MA Cross HeatmapThe Moving Average Cross Heatmap Created by Technicator , visualizes the crossing distances between multiple moving averages using a heat map style color coding.
The main purpose of this visualization is to help identify potential trend changes or trading opportunities by looking at where the moving averages cross over each other.
Key Features:
Can plot up to 9 different moving average with their cross lengths you set
Uses a heat map to show crossing distances between the MAs
Adjustable settings like crossing length percentage, color scheme, color ceiling etc.
Overlay style separates the heat map from the price chart
This is a unique way to combine multiple MA analysis with a visual heat map representation on one indicator. The code allows you to fine-tune the parameters to suit your trading style and preferences. Worth checking out if you trade using multiple moving average crossovers as part of your strategy.
M-oscillator
Oscillator Suite [KFB Quant]Oscillator Suite is a indicator designed to revolutionize your trading strategy. Developed by kikfraben, this innovative tool aggregates eleven powerful oscillators into one intuitive interface, providing you with a comprehensive view of market sentiment like never before.
Originality and Innovation:
Unlike traditional indicators that focus on single aspects of market analysis, Oscillator Suite stands out by integrating multiple oscillators, making it a pioneering solution in technical analysis. This unique approach empowers traders to gain deeper insights into market dynamics and make more informed trading decisions.
Functionality:
Oscillator Suite calculates signals for each selected oscillator based on its specific formula, offering a diverse range of market insights. Whether you're assessing trend strength, market momentum, or price movements, this indicator has you covered.
Aggregated Score:
The indicator combines signals from all chosen oscillators into an aggregated score, providing a holistic assessment of market sentiment. This aggregated score serves as a powerful tool for identifying trends and potential trading opportunities.
Customization and Ease of Use:
With customizable parameters such as colors, smoothing options, and oscillator settings, Oscillator Suite can be tailored to suit your unique trading style and preferences. Its user-friendly interface makes it easy to interpret and act upon the information presented.
How to Use:
Identify Trends: Analyze the aggregated score and individual oscillator signals to identify prevailing market trends.
Confirm Trade Signals: Use multiple oscillator alignments to strengthen the conviction behind trade signals.
Manage Risk: Gain insight into potential reversals or trend continuations to effectively manage risk.
This is not financial advice. Trading is risky & most traders lose money. Past performance does not guarantee future results. This indicator is for informational & educational purposes only.
Price Ratio Indicator [ChartPrime]The Price Ratio Indicator is a versatile tool designed to analyze the relationship between the price of an asset and its moving average. It helps traders identify overbought and oversold conditions in the market, as well as potential trend reversals.
◈ User Inputs:
MA Length: Specifies the length of the moving average used in the calculation.
MA Type Fast: Allows users to choose from various types of moving averages such as Exponential Moving Average (EMA), Simple Moving Average (SMA), Weighted Moving Average (WMA), Volume Weighted Moving Average (VWMA), Relative Moving Average (RMA), Double Exponential Moving Average (DEMA), Triple Exponential Moving Average (TEMA), Zero-Lag Exponential Moving Average (ZLEMA), and Hull Moving Average (HMA).
Upper Level and Lower Level: Define the threshold levels for identifying overbought and oversold conditions.
Signal Line Length: Determines the length of the signal line used for smoothing the indicator's values.
◈ Indicator Calculation:
The indicator calculates the ratio between the price of the asset and the selected moving average, subtracts 1 from the ratio, and then smooths the result using the chosen signal line length.
// 𝙄𝙉𝘿𝙄𝘾𝘼𝙏𝙊𝙍 𝘾𝘼𝙇𝘾𝙐𝙇𝘼𝙏𝙄𝙊𝙉𝙎
//@ Moving Average's Function
ma(src, ma_period, ma_type) =>
ma =
ma_type == 'EMA' ? ta.ema(src, ma_period) :
ma_type == 'SMA' ? ta.sma(src, ma_period) :
ma_type == 'WMA' ? ta.wma(src, ma_period) :
ma_type == 'VWMA' ? ta.vwma(src, ma_period) :
ma_type == 'RMA' ? ta.rma(src, ma_period) :
ma_type == 'DEMA' ? ta.ema(ta.ema(src, ma_period), ma_period) :
ma_type == 'TEMA' ? ta.ema(ta.ema(ta.ema(src, ma_period), ma_period), ma_period) :
ma_type == 'ZLEMA' ? ta.ema(src + src - src , ma_period) :
ma_type == 'HMA' ? ta.hma(src, ma_period)
: na
ma
//@ Smooth of Source
src = math.sum(source, 5)/5
//@ Ratio Price / MA's
p_ratio = src / ma(src, ma_period, ma_type) - 1
◈ Visualization:
The main plot displays the price ratio, with color gradients indicating the strength and direction of the ratio.
The bar color changes dynamically based on the ratio, providing a visual representation of market conditions.
Invisible Horizontal lines indicate the upper and lower threshold levels for overbought and oversold conditions.
A signal line, smoothed using the specified length, helps identify trends and potential reversal points.
High and low value regions are filled with color gradients, enhancing visualization of extreme price movements.
MA type HMA gives faster changes of the indicator (Each MA has its own specifics):
MA type TEMA:
◈ Additional Features:
A symbol displayed at the bottom right corner of the chart provides a quick visual reference to the current state of the indicator, with color intensity indicating the strength of the ratio.
Overall, the Price Ratio Indicator offers traders valuable insights into price dynamics and helps them make informed trading decisions based on the relationship between price and moving averages. Adjusting the input parameters allows for customization according to individual trading preferences and market conditions.
