA-VW through a weighted approach.
5. Standard Hull Moving Average (HMA)
The hull function computes the HMA using the standard weighted moving average (WMA).
4. Smoothed HMA-VW
This is an Exponential Moving Average (EMA) of the HMA-VW to smooth out short-term fluctuations.
How this works
First, the distance between the 2 MA's is calculated.
The distance is scored against the average price of the last 100 days.
By getting this score we can calculate extremes
The Extremes are categorized into 4 levels. The transparency of the background color distinguishes these 4 levels.
Only the MOST extremes are plotted ON THE CHART. Within the indicator, all 4 levels are plotted.
Usage
Extreme Buy zone: Consider entering the market when the indicator shows deep negative values (oversold). These are highlighted with a cyan background, with increasing opacity indicating stronger buy signals (Level 4 Zones).
Extreme Sell Zone: Consider exiting the market when the indicator shows high positive values (overbought). These are highlighted with a magenta background, with increasing opacity indicating stronger sell signals (Level 4 Zones).
Disclaimer
This indicator should not be used in isolation. It is recommended to use this as part of a systematic approach, incorporating other tools and analysis methods to confirm signals and make well-informed trading decisions.
Supertrend + BB + Consecutive Candles + QQE + EMA [Pineify]Overview
This indicator, developed by Pineify, is a comprehensive tool designed to assist traders in making informed decisions by combining multiple technical analysis methods. It integrates Supertrend, Bollinger Bands (BB), Consecutive Candles, Quantitative Qualitative Estimation (QQE), and Exponential Moving Averages (EMA) into a single, cohesive script. This multi-faceted approach allows traders to analyze market trends, volatility, and potential buy/sell signals with greater accuracy.
Key Features
1. Supertrend: Utilizes the Supertrend indicator to identify the prevailing market trend. It provides clear buy and sell signals based on the direction of the trend.
2. Bollinger Bands (BB): Measures market volatility and identifies overbought or oversold conditions. The script calculates the middle, upper, and lower bands, along with the Bollinger Band Width (BBW) and Bollinger Band %B (BBR).
3. Consecutive Candles: Detects sequences of consecutive bullish or bearish candles, providing signals when a specified number of consecutive candles are detected.
4. Quantitative Qualitative Estimation (QQE): Combines the Relative Strength Index (RSI) with a smoothing factor to generate buy and sell signals based on the QQE methodology.
5. Exponential Moving Averages (EMA): Includes both fast and slow EMAs to identify potential crossovers, which are used as buy and sell signals.
How It Works
- Supertrend: The Supertrend indicator is calculated using a factor and ATR length. It plots the trend direction and generates buy/sell signals when the trend changes.
- Bollinger Bands: The BB indicator calculates the middle band as a Simple Moving Average (SMA) of the closing prices. The upper and lower bands are derived by adding and subtracting a multiple of the standard deviation from the middle band.
- Consecutive Candles: This feature counts the number of consecutive candles that close higher or lower than the previous candle. When the count reaches a specified threshold, it generates a buy or sell signal.
- QQE: The QQE indicator smooths the RSI values and calculates the QQE Fast and QQE Slow lines. Buy and sell signals are generated based on the crossover of these lines.
- EMA: The script calculates fast and slow EMAs and generates buy/sell signals based on their crossovers.
How to Use
1. Inputs: Customize the indicator settings through the input parameters:
- Supertrend Factor and ATR Length
- BB Length
- Consecutive Candles Counting
- QQE RSI Length
- Fast and Slow EMA Lengths
- Enable/Disable Alerts for various signals
2. Alerts: Set up alerts for Supertrend, Consecutive Candles, and EMA crossovers. Alerts can be enabled or disabled based on user preference.
3. Visualization: The indicator plots the Supertrend, Bollinger Bands, and EMA lines on the chart. It also marks buy and sell signals with arrows and labels for easy identification.
Concepts Underlying Calculations
- Supertrend: Based on the Average True Range (ATR) to determine the trend direction and potential reversal points.
- Bollinger Bands: Utilizes standard deviation to measure market volatility and identify overbought/oversold conditions.
- Consecutive Candles: A method to detect momentum by counting consecutive bullish or bearish candles.
- QQE: Enhances the traditional RSI by smoothing it and using a dynamic threshold to generate signals.
- EMA: A widely used moving average that gives more weight to recent prices, making it responsive to market changes.
This indicator is a powerful tool for traders looking to combine multiple technical analysis methods into a single, easy-to-use script. By integrating these diverse techniques, it provides a comprehensive view of market conditions and potential trading opportunities.
AlgoBuilder [Trend-Following] | FractalystWhat's the strategy's purpose and functionality?
