动态因子、杠杆与多元随机波动率的已实现协方差
Dynamic factor, leverage and realized covariances in multivariate stochastic volatility
摘要：
在多变量股票日收益率的随机波动模型中，人们发现随着收益率维数的增加，参数的估计变得不稳定。为了解决这个问题，我们专注于多重收益的因子结构，并考虑两个额外的信息来源：第一，与市场因子相关的已实现股票指数，第二，从高频数据计算的已实现协方差矩阵。建议的动态因子模型与杠杆效应和实现的措施，适用于十大股票组成的交易所交易基金与SP500指数的投资回报挂钩，该模型被证明有一个稳定的优势，在投资组合的表现。
英文摘要：
In the stochastic volatility models for multivariate daily stock returns, it has been found that the estimates of parameters become unstable as the dimension of returns increases. To solve this problem, we focus on the factor structure of multiple returns and consider two additional sources of information: first, the realized stock index associated with the market factor, and second, the realized covariance matrix calculated from high frequency data. The proposed dynamic factor model with the leverage effect and realized measures is applied to ten of the top stocks composing the exchange traded fund linked with the investment return of the SP500 index and the model is shown to have a stable advantage in portfolio performance.
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