  Randomness in financial markets requires modern and robust multivariate
models of risk measures. This paper proposes a new approach for modeling
multivariate risk measures under Wasserstein barycenters of probability
measures supported on location-scatter families. Simple and advanced copulas
multivariate Value at Risk models are compared with the derived technique. The
performance of the model is also checked in market indices of United States
generated by the financial crisis due to COVID-19. The introduced model behaves
satisfactory in both common and volatile periods of asset prices, providing
realistic VaR forecast in this era of social distancing.
