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We develop a theoretical perspective on how the increasing data availability in the digital age affects firms’ strategic decisions. Specifically, we explore whether, and under which conditions, external experts’ collective assessment of product-technology domains impacts firms’ allocation of capital to their strategic business units engaged in these domains. Drawing on decision comprehensiveness theory, we propose that such expert sentiment has informational value for capital allocation decisions, and that this value is contingent on the available information’s determinacy and quantity. We find evidence for our propositions by studying 669 capital allocation decisions made by 85 pharmaceutical firms from 2005 to 2016, and by using supervised machine learning classifiers to analyse expert sentiment in almost 250,000 articles. Our study contributes to the behavioural theory of the firm by showing that, contrary to what scholars traditionally assume, decision makers broaden, rather than narrow, their information processing in comprehensive information environments.

This paper analyzes risk capital allocation problems. For risk capital allocation problems, the aim is to allocate the risk capital of a firm to its divisions. Risk capital allocation is of central importance in risk-based performance measurement. We consider a case in which the aggregate risk capital is determined via a coherent risk measure. The academic literature advocates an allocation rule that, in game-theoretic terms, is equivalent to using the Aumann-Shapley value as solution concept. This value is however not well-defined in case a differentiability condition is not satisfied. As an alternative, we introduce an allocation rule inspired by the Shapley value in a fuzzy setting. We take a grid on a fuzzy participation set, define paths on this grid and construct an allocation rule based on a path. Then, we define a rule as the limit of the average over these allocations, when the grid size converges to zero. We introduce this rule for a broad class of coherent risk measures. We show that if the Aumann-Shapley value is well-defined, the allocation rule coincides with it. If the Aumann-Shapley value is not defined, which is due to non-differentiability problems, the allocation rule specifies an explicit allocation. It corresponds with the Mertens value, which is originally characterized in an axiomatic way (Mertens, 1988), whereas we provide an asymptotic argument.

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.

In this paper we make a short survey on the problem of Capital Allocation through the use of risk measures and we apply some of the most popular Capital Allocation methods to a portfolio of risky positions by using Value at Risk, Conditional Value at Risk and the entropic risk measure. We then discuss and compare the results found in our numerical example.

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.

This paper deals with the problem of capital allocation for a peculiar class of risk measures, namely the Haezendonck-Goovaerts (HG) ones. We generalize the capital allocation rule (CAR) introduced by Xun et al. for Orlicz risk premia, using firstly an approach based on Orlicz quantiles and secondly a more general one based on the, here introduced, concept of linking functions. Further on, we use the same construction of to extend the CARs previously introduced to HG risk measures. We therefore study the properties of different CARs for HG risk measures, both in the quantile-based setting and in the linking one. Finally, we provide robust versions of the introduced CARs, both considering the case of ambiguity over the probabilistic model and the one of multiple Young functions, following the scheme of.

Operational risk management remains a major concern for financial institutions. Indeed, institutions are bound to manage their own funds to hedge this risk. In this paper, we propose an approach to allocate one&rsquo, s own funds based on a combination of historical data and expert opinion using the loss distribution approach (LDA) and Bayesian logic. The results show that internal models are of great importance in the process of allocating one&rsquo, s own funds, and the use of the Delphi method for modelling expert opinion is very useful in ensuring the reliability of estimates.

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.

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.

This paper makes the point on a well known property of capital allocation rules, namely the one called no-undercut. Its desirability in capital allocation stems from some stability game theoretical features that are related to the notion of core, both for finite and infinite games. We review these aspects, by relating them to the properties of the risk measures that are involved in capital allocation problems. We also discuss some problems and possible extensions that arise when we deal with non-coherent risk measures.

Major (2018) discusses Euler/Aumann-Shapley allocations for non-linear positively homogeneous portfolios. For such portfolio structures, plausibly arising in the context of reinsurance, he defines a distortion-type risk measure that facilitates assessment of ceded and net losses with reference to gross portfolio outcomes. Subsequently, Major (2018) derives explicit formulas for Euler allocations for this risk measure, thus (sub-)allocating ceded losses to the portfolio’s original components. In this comment, we build on Major’s (2018) insights but take a somewhat different direction, to consider Euler capital allocations for distortion risk measures directly applied to homogeneous portfolios. Explicit formulas are derived and our approach is compared with that of Major (2018) via a numerical example.

