Template-Type: ReDIF-Paper 1.0
Series: Tinbergen Institute Discussion Papers
Creation-Date: 2025-05-30 
Number: 25-036/III
Author-Name: Xia Zou
Author-Workplace-Name: Vrije Universiteit Amsterdam and Tinbergen Institute
Author-Name: Yicong Lin
Author-Workplace-Name: Vrije Universiteit Amsterdam and Tinbergen Institute
Author-Name: André Lucas
Author-Workplace-Name: Vrije Universiteit Amsterdam and Tinbergen Institute
Title: Improving Score-Driven Density Forecasts with an Application to Implied Volatility Surface Dynamics
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.
Classification-JEL: C32, C38
Keywords:
File-URL: https://papers.tinbergen.nl/25036.pdf
File-Format: application/pdf
File-Size: 1.367.298 bytes
Handle: RePEc:tin:wpaper:20250036