Blackrock Spot ETF Premium BTCUSD (COINBASE) V1I created an indicator that takes the spot BTC/USD pair from major exchanges and compares it to the Spot BTC/USD pair on Coinbase that institutions will use for their Spot ETFs.
Blackrock Spot ETF Premium BTCUSD (COINBASE)
I suspect we will see a new "Kimchi Premium" where the Spot ETF pressures from institutions will raise the Coinbase Bitcoin price by a factor of 10-50% premium to the other exchanges.
Naturally excess coins from other exchanges will flow into Coinbase to capture this.
This indicator should be good for some time until one of the other exchanges delist or stop using BTCUSD "spot" If it breaks it I will update it if I remember.
FederalXBT,
Oscillateurs
Hybrid EMA AlgoLearner⭕️Innovative trading indicator that utilizes a k-NN-inspired algorithmic approach alongside traditional Exponential Moving Averages (EMAs) for more nuanced analysis. While the algorithm doesn't actually employ machine learning techniques, it mimics the logic of the k-Nearest Neighbors (k-NN) methodology. The script takes into account the closest 'k' distances between a short-term and long-term EMA to create a weighted short-term EMA. This combination of rule-based logic and EMA technicals offers traders a more sophisticated tool for market analysis.
⭕️Foundational EMAs: The script kicks off by generating a 50-period short-term EMA and a 200-period long-term EMA. These EMAs serve a dual purpose: they provide the basic trend-following capability familiar to most traders, akin to the classic EMA 50 and EMA 200, and set the stage for more intricate calculations to follow.
⭕️k-NN Integration: The indicator distinguishes itself by introducing k-NN (k-Nearest Neighbors) logic into the mix. This machine learning technique scans prior market data to find the closest 'neighbors' or distances between the two EMAs. The 'k' closest distances are then picked for further analysis, thus imbuing the indicator with an added layer of data-driven context.
⭕️Algorithmic Weighting: After the k closest distances are identified, they are utilized to compute a weighted EMA. Each of the k closest short-term EMA values is weighted by its associated distance. These weighted values are summed up and normalized by the sum of all chosen distances. The result is a weighted short-term EMA that packs more nuanced information than a simple EMA would.
RSI with Close & Tail DivergencesRSI divergence is a cornerstone signal for both stock and cryptocurrency traders, renowned for its reliability.
The basis for measuring divergence can vary:
Historically, it's been determined by the candlestick's closing price.
However, a contemporary approach uses the tail values, specifically the high and low prices, of the candlestick.
Depending on the criteria selected, the resultant signals can be markedly different.
Our innovative indicator offers:
Divergence tracking based on the closing price of the candlestick.
Divergence tracking considering the candlestick's peak and trough values.
A unique convergence of both types of divergence signals.
With this tool, traders are empowered to make informed decisions, anchored in precise divergence cues.
This indicator boasts the following capabilities:
Displays divergence based on closing price, highs/lows, as well as a unique combined criterion.
Highlights pivot points.
Denotes divergence spots on the RSI chart with lines.
Offers a background color representation instead of labels.
RSI Screener Multi Timeframe [5ema]This indicator is the simple version of my indicator: RSI Screener and Divergence .
Only show table with values, signals at 5 custom timeframes.
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I reused some functions, made by (i believe that):
©paaax: The table position function.
@kingthies: The RSI divergence function.
@QuantNomad: The function calculated value and array screener for 40+ instruments.
I have commented in my code. Thanks so much!
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How it works:
1. Input :
Length of RSI => calculate RSI.
Upper/lower => checking RSI overbought/oversold.
Right bars / left bars => returns price of the pivot low & high point => checking divergence.
Range upper / lower bars => compare the low & high point => checking divergence.
Timeframe => request.security another time frame.
Table position => display screener table.
2. Input bool:
Regular Bearish divergence.
Hidden Bullish divergence .
Hidden Bearish divergence.
3. Basic calculated:
Make function for RSI , pivot low & high point of RSI and price.
Request.security that function for earch time frame.
Result RSI, Divergence.
4. Condition of signal:
Buy condition:
RSI oversold (1)
Bullish divergence (2).
=> Buy if (1) and (2), review buy (1) or (2).
Sell condition:
RSI overbought (3).
Bearish divergence (4).
=> Sell if (3) and (4), review sell (3) or (4).
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Table screener:
Time frame.
RSI (green - oversold, red - overbought)
Divergence (>> - regular bullish , << regular bearish , > - hidden bullish , < - hidden bearish ).
Signal (green ⦿ - Buy, red ⦿ - Sell, green 〇 - review buy, red 〇 - review sell).
- Regular Bearish divergence:
- Regular Bullish divergence:
- Regular Bullish divergence + RSI overSold
- Regular Bearish divergence + RSI overBought
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This indicator is for reference only, you need your own method and strategy.
If you have any questions, please let me know in the comments.
Coppock Curve w/ Early Turns [QuantVue]The Coppock Curve is a momentum oscillator developed by Edwin Coppock in 1962. The curve is calculated using a combination of the rate of change (ROC) for two distinct periods, which are then subjected to a weighted moving average (WMA).