Normalised T3 Oscillator [BackQuant]Normalised T3 Oscillator
The Normalised T3 Oscillator is an technical indicator designed to provide traders with a refined measure of market momentum by normalizing the T3 Moving Average. This tool was developed to enhance trading decisions by smoothing price data and reducing market noise, allowing for clearer trend recognition and potential signal generation. Below is a detailed breakdown of the Normalised T3 Oscillator, its methodology, and its application in trading scenarios.
1. Conceptual Foundation and Definition of T3
The T3 Moving Average, originally proposed by Tim Tillson, is renowned for its smoothness and responsiveness, achieved through a combination of multiple Exponential Moving Averages and a volume factor. The Normalised T3 Oscillator extends this concept by normalizing these values to oscillate around a central zero line, which aids in highlighting overbought and oversold conditions.
2. Normalization Process
Normalization in this context refers to the adjustment of the T3 values to ensure that the oscillator provides a standard range of output. This is accomplished by calculating the lowest and highest values of the T3 over a user-defined period and scaling the output between -0.5 to +0.5. This process not only aids in standardizing the indicator across different securities and time frames but also enhances comparative analysis.
3. Integration of the Oscillator and Moving Average
A unique feature of the Normalised T3 Oscillator is the inclusion of a secondary smoothing mechanism via a moving average of the oscillator itself, selectable from various types such as SMA, EMA, and more. This moving average acts as a signal line, providing potential buy or sell triggers when the oscillator crosses this line, thus offering dual layers of analysis—momentum and trend confirmation.
4. Visualization and User Interaction
The indicator is designed with user interaction in mind, featuring customizable parameters such as the length of the T3, normalization period, and type of moving average used for signals. Additionally, the oscillator is plotted with a color-coded scheme that visually represents different strength levels of the market conditions, enhancing readability and quick decision-making.
5. Practical Applications and Strategy Integration
Traders can leverage the Normalised T3 Oscillator in various trading strategies, including trend following, counter-trend plays, and as a component of a broader trading system. It is particularly useful in identifying turning points in the market or confirming ongoing trends. The clear visualization and customizable nature of the oscillator facilitate its adaptation to different trading styles and market environments.
6. Advanced Features and Customization
Further enhancing its utility, the indicator includes options such as painting candles according to the trend, showing static levels for quick reference, and alerts for crossover and crossunder events, which can be integrated into automated trading systems. These features allow for a high degree of personalization, enabling traders to mold the tool according to their specific trading preferences and risk management requirements.
7. Theoretical Justification and Empirical Usage
The use of the T3 smoothing mechanism combined with normalization is theoretically sound, aiming to reduce lag and false signals often associated with traditional moving averages. The practical effectiveness of the Normalised T3 Oscillator should be validated through rigorous backtesting and adjustment of parameters to match historical market conditions and volatility.
8. Conclusion and Utility in Market Analysis
Overall, the Normalised T3 Oscillator by BackQuant stands as a sophisticated tool for market analysis, providing traders with a dynamic and adaptable approach to gauging market momentum. Its development is rooted in the understanding of technical nuances and the demand for a more stable, responsive, and customizable trading indicator.
Thus following all of the key points here are some sample backtests on the 1D Chart
Disclaimer: Backtests are based off past results, and are not indicative of the future.
INDEX:BTCUSD
INDEX:ETHUSD
BINANCE:SOLUSD
[blackcat] L1 Dynamic Momentum Indicator
**1. Overview**
" L1 Dynamic Momentum Indicator" is a custom TradingView indicator designed to analyze price momentum and market trends. It combines the calculation methods of Stoch (RSV) and Moving Average (SMA) to provide market overbought and oversold signals.
**2. Calculation Method**
- **RSV Value Calculation**: The RSV value is calculated using the relative relationship between the current price and the lowest and highest prices over the past 89 periods.
- **K Value Calculation**: The calculated RSV value is subjected to a 3-period Simple Moving Average (SMA) to obtain the K value.
- **D Value Calculation**: The K value is subjected to a 3-period Simple Moving Average (SMA) to obtain the D value.
- **Momentum Difference Calculation**: The difference between the 13-period Exponential Moving Average (EMA) and the 34-period EMA of closing prices is calculated, and then the moving average of this difference is calculated.
**3. Indicator Display**
- **K and D Lines**: The moving averages of the K value and D value are displayed on the chart, indicating a strong market condition when the K line is above the D line, and a weak market condition when the K line is below the D line.
- **Threshold Line**: A fixed threshold line of 50 is displayed to distinguish the overbought and oversold areas.
- **Green and Red Bars**: Green and red bars are drawn on the chart based on the relationship between the momentum difference and the average value, indicating the market trend.
**4. Usage Suggestions**
- When the market is in a strong condition, a potential reversal may occur in the overbought area after selling. When the market is in a weak condition, a potential bounce may occur in the oversold area after buying.
- Pay attention to the changes in market trends, with the appearance of green bars may indicate that the market is about to rise, and the appearance of red bars may indicate that the market is about to fall.
**5. Caution**
- The indicator is based on the provided code and may require adjustments based on market conditions.
- The accuracy of the indicator depends on the selection of calculation parameters and the reliability of market data.
Advanced MACD [CryptoSea]Advanced MACD (AMACD) enhances the traditional MACD indicator, integrating innovative features for traders aiming for deeper insights into market momentum and sentiment. It's crafted for those seeking to explore nuanced behaviors of the MACD histogram, thus offering a refined perspective on market dynamics.
