January 2020
Beginner to intermediate
432 pages
11h 24m
English
Content preview from Python for Finance Cookbook
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How it works...
In Step 2, we defined parameters used for this recipe, such as the considered timeframe, the risky assets we wanted to use for building the portfolio, and the number of simulations. An important thing to note here is that we also ran RISKY_ASSETS.sort(), to sort the list alphabetically. This matters when interpreting the results as when downloading data from Yahoo Finance using the yfinance library, the obtained prices are ordered alphabetically, not as specified in the provided list. Having downloaded the stock prices, we calculated simple returns using the pct_change method of a pandas DataFrame, and dropped the first row containing NaNs.
For evaluating the potential portfolios, we needed the average (expected) annual return ...
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