Abstract
This article investigates several crucial issues that arise when modeling equity returns with stochastic variance. (i) Does the model need to include jumps even when using a nonaffine variance specification? We find that jump models clearly outperform pure stochastic volatility models. (ii) How do affine variance specifications perform when compared to nonaffine models in a jump diffusion setup? We find that nonaffine specifications outperform affine models, even after including jumps.
Data source: Index return data from CRSP
Data source: Index return data from CRSP
Original language | English |
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Pages (from-to) | 68-75 |
Number of pages | 8 |
Journal | Journal of Business & Economic Statistics |
Volume | 33 |
Issue number | 1 |
DOIs | |
Publication status | Published - 2 Jan 2015 |
Keywords
- Deviance information criteria
- Bayesian inference
- Stochastic volatility
- Markov chain Monte Carlo
- STOCHASTIC VOLATILITY MODELS
- CONTINUOUS-TIME MODELS
- BAYESIAN-ANALYSIS
- OPTION PRICES
- DYNAMICS
- RETURNS
- MARKETS
- SPOT