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Integrated Risk Management: Risk Aggregation and Allocation Using Intelligent Systems
Company: Computational Methods in Financial Engineering
Company Url: Click here to open
Year Of Publication: 2008
Month Of Publication: January
Resource Link: Click here to open
Pages: 317-342
Download Count: 0
View Count: 1760
Comment Num: 0
Language: English
Source: book chapter
Who Can Read: Free
Date: 12-31-2013
Publisher: Administrator
In this contribution an application of intelligent systems that provides management with risk-return efficient bank-wide asset allocation strategies is outlined. It is based on multi-objective evolutionary algorithms and considers different market risks and credit risk as well as position volume constraints. The presented novel approach is not only able to integrate the differing goals concerning the risk management function but also to partly overcome the obstacles for risk integration and aggregation. Using real market data a sample portfolio analysis is performed and possible conclusions for a bank risk manager are drawn. The approach is extendable concerning for instance advanced risk measurement methodologies, correlation assumptions, different time horizons and additional risk types. Further real-world constraints, such as regulatory capital, portfolio or P&L restrictions can also be easily integrated into the model.
Mitschele, Andreas Sign in to follow this author
Schlottmann, Frank Sign in to follow this author
Seese, Detlef Sign in to follow this author
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