The asymmetric response of conditional variances to positive versus negative news has
been traditionally modeled with threshold specifications that allow only two possible regimes: …

We analyze the predictive performance of various volatility models for stock returns. To
compare their performance, we choose loss functions for which volatility estimation is of …

… Gloria González-Rivera is associate professor and Steven M. Helfand assistant professor
in the Department of Economics at the University of California, Riverside. This article was …

This article introduces a semiparametric autoregressive conditional heteroscedasticity (ARCH)
model that has conditional first and second moments given by autoregressive moving …

… Both of these instances could be viewed from the perspective of symbolic data: in Zellner
and Tobias (2000) the data is an interval-valued time series and in González-Rivera, Lee, and …

Current regression models for interval-valued data do not guarantee that the predicted lower
bound of the interval is always smaller than its upper bound. We propose a constrained …

We adapt smoothing methods to histogram‐valued time series (HTS) by introducing a
barycentric histogram that emulates the “average” operation, which is the key to any smoothing …

Histogram time series (HTS) and interval time series (ITS) are examples of symbolic data sets.
Though there have been methodological developments in a cross-sectional environment, …

Within a flexible regression model (JD Hamilton, Econometrica 69 (3) (2001) 537) we offer a
battery of new Lagrange multiplier statistics that circumvent the problem of unidentified …

In this paper, we investigate the loss of asymptotic efficiency of semiparametric and quasi-maximum-likelihood
estimators relative to maximum-likelihood estimators in models with …