This paper investigates the causal relations between stock return and volume based on quantile regressions. We first define Granger non-causality in all quantiles and propose testing non-causality by a sup-Wald test. Such a test is consistent against any deviation from non-causality in...

We demonstrate that in time trend models, the likelihood-based tests of partial parameter stability have size distortions and cannot be applied to detect the changing pa-rameter. A two-step procedure is then proposed to distinguish between different trend-break models. This procedure involves...

In this paper, we reexamine the permanent income-consumption relationship analytically and empirically, based on the innovation regime-switching (IRS) model developed in [Kuan, C.M., Huang, Y.L., Tsay, R.S., 2005. An unobserved component model with switching permanent and transitory innovations....

In this paper we propose a new class of tests for the martingale difference hypothesis based on the moment conditions derived by Bierens (1982). In contrast with the existing consistent tests, the proposed test has a standard limiting distribution and is easy to implement. Comparing with many...

In this paper a new class of tests for parameter stability, the moving-estimates (ME) test, is proposed. It is shown that in the standard situation the ME test asymptotically equivalent to the maximal likelihood ratio test under the alternative of a temporary parameter shift. It is also shown...

In this article we reexamine the profitability of technical analysis using White's reality check and Hansen's SPA test that correct the data snooping bias. Compared to previous studies, we study a more complete "universe" of trading techniques, including not only simple rules but also complex...

A quasi-maximum likelihood estimator of the break date is analyzed. Consistency of the estimator is demonstrated under very general conditions, provided that the data-generating process is not integrated. However, the asymptotic distribution of the estimator is quite different for time series...