Squeeze Momentum Oscillator [AlgoAlpha]🎉📈 Introducing the Squeeze Momentum Oscillator by AlgoAlpha 📉🎊
Unlock the secrets of market dynamics with our innovative Squeeze Momentum Oscillator! Crafted for those who seek to stay ahead in the fast-paced trading environment, this tool amalgamates critical market momentum and volatility indicators to offer a multifaceted view of potential market movements. Here's why it's an indispensable part of your trading toolkit:
Key Features:
🌈 Customizable Color Schemes: Easily distinguish between bullish (green) and bearish (red) momentum phases for intuitive analysis.
🔧 Extensive Input Settings: Tailor the oscillator lengths for both Underlying and Swing Momentum to match your unique trading approach.
📊 Dedicated Squeeze Settings: Leverage precise volatility insights to identify market squeeze scenarios, signaling potential breakouts or consolidations.
🔍 Advanced Divergence Detection: Utilize sophisticated algorithms to detect and visualize both bullish and bearish divergences, pointing towards possible market reversals.
📈 Hyper Squeeze Detection: Stay alert to high-momentum market movements with our hyper squeeze feature, designed to extremely suppressed market volatility.
🔔 Comprehensive Alert System: Never miss a trading opportunity with alerts for momentum changes, squeeze conditions, and more.
Quick Guide to Using the Squeeze Momentum Oscillator:
🛠 Add the Indicator: Add the indicator to your favourites. Adjust the oscillator and squeeze settings to suit your trading preferences.
📊 Market Analysis: Keep an eye on the squeeze value and momentum z-score for insights into volatility and market direction. Hyper Squeeze signals are your cue for high momentum trading opportunities.
🔔 Alerts: Configure alerts for shifts in underlying and swing momentum, as well as entry and exit points for squeeze conditions, to capture market moves efficiently.
How It Works:
The Squeeze Momentum Oscillator by AlgoAlpha synergistically combines the principles of momentum tracking and market squeeze detection. By integrating the core logic of the Squeeze & Release indicator, it calculates the Squeeze Value (SV) through a comparison of the Exponential Moving Average (EMA) of the Average True Range (ATR) against the high-low price EMA. This SV is further analyzed alongside its EMA to pinpoint squeeze conditions, indicative of potential market breakouts or consolidations. In addition to this, the oscillator employs Hyper Squeeze Detection for identifying extremely low volatility. The momentum aspect of the oscillator evaluates the price movement relative to EMAs of significant highs and lows, refining these observations with a z-score normalization for short-term momentum insights. Moreover, the incorporation of divergence detection aids in identifying potential reversals, making this oscillator a comprehensive tool for traders looking to harness the power of volatility and momentum in their market analysis. The combination of the Squeeze & Release and the Momentum Oscillator allows traders to time their trades with more precision by entering when the market is in a squeeze and front running the volatility of a major move.
Elevate your trading strategy with the Squeeze Momentum Oscillator by AlgoAlpha and gain a competitive edge in deciphering market dynamics! 🌟💼 Happy trading!
Volatility
TrendVista Swing IndicatorOverview
The swing indicator is designed to offer traders a comprehensive analysis of market trends and volatility by integrating Bollinger Bands and the Average True Range (ATR). It aids in the visualization of price movements and volatility across multiple time frames, thereby providing insights into potential buy and sell opportunities.
Key Features
- Multitimeframe Analysis : By default, the indicator examines the market across the following time frames: 1 Day (1D), 4 Hours (4H), 1 Hour (1H), and 15 Minutes (15min). Users have the flexibility to modify these time frames to suit their trading strategy by adjusting the indicator's settings.
- Buy and Sell Timings : The indicator identifies optimal buy signals when the price drops below the lower Bollinger Band and subsequently re-enters the band's range. Additionally, a buy signal is generated during high volatility periods—signified by the ATR exceeding its 10-day average—helping traders spot potential liquidation points. Sell signals are tailored for traders looking to exit long positions rather than for initiating short positions.
- Bollinger Bands Phases : The indicator categorizes the market condition into three phases based on Bollinger Bands movement:
- Neutral Phase : When the closing price is within the Bollinger Bands' upper and lower limits.
- Bullish Phase : Signaled by the price closing above the upper Bollinger Band, suggesting an upward trend until the price closes below the middle band.
- Bearish Phase : Initiated when the price closes below the lower Bollinger Band, indicating a downtrend until the price closes above the middle band.
Users can opt to exclude the neutral phase from the analysis through the indicator's settings for a more focused view on bullish or bearish trends.
Indicator Customization
The swing indicator is versatile, allowing users to customize the time frames and phase visibility according to their preferences. This feature ensures that traders can tailor the indicator to match their specific analysis needs and trading strategies.
Considerations
- The signals provided by the swing indicator are not symmetrically designed for both buy and sell actions. The indicator primarily optimizes for identifying long positions, particularly in bull markets. The sell signals are intended for exiting existing long positions rather than for short selling.
