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Computational Finance 1 Lab Exercises

Welcome to the "Computational Finance 1 Lab Exercises" repository. This collection includes Jupyter Python notebooks covering various topics in computational finance. Explore the notebooks to gain insights into key concepts related to implied volatility, random number generators, SDE simulation in option pricing, and trinomial tree.

Notebook List:

  1. Implied Volatility.ipynb: Understand and analyze implied volatility in option pricing.

  2. Random Number Generators.ipynb: Explore the role of random number generators in computational finance.

  3. SDE Simulation in Option Pricing.ipynb: Implement simulations of Stochastic Differential Equations (SDE) for option pricing.

  4. Trinomial Tree.ipynb: Learn and apply the trinomial tree method in financial option pricing.

Feel free to delve into each notebook to enhance your understanding of computational finance concepts.

Usage

To run these Jupyter notebooks, make sure you have Python and Jupyter installed on your system. You can install Jupyter using:

pip install jupyter

Navigate to the specific notebook's file and execute the following command:

jupyter notebook notebook_name.ipynb

Replace notebook_name.ipynb with the desired notebook's file name.

Happy exploring! 📊📈