Hyperbolic Tangent Volatility Stop [InvestorUnknown]The Hyperbolic Tangent Volatility Stop (HTVS) is an advanced technical analysis tool that combines the smoothing capabilities of the Hyperbolic Tangent Moving Average (HTMA) with a volatility-based stop mechanism. This indicator is designed to identify trends and reversals while accounting for market volatility.
Hyperbolic Tangent Moving Average (HTMA):
The HTMA is at the heart of the HTVS. This custom moving average uses a hyperbolic tangent transformation to smooth out price fluctuations, focusing on significant trends while ignoring minor noise. The transformation reduces the sensitivity to sharp price movements, providing a clearer view of the underlying market direction.
The hyperbolic tangent function (tanh) is commonly used in mathematical fields like calculus, machine learning and signal processing due to its properties of “squashing” inputs into a range between -1 and 1. The function provides a non-linear transformation that can reduce the impact of extreme values while retaining a certain level of smoothness.
tanh(x) =>
e_x = math.exp(x)
e_neg_x = math.exp(-x)
(e_x - e_neg_x) / (e_x + e_neg_x)
The HTMA is calculated by applying a non-linear transformation to the difference between the source price and its simple moving average, then adjusting it using the standard deviation of the price data. The result is a moving average that better tracks the real market direction.
htma(src, len, mul) =>
tanh_src = tanh((src - ta.sma(src, len)) * mul) * ta.stdev(src, len) + ta.sma(src, len)
htma = ta.sma(tanh_src, len)
Important Note: The Hyperbolic Tangent function becomes less accurate with very high prices. For assets priced above 100,000, the results may deteriorate, and for prices exceeding 1 million, the function may stop functioning properly. Therefore, this indicator is better suited for assets with lower prices or lower price ratios.
Volatility Stop (VolStop):
HTVS employs a Volatility Stop mechanism based on the Average True Range (ATR). This stop dynamically adjusts based on market volatility, ensuring that the indicator adapts to changing conditions and avoids false signals in choppy markets.
The VolStop follows the price, with a higher ATR pushing the stop farther away to avoid premature exits during volatile periods. Conversely, when volatility is low, the stop tightens to lock in profits as the trend progresses.
The ATR Length and ATR Multiplier are customizable, allowing traders to control how tightly or loosely the stop follows the price.
pine_volStop(src, atrlen, atrfactor) =>
if not na(src)
var max = src
var min = src
var uptrend = true
var float stop = na
atrM = nz(ta.atr(atrlen) * atrfactor, ta.tr)
max := math.max(max, src)
min := math.min(min, src)
stop := nz(uptrend ? math.max(stop, max - atrM) : math.min(stop, min + atrM), src)
uptrend := src - stop >= 0.0
if uptrend != nz(uptrend , true)
max := src
min := src
stop := uptrend ? max - atrM : min + atrM
Backtest Mode:
HTVS includes a built-in backtest mode, allowing traders to evaluate the indicator's performance on historical data. In backtest mode, it calculates the cumulative equity curve and compares it to a simple buy and hold strategy.
Backtesting features can be adjusted to focus on specific signal types, such as Long Only, Short Only, or Long & Short.
An optional Buy and Hold Equity plot provides insight into how the indicator performs relative to simply holding the asset over time.
The indicator includes a Hints Table, which provides useful recommendations on how to best display the indicator for different use cases. For example, when using the overlay mode, it suggests displaying the indicator in the same pane as price action, while backtest mode is recommended to be used in a separate pane for better clarity.
The Hyperbolic Tangent Volatility Stop offers traders a balanced approach to trend-following, using the robustness of the HTMA for smoothing and the adaptability of the Volatility Stop to avoid whipsaw trades during volatile periods. With its backtesting features and alert system, this indicator provides a comprehensive toolkit for active traders.
趋势分析
Hyperbolic Tangent SuperTrend [InvestorUnknown]The Hyperbolic Tangent SuperTrend (HTST) is designed for technical analysis, particularly in markets with assets that have lower prices or price ratios. This indicator leverages the Hyperbolic Tangent Moving Average (HTMA), a custom moving average calculated using the hyperbolic tangent function, to smooth price data and reduce the impact of short-term volatility.
Hyperbolic Tangent Moving Average (HTMA):
The indicator's core uses a hyperbolic tangent function to calculate a smoothed average of the price. The HTMA provides enhanced trend-following capabilities by dampening the impact of sharp price swings and maintaining a focus on long-term market movements.
The hyperbolic tangent function (tanh) is commonly used in mathematical fields like calculus, machine learning and signal processing due to its properties of “squashing” inputs into a range between -1 and 1. The function provides a non-linear transformation that can reduce the impact of extreme values while retaining a certain level of smoothness.
tanh(x) =>
e_x = math.exp(x)
e_neg_x = math.exp(-x)
(e_x - e_neg_x) / (e_x + e_neg_x)
The HTMA is calculated by taking the difference between the price and its simple moving average (SMA), applying a multiplier to control sensitivity, and then transforming it using the hyperbolic tangent function.
htma(src, len, mul) =>
tanh_src = tanh((src - ta.sma(src, len)) * mul) * ta.stdev(src, len) + ta.sma(src, len)
htma = ta.sma(tanh_src, len)
Important Note: The Hyperbolic Tangent function becomes less accurate with very high prices. For assets priced above 100,000, the results may deteriorate, and for prices exceeding 1 million, the function may stop functioning properly. Therefore, this indicator is better suited for assets with lower prices or lower price ratios.
SuperTrend Calculation:
In addition to the HTMA, the indicator includes an Average True Range (ATR)-based SuperTrend calculation, which helps identify uptrends and downtrends in the market. The SuperTrend is adjusted dynamically using the HTMA to avoid false signals in fast-moving markets.
The ATR period and multiplier are customizable, allowing users to fine-tune the sensitivity of the trend signals.
pine_supertrend(src, calc_price, atrPeriod, factor) =>
atr = ta.atr(atrPeriod)
upperBand = src + factor * atr
lowerBand = src - factor * atr
prevLowerBand = nz(lowerBand )
prevUpperBand = nz(upperBand )
lowerBand := lowerBand > prevLowerBand or calc_price < prevLowerBand ? lowerBand : prevLowerBand
upperBand := upperBand < prevUpperBand or calc_price > prevUpperBand ? upperBand : prevUpperBand
int _direction = na
float superTrend = na
prevSuperTrend = superTrend
if na(atr )
_direction := 1
else if prevSuperTrend == prevUpperBand
_direction := calc_price > upperBand ? -1 : 1
else
_direction := calc_price < lowerBand ? 1 : -1
superTrend := _direction == -1 ? lowerBand : upperBand
Inbuilt Backtest Mode:
The HTST includes an inbuilt backtest mode that enables users to test the indicator's performance against historical data, similar to TradingView strategies.
The backtest mode allows you to compare the performance of different indicator settings with a simple buy and hold strategy to assess its effectiveness in different market conditions.
Hint Table for Display Modes:
The indicator includes a Hint Table that recommends the best pane to use for different display modes. For example, it suggests using the "Overlay" mode in the same pane as the price action, while the "Backtest Mode" is better suited for a separate pane. This ensures a more organized and clear visual experience.
The Hint Table appears as a small table at the bottom of the chart with easy-to-follow recommendations, ensuring the best setup for both visual clarity and indicator functionality.
With these features, the Hyperbolic Tangent SuperTrend Indicator offers traders a versatile and customizable tool for analyzing price trends while providing additional functionalities like backtesting and display mode hints for optimal usability.
Bullish Gap Up DetectionThis indicator is designed to identify gap-up trading opportunities in real-time. A gap-up occurs when the opening price of a stock is higher than the previous day's high, signaling potential bullish momentum.
Key Features :
Gap Detection : The indicator detects when today’s open is above yesterday’s high and remains above that level throughout the trading session.
Visual Alerts : A triangle shape appears below the price bar when a gap-up condition is met, providing clear visual signals for traders to consider potential entry points.
EMA Analysis : The indicator incorporates two Exponential Moving Averages:
10-day EMA: Used to assess short-term price trends and help determine if the stock is currently in an upward momentum phase.
20-day EMA: Provides additional context for medium-term trends, ensuring that gaps are only considered when the stock is in a favorable trend.
The indicator confirms that the 10-day EMA is above the 20-day EMA, indicating bullish sentiment in the market.
This indicator can be used in various trading strategies to capitalize on momentum following gap-up openings. It’s suitable for day traders and swing traders looking for entry points in trending stocks.