Divergence moves can offer insight into continuation or potential reversals in structure, the example below is a clear continuation signal.
Key Features
Enhanced Histogram Analysis: Precisely tracks movements of the MACD histogram, identifying growth or decline periods, essential for understanding market momentum.
High/Low Markers: Marks the highest and lowest points of the histogram within a user-defined period, signaling potential shifts in the market.
Dynamic Averages Calculation: Computes average durations of histogram phases, providing a benchmark against historical performance.
Color-Coded Histogram: Dynamically adjusts the histogram's color intensity based on the current streak's duration relative to its average, offering a visual cue of momentum strength.
Customisable MACD Settings: Enables adjustments to MACD parameters, aligning with individual trading strategies.
Interactive Dashboard: Showcases an on-chart table with average durations for each phase, aiding swift decision-making.
Settings & Customisation
MACD Settings: Customise fast length, slow length, and signal smoothing to tailor the MACD calculations to your trading needs.
Reset Period: Determine the number of bars to identify the histogram's significant high and low points.
Histogram High/Lows: Option to display critical high and low levels of the histogram for easy referencing.
Candle Colours: Select between neutral or traditional candle colors to match your analytical preferences.
When in strong trends, you can use the average table to determine when to look to get into a position. This example we are in a strong downtrend, we then see the histogram growing above the average in these conditions which is where we should look to get into a shorting position.
Strategic Applications
The AMACD serves not just as an indicator but as a comprehensive analytical tool for spotting market trends, momentum shifts, and potential reversal points. It's particularly useful for traders to:
Spot Momentum Changes Utilise dynamic coloring and streak tracking to alert shifts in momentum, helping anticipate market movements.
Identify Market Extremes Use high and low markers to spot potential market turning points, aiding in risk management and decision-making.
Alert Conditions
Above Average Movement Alerts: Triggered when the duration of the MACD histogram's growth or decline is unusually long, these alerts signal sustained momentum:
Above Zero: Alerts for both growing and declining movements above zero, indicating either continued bullish trends or potential bearish reversals.
Below Zero: Alerts for growth and decline below zero, pointing to potential bullish reversals or confirmed bearish trends.
High/Low Break Alerts: Activated when the histogram reaches new highs or falls to new lows beyond the set thresholds, these alerts are crucial for identifying shifts in market dynamics:
Break Above Last High: Indicates a potential upward trend as the histogram surpasses recent highs.
Break Below Last Low: Warns of a possible downward trend as the histogram drops below recent lows.
These alert conditions enable traders to automate part of their market monitoring or potential to automate the signals to take action elsewhere.
Crypto Realized Profits/Losses Extremes [AlgoAlpha]🌟🚀 Introducing the Crypto Realized Profits/Losses Extremes Indicator by AlgoAlpha 🚀🌟
Unlock the potential of cryptocurrency markets with our cutting-edge On-Chain Pine Script™ indicator, designed to highlight extreme realized profit and loss zones! 🎯📈
Key Features:
✨ Realized Profits/Losses Calculation: Uses real-time data from the blockchain to monitor profit and loss realization events.
📊 Multi-Crypto Compatibility: The Indicator is compatible on other Crypto tickers besides Bitcoin.
⚙️ Customizable Sensitivity: Adjust the look-back period, normalization period, and deviation thresholds to tailor the indicator to your trading style.
🎨 Visual Enhancements: Choose from a variety of colors for up and down trends, and toggle extreme profit/loss overlay for easy viewing.
🔔 Integrated Alerts: Set up alerts for high and extreme profit or loss conditions, helping you stay ahead of significant market movements.
🔍 How to Use:
🛠 Add the Indicator: Add the indicator to favorites. Customize settings like period lengths and deviation thresholds according to your needs.
📊 Market Analysis: Monitor the main oscillator and the bands to understand current profit and loss extremes in the market. When the oscillator is at the upper band, this means that the market is doing really well and traders/investors will be likely to take profit and cause a reversal. The opposite is true when the oscillator reaches the lower band. The main oscillator can also be used for trend analysis.
🔔 Set Alerts: Configure alerts to notify you when the market enters a zone of high profit or loss, or during trend changes, enabling timely decisions without constant monitoring.
How It Works:
The indicator calculates a normalized area under the RSI curve applied on on-chain data regarding the number of wallets in profit. It employs a custom "src" variable that aggregates data from the blockchain about profit and loss addresses, adapting to intraday or longer timeframes as needed. The main oscillator plots this normalized area, while the upper and lower bands are plotted based on a deviation metric to identify extreme conditions. Colored fills between these bands visually denote these zones. For interaction, the indicator plots bubbles for extreme profits or losses and provides optional bar coloring to reflect the current market trend.
🚀💹 Enjoy a comprehensive, customizable, and visually engaging tool that helps you stay ahead in the fast-paced crypto market!
RSI w/Hann WindowingThis RSI by John Ehlers of "Yet Another" Improved RSI. Taking advantage of the Hann windowing. As seen on PRC and published by John Ehlers, it has a zero mean and appears smoother than the classic RSI. In his own words " I prefer oscillator-type indicators to have a zero mean. We can achieve this simply by multiplying the classic RSI by 2 so it swings from 0 to 2, and then subtract 1 from the product so the indicator swings from -1 to +1." Ehlers goes on to say " Bear in mind 14 may not be the best length to analysis. So, the best length to use for the RSIH indicator is on the order of the dominant cycle period of the data."