History of the Coppock Curve:
The Coppock Curve was originally designed for use on a monthly time frame to identify buying opportunities in stock market indices, primarily after significant declines or bear markets.
Historically, the monthly time frame has been the most popular for the Coppock Curve, especially for long-term trend analysis and spotting the beginnings of potential bull markets after bearish periods.
The signal wasn't initially designed for finding sell signals, however it can be used to look for tops as well.
When the indicator is above zero it indicates a hold. When the indicator drops below zero it indicates a sell, and when the indicator moves above zero it signals a buy.
While this indicator was originally designed to be used on monthly charts of the indices, many traders now use this on individual equities and etfs on all different time frames.
About this Indicator:
The Coppock Curve is plotted with colors changing based on its position relative to the zero line. When above zero, it's green, and when below, it's red. (default settings)
An absolute zero line is also plotted in black to serve as a reference.
In addition to the classic Coppock Curve, this indicator looks to identify "early turns" or potential reversals of the Coppock Curve rather than waiting for the indicator to cross above or below the zero line.
Give this indicator a BOOST and COMMENT your thoughts!
We hope you enjoy.
Cheers!
TTP SuperTrend ADXThis indicator uses the strength of the trend from ADX to decide how the SuperTrend (ST) should behave.
Motivation
ST is a great trend following indicator but it's not capable of adapting to the trend strength.
The ADX, Average Directional Index measures the strength of the trend and can be use to dynamically tweak the ST factor so that it's sensitivity can adapt to the trend strength.
Implementation
The indicator calculates a normalised value of the ADX based on the data available in the chart.
Based on these values ST will use different factors to increase or reduce the factor use by ST: expansion or compression.
ST expansion vs compression
Expanding the ST would mean that the stronger a trends get the ST factor will grow causing it to distance further from the price delaying the next ST trend flip.
Compressing the ST would mean that the stronger a trends get the ST factor will shrink causing it to get closer to the price speeding up the next ST trend flip.
Features
- Alerts for trend flip
- Alerts for trend status
- Backtestable stream
- SuperTrend color gets more intense with the strength of the trend
Momentum Probability Oscillator [SS]This is the momentum based probability indicator.
What it does?
This takes the average of MFI, Stochastics and RSI and plots it out as an independent oscillator.
It then tracks bullish vs bearish instances. Bullish is defined as a greater move from open to high than open to low and inverse for bearish.
It stores this data and these averages and plots these levels as a graph.
The graph depicts the max bullish values at the top, the min bearish values at the bottom and the averages in between:
It will plot the average "threshold" value in yellow:
The threshold value is key. A ticker trading above the threshold is generally bullish. Below is bearish.
The threshold value frequently acts as support and resistance levels (see below):
Resistance:
Support:
The indicator also shows you the amount of time a ticker has spent in each region, over a defined lookback period (defaulted to 500):
When you see that cumulatively, more time has been spent in a bullish range or a bearish range, it can help you ascertain the prevailing sentiment at that time.
The indicator will also calculate the average price range based on the underlying oscillator value. It does this through use of ATR based techniques, as its not usually possible to calculate a price from an oscillator:
This is intended as a general reference and not a precise target, as it is using ATR as opposed to the actual technical value itself.
As this is an oscillator, you can use it to look for divergences as well. The advantage to having it formulated in this way is:
a) You get the power of all 3 indicators (stochastics, MFI and RSI) in one and
b) You are adding context to the underlying technical reading. The indicator is plotting out the average, max and min ranges for the selected ticker and performing assessments based on these ranges that add context to the current PA.
You also have the ability to see the specific technical levels associated with each specific technical indicator. If you open up the settings menu and select "Show Table", this will appear:
This will show you the exact values of each of the technicals the indicator is using in its range assessment.
And that is basically the bulk of the indicator!
I use this predominately on the smaller timeframes, especially when there is a lot of chop, to ascertain the overall sentiment.
I also will reference it on the 1 hour to see what the prevailing sentiment is and whether the stock is at an area of technical resistance or support. For example, here is what I referenced on SPY today:
QUICK NOTE:
It works best with RTH (regular trading hours) turned on and ETH (extended trading hours) turned off!
That's it!
Hopefully you like it and leave your comments and suggestions below!
Swing Point Oscillator with Trend Filter [Quantigenics]The "Swing Point Oscillator with Trend Filter" is a sophisticated trading oscillator designed to enhance trading decisions by adapting to market conditions. Oscillators typically signal overbought/oversold market states, often yielding false signals in strong trends. This trend indicator addresses this by implementing a 'Trend Filter' which changes color in strong trends, alerting traders to avoid typical oscillator reversals. In strong trends (when the trend Filter is red), mid-high or mid-low levels can be used for pullback entries. In more neutral markets (when the trend Filter is close to blue), extreme high and low levels (top and bottom) can be used, as a true 'over bought / over sold' oscillator. The oscillator combines components of the Stochastic Oscillator and the CCI, then normalizes the result, providing a unique, adaptive signal. The color-coded lines and Trend Filter offer clear visual cues, making this a comprehensive tool for various market scenarios.
