Exposure Of Assets Research Articles

Rapid remote volcanic ashfall impact assessment for the 2022 eruption of Hunga volcano, Tonga: a bespoke approach and lessons identified

When disasters occur, rapid impact assessments are required to prioritise response actions, support in-country efforts and inform the mobilisation of aid. The 15 January 2022 eruption of Hunga volcano, Tonga, and the resulting atmospheric shockwave, ashfall, underwater mass disturbance and tsunami, caused substantial impacts across the Kingdom of Tonga. Volcanic impacts on the scale observed after the eruption are rare, necessitating a reliance on international advice and assistance. The situation was complicated by the loss of Tonga’s international submarine fibreoptic cable (causing a complete loss of communications for approximately 20 days) along with border closures due to the COVID-19 pandemic. A need emerged for a rapid remote volcanic impact assessment and provision of specialist advice to help inform the response of international partners. Here we present a novel methodology for conducting rapid remote volcanic ashfall impact assessments, conducted over a 10-day period following the eruption. We used three different hazard models for ashfall thickness across the main island of Tongatapu and available asset information and vulnerability functions for buildings, agriculture, electricity networks, water supply and roads, to provide initial estimates of losses due to ashfall from the 15 January eruption. For buildings, we estimated losses both as total losses and as percentages of the total replacement cost of buildings on Tongatapu. For agriculture, we made probabilistic estimates of production losses for three different crop classes. For ashfall clean-up, we estimated ranges of ashfall volumes requiring clean-up from road surfaces and roofs. For water supply, electricity networks and roads, our analysis was limited to assessing the exposure of important assets to ashfall, as we had insufficient information on system configurations to take the analysis further. Key constraints on our analysis were the limited nature of critical infrastructure asset inventories and the lack of volcanic vulnerability models for tropical regions including Pacific Island nations. Key steps towards iteratively improving rapid remote impact assessments will include developing vulnerability functions for tropical environments as well as ground-truthing estimated losses from remote approaches against in-person impact assessment campaigns.

The Hedging Channel of Exchange Rate Determination

Abstract We propose the currency hedging channel that connects countries’ external imbalances to their exchange rate behavior. We present a model in which investors increase their currency hedging during periods of financial distress in proportion to their net foreign asset exposure. This behavior coupled with constrained financial intermediation explains observed relationships between gradually adjusting external imbalances and volatile spot and forward exchange rates. We find empirical support for the hedging channel in both the conditional and unconditional moments of exchange rates, option prices, and countries’ uses of Federal Reserve swap lines. (JEL E44, F31, F32, F41, G11, G15)

Hedging the climate change risks of China's brown assets: Green assets or precious metals?

A large discrepancy exists between the dire impact of climate change projected by most natural scientists and the modest estimates of damages calculated by mainstream economists. In this article, we first measure the climate risk, including the transition and physical risks, in China using textual analysis. Then, considering the heterogeneity of climate change's effect, we investigate the impact of climate risks on the brown and green assets of China (including price, volatility, and correlation) for the period from February 2012 to April 2022. In addition, the performance of China's green assets and international precious metal assets is examined in hedging the climate risk exposure of China's brown assets. The results reveal that transition and physical risks lead to contrary changes in the prices of brown and hedging assets. Transition risk causes the volatility of brown and green assets to change in the opposite direction, while physical risk causes the volatility of the two types of assets to change in the same direction. Under extreme climate risk conditions, the correlation between brown and hedging assets decreases. Finally, the findings show that the performance of international precious metals in hedging climate risk exposure is better than that of China's green equity assets.

Optimal dynamic climate adaptation pathways: a case study of New York City

AbstractAssessing climate risk and its potential impacts on our cities and economies is of fundamental importance. Extreme weather events, such as hurricanes, floods, and storm surges can lead to catastrophic damages. We propose a flexible approach based on real options analysis and extreme value theory, which enables the selection of optimal adaptation pathways for a portfolio of climate adaptation projects. We model the severity of extreme sea level events using the block maxima approach from extreme value theory, and then develop a real options framework, factoring in climate change, sea level rise uncertainty, and the growth in asset exposure. We then apply the proposed framework to a real-world problem, considering sea level data as well as different adaptation investment options for New York City. Our research can assist governments and policy makers in taking informed decisions about optimal adaptation pathways and more specifically about reducing flood and storm surge risk in a dynamic settings.

Nurturing partnerships to support data access for impact forecasts and warnings: Theoretical integration and synthesis

This paper presents a synthesis and theoretical integration of findings from a research project that explored the data needs and sources for implementing impact forecasts and warnings for hydrometeorological hazards. Impact forecasts and warnings (IFW) have received global attention in recent years as they offer a novel way of improving the communication of hazards and risks. The fundamental idea behind IFWs is to enable warning services to meaningfully communicate the anticipated outcomes, consequences, or impacts of the hazard interacting with society or the environment by incorporating knowledge about the underlying and dynamic exposure and vulnerability of people and assets. One key question for IFW implementation is about data needs and sources to inform IFWs.Using the Grounded Theory Methodology, we address the question “How can partnerships and collaboration better facilitate the collection, creation, and access to hazard, impact, vulnerability, and exposure data for IFWs?” Our findings point to partnerships and collaboration as a necessary strategy for implementing IFWs. Implementation requires accessing various types and sources of hazard, impact, vulnerability, and exposure data to assess and communicate the potential impacts of hydrometeorological hazards. Partnerships and collaboration facilitate the sharing of and access to required data and knowledge. Based on our findings, we provide recommendations to increase interagency communication and partnerships for IFWs and disaster risk reduction, such as making cohabitation arrangements between agencies, running joint training scenarios, and encouraging meteorological services and emergency responders to co-define tailored warning thresholds.

MCDM-Based Wildfire Risk Assessment: A Case Study on the State of Arizona

The increasing frequency of wildfires has posed significant challenges to communities worldwide. The effectiveness of all aspects of disaster management depends on a credible estimation of the prevailing risk. Risk, the product of a hazard’s likelihood and its potential consequences, encompasses the probability of hazard occurrence, the exposure of assets to these hazards, existing vulnerabilities that amplify the consequences, and the capacity to manage, mitigate, and recover from their consequences. This paper employs the multiple criteria decision-making (MCDM) framework, which produces reliable results and allows for the customization of the relative importance of factors based on expert opinions. Utilizing the AROMAN algorithm, the study ranks counties in the state of Arizona according to their wildfire risk, drawing upon 25 factors categorized into expected annual loss, community resilience, and social vulnerability. A sensitivity analysis demonstrates the stability of the results when model parameters are altered, reinforcing the robustness of this approach in disaster risk assessment. While the paper primarily focuses on enhancing the safety of human communities in the context of wildfires, it highlights the versatility of the methodology, which can be applied to other natural hazards and accommodate more subjective risk and safety assessments.

SIGeR-RV: A Web-Geographic Information System-Based System for Risk Management of Road Networks Exposed to Natural Hazards

The consequences of natural hazards are frequently estimated by the direct cost of recovering damaged infrastructure and the indirect costs to road users, economic activities, and impacts on society. Road networks are crucial in economic systems, logistic chain continuity, accessibility, mobility, and the evacuation of population during and after extreme events. Risk management systems (RMS) are used to estimate the potential consequences of natural events and to assess strategies for risk reduction. These commonly assess hazards, assets exposure, economic losses, and risk mitigation actions, among others. The general framework of RMS can be adapted to different scenarios. Still, local characteristics, such as the types of hazards and physical assets, cannot always be directly adopted from these systems. This study discusses the development of SIGeR-RV, an RMS developed in Chile for road networks exposed to multiple natural hazards. The RMS was implemented in a web-based geographic information system platform able to display hazard maps, quantify risk levels, prioritize mitigation strategies, and estimate direct and indirect costs and social vulnerability. The content and various capacities of the system are detailed, following the steps marked in its framework. This first version of SIGeR-RV considers seismic hazard, volcanic lahars, and hydro-meteorological hazards that affect road platforms, bridges, tunnels, and cut slopes. The system currently serves as a tool for the Ministry of Public Works of Chile and other decision makers to estimate budget requirements for increasing resilience of the road network, identifying vulnerable road segments, and assessing the socioeconomical impacts of risk reduction.

Future socioeconomic development along the West African coast forms a larger hazard than sea level rise

Sea level rise will exacerbate the vulnerability of low-lying coastal regions around the world in the coming decades, posing a severe threat to coastal populations. Here, we assess the future population and asset exposure of West Africa (WA) to normal and extreme coastal flooding based on the projected sea level rise scenarios reported in the IPCC Sixth Assessment Report using a bathtub modeling approach, MERIT DEM and gridded population gross domestic product datasets that are consistent with the Shared Socioeconomic Pathways. We find that socioeconomic development will be responsible for the maximum increase in future coastal flooding along the WA coast towards the end of the century. While contributions from climate-induced sea level rise will dominate and be responsible for changes in coastal flooding events in some countries, exposure to these events is likely to dominate in many countries if the ongoing horizontal infrastructural development and economic-oriented transformation continue. These results have important implications for both sustainable coastal planning and flooding risk mitigation for WA’s coastal areas and should be considered as a cautionary tale for managing increasing socioeconomic development and coastward migration at the expense of the region’s coastal ecosystems.

Gold and the herd of Cryptos: Saving oil in blurry times

This paper assesses the effectiveness of a broad set of 1066 active and continuously traded cryptocurrencies as a safe haven instrument against extreme oil price movements, in comparison to the corresponding roles of gold. The uncertainty for the oil market during the COVID-19 pandemic and the subsequent Russia–Ukraine conflict set the tone for natural experiments for our study. We use a trail-blazing dynamic generalized autoregressive score model to estimate the tail riskiness of the potential safe haven assets from January 1, 2020, to September 30, 2022. By estimating the risk exposure of all cryptocurrency assets, we determine top ten safest assets for investment. Our results show the emergence of new safe haven cryptocurrencies, which have previously been ignored by the academic literature and policy makers alike. Intriguingly, our findings reveal that gold has been replaced by altcoins as the safest assets during both the COVID-19 pandemic and the Russia–Ukraine conflict. At this instance, our findings suggest that Bitcoin provides lengthier safe haven properties than gold for oil returns in both periods. However, the safe haven properties of gold and cryptocurrencies are time varying. Last but not least, we introduce a new Cryptocurrency Tail Risk Index (CTRI) that captures the risk exposure of cryptocurrency market, as a whole. Our results suggest that investment in numerous cryptocurrencies provides lengthier safe haven properties than investing in gold alone.

Modelling economic risk to sea‐level rise and storms at the coastal margin

AbstractWe develop a methodological approach through integrated assessment using System Dynamics modelling and Scenario Planning to investigate the economic vulnerability of coastal communities to the compounding impacts of sea‐level rise (SLR) and storm flooding and inundation associated with climate change. The approach uses a coastal flood risk assessment that quantifies physical drivers alongside socio‐economic well‐being for coastal communities to provide a methodology for managing uncertain futures through causal relationships in System Dynamics. A New Zealand case study is used to illustrate the long‐term economic impacts of inaction under different SLR projections and recognise critical tolerance thresholds to help exposed property owners plan their future. Modelling scenarios using this integrated approach identified two stand‐out drivers that influence a behavioural response of communities to coastal inundation at the local scale: first, the ongoing likelihood of risk transfer to the insurance industry, and second, the decisions of households and firms to accept risk for the added value of coastal living. Model outputs suggest that the threat posed by coastal hazards drives a behavioural, socio‐economic response that exceeds the initial economic exposure of capital assets. In the economic short term (1–10 years) and medium term (10–20 years), vulnerable communities accept the risk of capital loss and loss of insurability, favouring the amenity of coastal living. However, in the long term (+20 years), economic losses from repeat flooding increase risk‐based insurance premiums, promote insurance withdrawal and drive negative corrections in property valuations. Unanticipated insights were obtained from the modelling, including the likely timing of tolerance thresholds, particularly the insurance withdrawal point, which is critical to insurer/consumer decision‐making and community planning.

