Marcel's Dynamic Profit / Loss Calculator for GoldOverview
This Dynamic Risk / Reward Tool for Gold is designed to help traders efficiently plan and manage their trades in the volatile gold market. This script provides a clear visualisation of trade levels (Entry, Stop Loss, Take Profit) while dynamically calculating potential profit and loss. It ensures gold traders can assess their positions with precision, saving time and improving risk management.
Key Features
1. Trade Level Visualisation:
Plots Entry (Blue), Stop Loss (Red), and Take Profit (Green) lines directly on the chart.
Helps you visualise and confirm trade setups quickly which is good for scalping and day trades.
2. Dynamic Risk and Reward Calculations:
Calculates potential profit and loss in real time based on user-defined inputs such as position size, leverage, and account equity.
Displays a summary panel showing risk/reward metrics directly on the chart.
3. Customisable Settings:
Allows you to adjust key parameters like account equity, position size, leverage, and specific price levels for Entry, Stop Loss, and Take Profit.
Defaults are dynamically generated for convenience but remain fully adjustable for flexibility.
How It Works
The script uses gold-specific conventions (e.g., 1 lot = 100 ounces, 1 pip = 0.01 price change) to calculate accurate risk and reward metrics.
It dynamically positions Stop Loss and Take Profit levels relative to the entry price, based on user-defined or default offsets.
A real-time summary panel is displayed in the bottom-right corner of the chart, showing:
Potential Profit: The monetary value if the Take Profit is hit.
Potential Lo
ss: The monetary value if the Stop Loss is hit.
How to Use It
1. Add the script to your chart on a gold trading pair (e.g., XAUUSD).
2. Input your:
Account equity.
Leverage.
Position size (in lots).
Desired En
try Price (default: current close price).
3. Adjust the Stop Loss and Take Profit levels to your strategy, or let the script use default offsets of:
500 pips below the Entry for Stop Loss.
1000 pips above the Entry for Take Profit.
4. Review the plotted levels and the summary panel to confirm your trade aligns with your risk/reward goals.
Why Use This Tool?
Clarity and Precision:
Provides clear trade visuals and financial metrics for confident decision-making.
Time-Saving:
Automates the calculations needed to evaluate trade risk and reward.
Improved Risk Management:
Ensures you never trade without knowing your exact potential loss and gain.
This script is particularly useful for both novice and experienced traders looking to enhance their risk management and trading discipline in the Gold market. Enjoy clearer trades at speed.
在脚本中搜索"涨幅大于1000的股票"
India market cap and smart dataThis indicator displays important financial and technical data, such as Market Cap, P/E Ratio, ADR %, etc.
It is specially designed for swing traders.
Key Features and Highlights
- Market Cap Alert: If the Market Cap of a stock is below 1000 crore , it is displayed in red to indicate a potential liquidity issue.
- P/E Ratio for Loss-Making Companies : For companies with net losses, the P/E ratio is shown as 0 and displayed in red , alerting you to the unprofitable status of the company.
- ADR Alert: When the ADR is below 4% , it is highlighted in red . Swing traders typically look for stocks with high ADR.
- 52-Week High Proximity: If a stock is more than 20% below its 52-week high , this data is shown in red .
- 52-Week Low Performance: If a stock is up by more than 70% from its 52-week low , the data is displayed in green , indicating strong performance.
Additional Features
- Toggle data points on or off as desired.
- Supports both dark and light modes.
- Position the table wherever preferred on the chart.
- Customize the ADR % calculation based on the desired number of days (default is 20 days).
Note: The calculation for the percentage away from the 52-week high is based on the closing price of the 52-week high candle, not the high price.
Ultimate Machine Learning RSI (Deep Learning Edition)This script represents an advanced implementation of a Machine Learning-based Relative Strength Index (RSI) indicator in Pine Script, incorporating several sophisticated techniques to create a more adaptive, intelligent, and responsive RSI.
Key Components and Features:
Lookback Period: The period over which the indicator "learns" from past data, set to 1000 bars by default.
Momentum and Volatility Weighting: These factors control how much the momentum and volatility of the market influence the learning and signal generation.
RSI Length Range: The minimum and maximum values for the RSI length, allowing the algorithm to adjust the RSI length dynamically.
Learning Rate: Controls how quickly the system adapts to new data. An adaptive learning rate can change based on market volatility.
Memory Factor: Influences how much the system "remembers" previous performance when making adjustments.
Monte Carlo Simulations: Used for probabilistic modeling to create a more robust signal.
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Price Change: Tracks the difference between the current close and the previous close.
Momentum: A measure of the rate of change in the price over the lookback period.
Volatility: Calculated using the standard deviation of the close prices.
ATR (Average True Range): Tracks the volatility of the market over a short period to influence decisions.
Monte Carlo Simulation:
Probabilistic Signal: This uses multiple random simulations (Monte Carlo) to generate potential future signals. These simulations are weighted by the momentum and volatility of the market. A cluster factor further enhances the simulation based on volatility regimes.
Z-Score for Extreme Conditions:
Z-Score: Measures how extreme current price movements are compared to the historical average, providing context for identifying overbought and oversold conditions.
Dynamic Learning Rate:
The learning rate adjusts based on the volatility of the market, becoming more responsive in high-volatility periods and slower in low-volatility markets. This prevents the system from overreacting to noise but ensures responsiveness to significant shifts.
Recursive Learning and Feedback:
Error Calculation: The system calculates the difference between the true RSI and the predicted RSI, creating an error that is fed back into the system to adjust the RSI length and other parameters dynamically.
RSI Length Adjustment: Based on the error, the RSI length is adjusted, ensuring that the system evolves over time to better reflect market conditions.
Adaptive Smoothing:
In periods of high volatility, the indicator applies a Triple Exponential Moving Average (TEMA) for faster adaptation, while in quieter markets, it uses an Exponential Moving Average (EMA) for smoother adjustments.
Recursive Memory Feedback:
The system maintains a memory of past RSI values, which helps refine the output further. The memory factor influences how much weight is given to past performance versus the current adaptive signal.
Volatility-Based Reinforcement: Higher market volatility increases the impact of this memory feedback, making the model more reactive in volatile conditions.
Multi-Factor Dynamic Thresholds:
Dynamic Overbought/Oversold: Instead of fixed RSI levels (70/30), the thresholds adjust dynamically based on the Z-Score, making the system more sensitive to extreme market conditions.
Combined Multi-Factor Signal:
The final output signal is the result of combining the true RSI, adaptive RSI, and the probabilistic signal generated from the Monte Carlo simulations. This creates a robust, multi-factor signal that incorporates various market conditions and machine learning techniques.
Visual Representation:
The final combined signal is plotted in blue on the chart, along with reference lines at 55 (overbought), 10 (oversold), and 35 (neutral).
Alerts are set up to trigger when the combined signal crosses above the dynamic overbought level or below the dynamic oversold level.
Conclusion:
This "Ultimate Machine Learning RSI" script leverages multiple machine learning techniques—probabilistic modeling, adaptive learning, recursive feedback, and dynamic thresholds—to create an advanced, highly responsive RSI indicator. The result is an RSI that continuously learns from market conditions, adjusts itself in real-time, and provides a more nuanced and robust signal compared to traditional fixed-length RSI. This indicator pushes the boundaries of what's possible with Pine Script and introduces cutting-edge techniques for technical analysis.
Advanced Physics Financial Indicator Each component represents a scientific theory and is applied to the price data in a way that reflects key principles from that theory.
Detailed Explanation
1. Fractal Geometry - High/Low Signal
Concept: Fractal geometry studies self-similar patterns that repeat at different scales. In markets, fractals can be used to detect recurring patterns or turning points.
Implementation: The script detects pivot highs and lows using ta.pivothigh and ta.pivotlow, representing local turning points in price. The fractalSignal is set to 1 for a pivot high, -1 for a pivot low, and 0 if there is no signal. This logic reflects the cyclical, self-similar nature of price movements.
Practical Use: This signal is useful for identifying local tops and bottoms, allowing traders to spot potential reversals or consolidation points where fractal patterns emerge.
2. Quantum Mechanics - Probabilistic Monte Carlo Simulation
Concept: Quantum mechanics introduces uncertainty and probability into systems, much like how future price movements are inherently uncertain. Monte Carlo simulations are used to model a range of possible outcomes based on random inputs.
Implementation: In this script, we simulate 100 random outcomes by generating a random number between -1 and 1 for each iteration. These random values are stored in an array, and the average of these values is calculated to represent the Quantum Signal.
Practical Use: This probabilistic signal provides a sense of randomness and uncertainty in the market, reflecting the possibility of price movement in either direction. It simulates the market’s chaotic nature by considering multiple possible outcomes and their average.
3. Thermodynamics - Efficiency Ratio Signal
Concept: Thermodynamics deals with energy efficiency and entropy in systems. The efficiency ratio in financial terms can be used to measure how efficiently the price is moving relative to volatility.
Implementation: The Efficiency Ratio is calculated as the absolute price change over n periods divided by the sum of absolute changes for each period within n. This ratio shows how much of the price movement is directional versus random, mimicking the concept of efficiency in thermodynamic systems.
Practical Use: A high efficiency ratio suggests that the market is trending smoothly (high efficiency), while a low ratio indicates choppy, non-directional movement (low efficiency, or high entropy).
4. Chaos Theory - ATR Signal
Concept: Chaos theory studies how complex systems are highly sensitive to initial conditions, leading to unpredictable behavior. In markets, chaotic price movements can often be captured through volatility indicators.
Implementation: The script uses a very long ATR period (1000) to reflect slow-moving chaos over time. The Chaos Signal is computed by measuring the deviation of the current price from its long-term average (SMA), normalized by ATR. This captures price deviations over time, hinting at chaotic market behavior.
Practical Use: The signal measures how far the price deviates from its long-term average, which can signal the degree of chaos or extreme behavior in the market. High deviations indicate chaotic or volatile conditions, while low deviations suggest stability.
5. Network Theory - Correlation with BTC
Concept: Network theory studies how different components within a system are interconnected. In markets, assets are often correlated, meaning that price movements in one asset can influence or be influenced by another.
Implementation: This indicator calculates the correlation between the asset’s price and the price of Bitcoin (BTC) over 30 periods. The Network Signal shows how connected the asset is to BTC, reflecting broader market dynamics.
Practical Use: In a highly correlated market, BTC can act as a leading indicator for other assets. A strong correlation with BTC might suggest that the asset is likely to move in line with Bitcoin, while a weak or negative correlation might indicate that the asset is moving independently.
6. String Theory - RSI & MACD Interaction
Concept: String theory attempts to unify the fundamental forces of nature into a single framework. In trading, we can view the RSI and MACD as interacting forces that provide insights into momentum and trend.
Implementation: The script calculates the RSI and MACD and combines them into a single signal. The formula for String Signal is (RSI - 50) / 100 + (MACD Line - Signal Line) / 100, normalizing both indicators to a scale where their contributions are additive. The RSI represents momentum, and MACD shows trend direction and strength.
Practical Use: This signal helps in detecting moments where momentum (RSI) and trend strength (MACD) align, giving a clearer picture of the asset's direction and overbought/oversold conditions. It unifies these two indicators to create a more holistic view of market behavior.
7. Fluid Dynamics - On-Balance Volume (OBV) Signal
Concept: Fluid dynamics studies how fluids move and flow. In markets, volume can be seen as a "flow" that drives price movement, much like how fluid dynamics describe the flow of liquids.
Implementation: The script uses the OBV (On-Balance Volume) indicator to track the cumulative flow of volume based on price changes. The signal is further normalized by its moving average to smooth out fluctuations and make it more reflective of price pressure over time.
Practical Use: The Fluid Signal shows how the flow of volume is driving price action. If the OBV rises significantly, it suggests that there is strong buying pressure, while a falling OBV indicates selling pressure. It’s analogous to how pressure builds in a fluid system.
8. Final Signal - Combining All Physics-Based Indicators
Implementation: Each of the seven physics-inspired signals is combined into a single Final Signal by averaging their values. This approach blends different market insights from various scientific domains, creating a comprehensive view of the market’s condition.
Practical Use: The final signal gives you a holistic, multi-dimensional view of the market by merging different perspectives (fractal behavior, quantum probability, efficiency, chaos, correlation, momentum/trend, and volume flow). This approach helps traders understand the market's dynamics from multiple angles, offering deeper insights than any single indicator.
9. Color Coding Based on Signal Extremes
Concept: The color of the final signal plot dynamically reflects whether the market is in an extreme state.
Implementation: The signal color is determined using percentiles. If the Final Signal is in the top 55th percentile of its range, the signal is green (bullish). If it is between the 45th and 55th percentiles, it is orange (neutral). If it falls below the 45th percentile, it is red (bearish).
Practical Use: This visual representation helps traders quickly identify the strength of the signal. Bullish conditions (green), neutral conditions (orange), and bearish conditions (red) are clearly distinguished, simplifying decision-making.
Institutional Levels (Whole, Half, Quarter) By CapitalwithcalebThis Pine Script indicator is designed to plot institutional levels, which are key price levels that traders often monitor. These levels include whole numbers (like 12000, 12500), half levels (like 12250), and quarter levels (like 12375). The script allows full customization of colors, line styles, and line widths for each type of level (whole, half, and quarter).
