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).
M-oscillator
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.
Gaussian Detrended ReversionThis strategy, titled "Gaussian Detrended Reversion Strategy," aims to identify potential price reversals using the customized Gaussian Detrended Price Oscillator (GDPO) in combination with smoothed price cycles.
Key Elements of the Strategy:
GDPO Calculation: The strategy first calculates the Detrended Price Oscillator (DPO) by comparing the close price to an Exponential Moving Average (EMA) of a specified period. This calculation helps identify short-term price cycles by detrending the price data.
Gaussian Smoothing: The DPO values are then smoothed using the Arnaud Legoux Moving Average (ALMA), applying a Gaussian smoothing technique. This smoothed version of the DPO is intended to filter out noise and provide a clearer picture of price trends.
Entry and Exit Conditions: The strategy defines conditions for both long and short entry points as well as exit points. It looks for specific crossover events between the smoothed GDPO and its lagged version. The strategy enters a long position when the smoothed GDPO crosses above the lag and is negative, and exits the long position when the smoothed GDPO crosses below the lag or the zero line. Similarly, the strategy enters a short position when the smoothed GDPO crosses below the lag and is positive, and exits the short position when the smoothed GDPO crosses above the lag or the zero line.
Visualization: The smoothed GDPO and its lag are plotted on the chart using distinct colors. The zero line is also displayed as a reference point. Additionally, the chart background changes color when the strategy enters a long or short position. Cross markers are also plotted at the crossover points as exit cues.
Overall, this strategy aims to capture potential price reversals using the GDPO and Gaussian smoothing, with specific entry and exit conditions to guide trading decisions.
EMA X Oscillator
This indicator combines elements of the Exponential Moving Average (EMA) crossover and Rate of Change (ROC), generating a solid simple tool for technical analysis.
Overall, this script creates an oscillator by calculating the Rate of Change between two Exponential Moving Averages (Fast and Slow) based on the chosen smoothing methods and lengths. The oscillator helps identify potential trends. It offers customization options for the types of smoothing and other parameters, making it versatile for various strategies.
Realized Profit & Loss [BigBeluga]The Realized Loss & Profit indicator aims to find potential dips and tops in price by utilizing the security function syminfo.basecurrency + "_LOSSESADDRESSES".
The primary objective of this indicator is to present an average, favorable buying/selling opportunity based on the number of people currently in profit or loss.
The script takes into consideration the syminfo.basecurrency, so it should automatically adapt to the current coin.
🔶 USAGE
Users have the option to enable the display of either Loss or Profit, depending on their preferred visualization.
Examples of displaying Losses:
Example of displaying Profits:
🔶 CONCEPTS
The concept aims to assign a score to the data in the ticker representing the realized losses. This score will provide users with an average of buying/selling points that are better to the typical investor.
🔶 SETTINGS
Users have complete control over the script settings.
🔹 Calculation
• Profit: Display people in profit on an average of the selected length.
• Loss: Display people in loss on an average of the selected length.
🔹 Candle coloring
• True: Color the candle when data is above the threshold.
• False: Do not color the candle.
🔹 Levels
- Set the level of a specific threshold.
• Low: Low losses (green).
• Normal: Low normal (yellow).
• Medium: Low medium (orange).
• High: Low high (red).
🔹 Z-score Length: Length of the z-score moving window.
🔹 Threshold: Filter out non-significant values.
🔹 Histogram width: Width of the histogram.
🔹 Colors: Modify the colors of the displayed data.
🔶 LIMITATIONS
• Since the ticker from which we obtain data works only on the daily timeframe, we are
restricted to displaying data solely from the 1D timeframe.
• If the coin does not have any realized loss data, we can't use this script.
Simple Angle MesurmentThis Pine Script indicator allows you to accurately measure the angle of any given source line on a chart. The angle is calculated based on the slope of the line, providing insights into the direction and steepness of the line's movement. By utilizing mathematical calculations and trigonometric functions, the indicator helps traders and analysts assess trends and make informed decisions.
QQE Weighted Oscillator [LuxAlgo]The QQE (Quantitative Qualitative Estimation) Weighted Oscillator improves on its original version by weighting the RSI based on the indications given by the trailing stop, requiring more effort in order for a cross with the trailing stop to occur.
