| |
| import yfinance as yf |
| import pandas as pd |
| import numpy as np |
| from datetime import datetime, date |
| def data_option(ticker, date, option_type,size_of_the_window=4): |
| |
|
|
| ''' |
| El ticker es un string |
| la fecha es un string en formato 'yyyy-mm-dd' |
| el tipo de opción es un string 'call' o 'put' por defecto se mostrará el de call |
| ''' |
|
|
| |
| price = yf.Ticker(ticker).info['regularMarketPrice'] |
|
|
| data = yf.Ticker(ticker).option_chain(date).puts.iloc[:, [0, 2, 3, 8, 10, 11, 13]] if option_type == 'put' else yf.Ticker(ticker).option_chain(date).calls.iloc[:, [0, 2, 3, 8, 10, 11, 13]] |
| data['impliedVolatility'] = data['impliedVolatility'].apply(lambda x: f"{x*100:.2f}%") |
| |
|
|
| data = data.sort_values(by='strike', key=lambda x: abs(x - price)) |
|
|
| price_row = pd.DataFrame([['░░░░░░░ Spot Price ░░░░░░░', price,'░░░░░░░░░░░░░░','░░░░░░░░░░','░░░░░░░░░░░░░░░░░░','░░░░░░░░░░░','░░░░░░░░░░']], columns= data.columns) |
| date_row = pd.DataFrame([[f"▓▓▓▓▓▓▓ {date} ▓▓▓▓▓▓▓",'▓▓▓▓▓▓▓','▓▓▓▓▓▓▓▓▓▓▓▓▓▓','▓▓▓▓▓▓▓▓▓▓', '▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓', '▓▓▓▓▓▓▓▓▓▓▓','▓▓▓▓▓▓▓▓▓▓']],columns = data.columns) |
| data = pd.concat( [data.head(size_of_the_window), price_row]).sort_values(by='strike') |
| data = pd.concat([date_row, data]) |
|
|
| return pd.DataFrame(data) |
| |
|
|
|
|