This strategy is designed for both traders and investors looking to rely on and trade based on historical and backtested data using automation. The main goal is to build profitable trend-following strategies that outperform the underlying asset in terms of returns while minimizing drawdown. For example, as for a benchmark, if the S&P 500 (SPX) has achieved an estimated 10% annual return with a maximum drawdown of -57% over the past 20 years, using this strategy with different entry and exit techniques, users can potentially seek ways to achieve a higher Compound Annual Growth Rate (CAGR) while maintaining a lower maximum drawdown.
Although the strategy can be applied to all markets and timeframes, it is most effective on stocks, indices, future markets, cryptocurrencies, and commodities and JPY currency pairs given their trending behaviors.
In trending market conditions, the strategy employs a combination of moving averages and diverse entry models to identify and capitalize on upward market movements. It integrates market structure-based trailing stop-loss mechanisms across different timeframes and provides exit techniques, including percentage-based and risk-reward (RR) based take profit levels.
Additionally, the strategy has also a feature that includes a built-in probability and sentiment function for traders who want to implement probabilities and market sentiment right into their trading strategies.
Performance summary, weekly, and monthly tables enable quick visualization of performance metrics like net profit, maximum drawdown, compound annual growth rate (CAGR), profit factor, average trade, average risk-reward ratio (RR), and more. This aids optimization to meet specific goals and risk tolerance levels effectively.
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How does the strategy perform for both investors and traders?
The strategy has two main modes, tailored for different market participants: Traders and Investors.
Trading:
1. Trading (1x):
- Designed for traders looking to capitalize on bullish trending markets.
- Utilizes a percentage risk per trade to manage risk and optimize returns.
- Suitable for active trading with a focus on trend-following and risk management.
- (1x) This mode ensures no stacking of positions, allowing for only one running position or trade at a time.
◓: Mode | %: Risk percentage per trade
2. Trading (2x):
Similar to the 1x mode but allows for two pyramiding entries.
This approach enables traders to increase their position size as the trade moves in their favor, potentially enhancing profits during strong bullish trends.
◓: Mode | %: Risk percentage per trade
3. Investing:
- Geared towards investors who aim to capitalize on bullish trending markets without using leverage while mitigating the asset's maximum drawdown.
- Utilizes 100% of the equity to buy, hold, and manage the asset.
- Focuses on long-term growth and capital appreciation by fully investing in the asset during bullish conditions.
- ◓: Mode | %: Risk not applied (In investing mode, the strategy uses 100% of equity to buy the asset)
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What's the purpose of using moving averages in this strategy? What are the underlying calculations?
Using moving averages is a widely-used technique to trade with the trend.
The main purpose of using moving averages in this strategy is to filter out bearish price action and to only take trades when the price is trading ABOVE specified moving averages.
The script uses different types of moving averages with user-adjustable timeframes and periods/lengths, allowing traders to try out different variations to maximize strategy performance and minimize drawdowns.
By applying these calculations, the strategy effectively identifies bullish trends and avoids market conditions that are not conducive to profitable trades.
The MA filter allows traders to choose whether they want a specific moving average above or below another one as their entry condition.
This comparison filter can be turned on (>/<) or off.
For example, you can set the filter so that MA#1 > MA#2, meaning the first moving average must be above the second one before the script looks for entry conditions. This adds an extra layer of trend confirmation, ensuring that trades are only taken in more favorable market conditions.
MA #1: Fast MA | MA #2: Medium MA | MA #3: Slow MA
⍺: MA Period | Σ: MA Timeframe
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What entry modes are used in this strategy? What are the underlying calculations?
The strategy by default uses two different techniques for the entry criteria with user-adjustable left and right bars: Breakout and Fractal.
1. Breakout Entries :
- The strategy looks for pivot high points with a default period of 3.
- It stores the most recent high level in a variable.
- When the price crosses above this most recent level, the strategy checks if all conditions are met and the bar is closed before taking the buy entry.
◧: Pivot high left bars period | ◨: Pivot high right bars period
2. Fractal Entries :
- The strategy looks for pivot low points with a default period of 3.
- When a pivot low is detected, the strategy checks if all conditions are met and the bar is closed before taking the buy entry.
◧: Pivot low left bars period | ◨: Pivot low right bars period
By utilizing these entry modes, the strategy aims to capitalize on bullish price movements while ensuring that the necessary conditions are met to validate the entry points.
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What type of stop-loss identification method are used in this strategy? What are the underlying calculations?
Initial Stop-Loss:
1. ATR Based:
The Average True Range (ATR) is a method used in technical analysis to measure volatility. It is not used to indicate the direction of price but to measure volatility, especially volatility caused by price gaps or limit moves.
Calculation:
- To calculate the ATR, the True Range (TR) first needs to be identified. The TR takes into account the most current period high/low range as well as the previous period close.
