Volatility-Adjusted DEMA Supertrend [QuantAlgo]Introducing the Volatility-Adjusted DEMA Supertrend by QuantAlgo 📈💫
Take your trading and investing strategies to the next level with the Volatility-Adjusted DEMA Supertrend , a dynamic tool designed to adapt to market volatility and provide clear, actionable trend signals. This innovative indicator is ideal for both traders and investors looking for a more responsive approach to market trends, helping you capture potential shifts with greater precision.
🌟 Key Features:
🛠 Customizable Trend Settings: Adjust the period for trend calculation and fine-tune the sensitivity to price movements. This flexibility allows you to tailor the Supertrend to your unique trading or investing strategy, whether you're focusing on shorter or longer timeframes.
📊 Volatility-Responsive Multiplier: The Supertrend dynamically adjusts its sensitivity based on real-time market volatility. This could help filter out noise in calmer markets and provide more accurate signals during periods of heightened volatility.
✨ Trend-Based Color-Coding: Visualize bullish and bearish trends with ease. The indicator paints candles and plots trend lines with distinct colors based on the current market direction, offering quick, clear insights into potential opportunities.
🔔 Custom Alerts: Set up alerts for key trend shifts to ensure you're notified of significant market changes. These alerts would allow you to act swiftly, potentially capturing opportunities without needing to constantly monitor the charts.
📈 How to Use:
✅ Add the Indicator: Add the Volatility-Adjusted DEMA Supertrend to your chart. Customize the trend period, volatility settings, and price source to match your trading or investing style. This ensures the indicator aligns with your market strategy.
👀 Monitor Trend Shifts: Watch the color-coded trend lines and candles as they dynamically shift based on real-time market conditions. These visual cues help you spot potential trend reversals and confirm your entries and exits with greater confidence.
🔔 Set Alerts: Configure alerts for key trend shifts, allowing you to stay informed of potential market reversals or continuation patterns, even when you're not actively watching the market.
⚙️ How It Works:
The Volatility-Adjusted DEMA Supertrend is designed to adapt to changes in market conditions, making it highly responsive to price volatility. The indicator calculates a trend line based on price and volatility, dynamically adjusting it to reflect recent market behavior. When the market experiences higher volatility, the trend line becomes more flexible, potentially allowing for greater sensitivity to rapid price movements. Conversely, during periods of low volatility, the indicator tightens its range, helping to reduce noise and avoid false signals.
The indicator includes a volatility-responsive multiplier, which further enhances its adaptability to market conditions. This means the trend direction would always be based on the latest market data, potentially helping you stay ahead of shifts or continuation trends. The Supertrend's visual color-coding simplifies the process of identifying bullish or bearish trends, while customizable alerts ensure you can stay on top of significant changes in market direction.
This tool is versatile and could be applied across various markets and timeframes, making it a valuable addition for both traders and investors. Whether you’re trading in fast-moving markets or focusing on longer-term investments, the Volatility-Adjusted DEMA Supertrend could help you remain aligned with the current market environment.
Disclaimer:
This indicator is designed to enhance your analysis by providing trend information, but it should not be used as the sole basis for making trading or investing decisions. Always combine it with other forms of analysis and risk management practices. No statements or claims aim to be financial advice, and no signals from us or our indicators should be interpreted as such. Past performance is not indicative of future results.
Educational
Dynamic Volume RSI (DVRSI) [QuantAlgo]Introducing the Dynamic Volume RSI (DVRSI) by QuantAlgo 📈✨
Elevate your trading and investing strategies with the Dynamic Volume RSI (DVRSI) , a powerful tool designed to provide clear insights into market momentum and trend shifts. This indicator is ideal for traders and investors who want to stay ahead of the curve by using volume-responsive calculations and adaptive smoothing techniques to enhance signal clarity and reliability.
🌟 Key Features:
🛠 Customizable RSI Settings: Tailor the indicator to your strategy by adjusting the RSI length and price source. Whether you’re focused on short-term trades or long-term investments, DVRSI adapts to your needs.
🌊 Adaptive Smoothing: Enable adaptive smoothing to filter out market noise and ensure cleaner signals in volatile or choppy market conditions.
🎨 Dynamic Color-Coding: Easily identify bullish and bearish trends with color-coded candles and RSI plots, offering clear visual cues to track market direction.
⚖️ Volume-Responsive Adjustments: The DVRSI reacts to volume changes, giving greater significance to high-volume price moves and improving the accuracy of trend detection.
🔔 Custom Alerts: Stay informed with alerts for key RSI crossovers and trend changes, allowing you to act quickly on emerging opportunities.
📈 How to Use:
✅ Add the Indicator: Set up the DVRSI by adding it to your chart and customizing the RSI length, price source, and smoothing options to fit your specific strategy.
👀 Monitor Visual Cues: Watch for trend shifts through the color-coded plot and candles, signaling changes in momentum as the RSI crosses key levels.
🔔 Set Alerts: Configure alerts for critical RSI crossovers, such as the 50 line, ensuring you stay on top of potential market reversals and opportunities.
🔍 How It Works:
The Dynamic Volume RSI (DVRSI) is a unique indicator designed to provide more accurate and responsive signals by incorporating both price movement and volume sensitivity into the RSI framework. It begins by calculating the traditional RSI values based on a user-defined length and price source, but unlike standard RSI tools, the DVRSI applies volume-weighted adjustments to reflect the strength of market participation.
The indicator dynamically adjusts its sensitivity by factoring in volume to the RSI calculation, which means that price moves backed by higher volumes carry more weight, making the signal more reliable. This method helps identify stronger trends and reduces the risk of false signals in low-volume environments. To further enhance accuracy, the DVRSI offers an adaptive smoothing option that allows users to reduce noise during periods of market volatility. This adaptive smoothing function responds to market conditions, providing a cleaner signal by reducing erratic movements or price spikes that could lead to misleading signals.
Additionally, the DVRSI uses dynamic color-coding to visually represent the strength of bullish or bearish trends. The candles and RSI plots change color based on the RSI values crossing critical thresholds, such as the 50 level, offering an intuitive way to recognize trend shifts. Traders can also configure alerts for specific RSI crossovers (e.g., above 50 or below 40), ensuring that they stay informed of potential trend reversals and significant market shifts in real-time.
The combination of volume sensitivity, adaptive smoothing, and dynamic trend visualization makes the DVRSI a robust and versatile tool for traders and investors looking to fine-tune their market analysis. By incorporating both price and volume data, this indicator delivers more precise signals, helping users make informed decisions with greater confidence.
Disclaimer:
The Dynamic Volume RSI is designed to enhance your market analysis but should not be used as a sole decision-making tool. Always consider multiple factors before making any trading or investment decisions. Past performance is not indicative of future results.
RishiMoney RSIRishiMoney RSI
The "RishiMoney RSI" indicator is designed for traders who want to leverage the power of the Relative Strength Index (RSI) across multiple timeframes.
In addition to regular RSI, this script allows the users to select custom timeframes for two additional RSI calculations, making it easier to identify trends, reversals, and potential entry or exit points.
