Search Results - subject_exact:"Ausreißer"

Comparative analysis of tail risk in emerging and developed equity markets : an extreme value theory perspective

Dlamini, Sthembiso; Shongwe, Sandile Charles - 2026

This research explores the application of extreme value theory in modelling and quantifying tail risks across different economic equity markets, with focus on the Nairobi Securities Exchange (NSE20), the South African Equity Market (FTSE/JSE Top40) and the US Equity Index (S&P500). The study...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015591162

Estimation and inference for the persistence of extremely high temperatures

Cai, Juan Juan; Lin, Yicong; Schaumburg, Julia; Wang, … - 2026

We propose a nonparametric framework for estimating the extremal index that captures the persistence of extreme observations. The framework provides unified and simple procedures for verifying the well-known local dependence condition D(ᵈ) (un), which characterizes the extremal index yet is...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015567815

Navigating extreme market fluctuations : asset allocation strategies in developed vs. emerging economies

Bonga-Bonga, Lumengo - 2026

This paper examines how assets from emerging and developed stock markets can be efficiently allocated during periods of financial crisis by integrating traditional portfolio theory with Extreme Value Theory (EVT), using the Generalized Pareto Distribution (GPD) and Generalized Extreme Value...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015640564

Joint extreme value-at-risk and expected shortfall dynamics with a single integrated tail shape parameter

D'Innocenzo, Enzo; Lucas, André; Schwaab, Bernd; Zhang, Xin - 2026

We propose a robust semi-parametric framework for persistent time-varying extreme tail behavior, including extreme Value-at-Risk (VaR) and Expected Shortfall (ES). The framework builds on Extreme Value Theory and uses a conditional version of the Generalized Pareto Distribution (GPD) for...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015592338

Consumer sentiment and spending in extreme events

Ardakani, Omid M.; Levine, Lindsay R. - 2026

We examine tail dependence between consumer sentiment and spending during crises, focusing on COVID-19 and the Global Financial Crisis. Using copula models on U.S. monthly data from 2003-2024, we quantify extreme co-movements and find asymmetric tail dependence that intensifies during crises:...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015633714

The geometry of heterogeneous extremes : optimal transport and entropic design

Buhai, Sebastian - 2026

Extreme outcomes depend not only on shock tails but also on heterogeneity in how many opportunities agents get to sample. In the mixed-Poisson search framework, a randomly drawn agent's normalized maximum converges to Hγ,F (x) = P0 (vγ (x)) , a Laplace-transform mixture of a classical...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015625042

Catastrophic-risk-aware reinforcement learning with extreme-value-theory-based policy gradients

Davar, Parisa; Godin, Frédéric; Garrido, José - 2025

This paper tackles the problem of mitigating catastrophic risk (which is risk with very low frequency but very high severity) in the context of a sequential decision making process. This problem is particularly challenging due to the scarcity of observations in the far tail of the distribution...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015654808

Extreme value inference for heterogeneous heavy-tailed data : a derandomization theory

Daouia, Abdelaati; Hachem, Joseph; Stupfler, Gilles - 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015625395

Enhancing insurer portfolio resilience and capital efficiency with green bonds : a framework combining dynamic R-vine copulas and tail-risk modeling

Thitivadee Chaiyawat; Pannarat Guayjarernpanishk - 2025

This study develops an integrated risk modeling framework to assess capital adequacy and optimize portfolio performance for Thai life and non-life insurers. Leveraging ARMA-GJR-GARCH models with skewed Student-t innovations, extreme value theory, and dynamic R-vine copulas, the framework...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015467328

Anomaly detection using surprisals

Hyndman, Rob J.; Frazier, David T. - 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015650671

Robust learning of tail dependence

Ardakani, Omid M. - 2025

Accurate estimation of tail dependence is difficult due to model misspecification and data contamination. This paper introduces a class of minimum f-divergence estimators for the tail dependence coefficient that unifies robust estimation with extreme value theory. I establish strong consistency...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015562118

Joint extreme Value-at-Rrisk and Expected Shortfall dynamics with a single integrated tail shape parameter

D'Innocenzo, Enzo; Lucas, André; Schwaab, Bernd; Zhang, Xin - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015324099

Extreme conditional tail risk inference in ARMA-GARCH models

Ma, Yaolan; Wei, Bo - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015556648

Extremal expected shortfall regressions : inference and an application to health care spending

Hoga, Yannick; Karlsson, Martin - 2025

This paper proposes feasible inference methods for extremal expected shortfall (ES) regressions. While standard ES regressions consider a fixed probability level, in extremal ES regressions the probability level becomes more extreme as a function of the sample size. We show that in extremal ES...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015616196