Thrax - Intraday Market Pressure ZonesTHRAX - INTRADAY MARKET PRESSURE ZONES
This indicator identifies potential support and resistance zones based on areas of significant market pressure. It dynamically plots these zones and adjusts their visibility based on real-time price action and user-defined thresholds. The indicator is useful for traders seeking to understand intraday market pressure, visualize zones of potential price reversals, and analyze volume imbalances at critical levels.
1. Support/Resistance Zones: Wherever the price retraces significantly from its high a support zone is drawn and when it retraces significantly from it low a resistance zone is drawn. The significant retracing is measured by the wick threshold percentage. For instance, if set to 75%, it implies price retracement of 75% either from high or from low for a particular candel
Volume delat: Displays volume delta information where the zones are formed. This can be used by trader to consider only those zones where delta is significant.
2. Breakout Detection: Monitors for price breakouts beyond established zones, deleting zones that are invalidated by price movement. when the price breaks a given zone with the threshold, it is considered to be mitigated and chances of trend continuation is decent.
Candle Coloring: Uses color codes (green, red, and yellow) to represent bullish, bearish, and indecisive (doji) candles, aiding quick visual assessment.
INPUTS
1. Wick Threshold (%) : Sets the minimum wick percentage required for a candle to be considered a support or resistance candidate.
2. Breakout Threshold (%) : Determines the percentage above or below a support or resistance zone that defines a breakout condition. if breaks a zone with the set threshold then the zone will be considered mititgated.
3. Max Number of Support/Resistance Zones : Limits the maximum number of support/resistance zones displayed on the chart, ranging from 1 to 5.
4. Show Wick Percentage Labels : Toggles the display of percentage values for upper and lower wicks on each candle.
TRADE SETUP
Identifying Entry Points: Look for the formation of support or resistance zones. Wait for price to retrace to these zones. if you are willing to take risk, you can consider even zones with low delta. If you want to be more cautious you should consider zones with high delta.
Volume Confirmation: Use the volume information to confirm the strength of the zone. Strong volume differences (displayed as labels) can indicate significant market pressure at these levels.
Breakout Trades: If price breaks through a support/resistance zone by more than the breakout threshold, consider this a signal for a potential trend continuation in the breakout direction.
Risk Management: Set stop-loss levels slightly outside of the identified zones to minimize risk in case of false breakouts. This can be set in input setting for breakout threshold.
Bonus Tip : Mark your significant highs and lows from where prices have retraced multiple times in the near past and if the zone is near these levels it can serve s a strong candidate of support or resistance
Therefore, in conclusion monitor the zones, based on delta and volume presence filter out the zone, wait for price retracement to the zone, intiate the trade with stop loss below zone with a set percentage.
Momentum Cloud.V33🌟 Introducing MomentumCloud.V33 🌟
MomentumCloud.V33 is a cutting-edge indicator designed to help traders capture market momentum with clarity and precision. This versatile tool combines moving averages, directional movement indexes (DMI), and volume analysis to provide real-time insights into trend direction and strength. Whether you’re a scalper, day trader, or swing trader, MomentumCloud.V33 adapts to your trading style and timeframe, making it an essential addition to your trading toolkit. 📈💡
🔧 Customizable Parameters:
• Moving Averages: Adjust the periods of the fast (MA1) and slow (MA2) moving averages to fine-tune your trend analysis.
• DMI & ADX: Customize the DMI length and ADX smoothing to focus on strong, actionable trends.
• Volume Multiplier: Modify the cloud thickness based on trading volume, emphasizing trends with significant market participation.
📊 Trend Detection:
• Color-Coded Clouds:
• Green Cloud: Indicates a strong uptrend, suggesting buying opportunities.
• Red Cloud: Indicates a strong downtrend, signaling potential short trades.
• Gray Cloud: Reflects a range-bound market, helping you avoid low-momentum periods.
• Dynamic Volume Integration: The cloud thickness adjusts dynamically with trading volume, highlighting strong trends supported by high market activity.
📈 Strength & Momentum Analysis:
• Strength Filtering: The ADX component ensures that only strong trends are highlighted, filtering out market noise and reducing false signals.
• Visual Momentum Gauge: The cloud color and thickness provide a quick visual representation of market momentum, enabling faster decision-making.
🔔 Alerts:
• Custom Alerts: Set up alerts for when the trend shifts or reaches critical levels, keeping you informed without needing to constantly monitor the chart.
🎨 Visual Enhancements:
• Gradient Cloud & Shadows: The indicator features a gradient-filled cloud with shadowed moving averages, enhancing both aesthetics and clarity on your charts.
• Adaptive Visual Cues: MomentumCloud.V33’s color transitions and dynamic thickness provide an intuitive feel for the market’s rhythm.
🚀 Quick Guide to Using MomentumCloud.V33
1. Add the Indicator: Start by adding MomentumCloud.V33 to your chart. Customize the settings such as MA periods, DMI length, and volume multiplier to match your trading style.
2. Analyze the Market: Observe the color-coded cloud and its thickness to gauge market momentum and trend direction. The thicker the cloud, the stronger the trend.
3. Set Alerts: Activate alerts for trend changes or key levels to capture trading opportunities without needing to watch the screen continuously.
⚙️ How It Works:
MomentumCloud.V33 calculates market momentum by combining moving averages, DMI, and volume. The cloud color changes based on the trend direction, while its thickness reflects the strength of the trend as influenced by trading volume. This integrated approach ensures you can quickly identify robust market movements, making it easier to enter and exit trades at optimal points.
Settings Overview:
• Moving Averages: Define the lengths for the fast and slow moving averages.
• DMI & ADX: Adjust the DMI length and ADX smoothing to focus on significant trends.
• Volume Multiplier: Customize the multiplier to control cloud thickness, highlighting volume-driven trends.
📚 How to Use MomentumCloud.V33:
• Trend Identification: The direction and color of the cloud indicate the prevailing trend, while the cloud’s thickness suggests the trend’s strength.
• Trade Execution: Use the green cloud to look for long entries and the red cloud for short positions. The gray cloud advises caution, as it represents a range-bound market.
• Alerts: Leverage the custom alerts to stay on top of market movements and avoid missing critical trading opportunities.
Unleash the power of trend and momentum analysis with MomentumCloud.V33! Happy trading! 📈🚀✨
Multi-Step FlexiSuperTrend - Indicator [presentTrading]This version of the indicator is built upon the foundation of a strategy version published earlier. However, this indicator version focuses on providing visual insights and alerts for traders, rather than executing trades. This one is mostly for @thorcmt.
█ Introduction and How it is Different
The **Multi-Step FlexiSuperTrend Indicator** is a versatile tool designed to provide traders with a highly customizable and flexible approach to trend analysis. Unlike traditional supertrend indicators, which focus on a single factor or threshold, the **FlexiSuperTrend** allows users to define multiple levels of take-profit targets and incorporate different trend normalization methods.
It comes with several advanced customization features, including multi-step take profits, deviation plotting, and trend normalization, making it suitable for both novice and expert traders.
BTCUSD 6hr Performance
█ Strategy, How It Works: Detailed Explanation
The **Multi-Step FlexiSuperTrend** works by calculating a supertrend based on multiple factors and incorporating oscillations from trend deviations. Here’s a breakdown of how it functions:
🔶 SuperTrend Calculation
At the heart of the indicator is the SuperTrend formula, which dynamically adjusts based on price movements.
🔶 Normalization of Deviations
To enhance accuracy, the **FlexiSuperTrend** calculates multiple deviations from the trend and normalizes them.
🔶 Multi-Step Take Profit Levels
The indicator allows setting up to three take profit levels, which are displayed via price level alerts. lows traders to exit part of their position at various profit intervals.
For more detail, please check the strategy version - Multi-Step-FlexiSuperTrend-Strategy:
and 'FlexiSuperTrend-Strategy'
█ Trade Direction
The **Multi-Step FlexiSuperTrend Indicator** supports both long and short trade directions.
This flexibility allows traders to adapt to trending, volatile, or sideways markets.
█ Usage
To use the **FlexiSuperTrend Indicator**, traders can set up their preferences for the following key features:
- **Trading Direction**: Choose whether to focus on long, short, or both signals.
- **Indicator Source**: The price source to calculate the trend (e.g., close, hl2).
- **Indicator Length**: The number of periods to calculate the ATR and trend (the larger the value, the smoother the trend).
- **Starting and Increment Factor**: These adjust how reactive the trend is to price movements. The starting factor dictates how far the initial trend band is from the price, and the increment factor adjusts subsequent trend deviations.