USAGE
While Returning the same information as a regular RSI the RishiMoney RSI provides two more RSI calculations One for Lagrgest Timeframe and one for middle Timeframe so that the users need not to check for higher timeframes separately Which is very Time consuming. This script solves the problem of time taking process of checking different timeframes RSI calculations.
This script is ideal for traders who want to confirm their analysis across multiple timeframes. By comparing the main RSI with larger and intermediate timeframes, traders can better understand the market's momentum and make more informed decisions.
The RishiMoney RSI crossing above the overbought level can be indicative of a strong uptrend which is highlighted as a green gradient area, while when RishiMoney RSI is crossing under the oversold level can be indicative of a strong downtrend which is highlighted as a red area.
Key Features:
Customizable RSI Period: Set your preferred RSI period for precise calculation and analysis.
Multi-Timeframe RSI:
Largest RSI Timeframe: Choose the largest timeframe for your analysis (Monthly, Weekly, Daily, Hourly, 15 minutes, or 5 minutes).
Middle RSI Timeframe: Select an intermediate timeframe for comparison with the main RSI.
Overbought and Oversold Levels: The indicator includes customizable overbought and oversold levels, which are clearly marked on the chart with dynamic bands.
Alerts: Set up alerts for when the RSI crosses into overbought or oversold territory, so you never miss a potential trading opportunity.
Visual Clarity: The script plots the RSI for your selected timeframes with distinct colors, helping you quickly identify trends across different timeframes.
This script is provided for educational purposes only and should not be considered financial advice. Always conduct your own research and consult with a financial advisor before making any trading decisions.
Volume Analysis - Heatmap and Volume ProfileHello All!
I have a new toy for you! Volume Analysis - Heatmap and Volume Profile . Honestly I started to work to develop Volume Heatmap then I decided to improve it and add more features such Volume profile, volume, difference in Buy/Sell volumes etc. I tried to put my abilities into this script and tried to use some new Pine Language™ features ( method, force_overlay, enum etc features ). I hope the usage of these new features would be an example for Pine Programmers.
Lets talk about how it works:
- It gets number of Rows/Columns from the user for each candle to create heatmap
- It calculates the number of the candles to analyze. Number of the candles may change by number of Rows/columns or if any volume / difference in volumes / volume profile is enabled
- It gets Closing/Opening price, Volume and Time info from lower time frame for each candle ( it can be up to 100K for each candle )
- After getting the data it calculates lower time frame to analyze
- Then it calculates how closing price moves, how much volume on each move and create boxes by the volume/move in each box
- The colors for each box calculated by volume info and closing price movements in the lower time frame
- It shows the boxes on Absolute places or Zero Line optionally
- it shows Volume, Cumulative volume, Difference between Buy/Sell volume for each column
- it changes empty box color by Chart background color, also you can change transparency
- At this time it creates Volume Profile with up to 25 rows
- As a new Pine Language™ feature, it can show Volume Profile in the indicator window or in Main chart, shows Value Area, Value Area High (VAH), Value Area Low (VAL), and draw it and POC (Point Of Control) in the indicator window and/or in the main chart
- Honestly the feature I like is that: For the markets that are not open 24/7, it combines the data from the lower time period without any gaps. For example, if you work for a market that is closed on Saturdays and Sundays, it ensures data integrity by omitting weekends and holidays. so for example if the data is like "ABC---DEF-X---YL-Z" then it makes this data like "ABCDEFXYLZ". In this way, there will be no data breaks in the displayed boxes, there will be no empty colons, and it will appear as if data is coming in at any time.
- Finally it shows Info Panel to give info, its background color automatically changes by the Chart background color
- Important! You should set your "Plan" accordingly, your plan is "Premium or Higher" or "Lower tier". so the script can understand the minimum time frame it can get data!!
I tried to share many screenshots below to explain it much better
How it looks?
it shows Highest Buy/Sell volumes brighter, move volume -> brighter
Volume Profile ( up to 25 row s) ( number of contained candles should be more than 1 )
Volume Profile can be shown in the main chart optionally
How the main chart looks:
Closing price shown and you can enable it, change colors & line width
Can include many candles according to Row&Column number you set
Optionally it can show cumulative volume for each candle
Closing prices from lower time frame
Shows Candle Body by changing background colors
It can shows all included candles on Zero line
You can change the colors of many things
You can set Empty box and border transparency
Table, Empty box Colors adjustment done automatically by chart background color
Sometimes we can not get data from some historical candles if time frame is high such 2days, 1 week etc, and it looks like:
It also checks if Chart time frame and Chart type is suitable
Enjoy!
DP-OCR MTF & MA 2024This script developed is designed for multi-timeframe analysis of previous open, close, and range, with additional signal plots based on various percentage extension levels. It also incorporates EMA calculations for crossover strategies. Here's a quick breakdown of what the script does:
Key Features:
1. Timeframes:
o Two separate timeframes (TF1 and TF2), which can be set by the user (e.g., 15 mins, 30 mins, daily, etc.). The script computes price actions and extensions for both timeframes. For better analysis, use Daily in TF1 and Weekly in TF2
2. Extension Levels:
o Calculates and plots 10%, 21%, 31%, 51%, and 61% extensions (both positive and negative) for each timeframe.
o The most commonly used extension levels are 61%, 31%, -61%, and -21%.
o These extension levels can be turned on or off by the user.
3. Open/Close/Range:
o Tracks the high, low, open, and close for both timeframes.
o Highlights open/close gaps.
o Plots the previous high/low range for both timeframes with a fill and different colors based on price movement.
How to Use:
• You can toggle specific extension levels on or off in the script’s settings.
• For example, when price hits a +61% extension, it could signal a breakout, and when it hits a -61% extension, it may indicate a potential retracement.
• Use these levels in conjunction with your price action analysis to set entry/exit points or stop-loss levels.
4. Today’s Open:
o Plots today’s opening price for both timeframes.
How to Use:
• Use today’s open as a key reference point to determine the day’s price action.
• Compare today’s open with the previous high/low or extension levels to evaluate possible trends or reversals.
5. EMA Calculations:
o The script calculates 5, 15, and 20 period EMAs and plots them on the chart.
o Additional EMA crossover signals can be included for strategy optimization.
How to Use:
• Observe the EMAs for potential crossover signals. For example, a 5-period EMA crossing above a 15-period or 20-period EMA may signal a buy opportunity, while a crossover in the opposite direction may signal a sell.
• Combine the EMA crossovers with extension levels or previous price data to refine your entries and exits.
Customizations Available:
• Users can select whether to display extension levels for either timeframe.
• The script allows automatic adaptation to intraday, daily, weekly, or monthly timeframes based on the current chart settings.
Moreover, the extension levels are calculated based on the previous period’s range, with the most commonly usable extension levels being 61, 31, -61, and -21. These levels are often used for identifying potential price retracements, breakouts, or reversal points in technical analysis.
Historical Fed Interest rate This script is Historical Fed Interest rate
The data is between 1991 - 2023 , but for some reason data between 1991 - 10/2001 is not work
Green line for rate cut and Red line for rate hike and detail at the label
Lot Size Calculator by MenolakRugiThe Lot Size Formula in forex trading is a critical tool that offers several key benefits to traders:
🟢Risk Management: By using the formula, traders can control the amount of capital they risk on each trade. This helps prevent excessive losses by aligning the lot size with a predefined risk tolerance, such as 1% or 2% of the account balance.
