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Machine Learning: Gaussian Process Regression [LuxAlgo]

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We provide an implementation of the Gaussian Process Regression (GPR), a popular machine-learning method capable of estimating underlying trends in prices as well as forecasting them.

While this implementation is adapted to real-time usage, do remember that forecasting trends in the market is challenging, do not use this tool as a standalone for your trading decisions.

🔶 USAGE

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The main goal of our implementation of GPR is to forecast trends. The method is applied to a subset of the most recent prices, with the Training Window determining the size of this subset.

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Two user settings controlling the trend estimate are available, Smooth and Sigma. Smooth determines the smoothness of our estimate, with higher values returning smoother results suitable for longer-term trend estimates.

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Sigma controls the amplitude of the forecast, with values closer to 0 returning results with a higher amplitude. Do note that due to the calculation of the method, lower values of sigma can return errors with higher values of the training window.

🔹Updating Mechanisms

The script includes three methods to update a forecast. By default a forecast will not update for new bars (Lock Forecast).

The forecast can be re-estimated once the price reaches the end of the forecasting window when using the "Update Once Reached" method.

Finally "Continuously Update" will update the whole forecast on any new bar.

🔹Estimating Trends

https://www.tradingview.com/x/VhQ0rx0T/

Gaussian Process Regression can be used to estimate past underlying local trends in the price, allowing for a noise-free interpretation of trends.

This can be useful for performing descriptive analysis, such as highlighting patterns more easily.

🔶 SETTINGS

  • Training Window: Number of most recent price observations used to fit the model
  • Forecasting Length: Forecasting horizon, determines how many bars in the future are forecasted.
  • Smooth: Controls the degree of smoothness of the model fit.
  • Sigma: Noise variance. Controls the amplitude of the forecast, lower values will make it more sensitive to outliers.
  • Update: Determines when the forecast is updated, by default the forecast is not updated for new bars.
版本注释
- Allows for greater training window
- Reduced matrix instability
artificial_intelligenceforecastforecastingforecastingtechniquesluxalgomachinelearningpredictionsmoothTrend Analysistrends

开源脚本

本着真正的TradingView精神,此脚本的作者已将其开源,以便交易者可以理解和验证它。向作者致敬!您可以免费使用它,但在出版物中重复使用此代码受网站规则约束。 您可以收藏它以在图表上使用。

想在图表上使用此脚本?


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