Pivot Length BandsPivot Length Bands Indicator
Description:
The Pivot Length Bands indicator is designed to visualize price volatility based on pivot points and ATR-adjusted pivot points. I. These bands can help traders identify potential support and resistance levels and assess the current volatility of the market.
Inputs:
Swing Length: The length of the swing used to calculate the pivot points and average true range.
Pivot Length Left Hand Side: The number of candles to the left of the current pivot point to consider when calculating the pivot high and low.
Pivot Length Right Hand Side: The number of candles to the right of the current pivot point to consider when calculating the pivot high and low.
Usage:
Traders can use the bands as potential levels for placing stop-loss orders or profit targets.
The width of the bands adjusts dynamically based on the current volatility of the market.
Note:
This indicator is best used in conjunction with other technical analysis tools and should not be relied upon as a standalone trading signal.
EXAMPLE 1:
Entry:
Exit:
EXAMPLE 2:
Entry:
Exit:
MTF BB+KC Avg
Bollinger Bands (BB) are a widely used technical analysis created by John Bollinger in the early 1980’s. Bollinger Bands consist of a band of three lines which are plotted in relation to instrument prices. The line in the middle is usually a Simple Moving Average (SMA) set to a period of 20 days (The type of trend line and period can be changed by the trader; however a 20 day moving average is by far the most popular). This indicator does not plot the middle line. The Upper and Lower Bands are used as a way to measure volatility by observing the relationship between the Bands and price. Typically the Upper and Lower Bands are set to two standard deviations away from the middle line, however the number of standard deviations can also be adjusted in the indicator.
Keltner Channels (KC) are banded lines similar to Bollinger Bands and Moving Average Envelopes. They consist of an Upper Envelope above a Middle Line (not plotted in this indicator) as well as a Lower Envelope below the Middle Line. The Middle Line is a moving average of price over a user-defined time period. Either a simple moving average or an exponential moving average are typically used. The Upper and Lower Envelopes are set a (user-defined multiple) of a range away from the Middle Line. This can be a multiple of the daily high/low range, or more commonly a multiple of the Average True Range.
This indicator is built on AVERAGING the BB and KC values for each bar, so you have an efficient metric of AVERAGE volatility. The indicator visualizes changes in volatility which is of course dynamic.
What to look for
High/Low Prices
One thing that must be understood about this indicator's plots is that it averages by adding BB levels to KC levels and dividing by 2. So the plots provide a relative definition of high and low from two very popular indicators. Prices are almost always within the upper and lower bands. Therefore, when prices move up near the upper or lower bands or even break through the band, many traders would see that price action as OVER-EXTENDED (either overbought or oversold, as applicable). This would preset a possible selling or buying opportunity.
Cycling Between Expansion and Contraction
Volatility can generally be seen as a cycle. Typically periods of time with low volatility and steady or sideways prices (known as contraction) are followed by period of expansion. Expansion is a period of time characterized by high volatility and moving prices. Periods of expansion are then generally followed by periods of contraction. It is a cycle in which traders can be better prepared to navigate by using Bollinger Bands because of the indicators ability to monitor ever changing volatility.
Walking the Bands
Of course, just like with any indicator, there are exceptions to every rule and plenty of examples where what is expected to happen, does not happen. Previously, it was mentioned that price breaking above the Upper Band or breaking below the Lower band could signify a selling or buying opportunity respectively. However this is not always the case. “Walking the Bands” can occur in either a strong uptrend or a strong downtrend.
During a strong uptrend, there may be repeated instances of price touching or breaking through the Upper Band. Each time that this occurs, it is not a sell signal, it is a result of the overall strength of the move. Likewise during a strong downtrend there may be repeated instances of price touching or breaking through the Lower Band. Each time that this occurs, it is not a buy signal, it is a result of the overall strength of the move.
Keep in mind that instances of “Walking the Bands” will only occur in strong, defined uptrends or downtrends.
Inputs
TimeFrame
You can select any timeframe froom 1 minute to 12 months for the bar measured.
Length of the internal moving averages
You can select the period of time to be used in calculating the moving averages which create the base for the Upper and Lower Bands. 20 days is the default.
Basis MA Type
Determines the type of Moving Average that is applied to the basis plot line. Default is SMA and you can select EMA.
Source
Determines what data from each bar will be used in calculations. Close is the default.
StdDev/Multiplier
The number of Standard Deviations (for BB) or Multiplier (for KC) away from the moving averages that the Upper and Lower Bands should be. 2 is the default value for each indicator.
Custom spreadThis indictor allows you to plot the spread over an arbitrary period, which can be especially useful for futures and other instruments.
Inputs:
Expression : symbols for calculation and arithmetic operation
Period: from to period and timeframe
The output will show bars for the given period
Particularly useful for comparing two selected contracts on two futures
Kalman Hull Supertrend [BackQuant]Kalman Hull Supertrend
At its core, this indicator uses a Kalman filter of price, put inside of a hull moving average function (replacing the weighted moving averages) and then using that as a price source for the supertrend instead of the normal hl2 (high+low/2).
Therefore, making it more adaptive to price and also sensitive to recent price action.
