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EM-algorithm is developed for estimation. Each element of the vector return at time t is endowed with a common univariate … volatility, but without the estimation problems associated with the latter, and being applicable in the multivariate setting for …
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This paper considers an institutional investor who is implementing a long-term portfolio allocation strategy using forecasts of financial returns. We compare the performance of two competing macro-finance models, an unrestricted Vector AutoRegression (VAR) and a fully structural Dynamic...
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This paper studies the predictability of ultra high-frequency stock returns and durations to relevant price, volume and transactions events, using machine learning methods. We find that, contrary to low frequency and long horizon returns, where predictability is rare and inconsistent,...
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