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Article

ROBERT CESKE, JOSÉ V. HERNÁNDEZ and LUIS M. SÁNCHEZ

Operational or event risk is not a new phenomenon for financial services companies. However, its measurement, as part of integrated risk management programs, has been the…

Abstract

Operational or event risk is not a new phenomenon for financial services companies. However, its measurement, as part of integrated risk management programs, has been the subject of recent focus. Property and casualty insurers have measured components of this risk class as part of the pricing and underwriting process. Although all financial services firms are exposed to direct and indirect (e.g., reputational) costs of operational risk events, few financial services firms actually measure “operational risk.” This article explores ways in which this may be done in practice.

Details

The Journal of Risk Finance, vol. 1 no. 3
Type: Research Article
ISSN: 1526-5943

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Article

Fatemeh Abdolshah, Saeed Moshiri and Andrew Worthington

The Iranian banking industry has been greatly affected by dramatic changes in macroeconomic conditions over the past several decades owing to volatile oil revenues…

Abstract

Purpose

The Iranian banking industry has been greatly affected by dramatic changes in macroeconomic conditions over the past several decades owing to volatile oil revenues, changing fiscal and monetary policies, and the imposition of US sanctions. The main objective of this paper is to estimate potential credit losses in the Iranian banking sector due to macroeconomic shocks and assess the minimum economic capital requirements under the baseline and distressed scenarios. The paper also contrasts the applications of linear and nonlinear models in estimating the impacts of macroeconomic shocks on financial institutions.

Design/methodology/approach

The paper uses a multistage approach to derive the portfolio loss distribution for banks. In the first step, the dynamic relationship between the selected macroeconomic variables are estimated using a VAR model to generate the stress scenarios. In the second step, the default probabilities are estimated using a quantile regression model and the results are compared with those of the conventional linear models. Finally, the default probabilities are simulated for a one-year time horizon using Monte-Carlo method and the portfolio loss distribution is calculated for hypothetical portfolios. The expected loss includes the loss given default for loans drawn randomly and uniformly distributed and exposed at default values when loans are assigned a fixed value.

Findings

The results indicate that the loss distributions under all scenarios are skewed to the right, with the linear model results being very similar to those of quantile at the 50% quantile, but very unlike those at the 10% and 90% quantiles. Specifically, the quantile model for the 90% (10%) quantile generates estimates of minimum economic capital requirement that are considerably higher (lower) than those using the linear model.

Research limitations/implications

The study has focused on credit risk because of lack of data on other types of risk at individual bank level. The future studies can estimate the aggregate economic capital using a risk aggregation approach and a panel data (not presently available), which could further improve the accuracy of the estimates.

Practical implications

The fiscal and monetary authorities in developing countries, specially oil-exporting countries, can follow the risk assessment approach to assess the health of their banking system and adapt policies to mitigate the impacts of large macroeconomic shocks on their financial markets.

Originality/value

This is the first paper estimating the portfolio loss distribution for the Iranian banks under turbulent macroeconomic conditions using linear and nonlinear models. The case study can be applied to other developing and emerging countries, particularly those highly dependent on natural resources, prone to extreme macroeconomic shocks.

Details

Journal of Economic Studies, vol. 48 no. 2
Type: Research Article
ISSN: 0144-3585

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Article

Ernestina Mawushie Amewornu and Nnamdi I. Nwulu

This research studies the impact of introducing distributed generators (DGs) into a distribution network. The aim of this paper is to optimally site DGs based on economic…

Abstract

Purpose

This research studies the impact of introducing distributed generators (DGs) into a distribution network. The aim of this paper is to optimally site DGs based on economic, environmental and reliability indices are presented.

Design/methodology/approach

The considered network was modelled by using the network’s line parameters and capacity of the load bus with the help of Power System Analysis Toolbox. The location of the DG is based on voltage stability index and power loss reduction index. The DG energy sources considered are the diesel generator, solar photo-voltaic (PV) and wind generator, and the objectives were to minimize cumulative cost while maximizing reliability of the network. The Advanced Interactive Multidimensional Modelling System was used for the mathematical modelling.

Findings

The obtained results in the cases of introducing renewable energy into a network improves network performance. The benefits of renewable energy on the distribution network measured in terms of electricity production cost, gas emission cost, fuel cost and value of energy not supplied were positive. The research also showed that the total benefit of renewable energy reduces as the price of the renewable generators increases.

Originality/value

This paper introduces a new approach to determining the optimal location of DG for reducing line losses and improved voltage profile. A new cost modelling function based on external grid power transfer cost, technical losses and cost because of the various energies source is also introduced.

