scholarly journals GCPM: A ?exible package to explore credit portfolio risk

2016 ◽  
Vol 45 (1) ◽  
pp. 25-44 ◽  
Author(s):  
Kevin Jakob ◽  
Matthias Fischer
Keyword(s):  
Sensitivity Analysis ◽  
Banking Industry ◽  
The Novel ◽  
Portfolio Risk ◽  
Model Framework ◽  
Model Risk ◽  
General Importance ◽  
Speed Up ◽  
Credit Portfolio ◽  
Credit Portfolio Model

In this article we introduce the novel GCPM package, which represents a generalized credit portfolio model framework. The package includes two of the most popular mod- eling approaches in the banking industry namely the CreditRisk+ and the CreditMetrics model and allows to perform several sensitivity analysis with respect to distributional or functional assumptions. Therefore, besides the pure quanti?cation of credit portfolio risk, the package can be used to explore certain aspects of model risk individually for every arbitrary credit portfolio. In order to guarantee maximum ?exibility, most of the models utilize a Monte Carlo simulation, which is implemented in C++, to achieve the loss dis- tribution. Furthermore, the package also o?ers the possibilities to apply simple pooling techniques to speed up calculations for large portfolios as well as a general importance sample approach. The article concludes with a comprehensive example demonstrating the ?exibility of the package.

scholarly journals Quantifying the impact of different copulas in a generalized CreditRisk+ framework An empirical study

2014 ◽  
Vol 2 ◽  
pp. 1-21 ◽  
Author(s):  
Kevin Jakob ◽  
Matthias Fischer
Keyword(s):  
Empirical Study ◽  
Banking Industry ◽  
Economic Capital ◽  
Regulatory Requirements ◽  
Economic Sectors ◽  
Loan Portfolio ◽  
Credit Portfolio ◽  
The Impact ◽  
Credit Losses ◽  
Credit Portfolio Model

AbstractWithout any doubt, credit risk is one of the most important risk types in the classical banking industry. Consequently, banks are required by supervisory audits to allocate economic capital to cover unexpected future credit losses. Typically, the amount of economical capital is determined with a credit portfolio model, e.g. using the popular CreditRisk+ framework (1997) or one of its recent generalizations (e.g. [8] or [15]). Relying on specific distributional assumptions, the credit loss distribution of the CreditRisk+ class can be determined analytically and in real time. With respect to the current regulatory requirements (see, e.g. [4, p. 9-16] or [2]), banks are also required to quantify how sensitive their models (and the resulting risk figures) are if fundamental assumptions are modified. Against this background, we focus on the impact of different dependence structures (between the counterparties of the bank’s portfolio) within a (generalized) CreditRisk+ framework which can be represented in terms of copulas. Concretely, we present some results on the unknown (implicit) copula of generalized CreditRisk+ models and quantify the effect of the choice of the copula (between economic sectors) on the risk figures for a hypothetical loan portfolio and a variety of parametric copulas.

Analysis of credit portfolio risk using hierarchical multifactor models

2014 ◽  
Vol 10 (4) ◽  
pp. 45-70 ◽  
Author(s):  
Pak-Wing Fok ◽  
Xiuling Yan ◽  
Guangming Yao
Keyword(s):  
Portfolio Risk ◽  
Multifactor Models ◽  
Credit Portfolio

scholarly journals Experimental Study on the Insulation Layer Thickness of a Novel Ice Coring Device in Loose Sandstone-Type Uranium Deposits

Energies ◽  
2021 ◽  
Vol 14 (21) ◽  
pp. 7448
Author(s):  
Chaoyang Huang ◽  
Jianming Peng ◽  
Yanliang Li ◽  
Moke Lian ◽  
Chao Guo ◽  
...  
Keyword(s):  
Laboratory Experiments ◽  
High Reliability ◽  
Freezing Process ◽  
The Novel ◽  
Uranium Deposits ◽  
Insulation Layer ◽  
Cold Source ◽  
Cold Energy ◽  
Speed Up ◽  
Drill Tool

The target strata of sandstone-type uranium deposits are usually located in the fragile and loose strata, which makes it difficult to obtain core samples; consequently, a novel ice coring device for loose sandstone-type uranium deposits is proposed to solve this problem. Experiments proved that the artificial sample can replace the natural sample, and the coring method has high reliability. Ensuring the allegro formation of an ice valve with a given cold source is critical for this coring system, and reducing the loss of cold energy with help of insulation layer is one of the methods to speed up the formation of ice valve. Since the diameter of the drill tool is limited by its working scenario, the thickness of insulation layer is limited to ensure the size of core. Therefore, this paper conducted laboratory experiments of the insulation layer with different thicknesses to study the effect of the insulation layer on the formation of the sand–ice valve. Results show that the insulation layer can reduce the loss of cold energy during the freezing process and significantly affect the formation time of the sand–ice valve. When the thickness of the aerogel insulation layer is 2 mm, the freezing time is 44% shorter than that without insulation layer. According to the tests, the novel ice coring device is expected to solve the coring problem in loose sandstone-type uranium deposits.