Limiting distribution of the maximum drawdown for Brownian motion with positive drift

Bermin, Hans-Peter; Holm, Magnus - 2025

The maximum drawdown of a stochastic process is the largest peak-to-trough decline observed over a given horizon [0, T]. Using arguments from extreme value theory, we derive the limiting distribution of the maximum drawdown for a Brownian motion with positive drift as T → ∞. We show that,...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015557774

A copula-based data augmentation strategy for the sensitivity analysis of extreme operational losses

Chokami, A. Khorrami; Rabitti, G. - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015534156

Electricity demand forecasting of value-at-risk and expected shortfall : the South African context

Masilo, Bofelo Moemedi; Makatjane, Katleho - 2025

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015404066

The devil is in the tail : macroeconomic tail risk expectations of firms

Menkhoff, Manuel - 2025

This paper examines novel survey evidence on firms’ beliefs about macroeconomic tail risk and their role in investment decisions. In a large survey of German firms, I elicit (i) the subjective probability of a severe macroeconomic downturn and (ii) firms’ exposure to such an event. I...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015396790

An evaluation of the adequacy of Lévy and extreme value tail risk estimates

Mozumber, Sharif; Hassan, M. Kabir; Kabir, M. Humayun - 2024

This study investigates the simplicity and adequacy of tail-based risk measures-valueat-risk (VaR) and expected shortfall (ES)-when applied to tail targeting of the extreme value (EV) model. We implement Lévy-VaR and ES risk measures as full density-based alternatives to the generalized Pareto...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10014547241

Detecting outliers in Malta pension schemes and insurance corporations datasets: A machine learning approach

Axiaq, Sarah; Carabott, Kristen - 2024

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015096902

Detecting outliers in Malta pension schemes and insurance corporations datasets : a machine learning approach

Axiaq, Sarah; Carabott, Kristen - 2024

This paper presents a Machine Learning approach adopted at the Statistics Department of the Central Bank of Malta to detect outliers in the Maltese Pension Schemes and Insurance datasets, which are collected by the Bank, at micro-level. The motive behind this study is to develop an outlier...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015062337

Comparing and quantifying tail dependence

Siburg, Karl Friedrich; Strothmann, Christopher; Weiß, … - 2024

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015067023

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Comparing and Quantifying Tail Dependence

Siburg, Karl Friedrich; Strothmann, Christopher; Weiß, … - 2022

Book / Working Paper

Measuring tail risk

Dierkes, Maik; Hollstein, Fabian; Prokopczuk, Marcel; … - 2024

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015075193

A simple theory of Pareto-distributed earnings

Harmenberg, Karl - 2024

I introduce a simple model which endogenously generates a Pareto distribution in top earnings. Workers inhabit different niches, and the earnings of a worker is determined by the niche-specific supply of labor and a downward-sloping labor demand curve. The highest paid workers are the ones that...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015075876

Extreme value inference for general heterogeneous data

He, Yi; Einmahl, John H. J. - 2024

Persistent link: https://ebvufind01.dmz1.zbw.eu/10014528470

Forecasting the effect of extreme sea-level rise on financial market risk

Garcia-Jorcano, Laura; Sanchis-Marco, Lidia - 2024

Persistent link: https://ebvufind01.dmz1.zbw.eu/10014535506

Tail copula estimation for heteroscedastic extremes

Einmahl, John H. J.; Chen Zhou - 2024

Persistent link: https://ebvufind01.dmz1.zbw.eu/10014467520

2T-POT Hawkes model for left- and right-tail conditional quantile forecasts of financial log returns : Out-of-sample comparison of conditional EVT models

Tomlinson, Matthew F.; Greenwood, David; … - 2024

Persistent link: https://ebvufind01.dmz1.zbw.eu/10014450274

What can volatility smiles tell us about the too big to fail problem?

Ngo, Phong T. H.; Puente-Moncayo, Diego L. - 2024

Persistent link: https://ebvufind01.dmz1.zbw.eu/10014520129

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What Can Volatility Smiles Tell Us About the Too Big to Fail Problem?

