Quantitative Measure Of Risk Research Articles

Quantitative measurement and management of liquidity risk in a banking context

Quantitative measurement and management of liquidity risk in a banking context

Assessing Credit Risk in the RMBS Sector

U.S. residential mortgage performance is expected to remain under pressure in 2012. Although default rates and the number of serious delinquent loans have been falling, negative equity for non-agency RMBS loans continues to be a primary driver of collateral performance for all borrowers. RMBS credit risk can be measured by various quantitative measures of risk as an alternative to ratings.

A Survey of Systemic Risk Analytics

We provide a survey of 31 quantitative measures of systemic risk in the economics and finance literature, chosen to span key themes and issues in systemic risk measurement and management. We motivate these measures from the supervisory, research, and data perspectives in the main text and present concise definitions of each risk measure—including required inputs, expected outputs, and data requirements—in an extensive Supplemental Appendix. To encourage experimentation and innovation among as broad an audience as possible, we have developed an open-source Matlab® library for most of the analytics surveyed, which, once tested, will be accessible through the Office of Financial Research (OFR) at http://www.treasury.gov/initiatives/wsr/ofr/Pages/default.aspx .

Application of quantitative metrics for assessing the investment risk

Identification and assessment of risk-especially in small and medium-sized enterprises - from the beginning were the part of the topics of research scientists. Significant investments are also related to the implementation and correct application of quantitative measures of risk assessment. The article compares the important quantitative measures of risk and presents their practical calculation. The paper shows the correct interpretation of the results of calculations, that should be helpful in decision-making by managers.

A Survey of Systemic Risk Analytics

We provide a survey of 31 quantitative measures of systemic risk in the economics and finance literature, chosen to span key themes and issues in systemic risk measurement and management. We motivate these measures from the supervisory, research, and data perspectives in the main text, and present concise definitions of each risk measure - including required inputs, expected outputs, and data requirements - in an extensive appendix. To encourage experimentation and innovation among as broad an audience as possible, we have developed open-source Matlab code for most of the analytics surveyed.

Quantifying time-inhomogeneous stochastic introgression processes with hazard rates

Introgression is the permanent incorporation of genes from one population into another through hybridization and backcrossing. It is currently of particular concern as a possible mechanism for the spread of modified crop genes to wild populations. The hazard rate is the probability per time unit that such an escape takes place, given that it has not happened before. It is a quantitative measure of introgression risk that takes the stochastic elements inherent in introgression processes into account. We present a methodology to calculate the hazard rate for situations with time-varying gene flow from a crop to a large recipient wild population. As an illustration, several types of time-inhomogeneity are examined, including deterministic periodicity as well as random variation. Furthermore, we examine the effects of an extended fitness bottleneck of hybrids and backcrosses in combination with time-varying gene flow. It is found that bottlenecks decrease the hazard rate, but also slow down and delay its changes in reaction to changes in gene flow. Furthermore, we find that random variation in gene flow generates a lower hazard rate than analogous deterministic variation. We discuss the implications of our findings for crop management and introgression risk assessment.

Abstract 17315: Comparing Knowledge and Attitudes about CHD Prevention Among Older Women Prior to and After a Cardiac Event

Purpose: Risk factors for coronary heart disease (CHD) are at epidemic proportions among older women but few recognize their actual risk. Our purpose was to compare and contrast knowledge and attitudes concerning CHD prevention among older women without a CHD diagnosis with those who had experienced a cardiac event. Method: Using a mixed-methods design, we measured standard cardiac risk factors to determine actual risk and obtained measures of self-perceived risk among 20 older women, 6-12 months post cardiac event, and 24 community-dwelling women (≥60 years) without a CHD diagnosis. Semi-structured individual qualitative interviews were conducted to query about knowledge and attitudes regarding CHD prevention and risk. Narratives were transcribed verbatim and analyzed using content analysis. Next, constant comparison was used to compare and contrast findings between the two groups with the quantitative risk measures for convergence/divergence of data. Results: Of the 44 women, 30% were African-American and 64% had some college education, with a mean age of 72 years. Despite a mean of 5.84 vs. 4.46 CHD risk factors (event vs. no CHD) indicating “high-risk” for both groups, personal risk perceptions were unrealistically low: 4.47 vs. 1.95 (0-10 scale). Narrative data indicated a general lack of understanding in both groups regarding risk factors and lifestyle behaviors that would reduce probability for experiencing a cardiac event. Few engaged in lifestyle risk factor modification and felt limited control of their health or did not think change was necessary. Most felt that taking daily medications and visiting their Provider were sufficient. They tended to rely on their Provider to recommend behavior changes and did not recall their Provider discussing risk factors or recommending lifestyle modifications. Conclusions: Results provide information that is critically important from which to derive interventions that facilitate primary and secondary prevention for older women with and without CHD. Tailored interventions that consider knowledge and attitudes about CHD risk and risk factors are needed to promote lifestyle behavior modification.

