How market capitalization-weighted index ETFs influence the volatility of underlying securities in the European market

Details

Supervisors

Iania, Leonardo

Faculty

Louvain School of Management

Degree label

Master [120] : ingénieur de gestion, à finalité spécialisée

Abstract

enThis thesis adopts a quantitative, deductive, and data-driven approach to examine the impact of ETF inclusion on the volatility of underlying stocks, with a particular focus on the European market. Using historical financial data and a time-series econometric framework, the study explores whether inclusion in major ETFs, particularly those tracking the EURO STOXX 50, structurally influences stock volatility, thus potentially amplified by trading volume. The analysis is conducted in Python. It leverages econometric modeling techniques, specifically the GARCH family of models, to capture the time-varying nature of volatility. A key component of the methodology is the incorporation of ETF exposure and trading volume as external variables of volatility dynamics. Finally, additional OLS regressions are conducted to validate and complement the findings from the GARCH models, to provide further evidence on the explanatory role of ETF inclusion and trading volume in influencing stock volatility. These modeling choices are derived from a literature review that reviews the Efficient Market Hypothesis, theories of market structure, and prior empirical research linking liquidity, volume and volatility. To validate the findings, the study employs robust model diagnostics, comparative analysis, and multiple specifications, maintaining a flexible and exploratory framework while remaining theoretically informed.