Multivariate continuous-time models have been playing important roles in finance and economics. We develop an omnibus specification test for multivariate continuous-time models using the conditional characteristic function, which often has a convenient closed form or can be accurately...

We propose a test for invertibility or fundamentalness of structural vector autoregressive moving average models generated by non-Gaussian independent and identically distributed (iid) structural shocks. We prove that in these models and under some regularity conditions the Wold innovations are...

We propose a test for invertibility or fundamentalness of structural vector autoregressive moving average models generated by non-Gaussian independent and identically distributed structural shocks. We prove that in these models and un- der some regularity conditions the Wold innovations are a...

We propose two nonparametric transition density-based speciÞcation tests for continuous-time diffusion models. In contrast to marginal density as used in the literature, transition density can capture the full dynamics of a diffusion process, and in particular, can distinguish processes with...

Wavelet analysis is a new mathematical tool developed as a unified field of science over the last decade. As spatially adaptive analytic tools, wavelets are useful for capturing serial correlation where the spectrum has peaks or kinks, as can arise from persistent/strong dependence, seasonality...

This paper proposes an adjusted-range based self-normalization method to construct confidence intervals for censored dependent data, which helps to circumvent the long-run variance estimation and tuning parameter selection problems. Simulation studies confirm the validity of this new approach