January 2020
Beginner to intermediate
432 pages
11h 24m
English
Content preview from Python for Finance Cookbook
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How to do it...
Execute the following steps to implement the CAPM in Python.
- Import the libraries:
import pandas as pdimport yfinance as yfimport statsmodels.api as sm
- Specify the risky asset and the time horizon:
RISKY_ASSET = 'AMZN'MARKET_BENCHMARK = '^GSPC'START_DATE = '2014-01-01'END_DATE = '2018-12-31'
- Download the necessary data from Yahoo Finance:
df = yf.download([RISKY_ASSET, MARKET_BENCHMARK], start=START_DATE, end=END_DATE, adjusted=True, progress=False)
- Resample to monthly data and calculate the simple returns:
X = df['Adj Close'].rename(columns={RISKY_ASSET: 'asset', MARKET_BENCHMARK: 'market'}) \ .resample('M') \ .last() \ .pct_change() \ .dropna()
- Calculate beta using the covariance approach:
covariance = X.cov().iloc[0,1] ...
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