OPEN-SOURCE SCRIPT
Local Volatility

The traditional calculation of volatility involves computing the standard deviation of returns,
which is based on the mean return. However, when the asset price exhibits a trending behavior,
the mean return could be significantly different from zero, and changing the length of the time
window used for the calculation could result in artificially high volatility values. This is because
more returns would be further away from the mean, leading to a larger sum of squared deviations.
To address this issue, our Local Volatility measure computes the standard deviation of the
differences between consecutive asset prices, rather than their returns. This provides a measure of
how much the price changes from one tick to the next, irrespective of the overall trend.
~ arxiv.org/abs/2308.14235
which is based on the mean return. However, when the asset price exhibits a trending behavior,
the mean return could be significantly different from zero, and changing the length of the time
window used for the calculation could result in artificially high volatility values. This is because
more returns would be further away from the mean, leading to a larger sum of squared deviations.
To address this issue, our Local Volatility measure computes the standard deviation of the
differences between consecutive asset prices, rather than their returns. This provides a measure of
how much the price changes from one tick to the next, irrespective of the overall trend.
~ arxiv.org/abs/2308.14235
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开源脚本
本着TradingView的真正精神,此脚本的创建者将其开源,以便交易者可以查看和验证其功能。向作者致敬!虽然您可以免费使用它,但请记住,重新发布代码必须遵守我们的网站规则。
免责声明
这些信息和出版物并不意味着也不构成TradingView提供或认可的金融、投资、交易或其它类型的建议或背书。请在使用条款阅读更多信息。