A previsão de demanda é uma metodologia da administração de empresas para estimar um
valor futuro de uma grandeza de interesse. Realizar previsões de demanda significa …

This paper studies the behavior of cryptocurrencies' financial time series, of which Bitcoin is
the most prominent example. The dynamics of these series are quite complex, displaying …

Time series data are data which are taken in a particular time interval, and may vary
drastically during the period of observation and hence it becomes highly nonlinear. Stock …

In this paper we investigate different VaR forecasts for daily energy commodities returns
using GARCH, EGARCH, GJR-GARCH, Generalized Autoregressive Score (GAS) and the …

This paper studies the behaviour of crypto currencies financial time-series of which Bitcoin is
the most prominent example. The dynamic of those series is quite complex displaying …

Since the financial crisis, risk management has been of growing interest to investors and the
approach of Value-at-Risk has gained wide acceptance. Investing in Cryptocurrencies …

This paper presents the R package GAS for the analysis of time series under the
Generalized Autoregressive Score (GAS) framework of Creal et al.(2013) and Harvey …

We propose a novel observation-driven finite mixture model for the study of banking data.
The model accommodates time-varying component means and covariance matrices, normal …

Since the introduction of the Autoregressive Conditional Heteroscedasticity (ARCH) model,
the literature on modeling the time‐varying second‐order conditional moment has become …

In this paper, using estimating function approach, a new optimal volatility estimator is
introduced and based on the recursive form of the estimator a data-driven generalized …