🔶 USAGE
The QQE Weighted Oscillator is comprised of a smoothed RSI oscillator and a trailing stop derived from this same RSI. The oscillator can be used to indicate whether the market is overbought/oversold as well as an early indication of trend reversals thanks to the leading nature of the RSI.
Using higher Factor values will return a longer-term trailing stop.
Like with a regular RSI divergence can be indicative of a reversal.
Further weighting will control how much "effort" is required for the trailing stop to cross the RSI. For example. For example, an RSI above the trailing stop will require a higher degree of negative price variations in order for a potential cross to occur when using higher weights.
This can cause higher weightings to return more cyclical and smoother results.
🔶 SETTINGS
Length: Length of the RSI oscillator.
Factor: Multiplicative factor used for the trailing stop calculation.
Smooth: Degree of smoothness of the RSI oscillator.
Weight: Degree of weighting used for the RSI calculation.
Machine Learning Momentum Index (MLMI) [Zeiierman]█ Overview
The Machine Learning Momentum Index (MLMI) represents the next step in oscillator trading. By blending traditional momentum analysis with machine learning, MLMI delivers a potent and dynamic tool that aligns with the complexities of modern financial landscapes. Offering traders an adaptive way to understand and act on market momentum and trends, this oscillator provides real-time insights into market momentum and prevailing trends.
█ How It Works:
Momentum Analysis: MLMI employs a dual-layer analysis, utilizing quick and slow weighted moving averages (WMA) of the Relative Strength Index (RSI) to gauge the market's momentum and direction.
Machine Learning Integration: Through the k-Nearest Neighbors (k-NN) algorithm, MLMI intelligently examines historical data to make more accurate momentum predictions, adapting to the intricate patterns of the market.
MLMI's precise calculation involves:
Weighted Moving Averages: Calculations of quick (5-period) and slow (20-period) WMAs of the RSI to track short-term and long-term momentum.
k-Nearest Neighbors Algorithm: Distances between current parameters and previous data are measured, and the nearest neighbors are used for predictive modeling.
Trend Analysis: Recognition of prevailing trends through the relationship between quick and slow-moving averages.
█ How to use
The Machine Learning Momentum Index (MLMI) can be utilized in much the same way as traditional trend and momentum oscillators, providing key insights into market direction and strength. What sets MLMI apart is its integration of artificial intelligence, allowing it to adapt dynamically to market changes and offer a more nuanced and responsive analysis.
Identifying Trend Direction and Strength: The MLMI serves as a tool to recognize market trends, signaling whether the momentum is upward or downward. It also provides insights into the intensity of the momentum, helping traders understand both the direction and strength of prevailing market trends.
Identifying Consolidation Areas: When the MLMI Prediction line and the WMA of the MLMI Prediction line become flat/oscillate around the mid-level, it's a strong sign that the market is in a consolidation phase. This insight from the MLMI allows traders to recognize periods of market indecision.
Recognizing Overbought or Oversold Conditions: By identifying levels where the market may be overbought or oversold, MLMI offers insights into potential price corrections or reversals.
█ Settings
Prediction Data (k)
This parameter controls the number of neighbors to consider while making a prediction using the k-Nearest Neighbors (k-NN) algorithm. By modifying the value of k, you can change how sensitive the prediction is to local fluctuations in the data.
A smaller value of k will make the prediction more sensitive to local variations and can lead to a more erratic prediction line.
A larger value of k will consider more neighbors, thus making the prediction more stable but potentially less responsive to sudden changes.
Trend length
This parameter controls the length of the trend used in computing the momentum. This length refers to the number of periods over which the momentum is calculated, affecting how quickly the indicator reacts to changes in the underlying price movements.
A shorter trend length (smaller momentumWindow) will make the indicator more responsive to short-term price changes, potentially generating more signals but at the risk of more false alarms.
A longer trend length (larger momentumWindow) will make the indicator smoother and less responsive to short-term noise, but it may lag in reacting to significant price changes.
Please note that the Machine Learning Momentum Index (MLMI) might not be effective on higher timeframes, such as daily or above. This limitation arises because there may not be enough data at these timeframes to provide accurate momentum and trend analysis. To overcome this challenge and make the most of what MLMI has to offer, it's recommended to use the indicator on lower timeframes.
