Risk Allocation Research Articles

Risk Allocation and Financial Intermediation

Risk Allocation and Financial Intermediation

РИСКИ В ГОСУДАРСТВЕННОЙ СИСТЕМЕ УПРАВЛЕНИЯ ЗАКУПКАМИ: ИДЕНТИФИКАЦИЯ И ОЦЕНКА

This article presents an original methodology for assessing the cumulative risk of procurement in the state contract system. A classification of procurement risks is proposed, including time risk, corruption risk, financial risk, organizational and legal risks and technical risks specific to each procurement entity (customer, contractor and consumer) at each stage of the procurement process (procurement planning, procurement implementation, monitoring, audit and control of procurement), including the allocation of procurement risks before the conclusion of the contract and during the execution of the contract. The risk assessment methodology includes a quantitative assessment of the private risks of all participants at different stages of procurement and the total risk of procurement using matrix and point approaches. The verification of the methodology showed the ability to determine the comparative overall risk in the field of procurement and bottlenecks both in the activities of a particular customer and contractor, and in the industry and the procurement system as a whole. The use of classification and risk assessment methodology in the field of public procurement makes it possible to develop a risk-based approach to management in the russian contract system, which is conceptually based on the concentration of limited state resources in areas of maximum risk and at the same time reducing the administrative burden in areas of reduced risk.

Use of the concession agreements for the attraction of investments into the urban improvement

The objective of this research is to develop some recommendations on the creation of comfortable public vacation spots (parks, etc.), which would be attractive to inhabitants and at the same time could attract investments of small business through cooperation of the authorities and entrepreneurs. The paper supports the idea about the possibility of the use of the concession mechanism for this purpose. Though such projects are still rare in the Russian Federation at the moment, the authors study few successful projects, implemented, proving their viability. The schemes of implementation of the projects of the urban improvement due to concessions, works sharing, responsibility sharing as well as the allocation of project risks between the participants are considered in this paper. The principles, which make the projects effective, are formulated. The results, received within this research, can be useful both for the authorities during drawing up the regional and municipal programmes of urban improvement and development, and for the private investors, interested in such investments.

Ethical and Political-Economic Dimensions and Potential Reforms of the Hybrid Leveraged, High Frequency, Artificial Intelligence Trading Model

The average annual profits before fees of the $10 billion plus Renaissance Technologies’ hybrid Medallion “Leveraged, High Frequency, Artificial Intelligence (LHFAI)” trading hedge fund between 1988 and 2019 were about 66 percent. Total trading profits during this period were over $100 billion. The fund has never had a losing year. The fund is not open to the general public. First, distinctions among, in more or less historical order, the traditional market-maker trading model, the hedge fund trading model, the artificial intelligence trading model, and the hybrid LHFAI trading model are discussed. Second, the micro components of the LHFAI trading model are explained in the context of Renaissance Technologies’ Medallion Fund. Third, key positive contributions of the model with respect to profitability, low annual volatility, market liquidity, and intellectual property development; negative ethical issues concerning exclusive access, tax fairness, financial transparency, shared responsibility for losses and systemic risk, and short vs. long-term capital allocation are discussed. Potential reforms that retain the positives, reduce the negatives, and that could positively transform the model are discussed. Fourth, potential impacts that the potential reforms might have on the macro LHFAI form of finance capitalism and the larger finance capitalism political-economic system are considered. Fifth, conclusions are offered and discussed.

Analysis of asset risk and household Financial Asset Allocation structure—Empirical analysis from a nonlinear model

Chinese households now have a good understanding of finance and their asset allocation choices are increasingly skewed towards financial products. At present, most domestic and foreign researches on the structure and choice of household asset allocation mainly analyze the influence of residents’ characteristics or financial literacy on household asset allocation, while few researches on the internal relationship between household risk, asset structure and allocation choice. Based on CHFS data and the theory of asset investment behavior, this paper systematically analyzes and risk assets and family financial asset allocation structure of mutual influence and role, an empirical analysis of the influencing factors of residents in our country family financial asset allocation structure by using Probit model and Tobit model, pay attention to risk assets, family income and other factors, a deeper understanding of family financial asset investment circumstances.

