Some existing nonparametric two-sample tests for equality of multivariate distributions perform unsatisfactorily when the two sample sizes are unbalanced. In particular, the power of these tests tends to diminish with increasingly unbalanced sample sizes. In this paper, we propose a new testing...

This paper proposes an easy-to-implement approach to forecasting the multivariate long memory process on same realization and further examines its usefulness on forecasting multivariate volatility series. This procedure bases on the extension of the analysis of Lewis and Reinsel (1985) to the...

This paper extends the multivariate filter approach of estimating potential output developed by Alichi and others (2018) to incorporate labor market hysteresis. This extension captures the idea that long and deep recessions (expansions) cause persistent damage (improvement) to the labor market,...

The modeling of multivariate time series in an agnostic manner, without assumptions about underlying theoretical structure is traditionally conducted using Vector Auto-Regressions. They are well suited for linear and state-independent evolution. A more general methodology of Multivariate...

When calculating the risk margins of a company with multiple Lines of Business–typically, a quantile in the right tail of an aggregate loss, assumptions about the dependence structure between the different Lines are crucial. Many current multivariate reserving methodologies focus on aggregated...

Firm-level default models are important for bottom-up modeling of the default risk of corporate debt portfolios. However, models in the literature typically have several strict assumptions which may yield biased results, notably a linear effect of covariates on the log-hazard scale, no...

We present new methodology and a case study in use of a class of Bayesian predictive synthesis (BPS) models for multivariate time series forecasting. This extends the foundational BPS framework to the multivariate setting, with detailed application in the topical and challenging context of...

This paper considers the problem of jointly decomposing a set of time series variablesinto cyclical and trend components, subject to sets of stochastic linear restrictionsamong these cyclical and trend components. We derive a closed form solution to anordinary problem featuring homogeneous...

This paper shows that expected uncertainty should be included as a key determinant in the derivation of the natural probability distribution of assets because it contains information that goes beyond information contained in state prices. I redefine the contingent state prices derived in the...

Mixed exponential distributions are frequently used in actuarial risk modeling. Distributions obtained through mixtures allow greater flexibility in the modeling of non-life insurance loss amounts . Several research works have studied mixed exponential distributions in univariate and...