ON HETEROGENEITY IN THE INDIVIDUAL MODEL WITH BOTH DEPENDENT CLAIM OCCURRENCES AND SEVERITIES

2018 ◽  
Vol 48 (02) ◽  
pp. 817-839 ◽  
Author(s):  
Yiying Zhang ◽  
Xiaohu Li ◽  
Ka Chun Cheung
Keyword(s):  
Claim Amount ◽  
Common Belief ◽  
Individual Model ◽  
Numerical Examples ◽  
Scale Parameters ◽  
Aggregate Claim ◽  
Left Tail ◽  
Insurance Portfolio ◽  
The Individual ◽  
Arrangement Increasing

AbstractIt is a common belief for actuaries that the heterogeneity of claim severities in a given insurance portfolio tends to increase its dangerousness, which results in requiring more capital for covering claims. This paper aims to investigate the effects of orderings and heterogeneity among scale parameters on the aggregate claim amount when both claim occurrence probabilities and claim severities are dependent. Under the assumption that the claim occurrence probabilities are left tail weakly stochastic arrangement increasing, the actuaries' belief is examined from two directions, i.e., claim severities are comonotonic or right tail weakly stochastic arrangement increasing. Numerical examples are provided to validate these theoretical findings. An application in assets allocation is addressed as well.

scholarly journals Estimation of the probable maximum loss based on extreme value theory for stock returns

Equilibrium ◽  
2009 ◽  
Vol 2 (1) ◽  
pp. 51-59
Author(s):  
Marcin Fałdziński
Keyword(s):  
Stock Returns ◽  
Extreme Value Theory ◽  
Value Theory ◽  
Claim Amount ◽  
Total Claim Amount ◽  
Maximum Loss ◽  
Probable Maximum Loss ◽  
Insurance Portfolio ◽  
Total Claim ◽  
The Individual

Probable maximum loss is a measure coming from the insurance market, where is applied to insurance portfolio analysis. This correspond to the 20-80 rule, which states that 20% of the individual claims are responsible for more than 80% of the total claim amount in a well defined portfolio. The main aim of the presented paper is estimation of the probable maximum loss for stock returns which are treated as portfolios of securities. It turns out that probable maximum loss is a useful tool for risk analysis or/and diagnostic purposes at capital markets, but we have to be aware of its drawbacks.

scholarly journals Wearable robotic exoskeletons: A socio-philosophical perspective on Duchenne muscular dystrophy research

2020 ◽  
Vol 11 (1) ◽  
pp. 404-413
Author(s):  
Alexandra Kapeller ◽  
Michael H. Nagenborg ◽  
Kostas Nizamis
Keyword(s):  
Duchenne Muscular Dystrophy ◽  
Muscular Dystrophy ◽  
Disability Studies ◽  
Philosophy Of Technology ◽  
Research Projects ◽  
Philosophical Perspective ◽  
Individual Model ◽  
Engineering Sciences ◽  
The Social ◽  
The Individual

AbstractRecently, several research projects in the Netherlands have focused on the development of wearable robotic exoskeletons (WREs) for individuals with Duchenne muscular dystrophy (DMD). Such research on WREs is often treated solely within the disciplines of biomedical and mechanical engineering, overlooking insights from disability studies and philosophy of technology. We argue that mainly two such insights should receive attention: the problematization of the ableism connected to the individual model of disability and the stigmatization by assistive technology. While disability studies have largely rejected the individual model of disability, the engineering sciences seem to still locate disability in an individual’s body, not questioning their own problematization of disability. Additionally, philosophy of technology has argued that technologies are not neutral instruments but shape users’ actions and perceptions. The design of WREs may convey a message about the understanding of disability, which can be comprehended as a challenge and an opportunity: stigmatization needs to be avoided and positive views on disability can be evoked. This article aims to highlight the benefits of considering these socio-philosophical perspectives by examining the case of WREs for people with DMD and proposing design principles for WREs. These principles may enhance acceptability of WREs, not only by individuals with DMD but also by other users, and help engineers to better place their work in the social context.