🟢Consistent Position Sizing: The formula ensures that position sizes are calculated based on the specific trade setup, including the distance to the stop loss. This consistency helps avoid over-leveraging and reduces the emotional aspect of trading.
🟢Adaptability: The lot size can be adjusted according to different currency pairs and market conditions. This flexibility ensures that traders can apply the formula across various trading instruments and environments.
🟢Improved Profit Potential: By managing risk effectively, traders can protect their capital while maximizing profit opportunities. When losses are controlled, traders are able to stay in the market longer and compound their gains over time.
🟢Precision in Trade Planning: Calculating the lot size allows traders to plan their trades more precisely, aligning their strategies with the amount they are willing to risk. This leads to more disciplined and structured trading, reducing impulsive decisions.
In summary, the lot size formula helps maintain a balanced approach to trading, where both risk and reward are carefully managed to increase the chances of long-term success.
ICT Asian Range and KillzonesThis TradingView indicator highlights key trading sessions and their price ranges on a chart. It identifies the Asian Range and the Killzones for both the London Open and New York Open sessions. Here’s a brief breakdown:
Asian Range:
Defines the high and low price levels during the Asian trading session (between the specified start and end hours, default 00:00 to 04:00 UTC).
Plots horizontal lines to mark the highest and lowest prices reached during the Asian session.
Adds labels showing the values of these high and low points after the session ends.
London and New York Killzones:
Identifies the “Killzones” or key trading windows for the London Open (default 06:00 to 09:00 UTC) and the New York Open (default 11:00 to 14:00 UTC).
Tracks the high and low price levels within these windows and plots rectangles ("boxes") on the chart to visualize these ranges.
The boxes are color-coded and customizable, indicating potential areas of high market activity or volatility.
Customizable Visuals:
Users can adjust the colors, border widths, and other visual properties for better clarity and chart integration.
Adaptive RSI-Stoch with Butterworth Filter [UAlgo]The Adaptive RSI-Stoch with Butterworth Filter is a technical indicator designed to combine the strengths of the Relative Strength Index (RSI), Stochastic Oscillator, and a Butterworth Filter to provide a smooth and adaptive momentum-based trading signal. This custom-built indicator leverages the RSI to measure market momentum, applies Stochastic calculations for overbought/oversold conditions, and incorporates a Butterworth Filter to reduce noise and smooth out price movements for enhanced signal reliability.
By utilizing these combined methods, this indicator aims to help traders identify potential market reversal points, momentum shifts, and overbought/oversold conditions with greater precision, while minimizing false signals in volatile markets.
🔶 Key Features
Adaptive RSI and Stochastic Oscillator: Calculates RSI using a configurable period and applies a dual-smoothing mechanism with Stochastic Oscillator values (K and D lines).
Helps in identifying momentum strength and potential trend reversals.
Butterworth Filter: An advanced signal processing filter that reduces noise and smooths out the indicator values for better trend identification.
The filter can be enabled or disabled based on user preferences.
Customizable Parameters: Flexibility to adjust the length of RSI, the smoothing factors for Stochastic (K and D values), and the Butterworth Filter period.
🔶 Interpreting the Indicator
RSI & Stochastic Calculations:
The RSI is calculated based on the closing price over the user-defined period, and further smoothed to generate Stochastic Oscillator values.
The K and D values of the Stochastic Oscillator provide insights into short-term overbought or oversold conditions.
Butterworth Filter Application:
What is Butterworth Filter and How It Works?
The Butterworth Filter is a type of signal processing filter that is designed to have a maximally flat frequency response in the passband, meaning it doesn’t distort the frequency components of the signal within the desired range. It is widely used in digital signal processing and technical analysis to smooth noisy data while preserving the important trends in the underlying data. In this indicator, the Butterworth Filter is applied to the trigger value, making the resulting signal smoother and more stable by filtering out short-term fluctuations or noise in price data.
Key Concepts Behind the Butterworth Filter:
Filter Design: The Butterworth filter works by calculating weighted averages of current and past inputs (price or indicator values) and outputs to produce a smooth output. It is characterized by the absence of ripple in the passband and a smooth roll-off after the cutoff frequency.
Cutoff Frequency: The period specified in the indicator acts as a control for the cutoff frequency. A higher period means the filter will remove more high-frequency noise and retain longer-term trends, while a lower period means it will respond more to short-term fluctuations in the data.
Smoothing Process: In this script, the Butterworth Filter is calculated recursively using the following formula,
butterworth_filter(series float input, int period) =>
float wc = math.tan(math.pi / period)
float k1 = 1.414 * wc
float k2 = wc * wc
float a0 = k2 / (1 + k1 + k2)
float a1 = 2 * a0
float a2 = a0
float b1 = 2 * (k2 - 1) / (1 + k1 + k2)
float b2 = (1 - k1 + k2) / (1 + k1 + k2)
wc: This is the angular frequency, derived from the period input.
k1 and k2: These are intermediate coefficients used in the filter calculation.
a0, a1, a2: These are the feedforward coefficients, which determine how much of the current and past input values will contribute to the filtered output.
b1, b2: These are feedback coefficients, which determine how much of the past output values will contribute to the current output, effectively allowing the filter to "remember" past behavior and smooth the signal.
Recursive Calculation: The filter operates by taking into account not only the current input value but also the previous two input values and the previous two output values. This recursive nature helps it smooth the signal by blending the recent past data with the current data.
float filtered_value = a0 * input + a1 * prev_input1 + a2 * prev_input2
filtered_value -= b1 * prev_output1 + b2 * prev_output2
input: The current input value, which could be the trigger value in this case.
prev_input1, prev_input2: The previous two input values.
prev_output1, prev_output2: The previous two output values.
This means the current filtered value is determined by the combination of:
A weighted sum of the current input and the last two inputs.
A correction based on the last two output values to ensure smoothness and remove noise.
In conclusion when filter is enabled, the Butterworth Filter smooths the RSI and Stochastic values to reduce market noise and highlight significant momentum shifts.
The filtered trigger value (post-Butterworth) provides a cleaner representation of the market's momentum.
Cross Signals for Trade Entries:
Buy Signal: A bullish crossover of the K value above the D value, particularly when the values are below 40 and when the Stochastic trigger is below 1 and the filtered trigger is below 35.
Sell Signal: A bearish crossunder of the K value below the D value, particularly when the values are above 60 and when the Stochastic trigger is above 99 and the filtered trigger is above 90.
These signals are plotted visually on the chart for easy identification of potential trading opportunities.
Overbought and Oversold Zones:
The indicator highlights the overbought zone when the filtered trigger surpasses a specific threshold (typically above 100) and the oversold zone when it drops below 0.
The color-coded fill areas between the Stochastic and trigger lines help visualize when the market may be overbought (likely a reversal down) or oversold (potential reversal up).
🔶 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.
Sinc MAKaiser Windowed Sinc Moving Average Indicator
The Kaiser Windowed Sinc Moving Average is an advanced technical indicator that combines the sinc function with the Kaiser window to create a highly customizable finite impulse response (FIR) filter for financial time series analysis.
