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英文文献：A Reduced Form Framework for Modeling Volatility of Speculative Prices based on Realized Variation Measures-基于已实现的变化措施的投机性价格波动建模的简化形式框架
英文文献作者：Torben G. Andersen,Tim Bollerslev,Xin Huang
英文文献摘要：
Building on realized variance and bi-power variation measures constructed from high-frequency financial prices, we propose a simple reduced form framework for effectively incorporating intraday data into the modeling of daily return volatility. We decompose the total daily return variability into the continuous sample path variance, the variation arising from discontinuous jumps that occur during the trading day, as well as the overnight return variance. Our empirical results, based on long samples of high-frequency equity and bond futures returns, suggest that the dynamic dependencies in the daily continuous sample path variability is well described by an approximate long-memory HAR-GARCH model, while the overnight returns may be modelled by an augmented GARCH type structure. The dynamic dependencies in the non-parametrically identified significant jumps appear to be well described by the combination of an ACH model for the time-varying jump intensities coupled with a relatively simple log-linear structure for the jump sizes. Lastly, we discuss how the resulting reduced form model structure for each of the three components may be used in the construction of out-of-sample forecasts for the total return volatility.
基于由高频金融价格构建的已实现的方差和双幂变异测度，我们提出了一个简单的简化形式框架，以有效地将日内数据纳入每日回报波动的模型。我们将总日收益率变异性分解为连续样本路径方差、交易日内发生的不连续跳跃引起的变异以及隔夜收益率方差。我们的实证结果，基于高频股票和债券期货收益的长样本，表明日连续样本路径变异性的动态依赖性可以用一个近似的长记忆haro -GARCH模型来描述，而隔夜收益可以用一个增广GARCH型结构来建模。非参数确定的显著跳跃中的动态依赖关系似乎可以通过对时变跳跃强度的ACH模型与跳跃大小相对简单的对数线性结构的组合来很好地描述。最后，我们将讨论如何将三个组成部分的简化模型结构用于构建总收益波动率的样本外预测。
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