Search Results for author: Timo Dimitriadis

Found 9 papers, 3 papers with code

Regressions under Adverse Conditions

no code implementations22 Nov 2023 Timo Dimitriadis, Yannick Hoga

We introduce a new regression method that relates the mean of an outcome variable to covariates, given the "adverse condition" that a distress variable falls in its tail.

regression Time Series

Evaluating Probabilistic Classifiers: The Triptych

no code implementations25 Jan 2023 Timo Dimitriadis, Tilmann Gneiting, Alexander I. Jordan, Peter Vogel

Probability forecasts for binary outcomes, often referred to as probabilistic classifiers or confidence scores, are ubiquitous in science and society, and methods for evaluating and comparing them are in great demand.

Efficient Sampling for Realized Variance Estimation in Time-Changed Diffusion Models

1 code implementation22 Dec 2022 Timo Dimitriadis, Roxana Halbleib, Jeannine Polivka, Jasper Rennspies, Sina Streicher, Axel Friedrich Wolter

This paper analyzes the benefits of sampling intraday returns in intrinsic time for the standard and pre-averaging realized variance (RV) estimators.

Dynamic CoVaR Modeling

1 code implementation28 Jun 2022 Timo Dimitriadis, Yannick Hoga

In this article, we propose joint dynamic forecasting models for the Value-at-Risk (VaR) and CoVaR.


On Testing Equal Conditional Predictive Ability Under Measurement Error

no code implementations21 Jun 2021 Yannick Hoga, Timo Dimitriadis

For such exactly robust loss functions, forecast loss differences are on average unaffected by the use of proxy variables and, thus, inference on conditional predictive ability can be carried out as usual.

Encompassing Tests for Value at Risk and Expected Shortfall Multi-Step Forecasts based on Inference on the Boundary

no code implementations15 Sep 2020 Timo Dimitriadis, Xiaochun Liu, Julie Schnaitmann

We propose forecast encompassing tests for the Expected Shortfall (ES) jointly with the Value at Risk (VaR) based on flexible link (or combination) functions.

Evaluating probabilistic classifiers: Reliability diagrams and score decompositions revisited

no code implementations7 Aug 2020 Timo Dimitriadis, Tilmann Gneiting, Alexander I. Jordan

A probability forecast or probabilistic classifier is reliable or calibrated if the predicted probabilities are matched by ex post observed frequencies, as examined visually in reliability diagrams.

Uncertainty Quantification

Testing Forecast Rationality for Measures of Central Tendency

1 code implementation28 Oct 2019 Timo Dimitriadis, Andrew J. Patton, Patrick W. Schmidt

We propose tests of forecast rationality when the measure of central tendency used by the respondent is unknown.

Forecast Encompassing Tests for the Expected Shortfall

no code implementations13 Aug 2019 Timo Dimitriadis, Julie Schnaitmann

We introduce new forecast encompassing tests for the risk measure Expected Shortfall (ES).

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