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업데이트됨 Kalman Ema Crosses - [JTCAPITAL]

Kalman Ema Crosses is a modified way to use the Kalman Filter over the price data as well as the EMA itself. It can be used for trend-following purposes.
The indicator works by calculating in the following steps:
1. Perform Kalman Calculations over the chosen source data.
2. Make EMA's from the Kalman Filtered source data.
3. Kalman Filter the EMA's separately
4. Define Buy and Sell conditions based on the crosses from the 2 Kalman Filtered EMA's.
--Buy and sell conditions--
- The buy and sell conditions are simply divined by a crossover of the EMA's
--Features and Parameters--
- Allows the usage of different sources
- Allows the changing of the length of both EMA's
- Allows the changing of the process noise used in the Kalman calculations
- Allows the changing of the measurement noise used in the Kalman calculations
- Allows the changing of which of the 2 Kalman Filters the price filtering is done on.
--Details--
Kalman Ema Crosses uses the Kalman Filter multiple times in an attempt to reduce false signals while maintaining the fast entries and exits we usually get from ema crosses. Also allowing the changing of what Kalman filter gets used for the filtering of price.
Using the Kalman filter calculations from the faster EMA for price increases sensitivity by a huge amount. Having fast EMA's while doing the price calculations on the Kalman filter of the fast EMA will result in an unnecessary amount of noise. On the other hand using the fast Kalman filter for price while using long ema lengths may reduce late entries.
Kalman filter is widely known and used for its ability to predict states of a linear dynamic input in an uncertain period. By using this on a noisy indicator such as EMA crosses we can filter out market noise, getting a more accurate analysis and signal.
The multiple parameters that can be changed can drastically alter the performance and speed of the Kalman filter, I have purposely left this open to allow people to use it on all asset classes and timeframes.
The EMA is a widely known indicator, and paired with another EMA on another length can provide meaningful signals and insights into the market. The downside of this amazing indicator is the amount of noise and false signals it produces. With this approach we have reduced the noise and increased the profitability of the indicator we all know and love.
Enjoy!
The indicator works by calculating in the following steps:
1. Perform Kalman Calculations over the chosen source data.
2. Make EMA's from the Kalman Filtered source data.
3. Kalman Filter the EMA's separately
4. Define Buy and Sell conditions based on the crosses from the 2 Kalman Filtered EMA's.
--Buy and sell conditions--
- The buy and sell conditions are simply divined by a crossover of the EMA's
--Features and Parameters--
- Allows the usage of different sources
- Allows the changing of the length of both EMA's
- Allows the changing of the process noise used in the Kalman calculations
- Allows the changing of the measurement noise used in the Kalman calculations
- Allows the changing of which of the 2 Kalman Filters the price filtering is done on.
--Details--
Kalman Ema Crosses uses the Kalman Filter multiple times in an attempt to reduce false signals while maintaining the fast entries and exits we usually get from ema crosses. Also allowing the changing of what Kalman filter gets used for the filtering of price.
Using the Kalman filter calculations from the faster EMA for price increases sensitivity by a huge amount. Having fast EMA's while doing the price calculations on the Kalman filter of the fast EMA will result in an unnecessary amount of noise. On the other hand using the fast Kalman filter for price while using long ema lengths may reduce late entries.
Kalman filter is widely known and used for its ability to predict states of a linear dynamic input in an uncertain period. By using this on a noisy indicator such as EMA crosses we can filter out market noise, getting a more accurate analysis and signal.
The multiple parameters that can be changed can drastically alter the performance and speed of the Kalman filter, I have purposely left this open to allow people to use it on all asset classes and timeframes.
The EMA is a widely known indicator, and paired with another EMA on another length can provide meaningful signals and insights into the market. The downside of this amazing indicator is the amount of noise and false signals it produces. With this approach we have reduced the noise and increased the profitability of the indicator we all know and love.
Enjoy!
릴리즈 노트
Cleaned code오픈 소스 스크립트
진정한 트레이딩뷰 정신에 따라 이 스크립트 작성자는 트레이더가 기능을 검토하고 검증할 수 있도록 오픈소스로 공개했습니다. 작성자에게 찬사를 보냅니다! 무료로 사용할 수 있지만 코드를 다시 게시할 경우 하우스 룰이 적용된다는 점을 기억하세요.
면책사항
이 정보와 게시물은 TradingView에서 제공하거나 보증하는 금융, 투자, 거래 또는 기타 유형의 조언이나 권고 사항을 의미하거나 구성하지 않습니다. 자세한 내용은 이용 약관을 참고하세요.
오픈 소스 스크립트
진정한 트레이딩뷰 정신에 따라 이 스크립트 작성자는 트레이더가 기능을 검토하고 검증할 수 있도록 오픈소스로 공개했습니다. 작성자에게 찬사를 보냅니다! 무료로 사용할 수 있지만 코드를 다시 게시할 경우 하우스 룰이 적용된다는 점을 기억하세요.
면책사항
이 정보와 게시물은 TradingView에서 제공하거나 보증하는 금융, 투자, 거래 또는 기타 유형의 조언이나 권고 사항을 의미하거나 구성하지 않습니다. 자세한 내용은 이용 약관을 참고하세요.