European Conference Proceedings

研报英文原文证据摘录

European Conference Proceedings

MayMay 19,19, 20262026

SPEAKER PRESENTATIONS

VOLATILITY FORECASTING FACTORS

Presenter: Ingmar Nolte

Institution: Professor of Finance and Econometrics, Lancaster University

Biography: Ingmar Nolte is Professor of Finance and Econometrics at Lancaster

University and Director of the Centre for Financial Econometrics, Asset

Markets and Macroeconomic Policy. He obtained his PhD in Econometrics

from the University of Konstanz, Germany in 2008 and held positions at the

University of Warwick before joining Lancaster in 2013. His current research

interests include volatility modelling using high-frequency data, factor and

next generation investing, signal extraction using machine learning

methods as well as research in climate finance such as the carbon risk

premia. His research has been published widely including in journals such

as the Journal of Econometrics, Journal of Business and Economic Statistics,

Journal of Financial Econometrics and Journal of Financial and Quantitative

Analysis.

Original Paper: • Volatility Forecasting Factors

Presentation: • Presentation Slides

Key Takeaways: • The paper asks whether equity volatility can be forecast more

accurately by treating it as a multivariate, factor-driven process

rather than a stock-by-stock univariate one, motivated by the

observation that existing HAR-family models ignore the rich cross-

sectional co-movement documented in realized variances across the

Fama-French factor zoo.

• The sample covers 5,370 U.S. common stocks listed on NYSE,

NASDAQ, and AMEX from 2014 to 2023, constructed from NYSE

TAQ millisecond tick data sampled on 1-second grids, yielding

approximately 320 billion data points, and supplemented by a high-

frequency factor zoo of 6 Fama-French factors plus 281 characteristic