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distribution theory for a generalized multiscale estimator including a feasible central limit theorem with optimal convergence rate …
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We devise a new high-frequency covariance matrix estimator based on price durations which is guaranteed to be positive-definite. Both non-parametric and parametric versions are proposed. A comprehensive Monte Carlo simulation shows that this class of estimators are less biased, more efficient,...
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correlation models are introduced depending on how the time-varying covariance matrix is formulated and whether or not it is a … basic models enable the study of the long memory properties of dynamic correlations, threshold correlation effects and …
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We formulate a bivariate stochastic volatility jump-diffusion model with correlated jumps and volatilities. An MCMC Metropolis-Hastings sampling algorithm is proposed to estimate the model's parameters and latent state variables (jumps and stochastic volatilities) given observed returns. The...
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