251 citations · 512 across the 26 of their papers we have counts for
29 papers
Inference for sparsely sampled Gauss-Markov processes under outcome-dependent dropout
Alexander Aue, Siegfried Hörmann, Maximilian Ofner
We consider sparsely observed functional data generated by a latent Gauss-Markov process modeled through a linear stochastic differential equation (SDE). Motivated by an applicatio…
Geometric Regime--Switching Diffusions on Stratified Riemannian Spaces with an Application to Covariance Matrices
Leonardo Marconi, Matteo Farnè, Alexander Aue
We construct geometric regime-switching diffusions, a class of Markov processes on locally compact stratified Riemannian state spaces. In contrast with classical regime-switching a…
An operator-level ARCH Model
Alexander Aue, Sebastian Kühnert, Gregory Rice +1
AutoRegressive Conditional Heteroscedasticity (ARCH) models are standard for modeling time series exhibiting volatility, with a rich literature in univariate and multivariate setti…
Bitcoin Forecasting with Classical Time Series Models on Prices and Volatility
Anmar Kareem, Alexander Aue
This paper evaluates the performance of classical time series models in forecasting Bitcoin prices, focusing on ARIMA, SARIMA, GARCH, and EGARCH. Daily price data from 2010 to 2020…
Estimating invertible processes in Hilbert spaces, with applications to functional ARMA processes
Sebastian Kühnert, Gregory Rice, Alexander Aue
Invertible processes are central to functional time series analysis, making the estimation of their defining operators a key problem. While asymptotic error bounds have been establ…
Two-sample tests for relevant differences in the eigenfunctions of covariance operators
Alexander Aue, Holger Dette, Gregory Rice
This paper deals with two-sample tests for functional time series data, which have become widely available in conjunction with the advent of modern complex observation systems. Her…