In this article, the authors investigate the multi-scale structure of the S&P500 minute-by-minute time series. The authors attempt to find the answer to the following question: Are upward and downward regimes in the S&P500 time series exhibit different long-range power-law correlations? To answer this question, the authors apply the discrete wavelet transform (DWT) to the original time series f...

A pair of non-adjacent edges is said to be separated in a circular ordering of vertices, if the endpoints of the two edges do not alternate in the ordering. The circular separation dimension of a graph G, denoted by π◦(G), is the minimum number of circular orderings of the vertices ofG such that every pair of non-adjacent edges is separated in at least one of the circular orderings. This notion...

One striking phenomenon in the U.S. labor market is the reversal of the gender gap in college attainment. Females have outnumbered males in college attainment since 1987. We develop a discrete choice model of college entry decisions to study the effects of changes in relative earnings, changes in parental education, and changes in the marriage market on time series observations of college attai...

The problem of change detection of time series with abrupt and smooth changes in the spectral characteristics is addressed. We first review the main characteristics of the discrete wavelet transform and the maximal overlap discrete wavelet transform. An algorithm for sequential change detection in time series is then reported based on the maximal overlap discrete wavelet transform and Bayesian ...

The purpose of this paper is to forecast the time evolution of a binary response variable from an associated continuous time series observed only at discrete time points that usually are unequally spaced. In order to solve this problem we are going to use a functional logit model based on functional principal component analysis of the predictor time series that takes into account its continuous...