Risk modeling is as much art as it is science: The Zen of Modeling aims to capture the struggle for risk modeling beauty An undocumented risk model is only a computer program A risk model that cannot be programmed is only a concept A risk model only comes to life with empirical validation Correct implementation of an imperfect model is better than wrong implementation of a perfect model In complex systems there is always more than one path to a risk model There are no persistently true models but there are many persistently wrong models Correlation is imperfectly correlated with causation Nirvana is the simplest model that is fit for purpose Hierarchical systems lead to hierarchical models.
A mini course on risk management, its perils and the silver lining: When talking about risk management, it is not very clear what we are talking about in broad terms, definitely not getting clearer when we start getting into the details and it is even not clear how to best use the (possibly flawed) insights we produce. Yet that’s what we have at this stage and with lemons we do lemonade.
Criteria for identifying simple, transparent and comparable securitisations: (See BIS D304) Our view is that securitisation is fundamental financial technology and there is no intrinsic technical reason why it could not be harnessed to best serve the functioning of modern economies. We believe, though, that a comprehensive overhaul of historical securitisation practices is the best means of addressing the stigma that has been attached to it in the follow up to the recent financial crisis.
Open Source Risk Modeling Manifesto: This post is a summary of a presentation given at the 2014 Autumn TopQuants Meeting, aka, the Open Source Risk Modeling Manifesto. The dismal state of quantitative risk modeling The current framework of internal risk modeling at financial institutions has had a fatal triple stroke. We saw in quick sequence: market risk, operational risk, and credit risk measurement failures, covering practically all business models. This fact left the science and art of quantitative risk modeling reeling under the crushing weight of empirical evidence.
Financial Risk Modelling has suffered enormous setbacks in recent years, with all major strands of modelling (market, credit, operational risk) proven to have debilitating limitations. It is impossible to imagine a modern financial system that does not make extensive use of risk quantification tools, yet rebuilding confidence that these tools are fit-for-purpose will require significant changes. These need to improve governance, transparency, quality standards and in some areas even the development of completely new strands of modelling.
We are happy to publish the first installment of a trilogy that focuses on the risk factors that can turn any credit portfolio toxic. The first topic is default correlation, a topic that is both core to understanding credit risk and much misunderstood. Enjoy!
The rationale for continuing with internal capital models in the Basel 3 world: Overview of the challenges and opportunities offered by internal capital models (economic capital models) in the post-crisis era. Conference Presentation given at: Venue: 2nd Annual Capital Modelling under Basel III (Marcus Evans Conference) Location: London Time: January 28th 2014 Link to presentation: Local file
A python module of analytic solutions suitable for testing credit portfolio models has been uploaded in the Open Risk github repository