10 papers
Comparative Analysis of Spatiotemporal Volatility Models: An Empirical Study on Financial Network Series
Ariane N. Meli Chrisko, Jessie Li, Philipp Otto +1
Various spatiotemporal and network GARCH models have recently been proposed to capture volatility interactions, such as the transmission of market risk across financial networks. T…
Forecasting Oil Volatility through Network Models with GARCH-Informed Correlation Weights
Fayçal Djebari, Kahina Mehidi, Khelifa Mazouz +1
This study addresses the computational challenges of forecasting volatility in high-dimensional commodity markets. Building on the Network log-ARCH framework, we introduce a novel…
A Simple and Robust Multi-Fidelity Data Fusion Method for Effective Modeling of Citizen-Science Air Pollution Data
Camilla Andreozzi, Pietro Colombo, Philipp Otto
We propose a robust multi-fidelity Gaussian process for integrating sparse, high-quality reference monitors with dense but noisy citizen-science sensors. The approach replaces the…
Estimation of Spatial and Temporal Autoregressive Effects using LASSO - An Example of Hourly Particulate Matter Concentrations
Elkanah Nyabuto, Philipp Otto, Yarema Okhrin
We present an estimation procedure of spatial and temporal effects in spatiotemporal autoregressive panel data models using the Least Absolute Shrinkage and Selection Operator, LAS…
Exponential Spatiotemporal GARCH Model with Asymmetric Volatility Spillovers
Ariane Nidelle Meli Chrisko, Philipp Otto, Wolfgang Schmid
This paper introduces a spatiotemporal exponential generalised autoregressive conditional heteroscedasticity (spatiotemporal E-GARCH) model, extending traditional spatiotemporal GA…
Multivariate Low-Rank State-Space Model with SPDE Approach for High-Dimensional Data
Jacopo Rodeschini, Lorenzo Tedesco, Francesco Finazzi +2
This paper proposes a novel low-rank approximation to the multivariate State-Space Model. The Stochastic Partial Differential Equation (SPDE) approach is applied component-wise to…