Investigating stylized facts of asset returns
Stylized facts are statistical properties that are 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 should be able to capture/replicate these properties.
In this recipe, we investigate the five stylized facts using an example of daily S&P 500 returns from the years 2000 to 2020.
Getting ready
As this is a longer recipe with further subsections, we import the required libraries and prepare the data in this section:
- Import the required libraries:
import pandas as pd import numpy as np import yfinance as yf import seaborn as sns import scipy.stats as scs import statsmodels.api as sm import statsmodels.tsa.api as smt
- Download the S&P 500 data and calculate the returns:
df = yf.download("^GSPC", start...