Key Features:
Range of Levels:
The user defines a minimum (minLevel) and maximum (maxLevel) price level, and the script plots levels in increments of 50 points (step size of 50 covers quarter, half, and whole levels).
Customizable Appearance:
Color Customization: You can choose separate colors for whole, half, and quarter levels.
Line Style Customization: You can choose between solid, dashed, or dotted lines for each level type (whole, half, and quarter).
Line Width Customization: You can adjust the width of the lines (1 to 5).
Automatic Level Detection:
The script automatically determines whether a level is a whole, half, or quarter level based on whether it is a multiple of 1000 (whole), 500 (half), or 250 (quarter).
Plotting of Lines:
It draws horizontal lines across the entire chart (extend.both) at the calculated levels.
For each level, it determines its type (whole, half, quarter) and plots it using the user-specified colors, line styles, and widths.
Functions:
getLineStyle(styleStr): A functional helper that converts the string input from the user ("Solid", "Dashed", "Dotted") into Pine Script's corresponding line style constants.
plotLevel(level, color, width, style): Another functional helper that plots a line at the given price level with the provided color, width, and line style.
Execution Flow:
User Input: The user specifies the minimum and maximum levels to display on the chart. They also configure the appearance of the lines (color, style, width).
Level Calculation: The script iterates over all levels between the minLevel and maxLevel with a step size of 50, checking if the level is a whole, half, or quarter level.
Line Plotting: The appropriate lines are drawn on the chart, based on the type of level and user settings.
Example Use Case:
If a user sets the minLevel to 12000 and maxLevel to 13000, the script will automatically plot lines at key institutional levels like:
12000 (whole), 12250 (quarter), 12500 (whole), 12750 (quarter), etc.
Combo 2/20 EMA & CCI
This is another part of my research work, where I test a combination of two strategies, receiving a combined signal. In order to understand which indicator combinations work better, which work worse, as filters for trades. This is combo strategies for get a cumulative signal.
First strategy
This indicator plots 2/20 exponential moving average. For the Mov Avg X 2/20 Indicator, the EMA bar will be painted when the Alert criteria is met.
Second strategy
The Commodity Channel Index (CCI) is best used with markets that display cyclical or seasonal characteristics, and is formulated to detect the beginning and ending of the cycles by incorporating a moving average together with a divisor that reflects both possible and actual trading ranges. The final index measures the deviation from normal, which indicates major changes in market trend.
Strategy tester settings:
Initial capital: 1000
Order size: 0.5
Commission: 0.1%
Other as default.
Indicator settings:
EMA Length: 50
CCI Length: 10
Fast MA Length: 15
Slow MA Length: 20
Other as default.
WARNING:
- For purpose educate only
- This script to change bars colors.
RSI Trend Following StrategyOverview
The RSI Trend Following Strategy utilizes Relative Strength Index (RSI) to enter the trade for the potential trend continuation. It uses Stochastic indicator to check is the price is not in overbought territory and the MACD to measure the current price momentum. Moreover, it uses the 200-period EMA to filter the counter trend trades with the higher probability. The strategy opens only long trades.
Unique Features
Dynamic stop-loss system: Instead of fixed stop-loss level strategy utilizes average true range (ATR) multiplied by user given number subtracted from the position entry price as a dynamic stop loss level.
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Two layers trade filtering system: Strategy utilizes MACD and Stochastic indicators measure the current momentum and overbought condition and use 200-period EMA to filter trades against major trend.
Trailing take profit level: After reaching the trailing profit activation level script activates the trailing of long trade using EMA. More information in methodology.
Wide opportunities for strategy optimization: Flexible strategy settings allows users to optimize the strategy entries and exits for chosen trading pair and time frame.
Methodology
The strategy opens long trade when the following price met the conditions:
RSI is above 50 level.
MACD line shall be above the signal line
Both lines of Stochastic shall be not higher than 80 (overbought territory)
Candle’s low shall be above the 200 period EMA
When long trade is executed, strategy set the stop-loss level at the price ATR multiplied by user-given value below the entry price. This level is recalculated on every next candle close, adjusting to the current market volatility.
At the same time strategy set up the trailing stop validation level. When the price crosses the level equals entry price plus ATR multiplied by user-given value script starts to trail the price with trailing EMA(by default = 20 period). If price closes below EMA long trade is closed. When the trailing starts, script prints the label “Trailing Activated”.
Strategy settings
In the inputs window user can setup the following strategy settings:
ATR Stop Loss (by default = 1.75)
ATR Trailing Profit Activation Level (by default = 2.25)
MACD Fast Length (by default = 12, period of averaging fast MACD line)
MACD Fast Length (by default = 26, period of averaging slow MACD line)
MACD Signal Smoothing (by default = 9, period of smoothing MACD signal line)
Oscillator MA Type (by default = EMA, available options: SMA, EMA)
Signal Line MA Type (by default = EMA, available options: SMA, EMA)
RSI Length (by default = 14, period for RSI calculation)
Trailing EMA Length (by default = 20, period for EMA, which shall be broken close the trade after trailing profit activation)
Justification of Methodology
This trading strategy is designed to leverage a combination of technical indicators—Relative Strength Index (RSI), Moving Average Convergence Divergence (MACD), Stochastic Oscillator, and the 200-period Exponential Moving Average (EMA)—to determine optimal entry points for long trades. Additionally, the strategy uses the Average True Range (ATR) for dynamic risk management to adapt to varying market conditions. Let's look in details for which purpose each indicator is used for and why it is used in this combination.
Relative Strength Index (RSI) is a momentum indicator used in technical analysis to measure the speed and change of price movements in a financial market. It helps traders identify whether an asset is potentially overbought (overvalued) or oversold (undervalued), which can indicate a potential reversal or continuation of the current trend.
How RSI Works? RSI tracks the strength of recent price changes. It compares the average gains and losses over a specific period (usually 14 periods) to assess the momentum of an asset. Average gain is the average of all positive price changes over the chosen period. It reflects how much the price has typically increased during upward movements. Average loss is the average of all negative price changes over the same period. It reflects how much the price has typically decreased during downward movements.
RSI calculates these average gains and losses and compares them to create a value between 0 and 100. If the RSI value is above 70, the asset is generally considered overbought, meaning it might be due for a price correction or reversal downward. Conversely, if the RSI value is below 30, the asset is considered oversold, suggesting it could be poised for an upward reversal or recovery. RSI is a useful tool for traders to determine market conditions and make informed decisions about entering or exiting trades based on the perceived strength or weakness of an asset's price movements.
This strategy uses RSI as a short-term trend approximation. If RSI crosses over 50 it means that there is a high probability of short-term trend change from downtrend to uptrend. Therefore RSI above 50 is our first trend filter to look for a long position.
The MACD (Moving Average Convergence Divergence) is a popular momentum and trend-following indicator used in technical analysis. It helps traders identify changes in the strength, direction, momentum, and duration of a trend in an asset's price.
The MACD consists of three components:
MACD Line: This is the difference between a short-term Exponential Moving Average (EMA) and a long-term EMA, typically calculated as: MACD Line = 12 period EMA − 26 period EMA
Signal Line: This is a 9-period EMA of the MACD Line, which helps to identify buy or sell signals. When the MACD Line crosses above the Signal Line, it can be a bullish signal (suggesting a buy); when it crosses below, it can be a bearish signal (suggesting a sell).
Histogram: The histogram shows the difference between the MACD Line and the Signal Line, visually representing the momentum of the trend. Positive histogram values indicate increasing bullish momentum, while negative values indicate increasing bearish momentum.
This strategy uses MACD as a second short-term trend filter. When MACD line crossed over the signal line there is a high probability that uptrend has been started. Therefore MACD line above signal line is our additional short-term trend filter. In conjunction with RSI it decreases probability of following false trend change signals.
The Stochastic Indicator is a momentum oscillator that compares a security's closing price to its price range over a specific period. It's used to identify overbought and oversold conditions. The indicator ranges from 0 to 100, with readings above 80 indicating overbought conditions and readings below 20 indicating oversold conditions.
It consists of two lines:
%K: The main line, calculated using the formula (CurrentClose−LowestLow)/(HighestHigh−LowestLow)×100 . Highest and lowest price taken for 14 periods.
%D: A smoothed moving average of %K, often used as a signal line.
This strategy uses stochastic to define the overbought conditions. The logic here is the following: we want to avoid long trades in the overbought territory, because when indicator reaches it there is a high probability that the potential move is gonna be restricted.
The 200-period EMA is a widely recognized indicator for identifying the long-term trend direction. The strategy only trades in the direction of this primary trend to increase the probability of successful trades. For instance, when the price is above the 200 EMA, only long trades are considered, aligning with the overarching trend direction.
Therefore, strategy uses combination of RSI and MACD to increase the probability that price now is in short-term uptrend, Stochastic helps to avoid the trades in the overbought (>80) territory. To increase the probability of opening long trades in the direction of a main trend and avoid local bounces we use 200 period EMA.
ATR is used to adjust the strategy risk management to the current market volatility. If volatility is low, we don’t need the large stop loss to understand the there is a high probability that we made a mistake opening the trade. User can setup the settings ATR Stop Loss and ATR Trailing Profit Activation Level to realize his own risk to reward preferences, but the unique feature of a strategy is that after reaching trailing profit activation level strategy is trying to follow the trend until it is likely to be finished instead of using fixed risk management settings. It allows sometimes to be involved in the large movements.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 2024.08.01. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 30%
Maximum Single Position Loss: -3.94%
Maximum Single Profit: +15.78%
Net Profit: +1359.21 USDT (+13.59%)
Total Trades: 111 (36.04% win rate)
Profit Factor: 1.413
Maximum Accumulated Loss: 625.02 USDT (-5.85%)
Average Profit per Trade: 12.25 USDT (+0.40%)
Average Trade Duration: 40 hours
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 2h BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
MACD with 1D Stochastic Confirmation Reversal StrategyOverview
The MACD with 1D Stochastic Confirmation Reversal Strategy utilizes MACD indicator in conjunction with 1 day timeframe Stochastic indicators to obtain the high probability short-term trend reversal signals. The main idea is to wait until MACD line crosses up it’s signal line, at the same time Stochastic indicator on 1D time frame shall show the uptrend (will be discussed in methodology) and not to be in the oversold territory. Strategy works on time frames from 30 min to 4 hours and opens only long trades.
Unique Features
Dynamic stop-loss system: Instead of fixed stop-loss level strategy utilizes average true range (ATR) multiplied by user given number subtracted from the position entry price as a dynamic stop loss level.
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Higher time frame confirmation: Strategy utilizes 1D Stochastic to establish the major trend and confirm the local reversals with the higher probability.
Trailing take profit level: After reaching the trailing profit activation level scrip activate the trailing of long trade using EMA. More information in methodology.
Methodology
The strategy opens long trade when the following price met the conditions:
MACD line of MACD indicator shall cross over the signal line of MACD indicator.
1D time frame Stochastic’s K line shall be above the D line.
1D time frame Stochastic’s K line value shall be below 80 (not overbought)
When long trade is executed, strategy set the stop-loss level at the price ATR multiplied by user-given value below the entry price. This level is recalculated on every next candle close, adjusting to the current market volatility.
At the same time strategy set up the trailing stop validation level. When the price crosses the level equals entry price plus ATR multiplied by user-given value script starts to trail the price with EMA. If price closes below EMA long trade is closed. When the trailing starts, script prints the label “Trailing Activated”.
Strategy settings
In the inputs window user can setup the following strategy settings:
ATR Stop Loss (by default = 3.25, value multiplied by ATR to be subtracted from position entry price to setup stop loss)
ATR Trailing Profit Activation Level (by default = 4.25, value multiplied by ATR to be added to position entry price to setup trailing profit activation level)
Trailing EMA Length (by default = 20, period for EMA, when price reached trailing profit activation level EMA will stop out of position if price closes below it)
User can choose the optimal parameters during backtesting on certain price chart, in our example we use default settings.
Justification of Methodology
This strategy leverages 2 time frames analysis to have the high probability reversal setups on lower time frame in the direction of the 1D time frame trend. That’s why it’s recommended to use this strategy on 30 min – 4 hours time frames.
To have an approximation of 1D time frame trend strategy utilizes classical Stochastic indicator. The Stochastic Indicator is a momentum oscillator that compares a security's closing price to its price range over a specific period. It's used to identify overbought and oversold conditions. The indicator ranges from 0 to 100, with readings above 80 indicating overbought conditions and readings below 20 indicating oversold conditions.
It consists of two lines:
%K: The main line, calculated using the formula (CurrentClose−LowestLow)/(HighestHigh−LowestLow)×100 . Highest and lowest price taken for 14 periods.
%D: A smoothed moving average of %K, often used as a signal line.
Strategy logic assumes that on 1D time frame it’s uptrend in %K line is above the %D line. Moreover, we can consider long trade only in %K line is below 80. It means that in overbought state the long trade will not be opened due to higher probability of pullback or even major trend reversal. If these conditions are met we are going to our working (lower) time frame.
On the chosen time frame, we remind you that for correct work of this strategy you shall use 30min – 4h time frames, MACD line shall cross over it’s signal line. The MACD (Moving Average Convergence Divergence) is a popular momentum and trend-following indicator used in technical analysis. It helps traders identify changes in the strength, direction, momentum, and duration of a trend in a stock's price.
The MACD consists of three components:
MACD Line: This is the difference between a short-term Exponential Moving Average (EMA) and a long-term EMA, typically calculated as: MACD Line=12-period EMA−26-period
Signal Line: This is a 9-period EMA of the MACD Line, which helps to identify buy or sell signals. When the MACD Line crosses above the Signal Line, it can be a bullish signal (suggesting a buy); when it crosses below, it can be a bearish signal (suggesting a sell).
Histogram: The histogram shows the difference between the MACD Line and the Signal Line, visually representing the momentum of the trend. Positive histogram values indicate increasing bullish momentum, while negative values indicate increasing bearish momentum.
In our script we are interested in only MACD and signal lines. When MACD line crosses signal line there is a high chance that short-term trend reversed to the upside. We use this strategy on 45 min time frame.
ATR is used to adjust the strategy risk management to the current market volatility. If volatility is low, we don’t need the large stop loss to understand the there is a high probability that we made a mistake opening the trade. User can setup the settings ATR Stop Loss and ATR Trailing Profit Activation Level to realize his own risk to reward preferences, but the unique feature of a strategy is that after reaching trailing profit activation level strategy is trying to follow the trend until it is likely to be finished instead of using fixed risk management settings. It allows sometimes to be involved in the large movements.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 2024.08.01. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 30%
Maximum Single Position Loss: -4.79%
Maximum Single Profit: +20.14%
Net Profit: +2361.33 USDT (+44.72%)
Total Trades: 123 (44.72% win rate)
Profit Factor: 1.623
Maximum Accumulated Loss: 695.80 USDT (-5.48%)
Average Profit per Trade: 19.20 USDT (+0.59%)
Average Trade Duration: 30 hours
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe between 30 min and 4 hours and chart (optimal performance observed on 45 min BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
Double CCI Confirmed Hull Moving Average Reversal StrategyOverview
The Double CCI Confirmed Hull Moving Average Strategy utilizes hull moving average (HMA) in conjunction with two commodity channel index (CCI) indicators: the slow and fast to increase the probability of entering when the short and mid-term uptrend confirmed. The main idea is to wait until the price breaks the HMA while both CCI are showing that the uptrend has likely been already started. Moreover, strategy uses exponential moving average (EMA) to trail the price when it reaches the specific level. The strategy opens only long trades.
Unique Features
Dynamic stop-loss system: Instead of fixed stop-loss level strategy utilizes average true range (ATR) multiplied by user given number subtracted from the position entry price as a dynamic stop loss level.
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Double trade setup confirmation: Strategy utilizes two different period CCI indicators to confirm the breakouts of HMA.
Trailing take profit level: After reaching the trailing profit activation level scrip activate the trailing of long trade using EMA. More information in methodology.
Methodology
The strategy opens long trade when the following price met the conditions:
Short-term period CCI indicator shall be above 0.
Long-term period CCI indicator shall be above 0.
Price shall cross the HMA and candle close above it with the same candle
When long trade is executed, strategy set the stop-loss level at the price ATR multiplied by user-given value below the entry price. This level is recalculated on every next candle close, adjusting to the current market volatility.
At the same time strategy set up the trailing stop validation level. When the price crosses the level equals entry price plus ATR multiplied by user-given value script starts to trail the price with EMA. If price closes below EMA long trade is closed. When the trailing starts, script prints the label “Trailing Activated”.
Strategy settings
In the inputs window user can setup the following strategy settings:
ATR Stop Loss (by default = 1.75)
ATR Trailing Profit Activation Level (by default = 2.25)
CCI Fast Length (by default = 25, used for calculation short term period CCI
CCI Slow Length (by default = 50, used for calculation long term period CCI)
Hull MA Length (by default = 34, period of HMA, which shall be broken to open trade)
Trailing EMA Length (by default = 20)
User can choose the optimal parameters during backtesting on certain price chart.
Justification of Methodology
Before understanding why this particular combination of indicator has been chosen let's briefly explain what is CCI and HMA.
The Commodity Channel Index (CCI) is a momentum-based technical indicator used in trading to measure a security's price relative to its average price over a given period. Developed by Donald Lambert in 1980, the CCI is primarily used to identify cyclical trends in a security, helping traders to spot potential buying or selling opportunities.
The CCI formula is:
CCI = (Typical Price − SMA) / (0.015 × Mean Deviation)
Typical Price (TP): This is calculated as the average of the high, low, and closing prices for the period.
Simple Moving Average (SMA): This is the average of the Typical Prices over a specific number of periods.
Mean Deviation: This is the average of the absolute differences between the Typical Price and the SMA.
The result is a value that typically fluctuates between +100 and -100, though it is not bounded and can go higher or lower depending on the price movement.
The Hull Moving Average (HMA) is a type of moving average that was developed by Alan Hull to improve upon the traditional moving averages by reducing lag while maintaining smoothness. The goal of the HMA is to create an indicator that is both quick to respond to price changes and less prone to whipsaws (false signals).
How the Hull Moving Average is Calculated?
The Hull Moving Average is calculated using the following steps:
Weighted Moving Average (WMA): The HMA starts by calculating the Weighted Moving Average (WMA) of the price data over a period square root of n (sqrt(n))
Speed Adjustment: A WMA is then calculated for half of the period n/2, and this is multiplied by 2 to give more weight to recent prices.
Lag Reduction: The WMA of the full period n is subtracted from the doubled n/2 WMA.
Final Smoothing: To smooth the result and reduce noise, a WMA is calculated for the square root of the period n.
The formula can be represented as:
HMA(n) = WMA(WMA(n/2) × 2 − WMA(n), sqrt(n))
The Weighted Moving Average (WMA) is a type of moving average that gives more weight to recent data points, making it more responsive to recent price changes than a Simple Moving Average (SMA). In a WMA, each data point within the selected period is multiplied by a weight, with the most recent data receiving the highest weight. The sum of these weighted values is then divided by the sum of the weights to produce the WMA.
This strategy leverages HMA of user given period as a critical level which shall be broken to say that probability of trend change to the upside increased. HMA reacts faster than EMA or SMA to the price change, that’s why it increases chances to enter new trade earlier. Long-term period CCI helps to have an approximation of mid-term trend. If it’s above 0 the probability of uptrend increases. Short-period CCI allows to have an approximation of short-term trend reversal from down to uptrend. This approach increases chances to have a long trade setup in the direction of mid-term trend when the short-term trend starts to reverse.
ATR is used to adjust the strategy risk management to the current market volatility. If volatility is low, we don’t need the large stop loss to understand the there is a high probability that we made a mistake opening the trade. User can setup the settings ATR Stop Loss and ATR Trailing Profit Activation Level to realize his own risk to reward preferences, but the unique feature of a strategy is that after reaching trailing profit activation level strategy is trying to follow the trend until it is likely to be finished instead of using fixed risk management settings. It allows sometimes to be involved in the large movements. It’s also important to make a note, that script uses HMA to enter the trade, but for trailing it leverages EMA. It’s used because EMA has no such fast reaction to price move which increases probability not to be stopped out from any significant uptrend move.
Backtest Results
Operating window: Date range of backtests is 2022.07.01 - 2024.08.01. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 100%
Maximum Single Position Loss: -4.67%
Maximum Single Profit: +19.66%
Net Profit: +14897.94 USDT (+148.98%)
Total Trades: 104 (36.54% win rate)
Profit Factor: 2.312
Maximum Accumulated Loss: 1302.66 USDT (-9.58%)
Average Profit per Trade: 143.25 USDT (+0.96%)
Average Trade Duration: 34 hours
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 2h BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
Bollinger Bands Enhanced StrategyOverview
The common practice of using Bollinger bands is to use it for building mean reversion or squeeze momentum strategies. In the current script Bollinger Bands Enhanced Strategy we are trying to combine the strengths of both strategies types. It utilizes Bollinger Bands indicator to buy the local dip and activates trailing profit system after reaching the user given number of Average True Ranges (ATR). Also it uses 200 period EMA to filter trades only in the direction of a trend. Strategy can execute only long trades.
Unique Features
Trailing Profit System: Strategy uses user given number of ATR to activate trailing take profit. If price has already reached the trailing profit activation level, scrip will close long trade if price closes below Bollinger Bands middle line.
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Major Trend Filter: Strategy utilizes 100 period EMA to take trades only in the direction of a trend.
Flexible Risk Management: Users can choose number of ATR as a stop loss (by default = 1.75) for trades. This is flexible approach because ATR is recalculated on every candle, therefore stop-loss readjusted to the current volatility.
Methodology
First of all, script checks if currently price is above the 200-period exponential moving average EMA. EMA is used to establish the current trend. Script will take long trades on if this filtering system showing us the uptrend. Then the strategy executes the long trade if candle’s low below the lower Bollinger band. To calculate the middle Bollinger line, we use the standard 20-period simple moving average (SMA), lower band is calculated by the substruction from middle line the standard deviation multiplied by user given value (by default = 2).
When long trade executed, script places stop-loss at the price level below the entry price by user defined number of ATR (by default = 1.75). This stop-loss level recalculates at every candle while trade is open according to the current candle ATR value. Also strategy set the trailing profit activation level at the price above the position average price by user given number of ATR (by default = 2.25). It is also recalculated every candle according to ATR value. When price hit this level script plotted the triangle with the label “Strong Uptrend” and start trail the price at the middle Bollinger line. It also started to be plotted as a green line.
When price close below this trailing level script closes the long trade and search for the next trade opportunity.
Risk Management
The strategy employs a combined and flexible approach to risk management:
It allows positions to ride the trend as long as the price continues to move favorably, aiming to capture significant price movements. It features a user-defined ATR stop loss parameter to mitigate risks based on individual risk tolerance. By default, this stop-loss is set to a 1.75*ATR drop from the entry point, but it can be adjusted according to the trader's preferences.
There is no fixed take profit, but strategy allows user to define user the ATR trailing profit activation parameter. By default, this stop-loss is set to a 2.25*ATR growth from the entry point, but it can be adjusted according to the trader's preferences.
Justification of Methodology
This strategy leverages Bollinger bangs indicator to open long trades in the local dips. If price reached the lower band there is a high probability of bounce. Here is an issue: during the strong downtrend price can constantly goes down without any significant correction. That’s why we decided to use 200-period EMA as a trend filter to increase the probability of opening long trades during major uptrend only.
Usually, Bollinger Bands indicator is using for mean reversion or breakout strategies. Both of them have the disadvantages. The mean reversion buys the dip, but closes on the return to some mean value. Therefore, it usually misses the major trend moves. The breakout strategies usually have the issue with too high buy price because to have the breakout confirmation price shall break some price level. Therefore, in such strategies traders need to set the large stop-loss, which decreases potential reward to risk ratio.
In this strategy we are trying to combine the best features of both types of strategies. Script utilizes ate ATR to setup the stop-loss and trailing profit activation levels. ATR takes into account the current volatility. Therefore, when we setup stop-loss with the user-given number of ATR we increase the probability to decrease the number of false stop outs. The trailing profit concept is trying to add the beat feature from breakout strategies and increase probability to stay in trade while uptrend is developing. When price hit the trailing profit activation level, script started to trail the price with middle line if Bollinger bands indicator. Only when candle closes below the middle line script closes the long trade.
Backtest Results
Operating window: Date range of backtests is 2020.10.01 - 2024.07.01. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 30%
Maximum Single Position Loss: -9.78%
Maximum Single Profit: +25.62%
Net Profit: +6778.11 USDT (+67.78%)
Total Trades: 111 (48.65% win rate)
Profit Factor: 2.065
Maximum Accumulated Loss: 853.56 USDT (-6.60%)
Average Profit per Trade: 61.06 USDT (+1.62%)
Average Trade Duration: 76 hours
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 4h BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
Oscillator Scatterplot Analysis [Trendoscope®]In this indicator, we demonstrate how to plot oscillator behavior of oversold-overbought against price movements in the form of scatterplots and perform analysis. Scatterplots are drawn on a graph containing x and y-axis, where x represent one measure whereas y represents another. We use the library Graph to collect the data and plot it as scatterplot.
Pictorial explanation of components is defined in the chart below.
🎲 This indicator performs following tasks
Calculate and plot oscillator
Identify oversold and overbought areas based on various methods
Measure the price and bar movement from overbought to oversold and vice versa and plot them on the chart.
In our example,
The x-axis represents price movement. The plots found on the right side of the graph has positive price movements, whereas the plots found on the left side of the graph has negative price movements.
The y-axis represents the number of bars it took for reaching overbought to oversold and/or oversold to overbought. Positive bars mean we are measuring oversold to overbought, whereas negative bars are a measure of overbought to oversold.
🎲 Graph is divided into 4 equal quadrants
Quadrant 1 is the top right portion of the graph. Plots in this quadrant represent the instances where positive price movement is observed when the oscillator moved from oversold to overbought
Quadrant 2 is the top left portion of the graph. Plots in this quadrant represent the instances where negative price movement is observed when the oscillator moved from oversold to overbought.