Some alternatives for the individual model

1994 ◽  
Vol 15 (2-3) ◽  
pp. 127-132 ◽  
Author(s):  
R. Kaas ◽  
H.U. Gerber
Keyword(s):  
Individual Model ◽  
The Individual

Trick or Treat: Does a Microfinance Loan Induce or Reduce the Chances of Spousal Violence against Women? Answers from India

2020 ◽  
pp. 088626052095768
Author(s):  
Debashree Sinha ◽  
Pradeep Kumar
Keyword(s):  
Violence Against Women ◽  
Policy Design ◽  
Positive Impact ◽  
Family Health ◽  
P Value ◽  
Spousal Violence ◽  
Common Belief ◽  
Program Participation ◽  
The Individual

It is a common belief that microfinance plays a dual role of poverty alleviation and socioeconomic upliftment of its women participants. However, there are enough researches that negates the positive impact of microfinance loans on spousal violence. Recognized as one of the most predominant social evils, violence against women is not only a violation of their human rights but also an act of exploitation and denial of freedom. In the present study, we have tried to investigate if microfinance loan takers experience more spousal violence as compared to their counterparts by analyzing the National Family Health Survey IV, 2015–16. Our results indicate that 40.8% of women microfinance participants experience spousal violence. Additionally, the likelihood of microfinance participants to experience spousal violence is much higher than the non-microfinance participants (odds ratio = 1.35, p value = .000). Microfinance programs are designed to increase the individual agencies of women participants, which, in turn, reduce the chances of them becoming victims of spousal violence. However, if the credit program participation induces the woman to be a victim of spousal violence together with becoming financially autonomous, then such hidden costs need to be taken into account while evaluating the effectiveness of the gendered policy design.

scholarly journals Ensemble Forecasts of Air Quality in Eastern China – Part 2. Evaluation of the MarcoPolo-Panda Prediction System, Version 1

2018 ◽  
Author(s):  
Anna Katinka Petersen ◽  
Guy P. Brasseur ◽  
Idir Bouarar ◽  
Johannes Flemming ◽  
Michael Gauss ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Observational Data ◽  
Prediction System ◽  
Model Ensemble ◽  
Individual Model ◽  
Forecasting System ◽  
The Individual ◽  
Pollution Events ◽  
Statistical Indicators

Abstract. An operational multi-model forecasting system for air quality has been developed to provide air quality services for urban areas of China. The initial forecasting system included seven state-of-the-art computational models developed and executed in Europe and China (CHIMERE, IFS, EMEP MSC-W, WRF-Chem-MPIM, WRF-Chem-SMS, LOTOS-EUROS and SILAMtest). Several other models joined the prediction system recently, but are not considered in the present analysis. In addition to the individual models, a simple multi-model ensemble was constructed by deriving statistical quantities such as the median and the mean of the predicted concentrations. The prediction system provides daily forecasts and observational data of surface ozone, nitrogen dioxides and particulate matter for the 37 largest urban agglomerations in China (population higher than 3 million in 2010). These individual forecasts as well as the multi-model ensemble predictions for the next 72 hours are displayed as hourly outputs on a publicly accessible web site (www.marcopolo-panda.eu). In this paper, the performance of the predictions system (individual models and the multi-model ensemble) for the first operational year (April 2016 until June 2017) has been analysed through statistical indicators using the surface observational data reported at Chinese national monitoring stations. This evaluation aims to investigate a) the seasonal behavior, b) the geographical distribution and c) diurnal variations of the ensemble and model skills. Statistical indicators show that the ensemble product usually provides the best performance compared to the individual model forecasts. The ensemble product is robust even if occasionally some individual model results are missing. Overall and in spite of some discrepancies, the air quality forecasting system is well suited for the prediction of air pollution events and has the ability to provide alert warning (binary prediction) of air pollution events if bias corrections are applied to improve the ozone predictions.

COMPARISON OF APPROXIMATIONS FOR COMPOUND POISSON PROCESSES

2015 ◽  
Vol 45 (3) ◽  
pp. 601-637 ◽  
Author(s):  
Raffaello Seri ◽  
Christine Choirat
Keyword(s):  
Random Variable ◽  
Cumulative Distribution ◽  
Claim Amount ◽  
Approximation Methods ◽  
Total Claim Amount ◽  
Aggregate Claim ◽  
Time Period ◽  
Total Claim ◽  
The Difference ◽  
Object Of Study

