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已更新 EMA-Deviation-Corrected T3 [Loxx]

EMA-Deviation-Corrected T3 is a T3 moving average that uses EMA deviation correcting to produce signals. This comes via the beloved genius Mladen.
The origin of the correcting algorithm can be attributed to Dr. Alexander Uhl, who developed a method to filter the moving average and identify signals. Originally, this method utilized standard deviation as a measure to correct the average values.
However, the current indicator in question employs a modified version of the correcting method. Instead of using standard deviation for calculation, it uses EMA deviation, which stands for Exponential Moving Average deviation. The idea behind using EMA deviation is two-fold:
Efficiency: EMA deviation can be calculated faster than standard deviation, resulting in more efficient code execution.
Signal Reduction: Surprisingly, this modified "correcting" approach generates fewer signals compared to using standard deviation. This is because EMA deviation is more responsive to price changes, making the correcting process less sensitive to whipsaws or false signals.
What is T3?
The T3 moving average, short for "Tim Tillson's Triple Exponential Moving Average," is a technical indicator used in financial markets and technical analysis to smooth out price data over a specific period. It was developed by Tim Tillson, a software project manager at Hewlett-Packard, with expertise in Mathematics and Computer Science.
The T3 moving average is an enhancement of the traditional Exponential Moving Average (EMA) and aims to overcome some of its limitations. The primary goal of the T3 moving average is to provide a smoother representation of price trends while minimizing lag compared to other moving averages like Simple Moving Average (SMA), Weighted Moving Average (WMA), or EMA.
To compute the T3 moving average, it involves a triple smoothing process using exponential moving averages. Here's how it works:
Calculate the first exponential moving average (EMA1) of the price data over a specific period 'n.'
Calculate the second exponential moving average (EMA2) of EMA1 using the same period 'n.'
Calculate the third exponential moving average (EMA3) of EMA2 using the same period 'n.'
The formula for the T3 moving average is as follows:
T3 = 3 * (EMA1) - 3 * (EMA2) + (EMA3)
By applying this triple smoothing process, the T3 moving average is intended to offer reduced noise and improved responsiveness to price trends. It achieves this by incorporating multiple time frames of the exponential moving averages, resulting in a more accurate representation of the underlying price action.
Included
The origin of the correcting algorithm can be attributed to Dr. Alexander Uhl, who developed a method to filter the moving average and identify signals. Originally, this method utilized standard deviation as a measure to correct the average values.
However, the current indicator in question employs a modified version of the correcting method. Instead of using standard deviation for calculation, it uses EMA deviation, which stands for Exponential Moving Average deviation. The idea behind using EMA deviation is two-fold:
Efficiency: EMA deviation can be calculated faster than standard deviation, resulting in more efficient code execution.
Signal Reduction: Surprisingly, this modified "correcting" approach generates fewer signals compared to using standard deviation. This is because EMA deviation is more responsive to price changes, making the correcting process less sensitive to whipsaws or false signals.
What is T3?
The T3 moving average, short for "Tim Tillson's Triple Exponential Moving Average," is a technical indicator used in financial markets and technical analysis to smooth out price data over a specific period. It was developed by Tim Tillson, a software project manager at Hewlett-Packard, with expertise in Mathematics and Computer Science.
The T3 moving average is an enhancement of the traditional Exponential Moving Average (EMA) and aims to overcome some of its limitations. The primary goal of the T3 moving average is to provide a smoother representation of price trends while minimizing lag compared to other moving averages like Simple Moving Average (SMA), Weighted Moving Average (WMA), or EMA.
To compute the T3 moving average, it involves a triple smoothing process using exponential moving averages. Here's how it works:
Calculate the first exponential moving average (EMA1) of the price data over a specific period 'n.'
Calculate the second exponential moving average (EMA2) of EMA1 using the same period 'n.'
Calculate the third exponential moving average (EMA3) of EMA2 using the same period 'n.'
The formula for the T3 moving average is as follows:
T3 = 3 * (EMA1) - 3 * (EMA2) + (EMA3)
By applying this triple smoothing process, the T3 moving average is intended to offer reduced noise and improved responsiveness to price trends. It achieves this by incorporating multiple time frames of the exponential moving averages, resulting in a more accurate representation of the underlying price action.
Included
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開源腳本
本著TradingView的真正精神,此腳本的創建者將其開源,以便交易者可以查看和驗證其功能。向作者致敬!雖然您可以免費使用它,但請記住,重新發佈程式碼必須遵守我們的網站規則。
Public Telegram Group, t.me/algxtrading_public
VIP Membership Info: patreon.com/algxtrading/membership
VIP Membership Info: patreon.com/algxtrading/membership
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。