Reisenhofer, Rafael; Bayer, Xandro; Hautsch, Nikolaus - 2022
Despite the impressive success of deep neural networks in many application areas, neural network models have so far not been widely adopted in the context of volatility forecasting. In this work, we aim to bridge the conceptual gap between established time series approaches, such as the...