From the 1 of 7 linked papers with an AI index.
7 papers
Time preference effects in forecasting
Yannick Hoga, Niklas V. Lehmann
The paper examines how forecasters who prefer immediate rewards over future ones may bias their predictions about when uncertain events will happen, and shows empirical evidence th…
Persistence-Robust Break Detection in Predictive CoVaR Regressions
Yannick Hoga
Forecasting risk (as measured by quantiles) and systemic risk (as measured by Adrian and Brunnermeiers's (2016) CoVaR) is important in economics and finance. However, past research…
Systemic Risk Surveillance
Timo Dimitriadis, Yannick Hoga
Following several episodes of financial market turmoil in recent decades, changes in systemic risk have drawn growing attention. Therefore, we propose surveillance schemes for syst…
Self-Normalized Inference in (Quantile, Expected Shortfall) Regressions for Time Series
Yannick Hoga, Christian Schulz
This paper proposes valid inference tools, based on self-normalization, in time series expected shortfall regressions and, as a corollary, also in quantile regressions. Extant meth…
Regressions under Adverse Conditions
Timo Dimitriadis, Yannick Hoga
We introduce a new regression method that relates the mean of an outcome variable to covariates, under the "adverse condition" that a distress variable falls in its tail. This allo…
Dynamic CoVaR Modeling and Estimation
Timo Dimitriadis, Yannick Hoga
The popular systemic risk measure CoVaR (conditional Value-at-Risk) and its variants are widely used in economics and finance. In this article, we propose joint dynamic forecasting…