This indicator works well with both bullish and bearish divergences. It also works well with oversold and overbought indications. Shown by the Red zone on top (Overbought) and the green zone on the bottom(oversold). Each which have an adjustable buffer zone. You may need to adjust the length of the RSIH to suit your asset. There are also multiply signal line's to choose from. Also take note of when the RSIH crosses up or down on the signal line.
None of this is financial advice.
Dynamic Cycle Oscillator [Quantigenics]This script is designed to navigate through the ebbs and flows of financial markets. At its core, this script is a sophisticated yet user-friendly tool that helps you identify potential market turning points and trend continuations.
How It Works:
The script operates by plotting two distinct lines and a central histogram that collectively form a band structure: a center line and two outer boundaries, indicating overbought and oversold conditions. The lines are calculated based on a blend of exponential moving averages, which are then refined by a root mean square (RMS) over a specified number of bars to establish the cyclic envelope.
The input parameters:
Fast and Slow Periods:
These determine the sensitivity of the script. Shorter periods react quicker to price changes, while longer periods offer a smoother view.
RMS Length:
This parameter controls the range of the cyclic envelope, influencing the trigger levels for trading signals.
Using the Script:
On your chart, you’ll notice how the Dynamic Cycle Oscillator’s lines and histogram weave through the price action. Here’s how to interpret the movements.
Breakouts and Continuations:
Buy Signal: Consider a long position when the histogram crosses above the upper boundary. This suggests a possible strong bullish run.
Sell Signal: Consider a short position when the histogram crosses below the lower boundary. This suggests a possible strong bearish run.
Reversals:
Buy Signal: Consider a long position when the histogram crosses above the lower boundary. This suggests an oversold market turning bullish.
Sell Signal: Consider a short position when the histogram crosses below the upper boundary. This implies an overbought market turning bearish.
The script’s real-time analysis can serve as a robust addition to your trading strategy, offering clarity in choppy markets and an edge in trend-following systems.
Thanks! Hope you enjoy!
Enhanced Predictive ModelThe "Enhanced Predictive Model" is a sophisticated TradingView indicator designed for traders looking for advanced predictive insights into market trends. This model leverages smoothed price data through an Exponential Moving Average (EMA) to ensure a more stable trend analysis and mitigate the effects of price volatility.
**Features of the Enhanced Predictive Model:**
- **Linear Regression Analysis**: Calculates a regression line over the smoothed price data to determine the prevailing market trend.
- **Predictive Trend Line**: Projects future market behavior by extending the current trend line based on the linear regression analysis.
- **EMA Smoothing**: Utilizes a dynamic smoothing mechanism to provide a clear view of the trend without the noise typically associated with raw price data.
- **Visual Trend Indicators**: Offers immediate visual cues through bar coloring, which changes based on the trend direction detected by the regression slope. Green indicates an uptrend, while red suggests a downtrend.
**Key Inputs:**
- **Regression Length**: Determines the number of bars used for the regression analysis, allowing customization based on the user's trading strategy.
- **EMA Length**: Sets the smoothing parameter for the EMA, balancing responsiveness and stability.
- **Future Bars Prediction**: Defines how many bars into the future the predictive line should extend, providing foresight into potential price movements.
- **Smoothing Length**: Adjusts the sensitivity of the trend detection, ideal for different market conditions.
This tool is ideal for traders focusing on medium to long-term trends and can be used across various markets, including forex, stocks, and cryptocurrencies. Whether you are a day trader or a long-term investor, the "Enhanced Predictive Model" offers valuable insights to help anticipate market moves and enhance your trading decisions.
**Usage Tips:**
- Best used in markets with moderate volatility for clearer trend identification.
- Combine with volume indicators or oscillators for a comprehensive trading strategy.
**Recommended for:**
- Trend Following
- Market Prediction
- Volatility Assessment
By employing this indicator, traders can not only follow the market trend but also anticipate changes, giving them a strategic edge in their trading activities.
Multiple Indicators Screener v2After taking the approval of Mr. QuantNomad
Multiple Indicators Screener by QuantNomad
New lists have been modified and added
Built-in indicators:
RSI (Relative Strength Index): Provides trading opportunities based on overbought or oversold market conditions.
MFI (Cash Flow Index): Measures the flow of cash into or from assets, which helps in identifying buying and selling areas.
Williams Percent Range (WPR): Measures how high or low the price has been in the last time period, giving signals of periods of saturation.
Supertrend: Used to determine market direction and potential entry and exit locations.
Volume Change Percentage: Provides an analysis of the volume change percentage, which helps in identifying demand and supply changes for assets.
How to use:
Users can choose which symbols they want to monitor and analyze using a variety of built-in indicators.
The indicator provides visual signals that help traders identify potential trading opportunities based on the selected settings.
RSI in purple = buy weak liquidity (safe entry).
MFI in yellow = Liquidity
WPR in blue = RSI, MFI and WPR in oversold areas for all.
Allows users to customize the display locations and appearance of the cursor to their personal preferences.
Disclaimer
Please remember that past performance may not be indicative of future results.
Due to various factors, including changing market conditions, the strategy may no longer perform as well as in historical backtesting.
This post and the script don’t provide any financial advice.
=========================================================================
فاحص لمؤشرات متعددة مع مخرجات جدول شاملة لتسهيل مراقبة الكثير من العملات تصل الى 99 في وقت واحد
بختصر الشرح
ظهور اللون البنفسجي يعني كمية الشراء ضعف السيولة .
