Over the past few years, interest has increased in models defined on positive and negative
integers. Several application areas lead to data that are differences between positive …

With increased penetration of solar energy sources, solar power forecasting has become
more crucial and challenging. This paper proposes a copula-based Bayesian approach to …

We establish strong consistency and asymptotic normality of the maximum likelihood
estimator for stochastic time-varying parameter models driven by the score of the predictive …

The analysis of the intraday dynamics of covariances among high-frequency returns is
challenging due to asynchronous trading and market microstructure noise. Both effects lead …

Policymakers, firms, and investors closely monitor traditional survey-based consumer
confidence indicators and treat them as an important piece of economic information. To …

In this research, we employ a full-range tail dependence copula to capture the intraday
dynamic tail dependence patterns of 30 s log returns among stocks in the US market in the …

The tick structure of the financial markets entails discreteness of stock price changes. Based
on this empirical evidence, we develop a multivariate model for discrete price changes …

This article investigates the benefits of combining information available from daily and
intraday data in financial return forecasting. The two data sources are combined via a …

In finance, durations between successive transactions are usually modeled by the
autoregressive conditional duration model based on a continuous distribution omitting zero …

A novel statistical approach to estimating latency, defined as the time it takes to learn about
an event and generate response to this event, is proposed. Our approach only requires a …