Update on raloxifene: role in reducing the risk of invasive breast cancer in postmenopausal women

Risk factors allow us to define women who are at increased lifetime risk for breast cancer, and the most important factor is age. Benign breast disease increases risk, and the most important histologies are atypical lobular or ductal hyperplasia and lobular carcinoma in situ. Family history of breast cancer among first-degree relatives (mother, sisters, daughters) also increases risk. Quantitative measures of risk give accurate predictions of breast cancer incidence for groups of women but not for individual subjects. Multiple published, randomized controlled trials, which employed selective estrogen receptor (ER) modulators (SERMs), have demonstrated consistent reductions of 35% or greater in the risk of ER-positive invasive and noninvasive breast cancer in postmenopausal women. Professional organizations in the US now recommend the use of SERMs to reduce the risk of breast cancer in high-risk, postmenopausal women. Raloxifene and tamoxifen reduce the risk of ER-positive invasive breast cancer with equal efficacy, but raloxifene is associated with a lower risk of thromboembolic disease, benign uterine conditions, and cataracts than tamoxifen in postmenopausal women. No evidence exists establishing whether a reduction in breast cancer risk from either agent translates into reduced breast cancer mortality. Overall quality of life is similar with raloxifene or tamoxifen, but the incidence of dyspareunia, weight gain, and musculoskeletal complaints is higher with raloxifene use, whereas vasomotor symptoms, bladder incontinence, gynecologic symptoms, and leg cramps were higher with tamoxifen use.

Developing safety performance functions incorporating reliability-based risk measures

Current geometric design guides provide deterministic standards where the safety margin of the design output is generally unknown and there is little knowledge of the safety implications of deviating from these standards. Several studies have advocated probabilistic geometric design where reliability analysis can be used to account for the uncertainty in the design parameters and to provide a risk measure of the implication of deviation from design standards. However, there is currently no link between measures of design reliability and the quantification of safety using collision frequency. The analysis presented in this paper attempts to bridge this gap by incorporating a reliability-based quantitative risk measure such as the probability of non-compliance (Pnc) in safety performance functions (SPFs). Establishing this link will allow admitting reliability-based design into traditional benefit–cost analysis and should lead to a wider application of the reliability technique in road design. The present application is concerned with the design of horizontal curves, where the limit state function is defined in terms of the available (supply) and stopping (demand) sight distances. A comprehensive collision and geometric design database of two-lane rural highways is used to investigate the effect of the probability of non-compliance on safety. The reliability analysis was carried out using the First Order Reliability Method (FORM). Two Negative Binomial (NB) SPFs were developed to compare models with and without the reliability-based risk measures. It was found that models incorporating the Pnc provided a better fit to the data set than the traditional (without risk) NB SPFs for total, injury and fatality (I+F) and property damage only (PDO) collisions.

Product demand risk management model based on empirical forecasting: consumer electronics product case

Producers continually need to determine how much of a particular product to produce. As market globalisation has changed their business, their demand uncertainty has become too big and too complex to manage. This study proposes a product's quantitative risk measurement and management model based on empirical sales forecasting. By introducing the concept of two time points of a product's lifecycle, two types of risks – the chance loss and the surplus loss caused by demand uncertainty – are defined. It provides a proposed volume under their risk-taking strategies even just after its release. Using a case study, this model is applied to consumer electronics device production planning and verifies how it works. This model proved to be able to provide optimised supply volume option and reduced product local risk compared with what is actually being done.

A Markovian infectious model for dependent default risk

Modelling dependent defaults has long been a central issue for credit risk measurement and management. To address this important issue, we introduce a Markovian infectious model to describe the dependent relationship of default processes of credit securities. The central tenant of the proposed model is the concept of common shocks which is one of the major approaches to describe insurance risk. Using real data default data, we compare the proposed model to some existing default risk models, such as one-sector and two-sector models discussed in Ching et al. (2008, 2010). A log likelihood ratio test is adopted for the purpose of model comparison. Our empirical results reveal that the proposed model outperforms both the one-sector and two-sector models. We also illustrate the application of the proposed model for quantitative risk measurement. In particular, numerical results for both the crisis value-at-risk and the crisis expected shortfall are provided.

Statistical analysis of mammographic breast composition measurements: towards a quantitative measure of relative breast cancer risk.

