Melanie Schienle
Biographic Data
| ID | 6067605 |
|---|---|
| NAME | Melanie Schienle |
| GIVEN NAMES | Melanie |
| FAMILY NAME | Schienle |
| SIGNATURE | SCHIENLE M |
| AFFILIATIONS | Karlsruhe Institute of Technology |
| ORCID | 0000-0001-6000-5653 |
| VERIFIED | Yes |
| TOTAL WORKS | 5 |
| TOTAL CITATIONS | 1 |
| AUTHOR COUNT | 5 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 1 |
Large Spillover Networks of Nonstationary Systems
This article proposes a vector error correction framework for constructing large consistent spillover networks of nonstationary systems grounded in the network theory of Diebold and Y ilmaz. We aim to provide a tailored methodology for the large nonstationary (macro)economic and financial system application settings avoiding technical and often hard to verify assumptions for general statistical high-dimensional approaches where the dimension can …
Direction Augmentation in the Evaluation of Armed Conflict Predictions
In many forecasting settings, there is a specific interest in predicting the sign of an outcome variable correctly in addition to its magnitude. For instance, when forecasting armed conflicts, positive and negative log-changes in monthly fatalities represent escalation and de-escalation, respectively, and have very different implications. In the ViEWS forecasting challenge, a prediction competition on state-based violence, a novel evaluation scor…
Collaborative Hubs
Detecting Structural Differences in Tail Dependence of Financial Time Series
An accurate assessment of tail inequalities and tail asymmetries of financial returns is key for risk management and portfolio allocation. We propose a new test procedure for detecting the full extent of such structural differences in the dependence of bivariate extreme returns. We decompose the testing problem into piecewise multiple comparisons of Cramér-von Mises distances of tail copulas. In this way, tail regions that cause differences in ex…
Testing for an Omitted Multiplicative Long-Term Component in GARCH Models
We consider the problem of testing for an omitted multiplicative long-term component in GARCH-type models. Under the alternative, there is a two-component model with a short-term GARCH component that fluctuates around a smoothly time-varying long-term component which is driven by the dynamics of an explanatory variable. We suggest a Lagrange multiplier statistic for testing the null hypothesis that the variable has no explanatory power. We derive…
Detecting Structural Differences in Tail Dependence of Financial Time Series
An accurate assessment of tail inequalities and tail asymmetries of financial returns is key for risk management and portfolio allocation. We propose a new test procedure for detecting the full extent of such structural differences in the dependence of bivariate extreme returns. We decompose the testing problem into piecewise multiple comparisons of Cramér-von Mises distances of tail copulas. In this way, tail regions that cause differences in ex…
Testing for an Omitted Multiplicative Long-Term Component in GARCH Models
We consider the problem of testing for an omitted multiplicative long-term component in GARCH-type models. Under the alternative, there is a two-component model with a short-term GARCH component that fluctuates around a smoothly time-varying long-term component which is driven by the dynamics of an explanatory variable. We suggest a Lagrange multiplier statistic for testing the null hypothesis that the variable has no explanatory power. We derive…
Collaborative Hubs
Direction Augmentation in the Evaluation of Armed Conflict Predictions
In many forecasting settings, there is a specific interest in predicting the sign of an outcome variable correctly in addition to its magnitude. For instance, when forecasting armed conflicts, positive and negative log-changes in monthly fatalities represent escalation and de-escalation, respectively, and have very different implications. In the ViEWS forecasting challenge, a prediction competition on state-based violence, a novel evaluation scor…
Large Spillover Networks of Nonstationary Systems
This article proposes a vector error correction framework for constructing large consistent spillover networks of nonstationary systems grounded in the network theory of Diebold and Y ilmaz. We aim to provide a tailored methodology for the large nonstationary (macro)economic and financial system application settings avoiding technical and often hard to verify assumptions for general statistical high-dimensional approaches where the dimension can …
Econometrics (4 works) · Economics (3 works) · Market Dynamics and Volatility (3 works) · Mathematics (3 works) · Complex Systems and Time Series Analysis (2 works) · COVID-19 epidemiological studies (2 works) · Financial Risk and Volatility Modeling (2 works) · Mathematical optimization (2 works) · Monetary Policy and Economic Impact (2 works) · Statistics (2 works)