Ngo, Phong T. H.; Puente-Moncayo, Diego - 2021

Book / Working Paper

Volatility and models based on the extreme value theory for gold returns

Krężołek, Dominik; Piontek, Krzysztof - 2024

In this study, we use daily gold log-returns to analyse the quality of forecasting expected shortfalls (ES) using volatility and models based on the extreme value theory (EVT). ES forecasts were calculated for conditional APARCH models formed on the entire distribution of returns, as well as for...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015125518

Forecasting tail risk of skewed financial returns having exponential-polynomial tails

Antwi, Albert; Gyamfi, Emmanuel Numapau; Adam, Anokye M. - 2024

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015110551

A unified theory of extreme Expected Shortfall inference

Daouia, Abdelaati; Stupfler, Gilles; Usseglio-Carleve, … - 2024

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015097279

Tail risk spillover network among green bond, energy and agricultural markets under extreme weather scenarios

Xue, Jianhao; Dai, Xingyu; Zhang, Dongna; Nghiem, Xuan-Hoa - 2024

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015323526

Multiple outlier detection in samples with exponential & pareto tails

Sornette, Didier; Wei, Ran - 2024

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015110737

Extreme risk spillovers between stock and bond markets

Ning, Cathy Q.; Ponrajah, Jeremey - 2024

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015052590

Maximum lq-likelihood estimator of the heavy-tailed distribution parameter

Kouider, Mohammed Ridha; Idiou, Nesrine; Toumi, Samia; … - 2024

Studying the extreme value theory (EVT) involves multiple main objectives, among them the estimation of the tail index parameter. Some estimation methods are used to estimate the tail index parameter like maximum likelihood estimation (MLE). Additionally, the Hill estimator is one type of...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015375901

Locally tail-scale invariant scoring rules for evaluation of extreme value forecasts

Olafsdottir, Helga Kristin; Rootzén, Holger; Bolin, David - 2024

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015438505

Bayesian inference for income inequality using a Pareto II tail with an uncertain threshold : combining EU-SILC and WID data

Silva, Mathias; Lubrano, Michel - 2024

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015130401

Modeling extreme events : time-varying extreme tail shape

D'Innocenzo, Enzo; Lucas, André; Schwaab, Bernd; Zhang, Xin - 2024

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015053506

Extremes in FX returns and fundamentals

Cumperayot, Phornchanok J.; Vries, Casper G. de - 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015579741

When to be discrete : the importance of time formulation in the modeling of extreme events in finance

Bień-Barkowska, Katarzyna; Herrera, Rodrigo - 2026

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015667963

From Extreme Events to Extreme Seasons

Dolk, Michaela; Laliotis, Dimitrios; Lamichhane, Sujan - 2024

This paper explores the financial stability implications of acute physical climate change risks using a novel approach focusing on a severe season associated with a series of tropical cyclone and flood events. Our approach was recently applied to study physical risks in the Mexican financial...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10014578931

Testing extreme warming and geographical heterogeneity

Gadea, María Dolores; Gonzalo, Jesús; Olmo, Jose - 2024

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015395810

Extreme value estimation for heterogeneous data

Einmahl, John H. J.; He, Yi - 2023

Persistent link: https://ebvufind01.dmz1.zbw.eu/10013540838

Tail recovery

Xu, Teng Andrea - 2024

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015195623

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Tail Recovery

Xu, Teng Andrea - 2023

Book / Working Paper

Extreme value theory modelling of the behaviour of Johannesburg stock exchange financial market data

Metwane, Maashele Kholofelo; Maposa, Daniel - 2023

Financial market data are abundant with outliers, and the search for an appropriate extreme value theory (EVT) approach to apply is an endless debate in the statistics of extremes research. This paper uses EVT methods to model the five-year daily all-share total return index (ALSTRI) and the...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10014484249

Analyzing and forecasting electricity price using regime-switching models : the case of New Zealand market

Kapoor, Gaurav; Wichitaksorn, Nuttanan; Zhang, WenJun - 2023

Persistent link: https://ebvufind01.dmz1.zbw.eu/10014432832

Tail Risk

Chow, Victor; Gu, Jiahao; Wang, Zhan - 2023

We develop a utility and asset pricing theory that features a novel measure of tail risk. Our model determines investor demand for both left and right-tail risk premia from an indifference curve incorporating tolerance for variance and tail risk. We show that the systematic tail risk factors...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10014355700

Understanding Uncertainty Shocks and the Role of Black Swans

Veldkamp, Laura; Orlik, Anna - 2023

Economic uncertainty is a powerful force in the modern economy. Research shows that surges in uncertainty can trigger business cycles, bank runs and asset price fluctuations. But where do sudden surges in uncertainty come from? This paper provides a data-disciplined theory of belief formation...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10014357057

Discovering intraday tail dependence patterns via a full-range tail dependence copula

Hua, Lei - 2023

In this research, we employ a full-range tail dependence copula to capture the intraday dynamic tail dependence patterns of 30 s log returns among stocks in the US market in the year of 2020, when the market experienced a significant sell-off and a rally thereafter. We also introduce a...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10014436379