Ehlers Fisher Transform
get_fisher_transform(quotes, lookback_periods=10)
Parameters
| name | type | notes |
|---|---|---|
quotes | Iterable[Quote] | Iterable of the Quote class or its sub-class. • See here for usage with pandas.DataFrame |
lookback_periods | int, default 10 | Number of periods (N) in the lookback window. Must be greater than 0. |
Historical quotes requirements
You must have at least N periods of quotes to cover the warmup periods.
quotes is an Iterable[Quote] collection of historical price quotes. It should have a consistent frequency (day, hour, minute, etc). See the Guide for more information.
Return
FisherTransformResults[FisherTransformResult]
- This method returns a time series of all available indicator values for the
quotesprovided. FisherTransformResultsis just a list ofFisherTransformResult.- It always returns the same number of elements as there are in the historical quotes.
- It does not return a single incremental indicator value.
⚞ Convergence warning: The first
N+15warmup periods will have unusable decreasing magnitude, convergence-related precision errors that can be as high as ~25% deviation in earlier indicator values.
FisherTransformResult
| name | type | notes |
|---|---|---|
date | datetime | Date |
fisher | float, Optional | Fisher Transform |
trigger | float, Optional | FT offset by one period |
Utilities
For pruning of warmup periods, we recommend using the following guidelines:
indicators.get_fisher_transform(quotes, lookback_periods)
.remove_warmup_periods(lookback_periods + 15)
See Utilities and Helpers for more information.
Example
from stock_indicators import indicators
# This method is NOT a part of the library.
quotes = get_historical_quotes("SPY")
# Calculate 10-period FisherTransform
results = indicators.get_fisher_transform(quotes, 10)
About Ehlers Fisher Transform
Created by John Ehlers, the Fisher Transform converts prices into a Gaussian normal distribution. [Discuss] 💬