The indicator then displays buy and sell signals on the chart, along with alerts for each take-profit level.
Local picture
█ Default Settings
The default settings of the **Multi-Step FlexiSuperTrend** are carefully designed to provide an optimal balance between sensitivity and accuracy. Let’s examine these default parameters and their effect on performance:
🔶 Indicator Length (Default: 10)
The **Indicator Length** determines the lookback period for the ATR calculation. A smaller value makes the indicator more reactive to price changes, but may generate more false signals. A longer length smooths the trend and reduces noise but may delay signals.
Effect on performance: Shorter lengths perform better in volatile markets, while longer lengths excel in trending markets.
🔶 Starting Factor (Default: 0.618)
This factor adjusts the starting distance of the SuperTrend from the current price. The smaller the starting factor, the closer the trend is to the price, making it more sensitive. Conversely, a larger factor allows more distance, reducing sensitivity but filtering out false signals.
Effect on performance: A smaller factor provides quicker signals but can lead to frequent false positives. A larger factor generates fewer but more reliable signals.
🔶 Increment Factor (Default: 0.382)
The **Increment Factor** controls how the trend bands adjust as the price moves. It increases the distance of the bands from the price with each iteration.
Effect on performance: A higher increment factor can result in wider stop-loss or trend reversal bands, allowing for longer trends to develop without frequent exits. A lower factor keeps the bands closer to the price and is more suited for shorter-term trades.
🔶 Take Profit Levels (Default: 2%, 8%, 18%)
The default take-profit levels are set at 2%, 8%, and 18%. These values represent the thresholds at which the trader can partially exit their positions. These multi-step levels are highly customizable depending on the trader’s risk tolerance and strategy.
Effect on performance: Lower take-profit levels (e.g., 2%) capture small, quick profits in volatile markets, while higher levels (8%-18%) allow for a more gradual exit in strong trends.
🔶 Normalization Method (Default: None)
The default normalization method is **None**, meaning the deviations are not normalized. However, enabling normalization (e.g., **Max-Min**) can improve the clarity of the indicator’s signals in volatile or choppy markets by smoothing out the noise.
Effect on performance: Using a normalization method can reduce the effect of extreme deviations, making signals more stable and less prone to false positives.
Bitcoin Logarithmic Growth Curve 2024The Bitcoin logarithmic growth curve is a concept used to analyze Bitcoin's price movements over time. The idea is based on the observation that Bitcoin's price tends to grow exponentially, particularly during bull markets. It attempts to give a long-term perspective on the Bitcoin price movements.
The curve includes an upper and lower band. These bands often represent zones where Bitcoin's price is overextended (upper band) or undervalued (lower band) relative to its historical growth trajectory. When the price touches or exceeds the upper band, it may indicate a speculative bubble, while prices near the lower band may suggest a buying opportunity.
Unlike most Bitcoin growth curve indicators, this one includes a logarithmic growth curve optimized using the latest 2024 price data, making it, in our view, superior to previous models. Additionally, it features statistical confidence intervals derived from linear regression, compatible across all timeframes, and extrapolates the data far into the future. Finally, this model allows users the flexibility to manually adjust the function parameters to suit their preferences.
The Bitcoin logarithmic growth curve has the following function:
y = 10^(a * log10(x) - b)
In the context of this formula, the y value represents the Bitcoin price, while the x value corresponds to the time, specifically indicated by the weekly bar number on the chart.
How is it made (You can skip this section if you’re not a fan of math):
To optimize the fit of this function and determine the optimal values of a and b, the previous weekly cycle peak values were analyzed. The corresponding x and y values were recorded as follows:
113, 18.55
240, 1004.42
451, 19128.27
655, 65502.47
The same process was applied to the bear market low values:
103, 2.48
267, 211.03
471, 3192.87
676, 16255.15
Next, these values were converted to their linear form by applying the base-10 logarithm. This transformation allows the function to be expressed in a linear state: y = a * x − b. This step is essential for enabling linear regression on these values.
For the cycle peak (x,y) values:
2.053, 1.268
2.380, 3.002
2.654, 4.282
2.816, 4.816
And for the bear market low (x,y) values:
2.013, 0.394
2.427, 2.324
2.673, 3.504
2.830, 4.211
Next, linear regression was performed on both these datasets. (Numerous tools are available online for linear regression calculations, making manual computations unnecessary).
Linear regression is a method used to find a straight line that best represents the relationship between two variables. It looks at how changes in one variable affect another and tries to predict values based on that relationship.
The goal is to minimize the differences between the actual data points and the points predicted by the line. Essentially, it aims to optimize for the highest R-Square value.
Below are the results:
It is important to note that both the slope (a-value) and the y-intercept (b-value) have associated standard errors. These standard errors can be used to calculate confidence intervals by multiplying them by the t-values (two degrees of freedom) from the linear regression.
These t-values can be found in a t-distribution table. For the top cycle confidence intervals, we used t10% (0.133), t25% (0.323), and t33% (0.414). For the bottom cycle confidence intervals, the t-values used were t10% (0.133), t25% (0.323), t33% (0.414), t50% (0.765), and t67% (1.063).
The final bull cycle function is:
y = 10^(4.058 ± 0.133 * log10(x) – 6.44 ± 0.324)
The final bear cycle function is:
y = 10^(4.684 ± 0.025 * log10(x) – -9.034 ± 0.063)
The main Criticisms of growth curve models:
The Bitcoin logarithmic growth curve model faces several general criticisms that we’d like to highlight briefly. The most significant, in our view, is its heavy reliance on past price data, which may not accurately forecast future trends. For instance, previous growth curve models from 2020 on TradingView were overly optimistic in predicting the last cycle’s peak.
This is why we aimed to present our process for deriving the final functions in a transparent, step-by-step scientific manner, including statistical confidence intervals. It's important to note that the bull cycle function is less reliable than the bear cycle function, as the top band is significantly wider than the bottom band.
Even so, we still believe that the Bitcoin logarithmic growth curve presented in this script is overly optimistic since it goes parly against the concept of diminishing returns which we discussed in this post:
This is why we also propose alternative parameter settings that align more closely with the theory of diminishing returns.
Our recommendations:
Drawing on the concept of diminishing returns, we propose alternative settings for this model that we believe provide a more realistic forecast aligned with this theory. The adjusted parameters apply only to the top band: a-value: 3.637 ± 0.2343 and b-parameter: -5.369 ± 0.6264. However, please note that these values are highly subjective, and you should be aware of the model's limitations.
Conservative bull cycle model:
y = 10^(3.637 ± 0.2343 * log10(x) - 5.369 ± 0.6264)
CANSLIM Screener [TrendX_]INTRODUCTION:
The CANSLIM investment strategy, developed by William J. O'Neil, is a powerful tool for identifying growth stocks that have the potential to outperform the market. TrendX has enhanced this approach with its unique indicators, making it easier for investors to assess stocks based on seven critical criteria.
➊ C: Current Quarterly EPS or PE with Growth Benchmark
The first criterion focuses on the Earnings Per Share (EPS) growth in the most recent quarter compared to previous quarters. A company should demonstrate significant EPS growth, ideally exceeding expectations and benchmarks within its industry.
➋ A: Average Annual EPS Growth with Growth Benchmark
This aspect evaluates a company's average annual EPS growth over the last three years. A consistent upward trend suggests that the company is effectively increasing its profitability. TrendX provides a customizable benchmark to help investors identify firms with sustainable growth trajectories.
➌ N: New Highs or New Product Development
TrendX interprets this criterion through an Annual Research & Development to Revenue Ratio (RNDR). A decreasing RNDR ratio may indicate that a company is finishing new products, which could lead to reduced revenue if product launches are unsuccessful.
➍ S: Supply and Demand
This component assesses supply and demand dynamics by analyzing the movement of Float Shares Outstanding. A decrease in float shares typically indicates higher demand for the stock, suggesting that the company is in good shape for future growth.
➎ L: Leader
TrendX employs comparative analysis between the Relative Strength Index (RSI) of a company and that of the overall market. If a company's RSI is higher than the market's, it signifies that the stock is leading rather than lagging.
➏ I: Institutional Sponsorship
Institutional sponsorship is gauged through the total dividends paid by a company. High dividend payouts can signal strong institutional interest, support and confidence in the company's future prospects.
➐ M: Market Direction
TrendX evaluates market direction by comparing a company's RSI against its Moving Average of RSI, along with utilizing Market Structure in Smart Money Concept indicator for alternative trend insights.
