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Python for Finance Cookbook

You're reading from  Python for Finance Cookbook

Product type Book
Published in Jan 2020
Publisher Packt
ISBN-13 9781789618518
Pages 432 pages
Edition 1st Edition
Languages
Author (1):
Eryk Lewinson Eryk Lewinson
Profile icon Eryk Lewinson

Table of Contents (12) Chapters

Preface Financial Data and Preprocessing Technical Analysis in Python Time Series Modeling Multi-Factor Models Modeling Volatility with GARCH Class Models Monte Carlo Simulations in Finance Asset Allocation in Python Identifying Credit Default with Machine Learning Advanced Machine Learning Models in Finance Deep Learning in Finance Other Books You May Enjoy

Investigating stylized facts of asset returns

Stylized facts are statistical properties that appear to be present in many empirical asset returns (across time and markets). It is important to be aware of them because when we are building models that are supposed to represent asset price dynamics, the models must be able to capture/replicate these properties.

In the following recipes, we investigate the five stylized facts using an example of daily S&P 500 returns from the years 1985 to 2018.

Getting ready

We download the S&P 500 prices from Yahoo Finance (following the approach in the Getting data from Yahoo Finance recipe) and calculate returns as in the Converting prices to returns recipe.

We use the following code...

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