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Information Entropy OscillatorHello Traders
This Trading Indicator / script is my interpritation of the use of shannons entropy in Trading, hope you find this usefull !!!
Information Entropy Oscillator :
In Physics, entropy is a concept and a measurable physical property that is most commonly associated with the state of disorder, randomness or uncertainty of a system. In the Thermodynamic field Entropy also describes how much energy is not available to do work, The more disordered a system and higher the entropy, the less of a system's energy is available to do work. This last definition is central to the idea of this trading idea, Briefly this is because the lower the information Entropy the “more predictable” is price movement which is characterized by a two states process up(h), and down(d) - (green and red candles), thus the more predictable a up or down move, Given the definition this also means more “energy” which can be thought of as the systems “predictive power” is available to do work, where work in this case to predict the likelihood of a trend continuation.
In Information Theory, the entropy of a random variable (A statistical term that describes either a discrete or continuous event with a respective (discrete or continuous) probability, where the latter is expressed via a CDF - cumulative distribution function) is the average level of "information", "surprise", or "uncertainty" inherent to the variable's possible outcomes. note : this is the definition for Entropy that this script is built upon
Formual Derivation :
Interpretations of Information Entropy Values (Polar approach)
when , …
H(x) = 0 Max-Information gain (purity of knowledge available)
H(x) = 1 No INformation gain, When both states probabilities are equal, i.e. H = T = 0.5, the function yields maximum uncertainty and therefore maximum entropy. This reflects
When Information gain is nearing 0, thus low, the script attempts to predict the proceeding trend direction, for example when entropy is low and all bars preceding the real market / time bars have all been positive and the real time bar closes as a red candle (close < yesterday's open) the script takes this as a high information gain signal, “predicting” a Bearish trend.
The Script Also comes with a Information Entropy heat map to plot entropy (inspired by Oppenheimer and Barbie lol), to see this turn off all candle plots, plots in the Chart settings, under the symbol header .
Normalized Adaptive Trend Lines [MAMA and FAMA]These indicators was originally developed by John F. Ehlers (Stocks & Commodities V. 19:10: MESA Adaptive Moving Averages). Everget wrote the initial functions for these in pine script. I have simply normalized the indicators and chosen to use the Laplace transformation instead of the hilbert transformation
How the Indicator Works:
The indicator employs a series of complex calculations, but we'll break it down into key steps to understand its functionality:
LaplaceTransform: Calculates the Laplace distribution for the given src input. The Laplace distribution is a continuous probability distribution, also known as the double exponential distribution. I use this because of the assymetrical return profile
MESA Period: The indicator calculates a MESA period, which represents the dominant cycle length in the price data. This period is continuously adjusted to adapt to market changes.
InPhase and Quadrature Components: The InPhase and Quadrature components are derived from the Hilbert Transform output. These components represent different aspects of the price's cyclical behavior.
Homodyne Discriminator: The Homodyne Discriminator is a phase-sensitive technique used to determine the phase and amplitude of a signal. It helps in detecting trend changes.
Alpha Calculation: Alpha represents the adaptive factor that adjusts the sensitivity of the indicator. It is based on the MESA period and the phase of the InPhase component. Alpha helps in dynamically adjusting the indicator's responsiveness to changes in market conditions.
MAMA and FAMA Calculation: The MAMA and FAMA values are calculated using the adaptive factor (alpha) and the input price data. These values are essentially adaptive moving averages that aim to capture the current trend more effectively than traditional moving averages.
But Omar, why would anyone want to use this?
The MAMA and FAMA lines offer benefits:
The indicator offers a distinct advantage over conventional moving averages due to its adaptive nature, which allows it to adjust to changing market conditions. This adaptability ensures that investors can stay on the right side of the trend, as the indicator becomes more responsive during trending periods and less sensitive in choppy or sideways markets.
One of the key strengths of this indicator lies in its ability to identify trends effectively by combining the MESA and MAMA techniques. By doing so, it efficiently filters out market noise, making it highly valuable for trend-following strategies. Investors can rely on this feature to gain clearer insights into the prevailing trends and make well-informed trading decisions.
