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The conditional value-at-risk (CVaR) is a useful risk measure in fields such as machine learning, finance, insurance, energy, etc. When measuring very extreme risk, the commonly used CVaR estimation method of sample averaging does not work…

Methodology · Statistics 2021-03-10 Dylan Troop , Frédéric Godin , Jia Yuan Yu

Appropriate risk management is crucial to ensure the competitiveness of financial institutions and the stability of the economy. One widely used financial risk measure is Value-at-Risk (VaR). VaR estimates based on linear and parametric…

Statistical Finance · Quantitative Finance 2020-09-16 Marius Lux , Wolfgang Karl Härdle , Stefan Lessmann

We introduce new forecast encompassing tests for the risk measure Expected Shortfall (ES). The ES currently receives much attention through its introduction into the Basel III Accords, which stipulate its use as the primary market risk…

Risk Management · Quantitative Finance 2020-08-31 Timo Dimitriadis , Julie Schnaitmann

We present the Shortfall Deviation Risk (SDR), a risk measure that represents the expected loss that occurs with certain probability penalized by the dispersion of results that are worse than such an expectation. SDR combines Expected…

Risk Management · Quantitative Finance 2020-08-04 Marcelo Brutti Righi , Paulo Sergio Ceretta

The left tail of the implied volatility skew, coming from quotes on out-of-the-money put options, can be thought to reflect the market's assessment of the risk of a huge drop in stock prices. We analyze how this market information can be…

Risk Management · Quantitative Finance 2016-08-16 Ronnie Sircar , Stephan Sturm

Accounting for model uncertainty in risk management and option pricing leads to infinite dimensional optimization problems which are both analytically and numerically intractable. In this article we study when this hurdle can be overcome…

Risk Management · Quantitative Finance 2020-01-16 Daniel Bartl , Samuel Drapeau , Ludovic Tangpi

Treatment effect heterogeneity plays an important role in many areas of causal inference and within recent years, estimation of the conditional average treatment effect (CATE) has received much attention in the statistical community. While…

Methodology · Statistics 2024-12-17 Simon Christoffer Ziersen , Torben Martinussen

Value-at-risk (VaR) has been playing the role of a standard risk measure since its introduction. In practice, the delta-normal approach is usually adopted to approximate the VaR of portfolios with option positions. Its effectiveness,…

Methodology · Statistics 2019-04-22 Junyao Chen , Tony Sit , Hoi Ying Wong

Value-at-Risk (VaR) and Expected Shortfall (ES) are widely used in the financial sector to measure the market risk and manage the extreme market movement. The recent link between the quantile score function and the Asymmetric Laplace…

Machine Learning · Statistics 2021-05-14 Zhengkun Li , Minh-Ngoc Tran , Chao Wang , Richard Gerlach , Junbin Gao

In recent years, it has become apparent that an isolated microprudential approach to capital adequacy requirements of individual institutions is insufficient. It can increase the homogeneity of the financial system and ultimately the cost…

Risk Management · Quantitative Finance 2023-11-27 Jana Hlavinova , Birgit Rudloff , Alexander Smirnow

Motivated by conflicting conclusions regarding hydrocortisone's treatment effect on ICU patients with vasopressor-dependent septic shock, we developed a novel instrumental variable (IV) estimator to assess the average treatment effect (ATE)…

Methodology · Statistics 2025-03-18 Runjia Li , Victor B. Talisa , Chung-Chou H. Chang

A shortcoming of black-box supervised learning models is their lack of interpretability or transparency. To facilitate interpretation, post-hoc global variable importance measures (VIMs) are widely used to assign to each predictor or input…

Methodology · Statistics 2025-12-25 Jingyu Zhu , Daniel W. Apley

Risk measure forecast and model have been developed in order to not only provide better forecast but also preserve its (empirical) property especially coherent property. Whilst the widely used risk measure of Value-at-Risk (VaR) has shown…

Risk Management · Quantitative Finance 2020-09-08 Bony Josaphat , Khreshna Syuhada

Recently defined expectile regions capture the idea of centrality with respect to a multivariate distribution, but fail to describe the tail behavior while it is not at all clear what should be understood by a tail of a multivariate…

Statistics Theory · Mathematics 2023-12-18 Ha Thi Khanh Linh , Andreas H Hamel

The conditional average treatment effect (CATE) is the best measure of individual causal effects given baseline covariates. However, the CATE only captures the (conditional) average, and can overlook risks and tail events, which are…

Machine Learning · Statistics 2025-06-05 Nathan Kallus , Miruna Oprescu

A new semi-parametric Expected Shortfall (ES) estimation and forecasting framework is proposed. The proposed approach is based on a two-step estimation procedure. The first step involves the estimation of Value-at-Risk (VaR) at different…

Risk Management · Quantitative Finance 2021-03-16 Giuseppe Storti , Chao Wang

Value at risk (VaR) is a risk measure that has been widely implemented by financial institutions. This paper measures the correlation among asset price changes implied from VaR calculation. Empirical results using US and UK equity indexes…

Risk Management · Quantitative Finance 2011-03-30 John Cotter , François Longin

In our previous paper, "A Unified Approach to Systemic Risk Measures via Acceptance Set" (\textit{Mathematical Finance, 2018}), we have introduced a general class of systemic risk measures that allow for random allocations to individual…

Mathematical Finance · Quantitative Finance 2019-04-26 Francesca Biagini , Jean-Pierre Fouque , Marco Frittelli , Thilo Meyer-Brandis

Dynamic assessment of mortality risk in the intensive care unit (ICU) can be used to stratify patients, inform about treatment effectiveness or serve as part of an early-warning system. Static risk scoring systems, such as APACHE or SAPS,…

Machine Learning · Statistics 2020-11-03 Jonathan Heitz , Joanna Ficek , Martin Faltys , Tobias M. Merz , Gunnar Rätsch , Matthias Hüser

Systemic risk is concerned with the instability of a financial system whose members are interdependent in the sense that the failure of a few institutions may trigger a chain of defaults throughout the system. Recently, several systemic…

Mathematical Finance · Quantitative Finance 2023-08-02 Çağın Ararat , Nurtai Meimanjan