HOW TO USE
The TrendX CANSLIM indicator provides an evaluation score based on each of the seven criteria outlined above, which displays in a table containing:
Scoring System: Each letter in CANSLIM contributes to a total score out of 100%. A stock does not need to meet all seven criteria; achieving a score above 70% (5 out of 7) is generally considered indicative of a promising growth stock.
Screening Feature: The tool includes a screening feature that evaluates multiple stocks simultaneously, allowing investors to compare their CANSLIM scores efficiently. This feature streamlines identifying potential investment opportunities across various sectors.
DISCLAIMER
This indicator is not financial advice, it can only help traders make better decisions. There are many factors and uncertainties that can affect the outcome of any endeavor, and no one can guarantee or predict with certainty what will occur.
Therefore, one should always exercise caution and judgment when making decisions based on past performance.
Support and ResistanceThis indicator, titled "Support and Resistance," is designed to identify and display key price levels based on volume and pivot points. It's a versatile tool that can be adapted for different market views and timeframes.
Key Features
Market View Options
The indicator offers three market view settings:
Short term
Standard
Long term
These settings affect the lookback periods used in calculations, allowing users to adjust the indicator's sensitivity to market movements.
Volume-Based Levels
The indicator calculates support and resistance levels using a rolling Point of Control (POC) derived from volume data. This approach helps identify price levels where the most trading activity has occurred.
Pivot Points
In addition to volume-based levels, the indicator incorporates pivot points to identify potential support and resistance areas.
Customizable Appearance
Users can adjust:
Number of lines to display (1-8)
Colors for support and resistance levels
Line thickness based on level importance
Calculation Methods
Rolling POC
The indicator uses a custom function f_rolling_poc to calculate the rolling Point of Control. This function analyzes volume distribution across price levels within a specified lookback period.
Pivot Points
Both standard and quick pivot points are calculated using the rolling POC as input, rather than traditional price data.
Level Importance
The indicator assigns importance to each level based on:
Number of touches (how often price has interacted with the level)
Duration (how long the level has been relevant)
This importance score determines the thickness of the displayed lines.
Unique Aspects
Dynamic Line Thickness: Lines become thicker when levels overlap, highlighting potentially stronger support/resistance areas.
Adaptive Coloring: The color of each line changes dynamically based on whether the current price is above or below the level, indicating whether it's acting as support or resistance.
Flexible Time Frames: The market view options allow the indicator to be easily adapted for different trading styles and timeframes.
Potential Uses
This indicator could be valuable for:
Identifying key price levels for entry and exit points
Recognizing potential breakout or breakdown levels
Understanding the strength of support and resistance based on line thickness
Adapting analysis to different market conditions and timeframes
Overall, this "Support and Resistance" indicator offers a sophisticated approach to identifying key price levels, combining volume analysis with pivot points and providing visual cues for level importance and current market position.
This Support and Resistance indicator is provided for informational and educational purposes only. It should not be considered as financial advice or a recommendation to buy or sell any security. The indicator's calculations are based on historical data and may not accurately predict future market movements. Trading decisions should be made after thorough research and consultation with a licensed financial advisor. The creator of this indicator is not responsible for any losses incurred from its use. Past performance does not guarantee future results. Use at your own risk.
Multi-Step FlexiMA - Strategy [presentTrading]It's time to come back! hope I can not to be busy for a while.
█ Introduction and How It Is Different
The FlexiMA Variance Tracker is a unique trading strategy that calculates a series of deviations between the price (or another indicator source) and a variable-length moving average (MA). Unlike traditional strategies that use fixed-length moving averages, the length of the MA in this system varies within a defined range. The length changes dynamically based on a starting factor and an increment factor, creating a more adaptive approach to market conditions.
This strategy integrates Multi-Step Take Profit (TP) levels, allowing for partial exits at predefined price increments. It enables traders to secure profits at different stages of a trend, making it ideal for volatile markets where taking full profits at once might lead to missed opportunities if the trend continues.
BTCUSD 6hr Performance
█ Strategy, How It Works: Detailed Explanation
🔶 FlexiMA Concept
The FlexiMA (Flexible Moving Average) is at the heart of this strategy. Unlike traditional MA-based strategies where the MA length is fixed (e.g., a 50-period SMA), the FlexiMA varies its length with each iteration. This is done using a **starting factor** and an **increment factor**.
The formula for the moving average length at each iteration \(i\) is:
`MA_length_i = indicator_length * (starting_factor + i * increment_factor)`
Where:
- `indicator_length` is the user-defined base length.
- `starting_factor` is the initial multiplier of the base length.
- `increment_factor` increases the multiplier in each iteration.
Each iteration applies a **simple moving average** (SMA) to the chosen **indicator source** (e.g., HLC3) with a different length based on the above formula. The deviation between the current price and the moving average is then calculated as follows:
`deviation_i = price_current - MA_i`
These deviations are normalized using one of the following methods:
- **Max-Min normalization**:
`normalized_i = (deviation_i - min(deviations)) / range(deviations)`
- **Absolute Sum normalization**:
`normalized_i = deviation_i / sum(|deviation_i|)`
The **median** and **standard deviation (stdev)** of the normalized deviations are then calculated as follows:
`median = median(normalized deviations)`
For the standard deviation:
`stdev = sqrt((1/(N-1)) * sum((normalized_i - mean)^2))`
These values are plotted to provide a clear indication of how the price is deviating from its variable-length moving averages.
For more detail:
🔶 Multi-Step Take Profit
This strategy uses a multi-step take profit system, allowing for exits at different stages of a trade based on the percentage of price movement. Three take-profit levels are defined:
- Take Profit Level 1 (TP1): A small, quick profit level (e.g., 2%).
- Take Profit Level 2 (TP2): A medium-level profit target (e.g., 8%).
- Take Profit Level 3 (TP3): A larger, more ambitious target (e.g., 18%).
At each level, a corresponding percentage of the trade is exited:
- TP Percent 1: E.g., 30% of the position.
- TP Percent 2: E.g., 20% of the position.
- TP Percent 3: E.g., 15% of the position.
This approach ensures that profits are locked in progressively, reducing the risk of market reversals wiping out potential gains.
Local
🔶 Trade Entry and Exit Conditions
The entry and exit signals are determined by the interaction between the **SuperTrend Polyfactor Oscillator** and the **median** value of the normalized deviations:
- Long entry: The SuperTrend turns bearish, and the median value of the deviations is positive.
- Short entry: The SuperTrend turns bullish, and the median value is negative.
Similarly, trades are exited when the SuperTrend flips direction.
* The SuperTrend Toolkit is made by @EliCobra
█ Trade Direction
The strategy allows users to specify the desired trade direction:
- Long: Only long positions will be taken.
- Short: Only short positions will be taken.
- Both: Both long and short positions are allowed based on the conditions.
This flexibility allows the strategy to adapt to different market conditions and trading styles, whether you're looking to buy low and sell high, or sell high and buy low.
█ Usage
This strategy can be applied across various asset classes, including stocks, cryptocurrencies, and forex. The primary use case is to take advantage of market volatility by using a flexible moving average and multiple take-profit levels to capture profits incrementally as the market moves in your favor.
How to Use:
1. Configure the Inputs: Start by adjusting the **Indicator Length**, **Starting Factor**, and **Increment Factor** to suit your chosen asset. The defaults work well for most markets, but fine-tuning them can improve performance.
2. Set the Take Profit Levels: Adjust the three **TP levels** and their corresponding **percentages** based on your risk tolerance and the expected volatility of the market.
3. Monitor the Strategy: The SuperTrend and the FlexiMA variance tracker will provide entry and exit signals, automatically managing the positions and taking profits at the pre-set levels.
█ Default Settings
The default settings for the strategy are configured to provide a balanced approach that works across different market conditions:
Indicator Length (10):
This controls the base length for the moving average. A lower length makes the moving average more responsive to price changes, while a higher length smooths out fluctuations, making the strategy less sensitive to short-term price movements.
Starting Factor (1.0):
This determines the initial multiplier applied to the moving average length. A higher starting factor will increase the average length, making it slower to react to price changes.
Increment Factor (1.0):
This increases the moving average length in each iteration. A larger increment factor creates a wider range of moving average lengths, allowing the strategy to track both short-term and long-term trends simultaneously.
Normalization Method ('None'):
Three methods of normalization can be applied to the deviations:
- None: No normalization applied, using raw deviations.
- Max-Min: Normalizes based on the range between the maximum and minimum deviations.
- Absolute Sum: Normalizes based on the total sum of absolute deviations.