Quadrant 3 is the bottom left portion of the chart. Plots in this quadrant represent the instances where negative price movement is observed when the oscillator moved from overbought to oversold.
Quadrant 4 is the bottom right portion of the chart. Plots in this quadrant represent the instances where positive price movement is observed when the oscillator moved from overbought to oversold.
🎲 Indicator components in Detail
Let's dive deep into the indicator.
🎯 Oscillator Selection
Select the Oscillator and define the overbought oversold conditions through input settings
Indicator - Oscillator base used for performing analysis
Length - Loopback length on which the oscillator is calculated
OB/OS Method - We use Bollinger Bands, Keltener Channel and Donchian channel to calculate dynamic overbought and oversold levels instead of static 80-10. This is also useful as other type of indicators may not be within 0-100 range.
Length and Multiplier are used for the bands for calculating Overbought/Oversold boundaries.
🎯 Define Graph Properties
Select different graph properties from the input settings that will instruct how to display the scatterplot.
Type - this can be either scatterplot or heatmap. Scatterplot will display plots with specific transparency to indicate the data, whereas heatmap will display background with different transparencies.
Plot Color - this is the color in which the scatterplot or heatmap is drawn
Plot Size - applicable mainly for scatterplot. Since the character we use for scatterplot is very tiny, the large at present looks optimal. But, based on the user's screen size, we may need to select different sizes so that it will render properly.
Rows and Columns - Number of rows and columns allocated per quadrant. This means, the total size of the chart is 2X rows and 2X columns. Data sets are divided into buckets based on the number of available rows and columns. Hence, changing this can change the appearance of the overall chart, even though they are representing the same data. Also, please note that tables can have max 10000 cells. If we increase the rows and columns by too much, we may get runtime errors.
Outliers - this is used to exclude the extreme data. 20% outlier means, the chart will ignore bottom 20% and top 20% when defining the chart boundaries. However, the extreme data is still added to the boundaries.
Smart Money Concepts by WeloTradesThe "Smart Money Concepts by WeloTrades" indicator is designed to offer traders a comprehensive tool that integrates multiple advanced features to aid in market analysis. By combining order blocks, liquidity levels, fair value gaps, trendlines, and market structure analysis, the indicator provides a holistic approach to understanding market dynamics and making informed trading decisions.
Components and Their Integration:
Order Blocks and Breaker Blocks Detection
Functionality: Order blocks represent areas where significant buying or selling occurred, creating potential support or resistance zones. Breaker blocks signal potential reversals.
Integration: By detecting and visualizing these blocks, the indicator helps traders identify key levels where price might react, aiding in entry and exit decisions. The customizable settings allow traders to adjust the visibility and parameters to suit their specific trading strategy.
Liquidity Levels Analysis
Functionality: Liquidity levels indicate zones where significant price movements can occur due to the presence of large orders. These are areas where smart money might be executing trades.
Integration: By tracking these high-probability liquidity areas, traders can anticipate potential price movements. Customizable display limits and mitigation strategies ensure that the information is tailored to the trader’s needs, providing precise and actionable insights.
Fair Value Gaps (FVG)
Functionality: Fair value gaps highlight areas where there is an imbalance between buyers and sellers. These gaps often represent potential trading opportunities.
Integration: The ability to identify and analyze FVGs helps traders spot potential entries based on market inefficiencies. The touch and break detection functionalities provide further refinement, enhancing the precision of trading signals.
Trendlines
Functionality: Trendlines help in identifying the direction of the market and potential reversal points. The additional trendline adds a layer of confirmation for breaks or retests.
Integration: Automatically drawn trendlines assist traders in visualizing market trends and making decisions about potential entries and exits. The additional trendline for stronger confirmation reduces the risk of false signals, providing more reliable trading opportunities.
Market Structure Analysis
Functionality: Understanding market structure is crucial for identifying key support and resistance levels and overall market dynamics. This component displays internal, external, and composite market structures.
Integration: By automatically highlighting shifts in market structure, the indicator helps traders recognize important levels and potential changes in market direction. This analysis is critical for strategic planning and execution in trading.
Customizable Alerts
Functionality: Alerts ensure that traders do not miss significant market events, such as the formation or breach of order blocks, liquidity levels, and trendline interactions.
Integration: Customizable alerts enhance the user experience by providing timely notifications of key events. This feature ensures that traders can act quickly and efficiently, leveraging the insights provided by the indicator.
Interactive Visualization
Functionality: Customizable visual aspects of the indicator allow traders to tailor the display to their preferences and trading style.
Integration: This feature enhances user engagement and usability, making it easier for traders to interpret the data and make informed decisions. Personalization options like colors, styles, and display formats improve the overall effectiveness of the indicator.
How Components Work Together
Comprehensive Market Analysis
Each component of the indicator addresses a different aspect of market analysis. Order blocks and liquidity levels highlight potential support and resistance zones, while fair value gaps and trendlines provide additional context for potential entries and exits. Market structure analysis ties everything together by offering a broad view of market dynamics.
Synergistic Insights
The integration of multiple features allows for cross-validation of trading signals. For instance, an order block coinciding with a high-probability liquidity level and a fair value gap can provide a stronger signal than any of these features alone. This synergy enhances the reliability of the insights and trading signals generated by the indicator.
Enhanced Decision Making
By combining these advanced features into a single tool, traders are equipped with a powerful resource for making informed decisions. The customizable alerts and interactive visualization further support this by ensuring that traders can act quickly on the insights provided.
Order Blocks ( OB) & Breaker Blocks (BB) Visuals:
📝 OB Input Settings
📊 Timeframe #1
TF #1🕑: Enable or disable Timeframe 1.
What it is: A boolean input to toggle the use of the first timeframe.
What it does: Enables or disables Timeframe 1 for the OB settings.
How to use it: Check or uncheck the box to enable or disable.
📊 Timeframe 1 Selection
Timeframe #1🕑: Select the timeframe for Timeframe 1.
What it is: A dropdown to select the desired timeframe.
What it does: Sets the timeframe for Timeframe 1.
How to use it: Choose a timeframe from the dropdown list.
📊 Timeframe #2
TF #2🕑: Enable or disable Timeframe 2.
What it is: A boolean input to toggle the use of the second timeframe.
What it does: Enables or disables Timeframe 2 for the OB settings.
How to use it: Check or uncheck the box to enable or disable.
📊 Timeframe 2 Selection
Timeframe #2🕑: Select the timeframe for Timeframe 2.
What it is: A dropdown to select the desired timeframe.
What it does: Sets the timeframe for Timeframe 2.
How to use it: Choose a timeframe from the dropdown list.
Additional Info: Higher TF Chart & Lower TF Setting / Lower TF Chart & Higher TF Setting.
📏 Show OBs
OB (Length)📏: Toggle the display of Order Blocks.
What it is: A boolean input to enable or disable the display of Order Blocks.
What it does: Shows or hides Order Blocks based on the selected swing length.
How to use it: Check or uncheck the box to enable or disable.
📏 Swing Length Option
Swing Length Option: Select the swing length option.
What it is: A dropdown to choose between SHORT, MID, LONG, or CUSTOM.
What it does: Sets the length of swings for Order Blocks.
How to use it: Choose an option from the dropdown.
Additional Info: Default lengths are SHORT=10, MID=28, LONG=50.
🔧 Custom Swing Length
🔧custom: Specify a custom swing length.
What it is: An integer input for setting a custom swing length.
What it does: Overrides the default swing lengths if set to CUSTOM.
How to use it: Enter a custom integer value (only shown when CUSTOM is selected).
📛 Show BBs
BB (Method)📛: Toggle the display of Breaker Blocks.
What it is: A boolean input to enable or disable the display of Breaker Blocks.
What it does: Shows or hides Breaker Blocks.
How to use it: Check or uncheck the box to enable or disable.
📛 OB End Method
OB End Method: Select the method for determining the end of a Breaker Block.
What it is: A dropdown to choose between Wick and Close.
What it does: Sets the criteria for when a Breaker Block is considered mitigated.
How to use it: Choose an option from the dropdown.
Additional Info: Wicks: OB is mitigated when the price wicks through the OB Level. Close: OB is mitigated when the closing price is within the OB Level.
🔍 Max Bullish Zones
🔍Max Bullish: Set the maximum number of Bullish Order Blocks to display.
What it is: A dropdown to select the maximum number of Bullish Order Blocks.
What it does: Limits the number of Bullish Order Blocks shown on the chart.
How to use it: Choose a value from the dropdown (1-10).
🔍 Max Bearish Zones
🔍Max Bearish: Set the maximum number of Bearish Order Blocks to display.
What it is: A dropdown to select the maximum number of Bearish Order Blocks.
What it does: Limits the number of Bearish Order Blocks shown on the chart.
How to use it: Choose a value from the dropdown (1-10).
🟩 Bullish OB Color
Bullish OB Color: Set the color for Bullish Order Blocks.
What it is: A color picker to set the color of Bullish Order Blocks.
What it does: Changes the color of Bullish Order Blocks on the chart.
How to use it: Select a color from the color picker.
🟥 Bearish OB Color
Bearish OB Color: Set the color for Bearish Order Blocks.
What it is: A color picker to set the color of Bearish Order Blocks.
What it does: Changes the color of Bearish Order Blocks on the chart.
How to use it: Select a color from the color picker.
🔧 OB & BB Range
↔ OB & BB Range: Select the range option for OB and BB.
What it is: A dropdown to choose between RANGE and CUSTOM.
What it does: Sets how far the OB or BB should extend.
How to use it: Choose an option from the dropdown.
Additional Info: RANGE = Current price, CUSTOM = Adjustable Range.
🔧 Custom OB & BB Range
🔧Custom: Specify a custom range for OB and BB.
What it is: An integer input for setting a custom range.
What it does: Defines how far the OB or BB should go, based on a custom value.
How to use it: Enter a custom integer value (range: 1000-500000).
💬 Text Options
💬Text Options: Set text size and color for OB and BB.
What it is: A dropdown to select text size and a color picker to choose text color.
What it does: Changes the size and color of the text displayed for OB and BB.
How to use it: Select a size from the dropdown and a color from the color picker.
💬 Show Timeframe OB
Text: Toggle to display the timeframe of OB.
What it is: A boolean input to show or hide the timeframe text for OB.
What it does: Displays the timeframe information for Order Blocks on the chart.
How to use it: Check or uncheck the box to enable or disable.
💬 Show Volume
Volume: Toggle to display the volume of OB.
What it is: A boolean input to show or hide the volume information for Order Blocks.
What it does: Displays the volume information for Order Blocks on the chart.
How to use it: Check or uncheck the box to enable or disable.
Additional Info:
What it represents: The volume displayed represents the total trading volume that occurred during the formation of the Order Block. This can indicate the level of participation or interest in that price level.
How it's calculated: The volume is the sum of all traded volumes within the candles that form the Order Block.
What it means: Higher volume at an Order Block level may suggest stronger support or resistance. It shows the amount of trading activity and can be an indicator of the potential strength or validity of the Order Block.
Why it's shown: To give traders an idea of the market participation and to help assess the strength of the Order Block.
💬 Show Percentage
%: Toggle to display the percentage of OB.
What it is: A boolean input to show or hide the percentage information for Order Blocks.
What it does: Displays the percentage information for Order Blocks on the chart.
How to use it: Check or uncheck the box to enable or disable.
Additional Info:
What it represents: The percentage displayed usually represents the proportion of price movement relative to the Order Block.
How it's calculated: This can be the percentage move from the start to the end of the Order Block or the retracement level that price has reached relative to the Order Block's range.
What it means: It helps traders understand the extent of price movement within the Order Block and can indicate the significance of the price level.
Why it's shown: To provide a clearer understanding of the price dynamics and the importance of the Order Block within the overall price movement.
Additional Information
Volume Example: If an Order Block forms over three candles with volumes of 100, 150, and 200, the total volume displayed for that Order Block would be 450.
Percentage Example: If the price moves from 100 to 110 within an Order Block, and the total range of the Order Block is from 100 to 120, the percentage shown might be 50% (since the price has moved halfway through the Order Block's range).
Liquidity Levels visuals:
📊 Liquidity Levels Input Settings
📊 Current Timeframe
TF #1🕑: Enable or disable the current timeframe.
What it is: A boolean input to toggle the use of the current timeframe.
What it does: Enables or disables the display of liquidity levels for the current timeframe.
How to use it: Check or uncheck the box to enable or disable.
📊 Higher Timeframe
Higher Timeframe: Select the higher timeframe for liquidity levels.
What it is: A dropdown to select the desired higher timeframe.
What it does: Sets the higher timeframe for liquidity levels.
How to use it: Choose a timeframe from the dropdown list.
📏 Liquidity Length Option
📏Liquidity Length: Select the length for liquidity levels.
What it is: A dropdown to choose between SHORT, MID, LONG, or CUSTOM.
What it does: Sets the length of swings for liquidity levels.
How to use it: Choose an option from the dropdown.
Additional Info: Default lengths are SHORT=10, MID=28, LONG=50.
🔧 Custom Liquidity Length
🔧custom: Specify a custom length for liquidity levels.
