top of page

Your certificate is now private

CertificateBackground.png

Certificate of Completion

ErdosHorizontal.png

THIS ACKNOWLEDGES THAT

HAS COMPLETED THE SPRING 2023 DATA SCIENCE BOOT CAMP

Palak Arora

Roman Holowinsky, PhD

JUNE 07, 2023

DIRECTOR

DATE

clear.png

TEAM

Forecasting Stock Volatility

George Mitchell, Waleed Ahmed, Thomas Polstra, Cameron Cinel, Yifan Wu, Palak Arora

clear.png

Volatility is a measure of a stock price's uncertainty and is used throughout quant finance, for instance in pricing options. However, volatility is not something that is easily observed in the market, and requires estimation techniques.
I propose a project where we forecast a stock's next-day (or next-month) volatility from the previous day's (month) volatility. We would use some high frequency data (possibly minute-by-minute prices scraped from yfinance) and use the data to train an auto-regressive (AR) model for volatility. We could also use other machine learning techniques to produce other forecasting models and compare them with the AR model.

Screen Shot 2022-06-03 at 11.31.35 AM.png
github URL
bottom of page