PLEASE Read the following, knowing what an indicator does at its core before adding it into a system is pivotal. The core concepts can allow you to include it in a logical and sound manner.
1. What is a Kalman Filter
The Kalman Filter is an algorithm renowned for its efficiency in estimating the states of a linear dynamic system amidst noisy data. It excels in real-time data processing, making it indispensable in fields requiring precise and adaptive filtering, such as aerospace, robotics, and financial market analysis. By leveraging its predictive capabilities, traders can significantly enhance their market analysis, particularly in estimating price movements more accurately.
If you would like this on its own, with a more in-depth description please see our Kalman Price Filter.
2. Hull Moving Average (HMA) and Its Core Calculation
The Hull Moving Average (HMA) improves on traditional moving averages by combining the Weighted Moving Average's (WMA) smoothness and reduced lag. Its core calculation involves taking the WMA of the data set and doubling it, then subtracting the WMA of the full period, followed by applying another WMA on the result over the square root of the period's length. This methodology yields a smoother and more responsive moving average, particularly useful for identifying market trends more rapidly.
3. Combining Kalman Filter with HMA
The innovative combination of the Kalman Filter with the Hull Moving Average (KHMA) offers a unique approach to smoothing price data. By applying the Kalman Filter to the price source before its incorporation into the HMA formula, we enhance the adaptiveness and responsiveness of the moving average. This adaptive smoothing method reduces noise more effectively and adjusts more swiftly to price changes, providing traders with clearer signals for market entries or exits.
The calculation is like so:
KHMA(_src, _length) =>
f_kalman(2 * f_kalman(_src, _length / 2) - f_kalman(_src, _length), math.round(math.sqrt(_length)))
4. Integration with Supertrend
Incorporating this adaptive price smoothing technique into the Supertrend indicator further enhances its efficiency. The Supertrend, known for its proficiency in identifying the prevailing market trend and providing clear buy or sell signals, becomes even more powerful with an adaptive price source. This integration allows the Supertrend to adjust more dynamically to market changes, offering traders more accurate and timely trading signals.
5. Application in a Trading System
In a trading system, the Kalman Hull Supertrend indicator can serve as a critical component for identifying market trends and generating signals for potential entry and exit points. Its adaptiveness and sensitivity to price changes make it particularly useful for traders looking to minimize lag in signal generation and improve the accuracy of their market trend analysis. Whether used as a standalone tool or in conjunction with other indicators, its dynamic nature can significantly enhance trading strategies.
6. Core Calculations and Benefits
The core of this indicator lies in its sophisticated filtering and averaging techniques, starting with the Kalman Filter's predictive adjustments, followed by the adaptive smoothing of the Hull Moving Average, and culminating in the trend-detecting capabilities of the Supertrend. This multi-layered approach not only reduces market noise but also adapts to market volatility more effectively. Benefits include improved signal accuracy, reduced lag, and the ability to discern trend changes more promptly, offering traders a competitive edge.
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
Range Finder [UAlgo]🔶 Description:
The "Range Finder " indicator aims at identifying and visualizing price ranges within a specified number of candles. By utilizing the Average True Range (ATR) indicator and Simple Moving Average (SMA), it detects potential breakout conditions and tracks consecutive candles that remain within the breakout range. This indicator offers flexibility by allowing users to customize settings such as range length, method for determining range breaks (based on either candle close or wick), and visualization options for displaying range breaks on the chart.
🔶 Key Features
Identifying Ranges: The Range Finder automatically adapts to the market by continuously evaluating the Average True Range (ATR) and its Simple Moving Average (SMA). This helps in dynamically adjusting the range based on market volatility.
Range Length: Users can specify the number of candles to be used for constructing the range via the "Range Length" input setting. This allows for customization based on trading strategies and preferences.
Range Break Method: The indicator offers the flexibility to choose between two methods for identifying range breaks. Users can select between "Close" or "Wick" based on their preference for using the closing price or the highs and lows (including wicks) of candles for defining the breakout.
Show Range Breaks: This option enables visual representation of range breaks on the chart. When activated, labels with the letter "B" will appear at the breakout point, colored according to the breakout direction (upward breakouts in the chosen up range color and downward breakouts in the chosen down range color).
Range Color Customization: The indicator provides the ability to personalize the visual appearance of the range by selecting preferred colors for ranges indicating potential upward and downward breakouts.
🔶 Disclaimer
It's important to understand that the Range Finder indicator is intended for informational purposes only and should not be solely relied upon for making trading decisions. Trading financial instruments involves inherent risks, and past performance is not necessarily indicative of future results.
ZigZag With ATR Filter [vnhilton](OVERVIEW)
The typical ZigZag indicator, which connects pivot points (see TradingView's Help Center regarding their indicator Pivot Points High Low, for an in depth explanation on how they are calculated) with lines, except instead of a percentage threshold, it uses ATR which adjusts for volatility of the ticker you are viewing. The ZigZag indicator can therefore be used to help visualise price legs and trends on a usually noisy looking chart.
(FEATURES)
- Toggles for pivot point label contents such as the value, the trend, or nothing at all.