A Model for Enhancing the Information Security Management Systems in Yemen Banks

Exposure of valuable assets of Yemen banking sector to various attacks and threats may violate the privacy, confidentiality, integrity and accessibility (availability) of their data, information or computer systems resulting in financial and valuable loss. Such a violation may adversely affect the continuity of the business and the competitive advantages they seek to achieve. The objective of this paper is to evaluate the current security performance of banking systems in Yemen and to introduce a framework for improving information security management based on the ISO 27002-2013 benchmark and standards. The proposed framework includes important security factors which are people, technology and process. IBM SPSS AMOS is applied for testing framework hypothesis on complex variable relationships and gain new insight. Such framework shows that the process variable has obtained the most direct positive effect on improving information security management system with value (0.990), while the technology variable has obtained the second direct positive effect on improving the information security management system with value (0.930). Finally, the people variable has obtained the least direct positive effect on improving the information security management system with value (0.740). The research methodology includes: data collection, data analysis, reliability testing and computing results. The model validated and compared with other similar models available in the literature and the results were in valid range. Also, the research hypotheses were significant and deferent results of the proposed model were very promising.

Understanding the Drivers of Coastal Flood Exposure and Risk From 1860 to 2100

AbstractGlobal coastal flood exposure (population and assets) has been growing since the beginning of the industrial age and is likely to continue to grow through 21st century. Three main drivers are responsible: (a) climate‐related mean sea‐level change, (b) vertical land movement contributing to relative sea‐level rise, and (c) socio‐economic development. This paper attributes growing coastal exposure and flood risk from 1860 to 2100 to these three drivers. For historic flood exposure (1860–2005) we find that the roughly six‐fold increase in population exposure and 53‐fold increase in asset exposure are almost completely explained by socio‐economic development (>97% for population and >99% for assets). For future exposure (2005–2100), assuming a middle‐of‐the‐road regionalized socio‐economic scenario (SSP2) without coastal migration and sea‐level rise according to RCP2.6 and RCP6.0, climate‐change induced sea‐level rise will become the most important driver for the growth in population exposure, while growth in asset exposure will still be mainly determined by socio‐economic development.

Inflation Forecasts and European Asset Returns: A Regime-Switching Approach

Considering market-based inflation expectations, we show that investors’ forecasts are non-linear. We capture this non-linear behavior with a Markov-switching model that allows us to identify a regime of high uncertainty, and a regime of low uncertainty and low concern about inflation. Using a complete cross-asset panel of equity sectors, bonds, and commodities, we perform regressions in both regimes including several control variables, and show that the exposure of European assets returns to implied inflation is regime-dependent. We show that inflation-indexed government bonds and oil are the best way to get exposure to slow upward revisions of future inflation that correspond to periods of rallying inflation. We thus identify alternatives to hedge oneself against revisions in inflation forecasts when inflation is considered as a variable of interest by market participants, which, in fact, corresponds to periods of breaks in the trend of realized inflation. In particular, we provide empirical evidence that some equity sectors exhibit good inflation-hedging properties.

An Unsettled “Stranded Asset Debt”? Proposing a Supply‐Side Counterpart to the “Climate Debt” in a Bid to Guide a Just Transition from Fossil Fuels in South Africa and Beyond

AbstractThe reign of the fossil fuel empire must come to an end if the average global temperature rise is to be meaningfully capped. Accordingly, a myriad of financial and non‐financial stranded assets will be generated in the process. Ample research has explored the implications for a South African fossil transition from a domestic perspective, but a lacuna persists in linking South Africa’s fossil regime to broader international finance flows, and particularly the role that actors from the “global North” should play in phasing out South African fossil fuels. This research finds that such institutions have exacerbated South Africa’s prospective stranded asset exposure, and by doing so, have accrued a Stranded Asset Debt (SAD)—as a supply‐side counterpart to the demand‐side climate debt, which they have also accumulated—perhaps to the tune of at least several dozens of billions of dollars. Although the Paris Agreement is flawed, it embodies language that can be leveraged to settle the SAD “bill”.