Caution: Always use the indicator in conjunction with other tools and analysis methods to confirm trading decisions. Avoid trading solely based on this indicator.
GOLD 4HR
CL1! 4HR
How to Use:
Swing Point Oscillator: Displays the momentum of the price relative to its recent high and low.
Trend Filter: Highlights the general direction of the market trend.
Zones: Visual representation to categorize oscillator values (Up Zone and Down Zone).
Interpretation:
Oscillator:
When the oscillator moves upward and approaches or enters the Up Zone, it indicates increasing bullish momentum.
When the oscillator moves downward and approaches or enters the Down Zone, it suggests increasing bearish momentum.
Values near the middle (around zero) often indicate indecision or consolidation in the market.
Trend Filter:
A trend filter line above the Mid-High or below the Mid-Low suggests a strong trend.
When the trend filter is between the Mid-High and Mid-Low, it might indicate a weaker or sideways trend.
Its color will change based on its position relative to the zones. For instance, it turns red when indicating a stronger trend.
Zones:
Up Zone: The area between the Top Line and the Mid-High. Indicates strong bullish momentum when the oscillator is within this zone.
Down Zone: The area between the Mid-Low and the Bottom Line. Indicates strong bearish momentum when the oscillator is in this zone.
Trading Tips:
Bullish Scenario: Consider long positions when the oscillator is rising, and the trend filter indicates a strong upward trend.
Bearish Scenario: Consider short positions when the oscillator is falling, and the trend filter indicates a strong downward trend.
Heikin-Ashi Rolling Time Decay Volume OscillatorThe indicator calculates a time-decayed moving sum of volume data for both bullish (green) and bearish (red) candles. It then generates a volume share oscillator as a smoothed and weighted (time-decayed) moving sum of bullish volume (positive share) or bearish volume (negative share) relative to the total volume.
The volume share is displayed as an area chart with gradient fills representing overbought and oversold regions. Additionally, an Arnaud Legoux Moving Average (ALMA) of the volume oscillator is plotted on the chart.
Trend Momentum and Price Control :
This indicator serves as a powerful tool for traders to gauge trend momentum and identify which side, bulls or bears, is controlling price movements. When the volume oscillator trends strongly in the green territory, it suggests that bulls are in control of price movements, indicating a potential uptrend. Conversely, when the oscillator tilts into the red, it indicates bearish dominance and a potential downtrend. With the incorporation of ALMA for smoothing, this indicator becomes an essential tool for traders and analysts navigating the dynamics of traded assets.
Source Candles :
This indicator is designed to work with Heiken Ashi or Japanese candlesticks to discern candle bias, whether it's red or green. Heiken Ashi tends to produce red candles during downtrends and green candles during uptrends, providing a clearer trend indication. In contrast, traditional candlesticks alternate colors regardless of the dominant price direction. Users can select between "Heikin-Ashi Candles" and regular "Japanese Candles" as the source for price direction."
A time decay cumulative sum, also known as a weighted moving sum or exponentially weighted moving sum, offers several advantages when it comes to determining market dynamics compared to other methods:
Responsive to Recent Data: Time decay cumulative sum gives more weight to recent data points and gradually reduces the impact of older data. This responsiveness is crucial in rapidly changing market conditions where recent price and volume information is more relevant for analysis.
Adaptive to Market Volatility : It adapts to changes in market volatility. When markets are highly volatile, it places more emphasis on recent data to reflect the current market environment accurately. Conversely, during calmer periods, it considers older data less important.
Effective for Identifying Turning Points : Time decay cumulative sums are particularly effective at identifying turning points in market dynamics. They can indicate shifts from bullish to bearish sentiment and vice versa, providing early signals of potential trend reversals.
Reduces Lag : Traditional cumulative sums or simple moving averages can lag behind actual market changes, making them less effective for real-time decision-making. Time decay cumulative sums reduce this lag by giving more weight to recent events.
Dynamic Weighting: The weighting scheme can be adjusted to fit specific market dynamics or trading strategies. Traders can customize the decay rate or smoothing factor to align with their analysis goals and timeframes.
Improved Signal Clarity : The time decay cumulative sum can provide clearer and more precise signals for overbought and oversold conditions, as well as trend strength, due to its ability to emphasize recent relevant data.
In summary, a time decay cumulative sum is a valuable tool in determining market dynamics because it adapts to changing market conditions, reduces noise, and provides timely and accurate insights into trends, turning points, and the relative strength of bullish and bearish forces. Its responsiveness and adaptability make it an essential component of many technical analysis and trading strategies.
Support and Resistance Oscillator [CC]The Support and Resistance Oscillator is an experimental script I created to identify when the current price breaks a support or resistance line and reflect this value in an oscillator formula. This indicator uses a threshold to decide the dividing line between buying and selling points. Feel free to change the threshold or smoothing settings to see if you find anything better since this is so experimental. I'm double smoothing the difference between the indicator and its signal line to attempt to capture a combo of the price momentum combined with the general support and resistance levels. I have used dark colors for strong signals and lighter colors for normal signals and make sure to buy when the line turns green and sell when it turns red.
Let me know if there are any other scripts or indicators you would like to see me publish!
Velocity Acceleration Convergence Divergence Indicator [CC]I created the Velocity Acceleration Convergence Divergence Indicator, and it is quite a mouthful if I do say so. I based this script on my two previous scripts: Velocity Indicator and Velocity Acceleration Indicator . This acts like a typical MACD but is much faster with the responses. This indicator is created by finding the difference between the Velocity Indicator and Velocity Acceleration Indicator to determine the overall trend strength of the underlying stock. Like the other scripts, I coded the general buy and sell signals the same, so you would want to buy when the indicator crosses over above the zero midline and sell when it crosses below the zero midline. I have also used the same colors, so darker colors for strong signals and lighter colors for normal signals.
Please let me know if you would like me to publish another script or if you want something custom done!
HTF Oscillators RSI/ROC/MFI/CCI/AO - Dynamic SmoothingThe Interplay of Time Frames: A Balanced View
Navigating the markets often involves interpreting trends from multiple angles. The HTF Oscillators with Dynamic Smoothing indicator enables you to do just that. This tool provides the option to integrate smoothed oscillator readings from Higher Time Frames (HTF) into lower time frame charts, such as a 1-minute chart. By doing so, the indicator offers a balanced viewpoint that bridges the gap between micro and macro perspectives, helping you make informed decisions without losing sight of the broader market context.
Features
Multi-Oscillator Support
Choose from a range of popular oscillators like the Relative Strength Index (RSI), Rate of Change (ROC), Money Flow Index (MFI), Commodity Channel Index (CCI), and Awesome Oscillator (AO). These oscillators are commonly used as foundational building blocks in trading strategy scripts by traders worldwide. Switch effortlessly between them, depending on your trading strategy and requirements. To maintain consistency and a familiar user experience, our script adopts the same visual aesthetics that you'll find in Pine Script indicators on TradingView: a sleek purple line for the oscillator and a transparent band filling. These visual elements are not only pleasing to the eye but also widely appreciated by the trading community.
Dynamic Smoothing
The unique dynamic smoothing feature calculates a smoothing factor based on the ratio of minutes between the Higher Time Frame (HTF) and your current time frame. This provides a sleek and responsive oscillator line that still holds the weight of the longer trend. One of the significant advantages of this feature is user experience; when you change your time frame, the HTF-values in your settings will remain consistent. This ensures that you can easily switch between different time frames without losing the insights provided by your selected HTF.
Visual Aids
Visual cues are an essential part of any trading strategy. The indicator not only plots signals to mark overbought and oversold conditions based on the dynamically smoothed oscillator but also provides you with the flexibility to customize your visual experience. You have the option to toggle on/off the display of these signals depending on your specific needs. Additionally, bands can be displayed at overbought and oversold levels, along with a reference middle line. If you switch between different oscillators (available in the parameter settings), remember to manually adjust the bands in the input settings to ensure signals matches with the type of oscillator to your liking.
User-Friendly Settings
We've grouped related settings together, making it easier for you to find what you're looking for. Adjust the oscillator type, length of bars, smoothing settings, and more with just a few clicks.
Information Table
A standout feature of this indicator is the real-time information table, which displays the values of all selected oscillators based on your specified Higher Time Frame (HTF) settings. This can be particularly useful for traders who depend on multiple indicators for their decision-making process. The data presented in the table is synchronized with the HTF options you've configured in the input settings, allowing for a more efficient and quick scan of values from higher time frames.
Educational Corner: The Power of the Information Table and Customization
The table incorporated into this indicator isn't just eye-candy; it's a practical tool designed to elevate your trading strategy. It dynamically displays real-time values of various oscillators for the HTF you've chosen. This is an exemplary use of TradingView's scripting capabilities to blend multiple indicators into a single visual panel, streamlining your analysis and decision-making process.
But here's the best part: You're not limited to what we've created. With some basic understanding of TradingView's scripting language, Pine Script, you can easily adapt this table to include different indicators that suit your unique trading style. The logic in the script is modular and can serve as a foundation for your own customized trading dashboard. So, go ahead, get creative and explore new combinations of indicators that will help you excel in your trading endeavors!
You no longer have to toggle between different charts or indicators to get the information you need; it's all there in one neatly organized table. We encourage you to tap into this feature and make it your own, empowering your trading like never before.
By doing so, you not only gain a more comprehensive toolset, but you also engage more deeply with your trading strategy, understanding its nuances and, ultimately, making more informed decisions.
Conclusion
The HTF Oscillators with Dynamic Smoothing is a versatile and powerful tool that brings together the best of both worlds: the perspective of higher time frames and the granularity of shorter ones. Its feature-rich setting options and real-time information table make it a potential useful addition to your trading toolkit.
Remember, while this indicator offers a comprehensive and smarter way to look at the markets, it is not a foolproof method for predicting market movements. Always use it in conjunction with other analysis methods and risk management strategies.
