Density forecasts and the leverage effect: Evidence from Observation and parameter-Driven volatility models

Leopoldo Catania, Nima Nonejad*

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

4 Citations (Scopus)

Abstract

The leverage effect refers to the well-known relationship between returns and volatility for an equity. When returns fall, volatility increases. We evaluate the role of the leverage effect with regards to generating density forecasts of equity returns using well-known observation and parameter-driven conditional volatility models. These models differ in their assumptions regarding: The parametric specification, the evolution of the conditional volatility process and how the leverage effect is specified. The ability of a model to generate accurate density forecasts when the leverage effect is incorporated or not as well as a comparison between different model-types is analyzed using a large number of financial time series. For each model type, the specification with the leverage effect tends to generate more accurate density forecasts than its no-leverage counterpart. Among the specifications considered, the Beta-t-EGARCH model is the top performer, regardless of whether we attach the same weight to each region of the conditional distribution or emphasize the left tail.

Original languageEnglish
JournalEuropean Journal of Finance
Volume26
Issue number2-3
Pages (from-to)100-118
Number of pages19
ISSN1351-847X
DOIs
Publication statusPublished - 11 Feb 2020

Bibliographical note

Publisher Copyright:
© 2019, © 2019 Informa UK Limited, trading as Taylor & Francis Group.

Keywords

  • Conditional volatility
  • density forecasts
  • leverage effect
  • wCRPS

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