The True Range is the largest of the following:
- Current Period High minus Current Period Low
- Absolute Value of Current Period High minus Previous Period Close
- Absolute Value of Current Period Low minus Previous Period Close
- The ATR is then calculated as the moving average of the TR over a specified period. (The default period is 14).
Example - ATR (14) * 1.5
⍺: ATR period | Σ: ATR Multiplier
2. ADR Based:
The Average Day Range (ADR) is an indicator that measures the volatility of an asset by showing the average movement of the price between the high and the low over the last several days.
Calculation:
- To calculate the ADR for a particular day:
- Calculate the average of the high prices over a specified number of days.
- Calculate the average of the low prices over the same number of days.
- Find the difference between these average values.
- The default period for calculating the ADR is 14 days. A shorter period may introduce more noise, while a longer period may be slower to react to new market movements.
Example - ADR (14) * 1.5
⍺: ADR period | Σ: ADR Multiplier
Application in Strategy:
- The strategy calculates the current bar's ADR/ATR with a user-defined period.
- It then multiplies the ADR/ATR by a user-defined multiplier to determine the initial stop-loss level.
By using these methods, the strategy dynamically adjusts the initial stop-loss based on market volatility, helping to protect against adverse price movements while allowing for enough room for trades to develop.
Trailing Stop-Loss:
One of the key elements of this strategy is its ability to detec buyside and sellside liquidity levels across multiple timeframes to trail the stop-loss once the trade is in running profits.
By utilizing this approach, the strategy allows enough room for price to run.
There are two built-in trailing stop-loss (SL) options you can choose from while in a trade:
1. External Trailing Stop-Loss:
- Uses sell-side liquidity to trail your stop-loss, allowing price to consolidate before continuation. This method is less aggressive and provides more room for price fluctuations.
Example - External - Wick below the trailing SL - 12H trailing timeframe
⍺: Exit type | Σ: Trailing stop-loss timeframe
2. Internal Trailing Stop-Loss:
- Uses the most recent swing low with a period of 2 to trail your stop-loss. This method is more aggressive compared to the external trailing stop-loss, as it tightens the stop-loss closer to the current price action.
Example - Internal - Close below the trailing SL - 6H trailing timeframe
⍺: Exit type | Σ: Trailing stop-loss timeframe
Each market behaves differently across various timeframes, and it is essential to test different parameters and optimizations to find out which trailing stop-loss method gives you the desired results and performance.
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What type of break-even and take profit identification methods are used in this strategy? What are the underlying calculations?
For Break-Even:
- You can choose to set a break-even level at which your initial stop-loss moves to the entry price as soon as it hits, and your trailing stop-loss gets activated (if enabled).
- You can select either a percentage (%) or risk-to-reward (RR) based break-even, allowing you to set your break-even level as a percentage amount above the entry price or based on RR.
For TP1 (Take Profit 1):
- You can choose to set a take profit level at which your position gets fully closed or 50% if the TP2 boolean is enabled.
- Similar to break-even, you can select either a percentage (%) or risk-to-reward (RR) based take profit level, allowing you to set your TP1 level as a percentage amount above the entry price or based on RR.
For TP2 (Take Profit 2):
- You can choose to set a take profit level at which your position gets fully closed.
- As with break-even and TP1, you can select either a percentage (%) or risk-to-reward (RR) based take profit level, allowing you to set your TP2 level as a percentage amount above the entry price or based on RR.
The underlying calculations involve determining the price levels at which these actions are triggered. For break-even, it moves the initial stop-loss to the entry price and activate the trailing stop-loss once the break-even level is reached.
For TP1 and TP2, it's specifying the price levels at which the position is partially or fully closed based on the chosen method (percentage or RR) above the entry price.
These calculations are crucial for managing risk and optimizing profitability in the strategy.
⍺: BE/TP type (%/RR) | Σ: how many RR/% above the current price
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What's the ADR filter? What does it do? What are the underlying calculations?
The Average Day Range (ADR) measures the volatility of an asset by showing the average movement of the price between the high and the low over the last several days.
The period of the ADR filter used in this strategy is tied to the same period you've used for your initial stop-loss.
Users can define the minimum ADR they want to be met before the script looks for entry conditions.
ADR Bias Filter:
- Compares the current bar ADR with the ADR (Defined by user):
- If the current ADR is higher, it indicates that volatility has increased compared to ADR (DbU).(⬆)
- If the current ADR is lower, it indicates that volatility has decreased compared to ADR (DbU).(⬇)
Calculations:
1. Calculate ADR:
- Average the high prices over the specified period.
- Average the low prices over the same period.
- Find the difference between these average values in %.
2. Current ADR vs. ADR (DbU):
- Calculate the ADR for the current bar.
- Calculate the ADR (DbU).
- Compare the two values to determine if volatility has increased or decreased.
