01_mainModelComplexitySP500.pdf (3.55 MB)
Model complexity and out-of-sample performance: evidence from S&P 500 index returns
journal contribution
posted on 2023-06-09, 11:47 authored by Andreas KaeckAndreas Kaeck, Paulo Rodrigues, Norman SeegerWe apply a range of out-of-sample specification tests to more than forty competing stochastic volatility models to address how model complexity affects out-of-sample performance. Using daily S&P 500 index returns, model confidence set estimations provide strong evidence that the most important model feature is the non-affinity of the variance process. Despite testing alternative specifications during the turbulent market regime of the global financial crisis of 2008, we find no evidence that either finite- or infinite-activity jump models or other previously proposed model extensions improve the out-of-sample performance further. Applications to Value-at-Risk demonstrate the economic significance of our results. Furthermore, the out-of-sample results suggest that standard jump diffusion models are misspecified.
History
Publication status
- Published
File Version
- Accepted version
Journal
Journal of Economic Dynamics and ControlISSN
0165-1889Publisher
ElsevierExternal DOI
Volume
90Page range
1-29Department affiliated with
- Accounting and Finance Publications
Research groups affiliated with
- Quantitative International Finance Network Publications
Full text available
- Yes
Peer reviewed?
- Yes
Legacy Posted Date
2018-01-26First Open Access (FOA) Date
2020-02-05First Compliant Deposit (FCD) Date
2018-01-26Usage metrics
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