Forecasting Equity Volatility Dynamics with Markov-Switching EGARCH Models

Understanding and anticipating stock market volatility enables better portfolio management. We forecast US equity volatility with a Markov-Switching EGARCH model with one high and one low volatility regime. We show that this model contains similar information about future volatility as the VIX Index. It also outperforms single-regime GARCH and EGARCH models. Moreover, the model’s 1-day ahead regime predictions are economically significant: market volatility and kurtosis, equity risk premia, and stock-bond relations shift when the model forecasts a regime change.

Name thesis:degree_name

Master

Department dc:contributor.department

Sloan School of Management

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2024

Author dc:creator

• Dennis-Sharma, Tyson

Advisor dc:contributor.advisor

• Kogan, Leonid

Statement dc:rights

• In Copyright - Educational Use Permitted
• Copyright retained by author(s)

Licence dc:rights.uri

• https://rightsstatements.org/page/InC-EDU/1.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/153697

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/153697