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We consider the problem of ex-ante forecasting conditional correlation patterns using ultra high frequency data … correlation matrices and exogenous factors. The Fisher-z transformation guarantees robustness of correlation estimators under … prominent parametric and nonparametric alternatives to correlation modeling. Based on economic performance criteria, we …
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It is well known that the correlation between financial series varies over time. Here, the forecasting performance of … different time-varying correlation models is compared for cross-country correlations of weekly G5 and daily European stock … market indices. In contrast to previous studies only the correlation and not the entire covariance matrix is forecasted and …
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We compare the performance of popular covariance forecasting models in the context of a portfolio of major European equity indices. We find that models based on high-frequency data offer a clear advantage in terms of statistical accuracy. They also yield more theoretically consistent predictions...
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This paper proposes a latent dynamic factor model for low- as well as high-dimensional realized covariance matrices of stock returns. The approach is based on the matrix logarithm and allows for flexible dynamic dependence patterns by combining common latent factors driven by HAR dynamics and...
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