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Green innovation is essential to sustainable development and carbon neutrality. How to adopt digital technology to promote corporate green innovation (CGI) has become a widespread topic among scholars. This paper examines how digital transformation influences CGI in Chinese non-financial listed companies from 2008 to 2020. Using textual analysis to construct indicators of digital transformation, we find that CGI can be significantly enhanced by enterprise digital transformation in both quantity and quality. We also explore the underlying channels and find that enterprise digital transformation promotes CGI by improving environmental management, human capital upgrading, and resource allocation efficiency. Moreover, we investigate the moderating effects of various factors and conclude that enterprise digital transformation's favorable effects on CGI are more pronounced in companies with good environmental responsibility, labor-intensive industries, high financial risks, intense market competition, and state-owned enterprises, as well as in companies located in regions with strong environmental regulations and a low level of digital economy development. This paper contributes to the literature on green innovation and digital transformation, as well as provides empirical evidence for enterprises in emerging market countries to promote energy saving and green transformation using digital technology. [ABSTRACT FROM AUTHOR]

China is in the stage of rapid development of new urbanization, cities are more vulnerable when facing various risks, and the construction of urban resilience (UR) makes cities more secure. At the same time, the allocation of digital factors has a vital impact on the construction of UR under energy constraints. Based on the panel data of cities in China from 2011 to 2020, this paper studies the influence and mechanism of digital factor allocation (DFA) on UR under energy constraints through panel fixed effect model (FE), mediation effect model, and panel threshold model. The main empirical results include: (1) The misallocation of digital factors has a negative impact on UR. In the case of differences in the division of urban agglomeration, the impact of digital factor misallocation (DFM) on UR will also be different. (2) The misallocation of digital factors has an impact on UR through the intermediary effects of capital allocation efficiency, green innovation and industrial structure upgrading. (3) There is a nonlinear relationship between the DFM and UR. [ABSTRACT FROM AUTHOR]

This paper proposes a theory about the allocation of human capital along the development process that helps to understand the controversial impact of this variable in growth regressions. We build a model in which human capital is allocated to three activities: production, tax collection (bureaucracy), and public education. At the first stage of development, countries have low effective tax rates because tax collection requires human capital, which is scarce. As countries accumulate human capital throughout the transition, the effective tax rate rises, diverting human capital from production to bureaucracy and public education. Consequently, at this stage, human capital has a weak impact on production, even when the human capital allocation is efficient. Furthermore, disparities in institutional quality may diminish the correlation between human capital and GDP. [ABSTRACT FROM AUTHOR]

Instantaneous data processing has the potential to enhance scalability, lessen power usage, and permit and improve data presentation in Consumer Internet of Things (CIoT) devices. In simple terms, cloud-based solutions cannot handle many IoT applications. According to Industrialized IoT (IIoT) technologies, an automated resource allocation system can improve service delivery and minimize healthcare costs. To maximize resource usage and response time for end users, there needs to be an effective method to efficiently distribute workload between Fog Layer and Cloud Connection and enhance cloud network capital allocation. Data analytics of complex and vital healthcare data requires timely responses, making it complicated. This paper proposes a design based on the Lanner Swarm Optimization (LSO) algorithm, which was developed to overcome inefficient heuristic strategies where data is transported to the cloud layer based on traffic type. The LSO algorithm is used to improve resource allocation and workload distribution in cloud-assisted CIoT applications for smart healthcare systems, improving scalability, power consumption, and data processing. The objective function determines if diverse virtual machines (VMs) vary accomplishment time the most, considering this study's updating and pruning restrictions. The experimentation analysis demonstrated that the proposed load balancing and work scheduling method outperforms evolutionary and heuristics algorithms. In experimentation, the research model attains a makespan of 10 s, response time of 5.5 s, resource utilization with a rate of 0.9, execution time of 13 s, latency of 10 ms, throughput of 0.78 s, and delivery rate of 0.74%. At resource scheduling, the LSO model had the best payload routing, latency, packet delivery ratio, and network lifetime. [ABSTRACT FROM AUTHOR]

We investigate capital allocation based on the higher moment risk measure at a confidence level q ∈ (0 , 1) . To reflect the excessive prudence of today's regulatory frameworks in banking and insurance, we consider the extreme case with q ↑ 1 and study the asymptotic behavior of capital allocation for heavy-tailed and asymptotically independent/dependent risks. Some explicit asymptotic formulas are derived, demonstrating that the capital allocated to a specific line is asymptotically proportional to the Value at Risk of the corresponding individual risk. In addition, some numerical studies are conducted to examine their accuracy. [ABSTRACT FROM AUTHOR]