Details

Journal of Engineering, Design and Technology , vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1726-0531

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Article

NISSO BUCAY and DAN ROSEN

In recent years, several methodologies for measuring portfolio credit risk have been introduced that demonstrate the benefits of using internal models to measure credit…

Abstract

In recent years, several methodologies for measuring portfolio credit risk have been introduced that demonstrate the benefits of using internal models to measure credit risk in the loan book. These models measure economic credit capital and are specifically designed to capture portfolio effects and account for obligor default correlations. An example of an integrated market and credit risk model that overcomes this limitation is given in Iscoe et al. [1999], which is equally applicable to commercial and retail credit portfolios. However, the measurement of portfolio credit risk in retail loan portfolios has received much less attention than the commercial credit markets. This article proposes a methodology for measuring the credit risk of a retail portfolio, based on the general portfolio credit risk framework of Iscoe et al. The authors discuss the practical estimation and implementation of the model. They demonstrate its applicability with a case study based on the credit card portfolio of a North American financial institution. They also analyze the sensitivity of the results to various assumptions.

Details

The Journal of Risk Finance, vol. 2 no. 3
Type: Research Article
ISSN: 1526-5943

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Article

Yajing Zhang and Guotai Chi

The purpose of this paper is to split loan customers to different credit ratings to ensure the results that show that customers with lower credit ratings have higher loss

Abstract

Purpose

The purpose of this paper is to split loan customers to different credit ratings to ensure the results that show that customers with lower credit ratings have higher loss rates, and the number of customers that satisfies the bell-shaped distribution. Hence, the number of credit ratings, the distribution of the rated obligors among ratings can achieve a meaningful differentiation of risk, which can avoid the loan pricing confusion.

Design/methodology/approach

The authors introduce a multi-objective programming to establish the credit rating model. Objective function 1 minimizes the absolute difference between the obligor number proportion and perfect client proportion, following a standard normal distribution. Objective function 2 minimizes the total difference of the deviation between two adjacent credit ratings’ loss rates. This study combines the two objective functions to ensure the obligor number distribution and the monotonicity of the loss rate, and applies genetic algorithm to solve the model.

Findings

This study’s analysis is based on data from 6,155 enterprises, provided by a Chinese bank and Prosper P2P loan data. The empirical results reveal that the proposed approach can ensure the balance between both criteria and avoid undue concentration of obligors in particular grades.

Originality/value

The proposed credit model could help building a reasonable credit rating system, which is the prerequisite of loan pricing; thus, inaccurate credit rating can cause incorrect loss rate estimates and loan pricing.

Details

Management Decision, vol. 56 no. 5
Type: Research Article
ISSN: 0025-1747

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Article

Jeffrey S. Pai and Milton S. Boyd

In the USA, private insurance companies serve as an integral part of the delivery and risk sharing of the federal crop insurance program. Governed by the Standard…

Abstract

Purpose

In the USA, private insurance companies serve as an integral part of the delivery and risk sharing of the federal crop insurance program. Governed by the Standard Reinsurance Agreement (SRA), private crop insurance companies must designate an eligible crop insurance contract to the assigned risk, developmental, or commercial funds. While the SRA restricts the private sector delivery system in a number of ways, the assignment of contracts to crop insurance funds, however, is left solely to the discretion of individual crop insurance companies. Thus, as to the companies' profitability viewpoint, the optimal selection of the crop insurance funds is the most important task. Therefore, the purpose of this paper is to provide a decision framework for crop insurance companies to make optimal decisions regarding the purchases of crop reinsurance. This information and framework may also be useful for crop insurance firms in China when considering crop reinsurance decisions.

Design/methodology/approach

The paper studied three commonly used parametric loss distributions and presented a general guideline to choose the most profitable fund within the company's risk bearing level.

Findings

The paper finds many important features in the commonly used loss distributions, which are useful to maximize the company's underwriting returns.

Originality/value

The paper provides a general decision framework for optimally ceding risks to reinsurance. While this paper focused on agricultural insurance decisions by firms, the concept could be applied to general reinsurance decisions.

Details

China Agricultural Economic Review, vol. 2 no. 2
Type: Research Article
ISSN: 1756-137X

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Article

Dmitry V. Vedenov, Mario J. Miranda, Robert Dismukes and Joseph W. Glauber

An economic analysis is presented of the Standard Reinsurance Agreement (SRA), the contract governing the relationship between the Federal Crop Insurance Corporation and…

Abstract

An economic analysis is presented of the Standard Reinsurance Agreement (SRA), the contract governing the relationship between the Federal Crop Insurance Corporation and the private insurance companies that deliver crop insurance products to farmers. The paper outlines provisions of the SRA and describes the modeling methodology behind the SRA simulator, a computer program developed to assist crop insurers and policy makers in assessing the economic impact of the Agreement. The simulator is then used to analyze how the SRA affects returns from underwriting crop insurance. The results are presented in aggregate and also at the regional and individual company levels.