What it is: An integer input for setting a custom swing length.
What it does: Overrides the default liquidity lengths if set to CUSTOM.
How to use it: Enter a custom integer value (only shown when CUSTOM is selected).
📛 Mitigation Method
📛Mitigation (Method): Select the method for determining the mitigation of liquidity levels.
What it is: A dropdown to choose between Close and Wick.
What it does: Sets the criteria for when a liquidity level is considered mitigated.
How to use it: Choose an option from the dropdown.
Additional Info:
Wick: Level is mitigated when the price wicks through the level.
Close: Level is mitigated when the closing price is within the level.
📛 Display Mitigated Levels
-: Select to display or hide mitigated levels.
What it is: A dropdown to choose between Remove and Show.
What it does: Displays or hides mitigated liquidity levels.
How to use it: Choose an option from the dropdown.
Additional Info:
Remove: Hide mitigated levels.
Show: Display mitigated levels.
🔍 Max Buy Side Liquidity
🔍Max Buy Side Liquidity: Set the maximum number of Buy Side Liquidity Levels to display.
What it is: An integer input to set the maximum number of Buy Side Liquidity Levels.
What it does: Limits the number of Buy Side Liquidity Levels shown on the chart.
How to use it: Enter a value between 0 and 50.
🟦 Buy Side Liquidity Color
Buy Side Liquidity Color: Set the color for Buy Side Liquidity Levels.
What it is: A color picker to set the color of Buy Side Liquidity Levels.
What it does: Changes the color of Buy Side Liquidity Levels on the chart.
How to use it: Select a color from the color picker.
Additional Info:
Tooltip: Set the maximum number of Buy Side Liquidity Levels to display. Default: 5, Min: 1, Max: 50.
If liquidity levels are not displayed as expected, try increasing the max count.
🔍 Max Sell Side Liquidity
🔍Max Sell Side Liquidity: Set the maximum number of Sell Side Liquidity Levels to display.
What it is: An integer input to set the maximum number of Sell Side Liquidity Levels.
What it does: Limits the number of Sell Side Liquidity Levels shown on the chart.
How to use it: Enter a value between 0 and 50.
🟥 Sell Side Liquidity Color
Sell Side Liquidity Color: Set the color for Sell Side Liquidity Levels.
What it is: A color picker to set the color of Sell Side Liquidity Levels.
What it does: Changes the color of Sell Side Liquidity Levels on the chart.
How to use it: Select a color from the color picker.
Additional Info:
Tooltip: Set the maximum number of Sell Side Liquidity Levels to display. Default: 5, Min: 1, Max: 50.
If liquidity levels are not displayed as expected, try increasing the max count.
✂ Box Style (Height)
✂ Box Style (↕): Set the box height style for liquidity levels.
What it is: A float input to set the height of the boxes.
What it does: Adjusts the height of the boxes displaying liquidity levels.
How to use it: Enter a value between -50 and 50.
Additional Info: Default value is -5.
📏 Box Length
b: Set the box length of liquidity levels.
What it is: An integer input to set the length of the boxes.
What it does: Adjusts the length of the boxes displaying liquidity levels.
How to use it: Enter a value between 0 and 500.
Additional Info: Default value is 20.
⏭ Extend Liquidity Levels
Extend ⏭: Toggle to extend liquidity levels beyond the current range.
What it is: A boolean input to enable or disable the extension of liquidity levels.
What it does: Extends liquidity levels beyond their default range.
How to use it: Check or uncheck the box to enable or disable.
Additional Info: Extend liquidity levels beyond the current range.
💬 Text Options
💬 Text Options: Set text size and color for liquidity levels.
What it is: A dropdown to select text size and a color picker to choose text color.
What it does: Changes the size and color of the text displayed for liquidity levels.
How to use it: Select a size from the dropdown and a color from the color picker.
💬 Show Text
Text: Toggle to display text for liquidity levels.
What it is: A boolean input to show or hide the text for liquidity levels.
What it does: Displays the text information for liquidity levels on the chart.
How to use it: Check or uncheck the box to enable or disable.
💬 Show Volume
Volume: Toggle to display the volume of liquidity levels.
What it is: A boolean input to show or hide the volume information for liquidity levels.
What it does: Displays the volume information for liquidity levels on the chart.
How to use it: Check or uncheck the box to enable or disable.
Additional Info:
What it represents: The volume displayed represents the total trading volume that occurred during the formation of the liquidity level. This can indicate the level of participation or interest in that price level.
How it's calculated: The volume is the sum of all traded volumes within the candles that form the liquidity level.
What it means: Higher volume at a liquidity level may suggest stronger support or resistance. It shows the amount of trading activity and can be an indicator of the potential strength or validity of the liquidity level.
Why it's shown: To give traders an idea of the market participation and to help assess the strength of the liquidity level.
💬 Show Percentage
%: Toggle to display the percentage of liquidity levels.
What it is: A boolean input to show or hide the percentage information for liquidity levels.
What it does: Displays the percentage information for liquidity levels on the chart.
How to use it: Check or uncheck the box to enable or disable.
Additional Info:
What it represents: The percentage displayed usually represents the proportion of price movement relative to the liquidity level.
How it's calculated: This can be the percentage move from the start to the end of the liquidity level or the retracement level that price has reached relative to the liquidity level's range.
What it means: It helps traders understand the extent of price movement within the liquidity level and can indicate the significance of the price level.
Why it's shown: To provide a clearer understanding of the price dynamics and the importance of the liquidity level within the overall price movement.
Fair Value Gaps visuals:
📊 Fair Value Gaps Input Settings
📊 Show FVG
TF #1🕑: Enable or disable Fair Value Gaps for Timeframe 1.
What it is: A boolean input to toggle the display of Fair Value Gaps.
What it does: Shows or hides Fair Value Gaps on the chart.
How to use it: Check or uncheck the box to enable or disable.
📊 Select Timeframe
Timeframe: Select the timeframe for Fair Value Gaps.
What it is: A dropdown to select the desired timeframe.
What it does: Sets the timeframe for Fair Value Gaps.
How to use it: Choose a timeframe from the dropdown list.
Additional Info: Higher TF Chart & Lower TF Setting or Lower TF Chart & Higher TF Setting.
📛 FVG Break Method
📛FVG Break (Method): Select the method for determining when an FVG is mitigated.
What it is: A dropdown to choose between Touch, Wicks, Close, or Average.
What it does: Sets the criteria for when a Fair Value Gap is considered mitigated.
How to use it: Choose an option from the dropdown.
Additional Info:
Touch: FVG is mitigated when the price touches the gap.
Wicks: FVG is mitigated when the price wicks through the gap.
Close: FVG is mitigated when the closing price is within the gap.
Average: FVG is mitigated when the average price (average of high and low) is within the gap.
📛 Show Mitigated FVG
show: Toggle to display mitigated FVGs.
What it is: A boolean input to show or hide mitigated Fair Value Gaps.
What it does: Displays or hides mitigated Fair Value Gaps.
How to use it: Check or uncheck the box to enable or disable.
📛 Fill FVG
Fill: Toggle to fill Fair Value Gaps.
What it is: A boolean input to fill the Fair Value Gaps with color.
What it does: Adds a color fill to the Fair Value Gaps.
How to use it: Check or uncheck the box to enable or disable.
📛 Shade FVG
Shade: Toggle to shade Fair Value Gaps.
What it is: A boolean input to shade the Fair Value Gaps.
What it does: Adds a shade effect to the Fair Value Gaps.
How to use it: Check or uncheck the box to enable or disable.
Additional Info: Select the method to break FVGs and toggle the visibility of FVG Breaks (fill FVG and/or shade FVG).
🔍 Max Bullish FVG
🔍Max Bullish FVG: Set the maximum number of Bullish Fair Value Gaps to display.
What it is: An integer input to set the maximum number of Bullish Fair Value Gaps.
What it does: Limits the number of Bullish Fair Value Gaps shown on the chart.
How to use it: Enter a value between 0 and 50.
🔍 Max Bearish FVG
🔍Max Bearish FVG: Set the maximum number of Bearish Fair Value Gaps to display.
What it is: An integer input to set the maximum number of Bearish Fair Value Gaps.
What it does: Limits the number of Bearish Fair Value Gaps shown on the chart.
How to use it: Enter a value between 0 and 50.
🟥 Bearish FVG Color
Bearish FVG Color: Set the color for Bearish Fair Value Gaps.
What it is: A color picker to set the color of Bearish Fair Value Gaps.
What it does: Changes the color of Bearish Fair Value Gaps on the chart.
How to use it: Select a color from the color picker.
Additional Info:
Tooltip: Set the maximum number of Bearish Fair Value Gaps to display. Default: 5, Min: 1, Max: 50.
If Fair Value Gaps are not displayed as expected, try increasing the max count.
🟦 Bullish FVG Color
Bullish FVG Color: Set the color for Bullish Fair Value Gaps.
What it is: A color picker to set the color of Bullish Fair Value Gaps.
What it does: Changes the color of Bullish Fair Value Gaps on the chart.
How to use it: Select a color from the color picker.
Additional Info:
Tooltip: Set the maximum number of Bullish Fair Value Gaps to display. Default: 5, Min: 1, Max: 50.
If Fair Value Gaps are not displayed as expected, try increasing the max count.
📏 FVG Range
↔ FVG Range: Set the range for Fair Value Gaps.
What it is: An integer input to set the range of the Fair Value Gaps.
What it does: Adjusts the range of the Fair Value Gaps displayed.
How to use it: Enter a value between 0 and 100.
Additional Info: Adjustable length only works when both RANGE & EXTEND display OFF. Range=current price, Extend=Full Range.
⏭ Extend FVG
Extend⏭: Toggle to extend Fair Value Gaps beyond the current range.
What it is: A boolean input to enable or disable the extension of Fair Value Gaps.
What it does: Extends Fair Value Gaps beyond their default range.
How to use it: Check or uncheck the box to enable or disable.
⏯ FVG Range
Range⏯: Toggle the range of Fair Value Gaps.
What it is: A boolean input to enable or disable the range display for Fair Value Gaps.
What it does: Sets the range of Fair Value Gaps displayed.
How to use it: Check or uncheck the box to enable or disable.
↕ Max Width
↕ Max Width: Set the maximum width of Fair Value Gaps.
What it is: A float input to set the maximum width of Fair Value Gaps.
What it does: Limits the width of Fair Value Gaps as a percentage of the price range.
How to use it: Enter a value between 0 and 5.0.
Additional Info: FVGs wider than this value will be ignored.
♻ Filter FVG
Filter FVG ♻: Toggle to filter out small Fair Value Gaps.
What it is: A boolean input to filter out small Fair Value Gaps.
What it does: Ignores Fair Value Gaps smaller than the specified max width.
How to use it: Check or uncheck the box to enable or disable.
➖ Mid Line Style
➖Mid Line Style: Select the style of the mid line for Fair Value Gaps.
What it is: A dropdown to choose between Solid, Dashed, or Dotted.
What it does: Sets the style of the mid line within Fair Value Gaps.
How to use it: Choose an option from the dropdown.
🎨 Mid Line Color
Mid Line Color: Set the color for the mid line within Fair Value Gaps.
What it is: A color picker to set the color of the mid line.
What it does: Changes the color of the mid line within Fair Value Gaps.
How to use it: Select a color from the color picker.
Additional Information
Mitigation Methods: Each method (Touch, Wicks, Close, Average) provides different criteria for when a Fair Value Gap is considered mitigated, helping traders to understand the dynamics of price movements within gaps.
Volume and Percentage: Displaying volume and percentage information for Fair Value Gaps helps traders gauge the strength and significance of these gaps in relation to trading activity and price movements.
Trendlines visuals:
📊 Trendlines Input Settings
📊 Show Trendlines
Trendlines & Trendlines Difference(%) ↕: Enable or disable trendlines and set the percentage difference from the first trendline.
What it is: A boolean input to toggle the display of trendlines.
What it does: Shows or hides trendlines on the chart and allows setting a percentage difference from the first trendline.
How to use it: Check or uncheck the box to enable or disable.
Additional Info: The percentage difference determines the distance of the second trendline from the first one.
📏 Trendline Length Option
📏Trendline Length: Select the length for trendlines.
What it is: A dropdown to choose between SHORT, MID, LONG, or CUSTOM.
What it does: Sets the length of trendlines.
How to use it: Choose an option from the dropdown.
Additional Info: Default lengths are SHORT=50, MID=100, LONG=200.
🔧 Custom Trendline Length
🔧custom: Specify a custom length for trendlines.
What it is: An integer input for setting a custom trendline length.
What it does: Overrides the default trendline lengths if set to CUSTOM.
How to use it: Enter a custom integer value (only shown when CUSTOM is selected).
🔍 Max Bearish Trendlines
🔍Max Trendlines Bearish: Set the maximum number of bearish trendlines to display.
What it is: A dropdown to select the maximum number of bearish trendlines.
What it does: Limits the number of bearish trendlines shown on the chart.
How to use it: Choose a value from the dropdown (2-20).
🟩 Bearish Trendline Color
Bearish Trendline Color: Set the color for bearish trendlines.
