🌟🚀 Dive into the future of trading with our latest innovation: the AI Adaptive Money Flow Index by AlgoAlpha Indicator! 🚀🌟
Developed with the cutting-edge power of Machine Learning, this indicator is designed to revolutionize the way you view market dynamics. 🤖💹 With its unique blend of traditional Money Flow Index (MFI) analysis and advanced k-means clustering,...
Multiple Logistic Regression Indicator
The Logistic Regression Indicator for TradingView is a versatile tool that employs multiple logistic regression based on various technical indicators to generate potential buy and sell signals. By utilizing key indicators such as RSI, CCI, DMI, Aroon, EMA, and SuperTrend, the indicator aims to provide a systematic approach...
This Indicator aims to fill a gap within traditional Standard Deviation Analysis. Rather than its usual applications, this Indicator focuses on applying Standard Deviation within an Oscillator and likewise applying a Machine Learning approach to it. By doing so, we may hope to achieve an Adaptive Oscillator which can help display when the price is deviating from...
Machine Learning: VWAP aims to use Machine Learning to Identify the best location to Anchor the VWAP at. Rather than using a traditional fixed length or simply adjusting based on a Date / Time; by applying Machine Learning we may hope to identify crucial areas which make sense to reset the VWAP and start anew. VWAP’s may act similar to a Bollinger Band in the...
This Indicator, will rate multiple different lengths of RSIs to determine which RSI to RSI MA cross produced the highest profit within the lookback span. This ‘Optimal RSI’ is then passed back, and if toggled will then be thrown into a Machine Learning calculation. You have the option to Filter RSI and RSI MA’s within the Machine Learning calculation. What this...
Trend lines have always been a key indicator that may help predict many different types of price movements. They have been well known to create different types of formations such as: Pennants, Channels, Flags and Wedges. The type of formation they create is based on how the formation was created and the angle it was created. For instance, if there was a strong...
Overview:
MFI Heat Maps are a visually appealing way to display the values of 29 different MFIs at the same time while being able to make sense of it. Each plot within the Indicator represents a different MFI value. The higher you get up, the longer the length that was used for this MFI. This Indicator also features the use of Machine Learning to help balance...
Overview:
Support and Resistance is normally based upon Pivot Points and Highest Highs and Lowest Lows. Many times coders even incorporate Volume, RSI and other factors into the equation. However there may be a downside to doing a pure technical approach based on historical levels. We live in a time where Machine Learning is becoming more and more used; thus we...
Overview:
AI Momentum is a kernel function based momentum Indicator. It uses Rational Quadratics to help smooth out the Moving Averages, this may give them a more accurate result. This Indicator has 2 main uses, first it displays ‘Zones’ that help you visualize the potential movement areas and when the price is out of bounds (Overvalued or Undervalued). Secondly...
⚠️❗ Important Limitations: Due to the way this script is designed, it operates specifically under certain conditions:
Stocks & Forex : Only compatible with timeframes of 8 hours and above ⏰
Crypto : Only works with timeframes starting from 4 hours and higher ⏰
❗Please note that the script will not work on lower timeframes.❗
Feature Extraction : It begins by...
The SuperTrend AI indicator is a novel take on bridging the gap between the K-means clustering machine learning method & technical indicators. In this case, we apply K-Means clustering to the famous SuperTrend indicator.
🔶 USAGE
Users can interpret the SuperTrend AI trailing stop similarly to the regular SuperTrend indicator. Using higher minimum/maximum...
The RSI-MFI Machine Learning Indicator is a technical analysis tool that combines the Relative Strength Index (RSI) and Money Flow Index (MFI) indicators with the Manhattan distance metric.
It aims to provide insights into potential trade setups by leveraging machine learning principles and calculating distances between current and historical data points.
...
█ OVERVIEW
A Lorentzian Distance Classifier (LDC) is a Machine Learning classification algorithm capable of categorizing historical data from a multi-dimensional feature space. This indicator demonstrates how Lorentzian Classification can also be used to predict the direction of future price movements when used as the distance metric for a novel implementation of...
This script is the my Dependent Variable Odd Generator script :
with the Put / Call Ratio ( PCR ) appended, only for CBOE and the instruments connected to it.
For CBOE this script is more accurate and faster than Dependent Variable Odd Generator. And the stagnant market odds are better and more realistic.
Do not use for timeframe periods less than 1 day.
Because...
Logic is correct.
But I prefer to say experimental because the sample set is narrow. (300 columns)
Let's start:
6 inputs : Volume Change , Bollinger Low Band chg. , Bollinger Mid Band chg., Bollinger Up Band chg. , RSI change , MACD histogram change.
1 output : Future bar change (Historical)
Training timeframe : 15 mins (Analysis TF > 4 hours (My...
NOTE : Deep learning was conducted in a narrow sample set for testing purposes. So this script is Experimental .
This system is based on the following article and is inspired by an external program:
hackernoon.com
None of the artificial neural networks in Tradingview work and are not based on completely correct logic. Unlike others in this system:
IMPORTANT...
![BTCUSD: AI Adaptive Money Flow Index (Clustering) [AlgoAlpha]](https://s3.tradingview.com/8/8c9igEZv_mid.png "AI Adaptive Money Flow Index (Clustering) [AlgoAlpha]")
![BTCUSDT: Machine Learning: STDEV Oscillator [YinYangAlgorithms]](https://s3.tradingview.com/4/4juIQs7S_mid.png "Machine Learning: STDEV Oscillator [YinYangAlgorithms]")
![BTCUSDT: Machine Learning: VWAP [YinYangAlgorithms]](https://s3.tradingview.com/v/vhEiWwdk_mid.png "Machine Learning: VWAP [YinYangAlgorithms]")
![BTCUSDT: Machine Learning: Optimal RSI [YinYangAlgorithms]](https://s3.tradingview.com/b/bLOzFkhi_mid.png "Machine Learning: Optimal RSI [YinYangAlgorithms]")
![BTCUSDT: Machine Learning: Trend Lines [YinYangAlgorithms]](https://s3.tradingview.com/u/U3CHwiXZ_mid.png "Machine Learning: Trend Lines [YinYangAlgorithms]")
![BTCUSDT: Machine Learning: MFI Heat Map [YinYangAlgorithms]](https://s3.tradingview.com/h/h3bdHkHg_mid.png "Machine Learning: MFI Heat Map [YinYangAlgorithms]")
![BTCUSDT: Machine Learning: Support and Resistance [YinYangAlgorithms]](https://s3.tradingview.com/h/hurudMoT_mid.png "Machine Learning: Support and Resistance [YinYangAlgorithms]")
![BTCUSDT: AI Momentum [YinYang]](https://s3.tradingview.com/n/NKUsm5uR_mid.png "AI Momentum [YinYang]")
![BTCUSD: SuperTrend AI (Clustering) [LuxAlgo]](https://s3.tradingview.com/w/wP7WWjLL_mid.png "SuperTrend AI (Clustering) [LuxAlgo]")
![ETHUSDT: RSI-MFI Machine Learning [ Manhattan distance ]](https://s3.tradingview.com/j/jrjOQDgc_mid.png "RSI-MFI Machine Learning [ Manhattan distance ]")
