In this article we study multivariate continuous-time autoregressive moving-average (MCARMA) processes with values in convex cones. More specifically, introduce matrix-valued MCARMA L\'evy noise and present necessary sufficient conditions for from class to be cone valued. We derive specific hands-on the following two cases: First, classical on $\mathbb{R}_{d}$ positive orthant $\mathbb{R}_{d}^{...

When modeling time series data using autoregressive-moving average processes, it is a common practice to presume that the residuals are normally distributed. However, sometimes we encounter non-normal residuals and asymmetry of data marginal distribution. Despite widespread use of pure autoregressive processes for modeling non-normal time series, the autoregressive-moving average models have le...