What it is: A color picker to set the color of bearish trendlines.
What it does: Changes the color of bearish trendlines on the chart.
How to use it: Select a color from the color picker.
Additional Info: Adjust to control how many bearish trendlines are displayed.
🔍 Max Bullish Trendlines
🔍Max Trendlines Bullish: Set the maximum number of bullish trendlines to display.
What it is: A dropdown to select the maximum number of bullish trendlines.
What it does: Limits the number of bullish trendlines shown on the chart.
How to use it: Choose a value from the dropdown (2-20).
🟥 Bullish Trendline Color
Bullish Trendline Color: Set the color for bullish trendlines.
What it is: A color picker to set the color of bullish trendlines.
What it does: Changes the color of bullish trendlines on the chart.
How to use it: Select a color from the color picker.
Additional Info: Adjust to control how many bullish trendlines are displayed.
📐 Degrees Text
📐Degrees ° (💬 Size): Enable or disable degrees text and set its size and color.
What it is: A boolean input to show or hide the degrees text for trendlines.
What it does: Displays the degrees text for trendlines.
How to use it: Check or uncheck the box to enable or disable.
📏 Text Size for Degrees
Text Size: Set the text size for degrees on trendlines.
What it is: A dropdown to select the size of the degrees text.
What it does: Changes the size of the degrees text displayed for trendlines.
How to use it: Choose a size from the dropdown (XS, S, M, L, XL).
🎨 Degrees Text Color
Degrees Text Color: Set the color for the degrees text on trendlines.
What it is: A color picker to set the color of the degrees text.
What it does: Changes the color of the degrees text on the chart.
How to use it: Select a color from the color picker.
♻ Filter Degrees
♻ Filter Degrees °: Enable or disable angle filtering and set the angle range.
What it is: A boolean input to filter trendlines by their angle.
What it does: Shows only trendlines within a specified angle range.
How to use it: Check or uncheck the box to enable or disable.
Additional Info: Angles outside this range will be filtered out.
🔢 Angle Range
Angle Range: Set the angle range for filtering trendlines.
What it is: Two float inputs to set the minimum and maximum angle for trendlines.
What it does: Defines the range of angles for which trendlines will be shown.
How to use it: Enter values for the minimum and maximum angles.
➖ Line Style
➖Style #1 & #2: Select the style of the primary and secondary trendlines.
What it is: Two dropdowns to choose between Solid, Dashed, or Dotted for the trendlines.
What it does: Sets the style of the primary and secondary trendlines.
How to use it: Choose a style from each dropdown.
📏 Line Thickness
: Set the thickness for the trendlines.
What it is: An integer input to set the thickness of the trendlines.
What it does: Adjusts the thickness of the trendlines displayed on the chart.
How to use it: Enter a value between 1 and 5.
Additional Information
Trendline Percentage Difference: Setting a percentage difference helps in analyzing the relative position and angle of trendlines.
Filtering by Angle: This feature allows focusing on trendlines within a specific angle range, enhancing the clarity of trend analysis.
BOS & CHOCH Market Structure visuals:
📊 BOS & CHOCH Market Structure Input Settings
📏 Market Structure Length Option
📏Market Structure: Select the market structure length option.
What it is: A dropdown to choose between INTERNAL, EXTERNAL, ALL, CUSTOM, or NONE.
What it does: Sets the type of market structure to be displayed.
How to use it: Choose an option from the dropdown.
Additional Info:
INTERNAL: Only internal structure.
EXTERNAL: Only external structure.
ALL: Both internal and external structures.
CUSTOM: Custom lengths.
NONE: No structure.
🔧 Custom Internal Length
🔧Custom Internal: Specify a custom length for internal market structure.
What it is: An integer input for setting a custom internal length.
What it does: Defines the length of internal market structures if CUSTOM is selected.
How to use it: Enter a custom integer value (only shown when CUSTOM is selected).
💬 Internal Label Size
💬Internal Label Size: Set the label size for internal market structures.
What it is: A dropdown to select the size of the labels.
What it does: Changes the size of the labels for internal market structures.
How to use it: Choose a size from the dropdown (XS, S, M, L, XL).
🟩 Internal Bullish Color
Internal Bullish Color: Set the color for bullish internal market structures.
What it is: A color picker to set the color of bullish internal market structures.
What it does: Changes the color of bullish internal market structures on the chart.
How to use it: Select a color from the color picker.
🟥 Internal Bearish Color
Internal Bearish Color: Set the color for bearish internal market structures.
What it is: A color picker to set the color of bearish internal market structures.
What it does: Changes the color of bearish internal market structures on the chart.
How to use it: Select a color from the color picker.
🔧 Custom External Length
🔧Custom External: Specify a custom length for external market structure.
What it is: An integer input for setting a custom external length.
What it does: Defines the length of external market structures if CUSTOM is selected.
How to use it: Enter a custom integer value (only shown when CUSTOM is selected).
💬 External Label Size
💬External Label Size: Set the label size for external market structures.
What it is: A dropdown to select the size of the labels.
What it does: Changes the size of the labels for external market structures.
How to use it: Choose a size from the dropdown (XS, S, M, L, XL).
🟩 External Bullish Color
External Bullish Color: Set the color for bullish external market structures.
What it is: A color picker to set the color of bullish external market structures.
What it does: Changes the color of bullish external market structures on the chart.
How to use it: Select a color from the color picker.
🟥 External Bearish Color
External Bearish Color: Set the color for bearish external market structures.
What it is: A color picker to set the color of bearish external market structures.
What it does: Changes the color of bearish external market structures on the chart.
How to use it: Select a color from the color picker.
📐 Show Equal Highs and Lows
EQL & EQH📐: Toggle visibility for equal highs and lows.
What it is: A boolean input to show or hide equal highs and lows.
What it does: Displays or hides equal highs and lows on the chart.
How to use it: Check or uncheck the box to enable or disable.
📏 Equal Highs and Lows Threshold
Equal Highs and Lows Threshold: Set the threshold for equal highs and lows.
What it is: A float input to set the threshold for equal highs and lows.
What it does: Defines the range within which highs and lows are considered equal.
How to use it: Enter a value between 0 and 10.
💬 Label Size for Equal Highs and Lows
💬Label Size for Equal Highs and Lows: Set the label size for equal highs and lows.
What it is: A dropdown to select the size of the labels.
What it does: Changes the size of the labels for equal highs and lows.
How to use it: Choose a size from the dropdown (XS, S, M, L, XL).
🟩 Bullish Color for Equal Highs and Lows
Bullish Color for Equal Highs and Lows: Set the color for bullish equal highs and lows.
What it is: A color picker to set the color of bullish equal highs and lows.
What it does: Changes the color of bullish equal highs and lows on the chart.
How to use it: Select a color from the color picker.
🟥 Bearish Color for Equal Highs and Lows
Bearish Color for Equal Highs and Lows: Set the color for bearish equal highs and lows.
What it is: A color picker to set the color of bearish equal highs and lows.
What it does: Changes the color of bearish equal highs and lows on the chart.
How to use it: Select a color from the color picker.
📏 Show Swing Points
Swing Points📏: Toggle visibility for swing points.
What it is: A boolean input to show or hide swing points.
What it does: Displays or hides swing points on the chart.
How to use it: Check or uncheck the box to enable or disable.
📏 Swing Points Length Option
Swing Points Length Option: Select the length for swing points.
What it is: A dropdown to choose between SHORT, MID, LONG, or CUSTOM.
What it does: Sets the length of swing points.
How to use it: Choose an option from the dropdown.
Additional Info: Default lengths are SHORT=10, MID=28, LONG=50.
💬 Swing Points Label Size
💬Swing Points Label Size: Set the label size for swing points.
What it is: A dropdown to select the size of the labels.
What it does: Changes the size of the labels for swing points.
How to use it: Choose a size from the dropdown (XS, S, M, L, XL).
🎨 Swing Points Color
Swing Points Color: Set the color for swing points.
What it is: A color picker to set the color of swing points.
What it does: Changes the color of swing points on the chart.
How to use it: Select a color from the color picker.
🔧 Custom Swing Points Length
🔧Custom Swings: Specify a custom length for swing points.
What it is: An integer input for setting a custom length for swing points.
What it does: Defines the length of swing points if CUSTOM is selected.
How to use it: Enter a custom integer value (only shown when CUSTOM is selected).
Additional Information
Market Structure Types: Understanding internal and external structures helps in analyzing different market behaviors.
Equal Highs and Lows: This feature identifies areas where price action is balanced, which can be significant for trading strategies.
Swing Points: Highlighting swing points aids in recognizing significant market reversals or continuations.
Benefits
Enhance your trading strategy by visualizing smart money's influence on price movements.
Make informed decisions with real-time data on significant market structures.
Reduce manual analysis with automated detection of key trading signals.
Ideal For
Traders looking for an edge in forex, equities, and cryptocurrency markets by understanding the underlying forces driving market dynamics.
Acknowledgements
Special thanks to these amazing creators for inspiration and their creations:
I want to thank these amazing creators for creating there amazing indicators , that inspired me and also gave me a head start by making this indicator! Without their amazing indicators it wouldn't be possible!
Flux Charts: Volumized Order Blocks
LuxAlgo: Trend Lines
UAlgo: Fair Value Gaps (FVG)
By Leviathan: Market Structure
Sonarlab: Liquidity Levels
Note
Remember to always backtest the indicator first before integrating it into your strategy! For any questions about the indicator, please feel free to ask for assistance.
Strategy SEMA SDI WebhookPurpose of the Code:
The strategy utilizes Exponential Moving Averages (EMA) and Smoothed Directional Indicators (SDI) to generate buy and sell signals. It includes features like leverage, take profit, stop loss, and trailing stops. The strategy is intended for backtesting and automating trades based on the specified indicators and conditions.
Key Components and Functionalities:
1.Strategy Settings:
Overlay: The strategy will overlay on the price chart.
Slippage: Set to 1.
Commission Value: Set to 0.035.
Default Quantity Type: Percent of equity.
Default Quantity Value: 50% of equity.
Initial Capital: Set to 1000 units.
Calculation on Order Fills: Enabled.
Process Orders on Close: Enabled.
2.Date and Time Filters:
Inputs for enabling/disabling start and end dates.
Filters to execute strategy only within specified date range.
3.Leverage and Quantity:
Leverage: Adjustable leverage input (default 3).
USD Percentage: Adjustable percentage of equity to use for trades (default 50%).
Initial Capital: Calculated based on leverage and percentage of equity.
4.Take Profit, Stop Loss, and Trailing Stop:
Inputs for enabling/disabling take profit, stop loss, and trailing stop.
Adjustable parameters for take profit percentage (default 25%), stop loss percentage (default 4.8%), and trailing stop percentage (default 1.9%).
Calculations for take profit, stop loss, trailing price, and maximum profit tracking.
5.EMA Calculations:
Fast and slow EMAs.
Smoothed versions of the fast and slow EMAs.
6.SDI Calculations:
Directional movement calculation for positive and negative directional indicators.
Difference between the positive and negative directional indicators, smoothed.
7.Buy/Sell Conditions:
Long (Buy) Condition: Positive DI is greater than negative DI, and fast EMA is greater than slow EMA.
Short (Sell) Condition: Negative DI is greater than positive DI, and fast EMA is less than slow EMA.
8.Strategy Execution:
If buy conditions are met, close any short positions and enter a long position.
If sell conditions are met, close any long positions and enter a short position.
Exit conditions for long and short positions based on take profit, stop loss, and trailing stop levels.
Close all positions if outside the specified date range.
Usage:
This strategy is used to automate trading based on the specified conditions involving EMAs and SDI. It allows backtesting to evaluate performance based on historical data. The strategy includes risk management through take profit, stop loss, and trailing stops to protect gains and limit losses. Traders can customize the parameters to fit their specific trading preferences and risk tolerance. Differently, it can perform leverage analysis and use it as a template.
By using this strategy, traders can systematically execute trades based on technical indicators, helping to remove emotional bias and improve consistency in trading decisions.
Important Note:
This script is provided for educational and template purposes and does not constitute financial advice. Traders and investors should conduct their research and analysis before making any trading decisions.
Spiral Levels [ChartPrime]SPIRAL LEVELS
⯁ OVERVIEW
The Spiral Levels [ ChartPrime ] indicator, designed for use on TradingView and developed with Pine Script™ , leveraging a combination of traditional pivot points and spiral geometry to visualize support and resistance levels on the chart. By plotting spirals from pivot points, the indicator provides a distinctive perspective on potential price movements.
It's an experiment inspired from spirals in the Pine documentation and the concept of using spirals to add padding/offsets to SR zones in a market (an idea we plan to expand on in the future).
◆ USAGE
● Identifying Pivot Points: The indicator identifies significant pivot highs and lows based on user-defined criteria.
● Filtered Pivot Points: Pivot points for spirals are filtered using volume and high/low thresholds to ensure they are significant.
● Spiral Visualization: Spirals are plotted from these pivots, indicating potential future support and resistance levels or as liquidity zones.
Additionally, the plotted levels can serve as liquidity zones where the price might attempt to grab liquidity, providing a deeper understanding of market behavior at significant volume levels.