Sinc Function: The Ideal Low-Pass Filter
At the core of this indicator is the sinc function, which represents the impulse response of an ideal low-pass filter. In signal processing and technical analysis, the sinc function is crucial because it allows for the creation of filters with precise frequency cutoff characteristics. When applied to financial data, this means the ability to separate long-term trends from short-term fluctuations with remarkable accuracy.
The primary advantage of using a sinc-based filter is the independent control over two critical parameters: the cutoff frequency and the number of samples used. The cutoff frequency, analogous to the "length" in traditional moving averages, determines which price movements are considered significant (low frequency) and which are treated as noise (high frequency). By adjusting the cutoff, analysts can fine-tune the filter to respond to specific market cycles or timeframes of interest.
The number of samples used in the filter doesn't affect the cutoff frequency but instead influences the filter's accuracy and steepness. Increasing the sample size results in a better approximation of the ideal low-pass filter, leading to sharper transitions between passed and attenuated frequencies. This allows for more precise trend identification and noise reduction without changing the fundamental frequency response characteristics.
Kaiser Window: Optimizing the Sinc Filter
While the sinc function provides excellent frequency domain characteristics, it has infinite length in the time domain, which is impractical for real-world applications. This is where the Kaiser window comes into play. By applying the Kaiser window to the sinc function, we create a finite-length filter that approximates the ideal response while minimizing unwanted oscillations (known as the Gibbs phenomenon) in the frequency domain.
The Kaiser window introduces an additional parameter, alpha, which controls the trade-off between the main-lobe width and side-lobe levels in the frequency response. This parameter allows users to fine-tune the filter's behavior, balancing between sharp cutoffs and minimal ripple effects.
Customizable Parameters
The Kaiser Windowed Sinc Moving Average offers several key parameters for customization:
Cutoff: Controls the filter's cutoff frequency, determining the divide between trends and noise.
Length: Sets the number of samples used in the FIR filter calculation, affecting the filter's accuracy and computational complexity.
Alpha: Influences the shape of the Kaiser window, allowing for fine-tuning of the filter's frequency response characteristics.
Centered and Non-Centered Modes
The indicator provides two operational modes:
Non-Centered (Real-time) Mode: Uses half of the windowed sinc function, suitable for real-time analysis and current market conditions.
Centered Mode: Utilizes the full windowed sinc function, resulting in a zero-phase filter. This mode introduces a delay but offers the most accurate trend identification for historical analysis.
Visualization Features
To enhance the analytical value of the indicator, several visualization options are included:
Gradient Coloring: Offers a range of color schemes to represent trend direction and strength.
Glow Effect: An optional visual enhancement for improved line visibility.
Background Fill: Highlights the area between the moving average and price, aiding in trend visualization.
Applications in Technical Analysis
The Kaiser Windowed Sinc Moving Average is particularly useful for precise trend identification, cycle analysis, and noise reduction in financial time series. Its ability to create custom low-pass filters with independent control over cutoff and filter accuracy makes it a powerful tool for analyzing various market conditions and timeframes.
Compared to traditional moving averages, this indicator offers superior frequency response characteristics and reduced lag in trend identification when properly tuned. It provides greater flexibility in filter design, allowing analysts to create moving averages tailored to specific trading strategies or market behaviors.
Conclusion
The Kaiser Windowed Sinc Moving Average represents an advanced approach to price smoothing and trend identification in technical analysis. By making the ideal low-pass filter characteristics of the sinc function practically applicable through Kaiser windowing, this indicator provides traders and analysts with a sophisticated tool for examining price trends and cycles.
Its implementation in Pine Script contributes to the TradingView community by making advanced signal processing techniques accessible for experimentation and further development in technical analysis. This indicator serves not only as a practical tool for market analysis but also as an educational resource for those interested in the intersection of signal processing and financial markets.
Related script:
Deep Crab Harmonic Pattern [TradingFinder] Reversal Zones🔵 Introduction
The Deep Crab pattern is a 5-point extension harmonic structure (X-A-B-C-D) used in technical analysis to identify potential reversal points in financial markets. Like the original Crab pattern, it heavily relies on a 1.618 XA projection to form the Potential Reversal Zone (PRZ).
However, the key difference lies in the B point, which must be an 0.886 retracement of the XA leg. The D point in this pattern typically extends beyond the X point, signaling a strong potential reversal in price movement.
Bullish Deep Crab :
The Bullish Deep Crab is a pattern used in technical analysis to spot potential trend reversals. It signals a shift from a downtrend to an uptrend. Traders enter a buy position at the D point and set a stop-loss below point X, anticipating a price increase.
Bearish Deep Crab :
The Bearish Deep Crab is a reversal pattern that indicates the potential end of an uptrend. Traders enter a sell position at point D and set a stop-loss above point X, expecting the price to fall afterward.
🟣 Crab Vs Deep Crab
The Crab and Deep Crab patterns are both used to identify reversal points in technical analysis, but they differ in terms of correction depth :
Crab : The B point retraces between 38.2% to 61.8% of the XA leg, and point D extends beyond X, indicating a price reversal after a smaller correction.
Deep Crab : The B point retraces more deeply, around 88.6% of the XA leg, and point D has a stronger extension, signaling a reversal after a deeper correction.
The Deep Crab is more suited for identifying stronger price movements.
🔵 How to Use
To effectively use the Deep Crab pattern, it’s essential to correctly identify its five key points (X, A, B, C, and D) based on Fibonacci retracements and extensions. Traders look for a deep retracement at point B, followed by an extended move to point D, which typically signals a strong price reversal.
Once these points are established, traders can strategically enter positions at point D with appropriate stop-loss and take-profit levels, capitalizing on the anticipated market reversal. Proper use of Fibonacci tools is crucial for accurate pattern identification.
🟣 Bullish Deep Crab
To use the Bullish Deep Crab pattern, a trader identifies point D as the key price reversal point in a downtrend. Using Fibonacci tools, points X, A, B, and C are identified, with point B showing an 88.6% retracement of XA, and CD extending 1.618% of XA.
The trader enters a buy position at point D and sets a stop-loss below X, expecting a reversal from a downtrend to an uptrend.
🟣 Bearish Deep Crab
In the Bearish Deep Crab pattern, point D acts as the reversal point in an uptrend. After identifying points X, A, B, and C, D extends 1.618% of XA. Point B retraces 88.6% of XA. Traders enter a sell position at point D and place a stop-loss above X, anticipating a drop in price.
🔵 Setting
🟣 Logical Setting
ZigZag Pivot Period : You can adjust the period so that the harmonic patterns are adjusted according to the pivot period you want. This factor is the most important parameter in pattern recognition.
Show Valid Forma t: If this parameter is on "On" mode, only patterns will be displayed that they have exact format and no noise can be seen in them. If "Off" is, the patterns displayed that maybe are noisy and do not exactly correspond to the original pattern.
Show Formation Last Pivot Confirm : if Turned on, you can see this ability of patterns when their last pivot is formed. If this feature is off, it will see the patterns as soon as they are formed. The advantage of this option being clear is less formation of fielded patterns, and it is accompanied by the latest pattern seeing and a sharp reduction in reward to risk.