ظهور اللون الازرق جميع المؤشرات وصلة الى مرحلة التشبع البيعي ( دخول آمن )
ظهور اللون الاصفر يعني السيولة ضعفين الشراء ( عكس اتجاه قريب ) == ركزو على هاللون خصوصا مع عملات الخفيفة
Slow Volume Strength Index (SVSI)The Slow Volume Strength Index (SVSI), introduced by Vitali Apirine in Stocks & Commodities (Volume 33, Chapter 6, Page 28-31), is a momentum oscillator inspired by the Relative Strength Index (RSI). It gauges buying and selling pressure by analyzing the disparity between average volume on up days and down days, relative to the underlying price trend. Positive volume signifies closes above the exponential moving average (EMA), while negative volume indicates closes below. Flat closes register zero volume. The SVSI then applies a smoothing technique to this data and transforms it into an oscillator with values ranging from 0 to 100.
Traders can leverage the SVSI in several ways:
1. Overbought/Oversold Levels: Standard thresholds of 80 and 20 define overbought and oversold zones, respectively.
2. Centerline Crossovers and Divergences: Signals can be generated by the indicator line crossing a midline or by divergences from price movements.
3. Confirmation for Slow RSI: The SVSI can be used to confirm signals generated by the Slow Relative Strength Index (SRSI), another oscillator developed by Apirine.
🔹 Algorithm
In the original article, the SVSI is calculated using the following formula:
SVSI = 100 - (100 / (1 + SVS))
where:
SVS = Average Positive Volume / Average Negative Volume
* Volume is considered positive when the closing price is higher than the six-day EMA.
* Volume is considered negative when the closing price is lower than the six-day EMA.
* Negative volume values are expressed as absolute values (positive).
* If the closing price equals the six-day EMA, volume is considered zero (no change).
* When calculating the average volume, the indicator utilizes Wilder's smoothing technique, as described in his book "New Concepts In Technical Trading Systems."
Note that this indicator, the formula has been simplified to be
SVSI = 100 * Average Positive Volume / (Average Positive Volume + Average Negative Volume)
This formula achieves the same result as the original article's proposal, but in a more concise way and without the need for special handling of division by zero
🔹 Parameters
The SVSI calculation offers configurable parameters that can be adjusted to suit individual trading styles and goals. While the default lookback periods are 6 for the EMA and 14 for volume smoothing, alternative values can be explored. Additionally, the standard overbought and oversold thresholds of 80 and 20 can be adapted to better align with the specific security being analyzed.
ATR Oscillator with DotsThe ATR Oscillator with Dots utilizes the Average True Range (ATR), a traditional measure that captures the extent of an asset's price movements within a given timeframe. Rather than depicting these values in a continuous line, the ATR Oscillator represents them as discrete dots, colored according to the price movement direction: green for upward movements when the current close is higher than the previous, and red for downward movements when the current close is lower.
In terms of functionality, the key feature of this oscillator is how it visualizes volatility through the spacing of the dots. During periods of high market volatility, the shifts between red and green dots tend to occur more frequently and with greater disparity in their positioning along the oscillator’s axis. This indicates sharp price changes and high trading activity. Conversely, periods of market consolidation are characterized by fewer color changes and a more clustered arrangement of dots, reflecting less price movement and lower volatility.
Traders can leverage the insights from the ATR Oscillator with Dots to better understand the market's behavior. For instance, a tight clustering of dots around the zero line suggests a consolidation phase, where the price is relatively stable and may be preparing for a breakout. On the other hand, widely spaced dots alternating between red and green signify strong price movements, offering opportunities for traders to capitalize on trends or prepare for potential reversals.
Imagine a scenario where a trader is monitoring a currency pair in a fluctuating forex market. An observed increase in the frequency and gap of alternating red and green dots would suggest a rise in volatility, possibly triggered by economic news or events. This could be an optimal time for the trader to seek entry or exit points, aligning their strategy with the increased activity. Conversely, a reduction in the frequency and gap of dot changes could signal an impending consolidation phase, prompting the trader to adopt a more cautious approach or explore range-bound trading strategies.
Therefore, the ATR Oscillator with Dots not only simplifies the interpretation of volatility and price momentum through visual cues but also enriches the trader’s strategy by highlighting periods of high activity and consolidation. This tool can be crucial for making informed decisions, particularly in fast-moving or uncertain market conditions, and can be effectively paired with other indicators to confirm trends and refine trading tactics.
Relative Strength Universal
Relative strength is a ratio between two assets, generally it is a stock and a market average (index). RS implementation details are explained here .
This script automatically decides benchmark index for RS calculation based on market cap input values and input benchmark indices values.
Relative strength calculation:
"To calculate the relative strength of a particular stock, divide the percentage change over some time period by the percentage change of a particular index over the same time period". This indicator value oscillates around zero. If the value is greater than zero, the investment has been relatively strong during the selected period; if the value is less than zero, the investment has been relatively weak.
In this script, You can input market cap values and all are editable fields. If company market cap value is grater than 75000(Default value) then stock value will be compared with Nifty index. If company market cap is between 75000 and 25000 then stock value will be compared with midcap 150 to calculate RS. If marketcap is greater than 5000 and less than 25000 then RS will be calculated based on smallcap250. If marketcap is less than 5000 and greater than 500 then it will be compared with NIFTY_MICROCAP250
Garman-Klass-Yang-Zhang Volatility EstimatorThe Garman-Klass-Yang-Zhang Volatility Estimator (GKYZVE) is yet another attempt to robustly measure volatility, integrating intra-candle and inter-candle dynamics. It is an extension of the Garman-Klass Volatility Estimator (GKVE) incorporating insights from the Yang-Zhang Volatility Estimator (YZVE) . Like the YZVE, the GKYZVE holistically considers open, high, low, and close prices. The formula for GKYZ is:
GKYZVE = 0.5 * σ_HL² + * σ_CC² + σ_OC²
Where:
σ_HL² is the variance based on the high and low prices (σ_HL² = (high - low)² / (4 * math.log(2))), weighted at 0.5.
