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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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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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Alternative strategies for predicting stock market volatility are examined. In out-of-sample forecasting experiments implied-volatility information, derived from contemporaneously observed option prices or history-based volatility predictors, such as GARCH models, are investigated, to determine...
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