The life insurance sector plays a critical role in financial system stability but is inherently exposed to extreme market fluctuations due to long-term liabilities and asset–liability mismatches. This study investigates extreme losses in the gr...
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/...
This study examines the effectiveness of Generalised Additive Models (GAMs) and log-log linear models for estimating the parameters of the generalised extreme value (GEV) distribution, which are then used to estimate flood quantiles in ungauged catch...
With evidence suggesting that climate change is resulting in changes within the hydrologic cycle, the ability to robustly model hydroclimatic response is critical. This paper assesses how extreme runoff—1:2- and 1:30-year return period (RP) eve...
This study presents regionalisation of the Generalised Extreme Value (GEV) distribution by adopting L moments and Bayesian Generalised Least Squares (BGLS) regression. This uses data from 88 gauged catchments in New South Wales, Australia. The region...
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 escalating frequency and intensity of extreme rainfall events driven by climate change threaten infrastructure resilience and societal safety, underscoring the urgent need for robust models to predict these events. Previous studies on the integra...
This study uses and compares stationary and non-stationary Generalised Extreme Value Distribution (GEVD) to model the behaviour of nitrogen dioxide (NO2) emission maxima from each of 13 Eskom’s coal-fuelled power stations. The pollutant is mode...
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...
During the past decades, seasonal autoregressive integrated moving average (SARIMA) had become one of a prevalent linear models in time series and forecasting. Empirical research advocated that forecasting with non-linear models can be an encouraging...
In this paper, a hybrid of a Wavelet Decomposition–Generalised Auto-Regressive Conditional Heteroscedasticity–Extreme Value Theory (WD-ARMA-GARCH-EVT) model is applied to estimate the Value at Risk (VaR) of BitCoin (BTC/USD) and the South...
Hydrological modelling to address the problem of flood risk corresponding to climate change can play an important role in water resources management. This paper describes the potential impact of climate change on an urban river catchment using a phys...
Accurate modelling of near surface wind speeds is essential for robust resource assessment, turbine design, and grid integration. This study presents a unified framework comparing four candidate marginal distributions—Weibull, Gamma, Lognormal,...
Cryptocurrencies are said to be very risky, and so are the currencies of emerging economies, including the South African rand. The steady rise in the movement of South Africans’ investments between the rand and BitCoin warrants an investigation...
Any damaged condition is a rare occurrence for mechanical systems, as it is very unlikely to be observed. Thus, it represents an extreme deviation from the median of its probability distribution. It is, therefore, necessary to apply proper statistica...
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...
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) a...
This study uses a hybrid model of the exponential generalised auto-regressive conditional heteroscedasticity (eGARCH)-extreme value theory (EVT)-Gumbel copula model to investigate the dependence structure between Bitcoin and the South African Rand, a...
This study presents a comprehensive assessment of historical and projected variability in the wind climate over Ireland and its adjacent marine regions, including the North Atlantic Ocean, Irish Sea, and Celtic Sea. First, the long-term wind characte...
Water is essential to all lifeforms including various ecological, geological, hydrological, and climatic processes/activities. With the changing climate, associated El Niño/Southern Oscillation (ENSO) events appear to stimulate highly uncertain patte...
Rainfall is a significant input for several engineering designs such as hydraulic structures, culverts, bridges and ducts, rainfall water sewer, and highway drainage system. The detailed statistical analysis of extreme daily rainfall of each arid env...
The expansion of urban areas and the increasing frequency and magnitude of intense rainfall events are anticipated to contribute to the widespread escalation of urban flood risk across the globe. To effectively mitigate future flood risks, it is cruc...
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Due to its location, its old sewage system, and the channelling of rivers, Oslo is highly exposed to urban flooding. Thus, it is crucial to provide relevant and reliable information on extreme precipitation in the planning and design of infrastructur...
The extreme rainfall events of recent years in central Italy are producing an increase in hydrogeological risk, with disastrous flooding in terms of human lives and economic losses, as well as triggering landslide phenomena in correspondence with the...
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...
Building performance and material change of cultural heritage in urban areas are negatively impacted by wind-driven rain (WDR). The frequency and intensity of WDR exposure are modified by climate change. Current approaches to exposure assessment emph...