Details

Agricultural Finance Review, vol. 64 no. 2
Type: Research Article
ISSN: 0002-1466

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Article

Mohammad Amin Jarrahi, Emad Roshandel, Mehdi Allahbakhshi and Mohammad Ahmadi

This paper aims to achieve an optimal design for distribution transformers considering cost and power losses. Particle swarm optimization (PSO) algorithm is used as an…

Abstract

Purpose

This paper aims to achieve an optimal design for distribution transformers considering cost and power losses. Particle swarm optimization (PSO) algorithm is used as an optimization tool for minimizing the objective functions of design procedure which are cost and electrical and iron losses.

Design/methodology/approach

In this paper, distribution transformer losses are considered as operating costs. Also, transformer construction cost which depends on the amount of iron and copper in the structure is assumed as its initial cost. In addition, some other important constraints such as appropriate ranges of transformer efficiency, voltage regulation, temperature rise, no-load current, and winding fill factor are investigated in the design procedure. The PSO algorithm is applied to find optimum amount of needed copper and iron for a typical distribution transformer. Moreover, transformer impedance considered as a constraint to achieve an acceptable voltage regulation in the design process.

Findings

It is shown that the proposed design procedure provides a simple and effective approach to estimate the flux and current densities for minimizing the active part cost and active power losses which means reduction in amount of transformer total owning cost (TOC).

Originality/value

The methodology advances a proposal for reducing distribution transformers costs using PSO algorithm. The approach considers the aforementioned constraints and TOC to minimize the active part cost and maximize the efficiency. It is demonstrated that a designed transformer will not be optimum when the transformer losses over years are not considered in design procedure. Finally, the results prove the effectiveness of the proposed procedure in designing cost-effective distribution transformers from its initial cost until its whole life.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering , vol. 38 no. 2
Type: Research Article
ISSN: 0332-1649

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Book part

Andrei V. Lopatin and Timur Misirpashaev

We propose a new model for the dynamics of the aggregate credit portfolio loss. The model is Markovian in two dimensions with the state variables being the total…

Abstract

We propose a new model for the dynamics of the aggregate credit portfolio loss. The model is Markovian in two dimensions with the state variables being the total accumulated loss Lt and the stochastic default intensity λt. The dynamics of the default intensity are governed by the equation dλt=κ(ρ(Lt,t)−λt)dt+σλtdWt. The function ρ depends both on time t and accumulated loss Lt, providing sufficient freedom to calibrate the model to a generic distribution of loss. We develop a computationally efficient method for model calibration to the market of synthetic single tranche collateralized debt obligations (CDOs). The method is based on the Markovian projection technique which reduces the full model to a one-step Markov chain having the same marginal distributions of loss. We show that once the intensity function of the effective Markov chain consistent with the loss distribution implied by the tranches is found, the function ρ can be recovered with a very moderate computational effort. Because our model is Markovian and has low dimensionality, it offers a convenient framework for the pricing of dynamic credit instruments, such as options on indices and tranches, by backward induction. We calibrate the model to a set of recent market quotes on CDX index tranches and apply it to the pricing of tranche options.

Details

Econometrics and Risk Management
Type: Book
ISBN: 978-1-84855-196-1

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Article

Venkataramana Veeramsetty, Venkaiah Chintham and Vinod Kumar D.M.

The purpose of this paper is to estimate the locational marginal price (LMP) at each distributed generation (DG) bus based on DG unit contribution in loss reduction. This…

Abstract

Purpose

The purpose of this paper is to estimate the locational marginal price (LMP) at each distributed generation (DG) bus based on DG unit contribution in loss reduction. This LMP value can be used by distribution company (DISCO) to control private DG owners and operate network optimally in terms of active power loss.

Design/methodology/approach

This paper proposes proportional nucleolus game theory (PNGT)-based iterative method to compute LMP at each DG unit. In this algorithm, PNGT has been used to identify the share of each DG unit in loss reduction. New mathematical modeling has been incorporated in the proposed algorithm to compute incentives being given to each DG owner.

Findings

The findings of this paper are that the LMP and reactive power price values for each DG unit were computed by the proposed method for the first time. Network can be operated with less loss and zero DISCO’s extra benefit, which is essential in deregulated environment. Fair competition has been maintained among private DG owners using the proposed method.

Originality/value

PNGT has been used for the first time for computation of LMP in distribution system based on loss reduction. Incentives to each DG unit has have been computed based on financial savings of DISCO due to loss reduction. Share of active and reactive power generation of each DG unit on change in active power loss of network due to that DG unit has been computed with new mathematical modeling. The proposed method provides LMP value to each DG unit in such a way that the network will be operated with less loss.

Details

International Journal of Energy Sector Management, vol. 12 no. 3
Type: Research Article
ISSN: 1750-6220

Keywords

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