type="main" xml:id="jtsa12100-abs-0001"This article proves consistency and asymptotic normality for the conditional-sum-of-squares estimator, which is equivalent to the conditional maximum likelihood estimator, in multivariate fractional time-series models. The model is parametric and quite...

type="main" xml:id="jtsa12093-abs-0001"Recent work in the literature has shown weighted variants of the classic portmanteau test for time series can be more powerful in many situations. In this article, we study the asymptotic distribution of weighted sums of the squared residual...

type="main" xml:id="jtsa12102-abs-0001"This article advances the theory and methodology of signal extraction by developing the optimal treatment of difference stationary multivariate time-series models. Using a flexible time-series structure that includes co-integrated processes, we derive and...

type="main" xml:id="jtsa12091-abs-0001"In this article, we propose a new joint portmanteau test for checking the specification of parametric conditional mean and variance functions of linear and nonlinear time-series models. The use of a joint test is motivated for complete control of the...

type="main" xml:id="jtsa12086-abs-0001"The notion of multivariate long-range dependence is reexamined here from the perspectives of time and spectral domains. The role of the so-called phase parameters is clarified and stressed throughout. In particular, examples of causal (one-sided)...

type="main" xml:id="jtsa12098-abs-0001"Many empirical findings show that volatility in financial time series exhibits high persistence. Some researchers argue that such persistency is due to volatility shifts in the market, while others believe that this is a natural fluctuation explained by...

type="main" xml:id="jtsa12074-abs-0001" <title type="main">Abstract</title> <p>We provide a fast algorithm for calculating the fractional difference of a time series. In standard implementations, the calculation speed (number of arithmetic operations) is of order T-super-2, where T is the length of the time series. Our...</p>