- ATR and pivot point periods.
- ATR multiplier minimum threshold to plot pivots and draw lines only when this threshold is met (helps eliminate small, perhaps insignificant price movements, to have a better focus on the overall trend).
- Show the last 2 to 499 ZigZag lines.
- Uptrend, downtrend and range colors for high and low pivot labels, text labels and lines, for both confirmed and real-time plots.
- Label size, and label styles for the high and low pivots.
- Customisable width and styles (Arrow Right, Dashed, Dotted, Solid) for the ZigZag line.
In the main chart picture, labels show both the pivot point value and the trend at that point. In the picture above, on the left shows only the pivot point value, the right shows only the trend.
Picture above shows just the label with 0 contents. Also notice the last recent line being blue instead of green. This is because the current bar hasn't finished so this line is currently live and not confirmed, so is subject to change. Keep in mind even if a pivot point is confirmed, it can be updated by a subsequent higher high/lower low.
Left chart shows a minimum ATR threshold multiplier of 1x; Right chart has 2x ATR minimum threshold. Notice the left chart highlights more price legs as more price legs satisfy a less strict threshold.
Fine-Tune Inputs: Fourier Smoothed Hybrid Volume Spread AnalysisUse this Strategy to Fine-tune inputs for the HSHVSA Indicator.
Strategy allows you to fine-tune the indicator for 1 TimeFrame at a time; cross Timeframe Input fine-tuning is done manually after exporting the chart data.
I suggest using " Close all " input False when fine-tuning Inputs for 1 TimeFrame. When you export data to Excel/Numbers/GSheets I suggest using " Close all " input as True , except for the lowest TimeFrame.
MEANINGFUL DESCRIPTION:
The Fourier Smoothed Hybrid Volume Spread Analysis (FSHVSA) Strategy/Indicator is an innovative trading tool designed to fuse volume analysis with trend detection capabilities, offering traders a comprehensive view of market dynamics.
This Strategy/Indicator stands apart by integrating the principles of the Discrete Fourier Transform (DFT) and volume spread analysis, enhanced with a layer of Fourier smoothing to distill market noise and highlight trend directions with unprecedented clarity.
This smoothing process allows traders to discern the true underlying patterns in volume and price action, stripped of the distractions of short-term fluctuations and noise.
The core functionality of the FSHVSA revolves around the innovative combination of volume change analysis, spread determination (calculated from the open and close price difference), and the strategic use of the EMA (default 10) to fine-tune the analysis of spread by incorporating volume changes.
Trend direction is validated through a moving average (MA) of the histogram, which acts analogously to the Volume MA found in traditional volume indicators. This MA serves as a pivotal reference point, enabling traders to confidently engage with the market when the histogram's movement concurs with the trend direction, particularly when it crosses the Trend MA line, signalling optimal entry points.
It returns 0 when MA of the histogram and EMA of the Price Spread are not align.
WHAT IS FSHVSA INDICATOR:
The FSHVSA plots a positive trend when a positive Volume smoothed Spread and EMA of Volume smoothed price is above 0, and a negative when negative Volume smoothed Spread and EMA of Volume smoothed price is below 0. When this conditions are not met it plots 0.
HOW TO USE THE STRATEGY:
Here you fine-tune the inputs until you find a combination that works well on all Timeframes you will use when creating your Automated Trade Algorithmic Strategy. I suggest 4h, 12h, 1D, 2D, 3D, 4D, 5D, 6D, W and M.
ORIGINALITY & USEFULNESS:
The FSHVSA Strategy is unique because it applies DFT for data smoothing, effectively filtering out the minor fluctuations and leaving traders with a clear picture of the market's true movements. The DFT's ability to break down market signals into constituent frequencies offers a granular view of market dynamics, highlighting the amplitude and phase of each frequency component. This, combined with the strategic application of Ehler's Universal Oscillator principles via a histogram, furnishes traders with a nuanced understanding of market volatility and noise levels, thereby facilitating more informed trading decisions.
DETAILED DESCRIPTION:
My detailed description of the indicator and use cases which I find very valuable.
What is the meaning of price spread?
In finance, a spread refers to the difference between two prices, rates, or yields. One of the most common types is the bid-ask spread, which refers to the gap between the bid (from buyers) and the ask (from sellers) prices of a security or asset.
We are going to use Open-Close spread.
What is Volume spread analysis?
Volume spread analysis (VSA) is a method of technical analysis that compares the volume per candle, range spread, and closing price to determine price direction.
What does this mean?
We need to have a positive Volume Price Spread and a positive Moving average of Volume price spread for a positive trend. OR via versa a negative Volume Price Spread and a negative Moving average of Volume price spread for a negative trend.
What if we have a positive Volume Price Spread and a negative Moving average of Volume Price Spread?
It results in a neutral, not trending price action.
Thus the Indicator/Strategy returns 0 and Closes all long and short positions.
In the next Image you can see that trend is negative on 4h, we just move Negative on 12h and Positive on 1D. That means trend/Strategy flipped negative .
