What I Built
Analyzed UK financial market reactions to 36 verified Brexit-era regulatory announcements (2016–2020) across Banks, Insurance, and Financial Services sectors. Used econometric models including OLS regression, GARCH family volatility models (GARCH, EGARCH, GJR-GARCH), and Granger causality tests to measure impact on returns and volatility.
What I Learned
Volatility tells the real story. While OLS showed no direct effect on returns, GARCH models revealed that regulatory news significantly increased volatility, with asymmetric effects where negative shocks created stronger volatility spikes than positive news. Insurance sector showed the most persistent volatility, while banks recovered faster.
Also learned that Granger causality tests revealed regulatory announcements do predict future returns (lag 1), confirming market efficiency isn’t perfect during uncertain periods.
Project
Methods Used: OLS Regression, GARCH/EGARCH/GJR-GARCH, Granger Causality | Data: FTSE 350, 36 regulatory events
Citation
@online{prasanna_koppolu,
author = {Prasanna Koppolu, Bhanu and Sakthivinayagam, Santhosh and
Shambhunath Kanojiya, Akash and D. Gupta, Shyam},
title = {Market {Reaction} to {Regulatory} {Changes} in the {UK}},
url = {https://bhanuprasanna2001.github.io/projects/market_brexit_analysis.html},
langid = {en}
}