This indicator is primarily suppoest to be used on the big timeframes to see which trend is prevailing, however I am not against someone using it on a timeframe below the 1D, just be careful if you are using this for modern portfolio theory, this is not suppoest to be a mid-term component, but rather a long term component that works well with proper use of detrended fluctuation analysis.
Dont hesitate to ask me if you have any questions
Again, I want to give credit to Everget and ChartPrime!
TRAX Detrended Price StrategyIn this script, the "TRAX" (TRIX) indicator is calculated using the Volume Weighted Moving Average (VWMA) instead of Exponential Moving Average (EMA) like the standard TRIX. The Detrended Price is used to identify short term cycles with a rate of change verses the rate of change from a triple smoothed TRAX VWMA . The strategy is intended for counter-trend trading, meaning it tries to capture potential reversals.
1. Indicators Used:
TRAX is calculated using the Volume Weighted Moving Average (VWMA) of the logarithm of the closing price.
DPO (Detrended Price Oscillator) is calculated by taking the closing price and subtracting a simple moving average (SMA) of the closing price shifted back.
2. Crossover Conditions:
Longs occur when DPO crosses above the TRAX, with the TRAX trending below 0, and the stock is trading above an adjustable simple moving average. Shorts occur due to the inverse conditions.
3. Visualization:
This script plots the SMA and the TRAX-DPO Combined Oscillator.
It highlights the periods of zero-line crossover using a green background for potential long positions and a red background for potential short positions. However, it will trigger verified entries/exits in accordance with the SMA.
In conclusion, this fun prototype underwent a unique alteration using the Volume Weighted Moving Average and focuses on capturing shorter counter-trend cycles. You have the freedom to fine-tune the strategy by adjusting parameters and incorporating other analysis methods that resonate with your trading style and risk tolerance.
VCC SmtmWorks better for Cryptos (1W and greater than) timeframes.
This strategy incorporates multiple indicators to make informed trading signals. It leverages the Stochastic indicator to assess price momentum, utilizes the Bollinger Band to identify potential oversold and overbought conditions, and closely monitors Moving Averages to gauge the trend's bullish or bearish nature.
A long signal will be displayed if the following conditions are met:
The Stochastic D and Stochastic K both indicate an oversold condition, with Stochastic K being lower than Stochastic D.
The current Price Low is below the Bollinger Lower Band.
The Price Close is currently below all Moving Averages.
A Death Cross pattern has formed among the Moving Averages.
A short signal will be displayed if the opposite of the long conditions are true:
The Stochastic D and Stochastic K both indicate an overbought condition, with Stochastic K being higher than Stochastic D.
The current Price High is above the Bollinger Upper Band.
The Price Close is currently above all Moving Averages.
A Golden Cross pattern has formed among the Moving Averages.
Expected Move from RSI [SS]Publishing this experimental indicator.
What it does:
The indicator uses a user-defined lookback period on a user-defined timeframe to lookback at all instances of RSI. It breaks RSI down as follows:
RSI between
0 - 10
10 - 20
20 - 30
30 - 40
40 - 50
50 - 60
60 - 70
70 - 80
80 - 90
90 - 100
From there, it stores the ticker's move from open to high and open to low. It will then use this data to look at the current RSI based on the specified timeframe and plot the expected move based on the average move the ticker does with a similar RSI reading.
It will plot the expected range, with the high range being plotted in green and the low range being plotted in red.
It will also display an infographic that dictates the current RSI based on the selected time frame, the anticipated up move and the anticipated down move. This infographic will also tell you the strength of the relationship (correlation) RSI has with the ticker's high or low price:
From there the user can determine whether this RSI reading is traditionally bullish or bearish for the ticker. A greater down move indicates that the RSI traditionally elicits a bearish response. A greater up move indicates the inverse.
The user can also view a chart of a breakdown of the anticipated moves based on RSI. If the option to "Show Expected Move Table" is select in the settings menu, the following table will appear:
From here you can see the average up move and down move a ticker does based on its corresponding RSI reading.
NOTE: When using the table, please adjust your chart timeframe to the selected timeframe on the indicator. Thus, if you are looking at the 1 hour levels, please adjust your chart to the 1 hour timeframe to use the chart.