Take Profit Levels:
- TP1 (2%): A quick exit to capture small price movements.
- TP2 (8%): A medium-term profit target for stronger trends.
- TP3 (18%): A long-term target for strong price moves.
Take Profit Percentages:
- TP Percent 1 (30%): Exits 30% of the position at TP1.
- TP Percent 2 (20%): Exits 20% of the position at TP2.
- TP Percent 3 (15%): Exits 15% of the position at TP3.
Effect of Variables on Performance:
- Short Indicator Lengths: More responsive to price changes but prone to false signals.
- Higher Starting Factor: Slows down the response, useful for longer-term trend following.
- Higher Increment Factor: Widens the variability in moving average lengths, making the strategy adapt to both short-term and long-term price trends.
- Aggressive Take Profit Levels: Allows for quick profit-taking in volatile markets but may exit positions prematurely in strong trends.
The default configuration offers a moderate balance between short-term responsiveness and long-term trend capturing, suitable for most traders. However, users can adjust these variables to optimize performance based on market conditions and personal preferences.
E9 PLRRThe E9 PLRR (Power Law Residual Ratio) is a custom-built indicator designed to evaluate the overvaluation or undervaluation of an asset, specifically by utilizing logarithmic price data and a power law-based model. It leverages a dynamic regression technique to assess the deviation of the current price from its expected value, giving insights into how much the price deviates from its long-term trend.
This indicator is primarily used to detect market extremes and cycles, often used in the analysis of long-term price movements in assets like Bitcoin, where cyclical behavior and significant price deviations are common.
This chart is back from 2019 and shows (From left to right) 2018 Bear market bottom at $3.5k (Dark Blue) , following a peak at 12k (dark red) before the Covid crash back down to EUROTLX:4K (Dark blue)
Key Components
Logarithmic Price Data:
The indicator works with logarithmic price data (ohlc4), which represents the average of open, high, low, and close prices. The logarithmic transformation is crucial in financial modeling, especially when analyzing long-term price data, as it normalizes exponential price growth patterns.
Dynamic Exponent 𝑘:
The model calculates a dynamic exponent k using regression, which defines the power law relationship between time and price. This exponent is essential in determining the expected power law price return and how far the current price deviates from that expected trend.
Power Law Price Return:
The power law price return is computed using the dynamic exponent
k over a defined period, such as 365 days (1 year). It represents the theoretical price return based on a power law relationship, which is used to compare against the actual logarithmic price data.
Risk-Free Rate:
The indicator incorporates an adjustable risk-free rate, allowing users to model the opportunity cost of holding an asset compared to risk-free alternatives. By default, the risk-free rate is set to 0%, but this can be modified depending on the user's requirements.
Volatility Adjustment:
A key feature of the PLRR is its ability to adjust for price volatility. The indicator smooths out short-term price fluctuations using a moving average, helping to detect longer-term cycles and trends.
PLRR Calculation:
The core of the indicator is the calculation of the Power Law Residual Ratio (PLRR). This is derived by subtracting the expected power law price return and risk-free rate from the logarithmic price return, then multiplying the result by a user-defined multiplier.
Color Gradient:
The PLRR values are represented visually using a color gradient. This gradient helps the user quickly identify whether the asset is in an undervalued, fair value, or overvalued state:
Dark Blue to Light Blue: Indicates undervaluation, with increasing blue tones representing a higher degree of undervaluation.
Green to Yellow: Represents fair value, where the price is aligned with the expected power law return.
Orange to Dark Red: Indicates overvaluation, with increasing red tones representing a higher degree of overvaluation.
Zero Line:
A zero line is plotted on the indicator chart, serving as a reference point. Values above the zero line suggest potential overvaluation, while values below indicate potential undervaluation.
Dots Visualization:
The PLRR is plotted using dots, with each dot color-coded based on the PLRR value. This dot-based visualization makes it easier to spot significant changes or reversals in market sentiment without overwhelming the user with continuous lines.
Bar Coloring:
The chart’s bars are colored in accordance with the PLRR value at each point in time, making it visually clear when an asset is potentially overvalued or undervalued.
Indicator Functionality
Cycle Identification : The E9 PLRR is especially useful for identifying cyclical market behavior. In assets like Bitcoin, which are known for their boom-bust cycles, the PLRR can help pinpoint when the market is likely entering a peak (overvaluation) or a trough (undervaluation).
Overvaluation and Undervaluation Detection: By comparing the current price to its expected power law return, the PLRR helps traders assess whether an asset is trading above or below its fair value. This is critical for long-term investors seeking to enter the market at undervalued levels and exit during periods of overvaluation.
Trend Following: The indicator helps users identify the broader trend by smoothing out short-term volatility. This makes it useful for both momentum traders looking to ride trends and contrarian traders seeking to capitalize on market extremes.
Customization
The E9 PLRR allows users to fine-tune several parameters based on their preferences or specific market conditions:
Lookback Period:
The user can adjust the lookback period (default: 100) to modify how the moving average and regression are calculated.
Risk-Free Rate:
Adjusting the risk-free rate allows for more realistic modeling of the opportunity cost of holding the asset.
Multiplier:
The multiplier (default: 5.688) amplifies the sensitivity of the PLRR, allowing users to adjust how aggressively the indicator responds to price movements.
This indicator was inspired by the works of Ashwin & PlanG and their work around powerLaw. Thank you. I hall be working on the calculation of this indicator moving forward to make improvements and optomisations.
KLNI RSI MTFDescription of the RSI Multi-Timeframe Indicator
The RSI Multi-Timeframe Indicator allows you to track and compare the Relative Strength Index (RSI) across three different timeframes on the same chart. This is particularly useful for traders who want to gauge the momentum of an asset over multiple time periods simultaneously, helping to make more informed trading decisions.
Key Features
Multi-Timeframe RSI:
You can select up to three timeframes to plot RSI on the same chart.
Available timeframe options include:
Current: Displays RSI for the current chart timeframe.
60 minutes (1 hour)
Daily
Weekly
Monthly
Custom RSI Settings:
Adjust the RSI length and source (e.g., close price) through user inputs, allowing you to tailor the indicator to your strategy.
Divergence Detection (Optional):
The indicator can optionally detect and display bullish and bearish divergences between price and RSI for the first selected timeframe.
Bullish divergence is shown when price makes a lower low, but RSI makes a higher low.
Bearish divergence is shown when price makes a higher high, but RSI makes a lower high.
Visual Aids:
Overbought and oversold RSI levels are highlighted with background colors for clarity.
Horizontal lines at 70 (overbought), 50 (neutral), and 30 (oversold) help quickly identify RSI conditions.
How to Use This Indicator
Inputs & Settings
Timeframe Settings:
First Timeframe: Choose the primary timeframe (e.g., 60 minutes, Daily, Weekly).
Second Timeframe: Select the second timeframe to plot on the chart.
Third Timeframe: Select the third timeframe for additional RSI analysis.
RSI Settings:
RSI Length: Set the period for RSI calculation (default: 14).
Source: Select the price data for RSI calculation (default: close price).
Show Divergence: Enable or disable the detection of divergence between price and RSI.
Plotting on Chart
The indicator will display three distinct RSI plots for the selected timeframes:
RSI TF1 (blue line) for the first timeframe.
RSI TF2 (green line) for the second timeframe.
RSI TF3 (red line) for the third timeframe.
Each RSI line corresponds to its chosen timeframe, allowing you to see how RSI behaves across different time periods.
Reading the RSI Values
Overbought: When RSI is above 70, the asset is considered overbought, potentially signaling a sell or short entry.
Oversold: When RSI is below 30, the asset is considered oversold, possibly indicating a buying opportunity.
Neutral: RSI around 50 is neutral and may suggest a lack of clear momentum.
Divergence Detection
If enabled, the indicator will highlight points of divergence:
Bullish Divergence: A green label will appear below the chart where price is making lower lows, but RSI is making higher lows, suggesting potential bullish momentum.
Bearish Divergence: A red label will appear when price is making higher highs, but RSI is making lower highs, indicating potential bearish pressure.
Practical Applications
Momentum Confirmation: Use this indicator to confirm the strength of a trend by comparing RSI across multiple timeframes. For example, if RSI is above 50 on all three timeframes, it may confirm strong upward momentum.
Overbought/Oversold Signals: When RSI is overbought on multiple timeframes, it could signal an impending reversal or correction. Conversely, oversold conditions across timeframes might indicate a buy opportunity.
Divergence Detection: Spot divergence between price and RSI to identify potential trend reversals early. Divergence can provide early signals of changing market momentum.