The article chooses nine indicators from scale, liquidity, financing function, investment function and effectiveness of stock market, using factor analysis to simplified them to three comprehensive indicators: capital allocation, investment and financing level and operation, then focuses on the different weight of each index based on its influence degree to build the index which can fully reflect the development of Chinese stock market. The results show that although the overall development of Chinese stock market in 2003-2012 was on the rise, there are still many problems, such as inefficient operation, the prevailing wind of speculation and the irrational investment behaviour.

In this paper we consider an extension to the aggregation of the FGM mixed Erlang risks, proposed by Cossette et al. (2013 Insurance: Mathematics and Economics, 52, 560–572), in which we introduce the Sarmanov distribution to model the dependence structure. For our framework, we demonstrate that the aggregated risk belongs to the class of Erlang mixtures. Following results from S. C. K. Lee and X. S. Lin (2010 North American Actuarial Journal, 14(1) 107–130), G. E. Willmot and X. S. Lin (2011 Applied Stochastic Models in Business and Industry, 27(1) 8–22), analytical expressions of the contribution of each individual risk to the economic capital for the entire portfolio are derived under both the TVaR and the covariance capital allocation principle. By analysing the commonly used dependence measures, we also show that the dependence structure is wide and flexible. Numerical examples and simulation studies illustrate the tractability of our approach.

The main objective of this work is to develop a detailed step-by-step guide to the development and application of a new class of efficient Monte Carlo methods to solve practically important problems faced by insurers under the new solvency regulations. In particular, a novel Monte Carlo method to calculate capital allocations for a general insurance company is developed, with a focus on coherent capital allocation that is compliant with the Swiss Solvency Test. The data used is based on the balance sheet of a representative stylized company. For each line of business in that company, allocations are calculated for the one-year risk with dependencies based on correlations given by the Swiss Solvency Test. Two different approaches for dealing with parameter uncertainty are discussed and simulation algorithms based on (pseudo-marginal) Sequential Monte Carlo algorithms are described and their efficiency is analysed., Risks, 5 (4)

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.

In order to protect stakeholders of insurance companies and financial institutions against adverse outcomes of risky businesses, regulators and senior management use capital allocation techniques. For enterprise-wide risk management, it has become important to calculate the contribution of each risk within a portfolio. For that purpose, bivariate lower and upper orthant tail value-at-risk can be used for capital allocation. In this paper, we present multivariate value-at-risk and tail-value-at-risk for d ≥ 2 , and we focus on three different methods to calculate optimal values for the contribution of each risk within the sums of random vectors to the overall portfolio, which could particularly apply to insurance and financial portfolios.

In this paper we introduce a new coherent cumulative risk measure on a subclass in the space of cadlag processes. This new coherent risk measure turns out to be tractable enough within a class of models where the aggregate claims is driven by a spectrally positive Levy process. We focus our motivation and discussion on the problem of capital allocation. Indeed, this risk measure is well-suited to address the problem of capital allocation in an insurance context. We show that the capital allocation problem for this risk measure has a unique solution determined by the Euler allocation method. Some examples and connections with existing results as well as practical implications are also discussed.

This article develops a unifying framework for allocating the aggregate capital of a financial firm to its business units. The approach relies on an optimization argument, requiring that the weighted sum of measures for the deviations of the business unit's losses from their respective allocated capitals be minimized. The approach is fair insofar as it requires capital to be close to the risk that necessitates holding it. The approach is additionally very flexible in the sense that different forms of the objective function can reflect alternative definitions of corporate risk tolerance. Owing to this flexibility, the general framework reproduces several capital allocation methods that appear in the literature and allows for alternative interpretations and possible extensions.

This paper described a theory of capital allocation for decentralized businesses, taking into account the costs associated with risk capital. We derive an adjusted present value expression for making investment decisions, that incorporates the time varying profile of risk capital. We discuss the implications for business performance measurement.

One of Chandler's basic insights was that the new organizational structures adopted after the 1920s reflected a specialization of the roles of business and corporate managers. Business managers coordinated functions and corporate managers allocated resources. This article studies the impact of corporate management on capital allocation decisions by comparing investment behavior in multi- and single-business companies. Using a new taxonomy to control for the quality of each business unit, we analyze a cross-sectional sample of U.S. companies and identify a number of empirical regularities that highlight the allocative decisions of corporate management. In particular, we find that, when dealing with cash-needy businesses, multi-business firms invest more intensively in those that are less profitable. We find no evidence that this subsidy results in a higher success rate in making those businesses profitable over time. We suggest a number of explanations for this empirical pattern. Copyright 2010 The Author 2010. Published by Oxford University Press on behalf of Associazione ICC. All rights reserved., Oxford University Press.

Tasche [Tasche, D., 1999. Risk contributions and performance measurement. Working paper, Technische Universität München] introduces a capital allocation principle where the capital allocated to each risk unit can be expressed in terms of its contribution to the conditional tail expectation (CTE) of the aggregate risk. Panjer [Panjer, H.H., 2002. Measurement of risk, solvency requirements and allocation of capital within financial conglomerates. Institute of Insurance and Pension Research, University of Waterloo, Research Report 01-15] derives a closed-form expression for this allocation rule in the multivariate normal case. Landsman and Valdez [Landsman, Z., Valdez, E., 2002. Tail conditional expectations for elliptical distributions. North American Actuarial J. 7 (4)] generalize Panjer's result to the class of multivariate elliptical distributions. In this paper we provide an alternative and simpler proof for the CTE-based allocation formula in the elliptical case. Furthermore, we derive accurate and easy computable closed-form approximations for this allocation formula for sums that involve normal and lognormal risks. © 2007 Elsevier Ltd. All rights reserved. ispartof: Insurance: Mathematics & Economics vol:42 issue:2 pages:855-863 status: published

The aim of this paper is twofold. First, we generalize the notion of capital requirement, originally formulated in a regulatory framework, in order to unify other apparently diverse financial concepts. Second, we stress the interpretation of a capital requirement as a measure of risk, providing a link with the theory of coherent risk measures. We define a capital requirement as the minimal initial cost of a hedging action that makes the original position acceptable. Three basic elements are involved in such a methodology: a system of prices, a class of permitted hedging actions and a criterion of acceptability. Our approach is very general, because we construct capital requirements on vector spaces. However, we will give some concrete applications related, in particular, to the availability of a financial market, to the presence of different business units in an institution or to the fact that pay-offs are spread over different dates.

Um dos motivos para a recente evolução da gestão de riscos em bancos internacionais é a proposta contida no Novo Acordo de Capital da Basiléia. Essa proposta busca uma maior especialização na alocação de capital em função dos riscos presentes nas atividades dos bancos, tendência que já vem sendo refletida no ambiente regulamentar local pelo Banco Central do Brasil. A gestão de riscos e a alocação de capital em seguradoras no mercado internacional encontram-se em um processo de convergência acelerada para os princípios requeridos dos bancos. O mesmo não pode ser dito no que se refere ao ambiente regulamentar para as seguradoras no Brasil, que ainda se encontra em um estágio de desenvolvimento inferior quando comparado a seu equivalente local para bancos. Neste ensaio, apresentamos as diferenças existentes entre os ambientes de requerimento regulamentar de capital para bancos e seguradoras no Brasil. Nosso objetivo é propor a unificação desses ambientes no mercado brasileiro, apresentando uma sugestão de como tal unificação deve ser conduzida. The New Basel Capital Accord is one of the main reasons behind the recent evolution of risk management in international banks. This proposal requires that capital be allocated to face the risks present in banks. This international trend is already being reflected in the Brazilian regulatory environment for banks. The regulatory environment for risk management and capital allocation for insurance companies is converging quickly to that of banks in international markets. The same is not true for the Brazilian regulatory environment for insurance companies, which is still far behind that of banks. In this article we present the main differences between the regulatory environment for capital allocation faced by banks and insurance companies in Brazil. Our main objective is to propose a unified regulatory framework to require capital in both banks and insurance companies in Brazil, showing how this convergence should be conducted.

A portfolio based model (Credit Risk of Credit Suisse First Boston) and recent Central Bank of Argentina credit bureau data are used to estimate whether current capital and provisioning regulations match actual risks. Arguing that provisions should cover expected losses and that capital requirements should cover potential losses beyond expected losses subject to some statistical level of tolerance, the article assesses how well actual capital and provisioning requirements match the estimated requirements given by the model. Actual provisioning requirements were found to be close to implied levels of expected losses. The estimate of potential losses was found to be highly sensitive to the assumptions of the model, especially the parameter relating the volatility of a loan's rate of default to its mean value. This volatility parameter cannot be estimated accurately with the credit bureau data because of the short time span covered, so proxy data were used to estimate it, and two values around that estimate were tried. The difficulty of estimating this critical parameter implies that the results should only be regarded as suggestive. Moreover, the methodology only does not seek to estimate credit risk and not interest rate risk or exchange rate risk, nor does it fully take into account the indirect effects of interest rates and exchange rates on credit risk. As recent events in Argentina have demonstrated, estimating credit risk along these lines should be thought of as just one tool in attempting to assess the appropriate level of bank provisions and capital.

Expected Shortfall (ES) has been widely accepted as a risk measure that is conceptually superior to Value-at-Risk (VaR). At the same time, however, it has been criticised for issues relating to backtesting. In particular, ES has been found not to be elicitable which means that backtesting for ES is less straightforward than, e.g., backtesting for VaR. Expectiles have been suggested as potentially better alternatives to both ES and VaR. In this paper, we revisit commonly accepted desirable properties of risk measures like coherence, comonotonic additivity, robustness and elicitability. We check VaR, ES and Expectiles with regard to whether or not they enjoy these properties, with particular emphasis on Expectiles. We also consider their impact on capital allocation, an important issue in risk management. We find that, despite the caveats that apply to the estimation and backtesting of ES, it can be considered a good risk measure. As a consequence, there is no sufficient evidence to justify an all-inclusive replacement of ES by Expectiles in applications. For backtesting ES, we propose an empirical approach that consists in replacing ES by a set of four quantiles, which should allow to make use of backtesting methods for VaR. Keywords: Backtesting; capital allocation; coherence; diversification; elicitability; expected shortfall; expectile; forecasts; probability integral transform (PIT); risk measure; risk management; robustness; value-at-risk, 27 pages, 1 table

This paper investigates how financial, trade, institutional and political liberalization policies have affected financial efficiency in Africa. It uses updated data to appraise second generation reforms in order to gather fresh evidence and derive more updated policy implications. The ‘freedom to trade’ and ‘economic freedom’ indices are also employed. The following findings are established. (1) Financial liberalization mitigates financial allocation efficiency, with the magnitude of the de jure indicator (KAOPEN) higher than that of the de facto measurement (FDI). (2) Exports significantly improve financial efficiency. (3) Institutional liberalization has a positive effect on the efficiency of allocation while the effect of political liberalization is not significant. (4) Freedom of trade decreases (improves) financial (banking) system efficiency. (5) Economic freedom facilitates the transformation of mobilized financial resources (deposits) into credit for economic operators. Justifications for these nexuses are provided.

peer-reviewed Server consolidation is an important problem in any enterprise, where capital allocators (CAs) must approve any cost saving plans involving the acquisition or allocation of new assets and the decommissioning of inefficient assets. Our paper describes iVMp an interactive VM placement algorithm, that allows CAs to become ???agile??? capital allocators that can interactively propose and update constraints and preferences as placements are recommended by the system. To the best of our knowledge this is the first time that this interactive VM placement recommendation problem has been addressed in the academic literature. Our results show that the proposed algorithm finds near optimal solutions in a highly efficient manner.

International audience; 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.

We extend the literature on how managerial traits relate to corporate choices by documenting that firms run by female CEOs have lower leverage, less volatile earnings, and a higher chance of survival than otherwise similar firms run by male CEOs. Additionally, transitions from male to female CEOs (or vice versa) are associated with economically and statistically significant reductions (increases) in corporate risk-taking. The results are robust to controlling for the endogenous matching between firms and CEOs using a variety of econometric techniques. We further document that this risk-avoidance behavior appears to lead to distortions in the capital allocation process. These results potentially have important macroeconomic implications for long-term economic growth.

In this paper we propose a new rule to allocate risk capital to portfolios or divisions within a firm. Specifically, we determine the capital allocation that minimizes the excesses of sets of portfolios in a lexicographical sense. The excess of a set of portfolios is defined as the expected loss of that set of portfolios in excess of the amount of risk capital allocated to them. The underlying idea is that large excesses are undesirable, and therefore the goal is to determine the allocation for which the largest excess is as small as possible. We show that this allocation rule yields a unique allocation, and that it satisfies some desirable properties. We also show that the allocation can be determined by solving a series of linear programming problems.

A competitive stock market is embedded into a neoclassical growth economy to analyze the interplay between the acquisition of information about firms, its partial revelation through stock prices, capital allocation, and income. The stock market allows investors to share their costly private signals in a cost-effective incentive-compatible way. It contributes to economic growth by raising total factor productivity (TFP). A calibration indicates the effect on TFP to be large but that on income to be modest. Several predictions on the evolution of real and financial variables are derived. Finally, the growth impact of two common forms of investor irrationality, overconfidence and inattention, are analyzed.

Previous research on capital investment has identified a tendency in multibusiness firms toward cross-subsidization from well-performing to poorly performing divisions, a phenomenon that has previously been attributed to principal-agent conflicts between headquarters and divisions (Stein, 2003). In this paper, we argue that cross-subsidization reflects a more general tendency toward even allocation over all divisions in multibusiness firms that is driven, at least in part, by the cognitive tendency to naively diversify when making investment decisions (Benartzi and Thaler, 2001). We observe that this tendency also leads to partition dependence in which capital allocations vary systematically with the divisions and subdivisions into which the firm is organized or over which capital is allocated. Our first study uses archival data to show that firms' internal capital allocations are biased toward equality over the number of business units into which the firm is partitioned. Two further experimental studies of experienced managers examine whether this bias persists when participants are asked to allocate capital to various divisions of a hypothetical firm. This methodology eliminates the possibility of agency conflicts. Nevertheless, allocations varied systematically with the divisional and subdivisional structure of the firm and with a centralized or decentralized capital allocation manner. Copyright © 2011 John Wiley & Sons, Ltd.

This paper considers the financial optimization problem of a firm with several sub-businesses striving for its optimal RORAC. An insightful example shows that the implementation of classical gradient capital allocation can be suboptimal if division managers are allowed to venture into all business whose marginal RORAC exceeds the firm’s RORAC. The marginal RORAC requirements are refined by adding a risk correction term that takes into account the interdependencies of the risks of different lines of business. It is shown that under certain stationarity conditions this approach can guarantee that the optimal RORAC will eventually be achieved.

Measuring value creation by comparing the RAROC of an exposure (the return on risk capital) with a single institution-wide hurdle rate is inconsistent with the standard theory of financial valuation. We use asset pricing theory to determine the appropriate hurdle rate for such a RAROC performance measure. We find that this hurdle rate varies with the skewness of asset returns. Thus the RAROC hurdle rate should differ substantially between equity which has a right skew and debt which has a pronounced left skew and also between different qualities of debt exposure. We discuss implications for financial institution risk management and supervision.

The capital structure of firms that face restrictions on liquidity (i.e. that cannot hedge continuously) is affected by the agency costs and moral-hazard implicit in the contracts they establish with stockholders and customers. It is demonstrated in this paper that then an optimal level of capital exists, which is characterised in terms of the actuarial prices of the involved agreements. The capital principle so obtained explicitly depends on risk and expectations and it can be naturally applied to allocate balances inside multidivisiona corporations. In particular, an optimal decentralised mechanism is defined, which stimulates the exchange of information between central and divisional administrations. A novel model of capital is thus formulated, which extends the classic theoretical framework (sustained by the well-known proposition of Modigliani and Miller and the model of deposit insurance of Robert Merton) and integrates the financial and actuarial theoretical settings.

This paper is accepted to appear in Springer Journal of computing and visualization in science.; In this paper, we generalize the parametric Delta-VaRmethods from portfolios with elliptic distributed risk factors to portfolios with mixture of elliptically distributed ones.We treat both the Expected Shortfall and the Value-at-Risk of such portfolios. Special attentionis given to the particular case of the mixture of Student-t distributions.

International audience; A fixed budget must be allocated to a finite number of different projects with uncertain outputs. The expected marginal productivity of capital in a project first increases then decreases with the amount of capital invested. Such behavior is common when output is a probability (of escaping infection, succeeding with an R&D project...). When the total budget is below some threshold, it is invested in a single project. Above this cutoff, the share invested in a project can be discontinuous and non-monotone in the total budget. Above an upper cutoff, all projects receive more capital as the budget increases.

In this paper, we generalize the parametric delta-VaR method from portfolios with normally distributed risk factors to portfolios with elliptically distributed ones. We treat both the expected shortfall and the Value-at-Risk of such portfolios. Special attention is given to the particular case of a multivariate t-distribution., Comment: This paper has been presented to the workshop of Financial Engineering du 6-8 Mai 2003 at Bad Herrelnab Germany. it is a preprint of Reims university and it is downloadble at http://www.univ-reims.fr\Labos\Mathematiques\pub03.html

This paper aims to study changes in capital allocation routines following the introduction of a new risk management system, enterprise risk management (ERM). Based on an institutional framework and empirical evidence from multiple sources in a large UK insurance company, we evaluated the extent and nature of organisational change. ERM was seen as an external driver to the change in the existing routines, which in turn led to internal changes in new capital allocation routines. The change was extreme, which signifies that existing capital allocation routines were not strong enough to deal with ERM as a key driver of change.