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the classic empirical asset pricing problem as a machine learningclassification problem. We construct classification …
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We demonstrate that the parameters controlling skewness and kurtosis in popular equity return models estimated at daily frequency can be obtained almost as precisely as if volatility is observable by simply incorporating the strong information content of realized volatility measures extracted...
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The NP-hard nature of cardinality constrained mean-variance portfolio optimization problems has led to a variety of different algorithms with varying degrees of success in reaching optimality given limited computational resources and under the presence of strict time constraints in practice. The...
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This technical note proves a simple mathematical relationship between the return on assets (ROA) of financial accounting standards and the return on investments (ROI) of investment performance standards. We show why this relationship is needed by users of APRA data to convert ROA to ROI for...
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We study mean-variance hedging under portfolio constraints in a general semimartingale model. The constraints are formulated via predictable correspondences, meaning that the trading strategy is restricted to lie in a closed convex set which may depend on the state and time in a predictable way....
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