Velocity Acceleration Indicator [CC]The Velocity Acceleration Indicator was created by Scott Cong (Stocks and Commodities Sep 2023, pgs 8-15). This is another personal variation of his formula designed to capture the overall velocity acceleration of the underlying stock by applying the velocity formula to the original indicator to find the acceleration of the underlying velocity. I changed a few things around and managed actually to get less lag and quicker signals for this version, so make sure you compare the Velocity Indicator script that I published yesterday. This indicator is also visually similar to a typical stochastic indicator but uses a different underlying calculation. This works well as a momentum indicator, and the values are completely unbounded, so the best ways to determine bullish or bearish trends is either by using a crossover or crossunder between the indicator and the midline or to buy or sell the indicator when it reaches a high or low point and starts to fall or rise respectively. I used the zero line for my default version to help determine the bullish or bearish trends. I have also included multiple colors to differentiate between very strong signals and normal signals, so very strong signals are darker in color, and normal signals use lighter colors. Buy when the line turns green and sell when it turns red.
Let me know if there are any other indicators or scripts you would like to see me publish! I will have some more new scripts in the next week or so.
Velocity Indicator [CC]The Velocity Indicator was created by Scott Cong (Stocks and Commodities Sep 2023, pgs 8-15). This is my variation of his formula designed to capture the overall velocity of the underlying stock by applying the typical velocity formula. This indicator is visually similar to a typical stochastic indicator but uses a different underlying calculation. This works well as a momentum indicator, and the values are completely unbounded, so the best ways to determine bullish or bearish trends is either by using a crossover or crossunder between the indicator and the midline or to buy or sell the indicator when it reaches a high or low point and starts to fall or rise respectively. For my default version, I used the zero line to help determine the bullish or bearish trends. I have also included multiple colors to differentiate between very strong signals and normal signals, so very strong signals are darker in color, and normal signals use lighter colors. Buy when the line turns green and sell when it turns red.
Let me know if there are any other indicators or scripts you would like to see me publish! I will have some more new scripts in the next week or so.
L&S Volatility Index Refurbished█ Introduction
This is my second version of the L&S Volatility Index, hence the name "Refurbished".
The first version can be found at this link:
The reason I released a separate version is because I rewrote the source code from scratch with the aim of both improving the indicator and staying as close as possible to the original concept.
I feel that the first version was somewhat exotic and polluted in relation to the indicator originally described by the authors.
In short, the main idea remains the same, however, the way of presenting the result has been changed, reiterating what was said.
█ CONCEPTS
The L&S Volatility Index measures the volatility of price in relation to a moving average.
The indicator was originally described by Brazilian traders Alexandre Wolwacz (Stormer) and Fábio Figueiredo (Vlad) from L&S Educação Financeira.
Basically, this indicator can be used in two ways:
1. In a mean reversion strategy, when there is an unusual distance from it;
2. In a trend following strategy, when the price is in an acceptable region.
As an indicator of volatility, the greatest utility is shown in first case.
This is because it allows identifying abnormal prices, extremely stretched in relation to an average, including market crashes.
How the calculation is done:
First, the distance of the price from a given average in percentage terms is measured.
Then, the historical average volatility is obtained.
Finally the indicator is calculated through the ratio between the distance and the historical volatility.
According to the description proposed by the creators, when the L&S Volatility Index is above 30 it means that the price is "stretched".
The closer to 100 the more stretched.
When it reaches 0, it means the price is on average.
█ What to look for
Basically, you should look at non-standard prices.
How to identify it?
When the oscillator is outside the Dynamic Zone and/or the Fixed Zone (above 30), it is because the price is stretched.
Nothing on the market is guaranteed.
As with the RSI, it is not because the RSI is overbought or oversold that the price will necessarily go down or up.
It is critical to know when NOT to buy, NOT to sell or NOT to do anything.
It is always important to consider the context.
█ Improvements
The following improvements have been implemented.
It should be noted that these improvements can be disabled, thus using the indicator in the "purest" version, the same as the one conceived by the creators.
Resources:
1. Customization of limits and zones:
2. Customization of the timeframe, which can be different from the current one.
3. Repaint option (prints the indicator in real time even if the bar has not yet closed. This produces more signals).
4. Customization of price inputs. This affects the calculation.
5. Customization of the reference moving average (the moving average used to calculate the price distance).
6. Customization of the historical volatility calculation strategy.
- Accumulated ATR: calculates the historical volatility based on the accumulated ATR.
- Returns: calculates the historical volatility based on the returns of the source.
Both forms of volatility calculation have their specific utilities and applications.
Therefore, it is worthwhile to have both approaches available, and one should not necessarily replace the other.
Each method has its advantages and may be more appropriate in different contexts.
The first approach, using the accumulated ATR, can be useful when you want to take into account the implied volatility of prices over time,
reflecting broader price movements and higher impact events. It can be especially relevant in scenarios where unexpected events can drastically affect prices.
The second approach, using the standard deviation of returns, is more common and traditionally used to measure historical volatility.
It considers the variability of prices relative to their average, providing a more general measure of market volatility.
Therefore, both forms of calculation have their merits and can be useful depending on the context and specific analysis needs.
Having both options available gives users flexibility in choosing the most appropriate volatility measure for the situation at hand.
