Typically, point forecasting methods are compared and assessed by means of an error
measure or scoring function, with the absolute error and the squared error being key …

In this article we present a theoretical review of the existing literature on Value at Risk (VaR)
specifically focussing on the development of new approaches for its estimation. We effect a …

This paper attempts to evaluate the capacity of Spanish domestic tourism to relieve the
national travel industry crisis in the situation of a complete or significant loss of international …

The interest in forecasting the Value at Risk (VaR) has been growing over the last two
decades, due to the practical relevance of this risk measure for financial and insurance …

This study proposes a new hybrid model that combines LSTM and BiLSTM neural networks
with GARCH type model forecasts using an ensemble approach to forecast volatility for one …

The dynamic conditional correlation (DCC) model by Engle (2002) is one of the most
popular multivariate volatility models. This model is based solely on closing prices. It has …

Is it possible to obtain an objective and quantifiable measure of risk backed up by choices
made by some specific groups of rational investors? To answer this question, in this paper …

Recent studies indicate that systemic risk has predictive power over severe economic
downturns. We propose a novel methodology that employs sparsity and targeting …

The main contribution of this study is to assess whether investor sentiment, as measured
through textual analysis of newspaper articles or social media posts, does have an effect on …

We propose a generalization of the Dynamic Conditional Correlation multivariate GARCH
model of Engle [RF Engle, Dynamic conditional correlation: a simple class of multivariate …