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We introduce an ensemble learning method based on Gaussian Process Regression (GPR) for predicting conditional expected …
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We explore the performance of mixed-frequency predictive regressions for stock returns from the perspective of a Bayesian investor. We develop a constrained parameter learning approach for sequential estimation allowing for belief revisions. Empirically, we find that mixed-frequency models...
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trades with each counterparty under both market and credit risk. We present a multi-Gaussian process regression approach … simulation or simulation and regression of cash flows by learning a Gaussian metamodel for the mark-to-market cube of a …
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