Extract Kaufman's Adaptive Moving Average #152
Assignees
Labels
Comments
jealous
added a commit
that referenced
this issue
Jun 23, 2023
The Efficiency Ratio (ER) is calculated by dividing the price change over a period by the absolute sum of the price movements that occurred to achieve that change. The resulting ratio ranges between 0 and 1 with higher values representing a more efficient or trending market. The default column is close. The default window is 10. Formular: * window_change = ABS(close - close[n]) * last_change = ABS(close-close[1]) * volatility = moving sum of last_change in n * KER = window_change / volatility Examples: * `df['ker']` retrieves the 10 periods KER of the close price * `df['high_5_ker']` retrieves 5 periods KER of the high price
jealous
added a commit
that referenced
this issue
Jun 23, 2023
The Efficiency Ratio (ER) is calculated by dividing the price change over a period by the absolute sum of the price movements that occurred to achieve that change. The resulting ratio ranges between 0 and 1 with higher values representing a more efficient or trending market. The default column is close. The default window is 10. Formular: * window_change = ABS(close - close[n]) * last_change = ABS(close-close[1]) * volatility = moving sum of last_change in n * KER = window_change / volatility Examples: * `df['ker']` retrieves the 10 periods KER of the close price * `df['high_5_ker']` retrieves 5 periods KER of the high price
jealous
added a commit
that referenced
this issue
Jun 23, 2023
The Efficiency Ratio (ER) is calculated by dividing the price change over a period by the absolute sum of the price movements that occurred to achieve that change. The resulting ratio ranges between 0 and 1 with higher values representing a more efficient or trending market. The default column is close. The default window is 10. Formular: * window_change = ABS(close - close[n]) * last_change = ABS(close-close[1]) * volatility = moving sum of last_change in n * KER = window_change / volatility Examples: * `df['ker']` retrieves the 10 periods KER of the close price * `df['high_5_ker']` retrieves 5 periods KER of the high price
jealous
added a commit
that referenced
this issue
Jun 23, 2023
The Efficiency Ratio (ER) is calculated by dividing the price change over a period by the absolute sum of the price movements that occurred to achieve that change. The resulting ratio ranges between 0 and 1 with higher values representing a more efficient or trending market. The default column is close. The default window is 10. Formular: * window_change = ABS(close - close[n]) * last_change = ABS(close-close[1]) * volatility = moving sum of last_change in n * KER = window_change / volatility Examples: * `df['ker']` retrieves the 10 periods KER of the close price * `df['high_5_ker']` retrieves 5 periods KER of the high price
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
The Kaufman's Adaptive Moving Average is used in KAMA.
Extract the implementation to retrieve it separately.
The text was updated successfully, but these errors were encountered: