Several new asymmetric distributions have arisen naturally in the modeling extreme values are uncovered and elucidated. The present paper deals with the extreme value theorem (EVT) under exponential normalization. An estimate of the shape parameter o...
The main aim of this study is to determine the threshold values for extreme sea and weather events on the Polish Baltic coast. The study is based on daily hydrometeorological data on the sea level; air temperature and atmospheric precipitation collec...
Recently, simulation-based methods for assessing company-specific risks have become increasingly popular in corporate finance. This is because modern capital market theory, with its assumptions of perfect and complete capital markets, cannot satisfac...
21 February 2022
A marathon was recently run in less than 2 h by a man who ran the three fastest marathons ever recorded in a span of three years—Eliud Kipchoge—in the Tokyo Olympic games. Here, we demonstrate that the best marathons were run according to...
Recognizing that, over the last several years, extreme rainfall has led to hazardous stress in humans, animals, plants, and even infrastructure, in the present study, we aimed to investigate the characteristics of droughts over the Free State (FS) Pr...
In the subject of statistics for engineering, physics, computer science, chemistry, and earth sciences, one of the sampling challenges is the accuracy, or, in other words, how representative the sample is of the population from which it was drawn. A...
On 13 February 2020, The Guardian, followed by many other newspapers and websites, published the news that on 9 February 2020, Antarctic air temperatures rose to about 20.75 ∘C in a base logged at Seymour Island. This value has not yet been validated...
Wi-Fi-based fingerprint indoor positioning technology has gained special attention, but the development of this technology has been full of challenges such as positioning time cost and positioning accuracy. Therefore, selecting reasonable Wireless Ac...
Probability-based distributions might be able to explain risk exposure well. Usually, one number, or at the very least, a limited number of numbers called the key risk indicators (KRIs), are used to describe the level of risk exposure. These risk exp...
This Perspective synthesizes recent (2023–2025) progress in predicting extreme environmental values by combining empirical formulations, physics-based simulation outputs, and sensor-network data. We argue that hybrid approaches—spanning p...
We analyze extreme gold price movements between 1975 and 2025 using Extreme Value Theory (EVT). Using both the Block-Maxima and Peaks-over-Threshold approaches on a daily return basis, we estimate Value-at-Risk (VaR) and Expected Shortfall (ES) for t...
We study the extreme value distribution of stochastic processes modeled by superstatistics. Classical extreme value theory asserts that (under mild asymptotic independence assumptions) only three possible limit distributions are possible, namely: Gum...
Bayesian extreme value analysis was used to forecast the optimal point in agricultural commodity futures prices in the United States for cocoa, coffee, corn, soybeans and wheat. Data were collected daily between 2000 and 2020. The estimation of extre...
When extreme wind pressure is predicted based on the extreme value distribution theory, the sampling time–distance and sample volume of wind pressure data are important influencing factors. To discuss and analyze the influence of time–dis...
In the present paper, a new special function, the so-called extreme value H-function, is introduced. This new function, which is a generalization of the H-function with a particular set of parameters, appears while dealing with products and quotients...
Since the 2008 financial crisis, modelling of the extreme values of financial risk has become important [...]
This paper uses the Extreme Value Theory (EVT) to model the rare events that appear as delivery delays in road transport. Transport delivery delays occur stochastically. Therefore, modeling such events should be done using appropriate tools due to th...
This study models the spatiotemporal heterogeneity of extreme rainfall over the Korean Peninsula using the generalised additive extreme value models (EVGAM) to address the limitations of traditional stationary approaches under climate change. Analyzi...
The reliability of extreme wind speed predictions at large mean recurrence intervals (MRI) is assessed by bootstrapping samples from representative known distributions. The classical asymptotic generalized extreme value distribution (GEV) and the gen...
This study concentrates on a new approach for solving a class of multi-cost convex interval-valued extremization problems. Namely, we apply the weighting technique to find efficient solutions to these problems, defined in terms of LU-efficiency and w...
Wind and waves present the main causes of environmental loading on seagoing ships and offshore structures. Thus, its detailed understanding can improve the design and maintenance of these structures. Wind and wave statistical models are developed bas...
This study reviews advanced extreme value theory techniques and applies them to extreme rainfall events recorded at two meteorological stations, Port Edward and Virginia, in the KwaZulu-Natal province of South Africa. The study aims to provide a comp...
In this work, the authors investigated the feasibility of calibrating a model which is suitable for the generation of continuous high-resolution rainfall series, by using only data from annual maximum rainfall (AMR) series, which are usually longer t...
This paper develops a method for assessing portfolio tail risk based on extreme value theory. The technique applies separate estimations of univariate series and allows for closed-form expressions for Value at Risk and Expected Shortfall. Its forecas...