I am sorry, the chart is a bit messy. The idea is to use the indicator/strategy over more than 1 Timeframe.
Use this Strategy to fine-tune inputs for the HSHVSA Indicator.
(Strategy allows you to fine-tune the indicator for 1 TimeFrame at a time; cross Timeframe Input fine-tuning is done manually after exporting the chart data)
I suggest using " Close all " input False when fine-tuning Inputs for 1 TimeFrame. When you export data to Excel/Numbers/GSheets I suggest using " Close all " input as True , except for the lowest TimeFrame. I suggest using 100% equity as your default quantity for fine-tune purposes. I have to mention that 100% equity may lead to unrealistic backtesting results. Be avare. When backtesting for trading purposes use Contracts or USDT.
Trend Analysis with Standard Deviation by zdmre This script analyzes trends in financial markets using standard deviation.
The script works by first calculating the standard deviation of a security's price over a specified period of time. The script then uses this standard deviation to identify potential trend reversals.
For example, if the standard deviation of a security's price is high, this could indicate that the security is overvalued and due for a correction. Conversely, if the standard deviation of a security's price is low, this could indicate that the security is undervalued and due for a rally.
The script can be used to analyze any security, including stocks, bonds, and currencies. It can also be used to analyze different time frames, such as daily, weekly, and monthly.
How to Use the Script
To use the script, you will need to specify the following parameters:
Time frame: The time frame you want to analyze.
Standard deviation: The standard deviation you want to use.
Once you have specified these parameters, the script will calculate the standard deviation of the security's price over the specified time frame. The script will then use this standard deviation to identify potential trend reversals.
#DYOR
Session LiquidityDescribes if markets are liquid enough for institutions to manipulate. Its often difficult to determine if markets will trend or chop, but by looking at how much volume we have at the open, we can determine of the session will be choppy or trendy, and take trades based on that.
Settings predefined for 1m timeframe on SPY. May work with other tickers, but I have not tested it out yet.
Designed for stocks(as of now, may update later)
ROC Since MorningThe "ROC Since Morning" indicator is designed for traders who wish to gauge the momentum of an asset from a specific time in the morning, allowing for a customizable analysis of pre-market and intraday movements. This indicator calculates the Rate of Change (ROC) from a user-defined hour, offering insights into how the price has moved since then.
How to Use:
Add the "ROC Since Morning" indicator to your chart.
Adjust the start hour input to your preferred time, considering pre-market hours or the official market opening time.
Analyze the ROC values to understand price movements and momentum since your specified start hour. A positive ROC indicates an upward price movement, while a negative ROC suggests downward movement.
Volume Quartile IndicatorThe Volume Quartile Indicator is a tool designed to analyze and classify trading volumes based on quartile levels, offering traders a visual means to assess market strength and momentum. This indicator calculates volume levels using a default length of 60 periods to determine the quartiles at 10%, 30%, 50%, 70%, and 90%. Each quartile range is represented by a specific color, providing a clear, visual representation of volume intensity relative to historical data.
Color-Coded Volume Strength: Volume strength is visually represented through a color-coded system for quick and intuitive analysis:
Red: Volume below the 10% level indicates very weak market activity.
Orange: Volume between 10% and 30% signifies weak market activity.
Gray: Volume in the 30% to 50% range represents medium activity with a weak bias.
Silver: Volume between 50% and 70% indicates medium activity with a strong bias.
Blue: Volume in the 70% to 90% range denotes strong market activity.
Green: Volume above the 90% level signifies very strong market activity.
Special Volume Markers: Yellow diamond markers highlight volumes that stand out due to their significance, providing traders with visual cues for potential market entry or exit points.
Q-Lines: The indicator draws q-lines at the 70%, 90%, and the midpoint between these two levels. The convergence of these q-lines suggests potential volatility in volume, which could significantly impact price movements.
The Volume Quartile Classification Indicator is atool for traders looking to incorporate volume analysis into their trading strategy.
Volume Liqidations [EagleVSniper]The Volume Liquidations Indicator is designed for traders who want to spot significant liquidation events in the cryptocurrency markets, particularly between spot and futures volumes. This powerful tool auto-detects the trading asset and compares the volume data from both spot and futures markets to highlight potential high-volume liquidation points that can significantly impact price movement. Raw source code owner - tartigradia
Features:
Auto-Detect Functionality: Automatically identifies the current trading asset, providing an option for manual selection for both spot and futures symbols.
Volume Comparison: Calculates the difference between futures and spot volumes within a user-defined timeframe, helping to identify liquidation events.
Customizable Parameters: Offers customizable options for multipliers, lookback periods, and timeframe selection to tailor the indicator to your trading strategy.
Visual Indicators: Displays liquidation volumes as color-coded columns, with green indicating potential long liquidations and red for short liquidations. It also highlights bars that exceed the high-volume threshold, providing a clear visual cue for significant liquidation events.
Spot and Futures Volume MA: Includes optional moving average plots for both spot and futures volumes, allowing for a deeper analysis of market trends.
