OPEN-SOURCE SCRIPT
已更新 Liquidity Weighted Moving Averages [AlgoAlpha]

Description:
The Liquidity Weighted Moving Averages by AlgoAlpha is a unique approach to identifying underlying trends in the market by looking at candle bars with the highest level of liquidity. This script offers a modified version of the classical MA crossover indicator that aims to be less noisy by using liquidity to determine the true fair value of price and where it should place more emphasis on when calculating the average.
Rationale:
It is common knowledge that liquidity makes it harder for market participants to move the price of assets, using this logic, we can determine the coincident liquidity of each bar by looking at the volume divided by the distance between the opening and closing price of that bar. If there is a higher volume but the opening and closing prices are near each other, this means that there was a high level of liquidity in that bar. We then use standard deviations to filter out high spikes of liquidity and record the closing prices on those bars. An average is then applied to these recorded prices only instead of taking the average of every single bar to avoid including outliers in the data processing.
Key features:
Customizable:
Fast Length - the period of the fast-moving average
Slow Length - the period of the slow-moving average
Outlier Threshold Length - the period of the outlier processing algorithm to detect spikes in liquidity
Significant Noise reduction from outliers:



The Liquidity Weighted Moving Averages by AlgoAlpha is a unique approach to identifying underlying trends in the market by looking at candle bars with the highest level of liquidity. This script offers a modified version of the classical MA crossover indicator that aims to be less noisy by using liquidity to determine the true fair value of price and where it should place more emphasis on when calculating the average.
Rationale:
It is common knowledge that liquidity makes it harder for market participants to move the price of assets, using this logic, we can determine the coincident liquidity of each bar by looking at the volume divided by the distance between the opening and closing price of that bar. If there is a higher volume but the opening and closing prices are near each other, this means that there was a high level of liquidity in that bar. We then use standard deviations to filter out high spikes of liquidity and record the closing prices on those bars. An average is then applied to these recorded prices only instead of taking the average of every single bar to avoid including outliers in the data processing.
Key features:
Customizable:
Fast Length - the period of the fast-moving average
Slow Length - the period of the slow-moving average
Outlier Threshold Length - the period of the outlier processing algorithm to detect spikes in liquidity
Significant Noise reduction from outliers:
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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。
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Code: HMD25
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Code: HMD25
🚨Get premium: algoalpha.io
🛜Get FREE signals: discord.gg/xCmqTVRexz
❓Do you have feedback or indicator ideas? Join our server to tell us about it!
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。
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。
🔱Get 50% off EVERYTHING for Mothers' Day!🔱(Ends soon!)
Code: HMD25
🚨Get premium: algoalpha.io
🛜Get FREE signals: discord.gg/xCmqTVRexz
❓Do you have feedback or indicator ideas? Join our server to tell us about it!
Code: HMD25
🚨Get premium: algoalpha.io
🛜Get FREE signals: discord.gg/xCmqTVRexz
❓Do you have feedback or indicator ideas? Join our server to tell us about it!
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。