● Volume-Based Coloring: Spirals are colored based on volume data, providing additional context about the strength of the price movement.
● Labeling and Line Extensions: Labels display volume information, and lines extend from the end of the spirals to the current bar for clarity.
● Spiral Rotation: By adjusting the "Number of spiral rotations" input, you can control the number of rotations each spiral makes around a pivot point, offering more detailed insights. This also allows you to control the distance of levels from a pivot. More rotations will extend the spiral further from the pivot point, potentially identifying support and resistance levels or liquidity zones at greater distances.
This modification emphasizes that the number of rotations not only provides more detailed insights but also affects the spatial distribution of the identified levels relative to the pivot point.
⯁ USER INPUTS
● Pivots
Left Bars: Determines the number of bars to the left of the pivot.
Right Bars: Determines the number of bars to the right of the pivot.
● Filter
Volume Filter: Sets the threshold for volume filtering.
High & Low Filter: Sets the threshold for filtering pivot highs and lows.
● Spiral
Spirals Shown: Specifies the number of spirals to be displayed on the chart.
Number of spiral rotations: Sets the number of rotations for each spiral.
X Scale: Adjusts the horizontal scale of the spirals.
Y Scale: Adjusts the vertical scale of the spirals, relative to the ATR(200).
Reverse Spirals: Option to reverse the direction of the spirals.
⯁ TECHNICAL NOTES
The indicator uses Pine Script's polyline feature for smooth spiral rendering.
It implements a custom cross detection function to manage line and label visibility.
The script is optimized to limit calculations to the last 1000 bars for performance.
It automatically manages the number of displayed elements to prevent clutter and ensure smooth performance.
The Spiral Levels ChartPrime indicator offers a unique and visually engaging method to identify potential support and resistance levels. By integrating volume data and pivot points with spiral geometry, traders can gain valuable insights into market dynamics and make more informed trading decisions.
Frequency and Volume ProfileFREQUENCY & VOLUME PROFILE
⚪ OVERVIEW
The Frequency and Volume Profile indicator plots a frequency or volume profile based on the visible bars on the chart, providing insights into price levels with significant trading activity.
⚪ USAGE
● Market Structure Analysis:
Identify key price levels where significant trading activity occurred, which can act as support and resistance zones.
● Volume Analysis:
Use the volume mode to understand where the highest trading volumes have occurred, helping to confirm strong price levels.
● Trend Confirmation:
Analyze the distribution of trading activity to confirm or refute trends, mark important levels as support and resistance, aiding in making more informed trading decisions.
● Frequency Distribution:
In statistics, a frequency distribution is a list of the values that a variable takes in a sample. It is usually a list. Displayed as a histogram.
⚪ SETTINGS
Source: Select the price data to use for the profile calculation (default: hl2).
Move Profile: Set the number of bars to offset the profile from the current bar (default: 100).
Mode: Choose between "Frequency" and "Volume" for the profile calculation.
Profile Color: Customize the color of the profile lines.
Lookback Period: Uses 5000 bars for daily and higher timeframes, otherwise 10000 bars.
The Frequency Profile indicator is a powerful tool for visualizing price levels with significant trading activity, whether in terms of frequency or volume. Its dynamic calculation and customizable settings make it a versatile addition to any trading strategy.
Fractal Breakout Trend Following StrategyOverview
The Fractal Breakout Trend Following Strategy is a trend-following system which utilizes the Willams Fractals and Alligator to execute the long trades on the fractal's breakouts which have a high probability to be the new uptrend phase beginning. This system also uses the normalized Average True Range indicator to filter trades after a large moves, because it's more likely to see the trend continuation after a consolidation period. Strategy can execute only long trades.
Unique Features
Trend and volatility filtering system: Strategy uses Williams Alligator to filter the counter-trend fractals breakouts and normalized Average True Range to avoid the trades after large moves, when volatility is high
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Flexible Risk Management: Users can choose the stop-loss percent (by default = 3%) for trades, but strategy also has the dynamic stop-loss level using down fractals.
Methodology
The strategy places stop order at the last valid fractal breakout level. Validity of this fractal is defined by the Williams Alligator indicator. If at the moment of time when price breaking the last fractal price is higher than Alligator's teeth line (8 period SMA shifted 5 bars in the future) this is a valid breakout. Moreover strategy has the additional volatility filtering system using normalized ATR. It calculates the average normalized ATR for last user-defined number of bars and if this value lower than the user-defined threshold value the long trade is executed.
When trade is opened, script places the stop loss at the price higher of two levels: user defined stop-loss from the position entry price or down fractal validation level. The down fractal is valid with the rule, opposite as the up fractal validation. Price shall break to the downside the last down fractal below the Willians Alligator's teeth line.
Strategy has no fixed take profit. Exit level changes with the down fractal validation level. If price is in strong uptrend trade is going to be active until last down fractal is not valid. Strategy closes trade when price hits the down fractal validation level.
Risk Management
The strategy employs a combined approach to risk management:
It allows positions to ride the trend as long as the price continues to move favorably, aiming to capture significant price movements. It features a user-defined stop-loss parameter to mitigate risks based on individual risk tolerance. By default, this stop-loss is set to a 3% drop from the entry point, but it can be adjusted according to the trader's preferences.
Justification of Methodology
This strategy leverages Williams Fractals to open long trade when price has broken the key resistance level to the upside. This resistance level is the last up fractal and is shall be broken above the Williams Alligator's teeth line to be qualified as the valid breakout according to this strategy. The Alligator filtering increases the probability to avoid the false breakouts against the current trend.
Moreover strategy has an additional filter using Average True Range(ATR) indicator. If average value of ATR for the last user-defined number of bars is lower than user-defined threshold strategy can open the long trade according to open trade condition above. The logic here is following: we want to open trades after period of price consolidation inside the range because before and after a big move price is more likely to be in sideways, but we need a trend move to have a profit.
Another one important feature is how the exit condition is defined. On the one hand, strategy has the user-defined stop-loss (3% below the entry price by default). It's made to give users the opportunity to restrict their losses according to their risk-tolerance. On the other hand, strategy utilizes the dynamic exit level which is defined by down fractal activation. If we assume the breaking up fractal is the beginning of the uptrend, breaking down fractal can be the start of downtrend phase. We don't want to be in long trade if there is a high probability of reversal to the downside. This approach helps to not keep open trade if trend is not developing and hold it if price continues going up.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 2024.05.01. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 30%
Maximum Single Position Loss: -3.19%
Maximum Single Profit: +24.97%
Net Profit: +3036.90 USDT (+30.37%)
Total Trades: 83 (28.92% win rate)
Profit Factor: 1.953
Maximum Accumulated Loss: 963.98 USDT (-8.29%)
Average Profit per Trade: 36.59 USDT (+1.12%)
Average Trade Duration: 72 hours
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 4h and higher time frames and the BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
ADR Study [TFO]This indicator is focused on the Average Daily Range (ADR), with the goal of collecting data to show how often price reaches/closes through these levels, as well as a look at historical moves that reached ADR and at similar times of day to study how price moved for the remainder of the session.
The ADR here (blue line) is calculated using the difference between a day's highest and lowest points. If our ADR length is 5, then we are taking this difference from the last 5 days and averaging them together. At the following day's open, we take half of this average and plot it above and below the daily opening price to place theoretical limits on how far price may move according to the lookback period. The triangles indicate when price has reached ADR (either +ADR or -ADR), and alerts can be created for these events.
The Scale Factor is an optional parameter to scale the ADR by a certain amount. If set to 2 for example, then the ADR would be 2x the average daily range. This value will be reflected in the statistics options so that users can see how different values affect the outcomes.
Show Table will display data collected on how often price reaches these levels, and how often price closes through them, for each day of the week. By default, these are colored as blue and red, respectively. From the following chart of NQ1!, we can see for example that on Mondays, price reached +ADR 38% of the time and closed through it 23% of the time. Note that the statistics for closing through the ADR levels are derived from all instances, not just those that reached ADR.
Show Sample Sizes will display how many instances were collected for all given sets of data. Referring to the same example of NQ1!, we can see that this particular chart has collected data from 109 Mondays. From those Mondays, 41 reached +ADR (38%, verifying our initial claim) and 25 closed through it (23%). This is important to understand the scope of the data that we're working with, as percentages can be misleading for smaller sample sizes.
Show Histogram will plot the same exact data as the table, just in a histogram form to visually emphasize the differences on a day-by-day basis. On this chart of RTY1!, we can see for example from the top histogram that on Wednesdays, 40% reached +ADR and only 22% closed through it. Similarly if we look at the bottom histogram, we can see that Wednesdays reached -ADR 46% of the time and closed through it only 28% of the time.
We can also use Show Sample Sizes to display the same information that would be in the table, showing how many instances were collected for each event. In this case we can see that we observed 175 Fridays, where 76 reached +ADR (43%) and 44 closed above it (25%).
Show Historical Moves is an interesting feature of this script. When enabled, if price has reached +/- ADR in the current session, the indicator will plot the evolution of the close prices from all past sessions that reached +/- ADR to see how they traded for the remainder of the session. These calculations are made with respect to the ADR range at the time that price traded through these levels.
Historical Proximity (Bars) allows the user to observe historical moves where price reached ADR within this many bars of the current session (assuming price has reached an ADR level in the current session). In the above chart, this is set to 1000 so that we can observe each and every instance where price reached an ADR level. However, we can refine this a bit more.
By limiting the Historical Proximity to something like 20, we are only considering historical moves that reached ADR within 20 bars of todays +ADR reach (9:50 am EST, noted by the blue triangle up). We can enable Show Average Move to display the average move by the filtered dataset, and Match +/-ADR to only observe moves inline with the current day's price action (in this case, only moves that reached +ADR, since price has not reached -ADR).
We can add one more filter to this data with the setting Only Show Days That: closed through ADR; closed within ADR; or either. The option either is what you see above, as we are considering both days that closed through ADR and days that closed within it (note that in this case, closing within ADR simply means that price reached +ADR and closed the day below it, and vice versa for -ADR; this does not mean that price must have closed in between +ADR and -ADR). If we set this to only show instances that closed within ADR, we see the following data.
Alternatively, we can choose to Only Show Days That closed through ADR, where we would see the following data. In this case, the average move very much resembles the price action that occurred on this particular day. This is in no way guaranteed, but it makes an interesting case for how we could use this data in our analysis by observing similar, historical price action.
Please note that this data will change over time on a rolling basis due to TradingView's bar lookback, and that for this same reason, lower timeframes will yield less data than larger timeframes.
SLOPED Trailing SL with ATR-V1SLOPED Trailing SL with ATR
I thought capital is sometime locked for long periods s when volatility is low, hence:
SLOPED Trailing SL with ATR
This indicator provides a trailing stop loss that dynamically adjusts based on the Average True Range (ATR) and incorporates a user-defined upward slope on flat areas. It is designed to follow the price movement more closely during trends while allowing for a customizable slope to maintain a trailing stop even when the price movement is flat.
Key Features:
ATR-Based Stop Loss:
Utilizes the ATR to calculate a dynamic stop loss level, adjusting to market volatility.
Provides a normal ATR stop loss line that only trails upwards, preventing it from decreasing.
Upward Slope on Flat Areas:
Adds a user-defined upward slope to the trailing stop loss when the price movement is flat.
The slope value is specified in 1/1000 increments (e.g., 0.1% per bar), allowing for fine-tuned control.
Momentum Alligator 4h Bitcoin StrategyOverview
The Momentum Alligator 4h Bitcoin Strategy is a trend-following trading system that operates on dual time frames. It utilizes the 1D Williams Alligator indicator to identify the prevailing major price trend and seeks trading opportunities on the 4-hour (4h) time frame when the momentum is turning up. The strategy is designed to close trades if the trend fails to develop or holding position if price continues increasing without any significant correction. Note that this strategy is specifically tailored for the 4-hour time frame.
Unique Features
2-layers market noise filtering system: Trades are only initiated in the direction of the 1D trend, determined by the Williams Alligator indicator. This higher time frame confirmation filters out minor trade signals, focusing on more substantial opportunities. At the same time, strategy has additional filter on 4h time frame with Awesome Oscillator which is showing the current price momentum.
Flexible Risk Management: The strategy exclusively opens long positions, resulting in fewer trades during bear markets. It incorporates a dynamic stop-loss mechanism, which can either follow the jaw line of the 4h Alligator or a user-defined fixed stop-loss. This flexibility helps manage risk and avoid non-trending markets.
Methodology
The strategy initiates a long position when the d-line of Stochastic RSI crosses up it's k-line. It means that there is a high probability that price momentum reversed from down to up. To avoid overtrading in potentially choppy markets, it skips the next two trades following a winning trade, anticipating sideways movement after a significant price surge.
This strategy has two layers trades filtering system: 4h and 1D time frames. The first one is awesome oscillator. It shall be increasing and value has to be higher than it's 5-period SMA. This is an additional confirmation that long trade is opened in the direction of the current momentum. As it was mentioned above, all entry signals are validated against the 1D Williams Alligator indicator. A trade is only opened if the price is above all three lines of the 1D Alligator, ensuring alignment with the major trend.
A trade is closed if the price hits the 4h jaw line of the Alligator or reaches the user-defined stop-loss level.