A number of studies have identified the relationship between the visual appearance of high breast density at mammography and an increased risk of breast cancer. With the advent of digital mammography and the promise of routine measurements of parameters associated with breast composition, the possibility arises of using breast composition in a quantitative manner to predict relative breast cancer risk. Previous measurements have shown that the average proportion of glandular and adipose tissue within the breast varies with both age and breast size. In order to be able to identify individual women with an unusually high volume of glandular tissue, it will therefore be necessary to make comparisons with a disease-free population matched for age and breast size. A large number of breast glandular thickness measurements were analysed to investigate the statistics of breast composition across a disease-free population as a test of a suitable methodology for relative risk estimation. The large data set is also used to revisit the trends in breast composition used in the current UK method of breast radiation dosimetry. It is demonstrated that a non-linear transformation can be used to produce normal statistical distributions, suitable for producing a standardised "Z-score" for breast composition. A standard "Z-score" approach to identify women with unusually glandular breasts is recommended and so provide a basis for cancer risk estimations.

Releasing Microdata: Disclosure Risk Estimation, Data Masking and Assessing Utility

Statistical Agencies need to make informed decisions when releasing sample microdata from social surveys with respect to the level of protection required in the data and the mode of access. These decisions should be based on objective quantitative measures of disclosure risk and data utility. This paper reviews recent developments in disclosure risk assessment and discusses how these can be integrated with established methods of data masking and utility assessment for releasing microdata. We illustrate the Disclosure risk-Data Utility approach based on samples drawn from a Census where the population is known and can be used to investigate sample-based methods and validate results.

Comparative Assessment of Civil Infrastructure Network Performance under Probabilistic and Scenario Earthquakes

The intensity of the seismic demand in a vulnerability assessment of an engineered system can be described in terms of either its annual probability of being exceeded or a scenario earthquake. A probabilistically stated hazard (e.g., one with a return period of 2,475 years) represents an aggregation of numerous earthquakes and may not represent the spatial distribution of seismic intensity from a severe earthquake over a region correctly, making its application to performance evaluation of a large-scale distributed civil infrastructure system questionable. A scenario earthquake models the spatial intensity correctly, but conveys no quantitative measure of the seismic risk. This paper examines the use of probabilistic seismic hazard analysis and corresponding scenario earthquakes as a basis for vulnerability assessment of a networked system. Following an examination of simple spatially distributed series and parallel system models, a vulnerability assessment of an electrical power network in a region of moderate seismicity in the Central United States offers additional insight into the issue.

A Total Risk Measurement Framework for Hedge Funds and Funds of Funds

This paper illustrates how qualitative analysis can be incorporated into quantitative risk measurement in order to construct an expected distribution of hedge fund returns that explicitly allows for market, residual and tail risk. We show how the combination of statistical criteria with out-of-sample model evaluation techniques, coupled with a qualitative understanding of the particular hedge fund strategy can lead to more robust risk factor models that capture the out-of-sample rather than the historical variation in hedge fund returns. Using Monte Carlo simulation techniques, that allow the most appropriate data generating process for each risk factor, we proceed to build a market risk based expected distribution of returns which is then adjusted for the presence of residual and tail risk. The residual risk distribution of expected returns is entirely based on the out-of-sample errors of the risk factor model and by using the out-of-sample explanatory power of the model as the weighting parameter we allow the model to ‘self correct’ when the actual returns deviate significantly from the model conditional expected returns. The tail risk distribution of returns and the correlation of these tails are solely based on qualitative analysis. We propose a methodology for the quantification of the potential impact of factors such as leverage, liquidity and concentration on the size and probability of excess losses due to tail risks. The proposed framework allows investors to explicitly measure, monitor and manage the modelable and non-modelable risks in a hedge fund portfolio.

Simulation discounted cash flow valuation for internet companies

Discounted cash flow (DCF) is the most accepted approach for company valuation. However, the DCF approach presents a number of serious weaknesses within the internet companies' context. One of these weaknesses is tackling the uncertainty that characterise future cash flows of these companies. This paper looks at the way in which uncertainty can be incorporated into the DCF approach so that the latter, which is otherwise conceptually sound, becomes relevant. This is done by utilising a probability-based valuation model (using Monte Carlo simulation) to incorporate uncertainty into the analysis and address the shortcomings of the current model. The process leads to a probability distribution of the valuation criterion used, giving investors a quantitative measure of risk involved. The paper takes the case of a real internet company to illustrate the approach and highlight the benefits and the difficulties, which are encountered.