The dominance of modern rationality in knowledge production implies that the distribution of intellectual capital highly depends on the capacity to gather representative data and generate generalizable theses. Furthermore, as research becomes more formalized and dominated by large funding schemes, intellectual capital allocation is increasingly associated with high economic, labor force and institutional power. This phenomenon has consequences at the global level. As the United Nations Educational, Scientific and Cultural Organization (UNESCO) has documented, there are significant disparities between countries in research capacities, with a marked difference between "core" countries with semi-monopolies over sanctioned knowledge production and "peripheral" states primarily used as data mines. The core–periphery divide in research capacity brings about what decolonial theorists call knowledge abysses: the widespread idea that core countries are the ultimate knowledge producers and thus the legitimate guides in humanity's road to "progress." In that context, the democratization of knowledge and the prevention of neo-colonial dynamics require the development of cheaper and more accessible ways of collecting representative data. In this article, we make a call for innovations in methods that can serve to overcome this, and we illustrate possible avenues for achieving sound research without incurring high financial costs by describing and discussing our experiences in researching narco-violence in Colombia and prostitution in Russia with what we call the "taxi method." [ABSTRACT FROM AUTHOR]

We empirically examine the interaction between different types of diversification (stage, industry, geography) and portfolio size, i.e., number of investee companies, in explaining venture capital (VC) funds' returns. We study a comprehensive dataset of 422 liquidated US VC funds to conduct multiple analyses in a large timeframe. The results show that large portfolio size and diversification in a limited number of industries contribute positively to fund performance, while stage and geographical diversification have no significant relationship with returns. Our findings can support both the practice of VC portfolio management in reaching better capital allocation efficiency and policymakers in providing guidance for VC fund development programmes backed by sovereign and international institutions. [ABSTRACT FROM AUTHOR]

In this paper, we study capital allocation for dynamic risk measures, with an axiomatic approach but also by exploiting the relation between risk measures and BSDEs. Although there is a wide literature on capital allocation rules in a static setting and on dynamic risk measures, only a few recent papers on capital allocation work in a dynamic setting and, moreover, those papers mainly focus on the gradient approach. To fill this gap, we then discuss new perspectives to the capital allocation problem going beyond those already existing in the literature. In particular, we introduce and investigate a general axiomatic approach to dynamic capital allocations as well as an approach suitable for risk measures induced by g-expectations under weaker assumptions than Gateaux differentiability. [ABSTRACT FROM AUTHOR]

A Systemic Optimal Risk Transfer Equilibrium (SORTE) was introduced in: "Systemic optimal risk transfer equilibrium", Mathematics and Financial Economics (2021), for the analysis of the equilibrium among financial institutions or in insurance-reinsurance markets. A SORTE conjugates the classical Bühlmann's notion of a risk exchange equilibrium with a capital allocation principle based on systemic expected utility optimization. In this paper we extend such a notion to the case when the value function to be optimized is multivariate in a general sense, and it is not simply given by the sum of univariate utility functions. This takes into account the fact that preferences of single agents might depend on the actions of other participants in the game. Technically, the extension of SORTE to the new setup requires developing a theory for multivariate utility functions and selecting at the same time a suitable framework for the duality theory. Conceptually, this more general framework allows us to introduce and study a Nash Equilibrium property of the optimizer. We prove existence, uniqueness, and the Nash Equilibrium property of the newly defined Multivariate Systemic Optimal Risk Transfer Equilibrium. [ABSTRACT FROM AUTHOR]

This article presents a model that combines financial analysis with macroeconomics to study society's asset allocation problem. The model considers the effects of technological changes and policy decisions on equilibrium, as well as the impact of financialization on optimal asset allocation. The model posits a capital allocation plane where agents allocate wealth between consumption and investment to maximize social utility. The article also discusses the project availability incline, which represents different combinations of projects based on their capital requirement, expected risk, and expected return. Exogenous changes, such as technological progress and government regulation, can affect capital allocation. The article suggests that further investigation is needed to understand the impact of financialization on the allocation of capital. [Extracted from the article]

This paper assesses the growth-enhancing and growth-retarding effects of different budgetary fiscal variables using a balanced panel of 32 middle-income countries for the time period of 2000–2017. Much of previous research requires to be re-evaluated as it ignores the biases associated with either incomplete or wrong specification, or both, of the budget constraint and the money supply. This paper addresses these gaps and obtains more unbiased, consistent and efficient estimates for the fiscal variables, using both static and dynamic panel econometric techniques. Specifically, this paper finds that (1) larger tax and non-tax revenues retard economic growth; (2) higher allocation to public capital expenditure appears to have positive and significant effect on growth; (3) fiscal deficit appears to have neutral-growth effects; and (4) controlling broad money supply corrects for biases in the orthogonal specification. [ABSTRACT FROM AUTHOR]

Value at risk (VaR) and expected shortfall (ES) have emerged as standard measures for detecting the market risk of financial assets and play essential roles in investment decisions, external regulations, and risk capital allocation. However, existing VaR estimation approaches fail to accurately reflect downside risks, and the ES estimation technique is quite limited owing to its challenging implementation. This causes financial institutions to overestimate or underestimate investment risk and finally leads to the inefficient allocation of financial resources. The main purpose of this study is to use machine learning to improve the accuracy of VaR estimation and provide an effective tool for ES estimation. Specifically, this study proposes a VaR estimator by combining quantile regression with "Mogrifier" recurrent neural networks to capture the "long memory" and "clustering" properties of financial assets; while for estimating ES, this study directly models the quantile of assets and employs generative adversarial networks to generate future tail risk scenarios. In addition to the typical properties of financial assets, the model design is also consistent with heterogeneous market theory. An empirical application to four major global stock indices shows that our model is superior to other existing models. [ABSTRACT FROM AUTHOR]

Risk aggregation and capital allocation are of paramount importance in business, as they play critical roles in pricing, risk management, project financing, performance management, regulatory supervision, etc. The state-of-the-art practice often includes two steps: (i) determine standalone capital requirements for individual business lines and aggregate them at a corporate level; and (ii) allocate the total capital back to individual lines of business or at more granular levels. There are three pitfalls with such a practice, namely, lack of consistency, negligence of cost of capital, and disentanglement of allocated capitals from standalone capitals. In this paper, we introduce a holistic approach that aims to strike a balance of optimality by taking into account competing interests of various stakeholders and conflicting priorities in a corporate hierarchy. While unconventional in its objective, the new approach results in an allocation of diversification benefit, which conforms to the diversification strategy of many risk management frameworks including regulatory capital and economic capital. The holistic capital setting and allocation principle provides a remedy to aforementioned problems with the existing two-step industry practice. [ABSTRACT FROM AUTHOR]

Whether heterogeneous environmental regulations in China can improve industrial green total factor energy efficiency (IGTFEE) is essential to sustainable industrial development nationwide. However, under China's fiscal decentralization system, the impact of heterogeneous environmental regulations on the IGTFEE and its underlying mechanism needs further exploration. This study incorporates capital misallocation and local government competition into the research framework and systematically investigates the mechanisms and effects of environmental regulations affecting the IGTFEE under China's fiscal decentralization system. Based on provincial panel data from 2007 to 2020, this study measured the IGTFEE using the Super-SBM model with undesirable outputs. Based on efficiency, this study uses a bidirectional fixed-effects model, an intermediary effect model, and a spatial Durbin model for empirical testing. The results show that the effect of command-and-control environmental regulation on the IGTFEE presents an inverted U shape, while the effect of market-incentive environmental regulation on the IGTFEE presents a U shape. Conversely, the effect of command-and-control environmental regulation on capital misallocation presents a U shape, while the effect of market-incentive environmental regulation on capital misallocation presents an inverted U shape. Capital misallocation is the mediating variable of heterogeneous environmental regulations affecting IGTFEE, but heterogeneous environmental regulations do not affect the IGTFEE through the same mechanisms. The spatial spillover effects of command-and-control and market-incentive environmental regulations on IGTFEE present a U shape. Local governments adopt a differentiation strategy for command-and-control environmental regulation and a simulation strategy for market-incentive environmental regulation. Environmental regulations have spillover effects on the IGTFEE under different competitive strategies, but only the imitation strategy, characterized by the race-to-the-top, can promote local and neighboring IGTFEE. Therefore, we propose the following recommendations: the central government should flexibly adjust the intensity of environmental regulations to maximize the capital allocation effect, set diversified performance assessment indicators to motivate local governments into the healthy competition and reform the modern fiscal system to correct distortions in the behavior of local governments. [ABSTRACT FROM AUTHOR]

Investing on behalf of a firm, a trader can feign personal skill by committing fraud that with high probability remains undetected and generates small gains, but with low probability bankrupts the firm, offsetting ostensible gains. Honesty requires enough skin in the game: if two traders with isoelastic preferences operate in continuous time and one of them is honest, the other is honest as long as the respective fraction of capital is above an endogenous fraud threshold that depends on the trader's preferences and skill. If both traders can cheat, they reach a Nash equilibrium in which the fraud threshold of each of them is lower than if the other one were honest. More skill, higher risk aversion, longer horizons and higher volatility all lead to honesty on a wider range of capital allocations between the traders. [ABSTRACT FROM AUTHOR]

Chinese government-led disaster relief mode has been timely, comprehensive, and highly efficient. China usually adopts a government-led disaster relief model to burden a share of catastrophe losses. However, adopting such a model has also exposed some important problems, such as excessive pressure on the government relief fund and an emerging imbalance in the catastrophe insurance market. The government disaster relief fund is subdivided into four categories: pre-disaster subsidy provided to insurance companies, pre-disaster subsidy to residents, post-disaster relief subsidy to insurance companies, and post-disaster relief to residents. By constructing a three-party evolutionary game model involving the government, potential catastrophe insurance participants, and insurance companies, the equilibrium of the catastrophe insurance market and the influencing factors that promote the stability of the evolutionary game was explored under the cooperation mechanism of bounded rationality in this paper. The allocation of the government disaster relief fund to insurance companies of potential catastrophe insurance participants for both before and after a disaster was discussed. Furthermore, possible shortcomings of catastrophe insurance disaster relief mode in China were analyzed. Lastly, a solution to the problem of how to relieve pressure on the government relief fund and how to enhance the ability of catastrophe risk protection was put forward. It is of great significance for China to establish a catastrophe insurance market based on commercial insurance products. [ABSTRACT FROM AUTHOR]

Balancing water environmental protection and economic growth is a priority for the local governments. Many literature analyses found that the reform of the River Chief System (RCS) had a significant effect on water quality improvement in China; however, it is important and necessary to comprehensively assess the impact of the RCS on the total factor productivity (TFP) of industrial enterprises, which provides a realistic basis for the decisions of local governments. This paper uses the quasi-natural experiment of the RCS in China and data from Chinese industrial enterprises to analyze the impact of the policy reform on the total factor productivity (TFP) of enterprises and the influence mechanism. The empirical analysis finds that the TFP of industrial enterprises in the reformed areas of the RCS is significantly lower than that in the non-reformed areas. This indicates that the implementation of the RCS is not conducive to the improvement of TFP of industrial enterprises. And this effect is mainly generated by reducing the output level and capital allocation efficiency of industrial enterprises. Meanwhile, the impact of the RCS on the TFP of industrial enterprises exists heterogeneity. [ABSTRACT FROM AUTHOR]

This paper investigates whether emerging digital finance can reduce environmental pollution in China based on data from 273 of China's prefecture-level cities spanning the period from 2010 to 2017. The dynamic spatial econometric models (DSDM) find a significant negative association between digital finance and pollutants emissions, and the impacts vary among regions and urban development stages. The impact mechanism test proves that digital finance reduces pollutants emissions through technological innovation, structural adjustment, and capital allocation effects. In addition, we explore the different dimensions of digital finance and find that the depth of use has a more practical effect on reducing emissions. Further analyses based on the threshold model show an inverted N-shaped nexus between digital finance and emissions. The threshold effect also exists in terms of the traditional financial level. Our study proves that emerging digital finance crucially affects its potential benefits to environment and provides an empirical basis for policy-makers to accelerate the digitalization of financial markets, particularly paying attention to its emission-reduction effects. [ABSTRACT FROM AUTHOR]

How to maintain the momentum of sustained economic growth has always been an important issue of concern to all countries in the world. Using a three-level progressive analysis framework, the article provides an in-depth analysis of the evolution of supply-side economic growth drivers in China from 2003 to 2021 and the magnitude of their roles. The results show that in terms of the composition of growth drivers, total factor productivity makes the largest contribution to economic growth, while the contributions of capital scale and labor scale rank second and third, respectively; in terms of the industrial dimension, the changes in the contributions of each factor to GDP growth mainly originate from the influence of secondary and tertiary industries. From the decomposition of total factor productivity growth, industrial capital productivity and capital allocation structure both play a positive pulling effect on overall capital productivity, but have a weak downward trend. Industrial labor productivity and labor allocation structure both play a slight negative pulling effect on overall labor productivity; from the deep decomposition of growth momentum, industrial factor productivity and industrial factor allocation structure play a major positive pushing effect and a weak negative pushing effect on economic growth, respectively. The conclusion of this paper provides a valuable reference for developing countries on how to maintain the momentum of economic growth. [ABSTRACT FROM AUTHOR]

Investment intensity is the level of investment in fixed assets that affects a company's long-term growth prospects. In order to make good investment decisions, investors pay more attention to achieving a high level of investment intensity. This study examines the impact of two non-GAAP measures of profitability—earnings before interest, tax, depreciation, and amortization and earnings before interest and tax—on investment intensity in Gulf Cooperation Council (GCC) member countries. The study also examines the preference for two non-GAAP measures of profitability from the perspective of foreign investors. The study conducts panel data regressions using 205 firm observations covering the period 2010–2019 to examine the relationship between earnings before interest, tax, depreciation and amortization, earnings before interest and tax, and investment intensity. The study used various statistical estimators to overcome the heterogeneity and endogeneity problems of panel data and employed many diagnostic tests to increase robustness. The study finds that earnings before interest, tax, depreciation and amortization are positively and significantly associated with investment intensity in all GCC countries, but earnings before interest and tax are negatively associated with investment intensity in these countries. The results indicate that foreign investors prefer to use earnings before interest, tax, depreciation, and amortization to make decisions about investment intensity. The main implication of the study is that capital market regulators and foreign investors should use earnings before interest, tax, depreciation, and amortization information as a guideline to improve investment intensity decisions and achieve a better allocation of resources in capital markets. [ABSTRACT FROM AUTHOR]

As a core driver for the high-tech enterprises, green technology innovation is crucial, even with high financial risk. Against this background, this paper empirically examines the impact of risk-taking on green technology innovation of high-tech enterprises, taking Chinese A-share listed companies from 2007 to 2020 as the research sample and considering the moderating effect of financial mismatch. Findings show the following: First, the effect of risk-taking on green technology innovation of high-tech enterprises is insignificant in most cases, and the inhibitory effect of financial mismatch is partly supported. Second, financial mismatch only counter-regulates the inhibitory effect of systematic risk-taking on the number of invention patents granted in the eastern sample. Third, the effect of risk-taking on green technology innovation is significantly heterogeneous in terms of property rights and regional heterogeneity, regardless of considering the moderating effect of financial mismatch or not. Finally, the policy implementations point out that the government should create a favorable investment environment, financial institutions should adjust the way of capital allocation, while high-tech enterprises should broaden the financing channels to enhance their risk-taking ability, and promote green technological innovation to achieve high-quality economic development. [ABSTRACT FROM AUTHOR]

Distorted allocation of capital factors will lead to the loss of capital market-based soil as the background support for green technology innovation, which will not be able to climb up the value chain and eventually become an economic "colony." This study empirically investigates the relationship between distorted capital factor allocation and green technology innovation using data from 2005 to 2018 for prefecture-level cities in China. The empirical results show that the distortion of capital factor allocation not only has a significant inhibiting effect on green technology innovation in the city, but also hinders the development of green technology innovation in neighboring cities. Mechanism test analysis suggests that there is negative impact via generating mismatch, crowding out, and rent-seeking effects. Further research shows that the effect of distorted capital factor allocation on urban green technology innovation is more influential in the eastern and western regions. The conclusions of this study have important practical significance for optimizing the rational allocation of factor resources, promoting green technology innovation, and achieving high-quality economic growth. [ABSTRACT FROM AUTHOR]

This document is a correction notice for an article titled "Modelling the Effects of Exogenous Changes on the Social Problem of Capital Allocation" published in the journal International Advances in Economic Research. The correction addresses an error in the affiliation details of one of the authors, Mariano Torras. The correct affiliation should have been listed as the Department of Finance and Economics, 201C Hagedorn Hall, Adelphi University, Garden City, NY, 11530, USA. The original article has been corrected. The publisher, Springer Nature, maintains a neutral stance on jurisdictional claims and institutional affiliations. The authors of the article are Robert S. Goldberg, Zahra Sedighi-Maman, and Mariano Torras. [Extracted from the article]

We propose a stochastic model allowing property and casualty insurers with multiple business lines to measure their liabilities for incurred claims risk and calculate associated capital requirements. Our model includes many desirable features which enable reproducing empirical properties of loss ratio dynamics. For instance, our model integrates a double generalized linear model relying on accident semester and development lag effects to represent both the mean and dispersion of loss ratio distributions, an autocorrelation structure between loss ratios of the various development lags, and a copula-based aggregation of risks model driving the dependence across the various business lines. Our work is the first in the literature to combine all such advantageous features within a loss triangle model. The model allows for a joint simulation of loss triangles and the quantification of the overall portfolio risk through risk measures. Consequently, a diversification benefit associated with the economic capital requirements can be measured, in accordance with IFRS 17 standards which allow for the recognition of such benefit. The allocation of capital across business lines based on the Euler allocation principle is then illustrated. The implementation of our model is performed by estimating its parameters based on a car insurance data obtained from the General Insurance Statistical Agency (GISA), and by conducting numerical simulations whose results are then presented. [ABSTRACT FROM AUTHOR]

Diversification decisions in banks can be atypical owing to the nature of banking business. Banks diversify across business segments such as retail, wholesale or treasury, and spread their sources of liabilities, asset exposures and income types across customer groups, industry sectors and geographies. While the more granular decisions of diversification have regulatory and policy norms to follow, less guidance is available for making segment diversification. Using data of business segments from annual reports of five private sector banks in India for the period 2008–2009 to 2015–2016, the study attempts to find out the decision factors behind their diversification. It is found that though being highly diversified universal banks now, these banks were initially oriented toward certain segments from where they have shifted their portfolios over time. Bank diversification decision involves pursuing segment growth and executed by making capital expenditure and risk capital allocation to the segments. Banks make higher capital expenditure on segments that contribute more to generation of deposits and liabilities. On the other hand, risk capital allocation is determined by segment's share of assets as well as their risk adjusted returns. Segment growth may be targeted with the intent of achieving higher profitability and capital efficiency, but the outcome appears to be uncertain. Business segment diversification of private banks, therefore, seem to be intended toward enhancing resources generation and targeting higher profitability while economizing on risk capital. [ABSTRACT FROM AUTHOR]

Solvency II Directive 2009/138/EC requires an insurance and reinsurance undertakings assessment of a Solvency Capital Requirement by means of the so-called "Standard Formula" or by means of partial or full internal models. Focusing on the first approach, the bottom-up aggregation formula proposed by the regulator allows for a capital reduction due to the diversification effect, according to the typical subadditivity property of risk measures. However, once the overall capital has been assessed no specific allocation formula is provided or required in order to evaluate the contribution of each risk source on the overall Solvency Capital Requirement. The aim of this paper is twofold. First, we provide a closed formula for capital allocation fully compliant with the Solvency II Capital Requirement assessed by means of the Standard Formula. The solution enables a top-down approach to assess the allocated Solvency Capital Requirement among the risks considered in the Solvency II multilevel aggregation scheme; we demonstrate that the allocation formula adopted is consistent with the Euler allocation principle. Second, a solution is found as a result of an optimum capital allocation problem based on a Return On Risk Adjusted Capital measure; we establish the equivalence between the Return On Risk Adjusted Capital optimization, when the risk adjusted capital is calculated according to the Standard Formula, and the Markowitz mean-variance optimization. [ABSTRACT FROM AUTHOR]

This paper introduces a new approach to face capital allocation problems from the perspective of acceptance sets, by defining the family of sub-acceptance sets. We study the relations between the notions of sub-acceptability and acceptability of a risky position as well as their impact on the allocation of risk. We define the notion of risk contribution rule and show how in this context it is interpretable as a tool for assessing the contribution of a sub-portfolio to a given portfolio in terms of acceptability without necessarily involving a risk measure. Furthermore, we investigate under which conditions on a risk contribution rule a representation of an acceptance set holds in terms of the risk contribution rule itself, thus extending to this setting the interpretation, classical in risk measures theory, of minimal amount required to hedge a risky position. [ABSTRACT FROM AUTHOR]

The challenges of using technology in the insurance field are opening new horizons for developing and distributing innovative products. Among these, peer-to-peer insurance schemes attract the interest of policyholders and insurance companies. Different types of peer-to-peer insurance have been introduced, from pure models to hybrid ones, as in the case of the broker model. In this paper, we focus on the broker model, where the groups of peers are formed by an insurance broker according to similar risk characteristics. The participants in the network pay an initial contribution defined by a cooperative rule that must be transparent and shared. A part or the whole of the collected contributions is set aside in a common fund. At the end of the year, if the common fund is sufficient to pay for the claims, the members obtain the excess over-retained premiums that is shared according to a capital allocation rule. We propose a cashback distribution mechanism based on the participant’s marginal contribution to the risk, framing the issue in a cooperative game and applying the concept of Shapley value to define an optimal allocation rule of the remaining capital. A numerical application based on a portfolio of motor third-party liability policies is developed to show how the model works. [ABSTRACT FROM AUTHOR]

Background: The wind energy industry is an important part of the renewable energy industry. Helpful financial support plays an essential role in the process of its development. This study analyzes the financial support efficiency not only from the aspect of capital raise, but also from the aspect of the allocation of up-, middle- and down-stream of the Chinese wind power industry chain (which includes the fan component manufacturing enterprises, the fan production enterprises, the wind farm generation and operation enterprises). Methods: Based on a data envelopment analysis (DEA) model, this study selected 30 representative public companies which sampled and extracted their financial data in a panel analysis from 2010 to 2015, in which the financial support efficiency for the Chinese wind power industry was investigated from the aspect of capital raise and allocation. Results: In terms of capital raise, the comprehensive efficiencies of these three streams all reached their peak in 2011, and then indicated a slight decline, whereas the fan component manufacturing enterprises had both the largest pure technical efficiency value in 2011 and a relatively high scale efficiency value during the sampling period. In terms of capital allocation, the fan component manufacturing enterprises and the wind farm generation and operation enterprises indicated both the highest comprehensive efficiency in 2011, which is merely the expansion period of the new energy industry. The wind farm generation and operation enterprises showed the lowest pure technical value in 2012, which is also the depression period of the new energy industry. The scale efficiency of the fan production enterprises as well as the wind energy generation and operation enterprises had a relatively high scale efficiency value from 2010 to 2015. Conclusion: The overall efficiency of financial support in the Chinese wind power industry has a close relationship to the macro-economic environment and capital raise while the allocation efficiency of up-, middle-and down-stream show different characteristics. Moreover, the lag of the core technology is the biggest barrier to the financial support efficiency of the wind power industry. [ABSTRACT FROM AUTHOR]

The 'beta' is one of the key quantities in the capital asset pricing model (CAPM). In statistical language, the beta can be viewed as the slope of the regression line fitted to financial returns on the market against the returns on the asset under consideration. The insurance counterpart of CAPM, called the weighted insurance pricing model (WIPM), gives rise to the so-called weighted-Gini beta. The aforementioned two betas may or may not coincide, depending on the form of the underlying regression function, and this has profound implications when designing portfolios and allocating risk capital. To facilitate these tasks, in this paper we develop large-sample statistical inference results that, in a straightforward fashion, imply confidence intervals for, and hypothesis tests about, the equality of the two betas. [ABSTRACT FROM AUTHOR]

In this paper we study the tail risk of a properly diversified credit portfolio under a latent risk factor model. The usual perception is that if the diversification leads to asymptotic independence among the risk factors, then, because of the relatively low probability of simultaneous defaults, the tail risk of the entire portfolio is negligible. However, we point out that in fact there may be substantial tail risk hidden in this situation. We use a conditional tail probability of the portfolio loss to quantify the hidden tail risk, and then provide an asymptotic characterization for the risk under a hidden regular variation structure assumed for the risk factors. We also propose applications of the characterization to the determination and allocation of related insurance risk capital, based on the Conditional Tail Expectation risk measure. To understand the impact of dependence on the quantities of interest, we study two special cases where the risk factors have a Gaussian copula or an Archimedean copula. Numerical examples are provided to illustrate the results. [ABSTRACT FROM AUTHOR]

This paper is a follow-up of the study realized by Vernic (2014) on the aggregation of dependent random variables joined by Sarmanov's multivariate distribution, with accent on the particular case of exponentially distributed marginals. More precisely, in this paper we present capital allocation formulas for a portfolio of risks following the just mentioned Sarmanov's distribution. The overall capital and its allocation to the risk sources are evaluated using the TVaR rule. The resulting formulas are illustrated in some particular cases. [ABSTRACT FROM AUTHOR]

The evolution of international regulation leads to new capital requirements imposed on globally active companies. Financial services firms allocate capital to business lines in order to withstand the materializing credit losses and to measure the performance of various business lines. In this study, we introduce a methodology for optimal credit capital allocation based on operations research approach. In particular, we focus on the efficient allocation of capital to business lines characterized by credit risk losses and cost of capital. We compare different allocation methods and provide a rationale behind using the OR approach. Finally, we formulate a multiobjective optimization model to capital allocation problem and apply it to a real-world case of two financial conglomerates. [ABSTRACT FROM AUTHOR]

In order to determine the risk capital for their aggregate portfolio, property and casualty insurance companies must fit a multivariate model to the loss triangle data relating to each of their lines of business. As an inadequate choice of dependence structure may have an undesirable effect on reserve estimation, a two-stage inference strategy is proposed in this paper to assist with model selection and validation. Generalized linear models are first fitted to the margins. Standardized residuals from these models are then linked through a copula selected and validated using rank-based methods. The approach is illustrated with data from six lines of business of a large Canadian insurance company for which two hierarchical dependence models are considered, i.e., a fully nested Archimedean copula structure and a copula-based risk aggregation model. [ABSTRACT FROM AUTHOR]

We examine two interrelated issues in risk-adjusted return on capital performance measurement: estimating hurdle rates and allocating capital to debt instruments in a portfolio. We consider a methodology to differentiate hurdle rates for individual debt instruments that incorporates obligor-specific information. These instrument-specific hurdle rates, which define the required compensation of the shareholders, enable a granular differentiation of systematic risk among debt contracts. Using the proposed approach, we show that the hurdle rate could be materially different among industry sectors and obligors of different credit quality. Profitability assessment could be significantly distorted if the difference in hurdle rates is ignored. [ABSTRACT FROM AUTHOR]

Enterprise risk management, actuarial science or finance are practice areas in which risk measures are important to evaluate for heterogeneous classes of homogeneous risks. We present new measures: bivariate lower and upper orthant Tail Value-at-Risk. They are based on bivariate lower and upper orthant Value-at-Risk, introduced in Cossette et al. (Insurance: Math Econ 50(2):247-256, ). Many properties and applications are derived. Notably, they are shown to be positive homogeneous, invariant under translation and subadditive in distribution. Capital allocation criteria are suggested. Moreover, results on the sum of random pairs are presented, allowing to use a more accurate model for dependent classes of homogeneous risks. [ABSTRACT FROM AUTHOR]

Assuming the multiplicative background risk model, which has been a popular model due to its practical applicability and technical tractability, we develop a general framework for analyzing portfolio performance based on its subportfolios. Since the performance of subportfolios is easier to assess, the herein developed stepwise portfolio construction (SPC) provides a powerful alternative to a number of traditional portfolio construction methods. Within this framework, we discuss a number of multivariate risk models that appear in the actuarial and financial literature. We provide numerical and graphical examples that illustrate the SPC technique and facilitate our understanding of the herein developed general results. [ABSTRACT FROM AUTHOR]

In this paper, we address the aggregation of dependent stop loss reinsurance risks where the dependence among the ceding insurer(s) risks is governed by the Sarmanov distribution and each individual risk belongs to the class of Erlang mixtures. We investigate the effects of the ceding insurer(s) risk dependencies on the reinsurer risk profile by deriving a closed formula for the distribution function of the aggregated stop loss reinsurance risk. Furthermore, diversification effects from aggregating reinsurance risks are examined by deriving a closed expression for the risk capital needed for the whole portfolio of the reinsurer and also the allocated risk capital for each business unit under the TVaR capital allocation principle. Moreover, given the risk capital that the reinsurer holds, we express the default probability of the reinsurer analytically. In case the reinsurer is in default, we determine analytical expressions for the amount of the aggregate reinsured unpaid losses and the unpaid losses of each reinsured line of business of the ceding insurer(s). These results are illustrated by numerical examples. [ABSTRACT FROM AUTHOR]

Built from given marginals with a flexible dependency structure, Sarmanov's family of multivariate distributions became of interest in various fields. In this paper, we present some formulas for the density of the sum of several random variables joined by Sarmanov's distribution, with accent on the particular case of exponentially distributed marginals. Such results are useful in solving, e.g., financial and actuarial problems. [ABSTRACT FROM AUTHOR]

In this paper, by an axiomatic approach, we propose the concepts of comonotonic subadditivity and comonotonic convex risk measures for portfolios, which are extensions of the ones introduced by Song and Yan (2006). Representation results for these new introduced risk measures for portfolios are given in terms of Choquet integrals. Links of these newly introduced risk measures to multi-period comonotonic risk measures are represented. Finally, applications of the newly introduced comonotonic coherent risk measures to capital allocations are provided. [ABSTRACT FROM AUTHOR]

This article reviews the literature on techniques of credit risk models, multi-period risk measurement, and capital allocation, and gives a tutorial on applying these techniques to credit portfolios with a focus on practical aspects. The effects of the choice of considered loss process concerning the handling of write-offs and matured assets or rating migration are displayed, and the impact on portfolio optimization decisions is discussed. We highlight the trade-off between short-term and long-term profitability and allude to the practical challenges of an application of multi-period risk measurement. [ABSTRACT FROM AUTHOR]

We are interested in the tail behavior of the randomly weighted sum $ \sum _{i=1}^{n}\theta _{i}X_{i}$, in which the primary random variables X, ..., X are real valued, independent and subexponentially distributed, while the random weights 휃, ..., 휃 are nonnegative and arbitrarily dependent, but independent of X, ..., X. For various important cases, we prove that the tail probability of $\sum _{i=1}^{n}\theta _{i}X_{i}$ is asymptotically equivalent to the sum of the tail probabilities of 휃 X, ..., 휃 X, which complies with the principle of a single big jump. An application to capital allocation is proposed. [ABSTRACT FROM AUTHOR]

Financial institutions are expected to play a crucial role in reallocating resources in favor of industries facing greater global and local shocks to growth opportunities. Fisman and Love, in their paper entitled 'Financial development and intersectoral allocation: A new approach', argue that growth opportunities are unobservable and propose a new methodology to test the capital allocation hypothesis. The methodology is based on correlations in the patterns of intra-industry growth between two countries and similarities in the level of financial development and income. This paper extends their methodology by proposing direct and forward- looking measures of local and global growth opportunities, obtained by interacting the country's patterns of industrial specialization with industry-level price-earnings ratios, as in the paper 'Global growth opportunities and market integration' by Bekaert et al. The results, obtained in a cross-section framework including 37 developed and developing countries over the period 1992-2006, confirm the relevance of financial development to promote economic growth and to help industries in taking advantage of global and local growth opportunities. They also show that the methodology developed by Fisman and Love can be extended to include direct measures of growth opportunities. [ABSTRACT FROM AUTHOR]

Capital allocation by percentile layer is a relatively new method. There is a claim that this method will generate different capital allocations than three other popular methods: CoVaR, Alternative CoVaR and CoTVAR methods. It is also claimed that capital allocation by percentile allocates more capital to catastrophic perils that will cause more severe losses. We study these four methods formally. We show neither of the two claims holds in general. The results of this paper will provide actuaries and other financial risk analysts with valuable insights into capital allocation by percentile layer. [ABSTRACT FROM AUTHOR]

In this paper we present an optimization framework to deal with the asset-liability portfolio selection problem. We consider a financial institution that has multiple lines of business. The capital allocation is obtained by minimizing the sum of the expected squared differences between the liability in each line of business and the value of the corresponding investment portfolio. We show that in certain circumstances the bottom-up approach is consistent with the top-down approach, where the optimal capital is determined for the whole portfolio rather than its individual components. Such a case happens for example if the same weight function is used for all lines of business in the two approaches. Finally, we obtain investment portfolios under some limitations on short sales. [ABSTRACT FROM AUTHOR]

In this paper, we propose an explicit estimation of Value-at-Risk (VaR) and Expected Shortfall (ES) for linear portfolios when the risk factors change with a convex mixture of generalized Laplace distributions (M-GLD). We introduce the dynamics Delta-GLD-VaR, Delta-GLD-ES, Delta-MGLD-VaR and Delta-MGLD-ES, by using conditional correlation multivariate GARCH. The generalized Laplace distribution impose less restrictive assumptions during estimation that should improve the precision of the VaR and ES through the varying shape and fat tails of the risk factors in relation with the historical sample data. We also suggested some areas of application to measure price risk in agriculture, risk management and financial portfolio optimization. [ABSTRACT FROM AUTHOR]

Responsible risk management is central to banking ethics. With the 1999 publication of the Basel Committee’s proposal, Basel II, for a New Capital Accord to replace the 1988 agreement, Basel I, an attempt has been made to address the problem of correlating banks’ risk management with their capital requirements. The Basel II framework, finalised in June 2004, is designed to improve risk management by using models based on past performance to help set the amount of capital banks are required to hold by regulators, with the purpose of improving the efficiency of capital allocation. The objectives of this study are to investigate how banks generally, but particularly those located in China, could improve their risk management systems and what the implications of these new regulations are for them. Three relevant propositions were formulated, namely, Basel II will improve risk management; Basel II will improve capital allocation efficiency; and compliance with advanced risk management systems is biased in favour of the large banks. Evidence was assembled with which to evaluate these three propositions by gathering relevant primary data by means of a representative survey of Chinese banking executives involved in risk management. The findings strongly support the first two of the above propositions and partly support the third proposition. [ABSTRACT FROM AUTHOR]