Additional Note: When using the table, an "NaN" means that there are no instances of the ticker being at that RSI level within the designated timeframe period. You can extend your lookback period to up to 500 candles to see if it finds additional instances of similar RSI. Otherwise, you can adjust the selected timeframe.
Uses:
The indicator can be used on all timeframes. It can help give you an idea as to whether the RSI indicates a bearish or bullish sentiment.
It can signal a potential reversal or continuation. It can also help you with determining target prices for day trades and scalp trades.
And that is the indicator. Its pretty straight forward. It is experimental and new, so feel free to play around with it and let me know your thoughts.
Safe trades everyone and thank you for reading!
MACDh with divergences & impulse system-----------------------------------------------------------------
General Description:
This indicator ( the one on the low panel ) is a classic MACD that also shows regular divergences between its histogram and the prices. This script is special because it can be adjusted to fit several criteria when trading divergences filtering them according to the "height" and "width" of the patterns. The script also includes the "extra feature" Impulse System, which you will hardly find anywhere else in similar classic MACD histogram divergence indicators.
The indicator helps to find trend reversals, and it works on any market, any instrument, any timeframe, and any market condition (except against really strong trends that do not show any other sign of reversion yet).
Please take on consideration that divergences should be taken with caution.
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Definition of classic Bullish and Bearish divergences:
* Bearish divergences occur in uptrends identifying market tops. A classical or regular bearish divergence occurs when prices reach a new high and then pull back, with an oscillator (MACD histogram in this case) dropping below its zero line. Prices stabilize and rally to a higher high, but the oscillator reaches a lower peak than it did on a previous rally.
In the chart above (weekly charts of NKE, Nike, Inc.), in area X (around August 2021), NKE rallied to a new bull market high and MACD-Histogram rallied with it, rising above its previous peak and showing that bulls were extremely strong. In area Y, MACD-H fell below its centerline and at the same time prices punched below the zone between the two moving averages. In area Z, NKE rallied to a new bull market high, but the rally of MACD-H was feeble, reflecting the bulls’ weakness. Its downtick from peak Z completed a bearish divergence, giving a strong sell signal and auguring a nasty bear market.
* Bullish divergences , in the other hand, occur towards the ends of downtrends identifying market bottoms. A classical (also called regular) bullish divergence occurs when prices and an oscillator (MACD histogram in this case) both fall to a new low, rally, with the oscillator rising above its zero line, then both fall again. This time, prices drop to a lower low, but the oscillator traces a higher bottom than during its previous decline.
In the example in the chart above (weekly charts of NKE, Nike, Inc.), you see a bearish divergence that signaled the October 2022 bear market bottom, giving a strong buy signal right near the lows. In area A, NKE (weekly charts) appeared in a free fall. The record low A of MACD-H indicated that bears were extremely strong. In area B, MACD-H rallied above its centerline. Notice the brief rally of prices at that moment. In area C, NKE slid to a new bear market low, but MACD-H traced a much more shallow low. Its uptick completed a bullish divergence, giving a strong buy signal.
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Extra feature: Impulse System
This indicator also includes the “ Impulse System ”. The Impulse System is based on two indicators, a 13-day exponential moving average and the MACD-Histogram, and identifies inflection points where a trend speeds up or slows down. The moving average identifies the trend, while the MACD-Histogram measures momentum. This unique indicator combination is color coded into the price bars or macd histogram bars for easy reference.
Calculation:
Green Price Bar: (13-period EMA > previous 13-period EMA) and
(MACD-Histogram > previous period's MACD-Histogram)
Red Price Bar: (13-period EMA < previous 13-period EMA) and
(MACD-Histogram < previous period's MACD-Histogram)
Histogram bars are colored blue when conditions for a Red Histogram Bar or Green Histogram Bar are not met. The MACD-Histogram is based on MACD(12,26,9).
The Impulse System works more like a censorship system. Green histogram bars show that the bulls are in control of both trend and momentum as both the 13-day EMA and MACD-Histogram are rising (you don't have permission to sell). A red histogram bar indicates that the bears have taken control because the 13-day EMA and MACD Histogram are falling (you don't have permission to buy). A blue histogram bar indicates mixed technical signals, with neither buying nor selling pressure predominating (either both buying or selling are permitted).
