Essays on asynchronous time series and related multidimensional data

This thesis focusses on asynchronous time series and related multidimensional data: timedependent measurements with varying publication delays. This class of data exists in a broad range of fields. In social sciences, most official time series and repeated surveys are indeed asynchronous in nature since statistical offices need time to collect and aggregate raw data. In STEM, statistical offices are generally less relevant and most publication delays are caused by more exotic factors. For instance, with series derived from technological networks, they are usually generated by a direct reference (digital or textual) of the past (e.g., publishing pictures of a trip done a week ago that was also photographed and posted in real time by a friend). As a result, the study of data releases is key for developing accurate real-time models and finds applications in forecasting, policy and risk management.