Period of Formation Last Pivot : Using this parameter you can determine that the last pivot is based on Pivot period.
🟣 Genaral Setting
Show : Enter "On" to display the template and "Off" to not display the template.
Color : Enter the desired color to draw the pattern in this parameter.
LineWidth : You can enter the number 1 or numbers higher than one to adjust the thickness of the drawing lines. This number must be an integer and increases with increasing thickness.
LabelSize : You can adjust the size of the labels by using the "size.auto", "size.tiny", "size.smal", "size.normal", "size.large" or "size.huge" entries.
🟣 Alert Setting
Alert : On / Off
Message Frequency : This string parameter defines the announcement frequency. Choices include: "All" (activates the alert every time the function is called), "Once Per Bar" (activates the alert only on the first call within the bar), and "Once Per Bar Close" (the alert is activated only by a call at the last script execution of the real-time bar upon closing). The default setting is "Once per Bar".
Show Alert Time by Time Zone : The date, hour, and minute you receive in alert messages can be based on any time zone you choose. For example, if you want New York time, you should enter "UTC-4". This input is set to the time zone "UTC" by default.
🔵 Conclusion
The Deep Crab pattern is a valuable reversal tool in technical analysis, known for its deep retracement and extended price movements.
Unlike other harmonic patterns, it emphasizes identifying critical points where price action is likely to reverse sharply. This pattern works well in both bullish and bearish market scenarios, offering clear signals for entry and exit points.
However, successful application requires a deep understanding of market behavior and precise use of technical tools like Fibonacci retracement. Overall, mastering this pattern can enhance trading strategies and risk management.
Password Generator by Chervolino [CHE]Enhancing Password Security with Pine Script: A Deep Dive into Brute-Force Attack Prevention
1. Introduction: The Importance of Password Security
Why Password Security Matters:
In today’s digital age, protecting sensitive information through strong passwords is vital. Weak passwords are vulnerable to brute-force attacks, where attackers try every possible character combination until they guess the correct one.
What is Pine Script?
Pine Script is a scripting language developed by TradingView. While mainly used for financial analysis and strategy creation, its versatility allows us to explore other domains, such as password generation and security analysis.
2. Understanding Brute-Force Attacks
What is a Brute-Force Attack?
A brute-force attack systematically tries every possible combination of characters until the correct password is found. The longer and more complex the password, the more secure it is.
Types of Characters in Passwords:
Lowercase Letters (26 characters): Examples include 'a' to 'z'.
Uppercase Letters (26 characters): Examples include 'A' to 'Z'.
Digits (10 characters): Examples include '0' to '9'.
Special Characters: Characters such as '!@#$%^&*' add further complexity to a password.
3. The Role of Password Length in Security
Why Does Password Length Matter?
The number of possible combinations grows exponentially as the length of the password increases.
For example, a password made of only lowercase letters has 26 possible characters. A 7-character password in this case has 26 raised to the power of 7 possible combinations, which equals about 8 billion possibilities.
In comparison, if uppercase letters are included, the possible combinations jump to 52 raised to the power of 7, resulting in over 1 trillion combinations.
Time to Crack a Password:
Assuming a computer can test 2.15 billion passwords per second:
A 7-character password with only lowercase letters can be cracked in about 3.74 seconds.
If uppercase letters are added, it takes approximately 8 minutes.
Adding numbers and special characters makes the cracking time increase further to hours or even days.
4. Password Strength Analysis Using Pine Script
How Pine Script Helps in Password Analysis:
Pine Script can simulate password strength by generating random passwords and calculating how long it would take for a brute-force attack to crack them based on different character combinations and lengths.
We can experiment with using different types of characters (uppercase, lowercase, digits, special characters) and varying the length of the password to estimate the security.
For example:
A password consisting only of lowercase letters would take just a few seconds to crack.
By adding uppercase letters, the time increases to several minutes.
Including digits and special characters can make a password secure for many hours, or even days, depending on the length.
5. Results: Time to Crack Passwords
Here’s a textual summary of how different passwords can be cracked based on their composition and length:
Password with Lowercase Letters Only:
Length: 8 characters
Time to Crack: Less than 1 second.
Password with Uppercase and Lowercase Letters:
Length: 8 characters
Time to Crack: Approximately 24 hours.
Password with Uppercase, Lowercase, and Digits:
Length: 8 characters
Time to Crack: Around 27 minutes.
Password with Uppercase, Lowercase, Digits, and Special Characters:
Length: 12 characters
Time to Crack: Several hundred years.
From these examples, you can see that adding complexity to a password by using a variety of character types and increasing its length exponentially increases the time required to crack it.
6. Best Practices for Password Security
Use a mix of character types: Include lowercase and uppercase letters, digits, and special characters to increase complexity.
Increase the password length: The longer the password, the more difficult it is to crack.
Avoid predictable patterns: Refrain from using common words, dates, or sequential characters like "123456" or "password123".
Use a password manager: Tools like 1Password or LastPass can help store and manage complex passwords securely, so you only need to remember one master password.
7. Conclusion
Password length and complexity are the two most important factors in protecting against brute-force attacks.
Pine Script offers a powerful way to simulate password generation and security analysis, giving you insights into how secure your password is and how long it would take to crack it.
By applying these techniques, you can ensure that your passwords are strong and secure, making brute-force attacks infeasible.
Earnings Date Highlighter - from0_to_1This indicator, called "Earnings Date Highlighter," is designed to visualize earnings data for up to four different stocks on a single chart. It's particularly useful for traders or investors who want to track earnings events for multiple companies simultaneously, such as the top holdings of an ETF.
Key features:
1. Tracks earnings data (estimates and actuals) for four user-defined symbols.
2. Plots earnings data points with customizable colors for each symbol.
3. Highlights earnings dates with background colors.
4. Displays green up arrows for earnings beats and red down arrows for earnings misses.
Why someone would use it:
1. To monitor earnings events for multiple stocks in a single view.
2. To quickly identify potential market-moving events for key components of an ETF or portfolio.
3. To spot patterns in earnings performance across different companies or sectors.
4. To help with timing trades or adjusting positions around earnings announcements.
This tool can be particularly valuable for investors focused on ETFs, as it allows them to visualize earnings dates and performance for the ETF's major holdings all in one place, potentially providing insights into how the ETF might behave around these key events.
Author:
www.tradingview.com
Kaiser Window MAKaiser Window Moving Average Indicator
The Kaiser Window Moving Average is a technical indicator that implements the Kaiser window function in the context of a moving average. This indicator serves as an example of applying the Kaiser window and the modified Bessel function of the first kind in technical analysis, providing an open-source implementation of these functions in the TradingView Pine Script ecosystem.
Key Components
Kaiser Window Implementation
This indicator incorporates the Kaiser window, a parameterized window function with certain frequency response characteristics. By making this implementation available in Pine Script, it allows for exploration and experimentation with the Kaiser window in the context of financial time series analysis.
Modified Bessel Function of the First Kind
The indicator includes an implementation of the modified Bessel function of the first kind, which is integral to the Kaiser window calculation. This mathematical function is now accessible within TradingView, potentially useful for other custom indicators or studies.
Customizable Alpha Parameter
The indicator features an adjustable alpha parameter, which directly influences the shape of the Kaiser window. This parameter allows for experimentation with the indicator's behavior:
Lower alpha values: The indicator's behavior approaches that of a Simple Moving Average (SMA)
Moderate alpha values: The behavior becomes more similar to a Weighted Moving Average (WMA)
Higher alpha values: Increases the weight of more recent data points
In signal processing terms, the alpha parameter affects the trade-off between main-lobe width and side lobe level in the frequency domain.
Centered and Non-Centered Modes
The indicator offers two operational modes:
Non-Centered (Real-time) Mode: Uses half of the Kaiser window, starting from the peak. This mode operates similarly to traditional moving averages, suitable for real-time analysis.
Centered Mode: Utilizes the full Kaiser window, resulting in a phase-correct filter. This mode introduces a delay equal to half the window size, with the plot automatically offset to align with the correct time points.
Visualization Options
The indicator includes several visualization features to aid in analysis:
Gradient Coloring: Offers three gradient options:
• Three-color gradient: Includes a neutral color
• Two-color gradient: Traditional up/down color scheme
• Solid color: For a uniform appearance
Glow Effect: An optional visual enhancement for the moving average line.
Background Fill: An option to fill the area between the moving average and the price.
Use Cases
The Kaiser Window Moving Average can be applied similarly to other moving averages. Its primary value lies in providing an example implementation of the Kaiser window and modified Bessel function in TradingView. It serves as a starting point for traders and analysts interested in exploring these mathematical concepts in the context of technical analysis.
Conclusion
The Kaiser Window Moving Average indicator demonstrates the application of the Kaiser window function in a moving average calculation. By providing open-source implementations of the Kaiser window and the modified Bessel function of the first kind, this indicator contributes to the expansion of available mathematical tools in the TradingView Pine Script environment, potentially facilitating further experimentation and development in technical analysis.
AnyTimeAndPrice
This indicator allows users to input a specific start time and display the price of a lower timeframe on a higher timeframe chart. It offers customization options for:
- Display name
- Label color
- Line extension
By adding multiple instances of the AnyTimeframeTimeAndPrice indicator, each customized for different times and prices, you can create a powerful and flexible tool for analyzing market data. Here's a potential setup:
1. Instance 1:
- Time: 08:23
- Price: Open
- Display Name: "8:23 Open"
- Label Color: Green
2. Instance 2:
- Time: 12:47
- Price: High
- Display Name: "12:47 High"
- Label Color: Red
3. Instance 3:
- Time: 15:19
- Price: Low
- Display Name: "3:19 Low"
- Label Color: Blue
4. Instance 4:
- Time: 16:53
- Price: Close
- Display Name: "4:53 Close"
- Label Color: Yellow
By having multiple instances, you can:
- Track different times and prices on the same chart
- Customize the display names, label colors, and line extensions for each instance
- Easily compare and analyze the relationships between different times and prices
This setup can be particularly useful for:
- Identifying key levels and support/resistance areas
- Analyzing market trends and patterns
- Making more informed trading decisions
Inputs:
1. AnyStartHour: Integer input for the start hour (default: 09, range: 0-23)
2. AnyStartMinute: Integer input for the start minute (default: 30, range: 0-59)
3. Sourcename: String input for the display name (default: "Open", options: "Open", "Close", "High", "Low")
4. Src_col: Color input for the label color (default: aqua)
5. linetimeExtMulti: Integer input for the line time extension (default: 1, range: 1-5)
Calculations:
1. AnyinputStartTime: Timestamp for the input start time
2. inputhour and inputminute: Hour and minute components of the input start time
3. formattedAnyTime: Formatted string for the input start time (HH:mm)
4. currenttime: Current timestamp
5. currenthour and currentminute: Hour and minute components of the current time
6. formattedTime: Formatted string for the current time (HH:mm)
7. onTime and okTime: Boolean flags for checking if the current time matches the input start time or is within the session
8. firstbartime: Timestamp for the first bar of the session
9. dailyminutesfromSource: Calculation for the daily minutes from the source
10. anyminSrcArray: Request security lower timeframe array for the source
11. ltf (lower timeframe): Integer variable for tracking the lower timeframe
12. Sourcevalue: Float variable for storing the source value
13. linetimeExt: Integer variable for line extension (calculated from linetimeExtMulti)
Logic:
1. Check if the current time matches the input start time or is within the session
2. If true, plot a line and label with the source value and formatted time
3. If not, check if the current time is within the daily session and plot a line and label accordingly
Notes:
- The script uses request.security_lower_tf to request data from a lower timeframe
- The script uses line.new and label.new to plot lines and labels on the chart
- The script uses str.format_time to format timestamps as strings (HH:mm)
- The script uses xloc.bar_time to position lines and labels at the bar time
This script allows users to input a specific start time and display the price of a lower timeframe on a higher timeframe chart, with options for customizing the display name, label color, and line extension.
TradeTracker v33 - Interactive Journal [AR33_]TradeTracker v33 - Interactive Journal is a unique tool designed to enhance your trading experience by integrating an interactive journal directly onto your charts. Unlike traditional trading journals that require manual entries outside of TradingView, this script allows traders to document, track, and review their trades in real-time, right where the action happens.
What sets TradeTracker v33 apart from existing tools is its seamless blend of note-taking, task management, and performance tracking—all within a single, intuitive interface. With features like customizable checklists, due dates, and color-coded status indicators, this script provides a powerful and practical solution for traders who want to stay organized and disciplined.
2. Description
. TradeTracker v33 - Interactive Journal is designed to keep traders on track by allowing them to record trade-related notes, set tasks, and mark progress directly on their charts.
Here’s how it works:
• Purpose: The script serves as an all-in-one journal and task manager, helping traders document their trading strategies, track ongoing tasks, and review completed actions. It’s particularly useful for maintaining discipline and ensuring that every trade is executed according to a well-thought-out plan.
• How It Works:
• Interactive Notes and Tasks: Users can create and manage notes and tasks directly on their charts. Each note can be customized with a title, description, due date, and completion status.
• Status Indicators: Tasks are color-coded based on their status—green for completed, red for overdue, and default colors for pending tasks—allowing traders to quickly assess their progress.
• Dynamic Display: Notes are displayed in a clean, organized table on the chart, making it easy to review multiple tasks without cluttering the trading interface.
• Usage:
• Adding Notes: Simply fill in the note title, content, and optional due date within the script’s input settings, and the note will appear on your chart.
• Tracking Progress: Mark tasks as completed with a simple toggle, and the script will update their status in real-time.
• Customizing Your Workflow: Adjust the position, size, and visibility of notes to fit your trading style, ensuring that your journal supports rather than distracts from your trading activities.
3. Chart Presentation
To provide a clear and focused user experience, TradeTracker v33 - Interactive Journal is designed to be the sole feature on your chart when published. This ensures that users can easily identify and interact with their notes and tasks without any unnecessary distractions.
• Clean and Focused Display: The chart will exclusively display the interactive journal, showcasing how tasks and notes appear and update in real-time as you manage them.