* When choosing "Accumulated ATR", if the indicator becomes difficult to see, there are 3 possibilities:
a) manually adjust the Fixed Zone value;
b) disable the Fixed Zone and use only the Dynamic Zone;
c) normalize the indicator.
7. Signal line (a moving average of the oscillator).
8. Option to normalize the indicator or not.
9. Colors to facilitate direction interpretation.
Since the L&S is a volatility indicator, it does not show whether the price is rising or falling.
This can sometimes confuse the user.
That said, the idea here is to show certain colors where the price is relative to the average, making it easier to analyze.
10. Alert messages for automations.
Short Term IndeXThe Short-Term Index (STIX) is a simple market indicator designed to assess short-term overbought or oversold conditions in the stock market. Leveraging a combination of advancing and declining issues, STIX provides valuable insights into market sentiment and potential reversals. To enhance its interpretability and reveal the underlying trend with greater clarity, STIX has been refined through a Heiken-Ashi transformation, ensuring a smoother representation of market dynamics.
Calculation and Methodology:
stix = ta.ema(adv / (adv + dec) * 100, len)
STIX is calculated by dividing the difference between the sum of advancing issues (ADV) by the total number of issues traded (ADV + DEC). This quotient is multiplied by 100 to express the result as a percentage. The STIX index ranges from 0 to 100, where extreme values indicate potential overbought (mainly above 60) or oversold (mainly below 40) market conditions.
Heiken-Ashi Transformation:
By applying a Heiken-Ashi transformation to STIX, the indicator gains improved visual clarity and noise reduction. This transformation enhances the ability to identify trend shifts and potential reversal points, making it an even more valuable tool for traders and investors.
Utility and Use Cases:
-The Short-Term Index (STIX) offers a range of practical applications-
1. Overbought/Oversold Conditions: STIX provides a clear indication of short-term overbought or oversold conditions, helping traders anticipate potential market reversals.
2. Reversal Points: STIX can help pinpoint potential reversal points in short-term market trends, providing traders with opportunities to enter or exit positions.
3. Trend Analysis: By observing STIX values over time, traders can assess the strength and sustainability of short-term trends, aiding in trend-following strategies.
The Short-Term Index (STIX), enhanced by its Heiken-Ashi transformation, equips traders and investors with a tool for assessing short-term market conditions, confirming price movements, and identifying potential reversal points. Its robust methodology and refined presentation contribute to a more comprehensive understanding of short-term market dynamics, enabling traders to make well-informed trading decisions.
See Also:
- Other Market Breadth Indicators-
Trig-Log Scaled Momentum OscillatorTaylor Series Approximations for Trigonometry:
1. The indicator starts by calculating sine and cosine values of the close price using Taylor Series approximations. These approximations use polynomial terms to estimate the values of these trigonometric functions.
Mathematical Component Formation:
2. The calculated sine and cosine values are then multiplied together. This gives us the primary mathematical component, termed as the 'trigComponent'.
Smoothing Process:
3. To ensure that our indicator is less susceptible to market noise and more reactive to genuine price movements, this 'trigComponent' undergoes a smoothing process using a simple moving average (SMA). The length of this SMA is defined by the user.
Logarithmic Transformation:
4. With our smoothed value, we apply a natural logarithm approximation. Again, this approximation is based on the Taylor expansion. This step ensures that all resultant values are positive and offers a different scale to interpret the smoothed component.
Dynamic Scaling:
5. To make our indicator more readable and comparable over different periods, the logarithmically transformed values are scaled between a range. This range is determined by the highest and lowest values of the transformed component over the user-defined 'lookback' period.
ROC (Rate of Change) Direction:
6. The direction of change in our scaled value is determined. This offers a quick insight into whether our mathematical component is increasing or decreasing compared to the previous value.
Visualization:
7. Finally, the indicator plots the dynamically scaled and smoothed mathematical component on the chart. The color of the plotted line depends on its direction (increasing or decreasing) and its boundary values.
MACD HTF - Dynamic SmoothingEnhancing Your 1-Minute Trades with Dynamic HTF MACD Smoothing
Ever found yourself glued to a 1-minute chart, trying to catch every minor price movement, yet feeling like you're missing the bigger picture? Picture this: a solid MACD line on that chart, dynamically smoothed from a higher timeframe (HTF). This tool offers two significant benefits over other existing HTF MACD indicators:
User-Friendly Interface: No need to manually adjust input parameters every time you switch to a different timeframe.
Smooth Charting: Say goodbye to the zigzag lines that often result from plotting higher time frame resolutions on a lower time frame.
Understanding the MACD
The Moving Average Convergence Divergence (MACD) is one of the most widely used and trusted technical indicators in the trading community. Invented by Gerald Appel in the late 1970s, the MACD helps traders understand the relationship between two moving averages of a security's price. It consists of the MACD line (difference between a 12-period and 26-period Exponential Moving Average) and the Signal line (9-period EMA of the MACD line). When the MACD line crosses above the Signal line, it's viewed as a bullish signal, and vice versa. The difference between the two lines is represented as a histogram, providing insights into potential buy or sell opportunities.
