Rosati, Emanuele (A.A. 2024/2025) Intraday volatility patterns in equity index futures: a statistical analysis using high-frequency data with a trading application. Tesi di Laurea in Big data and smart data analytics, Luiss Guido Carli, relatore Irene Finocchi, pp. 52. [Master's Degree Thesis]

Full text for this thesis not available from the repository.

Abstract/Index

Literature review and theoretical framework. Volatility in financial markets: definitions and stylized facts. Aggregate volatility models. High-frequency data and realized volatility measures. Temporal and seasonal patterns in volatility. Volatility and trading strategies: from theory to practice. Data and volatility measures. Dataset description. Trading sessions and time conventions. Data preprocessing and return construction. Volatility measures. Statistical methodology. Definition of intraday time intervals. How volatility is measured within each interval. Research questions. Regression model. Robustness procedures. Intraday volatility across broad market phases. Allocation of volatility within the trading day. Clock-time evidence at 5-minute frequency. Interval-based inference. Robustness checks.

References

Bibliografia: pp. 45-46.

Thesis Type:	Master's Degree Thesis
Institution:	Luiss Guido Carli
Degree Program:	Master's Degree Programs > Master's Degree Program in Data Science e Management (LM-91)
Chair:	Big data and smart data analytics
Thesis Supervisor:	Finocchi, Irene
Thesis Co-Supervisor:	Morandini, Lorenza
Academic Year:	2024/2025
Session:	Extraordinary
Deposited by:	Alessandro Perfetti
Date Deposited:	16 Sep 2026 12:06
Last Modified:	16 Sep 2026 12:06
URI:	https://tesi.luiss.it/id/eprint/46816

Downloads

Repository Staff Only

View Item