The impulse system can be removed from the chart any time.
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Options/adjustments for this indicator:
*Horizontal Distance (width) between two tops/bottoms criteria.
Refers to the horizontal distance between the MACH histogram peaks involved in the divergence
*Height of tops/bottoms criteria (for Histogram).
Refers to the difference/relation/vertical distance between the MACH HISTOGRAM peaks involved in the divergence: 1st Histogram Peak is X times the 2nd.
*Height/Vertical deviation of tops/bottoms criteria (for Price).
Deviation refers to the difference/relation/vertical distance between the PRICE peaks involved in the divergence.
*Plot Regular Bullish Divergences?.
*Plot Regular Bearish Divergences?.
*Delete Previous Cancelled Divergences?.
*This indicator also has the option to show the Impulse System over the MACD histogram bars
Crude Oil Top and Bottoms -by Trevor GeallDiscover the Crude Oil Tops and Bottoms Predictor Indicator: Your Key to Market Precision!
How to Use:
Ideal for the daily chart. Wait for the colored background to form.
Confirm signals by waiting for the first candle to close after the background disappears. That would be your sign to go long (if the line is crossing up) or short (if line is crossing dow).
Combine with other indicators for enhanced insights.
Unveil Market Secrets:
Identifies potential tops and bottoms in crude oil.
Empowers strategic trading decisions.
Advanced divergence detection and price channel analysis.
Note: While powerful, no indicator guarantees perfect predictions. Use it alongside comprehensive analysis and risk management. Elevate your crude oil trading now!
PS If I get enough positive feedback on my indicators ill release some of the better ones.
Qualitative Smoothed Strength Index***RSI CHART BELOW IS FOR COMPARSION TO SHOW HOE THEY MAKE SIMILIAR PATTERNS*** IT IS NOT PART OF THE INDICATOR***
The Qualitative Smoothed Strength Index (QSSI) is a simplified momentum oscillator whose values will oscillate between 0 and 1 . By converting price differences into binary values and smoothing them with a moving average, it identifies qualitative strength of price movements. This simplification allows traders to easily interpret trends and reversals. The QSSI offers advantages such as noise reduction, clear trend identification, and early signal detection, resulting in less lag compared to traditional oscillators. Traders can customize the indicator based on their preferences and use it across various markets.
QSSI Indicator uses the input function is used to define the input parameters of the indicator. In this case, there are two inputs:
length: The number of periods used for calculating the differences (a, b, c) and their assigned values. Default value is 5.
MAL: The length of the moving average used for smoothing the assigned values. Default value is 14.
The next few lines calculate 'a', 'b', and 'c', which represent the differences between the high, low, and close prices, respectively, and their corresponding previous simple moving averages (SMAs) of specified length. These differences are used to identify price movements.
The code assigns binary values (0 or 1) to a_assigned, b_assigned, and c_assigned, depending on whether the corresponding differences (a, b, c) are greater than 0. This step converts the differences into a binary representation, indicating upward or downward price movements.
Average_assigned calculates the average of the assigned binary values of a, b, and c. This average value represents the overall strength of the price movement.ma_assigned calculates the 14-day moving average of average_assigned, which smoothens the indicator and helps traders identify trends more easily.
The code plots the 14-day moving average (ma_assigned) on the chart as a blue line. It also plots the individual assigned values of a, b, and c as dots on the chart. a_assigned is shown in green, b_assigned in red, and c_assigned in black. These dots indicate the presence of upward or downward movements in the respective price components. By visualizing these dots on the chart, the trader can quickly identify the presence and direction of price movements for each of the price components. This information can be valuable for understanding how the different price elements (high, low, and close) are contributing to the overall trend and strength of the market. Traders can use this data to make more informed decisions, such as confirming the presence of trends, identifying potential reversals, or gauging the overall market sentiment based on the distribution of upward and downward movements across the price components.
Finally, the code draws horizontal dotted lines at levels 0.70 (0.8)and 0.30 (0.2). These levels are typically used to identify overbought (above 0.70 or 0.8) and oversold (below 0.30 or 0.2) conditions in the market.
The Qualitative Smoothed Strength Index (QSSI) provides traders with information about the strength and direction of price movements. By using assigned binary values, the indicator simplifies the interpretation of price data, making it easier to identify trends and potential reversals.