• Useful Annotations: Annotations such as checkboxes and status indicators are clearly explained within the script’s description and are vital to understanding the functionality of the tool.
• Minimal Distractions: Only elements directly related to the script’s functionality are included on the chart, ensuring that users can easily follow along and implement the script in their own trading setup.
Change in State of Delivery CISD ICT [TradingFinder] Liquidity 1🔵 Introduction
🟣 What is CISD ?
Change in State of Delivery (CISD) is a key concept in technical analysis, similar to Change of Character (ChoCh) and Market Structure Shift (MSS) in the ICT (Inner Circle Trader) and Smart Money trading styles. Like ChoCh and MSS, CISD helps traders identify critical changes in market structure and make timely entries into trades.
To determine the CISD Level, traders typically review the last 1 to 4 candles to identify the first positive or negative candle. The CISD Level is then set using the opening price of the next candle.
In this version of the indicator, support and resistance levels are defined based on liquidity, which includes patterns such as SFP (Swing Failure Pattern), fake breakout, and false breakout.
Bullish CISD :
Bearish CISD :
🔵 How to Use
🟣 Bullish CISD (Change in State of Delivery Upward)
In Bullish CISD, the trend shifts from bearish to bullish after the price hits a liquidity zone, typically indicated by patterns such as SFP, fake breakout, or false breakout.
The steps to identify Bullish CISD are as follow s:
Identify the liquidity zone (SFP, fake breakout).
Review the candles and find the first positive candle.
Set the CISD Level using the opening price of the next candle after the positive candle.
Confirm the change in state of delivery when the price closes above the CISD Level.
Enter the trade after CISD confirmation.
🟣 Bearish CISD (Change in State of Delivery Downward)
In Bearish CISD, the trader looks for a shift from a bullish to a bearish trend. This change typically occurs when the price hits a liquidity level, indicated by patterns such as SFP or false breakout.
The steps to identify Bearish CISD are :
Identify the liquidity zone.
Review the candles and find the first negative candle.
Set the CISD Level using the opening price of the next candle after the negative candle.
Confirm the change in state of delivery when the price closes below the CISD Level.
Enter a short trade after CISD confirmation.
🟣 CISD Compared to ChoCh and MSS (CISD Vs ChoCh/ MSS)
CISD, ChoCh, and MSS are all tools for identifying trend changes in the market, but they have some differences :
CISD: Focuses on a change in the state of delivery and uses liquidity patterns (SFP, fake breakout) and key candles to confirm trend reversals.
ChoCh: Identifies a change in the market’s character, often signaling rapid shifts in trend direction.
MSS: Focuses on changes in market structure and identifies the breaking of key levels as a signal of trend shifts.
🔵 Settings
🟣 CISD Logical settings
Bar Back Check : Determining the return of candles to identify the CISD level.
CISD Level Validity : CISD level validity period based on the number of candles.
🟣 SFP Logical settings
Swing period : You can set the swing detection period.
Max Swing Back Method : It is in two modes "All" and "Custom". If it is in "All" mode, it will check all swings, and if it is in "Custom" mode, it will check the swings to the extent you determine.
Max Swing Back : You can set the number of swings that will go back for checking.
🟣 CISD Display settings
Displaying or not displaying swings and setting the color of labels and lines.
🟣 SFP Display settings
Displaying or not displaying swings and setting the color of labels and lines.
🔵 Conclusion
CISD is a powerful tool for identifying trend reversals using liquidity patterns and key candle analysis. Traders can use the CISD Level to detect trend changes and find optimal entry and exit points.
This concept is similar to ChoCh and MSS but stands out with its focus on confirming trend changes through liquidity and specific patterns. With the right approach, CISD helps traders capitalize on market movements more effectively.
Volume-Price PercentileDescription:
The "Volume-Price Percentile Live" indicator is designed to provide real-time analysis of the relationship between volume percentiles and price percentiles on any given timeframe. This tool helps traders assess market activity by comparing how current volume levels rank relative to historical volume data and how current price movements (specifically high-low ranges) rank relative to historical price data. The indicator visualizes the ratio of volume percentile to price percentile as a histogram, allowing traders to gauge the relative strength of volume against price movements in real time.
Functionality:
Volume Percentile: Calculates the percentile rank of the current volume within a user-defined rolling period (default is 30 bars). This percentile indicates where the current volume stands in comparison to historical volumes over the specified period.
Price Percentile: Calculates the percentile rank of the current candle's high-low difference within a user-defined rolling period (default is 30 bars). This percentile reflects the current price movement's strength relative to past movements over the specified period.
Percentile Ratio (VP Ratio): The indicator plots the ratio of the volume percentile to the price percentile. This ratio helps identify periods when volume is significantly higher or lower relative to price movement, providing insights into potential market imbalances or strength.
Real-Time Data: By fetching data from a lower timeframe (e.g., 1-minute), the indicator updates continuously within the current timeframe, offering live, intra-candle updates. This ensures that traders can see the histogram change in real-time as new data becomes available, without waiting for the current candle to close.
How to Use:
Adding the Indicator: To use this indicator, add it to your chart on TradingView by selecting it from the Indicators list once it is published publicly.
Setting Parameters:
Volume Period Length: This input sets the rolling window length for calculating the volume percentile (default is 30). You can adjust it based on the desired sensitivity or historical period relevance.
Candle Period Length: This input sets the rolling window length for calculating the price percentile based on the high-low difference of candles (default is 30). Adjust this to match your trading style or analysis period.
Interpreting the Histogram:
The histogram represents the volume percentile divided by the price percentile.
Above 1: A value greater than 1 indicates that volume is relatively strong compared to price movement, which may suggest high activity or potential accumulation/distribution phases.
Below 1: A value less than 1 suggests that price movement is relatively stronger than volume, indicating potential weakness in volume relative to price moves.
Near 1: Values close to 1 suggest a balanced relationship between volume and price movement.
Application: Use this indicator to identify potential breakout or breakdown scenarios, assess the strength of price movements, and confirm trends. When volume percentile consistently leads price percentile, it might signal sustained interest and support for the current price trend. Conversely, if volume percentile lags significantly, it might warn of potential trend weakness.
Best Practices:
Multiple Timeframe Analysis: While the indicator provides real-time updates on any timeframe, consider using it alongside higher timeframe analysis to confirm trends and volume behavior across different periods.
Customization: Adjust the period lengths based on the asset’s typical volume and price behavior, as well as your trading strategy (e.g., short-term scalping vs. long-term trend following).
Complement with Other Indicators: Use this indicator in conjunction with other volume-based tools, trend indicators, or momentum oscillators to gain a comprehensive view of market dynamics.
Swing Failure Pattern SFP [TradingFinder] SFP ICT Strategy🔵 Introduction
The Swing Failure Pattern (SFP), also referred to as a "Fake Breakout" or "False Breakout," is a vital concept in technical analysis. This pattern is derived from classic technical analysis, price action strategies, ICT concepts, and Smart Money Concepts.
It’s frequently utilized by traders to identify potential trend reversals in financial markets, especially in volatile markets like cryptocurrencies and forex. SFP helps traders recognize failed attempts to breach key support or resistance levels, providing strategic opportunities for trades.