Initial test of the Seattle Asthma Severity and Control Questionnaire: a multidimensional assessment of asthma severity and control

The Seattle Asthma Severity and Control Questionnaire (SASCQ) was designed as a short, sensitive, and quantitative measure of asthma severity, impairment, and risk. To evaluate the distribution of responses to the SASCQ in a diverse asthma population and to determine whether the questionnaire is associated with other measures of asthma severity and control. A cross-sectional study of 188 asthmatic patients was conducted in a large academic primary care network. Asthma severity was confirmed in a subgroup of 44 patients by means of an in-person interview and lung function measurement. The SASCQ score had a nearly normal distribution across the heterogeneous population and less of a floor effect than the number of asthma-free days. The SASCQ score showed a higher symptom burden in the mildest asthmatic patients compared with nonasthmatic controls. Asthma severity evaluated using the questionnaire was correlated with asthma severity evaluated by means of in-person interview and with controller medication class. The SASCQ score was associated with primary care visits for asthma, emergency department treatment for asthma, days missed from work, and confidence to control asthma symptoms; the associations between these measures of impairment and risk were all stronger for the SASCQ score than for asthma-free days. The SASCQ is a quantitative measure of asthma that accurately discriminates between established levels of asthma severity and that is associated with other measures of asthma control and risk.

Generating SNP barcode to evaluate SNP–SNP interaction of disease by particle swarm optimization

Genome-wide association analysis involved many single-nucleotide polymorphisms (SNPs) data is challenging mathematically and computationally. Hence, we propose the odds ratio-based discrete binary particle swarm optimization (OR-DBPSO) method that uses the OR as a new quantitative measure of disease risk among many SNP combinations with genotypes called “SNP barcode”. DBPSO are applied to generate SNP barcode, which computes the maximal difference of occurrence between the case and control groups, to predict disease susceptibility such as osteoporosis. Different SNP barcode patterns may occur several times in either low or high bone mineral density (BMD) groups. Our results showed that a DBPSO can effectively identify a specific SNP barcode with an optimized fitness value. SNP barcodes with a low fitness value will naturally be discarded from the population. A representative SNP barcode with a variable number of SNPs is processed to OR analysis to determine the maximum difference between the low and high BMD groups in statistics manner. Therefore, this paper introduces a powerful procedure to analyze disease-associated SNP–SNP interaction in genome-wide genes.

An evaluation of risk factors impacting construction cash flow forecast

PurposeThe purpose of this paper is to identify and assess the extent of occurrence and impact of risk factors responsible for the variation between the forecast and actual construction cash flow.Design/methodology/approachThe study was conducted through a structured questionnaire administered to UK contracting organizations. Adopting a project‐by‐project approach, respondents were asked to provide opinions on the extent of occurrence of some identified risk factors and their impacts on cash flow forecast. Respondents were split into three groups of small, medium and large contracting firms based on their annual turnover so as to be able to investigate statistical differences of opinions between the groups. Statistical analyses were carried out using mean response analysis and univariate analysis of variance (ANOVA) in order to determine significant risk factors and also to investigate differences of opinions between respondents' groupings.FindingsThe research identified 11 significant risk factors out of 26 research risk variables. These significant risk variables can be grouped under three generic factors of “changes in the design or specification”, “project complexity” and “natural inhibition”. The significant risk variables are those ranking high in “extent of occurrence” and with critical impacts on cash flow forecast. The research further showed that there is no statistically significant difference in the opinions of different categories of contractors regarding the extent of risk occurrence and impacts on cash flow forecast.Research limitations/implicationsThe research showed that the order of extent of risk occurrence is different from the order of impact in case of occurrence. This suggests that further work needs to be done to measure the impact more objectively on a ratio scale so as to provide an avenue for a more quantitative measure of risk impacts on cash flow forecast. This objective is the next focus of this study.Practical implicationsBased on the finding, it is evident that the knowledge of the identified significant risk factors provides invaluable information to the construction contractor as regards what risk variables to focus attention on in cash flow forecasting.Originality/valueThe paper makes an original contribution of exploring the extent of risk occurrence and its impact on construction cash flow forecast from an objective point of view rather that the usual subjective point of view. The epistemic nature of the investigation makes the finding of practical value to the construction contractor in cash flow forecasting.

Estimating foreign currency exposure in the Canadian Department of National Defence

Quantifying foreign currency risk is not a trivial process, although it is generally accepted that the standard method for reporting financial risk today is the value-at-risk (VaR) method, which provides a quantitative measure of the downside risk of exposure in all foreign currency transactions. This paper documents the theory and application of a model that is built on forecasting expenditures related to departmental materiel procurement and capital equipment accounts, and the time-varying volatility of foreign currency returns. These diverse methodologies are combined into an overall VaR model to determine the maximum expected loss from adverse exchange rate fluctuations over the budget year. This is recognized as the first step the Canadian Department of National Defence must take before considering risk mitigation strategies to reduce and, hopefully, eliminate foreign transaction exposure.