Ehlers Fisher Transform

get_fisher_transform(quotes, lookback_periods=10)


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.



Convergence warning: The first N+15 warmup periods will have unusable decreasing magnitude, convergence-related precision errors that can be as high as ~25% deviation in earlier indicator values.


name type notes
date datetime Date
fisher float, Optional Fisher Transform
trigger float, Optional FT offset by one period


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.


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] 💬