Features of the Dynamic HTF MACD Smoothing Script
Time Frame Flexibility: Choose a higher timeframe to derive MACD values and apply dynamic smoothing to your current timeframe.
Multiple Moving Averages: The script supports various MA types like EMA, SMA, DEMA, TEMA, WMA and HMA.
Alerts: Get real-time alerts for MACD crossover and crossunder.
Customizability: From the type of moving average to its length, customize as per your strategy.
Visual Indicators: Clearly plots signals when MACD crossover or crossunder occurs for potential entries.
At last
A massive shoutout to all the wizards and generous contributors in the community! You inspire innovations and new tools, paving the path forward. Here's to a community where we learn and build together. Cheers to collective growth!
AI SuperTrend Clustering Oscillator [LuxAlgo]The AI SuperTrend Clustering Oscillator is an oscillator returning the most bullish/average/bearish centroids given by multiple instances of the difference between SuperTrend indicators.
This script is an extension of our previously posted SuperTrend AI indicator that makes use of k-means clustering. If you want to learn more about it see:
🔶 USAGE
The AI SuperTrend Clustering Oscillator is made of 3 distinct components, a bullish output (always the highest), a bearish output (always the lowest), and a "consensus" output always within the two others.
The general trend is given by the consensus output, with a value above 0 indicating an uptrend and under 0 indicating a downtrend. Using a higher minimum factor will weigh results toward longer-term trends, while lowering the maximum factor will weigh results toward shorter-term trends.
Strong trends are indicated when the bullish/bearish outputs are indicating an opposite sentiment. A strong bullish trend would for example be indicated when the bearish output is above 0, while a strong bearish trend would be indicated when the bullish output is below 0.
When the consensus output is indicating a specific trend direction, an opposite indication from the bullish/bearish output can highlight a potential reversal or retracement.
🔶 DETAILS
The indicator construction is based on finding three clusters from the difference between the closing price and various SuperTrend using different factors. The centroid of each cluster is then returned. This operation is done over all historical bars.
The highest cluster will be composed of the differences between the price and SuperTrends that are the highest, thus creating a more bullish group. The lowest cluster will be composed of the differences between the price and SuperTrends that are the lowest, thus creating a more bearish group.
The consensus cluster is composed of the differences between the price and SuperTrends that are not significant enough to be part of the other clusters.
🔶 SETTINGS
ATR Length: ATR period used for the calculation of the SuperTrends.
Factor Range: Determine the minimum and maximum factor values for the calculation of the SuperTrends.
Step: Increments of the factor range.
Smooth: Degree of smoothness of each output from the indicator.
🔹 Optimization
This group of settings affects the runtime performances of the script.
Maximum Iteration Steps: Maximum number of iterations allowed for finding centroids. Excessively low values can return a better script load time but poor clustering.
Historical Bars Calculation: Calculation window of the script (in bars).
TaLib RSI (ta-lib uses SMA)If you've ever been confused because Ta-Lib RSI differs from TradingView's RSI...
Look no further than here which instead of using the Rolling Moving Average, will instead use the Simple Moving Average
Gaussian Average Rate Oscillator
Within the ALMA calculation, the Gaussian function is applied to each price data point within the specified window. The idea is to give more weight to data points that are closer to the center and reduce the weight for points that are farther away.
The strategy calculates and compares two different Rate of Change (ROC) indicators: one based on the Arnaud Legoux Moving Average (ALMA) and the other based on a smoothed Exponential Moving Average (EMA). The primary goal of this strategy is to identify potential buy and sell signals based on the relationship between these ROC indicators.
Here's how the strategy logic works
Calculating the ROC Indicators:
The script first calculates the ROC (Rate of Change) of the smoothed ALMA and the smoothed EMA. The smoothed ALMA is calculated using a specified window size and is then smoothed further with a specified smoothing period. The smoothed EMA is calculated using a specified EMA length and is also smoothed with the same smoothing period.
Comparing ROCs:
The script compares the calculated ROC values of the smoothed ALMA and smoothed EMA.
The color of the histogram bars representing the ROC of the smoothed ALMA depends on its relationship with the ROC of the smoothed EMA. Green indicates that the ROC of ALMA is higher, red indicates that it's lower, and black indicates equality.
Similarly, the color of the histogram bars representing the ROC of the smoothed EMA is determined based on its relationship with the ROC of the smoothed ALMA, they are simply inversed so that they match.
With the default color scheme, green bars indicate the Gaussian average is outperforming the EMA within the breadth and red bars mean it's underperforming. This is regardless of the rate of average price changes.
Generating Trade Signals:
Based on the comparison of the ROC values, the strategy identifies potential crossover points and trends. Buy signals could occur when the ROC of the smoothed ALMA crosses above the ROC of the smoothed EMA. Sell signals could occur when the ROC of the smoothed ALMA crosses below the ROC of the smoothed EMA.
Additional Information:
The script also plots a zero rate line at the zero level to provide a reference point for interpreting the ROC values.
In summary, the strategy attempts to capture potential buy and sell signals by analyzing the relationships between the ROC values of the smoothed ALMA and the smoothed EMA. These signals can provide insights into potential trends and momentum shifts in the price data.
