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Fabio Sigrist
Fabio Sigrist
Verified email at stat.math.ethz.ch
Title
Cited by
Cited by
Year
The impact of sentiment and attention measures on stock market volatility
F Audrino, F Sigrist, D Ballinari
International Journal of Forecasting 36 (2), 334-357, 2020
2682020
A dynamic nonstationary spatio-temporal model for short term prediction of precipitation
F Sigrist, HR Künsch, WA Stahel
The Annals of Applied Statistics 6 (4), 1452-1477, 2012
1042012
Stochastic partial differential equation based modelling of large space–time data sets
F Sigrist, HR Künsch, WA Stahel
Journal of the Royal Statistical Society: Series B (Statistical Methodology), 2015
1012015
Grabit: Gradient tree-boosted Tobit models for default prediction
F Sigrist, C Hirnschall
Journal of Banking & Finance 102, 177-192, 2019
852019
Gradient and Newton boosting for classification and regression
F Sigrist
Expert Systems With Applications 167, 114080, 2021
542021
Gaussian Process Boosting
F Sigrist
Journal of Machine Learning Research 23, 1-46, 2022
482022
Using the censored gamma distribution for modeling fractional response variables with an application to loss given default
F Sigrist, WA Stahel
ASTIN Bulletin 41 (2), 673-710, 2011
432011
Maximum likelihood estimation of spatially varying coefficient models for large data with an application to real estate price prediction
JA Dambon, F Sigrist, R Furrer
Spatial Statistics 41, 100470, 2021
422021
Latent Gaussian Model Boosting
F Sigrist
IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (2), 1894-1905, 2023
262023
When does attention matter? The effect of investor attention on stock market volatility around news releases
D Ballinari, F Audrino, F Sigrist
International Review of Financial Analysis 82, 102185, 2022
242022
spate: An R package for spatio-temporal modeling with a stochastic advection-diffusion process
F Sigrist, HR Künsch, WA Stahel
Journal of Statistical Software 63 (14), 1-23, 2015
23*2015
KTBoost: Combined kernel and tree boosting
F Sigrist
Neural Processing Letters 53 (2), 1147-1160, 2021
202021
Machine learning for corporate default risk: Multi-period prediction, frailty correlation, loan portfolios, and tail probabilities
F Sigrist, N Leuenberger
European Journal of Operational Research 305 (3), 1390-1406, 2023
132023
An autoregressive spatio-temporal precipitation model
F Sigrist, HR Künsch, WA Stahel
Procedia Environmental Sciences 3, 2-7, 2011
122011
Examining the vintage effect in hedonic pricing using spatially varying coefficients models: a case study of single-family houses in the Canton of Zurich
JA Dambon, SS Fahrländer, S Karlen, M Lehner, J Schlesinger, F Sigrist, ...
Swiss Journal of Economics and Statistics 158 (1), 1-14, 2022
112022
varycoef: An R package for Gaussian process-based spatially varying coefficient models
JA Dambon, F Sigrist, R Furrer
arXiv preprint arXiv:2106.02364, 2021
42021
Deep learning for real estate price prediction
L Walthert, F Sigrist
Available at SSRN 3393434, 2019
42019
A comparison of machine learning methods for data with high-cardinality categorical variables
F Sigrist
arXiv preprint arXiv:2307.02071, 2023
32023
Joint variable selection of both fixed and random effects for Gaussian process-based spatially varying coefficient models
JA Dambon, F Sigrist, R Furrer
International Journal of Geographical Information Science 36 (12), 2525-2548, 2022
32022
Physics based dynamic modeling of space-time data
FRA Sigrist
ETH Zurich, 2013
12013
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