σ_CC² is the close-to-close variance (σ_CC² = (close - close)²), weighted at (2 ln 2) -1 for the logarithmic distribution of returns and emphasizing the impact of day-to-day price changes.
σ_OC² is the variance of the opening price against the closing price (σ_OC² = 0.5 * (open - close)²), weighted at 1.
The GKYZVE differs from the YZVE by using fixed weighing factors derived from theoretical calculations, leaning heavier into the assumption that returns are log-distributed.
This script also offers a choice for normalization between 0 and 1, turning the estimator into an oscillator for comparing current volatility to recent levels. Horizontal lines at user-defined levels are also available for clearer visualization. Both options are off by default.
References:
Garman, M. B., & Klass, M. J. (1980). On the estimation of security price volatilities from historical data. The Journal of Business, 53(1), 67-78.
Yang, D., & Zhang, Q. (2000). Drift-independent volatility estimation based on high, low, open, and close prices. The Journal of Business, 73(3), 477-492.
Volatility Estimator - YZ & RSThe Yang-Zheng Volatility Estimator (YZVE) integrates both intra-candle and inter-candle dynamics, such as overnight and weekend price changes, offering a more detailed analysis compared to traditional methods. The YZVE is proposed to improve over the standard deviation by accounting for the open, high, low, and close prices of trading periods, instead of only the close prices, and attempts to supplant the Parkinson's Volatility Estimator (PVE) by a also capturing inter-candle dynamics. The YZVE is calculated by this formula:
YZ Volatility Squared σ_YZ² = k * σ_o² + σ_rs² + (1 - k) * σ_c²
where k is a weighting factor that adjusts the emphasis between the overnight and close-to-close components, popularly estimated as:
k = 0.34 / (1.34 + (N+1) / (N-1))
where N is the lookback period. Optionally, users may opt to override this calculation with a specified constant (off by default). Next, the
Overnight Volatility Squared σ_o² = (log(O_t / C_(t-1)))²
measures the volatility associated with overnight price changes, from the previous candle's closing price C_(t-1) to the current candle's opening price O_t. It captures the market's reaction to news and events that occur outside of regular trading hours to reflect risk associated with holding positions over non-trading hours and gaps.
Next, the The Rogers-Satchell Volatility Estimator (RSVE) serves as an intermediary step in the computation of YZVE. It aggregates the logarithmic ratios between high, low, open, and close prices within each trading period, focusing on intra-candle volatility without assuming zero inter-candle drift as commonly implicitly assumed in other volatility models:
Rogers-Satchell Volatility Squared σ_rs² = (log(H_t / C_t) * log(H_t / O_t)) + (log(L_t / C_t) * log(L_t / O_t))
Finally,
Close-to-Close Volatility Squared σ_c² = (log(C_t / C_(t-1)))²
measures the volatility from the close of one candle to the close of the next. It reflects the typical candle volatility, similar to naive standard deviation.
This script also includes an option for users to apply the simpler RS Volatility exclusively, focusing on intraday price movements. Additionally, it offers a choice for normalization between 0 and 1, turning the estimator into an oscillator for comparing current volatility to recent levels. Horizontal lines at user-defined levels are also available for clearer visualization. Both are off by default.
References:
Yang, D., & Zhang, Q. (2000). Drift-independent volatility estimation based on high, low, open, and close prices. The Journal of Business, 73(3), 477-491.
Rogers, L.C.G., & Satchell, S.E. (1991). Estimating variance from high, low and closing prices. Annals of Applied Probability, 1(4), 504-512.
Parkinson's Volatility EstimatorThe Parkinson's Volatility Estimator (PVE) provides an alternative method for assessing market volatility using the highest and lowest prices within a given period. Unlike traditional models that predominantly rely on closing prices, the PVE considers the full range of intra-candle price movements, thereby potentially offering a more comprehensive gauge of market volatility. The estimator is derived from the logarithm of the ratio of the high to low prices, squared and then averaged over the period of interest. This calculation is rooted in the assumption that the logarithmic high-to-low ratio represents a normalized measure of price movements, capturing both upward and downward volatility in a symmetric manner (Parkinson, 1980).
In this specific implementation, the estimator is calculated as follows:
Parkinson’s Volatility = (1/4 log(2)) * (1/n) * Σ from i=1 to n of (log(High_i/Low_i))^2
where n is the lookback period defined by the user, and High_i and Low_i are the highest and lowest prices at each interval i within that period. This formulation takes advantage of the logarithmic properties to scale the volatility measure appropriately, utilizing a factor of 1/4 log(2) to normalize the variance estimate (Parkinson, 1980).
This implementation includes options for output normalization between 0 and 1 and for plotting horizontal lines at specified levels, allowing the estimator to function like an oscillator to evaluate volatility relative to recent market regimes. Users can customize these features through script inputs, enhancing flexibility for various trading scenarios and improving its utility for real-time volatility assessments on the TradingView platform.
Reference:
Parkinson, M. (1980). The extreme value method for estimating the variance of the rate of return. The Journal of Business, 53(1), 61-65.
