We calculated the cross correlations between the half-hourly times series of the ten Dow Jones US economic sectors over the period February 2000 to August 2008, the two-year intervals 2002–2003, 2004–2005, 2008–2009, and also over 11 segments within the present financial crisis, to...

We analyzed 546 stocks in the Singapore Stock Exchange (SGX) and 1173 stocks in the Hong Kong Stock Exchange (HKSE) in 2006 and 2007, to understand how financial hierarchies on these two markets change over market corrections and crashes. To do so, we introduced the digital cross correlation as...

We describe a bottom–up framework, based on the identification of appropriate order parameters and determination of phase diagrams, for understanding progressively refined agent-based models and simulations of financial markets. We illustrate this framework by starting with a deterministic toy...

To investigate whether diversification within a supply chain can help middlemen firms survive prolonged financial crises, we simulated an extension of the dynamical supply chain network model by Mizgier et al. (2012) under normal and crisis economic conditions. In these simulations, firms in the...

The authors performed a comprehensive time series segmentation study on the 36 Nikkei Japanese industry indices from 1 January 1996 to 11 June 2010. From the temporal distributions of the clustered segments, we found that the Japanese economy never fully recovered from the extended 1997-2003...

We propose the penalized estimator with the smoothly clipped absolute deviation (SCAD) penalty for varying coefficient time series models, which in autoregressive models actually performs lag order selection. Theoretical properties are established. Some numerical examples are also presented.

We consider joint rank and variable selection in multivariate regression. Previously proposed joint rank and variable selection approaches assume that different responses are related to the same set of variables, which suggests using a group penalty on the rows of the coefficient matrix....

Functional data are infinite-dimensional statistical objects which pose significant challenges to both theorists and practitioners. Both parametric and nonparametric regressions have received attention in the functional data analysis literature. However, the former imposes stringent constraints...

Generalized varying coefficient partially linear models are a flexible class of semiparametric models that deal with data with different types of responses. In this paper, we focus on polynomial spline estimator as a computationally easier alternative to the more commonly used local polynomial...

This article develops a mean field variational Bayes approximation algorithm for posterior inferences of the recently proposed partially linear additive models with simultaneous and automatic variable selection and linear/nonlinear component identification abilities. To solve the problem induced...