# 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
`quotes`

provided. `FisherTransformResults`

is just a list of`FisherTransformResult`

.- 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+15`

warmup 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] 💬