By using the ADR filter, the strategy ensures that trades are only taken in favorable market conditions where volatility meets the user's defined threshold, thus optimizing entry conditions and potentially improving the overall performance of the strategy.
>: Minimum required ADR for entry | %: Current ADR comparison to ADR of 14 days ago.
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What's the probability filter? What are the underlying calculations?
The probability filter is designed to enhance trade entries by using buyside liquidity and probability analysis to filter out unfavorable conditions.
This filter helps in identifying optimal entry points where the likelihood of a profitable trade is higher.
Calculations:
1. Understanding Swing highs and Swing Lows
Swing High: A Swing High is formed when there is a high with 2 lower highs to the left and right.
Swing Low: A Swing Low is formed when there is a low with 2 higher lows to the left and right.
2. Understanding the purpose and the underlying calculations behind Buyside, Sellside and Equilibrium levels.
3. Understanding probability calculations
1. Upon the formation of a new range, the script waits for the price to reach and tap into equilibrium or the 50% level. Status: "⏸" - Inactive
2. Once equilibrium is tapped into, the equilibrium status becomes activated and it waits for either liquidity side to be hit. Status: "▶" - Active
3. If the buyside liquidity is hit, the script adds to the count of successful buyside liquidity occurrences. Similarly, if the sellside is tapped, it records successful sellside liquidity occurrences.
5. Finally, the number of successful occurrences for each side is divided by the overall count individually to calculate the range probabilities.
Note: The calculations are performed independently for each directional range. A range is considered bearish if the previous breakout was through a sellside liquidity. Conversely, a range is considered bullish if the most recent breakout was through a buyside liquidity.
Example - BSL > 50%
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What's the sentiment Filter? What are the underlying calculations?
Sentiment filter aims to calculate the percentage level of bullish or bearish fluctuations within equally divided price sections, in the latest price range.
Calculations:
This filter calculates the current sentiment by identifying the highest swing high and the lowest swing low, then evenly dividing the distance between them into percentage amounts. If the price is above the 50% mark, it indicates bullishness, whereas if it's below 50%, it suggests bearishness.
Sentiment Bias Identification:
Bullish Bias: The current price is trading above the 50% daily range.
Bearish Bias: The current price is trading below the 50% daily range.
Example - Sentiment Enabled | Bullish degree above 50% | Bullish sentimental bias
>: Minimum required sentiment for entry | %: Current sentimental degree in a (Bullish/Bearish) sentimental bias
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What's the range length Filter? What are the underlying calculations?
The range length filter identifies the price distance between buyside and sellside liquidity levels in percentage terms. When enabled, the script only looks for entries when the minimum range length is met. This helps ensure that trades are taken in markets with sufficient price movement.
Calculations:
Range Length (%) = ( ( Buyside Level − Sellside Level ) / Current Price ) ×100
Range Bias Identification:
Bullish Bias: The current range price has broken above the previous external swing high.
Bearish Bias: The current range price has broken below the previous external swing low.
Example - Range length filter is enabled | Range must be above 5% | Price must be in a bearish range
>: Minimum required range length for entry | %: Current range length percentage in a (Bullish/Bearish) range
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What's the day filter Filter, what does it do?
The day filter allows users to customize the session time and choose the specific days they want to include in the strategy session. This helps traders tailor their strategies to particular trading sessions or days of the week when they believe the market conditions are more favorable for their trading style.
Customize Session Time:
Users can define the start and end times for the trading session.
This allows the strategy to only consider trades within the specified time window, focusing on periods of higher market activity or preferred trading hours.
Select Days:
Users can select which days of the week to include in the strategy.
This feature is useful for excluding days with historically lower volatility or unfavorable trading conditions (e.g., Mondays or Fridays).
Benefits:
Focus on Optimal Trading Periods:
By customizing session times and days, traders can focus on periods when the market is more likely to present profitable opportunities.
Avoid Unfavorable Conditions:
Excluding specific days or times can help avoid trading during periods of low liquidity or high unpredictability, such as major news events or holidays.
Increased Flexibility: The filter provides increased flexibility, allowing traders to adapt the strategy to their specific needs and preferences.
Example - Day filter | Session Filter
θ: Session time | Exchange time-zone
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What tables are available in this script?
Table Type:
- Summary: Provides a general overview, displaying key performance parameters such as Net Profit, Profit Factor, Max Drawdown, Average Trade, Closed Trades, Compound Annual Growth Rate (CAGR), MAR and more.
CAGR: It calculates the 'Compound Annual Growth Rate' first and last taken trades on your chart. The CAGR is a notional, annualized growth rate that assumes all profits are reinvested. It only takes into account the prices of the two end points — not drawdowns, so it does not calculate risk. It can be used as a yardstick to compare the performance of two strategies. Since it annualizes values, it requires a minimum 4H timeframe to display the CAGR value. annualizing returns over smaller periods of times doesn't produce very meaningful figures.