A GIS-based approach for estimating community transportation exposure and capacity in the context of disaster resilience

Transportation is a critical sector for communities. It is, however, particularly vulnerable to climate change, and a disruption in its infrastructure impacts the whole community. Enhancing the resilience of transportation infrastructure is vital for reliable and sustainable functionalities, and subsequently, to more resilient communities. There are indices and frameworks that assess and evaluate transportation resilience and performance, ranging from component-based, to network and system metrics. The existing approaches, however, usually overlook location and capacity of critical transportation components. These two characteristics possess significant effects on the resilience and performance of the transportation sector. Moreover, the stress type and its magnitude should be incorporated in the resilience assessment. In this work, we leverage a recent resilience quantification framework to compute the Exposure and Capacity-based Transportation Resilience Index (EC-TRI), describing the resilience of the transportation infrastructure, focusing on the location and capacity of certain assets. We argue for the adoption of this index as a complement to existing frameworks, and we develop a web-based GIS framework to evaluate EC-TRI for communities within New Jersey (NJ). The novelty of EC-TRI lies in its consideration for the stress level, the exposure and capacity characteristics of transportation assets, as well as in its practicality and scalability. Users can leverage EC-TRI to locate the weak and vulnerable components within the transportation network, and to provide a community-based assessment of the resilience level of the transportation infrastructure. In addition, we provide EC-TRI as a highly scalable GIS framework, providing users with the ability to adjust the quantification components as per local needs and priorities.

Pension Fund’s Risk Management Investment Portfolio in Tanzania

The study intends to assess the risk exposure of assets from the pension funds investment portfolio and suggest possible solutions of mitigating the risk of severe loss that is likely to occur over a given period of time. The study engaged secondary data of annual return series from five individual assets which are Government Securities (GSs), Fixed Deposits (FDs), Corporate Bonds (CBs), Equities and Real Estates (REs) with the total number of 18 observations. In order to achieve the objectives of the study, the author applied the Generalized Auto-Regressive Conditional Heteroskedasticity (GARCH) model and Cornish-Fisher expansion model for data analysis to calculate Value at Risk (VaR) for individual assets in Pension Funds investment portfolio from the financial year 1998/1999 to 2016/2017. The results from both techniques employed indicated that, Corporate Bonds (CBs) has the highest Value at Risk (VaR) followed by, Fixed Deposits (FDs), Equity, Real Estates and Government Securities (GSs). There were some renovations in the social security industry in Tanzania as among the approaches to combat risk that avails with minimal effects in the operationalization of Pension Funds, therefore the findings of the study are relevant to help pension funds in Tanzania to mitigate the risk of strict loss that is likely to occur in their investment portfolio due to market fluctuations over a given period of time.

Mapping shallow groundwater salinity in a coastal urban setting to assess exposure of municipal assets

Study regionChristchurch, New Zealand. Study focusLow-lying coastal cities worldwide are vulnerable to shallow groundwater salinization caused by saltwater intrusion and anthropogenic activities. Shallow groundwater salinization can have cascading negative impacts on municipal assets, but this is rarely considered compared to impacts of salinization on water supply. Here, shallow groundwater salinity was sampled at high spatial resolution (1.3 piezometer/km2), then mapped and spatially interpolated. This was possible due to a uniquely extensive set of shallow piezometers installed in response to the 2010–11 Canterbury Earthquake Sequence to assess liquefaction risk. The municipal assets located within the brackish groundwater areas were highlighted. New hydrological insights for the regionBrackish groundwater areas were centred on a spit of coastal sand dunes and inside the meander of a tidal river with poorly drained soils. The municipal assets located within these areas include: (i) wastewater and stormwater pipes constructed from steel-reinforced concrete, which, if damaged, are vulnerable to premature failure when exposed to chloride underwater, and (ii) 41 parks and reserves totalling 236 ha, within which salt-intolerant groundwater-dependent species are at risk. This research highlights the importance of determining areas of saline shallow groundwater in low-lying coastal urban settings and the co-located municipal assets to allow the prioritisation of sites for future monitoring and management.