Highlighting High-Volatility Candles: The indicator uniquely colors candles that reach a predefined volatility threshold, determined by the user-set multiplier. This functionality aims to spotlight moments of significant market volatility, providing traders with immediate visual cues.
Dynamic Ticker Selection: Seamlessly switches between auto and manual ticker selection, providing flexibility for all types of traders.
How to Use:
Setup: Configure the indicator to your preferences. You can choose between automatic or manual ticker selection, set the multiplier for the high-volume threshold, and define the lookback period for the moving average calculation.
Analysis: The indicator plots differences in volume between futures and spot markets as columns on your chart, color-coded to indicate the direction of potential liquidations.
Decision Making: Use the indicator to identify potential liquidation events. High-volume thresholds are highlighted, suggesting significant market movements. Combine this information with other analysis tools to make informed trading decisions.
VWAP SpiderThe VWAP Spider indicator enhances the conventional Volume Weighted Average Price (VWAP) analysis by anchoring it to the first candle and incorporating an extensive series of standard deviation (SD) lines, extending up to +8 SDs with additional half-step increments. This configuration provides a more suitable set of lines for identifying support and resistance, distinguishing it from existing VWAP and SD indicators. Its design, featuring color gradients for fills and distinct labels for each line, aims to improve the utility and user experience.
Optimal Timeframes:
It is recommended for use on weekly or monthly resolutions to ensure all price and volume history is included.
Distinctive Features:
The indicator includes a more extensive array of SD lines than typically found in VWAP indicators, enhancing the depth of market analysis.
The visual presentation is optimized with color gradients and clear labeling, facilitating ease of use and integration into trading strategies.
Practical Use of the VWAP Spider:
SD Lines as Support and Resistance : Observe the interactions between the price and the SD lines closely. These can serve as dynamic support and resistance indicators, influencing trading decisions.
Analyzing Historical Price Action : Investigate how the price has historically interacted with the SD lines. Identify which lines have frequently acted as support and resistance in the past, as they will often continue to be revisited.
Strategic Application : Leverage insights from the interactions between price and SD lines to fine-tune entry and exit points. For example, a rebound from an SD line may suggest a strong entry point, while breaching an SD line could indicate a potential exit.
This indicator is freely available and open-source on TradingView for all. It is designed to help traders enhance their market analysis and strategic decision-making.
Elastic Buy-Sell Volume Wighted SupertrendCredits: This uses Trading View's buy and sell volume script and the Super trend script.
Elastic Buy-Sell Volume Wighted Supertrend can be used like a traditional supertrend indicator however we do not have to arbitrarily choose a multiplier depending on the stock and time frame the code dynamically adjust the multiplier and this is described below.
The buy and sell ATR (Average True Range) play a crucial role in determining the levels for potential buy and sell signals in the market. These ATR values are calculated based on volume-weighted averages, providing insights into the strength of buying and selling pressures. By incorporating volume into the ATR calculation, the indicator can better adapt to market dynamics, as volume often reflects the intensity of price movements. Instead of using Volume as whole this uses up and down volume derived from lower time frames which is used to calculate buy and sell ATR.
The multiplier is a key factor in the Supertrend calculation, which adjusts the width of the trend bands. The multiplier in this indicator dynamically adjusts itself based on two key components: the ratio of the asset's Average True Range (ATR) to that of a broader market benchmark and the coefficient of variation (CV) of the True Range (TR). The ratio comparison provides a historical context of the asset's volatility relative to the wider market over a longer time frame, while the CV accounts for short-term fluctuations in volatility.
By comparing the asset's ATR to that of the benchmark, traders gain insights into the asset's historical volatility behavior. A higher multiplier suggests that the asset's volatility has historically exceeded that of the benchmark, indicating potentially larger price movements compared to the broader market. Conversely, a lower multiplier suggests the opposite.
The CV component measures short-term variability in the asset's volatility, ensuring that the multiplier adapts to both long-term trends and short-term fluctuations. This combined approach enables traders to make informed decisions, considering both historical volatility relative to the broader market and short-term variability. Ultimately, the dynamic multiplier enhances traders' ability to adjust their strategies effectively across various market conditions.
Overall, the use of buy and sell ATR, along with a dynamically adjusted multiplier, enhances the indicator's ability to identify trend directions and to use a dynamic stop loss level.
Realized volatility differentialAbout
This is a simple indicator that takes into account two types of realized volatility: Close-Close and High-Low (the latter is more useful for intraday trading).
The output of the indicator is two values / plots:
an average of High-Low volatility minus Close-Close volatility (10day period is used as a default)
the current value of the indicator
When the current value is:
lower / below the average, then it means that High-Low volatility should increase.
higher / above then obviously the opposite is true.
How to use it
It might be used as a timing tool for mean reversion strategies = when your primary strategy says a market is in mean reversion mode, you could use it as a signal for opening a position.
For example: let's say a security is in uptrend and approaching an important level (important to you).
If the current value is:
above the average, a short position can be opened, as High-Low volatility should decrease;
below the average, a trend should continue.
