What I Built
Analyzed UK financial market reactions to 36 verified Brexit-era regulatory announcements (2016–2020) across Banks, Insurance, and Financial Services sectors. Applied OLS regression, GARCH family volatility models (GARCH, EGARCH, GJR-GARCH), and Granger causality tests to quantify the impact on returns and volatility.
What I Learned
Volatility tells the real story. OLS showed no direct effect on returns, but GARCH models revealed regulatory news significantly increased volatility with asymmetric effects — negative shocks created stronger spikes than positive news. Insurance showed the most persistent volatility while banks recovered faster. Granger causality confirmed announcements predict future returns at lag 1, exposing inefficiencies during uncertain periods.
Key Results
| Finding | Detail |
|---|---|
| OLS on returns | No significant direct effect |
| GARCH volatility | Regulatory news significantly increases volatility |
| Asymmetric effects | Negative shocks > positive shocks (EGARCH, GJR-GARCH) |
| Granger causality | Announcements predict returns at lag 1 |
| Most affected sector | Insurance (most persistent volatility) |
Project
Tech Stack: Python, GARCH/EGARCH/GJR-GARCH, OLS, Granger Causality | Data: FTSE 350, 36 regulatory events (2016–2020)
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}
}