Improving Score-Driven Density Forecasts with an Application to Implied Volatility Surface Dynamics

Xia Zou, Yicong Lin and André Lucas
Additional contact information
Xia Zou: Vrije Universiteit Amsterdam and Tinbergen Institute
Yicong Lin: Vrije Universiteit Amsterdam and Tinbergen Institute
André Lucas: Vrije Universiteit Amsterdam and Tinbergen Institute

No 25-036/III, Tinbergen Institute Discussion Papers from Tinbergen Institute

Abstract: Point forecasts of score-driven models have been shown to behave at par with those of state-space models under a variety of circumstances. We show, however, that density rather than point forecasts of plain-vanilla score-driven models substantially underperform their state-space counterparts in a factor model context. We uncover the origins of this phenomenon and show how a simple adjustment of the measurement density of the score-driven model can put score-driven and state-space models approximately back on an equal footing again. The score-driven models can subsequently easily be extended with non-Gaussian features to fit the data even better without complicating parameter estimation. We illustrate our findings using a factor model for the implied volatility surface of S&P500 index options data.

JEL-codes: C32 C38 (search for similar items in EconPapers)
Date: 2025-05-30
New Economics Papers: this item is included in nep-ets and nep-rmg
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://papers.tinbergen.nl/25036.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:tin:wpaper:20250036

Access Statistics for this paper

More papers in Tinbergen Institute Discussion Papers from Tinbergen Institute Contact information at EDIRC.
Bibliographic data for series maintained by Tinbergen Office +31 (0)10-4088900 ().