scholarly journals Long-term stochastic risk models: the sixth generation of modern actuarial models?

2021 ◽  
Vol 26 ◽  
Keyword(s):  
Risk Models ◽  
Sixth Generation ◽  
Stochastic Risk

scholarly journals Long-term stochastic risk models: the sixth generation of modern actuarial models?

2021 ◽  
Vol 26 ◽  
Author(s):  
Bill Curry
Keyword(s):  
Risk Management ◽  
Value At Risk ◽  
Risk Model ◽  
Simulation Models ◽  
Life Insurers ◽  
Sixth Generation ◽  
Actuarial Risk ◽  
The Uk ◽  
Stochastic Risk

Abstract This paper discusses the use of modelling techniques for the purpose of risk management within life insurers. The key theme of the paper is that life insurance is long-term business and carries with it long-term risks, yet much of modern actuarial risk management is focussed on short-term modelling approaches. These typically include the use of copula simulation models within a 1-year Value-at-Risk (VaR) framework. The paper discusses the limitations inherent within the techniques currently used in the UK and discusses how the focus of the next generation of actuarial models may be on long-term stochastic projections. The scope of the paper includes a discussion of how existing techniques, together with new approaches, may be used to develop such models and the benefits this can bring. The paper concludes with a practical example of how a long-term stochastic risk model may be implemented.

scholarly journals Long‐Term Post‐CABG Survival: Performance of Clinical Risk Models Versus Actuarial Predictions

2015 ◽  
Vol 31 (1) ◽  
pp. 23-30 ◽  
Author(s):  
Brendan M. Carr ◽  
Jamie Romeiser ◽  
Joyce Ruan ◽  
Sandeep Gupta ◽  
Frank C. Seifert ◽  
...  
Keyword(s):  
Risk Models ◽  
Clinical Risk

scholarly journals UAV cooperative control with stochastic risk models

2011 ◽  
Author(s):  
Alborz Geramifard ◽  
Joshua Redding ◽  
Nicholas Roy ◽  
Jonathan P. How
Keyword(s):  
Cooperative Control ◽  
Risk Models ◽  
Stochastic Risk

scholarly journals Long-term risk of sudden cardiac death in hypertrophic cardiomyopathy - a cardiac magnetic resonance outcome study

2021 ◽  
Vol 22 (Supplement_1) ◽  
Author(s):  
A Seitz ◽  
S Greulich ◽  
D Herter ◽  
F Guenther ◽  
S Probst ◽  
...  
Keyword(s):  
Risk Factors ◽  
Cardiac Magnetic Resonance ◽  
Hypertrophic Cardiomyopathy ◽  
Risk Stratification ◽  
Cardiac Death ◽  
Risk Models ◽  
Lv Mass ◽  
Lge Cmr

Abstract Funding Acknowledgements Type of funding sources: Foundation. Main funding source(s): Robert Bosch Stiftung; Deutsche Forschungsgemeinschaft Background Sudden cardiac death (SCD) is an appalling complication of hypertrophic cardiomyopathy (HCM). There is an ongoing discussion about the optimal SCD risk stratification strategy in HCM since established SCD risk models have suboptimal discriminative power. Objective To evaluate the prognostic value of late gadolinium enhancement (LGE) cardiac magnetic resonance (CMR) for SCD risk stratification compared to the ESC SCD risk score and traditional SCD risk factors in an >10-year follow-up study. Methods 220 consecutive patients with HCM and LGE-CMR were enrolled. Follow-up data was available in 203 patients (median age 58 years, 61% male) after a median follow-up period of 10.4 years. Results LGE was present in 70% of patients with a median LGE amount of 1.6%, the median ESC 5-year SCD risk score was 1.84. In the overall cohort, SCD rates were 2.3% at 5 years, 4.8% at 10 years, and 15.7% at 15 years, independent from established risk models. A LGE amount of >5% (LV mass) portends the highest risk for SCD with SCD prevalences of 5.5% at 5 years, 13.0% at 10 years and 33.3% at 15 years. Conversely, patients with no or ≤5% LGE amount (of LV mass) have favorable prognosis. Conclusions LGE-CMR in HCM patients allows effective 10-year SCD risk stratification beyond established risk factors. LGE amount might be added to established risk models to improve its discriminatory power. Specifically, patients with >5% amount of LGE should be carefully monitored and might be adequate candidates for primary prevention ICD during the clinical long-term course. Abstract Figure.

Extrapolation Bias and Robust Dynamic Liquidity Management

2021 ◽  
Author(s):  
Seokwoo Lee ◽  
Alejandro Rivera
Keyword(s):  
Cash Flow ◽  
Ambiguity Aversion ◽  
Cash Flows ◽  
Risk Models ◽  
Worst Case ◽  
Liquidity Management ◽  
Optimal Dynamic ◽  
Cash Flow Volatility ◽  
Future Cash Flows

We consider the optimal dynamic liquidity management of a financially constrained firm when its existing shareholders are risk neutral but ambiguity averse with respect to the firm’s future cash flows. The shareholders’ ambiguity aversion generates endogenous time-varying worst-case beliefs that overweight recent cash flow realizations, thereby providing a microeconomic foundation for extrapolation bias. Moreover, shareholders’ ambiguity aversion has different implications on firms’ liquidity management and recapitalization policies than risk. Models with risk alone imply that higher cash flow volatility increases firms’ payout and refinancing thresholds. By contrast, our model predicts that, when ambiguity-averse shareholders face a higher long-term cash flow uncertainty, they optimally reduce firms’ payout and refinancing thresholds. The implications for investment are also studied. This paper was accepted by Agostino Capponi, finance.

