1.8k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of ViennaAT14 papers
- Sapienza University of RomeIT12 papers
- Complexity Science HubAT11 papers
- University of SalzburgAT9 papers
- Johannes Kepler University of LinzAT8 papers
- Humboldt-Universität zu BerlinDE7 papers
- The University of MelbourneAU7 papers
- TU WienAT7 papers
- ETH ZurichCH6 papers
- Queensland University of TechnologyAU5 papers
- University College DublinIE5 papers
- University of AmsterdamNL5 papers
20 papers · 1 filter
High-frequency and heteroskedasticity identification in multicountry models: Revisiting spillovers of monetary shocks
Michael Pfarrhofer, Anna Stelzer
We explore the international transmission of monetary policy and central bank information shocks originating from the United States and the euro area. Employing a panel vector auto…
Context Adaptivity as Enabler for Meaningful Pervasive Advertising
Christine Bauer
Socio-demographic user profiles are currently regarded as the most convenient base for successful personalized advertising. However, signs point to the dormant power of context rec…
Forecast Evaluation of Quantiles, Prediction Intervals, and other Set-Valued Functionals
Tobias Fissler, Rafael Frongillo, Jana Hlavinová +1
We introduce a theoretical framework of elicitability and identifiability of set-valued functionals, such as quantiles, prediction intervals, and systemic risk measures. A function…
Inequality is rising where social network segregation interacts with urban topology
Gergő Tóth, Johannes Wachs, Riccardo Di Clemente +4
Social networks amplify inequalities due to fundamental mechanisms of social tie formation such as homophily and triadic closure. These forces sharpen social segregation reflected…
A weak solution theory for stochastic Volterra equations of convolution type
Eduardo Abi Jaber, Christa Cuchiero, Martin Larsson +1
We obtain general weak existence and stability results for stochastic convolution equations with jumps under mild regularity assumptions, allowing for non-Lipschitz coefficients an…
Predicting credit default probabilities using machine learning techniques in the face of unequal class distributions
Anna Stelzer
This study conducts a benchmarking study, comparing 23 different statistical and machine learning methods in a credit scoring application. In order to do so, the models' performanc…
On the shapes of bilateral Gamma densities
Uwe Küchler, Stefan Tappe
We investigate the four parameter family of bilateral Gamma distributions. The goal of this paper is to provide a thorough treatment of the shapes of their densities, which is of i…
Comprehensive Process Drift Detection with Visual Analytics
Anton Yeshchenko, Claudio Di Ciccio, Jan Mendling +1
Recent research has introduced ideas from concept drift into process mining to enable the analysis of changes in business processes over time. This stream of research, however, has…
Shrinkage in the Time-Varying Parameter Model Framework Using the R Package shrinkTVP
Peter Knaus, Angela Bitto-Nemling, Annalisa Cadonna +1
Time-varying parameter (TVP) models are widely used in time series analysis to flexibly deal with processes which gradually change over time. However, the risk of overfitting in TV…
Elicitability and Identifiability of Systemic Risk Measures
Tobias Fissler, Jana Hlavinová, Birgit Rudloff
Identification and scoring functions are statistical tools to assess the calibration and the relative performance of risk measure estimates, e.g., in backtesting. A risk measures i…
Dealing with Stochastic Volatility in Time Series Using the R Package stochvol
Gregor Kastner
The R package stochvol provides a fully Bayesian implementation of heteroskedasticity modeling within the framework of stochastic volatility. It utilizes Markov chain Monte Carlo (…
Modeling Univariate and Multivariate Stochastic Volatility in R with stochvol and factorstochvol
Darjus Hosszejni, Gregor Kastner
Stochastic volatility (SV) models are nonlinear state-space models that enjoy increasing popularity for fitting and predicting heteroskedastic time series. However, due to the larg…
A Factor-Augmented Markov Switching (FAMS) Model
Gregor Zens, Maximilian Böck
This paper investigates the role of high-dimensional information sets in the context of Markov switching models with time varying transition probabilities. Markov switching models…
Ride-share matching algorithms generate income inequality
Eszter Bokányi, Anikó Hannák
Despite the potential of online sharing economy platforms such as Uber, Lyft, or Foodora to democratize the labor market, these services are often accused of fostering unfair worki…
Certainty Equivalent and Utility Indifference Pricing for Incomplete Preferences via Convex Vector Optimization
Birgit Rudloff, Firdevs Ulus
For incomplete preference relations that are represented by multiple priors and/or multiple -- possibly multivariate -- utility functions, we define a certainty equivalent as well…
colorspace: A Toolbox for Manipulating and Assessing Colors and Palettes
Achim Zeileis, Jason C. Fisher, Kurt Hornik +5
The R package colorspace provides a flexible toolbox for selecting individual colors or color palettes, manipulating these colors, and employing them in statistical graphics and da…
Optimal allocation of defibrillator drones in mountainous regions
Christian Wankmüller, Christian Truden, Christopher Korzen +3
Responding to emergencies in Alpine terrain is quite challenging as air ambulances and mountain rescue services are often confronted with logistics challenges and adverse weather c…
Evaluating Range Value at Risk Forecasts
Tobias Fissler, Johanna F. Ziegel
The debate of what quantitative risk measure to choose in practice has mainly focused on the dichotomy between Value at Risk (VaR) -- a quantile -- and Expected Shortfall (ES) -- a…
Approaches Toward the Bayesian Estimation of the Stochastic Volatility Model with Leverage
Darjus Hosszejni, Gregor Kastner
The sampling efficiency of MCMC methods in Bayesian inference for stochastic volatility (SV) models is known to highly depend on the actual parameter values, and the effectiveness…
Supplement to "Erratum: Higher Order Elicitability and Osband's Principle"
Tobias Fissler, Johanna F. Ziegel
This note corrects conditions in Proposition 3.4 and Theorem 5.2(ii) and comments on imprecisions in Propositions 4.2 and 4.4 in Fissler and Ziegel (2016).