scholarly journals Predicting the Stressed Expected Loss of Large U.S. Banks

2021 ◽  
pp. 106321
Author(s):  
Eric Jondeau ◽  
Amir Khalilzadeh
Keyword(s):  
Expected Loss

The Measurement of Performance in Probabilistic Diagnosis IV. Utility Considerations in Therapeutics and Prognostics

1981 ◽  
Vol 20 (02) ◽  
pp. 80-96 ◽  
Author(s):  
J. D. F. Habbema ◽  
J. Hilden
Keyword(s):  
Decision Theory ◽  
Figure Of Merit ◽  
Acute Abdominal Pain ◽  
Theory Approach ◽  
Expected Loss ◽  
Patient Benefit ◽  
Evaluation Approach ◽  
Average Loss ◽  
Actual Decision ◽  
Probabilistic Diagnosis

It is argued that it is preferable to evaluate probabilistic diagnosis systems in terms of utility (patient benefit) or loss (negative benefit). We have adopted the provisional strategy of scoring performance as if the system were the actual decision-maker (not just an aid to him) and argue that a rational figure of merit is given by the average loss which patients would incur by having the system decide on treatment, the treatment being selected according to the minimum expected loss principle of decision theory.A similar approach is taken to the problem of evaluating probabilistic prognoses, but the fundamental differences between treatment selection skill and prognostic skill and their implications for the assessment of such skills are stressed. The necessary elements of decision theory are explained by means of simple examples mainly taken from the acute abdomen, and the proposed evaluation tools are applied to Acute Abdominal Pain data analysed in our previous papers by other (not decision-theoretic) means. The main difficulty of the decision theory approach, viz. that of obtaining good medical utility values upon which the analysis can be based, receives due attention, and the evaluation approach is extended to cover more realistic situations in which utility or loss values vary from patient to patient.

Reliability and expected loss: A unifying principle

Psychometrika ◽  
1994 ◽  
Vol 59 (2) ◽  
pp. 203-216 ◽  
Author(s):  
Bruce Cooil ◽  
Roland T. Rust
Keyword(s):  
Expected Loss

scholarly journals Bayes Estimation of a Two-Parameter Geometric Distribution under Multiply Type II Censoring

2011 ◽  
Vol 2011 ◽  
pp. 1-10
Author(s):  
J. B. Shah ◽  
M. N. Patel
Keyword(s):  
Geometric Distribution ◽  
Correct Choice ◽  
Bayes Estimation ◽  
Loss Functions ◽  
Type Ii ◽  
Expected Loss ◽  
Bayes Estimators ◽  
Linex Loss ◽  
Type Ii Censored Data ◽  
Two Parameter

We derive Bayes estimators of reliability and the parameters of a two- parameter geometric distribution under the general entropy loss, minimum expected loss and linex loss, functions for a noninformative as well as beta prior from multiply Type II censored data. We have studied the robustness of the estimators using simulation and we observed that the Bayes estimators of reliability and the parameters of a two-parameter geometric distribution under all the above loss functions appear to be robust with respect to the correct choice of the hyperparameters a(b) and a wrong choice of the prior parameters b(a) of the beta prior.

scholarly journals Strategi Optimasi Sistem Manajemen Risiko Pembiayaan pada Bank Jabar Banten Syariah

2015 ◽  
Vol 10 (2) ◽  
pp. 143-150
Author(s):  
Adnan Sharif ◽  
Abdul Kohar Irwanto ◽  
Tubagus Nur Ahmad Maulana
Keyword(s):  
Analytical Hierarchy Process ◽  
Swot Analysis ◽  
Risk Mitigation ◽  
Risk Level ◽  
Expected Loss ◽  
Financing Risk ◽  
Strategic Policy ◽  
Productive Asset ◽  
Industry Sectors ◽  
Hierarchy Process

One of the success indicator for the bank into manage their financing risk is a Non Performing Financing (NPF) level. On the last three years, BJB Syariah’s NPF trend keep increased, then be required a research to find out profile and financing risk level that be faced by BJB Syariah. This research has some objective to: (1) Analyzing of financing risk level that be faced by BJB Syariah and (2) Analyzing, reviewing of management such as mitigation program for financing risk that be faced by BJB Syariah. To analyzing financing risk level has been used CreditRisk+ model, meanwhile to reviewing management and financing risk mitigation has been used internal and external analysis, SWOT analysis (Strengths, Weaknesses, Opportunities and Threats) and AHP (Analytical Hierarchy Process). The result from this research is profile and financing risk level of BJB Syariah still quite fit. This matter looks from expected loss period 2012-2014 still can be covered by reserved productive asset that has been done by BJB Syariah. Strategy that needed to be performed as follows enhancement director act to make a financing strategic policy such as financing portfolio spread for industry sectors that has fit prospect, making feasibility valuation for new debtor with more prudent and right on target also strengthen character valuation for new debtor using credit bureau until scorecard method

Budget allocation decisions for project risk response

Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yao Zhang ◽  
Xin Guan
Keyword(s):  
Optimization Model ◽  
Fault Tree ◽  
Critical Issue ◽  
Inadequate Response ◽  
Expected Loss ◽  
Project Risk ◽  
Content Type ◽  
Risk Response ◽  
Total Budget ◽  
Risk Protection

Purpose The purpose of this paper is to propose a method integrating fault tree analysis and optimization model to allocate response budget from the preventive and protective perspectives. Design/methodology/approach The proposed method consists of two main steps. The first step is to analyze and calculate the probability and the loss of the risk. The second step is to build an optimization model for allocating response budget. Findings First, there exists an optimal response budget. Second, risk protection is preferred to risk prevention when the total budget is limited. Third, the protective budget should be first invested for the consequence event with greatest expected loss. Fourth, the preventive budget should be first allocated to the risk cause with highest occurrence probability that belongs to the OR set in the fault tree. Practical implications Managerially, our results indicate that project managers (PMs) should make a tradeoff between the budget invested for risk response and reduced expected loss of the risk. Then, in the case of inadequate response budget, PMs should pay more attention to risk protection and cope with the event that can cause severe loss. In addition, under this circumstance, PMs had to better allocate the risk preventive budget in proper order. Originality/value Project risk response is a critical issue in project risk management as PMs can take actions actively to cope with project risks in this phase. Effective risk response, in general, requires financial support in practice, and reasonable allocation of the total budget among risk response strategies can produce better response effects.

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