Value-at-Risk and Models of Dependence in the U.S. Federal Crop Insurance Program

The federal crop insurance program covered more than 110 billion dollars in total liability in 2018. The program consists of policies across a wide range of crops, plans, and locations. Weather and other latent variables induce dependence among components of the portfolio. Computing value-at-risk (VaR) is important because the Standard Reinsurance Agreement (SRA) allows for a portion of the risk to be transferred to the federal government. Further, the international reinsurance industry is extensively involved in risk sharing arrangements with U.S. crop insurers. VaR is an important measure of the risk of an insurance portfolio. In this context, VaR is typically expressed in terms of probable maximum loss (PML) or as a return period, whereby a loss of certain magnitude is expected to return within a given period of time. Determining bounds on VaR is complicated by the non-homogeneous nature of crop insurance portfolios. We consider several different scenarios for the marginal distributions of losses and provide sharp bounds on VaR using a rearrangement algorithm. Our results are related to alternative measures of portfolio risks based on multivariate distribution functions and alternative copula specifications.

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Firm, industry and economic determinants of working capital at risk

International Journal of Financial Engineering ◽

10.1142/s2424786316500316 ◽

2016 ◽

Vol 03 (04) ◽

pp. 1650031 ◽

Cited By ~ 1

Author(s):

Tarek Ibrahim Eldomiaty ◽

Mohamed Hashem Rashwan ◽

Mohamed Bahaa El Din ◽

Waleed Tayel

Keyword(s):

At Risk ◽

Value At Risk ◽

Stock Exchange ◽

Statistical Tests ◽

Working Capital ◽

Short Term ◽

Firm Level ◽

Cash Conversion Cycle ◽

Wide Range ◽

Capital At Risk

Purpose: The objective of this study is to examine the relative contribution of firm-level, industry-level and country level variables to working capital at risk. Working capital at risk is treated as the value at risk for a portfolio of firm’s current assets. As far as short-term liquidity is concerned, working capital at risk, being the maximum amount that a firm may lose at a certain confidence interval, must be the most important part that a firm’s management must focus on. Design/methodology/approach: This study empirically examines the possible associations between wide range of variables and working capital at risk. The sample firms include 143 non-financial firms listed in Egypt stock exchange. The data cover the years 2000–2014. The statistical tests include the fixed and random effects, testing for linearity versus nonlinearity. The least squares dummy variables and discriminant analysis are utilized. The working capital at risk is classified into three levels: low, medium and high. Findings: The general findings of the study show that cash conversion cycle and the leverage are the most significant determinants of working capital at risk. Both determinants have significant influence on the level of volatility of working capital throughout the three categories of working capital at risk. Originality/value: This study offers a new approach that deals with working capital as a portfolio, rather than single ratios, that firm’s management must decrease its volatility (value at risk), therefore, short-term liquidity can be improved significantly. This approach can be considered a financial engineering in terms of monitoring and managing short-term liquidity exposure.

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MULTIVARIATE GEOMETRIC TAIL- AND RANGE-VALUE-AT-RISK

Astin Bulletin ◽

10.1017/asb.2019.31 ◽

2019 ◽

Vol 50 (1) ◽

pp. 265-292

Author(s):

Klaus Herrmann ◽

Marius Hofert ◽

Mélina Mailhot

Keyword(s):

At Risk ◽

Value At Risk ◽

Risk Measures ◽

Distribution Functions ◽

Special Cases ◽

Dimensional Distribution

AbstractA generalization of range-value-at-risk (RVaR) and tail-value-at-risk (TVaR) for d-dimensional distribution functions is introduced. Properties of these new risk measures are studied and illustrated. We provide special cases, applications and a comparison with traditional univariate and multivariate versions of the TVaR and RVaR.

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WEIGHTED COMONOTONIC RISK SHARING UNDER HETEROGENEOUS BELIEFS

Astin Bulletin ◽

10.1017/asb.2020.6 ◽

2020 ◽

Vol 50 (2) ◽

pp. 647-673

Author(s):

Haiyan Liu

Keyword(s):

At Risk ◽

Value At Risk ◽

Risk Sharing ◽

Optimal Allocation ◽

Risk Measures ◽

Risk Measure ◽

Sufficient Conditions ◽

Heterogeneous Beliefs ◽

Optimal Allocations ◽

Necessary And Sufficient

AbstractWe study a weighted comonotonic risk-sharing problem among multiple agents with distortion risk measures under heterogeneous beliefs. The explicit forms of optimal allocations are obtained, which are Pareto-optimal. A necessary and sufficient condition is given to ensure the uniqueness of the optimal allocation, and sufficient conditions are given to obtain an optimal allocation of the form of excess of loss or full insurance. The optimal allocation may satisfy individual rationality depending on the choice of the weight. When the distortion risk measure is value at risk or tail value at risk, an optimal allocation is generally of the excess-of-loss form. The numerical examples suggest that a risk is more likely to be shared among agents with heterogeneous beliefs, and the introduction of the weight enables us to prioritize some agents as part of a group sharing a risk.

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