Trend Correlation Oscillator [SS]Hello,
Publishing this simple indicator.
What is it?
The Trend Correlation Oscillator takes the concept of my autocorrelation oscillator but applies it simply to time instead of autocorrelation.
It performs a correlation assessment to time. The theory behind it is the stronger the correlation, the more "exhausted" the trend and the more likely the trend will reverse. It is kind of building off of random walk theory in which the market should be random and efficient.
Does it work?
If you follow me on my indicator side, you will know that my indicators are all based on my own research and findings and stuff that I personally find that works. All of this comes from years of losing money trying to use conventional systems and finally developing my own stuff that I find works well. This is such an invention. It does work extremely well but its best applied for day traders. If you want to use this as a swing trader, play around with the lookback length. I don't have general recommendations to swing traders wanting to use this because this isn't an indicator I personally would use for swing trading (I would use the autocorrelation oscillator for that).
How to use it:
The default setting is to a 14 candle lookback. This works the best. It also should really be used on the 5 minute chart and not the 1 minute chart, as from my experience this works much better.
When a trend is approaching "exhaustion" to the upside, the indicator will turn red to let you know we are approaching a trend exhaustion. Once the exhaustion is at its peak and beginning to reverse, the indicator will place a cross symbol on where your entry should be. See the image below for an example:
It also works well if you combine it with my PTCR Correlation Indicator:
Closing thoughts
That is basically the indicator. Its one of my more simple ones, but many times simple is better and most effective!
Hopefully you find it helpful.
As always let me know your questions, comments and feedback/recommendations for improvements below.
Please know I do read and make note of all recommendations for indicators and improvements, however as it is just me managing them, it takes time for implementation and review :-).
Safe trades!
P/VF BollThis code draws a custom indicator named "P/VF Boll" on the price chart with the following visual elements:
1. **Basis Line (Blue)**: This line represents the moving average value (ma_value) calculated based on the user-selected moving average type (SMA, EMA, or WMA) and length.
2. **Upper Bands (Green)**: The upper bands are calculated by adding a certain multiple of the standard deviation (dev1 to dev12) to the basis line. These bands represent a certain level of price volatility above the moving average.
3. **Lower Bands (Red)**: The lower bands are calculated by subtracting a certain multiple of the standard deviation (dev1 to dev12) from the basis line. These bands represent a certain level of price volatility below the moving average.
4. **Histogram (White and Gray)**: A histogram is drawn only when the average_price_change values are outside the 3rd standard deviation (dev3) and beyond. The histogram color alternates between white and gray, indicating higher price volatility.
The user can customize the following parameters:
- Average Length: The length of the moving average.
- Moving Average Type: The type of moving average to be used (SMA, EMA, or WMA).
- Timeframe: The timeframe used to calculate volume data.
- Deviation 1 to Deviation 12: Multipliers for calculating the upper and lower bands.
The purpose of this indicator is to visually represent the relationship between price volatility, volume, and the moving average, allowing traders to assess potential price breakouts or reversals when the price moves beyond certain levels of standard deviations from the moving average.
RSI-Volume Oscillator Quick Scalping By Akhilesh PatelTitle: RSI-Volume Oscillator Quick Scalping Indicator
Description:
The "RSI-Volume Oscillator Quick Scalping" is a powerful and versatile custom indicator designed for traders who engage in scalping strategies. This indicator combines the Relative Strength Index (RSI) with a Volume Oscillator to provide valuable insights into momentum and volume dynamics in the market. Traders can also select their preferred moving average types (SMA, EMA, or HMA) to further customize the indicator's behavior.
Key Features:
RSI and Volume Oscillator Fusion: The indicator blends the RSI and a custom Volume Oscillator to offer a comprehensive view of both price momentum and volume trends. This integration provides valuable signals for quick scalping opportunities.
Customizable Moving Averages: Traders can choose from three popular moving average types (SMA, EMA, or HMA) for further customization. This flexibility allows users to align the indicator with their preferred trading strategies.
Clear Visualization: The Combined RSI-Volume Oscillator is plotted as a solid blue line, while the three selected moving averages are represented by orange, purple, and green lines, respectively. The zero line, overbought, and oversold levels for RSI are also indicated for easy reference.