Golden Transform The Golden Transform Oscillator contains multiple technical indicators and conditions for making buy and sell decisions. Here's a breakdown of its components and what it's trying to achieve:
Strategy Setup:
The GT is designed to be plotted on the chart without overlaying other indicators.
Rate of Change (ROC) Calculation:
The Rate of Change (ROC) indicator is calculated with a specified period ("Rate of Change Length").
The ROC measures the percentage change in price over the specified period.
Hull Modified TRIX Calculation:
The Hull Modified TRIX indicator is calculated with a specified period ("Hull TRIX Length").
The Hull MA (Moving Average) formula, a modified WMA, is used to calculate a modified TRIX indicator, which is a momentum oscillator.
Hull MA Calculation:
A Hull Moving Average (Hull MA) is calculated as an entry filter.
Fisher Transform Calculation:
The Fisher Transform indicator is calculated to serve as a preemptive exit filter.
It involves mathematical transformations of price data to create an oscillator that can help identify potential reversals. The Fisher Transform is further smoothed using a Hull Moving Average (HMA).
Conditions and Signals:
Long conditions are determined based on crossovers between ROC and TRIX, as well as price relative the the MA. Short conditions are inversed.
Exit Conditions:
Exit conditions are defined for both long and short positions.
For long positions, the strategy exits if ROC crosses under TRIX, or if the smoothed Fisher Transform crosses above a threshold and declines. Once again, short conditions are the inverse.
Visualization and Plotting:
The script uses background colors for entry and shapes for exits to highlight different levels and conditions for the ROC/TRIX correlation.
It plots the Fisher Transform values and a lag trigger on the chart.
Overall, this script is a complex algorithm that combines multiple technical indicators and conditions to generate trading signals and manage positions in the financial markets. It aims to identify potential entry and exit points based on the interplay of the mentioned indicators and conditions.
OBV Oscillator Volume FilterOBV Oscillator Volume Filter
Introduction
The On-Balance Volume (OBV) is a widely-used technical indicator that aims to relate price and volume in trading. Price and volume are two of the most basic and yet crucial concepts in price movement. Together, they can reveal a lot about the instruments trends and the market's sentiment. This On Balance Volume (OBV) Oscillator incorporates enhanced features like a volume filter using a rolling window to detect outliers in accumulated volume, making it an advanced and more refined version of the standard OBV.
Interpreting the OBV Indicator
The primary function of the OBV is to accumulate volume. In simpler terms:
When the market closes higher than the previous candle, all of that candle's volume is considered 'up-volume'.
Conversely, when the market closes lower than the previous day, all of that candle's volume is considered 'down-volume'.
A rising OBV suggests that volume is being accumulated, indicating bullish market sentiment. A declining OBV, on the other hand, points to a bearish sentiment.
Features of the Script
1. Moving Averages Selection:
The script provides users with the option to select among six types of moving averages (EMA, DEMA, TEMA, SMA, WMA, HMA) to calculate the OBV. This feature offers flexibility and enables traders to choose an MA type they're most comfortable with or find the most effective.
2. Smoothing Option:
To reduce the inherent noise in the indicator, there's an option to apply smoothing. It uses a Simple Moving Average (SMA) to produce a clearer signal, making it easier for traders to interpret and respond to. If you don't want to use smoothing, just simply change the input length of smoothing to 1 in the settings.
3. Outlier Detection:
One of the standout features is the use of a rolling window to detect volume outliers. This ensures that the OBV only reacts to significant volume changes and isn't overly influenced by random spikes or drops. The volume filter is calculated based on a % of the highest OBV volume of X number of bars back. Users can adjust the time (# bars) and the sensitivity (%) of the volume filter. A longer timeperiode (# bars) and a higher % (sensitivity) in the settings result to less signals presented by the indicator.
4. Divergence Detection:
The script automatically highlights both regular and hidden divergences on the chart. Divergences can be a powerful signal of potential price reversals. This feature aids traders in spotting potential buy or sell opportunities based on divergences between price and OBV.
Regular Bullish Divergence: When the price makes lower lows, but the OBV makes higher lows.
Hidden Bullish Divergence: When the price makes higher lows, but the OBV makes lower lows.
Regular Bearish Divergence: When the price makes higher highs, but the OBV makes lower highs.
Hidden Bearish Divergence: When the price makes lower highs, but the OBV makes higher highs.
5. Alerts for Trend Reversals:
The script incorporates alerts that notify traders when the OBV indicates potential trend reversals. This feature can be instrumental in catching early entries or exits.
Disclaimer
It's crucial to understand that no single indicator should be used in isolation. To increase the probability of making accurate market predictions, always use the OBV Oscillator in conjunction with other indicators and tools. Remember that all trading involves risk, and it's possible to lose your invested capital. Always seek advice from a financial advisor before making any trading decisions. By enhancing the OBV with features like the volume filter, multiple MA types, smoothing, and divergence detection, this script becomes a potent tool in a trader's arsenal. Use it wisely, and always ensure to maintain proper risk management.
