INVITE-ONLY SCRIPT
已更新 Machine Learning : Dominant Cycle Elastic Volume KNN

About the Script
Dominant Cycle Elastic Volume KNN ,
is a non-parametric algorithm, which means that, initially it makes no assumptions about the underlying distribution of the time-series price as well as volume.
This approach gives it flexibility so that it can be used on a wide variety of securities at variety of timeframes.(even on lower timeframes such as seconds)
The main purpose of this indicator is to predict the trend of the underlying, by converging price, volume and dominant cycle as dimensions and generate signals of action.
Key terms :
Dominant cycle is a time cycle that has a greater influence on the overall behaviour of a system than other cycles.
The system uses Ehlers method to calculate Dominant Cycle/ Period.
Dominant cycle is used to determine the influencing period for the underlying.
Once the dominant cycle/ period is identified, it is treated as a dynamic length for considering further calculations
Elastic Volume MA is a volume based moving average which is generally used to converge the volume with price, the dominant period is used here as the length parameter
KNN K-Nearest Neighbour is one of the simplest Machine Learning algorithms based on Supervised Learning technique.
K-NN algorithm assumes the similarity between the new case/data and available cases and put the new case into the category that is most similar to the available categories.
K-NN algorithm stores all the available data and classifies a new data point based on the similarity. This means when new data appears then it can be easily classified into a well suite category by using K- NN algorithm. K-NN algorithm can be used for Regression as well as for Classification but mostly it is used for the Classification problems.
So, K-NN is used here to classify the trend of the Dominant Cycle Elastic Volume, and Generate Signals on top of it
How to Use the Indicator ?
The Buy Signal Candle

The Sell Signal Candle

The Buy Setup

The Sell Setup

Stop and Reverse Structure

What Timeframes and Symbols can this indicator be used on ?
The above indicator can be used on any liquid security which has volume information intact with ticker
and it can be used on any timeframe, but the best timeframes are [ 5min, 15min, 30min, 1hr ]
The indicator can also be used as a trend confirmatory indicators on lower time frames, like 30second
The Script has provision for alerts
Two alerts are there :
Alert 1= "LONG CONDITION : DCEV-ML"
Alert 2= "SHORT CONDITION : DCEV-ML"
How to request for access ?
Simply private message me !
Dominant Cycle Elastic Volume KNN ,
is a non-parametric algorithm, which means that, initially it makes no assumptions about the underlying distribution of the time-series price as well as volume.
This approach gives it flexibility so that it can be used on a wide variety of securities at variety of timeframes.(even on lower timeframes such as seconds)
The main purpose of this indicator is to predict the trend of the underlying, by converging price, volume and dominant cycle as dimensions and generate signals of action.
Key terms :
Dominant cycle is a time cycle that has a greater influence on the overall behaviour of a system than other cycles.
The system uses Ehlers method to calculate Dominant Cycle/ Period.
Dominant cycle is used to determine the influencing period for the underlying.
Once the dominant cycle/ period is identified, it is treated as a dynamic length for considering further calculations
Elastic Volume MA is a volume based moving average which is generally used to converge the volume with price, the dominant period is used here as the length parameter
KNN K-Nearest Neighbour is one of the simplest Machine Learning algorithms based on Supervised Learning technique.
K-NN algorithm assumes the similarity between the new case/data and available cases and put the new case into the category that is most similar to the available categories.
K-NN algorithm stores all the available data and classifies a new data point based on the similarity. This means when new data appears then it can be easily classified into a well suite category by using K- NN algorithm. K-NN algorithm can be used for Regression as well as for Classification but mostly it is used for the Classification problems.
So, K-NN is used here to classify the trend of the Dominant Cycle Elastic Volume, and Generate Signals on top of it
How to Use the Indicator ?
The Buy Signal Candle
The Sell Signal Candle
The Buy Setup
The Sell Setup
Stop and Reverse Structure
What Timeframes and Symbols can this indicator be used on ?
The above indicator can be used on any liquid security which has volume information intact with ticker
and it can be used on any timeframe, but the best timeframes are [ 5min, 15min, 30min, 1hr ]
The indicator can also be used as a trend confirmatory indicators on lower time frames, like 30second
The Script has provision for alerts
Two alerts are there :
Alert 1= "LONG CONDITION : DCEV-ML"
Alert 2= "SHORT CONDITION : DCEV-ML"
How to request for access ?
Simply private message me !
發行說明
Regarding TimeframesBest timeframe for usage is 15min,
but it can also be used for 30sec, 1min, 2min as a confirmatory indicator
on higher timeframes this can be used for 30min, 1hour, 3hour, daily and weekly
僅限邀請腳本
只有經作者授權的使用者才能訪問此腳本,且通常需付費。您可以將此腳本加入收藏,但需先向作者申請並獲得許可後才能使用 — 點擊此處了解更多。如需更多詳情,請依照作者說明或直接聯繫Ankit_1618。
除非您完全信任其作者並了解腳本的工作原理,否則TradingView不建議您付費或使用腳本。您也可以在我們的社群腳本中找到免費的開源替代方案。
作者的說明
For access related stuff, simply private message me!
提醒:在請求訪問權限之前,請閱讀僅限邀請腳本指南。
Get Ocs Ai Trader, Your personal Ai Trade Assistant here
→ ocstrader.com
About me
AlgoTrading Certification, ( University of Oxford, Säid Business School )
PGP Research Analysis, ( NISM, SEBI )
Electronics Engineer
→ ocstrader.com
About me
AlgoTrading Certification, ( University of Oxford, Säid Business School )
PGP Research Analysis, ( NISM, SEBI )
Electronics Engineer
免責聲明
這些資訊和出版物並不意味著也不構成TradingView提供或認可的金融、投資、交易或其他類型的意見或建議。請在使用條款閱讀更多資訊。
僅限邀請腳本
只有經作者授權的使用者才能訪問此腳本,且通常需付費。您可以將此腳本加入收藏,但需先向作者申請並獲得許可後才能使用 — 點擊此處了解更多。如需更多詳情,請依照作者說明或直接聯繫Ankit_1618。
除非您完全信任其作者並了解腳本的工作原理,否則TradingView不建議您付費或使用腳本。您也可以在我們的社群腳本中找到免費的開源替代方案。
作者的說明
For access related stuff, simply private message me!
提醒:在請求訪問權限之前,請閱讀僅限邀請腳本指南。
Get Ocs Ai Trader, Your personal Ai Trade Assistant here
→ ocstrader.com
About me
AlgoTrading Certification, ( University of Oxford, Säid Business School )
PGP Research Analysis, ( NISM, SEBI )
Electronics Engineer
→ ocstrader.com
About me
AlgoTrading Certification, ( University of Oxford, Säid Business School )
PGP Research Analysis, ( NISM, SEBI )
Electronics Engineer
免責聲明
這些資訊和出版物並不意味著也不構成TradingView提供或認可的金融、投資、交易或其他類型的意見或建議。請在使用條款閱讀更多資訊。