Quick Scalping Signals: The indicator helps traders spot potential buy and sell signals efficiently, making it ideal for quick scalping strategies in rapidly moving markets.
Usage Instructions:
Customize the indicator by selecting your preferred RSI length, Volume Oscillator length, and moving average type (SMA, EMA, or HMA).
Observe the Combined RSI-Volume Oscillator and moving averages for potential entry and exit points.
Look for crossovers between the Combined RSI-Volume Oscillator and the selected moving averages for buy and sell signals.
The overbought (70) and oversold (30) levels for RSI can be used to identify potential reversal points.
Important Note:
Test the indicator on historical data and demo accounts before using it in live trading to ensure it aligns with your trading strategy.
Understand that no indicator guarantees profits, and trading involves risk. Always use proper risk management and discipline when executing trades.
Overall, the "RSI-Volume Oscillator Quick Scalping" indicator is a valuable addition to any scalper's toolkit, providing comprehensive insights into momentum and volume dynamics to enhance trading decisions. Happy scalping!
AlexD Intraday market footprintThe indicator shows probability of a moving average non reversal at certain moment of day.
IMF_Predict line shows the probability of a reversal for the specified period.
moving average - period/2 shifted sma of typical price ( (close+high+low)/3 ).
Parameters:
Number of days - previous days to calculate the probability
SMA filter period - chart smoothing period
IMF smooth period - additional indicator smoothing after calculation
IMF predict period - period for calculating the probability of a reversal in the next N bars
Skip N hours in days(optimisation) - I recommend a half of the normal session time. Low values - long calculation time, High values - skipping days.
Anit Momentum IndicatorAnit Momentum Indicator: A Powerful Trend Continuation Tool for Long-Only Strategies
The "Anit Momentum Indicator" (AMI) is a powerful technical analysis tool designed to assist traders in identifying potential trend continuation opportunities in the financial markets. Unlike traditional trend reversal indicators, AMI is specifically crafted for long-only strategies, making it an ideal tool for traders seeking to capture sustained uptrends.
Concepts and Functionality:
1. Momentum Calculation:
The Anit Momentum Indicator begins by calculating the momentum of the closing price over a specified period. Momentum represents the rate of price change, offering clues about the strength and direction of price movements during the chosen duration.
2. RSI for Trend Continuation:
The script then applies the RSI to the previously computed momentum values. The RSI is a well-known oscillator used to measure the speed and magnitude of price changes. By utilizing the RSI on momentum data, the Anit Momentum Indicator gains a distinct advantage in gauging the strength of price momentum, leading to more accurate trend evaluations.
3. Rescaling for Better Visualization:
To enhance visual clarity and maintain consistent representation, the RSI on Momentum is rescaled to range from 0 to 100. This normalization ensures that the indicator's values remain within a fixed range, making it easier for traders to identify crucial overbought and oversold regions.
How to Use the Indicator:
Long-Only Strategy:
The AMI is most effective in long-only strategies. Traders can deploy the indicator to identify promising opportunities to go long on a stock or asset. A long position is established when the AMI crosses above 50, signaling a robust upward momentum.
Trend Continuation Confirmation:
The AMI's ability to capture trend continuation opportunities allows traders to stay invested in an uptrend for an extended period. As long as the AMI remains above 50, the uptrend is considered intact, and traders may continue to hold the position.
Higher Timeframe Advantage:
The AMI's effectiveness is further enhanced on higher timeframes. Longer timeframes provide a more reliable and sustained view of the underlying trend, giving traders greater confidence in their long-only strategies.
Conclusion:
The Anit Momentum Indicator is a valuable tool for traders pursuing trend continuation strategies, specifically long-only approaches. By leveraging the concept of momentum and RSI, the AMI helps traders identify and participate in sustained uptrends. With its focus on trend continuation rather than reversals, the AMI can be a key component in building successful long-only trading strategies, especially on higher timeframes. Traders can use this indicator to stay invested in robust uptrends, maximizing their profit potential while minimizing exposure to counter-trend moves by staying long till AMI value is greater than 50,it is better to stay away or exit from the asst class when AMI value is less than 50.
