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We present a computational method for measuring financial risk by estimating the Value at Risk and Expected Shortfall from financial series. We have made two assumptions: First, that the predictive distributions of the values of an asset…

Risk Management · Quantitative Finance 2011-12-14 I. Garcia , J. Jimenez

Since the Great Financial Crisis (GFC), the use of stress tests as a tool for assessing the resilience of financial institutions to adverse financial and economic developments has increased significantly. One key part in such exercises is…

Econometrics · Economics 2022-02-08 Martin Guth

We discuss systematically two versions of confidence regions: those based on p-values and those based on e-values, a recent alternative to p-values. Both versions can be applied to multiple hypothesis testing, and in this paper we are…

Statistics Theory · Mathematics 2024-03-05 Vladimir Vovk , Ruodu Wang

In order to optimize the usage of testing efforts and to assess risks of software-based systems, risk-based testing uses risk (re-)assessments to steer all phases in a test process. Several risk-based testing approaches have been proposed…

Software Engineering · Computer Science 2018-01-23 Michael Felderer , Juergen Grossmann , Ina Schieferdecker

Formula alpha mining, which generates predictive signals from financial data, is critical for quantitative investment. Although various algorithmic approaches-such as genetic programming, reinforcement learning, and large language…

Artificial Intelligence · Computer Science 2025-08-20 Hongjun Ding , Binqi Chen , Jinsheng Huang , Taian Guo , Zhengyang Mao , Guoyi Shao , Lutong Zou , Luchen Liu , Ming Zhang

The study of systemic risk is often presented through the analysis of several measures referring to quantities used by practitioners and policy makers. Almost invariably, those measures evaluate the size of the impact that exogenous events…

Physics and Society · Physics 2023-04-13 Luka Klinčić , Vinko Zlatić , Guido Caldarelli , Hrvoje Štefančić

Cross-validation is a popular non-parametric method for evaluating the accuracy of a predictive rule. The usefulness of cross-validation depends on the task we want to employ it for. In this note, I discuss a simple non-parametric setting,…

Methodology · Statistics 2019-09-27 Stefan Wager

Critical infrastructure systems must be both robust and resilient in order to ensure the functioning of society. To improve the performance of such systems, we often use risk and vulnerability analysis to find and address system weaknesses.…

Physics and Society · Physics 2015-05-08 Sarah LaRocca , Jonas Johansson , Henrik Hassel , Seth Guikema

Predictive models are often introduced to decision-making tasks under the rationale that they improve performance over an existing decision-making policy. However, it is challenging to compare predictive performance against an existing…

Machine Learning · Computer Science 2024-06-13 Luke Guerdan , Amanda Coston , Kenneth Holstein , Zhiwei Steven Wu

Asymmetric causality tests are increasingly gaining popularity in different scientific fields. This approach corresponds better to reality since logical reasons behind asymmetric behavior exist and need to be considered in empirical…

Econometrics · Economics 2024-10-10 Abdulnasser Hatemi-J

This paper presents non-parametric estimates of spectral risk measures applied to long and short positions in 5 prominent equity futures contracts. It also compares these to estimates of two popular alternative measures, the Value-at-Risk…

Risk Management · Quantitative Finance 2011-03-30 john cotter , kevin dowd

Following several episodes of financial market turmoil in recent decades, changes in systemic risk have drawn growing attention. Therefore, we propose surveillance schemes for systemic risk, which allow to detect misspecified systemic risk…

Econometrics · Economics 2026-01-14 Timo Dimitriadis , Yannick Hoga

A novel forecast combination and weighted quantile based tail-risk forecasting framework is proposed, aiming to reduce the impact of modelling uncertainty in tail-risk forecasting. The proposed approach is based on a two-step estimation…

Risk Management · Quantitative Finance 2021-07-20 Giuseppe Storti , Chao Wang

In this paper, we are interested in evaluating the resilience of financial portfolios under extreme economic conditions. Therefore, we use empirical measures to characterize the transmission process of macroeconomic shocks to risk…

Applications · Statistics 2019-05-21 Helder Rojas , David Dias

Cross-validation is a widely used technique for evaluating the performance of prediction models, ranging from simple binary classification to complex precision medicine strategies. It helps correct for optimism bias in error estimates,…

Forecasting and forecast evaluation are inherently sequential tasks. Predictions are often issued on a regular basis, such as every hour, day, or month, and their quality is monitored continuously. However, the classical statistical tools…

Methodology · Statistics 2022-07-04 Sebastian Arnold , Alexander Henzi , Johanna F. Ziegel

The issue addressed in this paper is that of testing for common breaks across or within equations of a multivariate system. Our framework is very general and allows integrated regressors and trends as well as stationary regressors. The null…

Statistics Theory · Mathematics 2018-01-12 Tatsushi Oka , Pierre Perron

No matter the nature of the response and/or explanatory variables in a regression model, some basic issues such as the existence of an effect of the predictor on the response, or the assessment of a common shape across groups of…

Applications · Statistics 2020-09-01 María Alonso-Pena , Jose Ameijeiras-Alonso , Rosa M. Crujeiras

The notion of an e-value has been recently proposed as a possible alternative to critical regions and p-values in statistical hypothesis testing. In this paper we consider testing the nonparametric hypothesis of symmetry, introduce…

Statistics Theory · Mathematics 2024-01-29 Vladimir Vovk , Ruodu Wang

Performance metrics measuring in Financial Integrity systems are crucial for maintaining an efficient and cost effective operation. An important performance metric is False Positive Rate. This metric cannot be directly monitored since we…

Machine Learning · Computer Science 2022-08-30 Moshe Tocker