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A discrete-time model for daily S & P500 returns and realized variations: Jumps and leverage effects

机译:S&P500每日收益和已实现变化的离散时间模型:跳跃和杠杆效应

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摘要

We develop an empirically highly accurate discrete-time daily stochastic volatility model that explicitly distinguishes between the jump and continuous-time components of price movements using nonparametric realized variation and Bipower variation measures constructed from high-frequency intraday data. The model setup allows us to directly assess the structural inter-dependencies among the shocks to returns and the two different volatility components. The model estimates suggest that the leverage effect, or asymmetry between returns and volatility, works primarily through the continuous volatility component. The excellent fit of the model makes it an ideal candidate for an easy-to-implement auxiliary model in the context of indirect estimation of empirically more realistic continuous-time jump diffusion and Levy-driven stochastic volatility models, effectively incorporating the interdaily dependencies inherent in the high-frequency intraday data.
机译:我们开发了一种经验高度准确的离散时间每日随机波动率模型,该模型使用非参数实现的变差和从高频日内数据构造的Bipower变差指标来明确区分价格变动的跳跃和连续时间部分。该模型设置使我们可以直接评估收益冲击和两个不同波动率成分之间的结构相互依赖性。该模型估计表明,杠杆效应或收益率和波动率之间的不对称性主要通过持续波动率成分起作用。该模型的出色拟合使其成为易于实现的辅助模型的理想候选者,可以间接估算经验上更现实的连续时间跳跃扩散和Levy驱动的随机波动率模型,从而有效地整合了内部固有的日间依存关系。高频日内数据。

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