## 7 Future Works  
Considering the shortcomings of CRPS-Sum, there is an urgent need for an assessment metric for multivariate probabilistic forecast models. A desirable metric would be a strictly proper scoring rule that summarizes the model performance in a single value using a reasonable number of samples. Furthermore, it should be capable of reflecting the precision of the model in learning the probability distribution of each dimension, as well as model accuracy in capturing cross-dimension dependencies. Additionally, it is desirable to investigate the discrimination ability of such metrics using various probabilistic forecasting methods on multiple real-world datasets. [PERSON]. Developed the main idea, conducted the main experiment, analyzed the results and wrote the manuscript, [PERSON] provided analysis of the results and reviewed manuscript, [PERSON] supervised the entire process and provided consultation on the results and manuscript, [PERSON] provided consultation on developing the main idea, analyzed the results, and wrote and reviewed manuscript. All authors have read and agreed to the published version of the manuscript. This research received no external funding. Not applicable. The authors declare no conflict of interest. \begin{table}
\begin{tabular}{l c c c} \hline \hline  & **GP-copula** & **Dummy Univariate** & **Dummy Multivariate** \\ \hline CRPS-Sum & 0.1703 & 0.4685 & 0.4705 \\ CRPS & 0.3336 & 0.6778 & 0.7543 \\ ES & 0.0138 & 0.0284 & 0.0318 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: This table illustrates the results from dummy models on the taxi dataset and compares their performance with GP-copula based on CRPS-Sum, CRPS, and ES. In contrast to the exchange-rate dataset, it is not feasible to cross-check these quantities in higher dimensionalities. * [PERSON] (1991) [PERSON] Conditional heteroskedasticity in asset returns: A new approach. _Econom. J. Econom. Soc._**1991**, _59_, 347-370. [CrossRef]
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