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We propose a Conditional Autoregressive Wishart (CAW) model for the analysis of realized covariance matrices of asset returns. Our model assumes a generalized linear autoregressive moving average structure for the scale matrix of the Wishart distribution allowing to accommodate for complex...
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This chapter builds on previous work by Bhardwaj and Swanson (2004) who address the notion that many fractional I(d) processes may fall into the empty boxʺ category, as discussed in Granger (1999). However, rather than focusing primarily on linear models, as do Bhardwaj and Swanson, we analyze...
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We develop likelihood-based tests for autocorrelation and predictability in a first order non-Gaussian and noninvertible ARMA model. Tests based on a special case of the general model, referred to as an all-pass model, are also obtained. Data generated by an all-pass process are uncorrelated...
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