We apply a functional data approach for mixture model-based multivariate innovation clustering to identify different regional innovation portfolios in Europe, considering patterns of specialization among innovation types. We combine patent registration data and other innovation and economic data...

Multivariate GARCH models do not perform well in large dimensions due to the so-called curse of dimensionality. The recent DCC-NL model of Engle et al. (2019) is able to overcome this curse via nonlinear shrinkage estimation of the unconditional correlation matrix. In this paper, we show how...

This paper proposes a Bayesian estimation framework for panel-data sets with binary dependent variables where a large number of cross-sectional units is observed over a short period of time, and cross-sectional units are interdependent in more than a single network domain. The latter provides...

In many applications of the multivariate analyses of variance, the classic parametric solutions for testing hypotheses of equality in population means or multisample and multivariate location problems might not be suitable for various reasons. Multivariate multisample location problems lack a...

We construct a parsimonious test of constancy of the correlation matrix in the multivariate conditional correlation GARCH model, where the GARCH equations are time-varying. The alternative to constancy is that the correlations change deterministically as a function of time. The alternative is a...

Markowitz portfolio selection is a cornerstone in finance, both in academia and in the industry. Most academic studies either ignore transaction costs or account for them in a way that is both unrealistic and suboptimal by (i) assuming transaction costs to be constant across stocks and (ii)...

This paper investigates the ability of several generalized Bayesian vector autoregressions to cope with the extreme COVID-19 observations and discusses their impact on prior calibration for inference and forecasting purposes. It shows that the preferred model interprets the pandemic episode as a...

We estimate the euro area output gap by applying the Beveridge-Nelson decomposition based on a large Bayesian vector autoregression. Our approach incorporates multivariate information through the inclusion of a wide range of variables in the analysis and addresses data issues associated with the...

This paper introduces a unified multivariate overnight GARCH-Ito model for volatility matrix estimation and prediction both in the low- and high-dimensional set-up. To account for whole-day market dynamics in the financial market, the proposed model has two different instantaneous volatility...

In this paper we analyse multivariate Chebyshev interpolation for function approximation. We propose an algorithm for Chebyshev coefficient calibration and function interpolation that utilises high-level linear algebra operations. Such operations allow deferring large portions of the calculation...

Quadratic Hawkes (QHawkes) processes have proved effective at reproducing the statistics of price changes, capturing many of the stylised facts of financial markets. Motivated by the recently reported strong occurrence of endogenous co-jumps (simultaneous price jumps of several assets) we extend...

Risk evaluation is a forecast, and its validity must be backtested. Probability distribution forecasts are used in this work and allow for more powerful validations compared to point forecasts. Our aim is to use bivariate copulas in order to characterize the in-sample copulas and to validate...

This paper develops a multivariate model for count time series, in which the time-varying intensity parameter determining the probability that an event occurs evolves according to general autoregressive score (GAS) models (see Creal et al., 2013; Harvey, 2013).The model is particularly suitable to...

The aim of this paper is to propose a multivariate INAR(1) model for addressing all the challenges in high-dimensional non-life claim count data sets that exhibit time and cross dependence and a zero-inflation attribute. In particular, the innovation terms are modelled using a multivariate...

Interest rates have fallen worldwide in recent decades, a phenomenon that has been linked at least in part to a decline in the natural rate of interest, r* (a.k.a. “r-star”). To investigate this decline, we consider a multivariate trend-cycle decomposition of real interest rates using a...

In this paper, we present a unified statistical model for multivariate and multi-modal sub-band distribution in multi-resolution transforms of color-texture images. This model is based on the formalism of finite mixtures of multivariate generalized Gaussians (MoMGG) which enables accurate...

In this paper, we propose an intersection-union test for multivariate forecast accuracy based on the combination of a sequence of univariate tests. The testing framework evaluates a global null hypothesis of equal predictive ability using any number of univariate forecast accuracy tests under...

This paper derives a finite-sample oracle inequality for a class of misspecified multivariate conditional autoregressive quantile forecasts. This inequality is used to establish that the M-estimator of a multivariate version of the conditional autoregressive Value-at-Risk model (CAViaR) achieves...

In underground mining, the tunnels are performed mainly by blasting. Unfortunately, their quality may be different than expected. It is important to monitor both the quality and changes of existing tunnels. The length of corridors in underground mines is massive. Even if one wants to limit...

Stock markets are considered a barometer of the respective country’s economy around the world. Modern portfolio theory advocates diversification for risk management, which helps maintain returns as long as indices around the world are not perfectly correlated. The relationship exists across...

Evidence that cryptocurrencies exhibit speculative bubble behavior is well documented. This evidence could trigger global financial instability leading to systemic risk. It is therefore crucial to quantify systemic risk and investigate its transmission mechanism across crypto markets and other...

Disaggregation of mortality by cause has advanced the development of life tables for life insurance and pension purposes. However, the assumption that the causes of death are independent is a challenge in reality. Furthermore, models that determine relationships among causes of death such as...

This paper improves a standard Structural Panel Bayesian Vector Autoregression model in order to jointly deal with issues of endogeneity, because of omitted factors and unobserved heterogeneity, and volatility, because of policy regime shifts and structural changes. Bayesian methods are used to...

This paper derives the statistical properties of a two-step approach to estimating multivariate rotated GARCH-BEKK (RBEKK) models. From the definition of RBEKK, the unconditional covariance matrix is estimated in the first step to rotate the observed variables in order to have the identity...

This study examines money market and foreign exchange market dynamics in Nigeria by estimating the dynamic correlation and volatility spillovers between Nigeria Naira/US Dollar Bureau De Change (BDC) exchange rate and interbank call rate with data from January 2007 to August 2019. The study...

This paper shows the effects of the COVID-19 pandemic on energy markets. We estimate daily volatilities and correlations among energy commodities relying on a mixed-frequency approach that exploits information from the number of weekly deaths related to COVID-19 in the United States. The...