Risk Management
The strategy employs a combined approach to risk management:
It allows positions to ride the trend as long as the price continues to move favorably, aiming to capture significant price movements. It features a user-defined stop-loss parameter to mitigate risks based on individual risk tolerance. By default, this stop-loss is set to a 2% drop from the entry point, but it can be adjusted according to the trader's preferences.
Justification of Methodology
This strategy leverages Stochastic RSI on 4h time frame to open long trade when momentum started reversing to the upside. On the one hand, Stochastic RSI is one of the most sensitive indicator, which allows to react fast on the potential trend reversal. On the other hand, this indicator can be too sensitive and provide a lot of false trend changing signals. To eliminate this weakness we use two-layers trades filtering system.
The first layer is the 4h Awesome oscillator. This is less sensitive momentum indicator. Usually it starts increasing when price has already passed significant distance from the actual reversal point. The strategy opens long trade only is Awesome oscillator is increasing and above it's 5-period SMA. This approach increases the probability to filter the false signals during the choppy market or if the reversal is false.
The second layer filter is the Williams Alligator indicator on 1D time frame. The 1D Alligator serves as a filter for identifying the primary trend and increases probability to avoid the trades with low potential because trading against major trend usually is more risky. It's much better to catch the trend continuation than local bounce.
Last but not least feature of this strategy is close trades condition. It uses the flexible approach. First of all, user can set up the fixed stop-loss according to his own risk-tolerance, by default this value is 2% of price movement. It restricts the potential loss at the moment when trade has just been opened. Moreover strategy utilizes the 4h Williams Alligator's jaw line to exit the trade. If price fell below it trade is closed. This approach helps to not keep open trade if trend is not developing and hold it if price continues going up.
Backtest Results:
Operating window: Date range of backtests is 2021.01.01 - 2024.05.01. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 50%
Maximum Single Position Loss: -3.04%
Maximum Single Profit: +29.67%
Net Profit: +6228.01 USDT (+62.28%)
Total Trades: 118 (24.58% win rate)
Profit Factor: 1.71
Maximum Accumulated Loss: 1527.69 USDT (-11.52%)
Average Profit per Trade: 52.78 USDT (+0.89%)
Average Trade Duration: 60 hours
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
How to Use:
Add the script to favorites for easy access.
Apply to the 4h timeframe desired chart (optimal performance observed on the BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
Breadth Indicators NYSE Percent Above Moving AverageBreadth Indicators NYSE - transmits the processed data from the Barchart provider
NYSE - Breadth Indicators
S&P 500 - Breadth Indicators
DOW - Breadth Indicators
RUSSEL 1000 - Breadth Indicators
RUSSEL 2000 - Breadth Indicators
RUSSEL 3000 - Breadth Indicators
Moving Average - 5, 20, 50, 100, 150, 200
The "Percentage above 50-day SMA" indicator measures the percentage of stocks in the index trading above their 50-day moving average. It is a useful tool for assessing the general state of the market and identifying overbought and oversold conditions.
One way to use the "Percentage above 50-day SMA" indicator in a trading strategy is to combine it with a long-term moving average to determine whether the trend is bullish or bearish. Another way to use it is to combine it with a short-term moving average to identify pullbacks and rebounds within the overall trend.
The purpose of using the "Percentage above 50-day SMA" indicator is to participate in a larger trend with a better risk-reward ratio. By using this indicator to identify pullbacks and bounces, you can reduce the risk of entering trades at the wrong time.
Bull Signal Recap:
150-day EMA of $SPXA50R crosses above 52.5 and remains above 47.50 to set the bullish tone.
5-day EMA of $SPXA50R moves below 40 to signal a pullback
5-day EMA of $SPXA50R moves above 50 to signal an upturn
Bear Signal Recap:
150-day EMA of $SPXA50R crosses below 47.50 and remains below 52.50 to set the bearish tone.
5-day EMA of $SPXA50R moves above 60 to signal a bounce
5-day EMA of $SPXA50R moves below 50 to signal a downturn
Tweaking
There are numerous ways to tweak a trading system, but chartists should avoid over-optimizing the indicator settings. In other words, don't attempt to find the perfect moving average period or crossover level. Perfection is unattainable when developing a system or trading the markets. It is important to keep the system logical and focus tweaks on other aspects, such as the actual price chart of the underlying security.
What do levels above and below 50% signify in the long-term moving average?
A move above 52.5% is deemed bullish, and below 47.5% is deemed bearish. These levels help to reduce whipsaws by using buffers for bullish and bearish thresholds.
How does the short-term moving average work to identify pullbacks or bounces?
When using a 5-day EMA, a move below 40 signals a pullback, and a move above 60 signals a bounce.
How is the reversal of pullback or bounce identified?
A move back above 50 after a pullback or below 50 after a bounce signals that the respective trend may be resuming.
How can you ensure that the uptrend has resumed?
It’s important to wait for the surge above 50 to ensure the uptrend has resumed, signaling improved breadth.
Can the system be tweaked to optimize indicator settings?
While there are various ways to tweak the system, seeking perfection through over-optimizing settings is advised against. It's crucial to keep the system logical and focus tweaks on the price chart of the underlying security.
RUSSIAN \ Русская версия.
Индикатор "Процент выше 50-дневной скользящей средней" измеряет процент акций, торгующихся в индексе выше их 50-дневной скользящей средней. Это полезный инструмент для оценки общего состояния рынка и выявления условий перекупленности и перепроданности.
Один из способов использования индикатора "Процент выше 50-дневной скользящей средней" в торговой стратегии - это объединить его с долгосрочной скользящей средней, чтобы определить, является ли тренд бычьим или медвежьим. Другой способ использовать его - объединить с краткосрочной скользящей средней, чтобы выявить откаты и отскоки в рамках общего тренда.
Цель использования индикатора "Процент выше 50-дневной скользящей средней" - участвовать в более широком тренде с лучшим соотношением риска и прибыли. Используя этот индикатор для выявления откатов и отскоков, вы можете снизить риск входа в сделки в неподходящее время.
Краткое описание бычьего сигнала:
150-дневная ЕМА на уровне $SPXA50R пересекает отметку 52,5 и остается выше 47,50, что задает бычий настрой.
5-дневная ЕМА на уровне $SPXA50R опускается ниже 40, сигнализируя об откате
5-дневная ЕМА на уровне $SPXA50R поднимается выше 50, сигнализируя о росте
Обзор медвежьих сигналов:
150-дневная ЕМА на уровне $SPXA50R пересекает уровень ниже 47,50 и остается ниже 52,50, что указывает на медвежий настрой.
5-дневная ЕМА на уровне $SPXA50R поднимается выше 60, сигнализируя о отскоке
5-дневная ЕМА на уровне $SPXA50 опускается ниже 50, что сигнализирует о спаде
Корректировка
Существует множество способов настроить торговую систему, но графологам следует избегать чрезмерной оптимизации настроек индикатора. Другими словами, не пытайтесь найти идеальный период скользящей средней или уровень пересечения. Совершенство недостижимо при разработке системы или торговле на рынках. Важно поддерживать логику системы и уделять особое внимание другим аспектам, таким как график фактической цены базовой ценной бумаги.
Что означают уровни выше и ниже 50% в долгосрочной скользящей средней?
Движение выше 52,5% считается бычьим, а ниже 47,5% - медвежьим. Эти уровни помогают снизить риски, используя буферы для бычьих и медвежьих порогов.
Как краткосрочная скользящая средняя помогает идентифицировать откаты или отскоки?
При использовании 5-дневной ЕМА движение ниже 40 указывает на откат, а движение выше 60 указывает на отскок.
Как определяется разворот отката или отскока?
Движение выше 50 после отката или ниже 50 после отскока сигнализирует о возможном возобновлении соответствующего тренда.
Как вы можете гарантировать, что восходящий тренд возобновился?
Важно дождаться скачка выше 50, чтобы убедиться в возобновлении восходящего тренда, сигнализирующего о расширении диапазона.
Можно ли настроить систему для оптимизации настроек индикатора?
Хотя существуют различные способы настройки системы, не рекомендуется стремиться к совершенству с помощью чрезмерной оптимизации настроек. Крайне важно сохранить логичность системы и сфокусировать изменения на ценовом графике базовой ценной бумаги.
Volume Storm Trend [ChartPrime]The Volume Storm Trend (VST) indicator is a robust tool for traders looking to analyze volume momentum and trend strength in the market. By incorporating key volume-based calculations and dynamic visualizations, VST provides clear insights into market conditions.
Components:
Calculating the median of the source data.
Volume Power Calculation: The indicator calculates the "heat power" and "cold power" by applying an Exponential Moving Average (EMA) to the median of volume data arrays.
// ---------------------------------------------------------------------------------------------------------------------}
// 𝙄𝙉𝘿𝙄𝘾𝘼𝙏𝙊𝙍 𝘾𝘼𝙇𝘾𝙐𝙇𝘼𝙏𝙄𝙊𝙉𝙎
// ---------------------------------------------------------------------------------------------------------------------{
max_val = 1000
src = close
source = ta.median(src, len)
heat.push(src > source ? (volume > max_val ? max_val : volume) : 0)
heat.remove(0)
cold.push(src < source ? (volume > max_val ? max_val : volume) : 0)
cold.remove(0)
heat_power = ta.ema(heat.median(), 10)
cold_power = ta.ema(cold.median(), 10)
Visualization:
Gradient Colors: The indicator uses gradient colors to visualize bullish volume and bearish volume powers, providing a clear contrast between rising and falling trends.
Bars Fill Color: The color fill between high and low prices changes based on whether the heat power is greater than the cold power.
Bottom Line: A zero line with changing colors based on the dominance of heat or cold power.
Weather Symbols: Visual indicators ("☀" for hot weather and "❄" for cold weather) appear on the chart when the heat and cold powers crossover, helping traders quickly identify trend changes.
Inputs:
Source: The input data source, typically the closing price.
Median Length: The period length for calculating the median of the source. Default is 40.
Volume Length: The period length for calculating the average volume. Default is 3.
Show Weather: A toggle to display weather symbols on the chart. Default is false.
Temperature Type: Allows users to choose between Celsius (°C) and Fahrenheit (°F) for temperature display.
Show Weather Function:
The `Show Weather?` function enhances the VST indicator by displaying weather symbols ("☀" for hot and "❄" for cold) when there are significant crossovers between heat power and cold power. This feature adds a visual cue for potential market tops and bottoms. When the market heats to a high temperature, it often indicates a potential top, signaling traders to consider exiting long positions or preparing for a reversal.
Additional Features:
Dynamic Table Display: A table displays the current "temperature" on the chart, indicating market heat based on the calculated heat and cold powers.
The Volume Storm Trend indicator is a powerful tool for traders
looking to enhance their market analysis with volume and momentum insights, providing a clear and visually appealing representation of key market dynamics.
20% in Last 5 DaysWhat we have
Condition met 1 --> It means we have more than 20% move in last 5 Days
we have Lookback Period of 504 days that means 2 years data it will analyze
The first blue label means --> We have a move of 20% or more in last fast days
--It is very helpful who want to create a idea chart book for them to study all 20% moves
--Like what happened on the first day, second day, third day, fourth day and fifth day
--If they study a lot of charts they have many 20% moves in last 5 days
After analyzing 1000 of charts You can create a model book for best 100 charts
Like what you want to see in the full move
it will create a visual memory and help you in trading 20% moves in 5 days
IU Support and Resistance How this script works :
1. This script is an indicator script which calculates the support and resistance based on pivot high and pivot low and plot them as zone onto the chart.
2. The first user input is minimum number of touches which indicates how many time pivot high or pivot low should be tested in order to be a valid support or resistance level.
3.The second user input "Set Buffer" check if the user wants to use a custom buffer or not if it's unchanged then the default is 50% of the 1000 period ATR value .
4. If "Set Buffer" is checked meaning if it's set to true then only the third user input will be execute which is the "buffer" which indicates how much price range user wants his zone to have.
5. After the user input part this script create two arrays to store the pivot high and pivot low values every time he have a new value.
6. This script also creates two arrays to store the bar index of the bar where the new pivot high or pivot low is detected those bar index will be later use while creating the support and resistance zones.
7. Then the script creates four more arrays to store the final support and resistance values and their respective bar index which will be use for creating the support and resistance zones.
8. After this the script check that we are at the last bar of our chart if we are then we sort the support and resistance indices by descending order and store them into an new variable after that we sort the support and resistance arrays by descending order, then we loop through the arrays elements and we check if the previous element comes under the zone of the current element if so we increase the "minimum touch" variable by 1, once we have 5 or more count in our variable and we no longer have a valid zone then we store the element value and the sorted index of the element into our final arrays.
9. Finally the script will loop through the final support and resistance arrays and it will create a box for each support and resistance with respect to extending it on both directions.
10.The green zones are the support and the red zones are the resistance.
How user can benifits from this script:
1. User can automatically identify support and resistance zones and he can plan his trade as per that.
2. User can test how different markets reacts with support and resistance zones.
3. User can plan breakout trade on the break of the support or resistance level.
4. User can adjust he stop loss and take profit as per the support and resistance zones.