MAR: Measure of return adjusted for risk: CAGR divided by Max Drawdown. Indicates how comfortable the system might be to trade. Higher than 0.5 is ideal, 1.0 and above is very good, and anything above 3.0 should be considered suspicious and you need to make sure the total number of trades are high enough by running a Deep Backtest in strategy tester. (available for TradingView Premium users.)
Avg Trade: The sum of money gained or lost by the average trade generated by a strategy. Calculated by dividing the Net Profit by the overall number of closed trades. An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit.
MaxDD: Displays the largest drawdown of losses, i.e., the maximum possible loss that the strategy could have incurred among all of the trades it has made. This value is calculated separately for every bar that the strategy spends with an open position.
Profit Factor: The amount of money a trading strategy made for every unit of money it lost (in the selected currency). This value is calculated by dividing gross profits by gross losses.
Avg RR: This is calculated by dividing the average winning trade by the average losing trade. This field is not a very meaningful value by itself because it does not take into account the ratio of the number of winning vs losing trades, and strategies can have different approaches to profitability. A strategy may trade at every possibility in order to capture many small profits, yet have an average losing trade greater than the average winning trade. The higher this value is, the better, but it should be considered together with the percentage of winning trades and the net profit.
Winrate: The percentage of winning trades generated by a strategy. Calculated by dividing the number of winning trades by the total number of closed trades generated by a strategy. Percent profitable is not a very reliable measure by itself. A strategy could have many small winning trades, making the percent profitable high with a small average winning trade, or a few big winning trades accounting for a low percent profitable and a big average winning trade. Most trend-following successful strategies have a percent profitability of 15-40% but are profitable due to risk management control.
BE Trades: Number of break-even trades, excluding commission/slippage.
Losing Trades: The total number of losing trades generated by the strategy.
Winning Trades: The total number of winning trades generated by the strategy.
Total Trades: Total number of taken traders visible your charts.
Net Profit: The overall profit or loss (in the selected currency) achieved by the trading strategy in the test period. The value is the sum of all values from the Profit column (on the List of Trades tab), taking into account the sign.
- Monthly: Displays performance data on a month-by-month basis, allowing users to analyze performance trends over each month.
- Weekly: Displays performance data on a week-by-week basis, helping users to understand weekly performance variations.
- OFF: Hides the performance table.
Labels:
- OFF: Hides labels in the performance table.
- PnL: Shows the profit and loss of each trade individually, providing detailed insights into the performance of each trade.
- Range: Shows the range length and Average Day Range (ADR), offering additional context about market conditions during each trade.
Profit Color:
- Allows users to set the color for representing profit in the performance table, helping to quickly distinguish profitable periods.
Loss Color:
- Allows users to set the color for representing loss in the performance table, helping to quickly identify loss-making periods.
These customizable tables provide traders with flexible and detailed performance analysis, aiding in better strategy evaluation and optimization.
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User-input styles and customizations:
To facilitate studying historical data, all conditions and rules can be applied to your charts. By plotting background colors on your charts, you'll be able to identify what worked and what didn't in certain market conditions.
Please note that all background colors in the style are disabled by default to enhance visualization.
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How to Use This Algobuilder to Create a Profitable Edge and System:
Choose Your Strategy mode:
- Decide whether you are creating an investing strategy or a trading strategy.
Select a Market:
- Choose a one-sided market such as stocks, indices, or cryptocurrencies.
Historical Data:
- Ensure the historical data covers at least 10 years of price action for robust backtesting.
Timeframe Selection:
- Choose the timeframe you are comfortable trading with. It is strongly recommended to use a timeframe above 15 minutes to minimize the impact of commissions on your profits.
Set Commission and Slippage:
- Properly set the commission and slippage in the strategy properties according to your broker or prop firm specifications.
Parameter Optimization:
- Use trial and error to test different parameters until you find the performance results you are looking for in the summary table or, preferably, through deep backtesting using the strategy tester.
Trade Count:
- Ensure the number of trades is 100 or more; the higher, the better for statistical significance.
Positive Average Trade:
- Make sure the average trade value is above zero.
(An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit.)
Performance Metrics:
- Look for a high profit factor, MAR (Mar Ratio), CAGR (Compound Annual Growth Rate), and net profit with minimum drawdown. Ideally, aim for a drawdown under 20-30%, depending on your risk tolerance.
Refinement and Optimization:
- Try out different markets and timeframes.
- Continue working on refining your edge using the available filters and components to further optimize your strategy.
Automation:
- Once you’re confident in your strategy, you can use the automation section to connect the algorithm to your broker or prop firm.
- Trade a fully automated and backtested trading strategy, allowing for hands-free execution and management.
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What makes this strategy original?
