Skip to content

This project implements a script to calculate an option price using the Black-Scholes model.

Notifications You must be signed in to change notification settings

SantiagoMorenoV/Black_Scholes_Apple_Stock_Option_Price

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

10 Commits
 
 
 
 
 
 

Repository files navigation

Apple Stock Option Price Valuation with Black-Scholes

Business Problem

The goal of this project is to implement the Black-Scholes equation to determine an option's strike price using Apple Stock's time series data from 2022-05-03 to 2023-05-03. The project calculates the daily returns as a logarithmic difference, the stock's volatility, and determines the call option value based on the user's input.

Stock Market

Libraries used

This project is implemented using the following Python libraries:

pandas numpy matplotlib seaborn scipy outlier-utils

Dataset

The dataset used in this project is the Apple Stock time series from 2022-05-03 to 2023-05-03. The dataset is available in a CSV format, which is loaded using the pandas library.

How to use the code

The user is free to use this code for their purposes. To calculate the call option value, the user needs to input the strike price, the time to expiration in years, and the risk-free rate.

Contributions

Contributions to this repository are welcome. If you find a bug or have suggestions for improvement, please open an issue or submit a pull request.

Results

Based on the upward trend of the Apple Stock and evaluating the strike price, time to expiration, and the risk-free rate, the option to buy a share within the month would be $7.90 per share.

Note: If the Colab notebook is not being displayed, please copy the URL and paste it on nbviewer so you can see the code.

Credits

This project was created by Santiago Moreno Velasquez.