Intended securities
Futures contracts
Liquidity SpotterIndicator Setup:
The script sets up a TradingView indicator titled "Liquidity Spotter" with a short title "PWWTC LS". It's designed to overlay on the price chart (overlay=true).
Input Variables:
The script defines input variables that allow users to customize the behavior of the indicator:
atr_length: Length of the Average True Range (ATR) used in calculations.
volume_multiplier: Multiplier used to compare the volume of the current bar with the average volume.
range_multiplier: Multiplier used to calculate the range condition.
highlight_color: Color used to highlight bars when conditions are met.
Calculations:
The script calculates the ATR and average volume using the ta.atr and ta.sma functions provided by TradingView's Pine Script.
It sets the avg_range to the value of the ATR, essentially making it the same as atr_value.
Conditions:
The script checks several conditions based on the calculated values:
range_condition: Compares the range (high - low) of the current bar with the average range multiplied by the range multiplier.
volume_condition: Compares the volume of the current bar with the average volume multiplied by the volume multiplier.
range_volume_condition: Compares the ratio of range to volume with the ratio of average range to average volume.
Plotting:
Based on the conditions being met or not, the script sets the color of the price bars. If all conditions are met, the color of the bars will be set to highlight_color, otherwise, it will remain unchanged (na).
Overall, this script visually highlights price bars on the chart where specific conditions related to range, volume, and their ratio are met, potentially indicating trading opportunities.
TrippleMACDCryptocurrency Scalping Strategy for 1m Timeframe
Introduction:
Welcome to our cutting-edge cryptocurrency scalping strategy tailored specifically for the 1-minute timeframe. By combining three MACD indicators with different parameters and averaging them, along with applying RSI, we've developed a highly effective strategy for maximizing profits in the cryptocurrency market. This strategy is designed for automated trading through our bot, which executes trades using hooks. All trades are calculated for long positions only, ensuring optimal performance in a fast-paced market.
Key Components:
MACD (Moving Average Convergence Divergence):
We've utilized three MACD indicators with varying parameters to capture different aspects of market momentum.
Averaging these MACD indicators helps smooth out noise and provides a more reliable signal for trading decisions.
RSI (Relative Strength Index):
RSI serves as a complementary indicator, providing insights into the strength of bullish trends.
By incorporating RSI, we enhance the accuracy of our entry and exit points, ensuring timely execution of trades.
Strategy Overview:
Long Position Entries:
Initiate long positions when all three MACD indicators signal bullish momentum and the RSI confirms bullish strength.
This combination of indicators increases the probability of successful trades, allowing us to capitalize on uptrends effectively.
Utilizing Linear Regression:
Linear regression is employed to identify consolidation phases in the market.
Recognizing consolidation periods helps us avoid trading during choppy price action, ensuring optimal performance.
Suitability for Grid Trading Bots:
Our strategy is well-suited for grid trading bots due to frequent price fluctuations and opportunities for grid activation.
The strategy's design accounts for price breakthroughs, which are advantageous for grid trading strategies.
Benefits of the Strategy:
Consistent Performance Across Cryptocurrencies:
Through rigorous testing on various cryptocurrency futures contracts, our strategy has demonstrated favorable results across different coins.
Its adaptability makes it a versatile tool for traders seeking consistent profits in the cryptocurrency market.
Integration of Advanced Techniques:
By integrating multiple indicators and employing linear regression, our strategy leverages advanced techniques to enhance trading performance.
This strategic approach ensures a comprehensive analysis of market conditions, leading to well-informed trading decisions.
Conclusion:
Our cryptocurrency scalping strategy offers a sophisticated yet user-friendly approach to trading in the fast-paced environment of the 1-minute timeframe. With its emphasis on automation, accuracy, and adaptability, our strategy empowers traders to navigate the complexities of the cryptocurrency market with confidence. Whether you're a seasoned trader or a novice investor, our strategy provides a reliable framework for achieving consistent profits and maximizing returns on your investment.
Effort Versus ResultsThis indicator, named "Effort Versus Results" (CCB), is designed to visually highlight price bars on a TradingView chart based on user-defined criteria. The purpose of this indicator is to identify potential trading opportunities or signal areas of interest for further analysis.
Once the inputs are specified, the indicator calculates the ratio of the first ATR to the average volume and compares it to the product of the multiplier and the ratio of the second ATR to the average volume. If the calculated condition is met, indicating that the first ATR relative to volume is greater than the second ATR relative to volume multiplied by the specified multiplier, the indicator colors the corresponding price bars red.
By customizing the parameters, traders can adapt the indicator to suit their trading strategies, risk tolerance, and market conditions. The highlighted bars may signify potential areas of increased volatility or trading activity, prompting traders to further investigate potential trading opportunities. However, as with any technical indicator, it is essential to use this tool in conjunction with other analysis techniques and risk management strategies for informed decision-making.
The indicator utilizes three main inputs that users can customize:
1. **ATR Length 1 (`atr_length_1`)**: This parameter allows users to specify the length of the first Average True Range (ATR) period. ATR is a measure of market volatility and represents the average range of price movement over a specified period.
