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This paper introduces a multivariate kernel based forecasting tool for the prediction of variance-covariance matrices of stock returns. The method introduced allows for the incorporation of macroeconomic variables into the forecasting process of the matrix without resorting to a decomposition of...
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Mt of the realized semicovariance. DRD decomposition is carried out for Pt to obtain the realized volatility matrix Dt …+ and the realized correlation matrix Rt+. We construct a deep-learning long short-term memory (LSTM) model to predict Dt …
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