Fat Tails
Python package and Jupyter notebooks for fat-tailed statistics. Inspired by Nassim Taleb's Technical Incerto.
Content
Notebooks
See the notebooks/README.md for more detail.
My favourite notebooks so far:
- Central Limit Theorem: How the sum of Uniform values is Gaussian
- S&P500: How geometric average return is impossible
- GameStop: January 2021 was not an outlier if you assume Power Law tails.
Functions
Quick Access:
-
fattails.mad(): Calculates mean absolute deviation. -
fattails.plot_MS_moments(): Plots the cumulative max/sum ratio of moments 1 to 4.
Other:
-
fattails.metrics.get_survival_probability(): Calculate survival probabilities for a given dataset. -
fattails.metrics.calculate_moments(): Generate dataframe with the chosen moments for each datapoint -
fattails.metrics.max_over_sum(): Calculate the cumulative max/sum ratio
Example:
$ pip install fattails
$ python
>>> import fattails
>>>
>>>
>>> fattails.mad([1,2,3]) # Calculate Mean Absolute Deviation of [1,2,3]
0.6666666666666666
>>>
>>>
>>> fattails.metrics.get_survival_probability([1,2,3]) # Get survival probability for each value in your data
0 0.75
1 0.50
2 0.25
Name: survival_probability, dtype: float64
Derivations
Contact
Jump straight to discussions or check out the contributing guidelines. Feedback and suggestions are really appreciated!
Contributors
Special thanks to:
- Daniel Reti: github.com/drettt
External Resources
Technical Incerto Book One:
- Free PDF: researchers.one, arxiv.org
- Errata: fooledbyrandomness.com
More Links:
- Incerto Reading Club: Website, GitHub
-
StatisticalConsequencesOfFatTails: Code and Links collected by Marcos Carreira