1. Incorporating direct integration of probabilities into the strategy.
2. Leveraging market sentiment to construct a profitable approach.
3. Utilizing built-in market structure-based trailing stop-loss mechanisms across various timeframes.
4. Offering both investing and trading strategies, facilitating optimization from different perspectives.
5. Automation for efficient execution.
6. Providing a summary table for instant access to key parameters of the strategy.
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How to use automation?
For Traders:
1. Ensure the strategy parameters are properly set based on your optimized parameters.
2. Enter your PineConnector License ID in the designated field.
3. Specify the desired risk level.
4. Provide the Metatrader symbol.
5. Check for chart updates to ensure the automation table appears on the top right corner, displaying your License ID, risk, and symbol.
6. Set up an alert with the strategy selected as Condition and the Message as {{strategy.order.alert_message}}.
7. Activate the Webhook URL in the Notifications section, setting it as the official PineConnector webhook address.
8. Double-check all settings on PineConnector to ensure the connection is successful.
9. Create the alert for entry/exit automation.
For Investors:
1. Ensure the strategy parameters are properly set based on your optimized parameters.
2. Choose "Investing" in the user-input settings.
3. Create an alert with a specified name.
4. Customize the notifications tab to receive alerts via email.
5. Buying/selling alerts will be triggered instantly upon entry or exit order execution.
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Strategy Properties
This script backtest is done on 4H COINBASE:BTCUSD , using the following backtesting properties:
Balance: $5000
Order Size: 10% of the equity
Risk % per trade: 1%
Commission: 0.04% (Default commission percentage according to TradingView competitions rules)
Slippage: 75 ticks
Pyramiding: 2
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Terms and Conditions | Disclaimer
Our charting tools are provided for informational and educational purposes only and should not be construed as financial, investment, or trading advice. They are not intended to forecast market movements or offer specific recommendations. Users should understand that past performance does not guarantee future results and should not base financial decisions solely on historical data.
Built-in components, features, and functionalities of our charting tools are the intellectual property of @Fractalyst Unauthorized use, reproduction, or distribution of these proprietary elements is prohibited.
By continuing to use our charting tools, the user acknowledges and accepts the Terms and Conditions outlined in this legal disclaimer and agrees to respect our intellectual property rights and comply with all applicable laws and regulations.
stockexploderits just for identifying moving average crossover 20 and 50 to identify trend in stocks
easily without taking much time
IsAlgo - Ultra Trend Strategy► Overview:
The Ultra Trend strategy is designed to identify trend lines based on average price movement and execute trades when the price crosses the middle line, confirmed by an entry candle. This strategy combines ATR, Moving Averages, and customizable candlestick patterns to provide a versatile and robust trading approach.
► Description:
The Ultra Trend strategy employs a multi-faceted approach to accurately gauge market trends and execute trades. It combines the Average True Range (ATR) with trendline analysis and Moving Averages, providing a comprehensive view of market conditions. The strategy uses ATR to measure market volatility and the average price movement, helping to set dynamic thresholds for trend detection and adapting to changing market conditions. The slope of the trend is calculated based on the angle of price movement, which aids in identifying the strength and direction of the trend.
Additionally, a Moving Average is used to filter trades, ensuring alignment with the broader market direction and reducing false signals, thereby enhancing trade accuracy.
Traders can configure the strategy to enter trades in the direction of the trend, against the trend, or both. This feature enhances the adaptability of the Ultra Trend strategy, making it suitable for various trading styles and market environments.
↑ Long Entry:
A long trade is executed when the entry candle crosses and closes above the trend line. This indicates a bullish market condition, signaling an opportunity to enter a buy position.
↓ Short Entry:
A short trade is executed when the entry candle crosses and closes below the trend line. This indicates a bearish market condition, signaling an opportunity to enter a sell position.
✕ Exit Conditions:
The strategy offers multiple stop-loss options to manage risk effectively. Traders can set stop-loss levels using fixed pips, ATR-based calculations, the higher/lower price of past candles, or close a trade if a candle moves against the trade direction.
Up to three take profit levels can be set using methods such as fixed pips, ATR, and risk-to-reward ratios. This allows traders to secure profits at various stages of the trade.
A trailing stop feature adjusts the stop loss as the trade moves into profit, locking in gains while allowing the trade to continue capturing potential upside. Additionally, a break-even feature moves the stop loss to the entry price once a certain profit level is reached, protecting against losses.
Trades can also be closed when a trend change is detected or when a candle closes outside a predefined channel, ensuring that positions are exited promptly in response to changing market conditions.
► Features and Settings:
⚙︎ Trend: Users can configure the trend direction, length, factor, and slope, allowing for precise control over how trends are identified and followed.
⚙︎ Moving Average: An Exponential Moving Average (EMA) can be employed to confirm the trend direction indicated by the trend lines. This provides further assurance that the trend line breakout is not a false signal. The EMA can be enabled or disabled based on user preference.
⚙︎ Entry Candle: The entry candle is the candle that breaks the trend line, signaling an entry opportunity. Users can specify the minimum and maximum size of the candle's body and the ratio of the body to the entire candle size. This ensures that only significant breakouts trigger trades.
⚙︎ Trading Session: This feature allows users to define specific trading hours during which the strategy should operate, ensuring trades are executed only during preferred market periods.
⚙︎ Trading Days: Users can specify which days the strategy should be active, offering the flexibility to avoid trading on specific days of the week.
⚙︎ Backtesting: Enables a backtesting period during which the strategy can be tested over a selected start and end date. This feature can be deactivated if not needed.
⚙︎ Trades: This includes configuring the direction of trades (long, short, or both), position sizing (fixed or percentage-based), the maximum number of open trades, and limitations on the number of trades per day or based on trend.
⚙︎ Trades Exit: The strategy offers various exit methods, such as setting profit or loss limits, specifying the duration a trade should remain open, or closing trades based on trend reversal.
⚙︎ Stop Loss: Various stop-loss methods are available, including a fixed number of pips, ATR-based, or using the highest or lowest price points within a specified number of previous candles. Additionally, trades can be closed after a specific number of candles move in the opposite direction of the trade.
⚙︎ Break Even: This feature adjusts the stop loss to a break-even point once certain conditions are met, such as reaching predefined profit levels, to protect gains.
⚙︎ Trailing Stop: The trailing stop feature adjusts the stop loss as the trade moves into profit, securing gains while potentially capturing further upside.
⚙︎ Take Profit: Up to three take-profit levels can be set using various methods, such as a fixed amount of pips, ATR, or risk-to-reward ratios based on the stop loss. Alternatively, users can specify a set number of candles moving in the direction of the trade.
⚙︎ Alerts: The strategy includes a comprehensive alert system that informs the user of all significant actions, such as trade openings and closings. It supports placeholders for dynamic values like take-profit levels and stop-loss prices.
⚙︎ Dashboard: A visual display provides detailed information about ongoing and past trades on the chart, helping users monitor the strategy's performance and make informed decisions.
► Backtesting Details:
Timeframe: 5-minute US30 chart
Initial Balance: $10,000
Order Size: 4% of equity per trade
Commission: $0.05 per contract
Slippage: 5 ticks
Stop Loss: ATR-based
Death Cross and Golden Cross HighlighterOverview
The script is designed to visually indicate the occurrence of Death Cross and Golden Cross events on a TradingView chart. It achieves this by calculating two moving averages (short-term and long-term) and plotting them on the chart. It then detects when these moving averages cross and highlights these points with labels and background colors.
Inputs
The script begins by defining input parameters:
- Short Moving Average Length: This is set to 50 by default, representing the short-term moving average period.
- Long Moving Average Length: This is set to 200 by default, representing the long-term moving average period.
These inputs allow users to customize the lengths of the moving averages according to their trading strategy.
Moving Averages Calculation
The script calculates two simple moving averages (SMAs) based on the closing prices:
- Short Moving Average (shortMA): Calculated over the short-term period specified by the user.
- Long Moving Average (longMA): Calculated over the long-term period specified by the user.
Plotting the Moving Averages
The moving averages are then plotted on the chart:
- The short-term moving average is plotted in blue.
- The long-term moving average is plotted in red.
These lines help users visually track the trends and potential crossover points.
Identifying Crossovers
The script identifies two key events:
- Golden Cross: Occurs when the short-term moving average crosses above the long-term moving average. This is typically considered a bullish signal, indicating a potential upward trend.
- Death Cross: Occurs when the short-term moving average crosses below the long-term moving average. This is typically considered a bearish signal, indicating a potential downward trend.
Highlighting Crossovers
To make the crossover events more noticeable, the script adds visual cues:
- Golden Cross: When a Golden Cross is detected, a green label with an upward arrow is plotted below the bar where the crossover occurs.
- Death Cross: When a Death Cross is detected, a red label with a downward arrow is plotted above the bar where the crossover occurs.
Background Coloring
Additionally, the script highlights the background of the chart:
- When a Golden Cross occurs, the background color is changed to a translucent green.
- When a Death Cross occurs, the background color is changed to a translucent red.
These background colors help emphasize the crossover events, making them easier to spot.
Usage
To use this script, a user would:
1. Copy the script and paste it into the Pine Script editor on TradingView.
2. Save the script and apply it to their chart.
By doing so, the user will see the moving averages plotted, and any Golden Cross or Death Cross events will be highlighted with labels and background colors. This visual aid helps traders quickly identify significant crossover events, which can inform their trading decisions.