AbstractIn this paper, we compare the error in several approximation methods for the cumulative aggregate claim distribution customarily used in the collective model of insurance theory. In this model, it is usually supposed that a portfolio is at risk for a time period of length t. The occurrences of the claims are governed by a Poisson process of intensity μ so that the number of claims in [0,t] is a Poisson random variable with parameter λ = μ t. Each single claim is an independent replication of the random variable X, representing the claim severity. The aggregate claim or total claim amount process in [0,t] is represented by the random sum of N independent replications of X, whose cumulative distribution function (cdf) is the object of study. Due to its computational complexity, several approximation methods for this cdf have been proposed. In this paper, we consider 15 approximations put forward in the literature that only use information on the lower order moments of the involved distributions. For each approximation, we consider the difference between the true distribution and the approximating one and we propose to use expansions of this difference related to Edgeworth series to measure their accuracy as λ = μ t diverges to infinity. Using these expansions, several statements concerning the quality of approximations for the distribution of the aggregate claim process can find theoretical support. Other statements can be disproved on the same grounds. Finally, we investigate numerically the accuracy of the proposed formulas.

Travel and Travelers

2010 ◽  
Author(s):  
James Muldoon
Keyword(s):  
Cross Section ◽  
Medieval Literature ◽  
Canterbury Tales ◽  
Common Belief ◽  
China And India ◽  
The Bible ◽  
The World ◽  
English Society ◽  
The Individual ◽  
The Village

There is a common belief that medieval men and women lived their lives within a narrow geographical and psychological space, the village and the neighboring fields for the most part. According to this opinion, it was not until the Renaissance and the voyages of Columbus and those who followed him that Europeans became aware of the wider world around them and shed the blinders that had constrained them for centuries. What makes this opinion so at odds with medieval reality is that one of the most famous and widely read pieces of medieval literature, Chaucer’s Canterbury Tales, deals with the travels of a group of medieval Christians who range from a crusading knight to farm laborers, individuals representing a cross section of the middling levels of 14th-century English society. Merchants, crusaders, missionaries, pilgrims, exiles, and others motivated by simple restless curiosity traveled around Europe, to the edges of the Christian world, and then all the way to China and India and, sailing westward, to North America. Travel and travel imagery also played an important role in Christian life. The Bible begins with the creation of the world, traces the course of God’s involvement with his people over time, and concludes with the end of the world, the ultimate goal of mankind as defined by the Creator. The life of the individual Christian is a pilgrimage within this context, the movement of the soul to union with God, a microcosm of this larger narrative. It is no coincidence that the most famous work of medieval literature, Dante’s Divine Comedy, was cast as a travel tale.

scholarly journals A Functional Approach to Approximations for the Individual Risk Model

2004 ◽  
Vol 34 (2) ◽  
pp. 379-397 ◽  
Author(s):  
Susan M. Pitts
Keyword(s):  
Negative Binomial ◽  
Risk Model ◽  
Order Approximation ◽  
Functional Approach ◽  
Individual Risk ◽  
Claim Amount ◽  
Total Claim Amount ◽  
Total Claim ◽  
Binomial Approximation ◽  
The Individual

A functional approach is taken for the total claim amount distribution for the individual risk model. Various commonly used approximations for this distribution are considered, including the compound Poisson approximation, the compound binomial approximation, the compound negative binomial approximation and the normal approximation. These are shown to arise as zeroth order approximations in the functional set-up. By taking the derivative of the functional that maps the individual claim distributions onto the total claim amount distribution, new first order approximation formulae are obtained as refinements to the existing approximations. For particular choices of input, these new approximations are simple to calculate. Numerical examples, including the well-known Gerber portfolio, are considered. Corresponding approximations for stop-loss premiums are given.

Modeling Disruption Risk in Supply Chain Risk Management

2012 ◽  
Vol 3 (3) ◽  
pp. 15-39 ◽  
Author(s):  
Ragip Ufuk Bilsel ◽  
A. Ravi Ravindran
Keyword(s):  
Risk Management ◽  
Supply Chain ◽  
Individual Component ◽  
Supply Chain Risk Management ◽  
Supply Chain Risk ◽  
Numerical Examples ◽  
Disruption Risk ◽  
The Individual ◽  
Disruption Risks ◽  
Analytical Frameworks

Disruptions have often been ignored in supply chain models due to their infrequency; however, there is evidence that disruptions are among the most significant threats to supply chains. This paper presents analytical methods to model and quantify disruption risks. The methods consist of breaking disruption risks down into four components: impact, occurrence, detectability and recovery. Analytical frameworks to quantify each individual component is provided. Methods to combine the individual components of risk are discussed and illustrated with numerical examples.

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