Presentation and notebook for the lightning talk A Quick Intro to Hidden Markov Models Applied to Stock Volatility presented in R/Finance 2017.
-
Updated
May 18, 2017 - HTML
#
volatility
Here are 5 public repositories matching this topic...
Public repo of some of my options modeling projects
-
Updated
Jan 7, 2024 - Jupyter Notebook
Quantitative Finance, Financial Machine Learning and visualizations Notebooks
-
Updated
Sep 17, 2019 - Jupyter Notebook
This repository holds 2 Jupyter notebooks and one csv file on Time Series analysis for the A Yen for the Future exercises. The purpose of this code is to demonstrate understanding of time series work in Python: ARMA, ARIMA and related concepts.
-
Updated
Feb 11, 2022 - Jupyter Notebook
In this project, I implement the Black & Scholes model to price options and analyze their Greeks, including Delta, Gamma, Theta, Vega, and Rho, along with implied volatility. The repository features interactive Jupyter notebooks and practical examples to help you understand how these concepts apply in real-world scenarios.
-
Updated
Aug 25, 2024 - Jupyter Notebook
Improve this page
Add a description, image, and links to the volatility topic page so that developers can more easily learn about it.
Add this topic to your repo
To associate your repository with the volatility topic, visit your repo's landing page and select "manage topics."