In this study, we analyze the risk of extreme value dependence in Chinese regional carbon emission markets. After filtering the daily return data of six carbon markets in China using a generalized autoregressive conditional heteroscedasticity (GARCH)...
This paper aims to mark out new concepts of r-single valued neutrosophic sets, called r-single valued neutrosophic £-closed and £-open sets. The definition of £-single valued neutrosophic irresolute mapping is provided and its chara...
The generalized Pareto distribution is frequently used for modeling extreme values above an appropriate threshold level. Since the process of determining the appropriate threshold value is difficult, a mixture of extreme value models rises to promine...
Floods are the most common and widely distributed natural risk, causing over £1 billion of damage per year in the UK as a result of recent events. Climatic projections predict an increase in flood risk; it becomes urgent to assess climate change imp...
The Hurwitz complex continued fraction is a generalization of the nearest integer continued fraction. In this paper, we prove various results concerning extremes of the modulus of Hurwitz complex continued fraction digits. This includes a Poisson law...
Extreme value modeling for extreme rainfall is one of the most important processes in the field of hydrology. For the improvement of extreme value modeling and its physical meaning, large-scale climate modes have been widely used as covariates of dis...
Biomarkers are measurements of biological variables that can determine a state of health. They consist of measuring a single variable or a combination of variables related to the state of health that these variables represent. Biomarkers can provide...
Climate change poses higher requirements on ocean engineering design, and reasonable estimation of design wave heights plays a crucial role in coastal protection and offshore engineering. Extreme value analysis is widely used in frequency calculation...
This paper attempted to calculate the market risk in the Tehran Stock Exchange by estimating the Conditional Value at Risk. Since the Conditional Value at Risk is a tail-related measure, Extreme Value Theory has been utilized to estimate the risk mor...
In this paper, the generalised extreme value distribution (GEVD) model is employed to estimate financial risk in the form of return levels and the value at risk (VaR) for the two exchange rates, BitCoin/US dollar (BTC/USD) and the South African rand/...
A characterizing property of Zenga (1984) inequality curve is exploited in order to develop an estimator for the extreme value index of a distribution with regularly varying tail. The approach proposed here has a nice graphical interpretation which p...
We consider a risk-aware multi-armed bandit framework with the goal of avoiding catastrophic risk. Such a framework has multiple applications in financial risk management. We introduce a new conditional value-at-risk (CVaR) estimation procedure combi...
This paper deals with the extreme value analysis for the triangular arrays which appear when some parameters of the mixture model vary as the number of observations grows. When the mixing parameter is small, it is natural to associate one of the comp...
Due to its geographical position, Mexico is exposed annually to cold fronts and tropical cyclones, registering extremely high values that are atypical in the series of maximum annual flows. Univariate mixed probability distribution functions have bee...
As the distribution function of traffic load effect on bridge structures has always been unknown or very complicated, a probability model of extreme traffic load effect during service periods has not yet been perfectly predicted by the traditional ex...
Earthquake catastrophe bond pricing models (ECBPMs) employ extreme value theory (EVT) to predict severe losses, although studies on EVT’s use in ECBPMs are still rare. Therefore, this study aimed to use a mini-review approach (MRA) to examine t...
Arguably, the most fundamental problem in Network Science is finding structure within a complex network. Often, this is achieved by partitioning the network’s nodes into communities in a way that maximizes an objective function. However, findin...
In this paper, we study the existence of extremal solutions for a Caputo-type fractional-order initial value problem. By using the monotone iteration technique and the upper–lower solution method, we obtain our existence theorem when the nonlin...
We present an enhanced Extreme Value Analysis (EVA) framework designed to improve the forecasting of extremely low-production events in photovoltaic (PV) systems and to reveal the key inter-variable relationships governing performance under extreme c...
One of the key components of financial risk management is risk measurement. This typically requires modeling, estimating and forecasting tail-related quantities of the asset returns’ conditional distribution. Recent advances in the financial ec...
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...
Clustering is a critical part of many tasks and, in most applications, the number of clusters in the data are unknown and must be estimated. This paper presents an Extreme Value Theory-based approach to threshold selection for clustering, proving tha...
This paper proposes the lower-bounded Fréchet–log-logistic distribution (LFLD), a probability model designed for robust flood frequency analysis (FFA). The LFLD addresses key limitations of traditional distributions (e.g., generalized ex...
The field of statistical extreme value theory (EVT) focuses on estimating parameters associated with extreme events, such as the probability of exceeding a high threshold or determining a high quantile that lies at or beyond the observed data range....
In recent times, investing in volatile security increases the risk of losses and reduces gains. Many traders who depend on these risks indulge in multiple volatility procedures to inform their trading strategies. We explore two models to measure the...
The advantage of quantum mechanics to shift up the ability to econometrically understand extreme tail losses in financial data has become more desirable, especially in cases of Value at Risk (VaR) and Expected Shortfall (ES) predictions. Behind the n...
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