The Swing Failure Pattern (SFP) is a popular strategy among traders used to identify false breakouts and potential trend reversals in the market. This strategy involves spotting moments where the price attempts to break above or below a previous high or low (breakout) but fails to sustain the move, leading to a sharp reversal.
Traders use this strategy to identify liquidity zones where stop orders (stop hunt) are typically placed and targeted by larger market participants or whales.
When the price penetrates these areas but fails to hold the levels, a liquidity sweep occurs, signaling exhaustion in the trend and a potential reversal. This strategy allows traders to enter the market at the right time and capitalize on opportunities created by false breakouts.
🟣 Types of SFP
When analyzing SFPs, two main variations are essential :
Real SFP : This occurs when the price breaks a critical level but fails to close above it, then quickly reverses. Due to its clarity and strong signal, this SFP type is highly reliable for traders.
Considerable SFP : In this scenario, the price closes slightly above a key level but quickly declines. Although significant, it is not as definitive or trustworthy as a Real SFP.
🟣 Understanding SFP
The Swing Failure Pattern, or False Breakout, is identified when the price momentarily breaks a crucial support or resistance level but cannot maintain the movement, leading to a rapid reversal.
The pattern can be categorized as follows :
Bullish SFP : This type occurs when the price dips below a support level but rebounds above it, signaling that sellers failed to push the price lower, indicating a potential upward trend.
Bearish SFP : This pattern forms when the price surpasses a resistance level but fails to hold, suggesting that buyers couldn’t maintain the higher price, leading to a potential decline.
🔵 How to Use
To effectively identify an SFP or Fake Breakout on a price chart, traders should follow these steps :
Identify Key Levels: Locate significant support or resistance levels on the chart.
Observe the Fake Breakout: The price should break the identified level but fail to close beyond it.
Monitor Price Reversal: After the breakout, the price should quickly reverse direction.
Execute the Trade: Traders typically enter the market after confirming the SFP.
🟣 Examples
Bullish Example : Bitcoin breaks below a $30,000 support level, drops to $29,000, but closes above $30,000 by the end of the day, signaling a Real Bullish SFP.
Bearish Example : Ethereum surpasses a $2,000 resistance level, rises to $2,100, but then falls back below $2,000, forming a Bearish SFP.
🟣 Pros and Cons of SFP
Pros :
Effective in identifying strong reversal points.
Offers a favorable risk-to-reward ratio.
Applicable across different timeframes.
Cons :
Requires experience and deep market understanding.
Risk of encountering false breakouts.
Should be combined with other technical tools for optimal effectiveness.
🔵 Settings
🟣 Logical settings
Swing period : You can set the swing detection period.
SFP Type : Choose between "All", "Real" and "Considerable" modes to identify the swing failure pattern.
Max Swing Back Method : It is in two modes "All" and "Custom". If it is in "All" mode, it will check all swings, and if it is in "Custom" mode, it will check the swings to the extent you determine.
Max Swing Back : You can set the number of swings that will go back for checking.
🟣 Display settings
Displaying or not displaying swings and setting the color of labels and lines.
🟣 Alert Settings
Alert SFP : Enables alerts for Swing Failure Pattern.
Message Frequency : Determines the frequency of alerts. Options include 'All' (every function call), 'Once Per Bar' (first call within the bar), and 'Once Per Bar Close' (final script execution of the real-time bar). Default is 'Once per Bar'.
Show Alert Time by Time Zone : Configures the time zone for alert messages. Default is 'UTC'.
🔵 Conclusion
The Swing Failure Pattern (SFP), or False Breakout, is an essential analytical tool that assists traders in identifying key market reversal points for successful trading.
By understanding the nuances between Real SFP and Considerable SFP, and integrating this pattern with other technical analysis tools, traders can make more informed decisions and better manage their trading risks.
Buy script for stocks mathematical calculation chart. it is totally based on the square root calculation of previous day + 66.66% of Square root. ( last dat sqrt+66.66% of Sqrt). buy above the value. best for stock in intraday
Open-Close Price DifferenceInput time A (open time) and time B (closing time)
do not do anything with the year-month-date, it's there because I don't know how to fix it and it needs to be in such format.
the difference of price will be shown on the indicator window one candle after the closing time (opening at such time)
For research purpose only, no other intended purposes.
Greer BuyZone toolGreer BuyZone Tool
Description:
The Greer BuyZone Tool is a custom Pine Script indicator designed to help identify potential long-term investment opportunities by marking BuyZones on the chart. This tool utilizes the Aroon indicator in combination with Fibonacci numbers to define periods where the asset might be a good candidate for dollar-cost averaging.
Features:
BuyZone Detection: The script identifies and marks the beginning and end of a BuyZone with vertical lines and labels.
Visual Markers: A red vertical line and label indicate the start of a BuyZone, while a green vertical line and label mark the end of a BuyZone.
Aroon Indicator Calculation: Utilizes the Aroon indicator with a Fibonacci length (233) to determine key price levels.
How to Use:
Setup: Add the Greer BuyZone Tool to your TradingView chart. It will display vertical lines and labels marking the BuyZone periods.
BuyZone Identification: Use the red lines and labels ("BZ Begins ->>") to identify the start of a BuyZone, and the green lines and labels ("<<- BZ Ends") to determine when the BuyZone ends.
Long-Term Investment: This tool is intended for long-term investing and dollar-cost averaging strategies, not for day trading.
Disclaimer:
This script is provided for informational purposes only and is not intended as financial advice. The Greer BuyZone Tool is designed to assist in identifying potential long-term investment opportunities and is not suitable for day trading. The use of this tool involves risk, and there is no guarantee of profitability. Users are advised to conduct their own research and consult with a qualified financial advisor before making any investment decisions. The creator of this script assumes no liability for any losses or damages resulting from the use of this indicator.
Author: Sean Lee Greer
Date: 9/1/2024
Dynamic Trailing Stop with Trend ChangeKey features of this script:
Trend Identification: Uses previous day's high/low breaks to identify trend changes.
Uptrend starts when price closes above the previous day's high.
Downtrend starts when price closes below the previous day's low.
Dynamic Trailing Stop:
In an uptrend, the stop is set to the previous day's low and trails higher.
In a downtrend, the stop is set to the previous day's high and trails lower.
Visual Indicators:
Green triangle for uptrend start, red triangle for downtrend start.
Green/red line for the trailing stop.
Background color changes to light green in uptrends, light red in downtrends.
Alerts:
Trend change alerts when a new trend is identified.
Stop hit alerts when price crosses the trailing stop, suggesting a potential exit.
This implementation allows you to:
Identify trend changes based on previous day's high/low breaks.
Trail your stop loss dynamically as the trend progresses.
Get visual and alert-based signals for trend changes and potential exit points.
For swing trading, you could:
Enter long when an uptrend starts (green triangle).
Set your initial stop loss to the trailing stop (green line).
Exit if the price closes below the trailing stop or a downtrend starts (red triangle).
(Reverse for short trades)
Remember, while this strategy can be effective, it's important to combine it with other forms of analysis and proper risk management. The effectiveness can vary depending on the volatility of the asset and overall market conditions. Always test thoroughly before using in live trading.