scholarly journals Genetic Barcodes for Improved Environmental Tracking of an Anthrax Simulant

2012 ◽  
Vol 78 (23) ◽  
pp. 8272-8280 ◽  
Author(s):  
Patricia Buckley ◽  
Bryan Rivers ◽  
Sarah Katoski ◽  
Michael H. Kim ◽  
F. Joseph Kragl ◽  
...  
Keyword(s):  
Environmental Fate ◽  
Wild Type ◽  
Risk Models ◽  
Content Type ◽  
Genetic Signatures ◽  
Isogenic Strains ◽  
Type Strains ◽  
Long Term Studies

ABSTRACTThe development of realistic risk models that predict the dissemination, dispersion and persistence of potential biothreat agents have utilized nonpathogenic surrogate organisms such asBacillus atrophaeussubsp.globigiior commercial products such asBacillus thuringiensissubsp.kurstaki. Comparison of results from outdoor tests under different conditions requires the use of genetically identical strains; however, the requirement for isogenic strains limits the ability to compare other desirable properties, such as the behavior in the environment of the same strain prepared using different methods. Finally, current methods do not allow long-term studies of persistence or reaerosolization in test sites where simulants are heavily used or in areas whereB. thuringiensissubsp.kurstakiis applied as a biopesticide. To create a set of genetically heterogeneous yet phenotypically indistinguishable strains so that variables intrinsic to simulations (e.g., sample preparation) can be varied and the strains can be tested under otherwise identical conditions, we have developed a strategy of introducing small genetic signatures (“barcodes”) into neutral regions of the genome. The barcodes are stable over 300 generations and do not impactin vitrogrowth or sporulation. Each barcode contains common and specific tags that allow differentiation of marked strains from wild-type strains and from each other. Each tag is paired with specific real-time PCR assays that facilitate discrimination of barcoded strains from wild-type strains and from each other. These uniquely barcoded strains will be valuable tools for research into the environmental fate of released organisms by providing specific artificial detection signatures.

scholarly journals Validation of Eurolung risk models in a Japanese population: a retrospective single-centre analysis of 612 cases

2019 ◽  
Vol 29 (5) ◽  
pp. 722-728 ◽  
Author(s):  
Akihiro Nagoya ◽  
Ryu Kanzaki ◽  
Takashi Kanou ◽  
Naoko Ose ◽  
Soichiro Funaki ◽  
...  
Keyword(s):  
Overall Survival ◽  
Mortality Rate ◽  
Japanese Population ◽  
Multivariable Analysis ◽  
Morbidity And Mortality ◽  
Risk Scores ◽  
Long Term Outcomes ◽  
Risk Models ◽  
Aggregate Risk

Abstract OBJECTIVES The objective of this study was to evaluate the validity of Eurolung risk models in a Japanese population and assess their utility as predictive indicators for the prognosis. METHODS Between 2007 and 2014, 612 anatomic lung resections were performed among 694 lung cancer patients in our institution. We analysed the cardiopulmonary morbidity and mortality and compared them with the predicted results. We also investigated the association between the Eurolung aggregate risk scores and the long-term outcomes using the Kaplan–Meier method and a multivariable analysis. RESULTS The percentage of cardiopulmonary complications was lower than that predicted by Eurolung 1 (22.4% vs 24.6%). The mortality rate was significantly lower than predicted by Eurolung 2 (0.7% vs 3.0%). The morbidity rate was stratified by Aggregate Eurolung 1. The stratification of the mortality rate by the Eurolung 2 aggregate score was also in line with the increase in score, although the observed number of deaths was quite small (4 cases). The 5-year overall survival was clearly separated according to the stratified Aggregate Eurolung 1 and 2 (P < 0.01 and P < 0.01, respectively). Besides pathological stage, both the Aggregate Eurolung 1 (score 0–7 vs 8–20) and 2 (score 0–8 vs 9–19) scores were shown to be independently associated with overall survival on multivariable. CONCLUSIONS Eurolung risk models cannot be directly applied to the patients in our institution. However, Eurolung aggregate risk scores were helpful not only for stratifying morbidity and mortality after anatomic lung resection but also for predicting the long-term outcomes.

scholarly journals Managing Customer Credit to Reduce the Company's Risk and Overdue Credits

2019 ◽  
pp. 561-585
Author(s):  
Inês Lisboa ◽  
Teresa Costa ◽  
Nuno Teixeira
Keyword(s):  
Credit Risk ◽  
Credit Policy ◽  
Risk Models ◽  
Recovery Method ◽  
Pros And Cons ◽  
A Company

Most companies give credit to customers when selling products or providing services. It has advantages as more customers may be willing to negotiate with the company, but it increases the company's risk. Therefore, the company must analyze the pros and cons of giving credit. This chapter summarizes all information needed for a company to establish credit policy for each customer or group of customers. First, credit risk and customers' credit risk are explained to call the attention to the need to manage it. Then it shows how a company can manage credit to maximize its value and reduce its risk. The inputs needed to determine a customer credit policy are explained. Credit risk models are presented. And finally, a recovery method to collect overdue credits is presented. This chapter aims the help the company to solve liquidity and solvency problems and to stablish long-term relationships with customers.

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