Summary
This indicator is a powerful tool for multi-timeframe RSI analysis, helping traders understand momentum shifts across different timeframes. It offers customizability, divergence detection, and visual aids to streamline your technical analysis and decision-making process.
Price Action Volumetric Breaker Blocks [UAlgo]The Price Action Volumetric Breaker Blocks indicator is designed to identify and visualize significant price levels in the market. It combines concepts of price action, volume analysis, and market structure to provide traders with a comprehensive view of potential support and resistance areas. This indicator identifies "breaker blocks," which are price zones where the market has shown significant interest in the past.
These blocks are created based on swing highs and lows, and are further analyzed using volume data to determine their strength. The indicator also tracks market structure shifts, providing additional context to price movements.
By visualizing these key levels and market structure changes, traders can gain insights into potential areas of price reversal or continuation, helping them make more informed trading decisions.
🔶 Key Features
Dynamic Breaker Block Identification: The indicator automatically detects and draws breaker blocks based on swing highs and lows. These blocks represent areas of potential support and resistance.
Volume-Weighted Strength Analysis: Each breaker block is analyzed using volume data to determine its bullish and bearish strength. This is visually represented by the proportion of green (bullish) and red (bearish) coloring within each block.
Market Structure Break (MSB) and Break of Structure (BOS): The indicator identifies and labels Market Structure Breaks (MSB) and Break of Structure (BOS) events, providing context to larger market trends.
Customizable Settings:
- Adjustable swing length for identifying pivot points
- Option to show a specific number of recent breaker blocks
- Choice between wick or close price for violation checks
- Toggle to hide overlapping blocks for cleaner analysis
Violation Detection: Automatically detects when a breaker block has been violated (broken through), either by wick or close price, depending on user settings.
Overlap Control: Provides an option to hide overlapping order blocks, ensuring that the chart remains clean and easy to read when multiple blocks are detected in close proximity.
🔶 Interpreting Indicator
Breaker Blocks:
Breaker blocks are key areas where the price moves through and invalidates a previously identified order block. The indicator detects a breaker block when the price violates an order block by exceeding its high or low (depending on whether it's a bullish or bearish block). This violation is determined by either the wick or the close of a candle, depending on the user's selection in the "Violation Check" setting. When a breaker block is detected, the indicator removes the violated order block from the chart, signaling that the zone is no longer relevant for future price action.
Bullish Breaker Block: This occurs when a bearish order block (red) is violated by the price closing above the block’s top boundary or when the wick surpasses this level. It signals that a prior bearish structure has been invalidated, and the market may shift to a bullish trend.
Bearish Breaker Block: This occurs when a bullish order block (teal) is violated by the price closing below the block’s bottom boundary or when the wick drops below it. It suggests that a previous bullish structure has been broken, indicating potential bearish momentum.
Market Structure Labels:
"MSB" (Market Structure Break) labels indicate a potential change in trend direction.
"BOS" (Break of Structure) labels confirm the continuation of the current trend after breaking a significant level.
Block Strength:
A block with more green indicates stronger bullish interest.
A block with more red indicates stronger bearish interest.
The relative sizes of the green and red portions show the balance of power between buyers and sellers at that level.
🔶 Disclaimer
Use with Caution: This indicator is provided for educational and informational purposes only and should not be considered as financial advice. Users should exercise caution and perform their own analysis before making trading decisions based on the indicator's signals.
Not Financial Advice: The information provided by this indicator does not constitute financial advice, and the creator (UAlgo) shall not be held responsible for any trading losses incurred as a result of using this indicator.
Backtesting Recommended: Traders are encouraged to backtest the indicator thoroughly on historical data before using it in live trading to assess its performance and suitability for their trading strategies.
Risk Management: Trading involves inherent risks, and users should implement proper risk management strategies, including but not limited to stop-loss orders and position sizing, to mitigate potential losses.
No Guarantees: The accuracy and reliability of the indicator's signals cannot be guaranteed, as they are based on historical price data and past performance may not be indicative of future results.
S&R Precision Cloud by Dr. Abiram Sivprasad -4 directional biasDescription of the Script
**Script Name:** S&R Precision Cloud by Dr. Abhiram Sivprasad
**Overview:**
This script is designed to identify key support and resistance levels using the Central Pivot Range (CPR) methodology along with daily, weekly, and monthly pivots. It incorporates the Lagging Span from the Ichimoku Cloud to enhance decision-making in trading strategies for intraday, swing, and long-term positions mainly for directional bias.
---
### Key Components:
1. **Central Pivot Range (CPR):**
- **Central Pivot (CP):** Calculated as the average of the high, low, and close prices. This serves as a reference point for price action.
- **Below Central Pivot (BC) and Top Central Pivot (TC):** Derived to create a range that aids in identifying support and resistance levels.
2. **Support and Resistance Levels:**
- The script computes three support (S1, S2, S3) and resistance (R1, R2, R3) levels based on the Central Pivot.
- These levels are plotted for daily, weekly, and monthly time frames, providing traders with multiple reference points.
3. **Lagging Span:**
- The Lagging Span is plotted as the closing price shifted backward by 26 periods (as per Ichimoku settings).
- This serves as a filter for trade entries, where positions should only be taken in the direction opposite to where the price is relative to this line.
4. **User Inputs:**
- The script allows customization through checkboxes to plot daily, weekly, and monthly support and resistance levels as needed.
- Users can choose whether to display CPR and various support/resistance levels for better visual clarity.
5. **Color Coding:**
- The support and resistance lines are color-coded to distinguish between different levels (green for support, red for resistance, and blue for pivots).
---
### Trading Strategies:
- **Intraday Trading:**
- Utilize price movements around the Lagging Span and support/resistance levels for quick trades.
- **Swing Trading:**
- Identify potential reversal points at S2 and R2 levels, confirmed by divergences in price movement.
- **Long-Term Trading:**
- Monitor price behavior against the Lagging Span and significant pivot levels to capture longer trends.
---
### Summary:
This script equips traders with essential tools for technical analysis by clearly defining critical price levels and incorporating the Lagging Span for directional bias. It is suitable for various trading styles, including intraday, swing, and long-term strategies, making it a versatile addition to any trader’s toolkit.
Custom Time Range HighlighterCustom Time Range Highlighter
This versatile indicator allows traders to highlight specific time ranges on their charts, accommodating users worldwide by supporting customizable UTC offsets. Traders can define two distinct time ranges, setting start and end hours in their local time zone.
A toggle option enables the display of highlights for today only , ensuring focus on current trading conditions.
Ideal for day traders and those following specific market sessions, this tool enhances visibility of active trading periods and aids in effective trade management.
Liquidity Zones [BigBeluga]This indicator is designed to detect liquidity zones on the chart by identifying significant pivot highs and lows filtered by volume strength. It plots these zones as boxes, highlighting areas where liquidity is likely to accumulate. The indicator also draws lines extending from these boxes, marking the levels where price may "grab" this liquidity. The size of these boxes can be dynamic, adjusting based on the volume size, offering a visual representation of market areas where traders might expect significant price reactions.
🔵 IDEA
The idea behind the Liquidity Zones indicator is to help traders identify key market levels where liquidity accumulates. Liquidity zones are areas where there are enough buy or sell orders that can potentially lead to significant price movements. By focusing on pivot points filtered by volume strength, the indicator aims to provide a clearer picture of where large players may have positioned their orders. This insight allows traders to anticipate potential market reactions, such as reversals or breakouts, when the price reaches these zones. The option for dynamic box height further refines the visualization, showing the extent of liquidity based on the volume's intensity.
🔵 KEY FEATURES & USAGE
◉ Volume-Filtered Pivot Highs and Lows:
The indicator scans for pivot highs and lows on the chart, filtering these points based on the volume strength setting (Low, Mid, High). This ensures that only the most significant liquidity zones, backed by notable trading volume, are highlighted. Traders can adjust the filter to focus on different levels of market activity, from small fluctuations to major volume spikes.
Low:
Mid:
High:
◉ Dynamic and Static Liquidity Zones:
Liquidity zones are plotted as boxes around pivot points, with an optional dynamic mode that adjusts the box height based on the normalized volume. This dynamic adjustment reflects the liquidity carried by the volume, making it easier to gauge the significance of each zone. In static mode, the boxes have a fixed height, providing a consistent visual reference for the zones.
◉ Color Intensity Based on Volume:
The indicator adjusts the color intensity of the liquidity zones based on the volume strength. Higher volume zones will be displayed with more intense colors, giving a visual cue to the strength of the liquidity present in that area. This makes it easier to differentiate between zones of varying importance at a glance, allowing traders to quickly identify where the market has the highest concentration of liquidity.