Cipher Mean ReversionThe Cipher Mean Reversion Indicator is an advanced trading tool that dynamically adjusts to market volatility to provide optimal entry and exit signals. This indicator is designed to identify significant deviations from a calculated mean, signaling potential reversal points where prices might revert to their average.
Core Functionality:
Cipher Mean Reversion uses an Exponential Moving Average (EMA) as the foundation for its mean price calculation. What sets Cipher apart is its dynamic adjustment mechanism that adapts the sensitivity of the EMA based on a volatility index. This index assesses both the rate and magnitude of price changes over a user-specified period, utilizing standard deviation and average true range calculations to gauge market volatility.
Unique Features:
Dynamic Sensitivity Adjustment: The sensitivity of our mean reversion detection changes in real-time, driven by our proprietary volatility index. This index is calculated using a combination of standard deviation and average true range, providing a robust measure of market volatility that informs the adjustment of our signal thresholds.
Adaptive Signal Thresholds: Instead of static buy and sell thresholds, Cipher uses thresholds that adapt to ongoing market conditions. These thresholds expand during periods of high volatility to reduce the risk of false signals and contract during quieter market conditions to capture smaller price reversals.
Signal Generation:
Buy Signals: Generated when the price falls significantly below the dynamically adjusted lower threshold, indicating an oversold condition ripe for reversal.
Sell Signals: Occur when the price exceeds the dynamically adjusted upper threshold, suggesting an overbought condition likely to revert.
Usage Tips:
Parameter Customization: Users can adjust the lookback period for the volatility assessment and the length of the EMA to better fit different assets and trading styles.
Complementary Analysis: For enhanced trading decisions, combine the Cipher Mean Reversion with other analytical tools such as volume indicators or momentum oscillators.
Risk Management: Employ risk management strategies, including predefined stop-loss and take-profit levels, tailored to the volatility insights provided by the indicator.
Originality and Usefulness:
The Cipher Mean Reversion Indicator offers a novel approach to mean reversion analysis by integrating real-time volatility adaptations into the signal generation process. This methodology ensures that the indicator remains highly responsive to changing market dynamics, providing traders with signals that are both timely and relevant.
Intended Use:
Cipher is versatile and can be used across various asset classes, including stocks, forex, and commodities. It is ideal for traders who require an indicator that can adapt to different market environments, from fast-moving markets to more stable conditions.
Volume-Enhanced Momentum Moving Average (VEMMA)Volume-Enhanced Momentum Moving Average (VEMMA)
Overview:
The Volume-Enhanced Momentum Moving Average (VEMMA) helps you spot market trends by combining momentum and volume as a moving average. This unique moving average adjusts itself based on the strength and activity of the market, giving you a clearer picture of what’s happening.
How It Works:
1. Key Settings (all of these are adjustable in the settings panel of the indicator):
◦ Base Length: Looks back over the last 50 days by default.
◦ Momentum Length: Uses the past 14 days to measure market strength.
◦ Volume Length: Uses the past 30 days to average trading volume.
◦ High/Low Thresholds: Considers RSI values above 70 as high momentum and below 30 as low momentum.
2. Momentum and Volume:
◦ Momentum: Calculated using the Relative Strength Index (RSI) to see if the market is gaining or losing strength.
◦ Volume: Average trading volume is calculated over the last 30 days to gauge trading activity.
3. VEMMA Calculation:
◦ For each of the past 50 days:
▪ Check Momentum: If RSI > 70, it’s high momentum; if RSI < 30, it’s low.
▪ Weight by Volume: High momentum days with high volume get more weight; low momentum days get less.
▪ Combine: Multiply the closing price by this weight and sum it up.
◦ Average: Divide the total by 50 to get the VEMMA value.
4. Visuals:
◦ Lines: Two lines, VEMMA1 (blue) and VEMMA2 (orange), show the adjusted moving averages.
◦ Colours: Background colors help you quickly spot high (green) and low (red) momentum periods.
How to Use:
• Spot Trends: Rising VEMMA lines suggest an uptrend; falling lines suggest a downtrend.
• Confirm Signals: When both VEMMA1 and VEMMA2 move together, it indicates a strong trend.
• Identify Reversals: Watch for background color changes from green to red or vice versa to catch potential trend reversals.
If the market has been strong and active, the VEMMA line will rise more sharply. If the market is weak and quiet, the line will be smoother.
Benefits:
• Integrated View: Combines market strength and trading activity for a fuller picture.
• Responsive: Adapts to significant market changes, highlighting key movements.
• Easy to Read: Clear visuals with color-coded backgrounds make interpretation simple.
Remember, just like any other indicator, this is not supposed to be used alone. Use it as part of your greater trading strategy. I do however believe it works exceptionally well for finding longer term trends early. The default VEMMA settings work very well as replacement for the EMA 200. Try it and see how it goes. Play around with the settings. Feedback appreciated.
