This paper proposes an adjusted-range based self-normalized tests for changes in correlation coefficient and correlation matrix. Unlike the self-normalization approach proposed by Lobato (2001) and Shao (2010), which relies on the variance of a partial sum process as the self-normalizer, here we...

This paper proposes an adjusted-range based self-normalized test for change in correlation. Unlike the self-normalization approach proposed by Lobato (2001) and Shao (2010), which relies on the variance of the partial sum process as a self-normalizer, and used by Choi and Shin (2020) to...

This paper proposes a new self-normalization method to construct confidence intervals for quantities of stationary time series. Unlike the self-normalization approach in Shao (2010) and Lobato (2001), which utilize the variance of a partial as the self-normalizer, we propose the use of its...

This article considers model averaging in the class of the integer-valued autoregressive (INAR) processes. The INAR process is a class of structural models that can be used to model dependent count data in fields such as medicine, economics, finance and marketing. It specifies the data...

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

We study the mechanism that controls the shape of the bear market through an information diffusion perspective, and establish a frontier of market decline, in terms of a trade-off between amplitude, duration and the rate of information diffusion. Empirical analysis using data from 15 stock...

Inspired by the increasing evidence of financialization/speculation in commodity pricing, this paper constitutes a first attempt to build an information diffusion-based asset pricing framework for the oil futures market. With gradual information dissemination, slowly decaying uncertainty about...