<jupyter_start><jupyter_text>For this notebook, I have just created some examples and wrapped the IEX functions so that they are as easy as possible to use in order to use thse functions it will be necessary to get an IEX API key from their website and put the value in a .env file in the root of the project or specify it in the notebook<jupyter_code>import numpy as np
import pandas as pd

df = pd.DataFrame({'volatility':np.arange(.15,.25,0.001)})
#df['volatility'] = df.vol/100
#df['call_price'],df['put_price'] =
df['bs'] = df['volatility'].map(lambda x: BlackSholes(166.36, 175, x, 0.017,'1/15/2021'))
df[['call_price','put_price']] = pd.DataFrame(df['bs'].tolist(),index=df.index)
df.drop(columns=['bs'],inplace=True)
df.plot(x="volatility",kind='line')




df<jupyter_output><empty_output>
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{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '611710', 'license': 'MIT', 'n_tokens_mistral': 298, 'n_tokens_neox': 269, 'n_words': 87, 'path': 'notebooks/black-sholes.ipynb', 'repo_name': 'MLDERES/isys599v', 'size': '797'}