Earthquake-induced liquefaction is one of the main causes of levee breaches that can threaten human life and property. Conventionally, liquefaction hazard has been assessed in terms of the factor of safety
This paper provides an Extreme Value Analysis (EVA) of the hourly water level record at Fort Denison dating back to 1915 to understand the statistical likelihood of the combination of high predicted tides and the more dynamic influences that can driv...
When one is using climate simulation outputs, one critical issue to consider is the systematic bias affecting the modelled data. The bias correction of modelled data is often used when one is using impact models to assess the effect of climate events...
River water quality assessment has traditionally been conducted using univariate or threshold-based approaches; however, the exploration of extremes assessment under bivariate water quality variables has been limited by many studies. Understanding th...
The Einstein equivalence principle is based on the equality of gravitational and inertial mass, which has led to the universality of a free-fall concept. The principle has been extremely well tested so far and has been tested with a great precision....
Understanding the nature of frequent floods is important for characterising channel morphology, riparian and aquatic habitat, and informing river restoration efforts. This paper presents results from an analysis on frequency estimates of low magnitud...
Extreme rainfall events have made significant damages to properties, public infrastructure and agriculture in some provinces of South Africa notably in KwaZulu-Natal and Gauteng among others. The general global increase in the frequency and intensity...
The frequency and severity of extremes, including extreme precipitation events, extreme evapotranspiration and extreme water storage deficit events, are changing. Thus, the necessity for developing a framework that estimates non-stationary conditions...
The severity and frequency of extremes are changing; thus, it is becoming necessary to evaluate the impacts of land cover changes and urbanisation along with climate change. A framework of the Generalised Extreme Value (GEV) method, Google Earth Engi...
The classical Chow test for structural instability requires strictly exogenous regressors and a break-point specified in advance. In this paper, we consider two generalisations, the one-step recursive Chow test (based on the sequence of studentised r...
Accurate prediction of winter oilseed rape yield is essential for optimising crop management and improving production efficiency. However, the reliability of commonly reported model performance remains uncertain due to the widespread use of random va...
The formation mechanism of extreme waves in the coastal areas is still an open contemporary problem in fluid mechanics and ocean engineering. Previous studies have shown that the transition of water depth from a deeper to a shallower zone increases t...
This paper demonstrates seasonal variations in the generalised extreme value (GEV) distribution shape parameter and discrepancies in GEV types within the same location. Daily rainfall data from 26 rain gauge stations located in Tasmania were used as...
Regulatory risk measurement under Basel III’s Fundamental Review of the Trading Book places Expected Shortfall (ES) at the center of market risk capital, yet the fourth-order Edgeworth expansion, still widely used for Value-at-Risk (VaR) and ES...
Intensity–Frequency–Duration Curves (IDF curves) are a tool applied in hydraulic and hydrology engineering to design infrastructure for rainfall management. They express how precipitation, with a defined duration (D) and intensity (I), is...
In the context of global warming, the Clausius–Clapeyron (CC) relationship has been widely used as an indicator of the evolution of the precipitation regime, including daily and sub-daily extremes. This study aims to verify the existence of lin...
This study evaluates the wind energy potential of Polokwane, South Africa, using statistical distribution models to estimate wind power density (WPD) and assess turbine performance under low-wind inland conditions. Hourly wind speed and direction dat...
This study assesses whether the association of place-branded foods and the adoption of responsible and sustainable management practices (e.g., quality management, environmental management, and corporate social responsibility) influence the financial...
Natural disasters can cause severe damages to civil infrastructure and lead to extensive economic losses and casualties. To improve the emergency response capability of civil infrastructure under extreme circumstances such as natural disasters and hu...
This study investigates wind speed prediction using advanced machine learning techniques, comparing the performance of Vanilla long short-term memory (LSTM) and convolutional neural network (CNN) models, alongside the application of extreme value the...
Accurate forecasting of local weather patterns is essential for climate resilience and sustainable planning. This study analysed 35 years (1990–2025) of hourly temperature and precipitation data from Thohoyandou, South Africa, to assess the imp...
Land cover changes in mountainous regions are potential precursors to landslide disasters. However, the effects of past long-term land cover changes on the characteristics of recent landslides remains underexplored. We studied land cover evolution ov...
The objective of this study was to model the operation of a vertical-flow constructed wetland (VF-CW) for domestic wastewater, using Monte-Carlo simulations and selected probability distributions of various random variables. The analysis was based on...
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