INVITE-ONLY SCRIPT
업데이트됨 Optimal Confidence Scalper [OCS]

Introduction
OCS : Optimal Confidence Scalpers, Utilise the computational approach towards finding confidence estimating in signal generating process, It helps u enter and exit the financial markets quickly, It buy and sell many times in a day with the objective of making consistent profits from incremental movements in the traded security's price. As we all know Lag is very undesirable because a trading system. Late trades can many times be worse than no trades at all, Main aim of the System is to find optimal Entry and Exit points for a successful trade
Mathematics behind the indicator
The indicator use two fundamentals pillars :
Estimation of a Confidence Interval
In frequentist statistics, a confidence interval (CI) is a range of estimates for an unknown parameter. A confidence interval is computed at a designated confidence level; the 95% confidence level is most common, but other levels, such as 90% or 99%, are sometimes used.
Desired properties are Validity, Optimality and Invariance
Polynomial Filters
The polynomial filters are based on the orthogonal polynomials of Legendre and Laguerre. Orthogonal polynomials are widely used in applied mathematics, physics and engineering, and the Legendre and Laguerre polynomials are only two of infinitely many sets, each of which has its own weight function.
They can be characterized in three equivalent ways:
1. They are the optimal lowpass filters that minimize the NRR, subject to additional constraints than the DC unity-gain condition
2. They are the optimal filters that minimize the NRR whose frequency response H(ω) satisfies certain flatness constraints at DC
3. They are the filters that optimally fit, in a least-squares sense, a set of data points to polynomials of different degrees.
The System uses Predictive Differentiation Filters, as subset to Polynomial Filters
Components of the System
Buy Signal and Sell Signals

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=====================------ HOW TO USE IT
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ENTRY and EXITS




Momentum Bands

Confidence Levels

Indicator Properties
Provision For Alerts
1. Buy Signal Alert
2. Sell Signal Alert
3. Exit Alert if in Buy Trade
4. Exit Alert if in Sell Trade
Some Examples




What TimeFrames To Use
U can use any Timeframe, The indicator is Adaptive in Nature,
I personally use timeframes such as : 1m, 5m 10m, 15m, ..... 1D, 1W
How to Access
U will need to privately message me.
use comment box for constructive comments
Thanks
OCS : Optimal Confidence Scalpers, Utilise the computational approach towards finding confidence estimating in signal generating process, It helps u enter and exit the financial markets quickly, It buy and sell many times in a day with the objective of making consistent profits from incremental movements in the traded security's price. As we all know Lag is very undesirable because a trading system. Late trades can many times be worse than no trades at all, Main aim of the System is to find optimal Entry and Exit points for a successful trade
Mathematics behind the indicator
The indicator use two fundamentals pillars :
Estimation of a Confidence Interval
In frequentist statistics, a confidence interval (CI) is a range of estimates for an unknown parameter. A confidence interval is computed at a designated confidence level; the 95% confidence level is most common, but other levels, such as 90% or 99%, are sometimes used.
Desired properties are Validity, Optimality and Invariance
Polynomial Filters
The polynomial filters are based on the orthogonal polynomials of Legendre and Laguerre. Orthogonal polynomials are widely used in applied mathematics, physics and engineering, and the Legendre and Laguerre polynomials are only two of infinitely many sets, each of which has its own weight function.
They can be characterized in three equivalent ways:
1. They are the optimal lowpass filters that minimize the NRR, subject to additional constraints than the DC unity-gain condition
2. They are the optimal filters that minimize the NRR whose frequency response H(ω) satisfies certain flatness constraints at DC
3. They are the filters that optimally fit, in a least-squares sense, a set of data points to polynomials of different degrees.
The System uses Predictive Differentiation Filters, as subset to Polynomial Filters
Components of the System
Buy Signal and Sell Signals
=====================
=====================------ HOW TO USE IT
=====================
ENTRY and EXITS
Momentum Bands
Confidence Levels
Indicator Properties
Provision For Alerts
1. Buy Signal Alert
2. Sell Signal Alert
3. Exit Alert if in Buy Trade
4. Exit Alert if in Sell Trade
Some Examples
What TimeFrames To Use
U can use any Timeframe, The indicator is Adaptive in Nature,
I personally use timeframes such as : 1m, 5m 10m, 15m, ..... 1D, 1W
How to Access
U will need to privately message me.
use comment box for constructive comments
Thanks
릴리즈 노트
Update : Adds The way to guide on the Targets HISTORICAL PERFORMANCE
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초대 전용 스크립트
이 스크립트는 작성자가 승인한 사용자만 접근할 수 있습니다. 사용하려면 요청을 보내고 승인을 받아야 합니다. 일반적으로 결제 후에 승인이 이루어집니다. 자세한 내용은 아래 작성자의 지침을 따르거나 Ankit_1618에게 직접 문의하세요.
트레이딩뷰는 스크립트 작성자를 완전히 신뢰하고 스크립트 작동 방식을 이해하지 않는 한 스크립트 비용을 지불하거나 사용하지 않는 것을 권장하지 않습니다. 무료 오픈소스 대체 스크립트는 커뮤니티 스크립트에서 찾을 수 있습니다.
작성자 지시 사항
Please privately message me to use this indicator, use comment box for constructive comments
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
면책사항
이 정보와 게시물은 TradingView에서 제공하거나 보증하는 금융, 투자, 거래 또는 기타 유형의 조언이나 권고 사항을 의미하거나 구성하지 않습니다. 자세한 내용은 이용 약관을 참고하세요.
초대 전용 스크립트
이 스크립트는 작성자가 승인한 사용자만 접근할 수 있습니다. 사용하려면 요청을 보내고 승인을 받아야 합니다. 일반적으로 결제 후에 승인이 이루어집니다. 자세한 내용은 아래 작성자의 지침을 따르거나 Ankit_1618에게 직접 문의하세요.
트레이딩뷰는 스크립트 작성자를 완전히 신뢰하고 스크립트 작동 방식을 이해하지 않는 한 스크립트 비용을 지불하거나 사용하지 않는 것을 권장하지 않습니다. 무료 오픈소스 대체 스크립트는 커뮤니티 스크립트에서 찾을 수 있습니다.
작성자 지시 사항
Please privately message me to use this indicator, use comment box for constructive comments
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
면책사항
이 정보와 게시물은 TradingView에서 제공하거나 보증하는 금융, 투자, 거래 또는 기타 유형의 조언이나 권고 사항을 의미하거나 구성하지 않습니다. 자세한 내용은 이용 약관을 참고하세요.