Event Study: A High-Frequency Approach: Econometrics
Author
Kvist, Olivia My Töffner
Term
4. term
Education
Publication year
2024
Pages
48
Abstract
This thesis develops a high-frequency event study framework to identify price jumps in equities around defined events. It consolidates contributions from the first two years of a 4+4 PhD program and introduces two papers that rely on the same theory for jump detection. Methodologically, it covers handling of high-frequency trade data, jump-robust realized volatility estimators, and the Lee and Mykland and the Barndorff-Nielsen and Shephard jump tests. A simulation study based on a jump-diffusion model with manually inserted jumps is used to verify that the price jump test captures the intended signals, showing sensitivity down to a certain jump magnitude. The approach is then applied to green and brown stocks around key moments during COP28, where price jumps are detected in all analyzed assets. The thesis concludes by outlining future research directions for the remaining PhD period.
Dette speciale udvikler en højfrekvent tilgang til eventstudier med fokus på at identificere prisspring i aktier omkring definerede begivenheder. Arbejdet samler bidrag fra de første to år af et 4+4 ph.d.-forløb og introducerer to artikler, der bygger på samme teori for springidentifikation. Metodisk behandles håndtering af højfrekvente handelsdata, springrobuste estimater af realiseret volatilitet samt Lee og Mykland- og Barndorff-Nielsen og Shephard-springtestene. En simulationsundersøgelse baseret på en jump-diffusionsmodel med manuelt indsatte spring bruges til at verificere, at prisspringtesten fanger de tilsigtede signaler, og den viser følsomhed ned til en vis springstørrelse. Tilgangen anvendes derefter på grønne og brune aktier omkring nøglehændelser under COP28, hvor der identificeres prisspring i alle analyserede aktier. Specialet afrundes med at skitsere mulige forskningsspor for den resterende ph.d.-periode.
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