Unmitigated Liquidity Imbalances [AlgoAlpha]🎉 Introducing the Unmitigated Liquidity Imbalance Indicator by AlgoAlpha! 🎉
Dive into the depths of market analytics with our "Unmitigated Liquidity Imbalance" indicator. This tool harnesses unique algorithms to detect liquidity imbalances between bulls and bears, helping traders spot trends and potential entry and exit points with greater accuracy. 📈🚀
🔍 Key Features:
🌟 Advanced Analysis : Analyses candle direction and length to forecast market peaks and valleys.
🎨 Customizable Visuals : Tailor the chart with your choice of bullish green or bearish red to reflect different market conditions.
🔄 Real-Time Updates : Continuously updates to reflect live market changes.
🔔 Configurable Alerts : Set up alerts for key trading signals such as bullish and bearish reversals, as well as trend shifts.
📐 How to Use:
🛠 Add the Indicator : Add the indicator to your favourites and customize the settings to suite your needs.
📊 Market Analysis : Monitor the oscillator threshold; readings above 0.5 suggest bullish sentiment, while below 0.5 indicate bearish conditions. And reversal signals are displayed to show potential entry points.
🔔 Set Alerts : Enable notifications for reversal conditions or trend changes to seize trading opportunities without constant chart watching.
🧠 How It Works:
The core mechanism of the indicator is based on detecting changes in candlestick size and direction to identify bullish and bearish liquidity levels from the peak & valley indicator's logic. By comparing the length of a current candle to the previous one and checking the change in direction, it pinpoints moments where market sentiment could be shifting, indicating if the liquidity at that point is bullish or bearish. The script then looks at what percentage of the past few unmitigated levels are bullish or bearish based on a customizable lookback and determines the liquidity imbalance which can then be interpreted as trend.
Empower your trading with the Unmitigated Liquidity Imbalance indicator and navigate the markets with confidence and precision. 🌟💹
Happy trading, and may your charts be ever in your favour! 🥳✨
💎 Related Indicator
RMVH by mycroftlearnstotradeThe RMVH indicator combines several popular technical analysis tools to provide a comprehensive view of market conditions. It includes Relative Strength Index (RSI), Moving Average Convergence Divergence (MACD), Volume, and Smoothed Heiken Ashi.
RSI (Relative Strength Index):
The RSI measures the strength and speed of price movements. It oscillates between 0 and 100, with levels above 70 indicating overbought conditions and levels below 30 indicating oversold conditions.
MACD (Moving Average Convergence Divergence):
The MACD is a trend-following momentum indicator that shows the relationship between two moving averages of a security’s price. It consists of the MACD line (the difference between a short-term and a long-term moving average) and the signal line (a moving average of the MACD line). The MACD histogram represents the difference between the MACD line and the signal line.
Volume:
The volume displays the total trading volume over a specified period. It helps traders gauge the strength or weakness of price movements. Typically, high volume accompanies strong price moves, while low volume may signal a lack of conviction in the market.
Smoothed Heiken Ashi:
The Smoothed Heiken Ashi is a variation of Japanese candlestick charts that aims to filter out market noise and highlight trends more effectively. It is calculated based on the open, high, low, and close prices, resulting in smoother candlesticks compared to traditional candlestick charts.
Usage:
Traders can use the RMVH indicator to identify potential trend reversals, overbought or oversold conditions, and divergence between price and momentum. Additionally, the volume component can help confirm the strength of price movements, while the Smoothed Heiken Ashi can provide a clearer visualization of trends.
Bullish signals may occur when the RSI and MACD indicate oversold conditions, accompanied by high volume and rising Smoothed Heiken Ashi values. Conversely, bearish signals may occur when the RSI and MACD indicate overbought conditions, accompanied by high volume and declining Smoothed Heiken Ashi values.
Note:
While the RMVH indicator combines multiple technical analysis tools, traders should exercise caution and use additional analysis to confirm signals before making trading decisions. No indicator is foolproof, and market conditions can change rapidly.
Hybrid Overbought/Oversold OverlayIntroduction
This is a new representation of my well-known oscillator Hybrid Overbought/Oversold Detector overlaid on the chart. The script utilizes the following 12 different oscillators to bring forth a new indicator which I call it Hybrid OB/OS .
Utilized Oscillators
The utilized oscillators here are:
Bollinger Bands %B
Chaikin Money Flow (CMF)
Chande Momentum Oscillator (CMO)
Commodity Channel Index (CCI)
Disparity Index (DIX)
Keltner Channel %K
Money Flow Index (MFI)
Rate Of Change (ROC)
Relative Strength Index (RSI)
Relative Vigor Index (RVI/RVGI)
Stochastic
Twiggs Money Flow (TMF)
The challenging part of utilizing mentioned oscillators was that some of their formulas range are not similar and some of them does not have a mathematical range at all. So I used a normalization function to normalize all their output values to (0, 100) interval.
Overbought/Oversold Levels Calculation
I noticed that the levels which considered as OB/OS level by various traders for each of the utilized oscillators are so different, e.g., many traders consider 30 as OS level and 70 as OB level for RSI and some others take 20 and 80 as the levels, or some traders consider 20 and 80 as OS/OB levels for Stochastic oscillator. Also these levels could be different on different assets, e.g., OB/OS levels for CCI on EURUSD chart might be 80 and 20 while the levels on BTCUSDT chart might be 75 and 25, and so on.
So I decided to make a routine to automate the calculation of these levels using historical data. By this feature, my indicator would calculate the corresponding levels for the oscillators on current chart and then decide about the overbought/oversold situation of each one, which leads to a more accurate Hybrid OB/OS indication.