◉ Liquidity Grab Detection and Red Circles:
When the price interacts with a liquidity zone, the indicator detects whether liquidity has been "grabbed" at these levels. If the price moves into a zone and crosses a level, the box label changes to "Liquidity Grabbed," and the line marking the level becomes dashed.
Reversal Points:
The beginning of a trend:
Additionally marks these "liquidity grabs" with red circles, indicating both recent and past liquidity grabs. This feature helps traders identify areas where liquidity has been absorbed by the market, which may signal potential reversals or shifts in market direction.
◉ Dashboard Display:
A dashboard in the upper right corner of the chart provides an overview of the indicator's settings and status. It shows the number of plotted zones, as set in the input settings, and whether the dynamic mode is active. This quick reference helps traders stay informed about the indicator's configuration without needing to open the settings panel.
🔵 CUSTOMIZATION
Length & Zones Amount: Set the length for pivot detection and the maximum number of zones to be displayed on the chart. This allows you to control how many liquidity zones you want to monitor at any given time.
Volume Strength Filter: Adjust the filter to Low, Mid, or High to control the strength of volume required for a pivot to be considered a significant liquidity zone. Higher settings focus on zones with greater volume, indicating stronger liquidity.
Dynamic Distance Mode: Enable or disable the dynamic mode, which adjusts the box height based on the volume size. When dynamic mode is off, the boxes have a fixed height based on the ATR, offering a consistent visualization regardless of the volume size.
The Liquidity Zones indicator is a versatile tool for identifying areas of significant market activity, offering a clear view of where liquidity is likely to reside. By filtering these zones through volume strength and providing dynamic or static visualization options, it equips traders with insights into potential market reaction points, enhancing their ability to anticipate and respond to market movements. The varying color intensity based on volume further aids in quickly recognizing the most critical liquidity zones on the chart.
Optimized Comprehensive Analysis Table# Enhanced Comprehensive Analysis Table
This advanced indicator provides a holistic view of market sentiment by analyzing multiple technical indicators simultaneously. It's designed to give traders a quick, at-a-glance summary of market conditions across various timeframes and analysis methods.
## Key Features:
- Analyzes 9 popular technical indicators
- Weighted voting system for overall market sentiment
- Customizable indicator weights
- Clear, color-coded table display
## Indicators Analyzed:
1. MACD (Moving Average Convergence Divergence)
2. RSI (Relative Strength Index)
3. Moving Averages (50, 100, 200-period)
4. Stochastic Oscillator
5. Parabolic SAR
6. MFI (Money Flow Index)
7. CCI (Commodity Channel Index)
8. OBV (On Balance Volume)
9. ADX (Average Directional Index)
## How It Works:
Each indicator's signal is calculated and classified as bullish, bearish, or neutral. These signals are then weighted according to user-defined inputs. The weighted votes are summed to determine an overall market sentiment.
## Interpretation:
- The table displays the state of each indicator and the overall market sentiment.
- Green indicates bullish conditions, red bearish, and yellow neutral.
- The "Overall State" row at the bottom provides a quick summary of the combined analysis.
## Customization:
Users can adjust the weight of each indicator to fine-tune the analysis according to their trading strategy or market conditions.
This indicator is ideal for traders who want a comprehensive overview of market conditions without having to monitor multiple indicators separately. It's particularly useful for confirming trade setups, identifying potential trend reversals, and managing risk.
Note: This indicator is meant to be used as part of a broader trading strategy. Always combine with other forms of analysis and proper risk management.
Price Movement > Custom Points with Day of WeekThe code is a TradingView Pine Script indicator designed to track and visualize price movements in a financial market (like stocks or cryptocurrencies) based on a specific point threshold. Here’s a breakdown of its functionality:
Purpose of the Code:
Price Movement Calculation: It calculates the difference between the closing price and the opening price of each bar (or candle) to determine if the price has moved significantly.
Threshold Input: The user can set a threshold (e.g., 500 points) to determine what constitutes a significant movement.
Movement Conditions:
Positive Movement: If the price movement is greater than the threshold, it’s marked as a positive movement.
Negative Movement: If the price movement is less than the negative threshold (i.e., below -500 points), it’s marked as a negative movement.
Day of the Week Identification: The script identifies the day of the week for each bar (Monday through Sunday).
Visual Output:
It plots shapes (like labels) on the chart:
For positive movements, it shows "YES" in green, indicating the movement exceeded the threshold for that day.
For negative movements, it shows "YES" in red, indicating the movement fell below the negative threshold for that day.
Use Cases:
Traders: It helps traders quickly identify days where significant price movements occurred, allowing them to analyze trends and make informed trading decisions.
Market Analysis: The indicator can be used for backtesting strategies based on significant price movements.
Overall, this code serves as a visual tool for analyzing price volatility in a market based on user-defined thresholds and day-based observations. If you have any specific questions or need further clarification about any part of it, feel free to ask!
Demand and Supply Conditions with SignalsIntroduction:
This document outlines a trading strategy that utilizes price action analysis and color signals to make informed trading decisions. The strategy focuses on identifying demand and supply conditions, curve patterns, and generating signals based on historical price data. The colors associated with each condition and signal serve as visual indicators to assist in decision-making.
I. Strategy Overview:
Objective:
The objective of this trading strategy is to identify potential trading opportunities based on price action analysis and color signals.
Key Components:
Demand Condition: A green upward-facing triangle indicates a potential demand condition.
Supply Condition: A red downward-facing triangle indicates a potential supply condition.
Curve Pattern Condition: A blue upward-facing triangle indicates a potential curve pattern condition.
Signal Condition: A yellow upward-facing triangle indicates a potential buy signal.
II. Understanding the Colors:
* Green: Represents the demand condition, which suggests potential buying pressure in the market. A green upward-facing triangle is plotted on the chart when the demand condition is met at a specific candle or bar.
* Red: Represents the supply condition, which suggests potential selling pressure in the market. A red downward-facing triangle is plotted on the chart when the supply condition is met at a specific candle or bar.
* Blue: Represents the curve pattern condition, which suggests the presence of a specific pattern based on price action analysis. A blue upward-facing triangle is plotted on the chart when the curve pattern condition is met at a specific candle or bar.
* Yellow: Represents the signal condition, which is a combination of the demand condition and the curve pattern condition. A yellow upward-facing triangle is plotted on the chart when the signal condition is met at a specific candle or bar, indicating a potential buy signal.
III. Decision-Making Process:
* Demand and Supply Conditions: Identify potential buying opportunities when a green demand condition is present. Consider potential selling opportunities when a red supply condition is present. Use these conditions to assess the overall market sentiment and potential price reversals.
* Curve Patterns: Analyze the presence of blue curve pattern conditions to identify specific price patterns. These patterns can provide additional confirmation for potential trading decisions.
* Signal Condition: Pay attention to the yellow signal condition, which indicates a potential buy signal. Evaluate the overall market context and consider entering a buy position when the signal condition is met.
* Risk Management: Implement proper risk management techniques such as setting stop-loss orders and position sizing to protect against potential losses.
IV. Conclusion:
This trading strategy leverages price action analysis and color signals to identify potential trading opportunities. The colors associated with each condition and signal serve as visual aids to highlight specific points on the chart. It's important to thoroughly backtest and validate the strategy before applying it to real-world trading scenarios. Additionally, always consider market conditions, risk management, and individual trading preferences when making trading decisions.
Disclaimer: Trading involves risks, and this document does not guarantee profitable outcomes. Traders should exercise caution and perform their own due diligence before engaging in any trading activity.
Remember to continually review and adapt your trading strategy based on market conditions and personal experiences to enhance its effectiveness.
E9 ASIA Session
*note: Upon updating the script the conversion from V4 to v5 has lost the weekend extended lines and now prints an asia session for each day. It is recommended (esp for crypto) to extend these lines across the weekend like in the chart example above.
The E9 Asia Session Indicator is a valuable tool for traders aiming to track and analyze the Asia trading session on financial charts. This indicator provides insights into price behavior during the Asia session, which is crucial for making informed trading decisions. Here's an overview of its key functionalities and uses:
1. Session Highs and Lows
Purpose:
The indicator calculates and plots the high and low of the Asia session.
It helps identify key levels of support and resistance established during this trading period.
Importance:
These levels can act as significant reference points for future price movements.
Price action that occurs near these levels often provides clues about potential breakouts or reversals.
