Decomposing Dynamic Risks into Risk Components

2020 ◽  
Vol 66 (12) ◽  
pp. 5738-5756
Author(s):  
Katja Schilling ◽  
Daniel Bauer ◽  
Marcus C. Christiansen ◽  
Alexander Kling

The decomposition of dynamic risks a company faces into components associated with various sources of risk, such as financial risks, aggregate economic risks, or industry-specific risk drivers, is of significant relevance in view of risk management and product design, particularly in (life) insurance. Nevertheless, although several decomposition approaches have been proposed, no systematic analysis is available. This paper closes this gap in literature by introducing properties for meaningful risk decompositions and demonstrating that proposed approaches violate at least one of these properties. As an alternative, we propose a novel martingale representation theorem (MRT) decomposition that relies on martingale representation and show that it satisfies all of the properties. We discuss its calculation and present detailed examples illustrating its applicability. This paper was accepted by Baris Ata, stochastic models and simulation.

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Isaac Akomea-Frimpong ◽  
Xiaohua Jin ◽  
Robert Osei-Kyei

PurposeGlobally, the management of financial risks has gained much attention in the public–private partnerships (PPP) market in recent years. Existing studies rank financial risks among the topmost risk factors that determine the success or failure of a PPP project. As essential for managing financial risks, a systematic review of previous studies on financial risk management of PPP from 1995 to 2019 (inclusive of both years) has been presented in this paper.Design/methodology/approachThe paper undertakes a systematic analysis of 49 relevant and available studies on financial risk management of PPP projects.FindingsFrom the results, high-interest charges, increased construction costs and increased market risks are some of the key financial risks hampering the success of PPP projects. Techniques used to assess financial risks include Monte Carlo Simulation (MCS) and Net Present Value (NPV). Financial risks control adopted by project managers include minimum revenue guarantee and real option pricing. Extremely limited studies on financial risk management in PPP projects in developing economies was revealed.Practical implicationsProject managers in developing financial risk management models may use the outcome of this paper to improve the financial success of PPP projects. Holistically, researchers will be guided to investigate and heighten the pertinent issues on financial risk management of PPP projects in academia.Originality/valueThe results provide a rare guide to project managers in controlling financial risks of PPP projects which is an unexplored topic. It is also the first paper to highlight the issues of financial risk management in PPP projects research.


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