scholarly journals Analysis of Different Pressure Thermally Coupled Extractive Distillation Column

2014 ◽  
Vol 8 (1) ◽  
pp. 12-18 ◽  
Author(s):  
Lanyi Sun ◽  
Kang He ◽  
Yuliang Liu ◽  
Qiuyuan Wang ◽  
Dingding Wang
Keyword(s):  
Sensitivity Analysis ◽  
Distillation Column ◽  
Extractive Distillation ◽  
Total Annual Cost ◽  
Operating Parameters ◽  
The Novel ◽  
Economic Aspects ◽  
Distillation Process ◽  
Aqueous Acetonitrile ◽  
New Process

In this contribution, a different pressure thermally coupled extractive distillation process has been applied on the separation of propylene and propane with aqueous acetonitrile (ACN) solution as entrainer. The novel distillation pro-cess integration is the combination of different pressure thermally coupled distillation (DPTCD) and extractive distillation (ED). Both the new process and the conventional process have been simulated in Aspen Plus. Sensitivity analysis has been conducted to select an appropriate compression ratio and other operating parameters based on the priority that the propylene product purity is 99.2 wt % and less energy consumption. The influence of the proposed distillation column on energetic and economic aspects is evaluated through intensive comparison against the conventional stand-alone column, and better performance is achieved with up to 46.02% energy saving and close to 9.7% saving in total annual cost (TAC).

scholarly journals Deep Reinforcement Learning Approach with Multiple Experience Pools for UAV’s Autonomous Motion Planning in Complex Unknown Environments

Sensors ◽  
2020 ◽  
Vol 20 (7) ◽  
pp. 1890 ◽  
Author(s):  
Zijian Hu ◽  
Kaifang Wan ◽  
Xiaoguang Gao ◽  
Yiwei Zhai ◽  
Qianglong Wang
Keyword(s):  
Reinforcement Learning ◽  
Motion Planning ◽  
Predictive Control ◽  
Experimental Testing ◽  
The Novel ◽  
Simulation Environment ◽  
Unknown Environments ◽  
Autonomous Motion ◽  
Policy Gradient ◽  
Speed Up

Autonomous motion planning (AMP) of unmanned aerial vehicles (UAVs) is aimed at enabling a UAV to safely fly to the target without human intervention. Recently, several emerging deep reinforcement learning (DRL) methods have been employed to address the AMP problem in some simplified environments, and these methods have yielded good results. This paper proposes a multiple experience pools (MEPs) framework leveraging human expert experiences for DRL to speed up the learning process. Based on the deep deterministic policy gradient (DDPG) algorithm, a MEP–DDPG algorithm was designed using model predictive control and simulated annealing to generate expert experiences. On applying this algorithm to a complex unknown simulation environment constructed based on the parameters of the real UAV, the training experiment results showed that the novel DRL algorithm resulted in a performance improvement exceeding 20% as compared with the state-of-the-art DDPG. The results of the experimental testing indicate that UAVs trained using MEP–DDPG can stably complete a variety of tasks in complex, unknown environments.

Credit Portfolio Risk and Diversification

2013 ◽  
pp. 153-170
Author(s):  
Rudi Schäfer ◽  
Alexander F. R. Koivusalo ◽  
Thomas Guhr
Keyword(s):  
Portfolio Risk ◽  
Credit Portfolio

scholarly journals Investigating Mortality Uncertainty Using the Block Bootstrap

2010 ◽  
Vol 2010 ◽  
pp. 1-15 ◽  
Author(s):  
Xiaoming Liu ◽  
W. John Braun
Keyword(s):  
Life Expectancy ◽  
Mortality Risk ◽  
Spatial Dependence ◽  
Bootstrap Method ◽  
Prediction Intervals ◽  
Block Bootstrap ◽  
Model Framework ◽  
Model Risk ◽  
Process Risk ◽  
Carter Model

This paper proposes a block bootstrap method for measuring mortality risk under the Lee-Carter model framework. In order to take account of all sources of risk (the process risk, the parameter risk, and the model risk) properly, a block bootstrap is needed to cope with the spatial dependence found in the residuals. As a result, the prediction intervals we obtain for life expectancy are more accurate than the ones obtained from other similar methods.

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