2. **ATR Length 2 (`atr_length_2`)**: Users can set the length of the second ATR period, allowing for comparison between two different ATR values.
3. **Volume Length (`volume_length`)**: This input enables users to define the length of the volume period. Volume is a measure of the number of shares or contracts traded during a given period and is often used to confirm price movements.
4. **Multiplier (`multiplier`)**: Users can specify a multiplier value to adjust the threshold for comparison between the two ATR values divided by volume. This parameter allows for flexibility in setting the sensitivity of the indicator.
Dynamic Bern TrailThis indicator will help you following price movements in trending or ranging markets. Within it's calculations it uses ATR, EMA with a smoothing effect. It includes a buffer zone to help determine where price may turn around and reverse or to identify when a breakout occurs by breaking through the ATR trail. You can customize and play around with several settings to adjust it for your asset. Adjustments that can be made besides visuals are ATR Length, ATR Multiplier, EMA Length, Smoothing Length and the Buffer Multiplier.
SVMKR_UT_Bot_HMA_UCS_LRSThis Pine Script code is a TradingView study script titled "SVMKR_UT_Bot_HMA_UCS_LRS". It combines two separate trading indicators: the UT Bot (Ultimate Trailing Stop Bot) and the UCS_LRS (Linear Regression Slope) indicator.
UT Bot (Ultimate Trailing Stop Bot):
The UT Bot is designed to provide buy and sell signals based on a trailing stop strategy.
It calculates the trailing stop level using the Average True Range (ATR) and Heikin Ashi candle signals if enabled.
Buy signals are generated when the price crosses above the trailing stop, while sell signals occur when the price crosses below the trailing stop.
Additionally, buy and sell signals are visually represented on the chart with corresponding labels and shapes.
The script also includes options to customize the sensitivity of the trailing stop and to color the bars based on buy or sell signals.
Hull Moving Average (HMA):
This section calculates and plots the Hull Moving Average, a type of moving average that reduces lag and improves smoothing compared to traditional moving averages.
It uses the weighted moving average (WMA) to compute the HMA, which helps to identify trend direction and potential reversal points.
UCS_LRS (Linear Regression Slope):
The UCS_LRS indicator calculates the linear regression slope of the closing prices over a specified period.
It then applies exponential smoothing to the slope values and calculates an average slope.
Buy signals are generated when the current slope is greater than the average slope and positive, indicating an uptrend.
Conversely, sell signals are generated when the current slope is less than the average slope and negative, suggesting a downtrend.
The linear regression slope and its average are plotted on the chart, allowing traders to visually identify trend strength and potential reversal points.
Overall, this combined script provides traders with a comprehensive set of tools for trend following and momentum trading strategies, integrating trailing stop analysis, moving average smoothing, and linear regression slope analysis into a single script for technical analysis on TradingView charts.
Trend AngleThe "Trend Angle" indicator serves as a tool for traders to decipher market trends through a methodical lens. It quantifies the inclination of price movements within a specified timeframe, making it easy to understand current trend dynamics.
Conceptual Foundation:
Angle Measurement: The essence of the "Trend Angle" indicator is its ability to compute the angle between the price trajectory over a defined period and the horizontal axis. This is achieved through the calculation of the arctangent of the percentage price change, offering a straightforward measure of market directionality.
Smoothing Mechanisms: The indicator incorporates options for "Moving Average" and "Linear Regression" as smoothing mechanisms. This adaptability allows for refined trend analysis, catering to diverse market conditions and individual preferences.
Functional Versatility:
Source Adaptability: The indicator affords the flexibility to select the desired price source, enabling users to tailor the angle calculation to their analytical framework and other indicators.
Detrending Capability: With the detrending feature, the indicator allows for the subtraction of the smoothing line from the calculated angle, highlighting deviations from the main trend. This is particularly useful for identifying potential trend reversals or significant market shifts.
Customizable Period: The 'Length' parameter empowers traders to define the observation window for both the trend angle calculation and its smoothing, accommodating various trading horizons.
Visual Intuition: The optional colorization enhances interpretability, with the indicator's color shifting based on its relation to the smoothing line, thereby providing an immediate visual cue regarding the trend's direction.
Interpretative Results:
Market Flatness: An angle proximate to 0 suggests a flat market condition, indicating a lack of significant directional movement. This insight can be pivotal for traders in assessing market stagnation.
Trending Market: Conversely, a relatively high angle denotes a trending market, signifying strong directional momentum. This distinction is crucial for traders aiming to capitalize on trend-driven opportunities.
Analytical Nuance vs. Simplicity:
While the "Trend Angle" indicator is underpinned by mathematical principles, its utility lies in its simplicity and interpretative clarity. However, it is imperative to acknowledge that this tool should be employed as part of a comprehensive trading strategy , complemented by other analytical instruments for a holistic market analysis.
In essence, the "Trend Angle" indicator exemplifies the harmonization of simplicity and analytical rigor. Its design respects the complexity of market behaviors while offering straightforward, actionable insights, making it a valuable component in the arsenal of both seasoned and novice traders alike.