As the result, if all 12 individual oscillators say it's overbought/oversold, the Hybrid OB/OS shows 100% overbought/oversold, vice versa, if none of them say it's overbought/oversold, the Hybrid OB/OS shows 0, and so on.
The Overlaying Oscillator Problem!
A programming-related challenge here was that Pine Script assigns two separate spaces to the oscillators and the overlaid indicators, and the programmers are limited to use just one of them in each of their codes.
Knowing this, I was forced to simulate the oscillator space on the chart and display my oscillator as a diagram somehow. Of course it won't be as nice as the oscillator itself, because the relation between the main chart bars and the oscillator bars could not be obtained, but it's better than nothing!
Settings and Usage
The indicator settings contain some options about the calculations, the diagram display and the signals appearance. By default they are fine, but you could change them as you prefer.
This indicator is better to be used alongside other indicators as a confirmation (specially in counter-trend strategies I believe). Also it generates an external signal which you could use it in your own designed indicators as well.
Feel free to test it and also the former form of the Hybrid OB/OS . Good Luck!
Multi Timeframe ATR IndicatorThe Average True Range (ATR) indicator is a technical analysis tool used to measure market volatility. The ATR indicator is designed to capture the degree of price movement or price volatility over a specified period of time. It does this by calculating the true range for each bar or candlestick on a chart and then taking an average of these true range values over a set period.
In the provided Pine Script code, the ATR indicator is being calculated for two different timeframes, which allows traders to compare volatility across different periods. The script includes user-defined inputs for the length of the ATR calculation and the type of smoothing (RMA or SMA) to be applied to the true range values. The 'smoothingFunc' function within the script determines whether to use the RMA (Relative Moving Average) or SMA (Simple Moving Average) based on the user's selection.
The true range for each bar is calculated as the maximum of the following three values: the difference between the current high and low, the absolute value of the difference between the current high and the previous close, and the absolute value of the difference between the current low and the previous close. This calculation is designed to ensure that gaps and limit moves are properly accounted for in the volatility measurement.
The script then uses the 'smoothingFunc' to calculate the ATR values for the two timeframes, and these values are plotted on the chart as two separate lines, allowing traders to visually assess the volatility levels.
Overall, this custom ATR indicator is a versatile tool for traders who wish to analyse market volatility and compare it across different timeframes, potentially aiding in making more informed trading decisions based on the prevailing market conditions.
UM-Relative Strength Index with Trending EMA and Fill
Description
This is a different take on the traditional RSI - Relative Strength Index. This indicator turns the RSI line green when above 50 and red when below 50 making directional changes highly visual. Additionally, an exponential Moving Average is drawn of the RSI. The EMA is green when trending higher and red when trending lower. The area between the RSI and EMA lines are green when the RSI is above the RSI EMA and red when the RSI is below the EMA.
About
The RSI by itself is a good tool to determine trend with the colors. It can also be used to determined overbought and oversold extremes. The EMA of the RSI is a smoothing technique. The indicator can also be used to determine trend with the directional color changes.
Recommended Usage
I look for crossovers; bullish crossovers when the RSI crosses above the EMA AND the RSI crosses above 50. A bearish crossover is when the RSI crosses down through the EMA AND crosses below 50. It can also be used for trade confirmation; for example if the RSI EMA is green consider staying long. The indicator works on any timeframe and any security. I use it on smaller timeframes, 3 minute, 1 hour, and 3 hour, to better time entries/exits.
Default settings
The defaults are the author's preferred settings:
- RSI period is 10 using the open, high, low, and close for calculation. The additional data points using the OHLC give smoother effect.
- The EMA used by default is 34.
All parameters and colors are user-configurable.
Alerts
Alerts can be set on the indicator itself and/or alert on color changes of the EMA.
Helpful Hints:
Look for positive or negative crossovers.
Look for crosses above or below 50
Look for RSI divergences, for example if a security hits a new high, the RSI does not, this a sign of subtle weakness.
Draw trend lines on the RSI line. A violation of a recent trend line may indicate a change of trend for the security.
Bayesian Bias OscillatorWhat is a Bayes Estimator?
Bayesian estimation, or Bayesian inference, is a statistical method for estimating unknown parameters of a probability distribution based on observed data and prior knowledge about those parameters. At first , you will need a prior probability distribution, which is a prior belief about the distribution of the parameter that you are interested in estimating. This distribution represents your initial beliefs or knowledge about the parameter value before observing any data. Second , you need a likelihood function, which represents the probability of observing the data given different values of the parameter. This function quantifies how well different parameter values explain the observed data. Then , you will need a posterior probability distribution by combining the prior distribution and the likelihood function to obtain the posterior distribution of the parameter. The posterior distribution represents the updated belief about the parameter value after observing the data.
Bayesian Bias Oscillator
This tool calculates the Bayes bias of returns, which are directional probabilities that provide insight on the "trend" of the market or the directional bias of returns. It comes with two outputs: the default one, which is the Z-Score of the Bayes Bias, and the regular raw probability, which can be switched on in the settings of the indicator.
The Z-Score output value doesn't tell you the probability, but it does tell you how much of a standard deviation the value is from the mean. It uses both probabilities, the probability of a positive return and the probability of a negative return, which is just (1 - probability of a positive return).
The probability output value shows you the raw probability of a positive return vs. the probability of a negative return. The probability is the value of each line plotted (blue is the probability of a positive return, and purple is the probability of a negative return).