Interference-Based Consensus and Transaction Validation Mechanisms for Blockchain-Based Spectrum Management

The convergence of dynamic spectrum access (DSA) and blockchain has been regarded as the new paradigm of spectrum management. Because of the inherent properties of blockchain, such as decentralization and tamper-resistance, the deployment of blockchain in future networks has advantages to address problems exposed in traditional centralized spectrum management systems, such as high security risk and low allocation efficiency. In this article, we first compare blockchain-based spectrum management with the traditional centralized approach and then present a reference architecture for blockchain-based spectrum management. In particular, we propose an interference-based consensus mechanism, which can be employed to improve transaction efficiency and reduce system overhead while promoting spectrum sharing. The proposed consensus mechanism is based on the comparison of aggregated interference experienced by each node, such that the node that suffers the most aggregated interference will obtain the accounting right as a compensation. Furthermore, to avoid harmful interference caused by spectrum traders, an interference-based transaction validation mechanism is designed to validate the spectrum transactions stored in the blocks. Different from existing transaction validation mechanisms in which every transaction needs to be validated by all nodes, a “transaction validation area” is determined for each spectrum transaction, and only the nodes located in the validation area need to validate the transaction. The simulation results show that the system fairness and nodes’ signal-to-interference-and-noise power ratio (SINR) can be improved by adopting the proposed mechanisms while reducing the system overhead.

Risk Aggregation and Capital Allocation Using a New Generalized Archimedean Copula

In this paper, we address risk aggregation and capital allocation problems in the presence of dependence between risks. The dependence structure is defined by a mixed Bernstein copula which represents a generalization of the well-known Archimedean copulas. Using this new copula, the probability density function and the cumulative distribution function of the aggregate risk are obtained. Then, closed-form expressions for basic risk measures, such as tail value-at risk (TVaR) and TVaR-based allocations, are derived.

Tools and options for hydrogen and CCS cluster development and acceleration – UK case study, ELEGANCY project

Development of hydrogen and Carbon Capture and Storage (CCS) in the United Kingdom is investigated for the UK by research in the ELEGANCY Project to accelerate carbon dioxide (CO2) emissions reduction. Industry plans and concepts including large-scale production of hydrogen with CCS (H2-CCS) are used to estimate the potential magnitude and rate of CO2 supply for the Grangemouth and Teesside industrial sites. Annual emissions reductions from these two sites by CCS operations could exceed 30 million tonnes (Mt) by 2035 and 50 Mt by 2045. Implementation of carbon-negative technologies would increase these estimated reductions. The application of the H2-CCS chain tool to Great Britain has identified the resource and technology needs for scaling up the H2 economy. It has also highlighted challenges to overcome such as the increased costs, magnitude of H2 and CO2 storage requirements, reduction in upstream emissions, etc. Importantly, there is an urgent need for policy makers, regulators, suppliers, and consumers to coordinate their efforts to achieve timely progress towards net-zero in a socially responsible manner. An application of the business model and business case assessment methodology and tools to the delivery of large-scale H2-CCS infrastructure for decarbonising residential heating in the north of England is presented. A resulting high-level system business model which allows the removal of the investment barriers and addresses major business risks to investment is defined through realistic risk allocation and collaboration between the public and private sectors. A conceptual business case is articulated with a strategic rationale consistent with support for UK energy system decarbonisation and the UK government’s legal 2050 net-zero emissions target. Recommendations for achieving the first phase of infrastructure development ensuring low regrets outcomes and flexible real options are described.

Developing a new mobile network ownership model using a risk allocation framework

Developing a new mobile network ownership model using a risk allocation framework

Development characteristics of public-private partnership projects using fuzzy approach in China during 2016–2018

Public-Private Partnership (PPP) has been adopted extensively in public infrastructures in China. Numerous studies have explored development patterns for future PPP projects success based on either literature review or case studies. This paper aims to probe into the spatiotemporal dynamics of China’s PPP and clarify regional differentiation by frequency analysis, coefficient of variation and cluster analysis. The result shows that the implementation rate has a slight increase along with time series although PPP projects gradually return to rational development. The fuzzy set is utilized to handle with ambiguity in some linguistic risk allocation criteria to lower the fuzziness and bias in knowledge expert which is qualitative that handles real time decision making. The municipal sector has been occupied the largest share of PPP projects while state-owned enterprises still dominate the biggest PPP marketed components. Local governments prefer viability gap subsidies although central government encourages user payment. Spatial difference coefficient is so high reflecting obvious regional differentiation of provincial PPP development. Recommendations are ultimately put forward to enhance China’s future PPP promotion, which will provide a valuable direction for government to make PPP customized policies.

ОЦІНКА ЕФЕКТИВНОСТІ АУТСОРСИНГУ УПРАВЛІНСЬКИХ ФУНКЦІЙ

The view of the outsourcing process differs significantly includes not only the classical view of outsourcing as the transfer of traditional non-key functions of the organization to external contractors, but also long-term transfer of management functions and, if necessary, available resources to external contractors. A successful model of effective business, that allows to gain competitive advantage, may include outsourcing management functions. According to some economists, the motives for outsourcing certain functions are the cost and quality of the product, and the possible loss of control over the business is not a first-rate factor. Systemic cost optimization addresses the problem of costs that can be avoided. It should be noted that the indicator on which the consumer of outsourcing services should focus is the economic effect. The process of transferring accounting functions to another company is not suitable for the classical definition of outsourcing. In practice, the most common types of outsourcing of management functions are accounting and tax accounting, legal support, maintenance of information systems. There are different ways to can quantify the efficiency of accounting outsourcing, including a cost approach. The most important advantage of accounting outsourcing in the strategic aspect is the ability to share risk. Financial or tax reporting outsourcing is primarily a matter of risk allocation, so the assessment of the efficiency of this type of outsourcing should be developed from this standpoint. A successful model of effective business can use outsorcing. It is important that especially during the busines development in the market, the company can not perform well on certain production processes and some management functions or sometimes lacks the means to ensure this process or function. When transferring non-key functions to external organizations, it is difficult to identify key processes that are strategically important for the company. Separating the accounting process into components and outsourcing only individual processes reduces the level of risk.

A numerical approach to the risk capital allocation problem

Capital risk allocation is an important problem in corporate, financial and insurance risk management. There are two theoretical aspects to this problem. The first aspect consists of choosing a risk measure, and the second consists of choosing a capital allocation rule subordinated to the risk measure. When these two complementary aspects are settled, the problem is reduced to a computational problem. No universal prescription for choosing a risk measure exists, let alone a subordinated capital allocation rule. However, expert opinion may be expressed as a range of capital to be allocated to each risk. For example, the managers of each line of activity of a corporation or bank may have a way to estimate a minimum and maximum losses with high confidence. In that case, one is confronted with two interesting numerical problems. First, to devise a method to allocate risk capital within the bounds provided by the expert. Second, to use the upper bounds as stand-alone risk prices to determine a risk measure, which can then be used to compute the prices of other risks. The risk measure could also be used to compute a range for the capital allocations of a new collection of risks, to which our numerical procedure to allocate risk capital can be applied. The aim of this paper is to use a model-free, nonparametric approach based on the method of maximum entropy in the mean to solve both problems and to examine how they are intertwined. In this way we circumvent the problem of choosing between risk valuation and risk pricing methods, and between risk capital allocation rules consistent with them. Also, the maximum-entropy-based methodology provides us with a method to determine coherent risk measures consistent with the bounds provided by expert opinion or management. The risk measure provides us with a method to determine either risk prices or bounds to be used for capital allocation for a different collection of risks.

Measuring Financial Advice: Aligning Client Elicited and Revealed Risk

Financial advisors use questionnaires and discussions with clients to determine a suitable portfolio of assets that will allow clients to reach their investment objectives. Financial institutions assign risk ratings to each security they offer, and those ratings are used to guide clients and advisors to choose an investment portfolio risk that suits their stated risk tolerance. This paper compares client Know Your Client (KYC) profile risk allocations to their investment portfolio risk selections using a value-at-risk discrepancy methodology. Value-at-risk is used to measure elicited and revealed risk to show whether clients are over-risked or under-risked, changes in KYC risk lead to changes in portfolio configuration, and cash flow affects a client's portfolio risk. We demonstrate the effectiveness of value-at-risk at measuring clients' elicited and revealed risk on a dataset provided by a private Canadian financial dealership of over 50,000 accounts for over 27,000 clients and 300 advisors. By measuring both elicited and revealed risk using the same measure, we can determine how well a client's portfolio aligns with their stated goals. We believe that using value-at-risk to measure client risk provides valuable insight to advisors to ensure that their practice is KYC compliant, to better tailor their client portfolios to stated goals, communicate advice to clients to either align their portfolios to stated goals or refresh their goals, and to monitor changes to the clients' risk positions across their practice.

Evidence on Optimal Risk Allocation Models for Indonesian Geothermal Projects Under PPP Contracts

Evidence on Optimal Risk Allocation Models for Indonesian Geothermal Projects Under PPP Contracts

The Drivers of Stock Market Growth in Pakistan: How Relevant is Irrelevant?

Pakistan’s stock market has experienced severe downside volatility after its classification in MSCI’s emerging market index in 2016. Global pandemic, political instability and capital limitations through money laundering control mechanisms have exposed the foundations of capital allocation to an escalating risk of default. The situation prerequisites a review of contentious relationship between drivers of economic growth and stock market expansion.
 This paper seeks to examine the relationship between non-financial and banal drivers of economic growth and their relative impact on stock market development in Pakistan, building on the fact that financial market development is a direct outcome of economic growth and development of the generic capabilities of production and capital formation through profit trails.
 GMM approach is used to analyze the contribution of capital formation and allocation through generic productivity and risk allocation mechanism. The paper discusses GDP growth, Gross fixed capital formation, Private credit and use of IMF credit as instrumental in determining stock market expansion. Originality of the research transpires from the fact that key outputs of real sector have been added to analyze the development of financial market which have long been ignored as extraneous for empirical analysis.

The Determinants of Risk-Sharing Strategies of Food-Retailers: A Study on Chittagong, Bangladesh

Food-retailers have access to various risk management strategies to manage the risks in food processing and trading. Risk-sharing is a powerful instrument amongst risk management strategies. It comprises a negotiation of risk allocation between at least two agents to reduce risk and to increase expected utility. The objective of the study is to identify the factors that affect the selection of risk-sharing strategies of food-retailers. In this regard, the study explains risk-sharing instruments from three perspectives: risk reduction; risk mitigation; and risk coping strategies. Food-retailers choose these risk-sharing strategies according to their preference. We link a theoretical understanding of the existing risk-sharing strategies with an empirical model. For quantitative analysis, primary data encompassing 24 variables is sampled from 109 randomly selected food-retailers from and around the city of Chittagong, Bangladesh. This study uses a multiple regression model to identify the significant factors in selecting risk-sharing strategies. The results infer that Family Employment, Hired Employment, Value Chain Challenges, Institutional Challenges, Societal Challenges, Risk Attitudes on Marketing and Promotion, Risk Attitudes on Innovation, Risk Attitudes on Business-in-General, Gender and Expectation for Succession, have a significant effect on the selection of risk-sharing strategies. The analysis is performed on SPSS (version-26). This study covers only off-business risk-sharing instruments of food-retailing. Consequently, this result is irrespective of on-business risk management strategies.

Do pastoralist cattle fear African lions?

Fear of predators fundamentally shapes the ecology of prey species and drives both inter‐ and intra‐specific interactions. Extensive research has examined the consequences of predation risk from large carnivores on the behavior of wild ungulate prey species. However, many large carnivores not only hunt wild prey but also depredate domestic livestock, especially in pastoralist systems where livestock share land and resources with large carnivores. Northern Tanzania is a hotspot for human–carnivore conflict driven by livestock depredation and interactions are particularly severe between African lions Panthera leo and pastoralist cattle Bos taurus. In this ecosystem, we explored the degree to which pastoralist cattle exhibited anti‐predator behaviors during their daily grazing routines. Using focal animal sampling, we compared two typical anti‐predator behaviors, vigilance and grouping, among cattle in village rangelands with high and low background depredation rates. We found that cattle in high risk village rangelands formed 21.2% larger groups than cattle in low risk village rangelands. Interestingly, cattle in low risk village rangelands spent 68.4% more time vigilant than cattle in high risk village rangelands. These patterns were influenced significantly by the time of day: as sunset approached, cattle in low risk village rangelands spent more time vigilant and cattle in high risk village rangelands formed larger groups. These results suggest that pastoralist cattle exhibit anti‐predator strategies that vary both spatially and temporally, and that such strategies might help livestock optimally tradeoff the costs and benefits of anti‐predator behavior across timescales (i.e. the risk allocation hypothesis). We discuss the implications of our results for husbandry techniques that might reduce behavioral costs associated with cattle anti‐predator behaviors and help increase tolerance for lions and other large carnivores. These improvements are critical to human–carnivore coexistence given the prevalence of pastoralism globally and the rising potential for conflict with large carnivores such as lions.

ОРГАНІЗАЦІЯ ЗАХИСТУ ОБЛІКОВОЇ ІНФОРМАЦІЇ В УМОВАХ ЗАБЕЗПЕЧЕННЯ КІБЕРБЕЗПЕКИ

The purpose of the article is to summarize the existing approaches and outline promising areas for the organization of protection of accounting information in terms of cybersecurity. In the course of the research methods of observation, comparison, analysis, synthesis, generalization were used. The article proves the importance of accounting information for the economic life of the business entity. The importance of the Internet and IT technologies application to reflect certain facts of economic life in the accounting system (cash flow management, sales process, calculations, delivery, online trade, reporting)is substantiated. As shown in the example of the impact of cyberattacks on the accounting system and related costs are described on the example of the Program-Fraudster Violation of confidentiality Hacking Malicious software. The risks faced by electronic accounting information systems based on the allocation of risks for each component of the accounting process (risks associated with the collection and input of data into an automated system; risks associated with information processing and storage on electronic media; risks associated with stage of generalization and transfer of information). It is proved that the protection of accounting information and avoidance of the «hook» of a cyber attack is possible only in the case of compliance with comprehensive measures and joint actions of management, accounting staff, auditors and educational institutions in the training of future professionals. It is concluded that effective communication and strategies between management, accountants and auditors are important to reduce or protect against emerging threats to the accounting information system.

China’s new fund custodian rules

Purpose To explain the key amendments to China’s rules governing fund custody business and highlight the implications for private fund managers. Design/methodology/approach The article analyses, from the perspective of private fund managers, the key amendments to the rules governing fund the custody business in China in terms of custody of fund assets, the fund settlement and clearing process, valuation, disclosure and reports, investment supervision, review of distributions and governance. Findings The revised rules governing the fund custody business allow private fund managers to use their global custodian in China locally and leave room for managers and custodians to agree on their responsibilities and risk allocation in the fund contract. Originality/value The article offers practical guidance on how private fund managers may contractually allocate responsibilities and risks between themselves and fund custodians in the fund contract.

County-level phenomapping to identify disparities in cardiovascular outcomes: An unsupervised clustering analysis: Short title: Unsupervised clustering of counties and risk of cardiovascular mortality

IntroductionSignificant heterogeneity in cardiovascular disease (CVD) risk and healthcare resource allocation has been demonstrated in the United States, but optimal methods to capture heterogeneity in county-level characteristics that contribute to CVD mortality differences are unclear. We evaluated the feasibility of unsupervised machine learning (ML)-based phenomapping in identifying subgroups of county-level social and demographic risk factors with differential CVD outcomes. MethodsWe performed a cross-sectional study using county-level data from 2008 to 2018 from the Centers for Disease Control (CDC) WONDER platform and the 2020 Robert Wood Johnson County Health Rankings program. Unsupervised clustering was performed on 46 facets of population characteristics spanning the demographic, health behaviors, socioeconomic, and healthcare access domains. Spatial autocorrelation was assessed using the Moran’s I test, and temporal trends in age-adjusted CVD outcomes were evaluated using linear mixed effect models and least square means. ResultsAmong 2676 counties, 4 county-level phenogroups were identified (Moran’s I p-value <0.001). Phenogroup 1 (N ​= ​924; 24.5%) counties were largely white, suburban households with high income and access to healthcare. Phenogroup 2 counties (N ​= ​451; 16.9%) included predominantly Hispanic residents and below-average prevalence of CVD risk factors. Phenogroup 3 (N ​= ​951; 35.5%) counties included rural, white residents with the lowest levels of access to healthcare. Phenogroup 4 (350; 13.1%) comprised counties with predominantly Black residents, substantial cardiovascular comorbidities, and physical and socioeconomic burdens. Least square means in age-adjusted cardiovascular mortality over time increased in a stepwise fashion from 223 in phenogroup 1 to 317 per 100,000 residents in phenogroup 4. ConclusionsUnsupervised ML-based clustering on county-level population characteristics can identify unique phenogroups with differential risk of CVD mortality. Phenogroup identification may aid in developing a uniform set of preventive initiatives for clustered counties to address regional differences in CVD mortality.