2. Session Background Color
Purpose:
The indicator can shade the background of the chart during the Asia session.
Importance:
This visual cue helps quickly identify the session's timeframe, enhancing the trader’s ability to observe price behavior within this specific period.
It aids in distinguishing between different trading sessions and understanding their influence on price action.
3. Start of Session Marker
Purpose:
A visual marker (such as a circle) is plotted at the beginning of each Asia session.
Importance:
This marker helps traders visually pinpoint the start of the session, making it easier to analyze how the price reacts from the session's opening.
4. End of Session Marker
Purpose:
A marker is plotted at the end of the Asia session, indicating where the session closes.
Importance:
This marker is useful for tracking the end of the session and observing price behavior around this critical juncture.
It helps in analyzing whether the session's high or low gets revisited or broken in subsequent sessions.
Practical Uses:
Strategic Planning: Traders can use the plotted high and low levels to set their trading strategies, stop-loss orders, and profit targets.
Market Analysis: Understanding how price interacts with the Asia session’s high and low levels can provide insights into market sentiment and potential price movements.
By incorporating the E9 Asia Session Indicator into your trading toolkit, you can gain a deeper understanding of the Asia session's impact on price dynamics, enhancing your overall trading strategy and decision-making process.
Disclaimer: The information contained in this article does not constitute financial advice or a solicitation to buy or sell any securities. All investments involve risk, and past performance does not guarantee future results. Always evaluate your financial circumstances and investment objectives before making trading decisions.
Gaussian SWMA For LoopGaussian SWMA For Loop Indicator
The "Gaussian SWMA For Loop" is a sophisticated indicator designed to identify potential trading opportunities by combining a Gaussian-weighted moving average (WMA) with a simple moving average (SMA), enhanced by a loop-based scoring system. This indicator is tailored for traders looking to capture trends and reversals with a refined approach, making use of advanced filtering techniques and custom thresholds for signal generation.
Key Features:
1. Gaussian Weighted Moving Average (WMA):
The indicator starts by applying a Gaussian filter to the input price data (default is the closing price). The Gaussian filter smooths the data by applying weights according to a Gaussian distribution, determined by the Gaussian Sigma parameter. This results in a smooth, noise-reduced WMA, which is more responsive to significant price movements while ignoring minor fluctuations.
2. Simple Moving Average (SMA) on Smoothed Data:
After the data is smoothed using the Gaussian filter, an SMA is calculated over this smoothed data. The length of this SMA can be adjusted via the SMA Length input, allowing users to control the level of additional smoothing applied to the already filtered data.
3. Loop-Based Scoring System:
Range Analysis: The core feature of this indicator is the loop-based scoring system. It evaluates the filtered SMA by comparing its current value to previous values over a specified range, defined by the From and To parameters.
Score Calculation: The loop iterates through each value within the defined range and adjusts a score based on whether the current filtered SMA is higher or lower than its historical values. This score is a measure of the trend's strength and direction.
Thresholds for Signal Generation: Users can define custom thresholds for long (Long Threshold) and short (Short Threshold) signals. The score is compared against these thresholds to generate buy and sell signals.
4. Signal Generation:
Buy Signal (L): Triggered when the score exceeds the user-defined Long Threshold.
Sell Signal (S): Triggered when the score falls below the Short Threshold.
5. Visual Enhancements:
The indicator plots the filtered SMA on the chart, with the line and bar colors changing based on the buy and sell signals:
Teal (color.rgb(0, 255, 187)) for a buy signal.
Magenta (color.rgb(255, 0, 157)) for a sell signal.
Gray for a neutral condition.
Additionally, the fill between the current and previous SMA values is colored based on the signal, providing a clear visual cue for trend direction and strength.
6. Alert Conditions:
The indicator includes customizable alerts that notify the user when a buy or sell signal is generated:
Long Alert: Notifies when a buy signal is triggered.
Short Alert: Notifies when a sell signal is triggered.
Configurable Inputs:
Main Group:
WMA Length (length): Sets the length of the Gaussian-weighted moving average.
SMA Length (len): Specifies the period for the SMA applied to the Gaussian-smoothed data.
Source (src): The price data used for calculations (default is the closing price).
Gaussian Sigma (sigma): Determines the standard deviation of the Gaussian distribution, influencing the smoothing effect.
For Loop Group:
From (a): The starting point for the loop-based score analysis.
To (b): The endpoint for the loop-based score analysis.
Threshold Group:
Long Threshold (threshold_L): Defines the score threshold above which a buy signal is triggered.
Short Threshold (threshold_S): Defines the score threshold below which a sell signal is triggered.
Practical Use:
This indicator is ideal for traders who want to identify trends and potential reversals with precision. The combination of Gaussian smoothing, SMA, and the loop-based scoring system offers a robust method to filter out noise and focus on significant market moves. The customizable thresholds and alert system further enhance its utility, making it a powerful tool for both manual and automated trading strategies.
Note: As with any trading indicator, it's recommended to backtest the "Gaussian SWMA For Loop" under various market conditions and use it in conjunction with other analysis techniques to confirm signals before making trading decisions.
Birdies [LuxAlgo]The Birdies indicator uses a unique technique to provide support/resistance curves based on a circle connecting the last swing high/low.
A specific, customizable part of this circle acts as a curve of interest, which can trigger visual breakout signals.
🔶 USAGE
The script projects a bird-like pattern when a valid Swing point is found. Multiple customization options are included.
🔹 Trend & Support/Resistance Tool
The color fill patterns and the wing boundaries can give insights into the current trend direction as well as serve as potential support/resistance areas.
In the example above, "Birdies" coincide with pullback and support/resistance zones.
🔹 Swing Length & Buffer
Besides the "Swing Length", with higher values returning longer-term Swing Levels, the script's behavior can be fine-tuned with filters ("Settings" - "Validation").
🔹 Validation
To minimize clutter, three filters are included:
Minimum X-Distance: The minimum amount of bars between subsequent Swings
Minimum Y-Distance: The minimum amount of bars between subsequent Swings
Buffer (Multiple of ATR)
The "Minimum X/Y-Distance" creates a zone where a new Swing is considered invalid. Only when the Swing is out of the zone, can it be considered valid.
In other words, in the example above, a Swing High can only be valid when enough bars/time have passed, and the difference between the last Swing and the previous is more than the ATR multiplied by the "Minimum Y-Distance" factor.
The "Buffer" creates a line above/below the "Birdy", derived from the measured ATR at the conception of the "Birdy" multiplied with a factor ("Buffer").
When the closing price crosses the "Birdy", it must also surpass this buffer line to produce a valid signal, lowering the risk of clutter as a result.
🔶 DETAILS
Birdies are derived from a circle that connects two Swing points. The left-wing curve originates from the most recent "Swing point" to the last value on the circle before crossing its midline. The mirror image of the left wing creates the right wing.
Enabling "Origine" will draw a line from the last Swing to the first.
🔹 Style
The publication includes a style setting with four options.
The first, "Birdy," shows a bird-like shape derived from a circle connecting the last Swing High and Swing Low.
The second option holds everything from the first option but connects both wingtips, providing potential horizontal levels of interest.
When setting "Birdy" to "None", the visual breakout signals will not defer from previous settings, but the focus is shifted towards the fill color, which can help detect potential trend shift.
A fourth setting, "Left Wing", will only show the left part of the "Birdy" pattern, removing the right part from the equation. This will change the visual breakout signals, providing alternative signals.
🔶 SETTINGS
Swing Length: The period used for swing detection, with higher values returning longer-term Swing Levels.
🔹 Validation
Minimum X-Distance: The minimum amount of bars between subsequent Swings
Minimum Y-Distance: The minimum amount of bars between subsequent Swings
Buffer (Multiple of ATR)
🔹 Style
Bullish Patterns: Enable / color
Bearish Patterns: Enable / color
Buffer Zone: Show / Color
Color Fill: Show color fill between two Birdies (if available)
Origine: Show the line between both Swing Points
🔹 Calculation
Calculated Bars: Allows the usage of fewer bars for performance/speed improvement
Absolute ZigZagThis ZigZag Indicator is a bit unique in it's kind.
It uses my own Absolute ZigZag Lib to calculate the pivots:
Instead of using percentages or looking more than 1 bar left or right, this Zigzag library calculates pivots by just looking at the current bar highs and lows and the ones of one bar earlier. This is a very fast and accurate way of calculating pivots.
The library also features a solution for bars that have both a higher high and a higher low like seen below.
You can also use your own colors for the labels and the lines:
You can also quickly select a one-colored theme without changing all colors at once:
