Loss-Based Risk Measures

Starting from the requirement that risk measures of financial portfolios should be based on their losses, not their gains, we define the notion of loss-based risk measure and study the properties of this class of risk measures. We characterize loss-based risk measures by a representation theorem and give examples of such risk measures. We then discuss the statistical robustness of estimators of loss-based risk measures: we provide a general criterion for qualitative robustness of risk estimators and compare this criterion with sensitivity analysis of estimators based on influence functions. Finally, we provide examples of statistically robust estimators for loss-based risk measures.Comment: 40 page

Risk-Based Capacitor Placement in Distribution Networks

In this paper, the problem of sizing and placement of constant and switching capacitors in electrical distribution systems is modelled considering the load uncertainty. This model is formu- lated as a multicriteria mathematical problem. The risk of voltage violation is calculated, and the stability index is modelled using fuzzy logic and fuzzy equations. The instability risk is introduced as the deviation of our fuzzy-based stability index with respect to the stability margin. The capacitor placement objectives in our paper include: (i) minimizing investment and installation costs as well as loss cost; (ii) reducing the risk of voltage violation; and (iii) reducing the instability risk. The proposed mathematical model is solved using a multi-objective version of a genetic algorithm. The model is implemented on a distribution network, and the results of the experiment are discussed. The impacts of constant and switching capacitors are assessed separately and concurrently. Moreo- ver, the impact of uncertainty on the multi-objectives is determined based on a sensitivity analysis. It is demonstrated that the more the uncertainty is, the higher the system cost, the voltage risk and the instability risk are

Risk based resilient network design

This paper presents a risk-based approach to resilient network design. The basic design problem considered is that given a working network and a fixed budget, how best to allocate the budget for deploying a survivability technique in different parts of the network based on managing the risk. The term risk measures two related quantities: the likelihood of failure or attack, and the amount of damage caused by the failure or attack. Various designs with different risk-based design objectives are considered, for example, minimizing the expected damage, minimizing the maximum damage, and minimizing a measure of the variability of damage that could occur in the network. A design methodology for the proposed risk-based survivable network design approach is presented within an optimization model framework. Numerical results and analysis illustrating the different risk based designs and the tradeoffs among the schemes are presented. © 2011 Springer Science+Business Media, LLC

A comparison of risk-based capital and risk-based deposit insurance

A comparison of alternative bank regulatory proposals for controlling the level of bank risk, using a model based on six FDIC variables for predicting bank failure or loss.Risk ; Capital

A Risk-Return Paradox: Risk, Performance-Based Pay and Performance

[Excerpt] In recent years, strategy researchers have examined the relationship between business risk and performance. The logic underlying this relationship is that organizations facing greater business risk seek to offset it with the prospect of higher financial returns. The research typically involves various financial measures of organization performance regressed on measures of risk. Surprisingly, the findings are contradictory. While some studies report evidence supporting a positive relationship between the risk organizations face and their performance (Aaker & Jacobson, 1987; Fiegenbaum & Thomas, 1988), others reported an inverse relationship (Bowman, 1982, 1984). These different results called into question the basic premise about the form of the risk-return relationship and left a void in understanding why organization decision makers might pursue more risky strategies. Advancing this line of inquiry, Miller and Bromiley (1990) noted that business risk, like financial performance, is multi-dimensional. Several dimensions of business risk emerged from their work including income stream and strategic or financial risk. They suggested that differences reported in the risk-return relationship resulted from different operationalizations of business risk

Risk based capital allocation

In this paper, we focus on the economic research of corruption. In the first part, we define corruption, types of corruption, its factors and ways to measure it. This section brings together various definitions by notable authors of this domain, such as Begovic, Tanzi, Mauro or Lambsdorff. Before moving to the second section, we are presenting definitions, typologies and factors already researched by acclaimed authors. In the second part, we focus on the channels by which corruption transmits its effects through the economy. This section consists of two major sub-parts, the first one in which we take part in a vivid scientific discussion with the ‘’apologists’’ of corruption, i.e. with those economists who underline positive roles of corruption. In the second sub-part of the second section, as a logic continuation of the previous sub-part, we are listing three important consequences of rampant corruption in one economy: consequences to economic growth, foreign direct investments and economic efficiency. Major contribution of this paper is compilation of significant scientific discoveries in the area, as well as bringing new arguments in the discussion on the economic consequences of corruption. The paper uses traditional approach of the New institutional economics (NIE), by underlining the importance of governance, transaction costs and rent seeking.corruption, institutional capacities, new institutional economics, transaction costs, FDI

Risk Based Capital Allocation

The present contribution reviews the procedures (absolute, incremental and marginal capital allocation) as well as the general principles (proportional allocation, covariance-principle, conditional expectation-principle, conditional value-at-risk principle, Euler-principle) for risk based capital allocation. The approaches discussed are applicable for the insurance case, the investment case and as well for credit risks.