Measuring the Climate Risk Exposure of Financial Assets : Methodological Challenges and Central Bank Practices

In order to understand climate-related risks and opportunities, the availability and transparency of reliable financial information is essential. In this regard, the financial sector plays a special role owing to its ties to other economic sectors, and the exposure of financial institutions highlights the responsibility of central banks. This paper uses the literature related to environmental sustainability reporting as well as practical experience to describe the challenges encountered in assessing the green risks of financial assets (absence and heterogeneity of data, differences in definitions and requirements, lack of a uniform methodology, limits of rating schemes) and also details the climate risk measurement methodologies and practical solutions employed by central banks publishing their own climate-related financial disclosures, i.e. the Bank of England, the Banque de France and the Magyar Nemzeti Bank.

A preliminary assessment of coastal vulnerability for Ngazidja Island, Comoros Archipelago, Western Indian Ocean

In previous studies, an emphasis on the particular vulnerability of small island states to future sea-level rise and the intensity of increasing storm surges have been discussed. This preliminary assessment develops a Coastal Vulnerability Index (CVI) along the 202 km-long coastline of Ngazidja Island (formerly Grande Comore, Comoros Archipelago), using fieldwork, remote sensing, and geographic information system tools (GIS). The CVI considers nine variables: geology (a), geomorphology (b), topography (c), shoreline change (d), shoreline exposure (e), relative sea-level rise (f), significant wave height (g), mean tide range (h), and land-use (i). The land-use variable was added in this analysis to highlight the human asset exposure in the surrounding areas. Each variable was ranked based on local physical and hydrodynamic conditions and their vulnerability contribution to sea-level rise. The CVI was computed in 270 sections. According to the vulnerability index, approximately 57.5% of the coastline is under low and moderate vulnerability. High and very high vulnerabilities refer specifically to beaches and shores with old volcanic lava flows located mainly in the northern, northeastern, and southeastern parts of the island, approximately 42.5% of the coastline. The lowest value of CVI is 9.2 on high, rocky cliffs and the highest value is 160 on beaches. This vulnerability partition along the coastline is consistent with in situ indicators of coastal erosion and flooding. In a sea-level rise context, it is of prime importance to integrate coastal vulnerability maps with planning and sustainable management of the coastal zone.

Process Approach and Construction of the Database for Non-Core Asset Management in Credit Organizations

A method for building end-to-end management accounting in a division of the Bank’s subdevision specializing in working with non-core assets is proposed. Has been proposed the process approach, an algorithm for building a database for the formation of key performance and control indicators. Has been described the key stages of the department's work, the attribute composition of entities (set) arriving, enriched and transmitted at each stage of the department's work. By modeling the process has been built a role model, access and editing rights for employees. Data sources (reference books) for optimization and unification of the process of filling the database (tuple) are proposed. A method of accessing the database in the Power Query Microsoft Excel add-in is proposed, which allows you to collect data from files of all basic data types, process and refine the received data. In the interactive programming environment Jupyter Notebook, mathematical and financial models for data analysis (logistic regression, decision tree and discounted cash flow method) were built based on data in order to predict costs, the timing of asset exposure and make a decision on the optimal cost of putting property on the Bank's balance sheet and selling price. Based on ready-made libraries (matpotlib, seaborn, plotly), options for data visualization for management are proposed. Using the example of the Bank's division, the author describes the positive effects and opportunities that open up to the management of different levels in solving day-to-day tasks and planning the activities of the division. A technical task was proposed for the development of a showcase for the sale of non-core assets on the Bank's website as an environment for the accumulation of external data for making flexible management decisions.