Top 10 Reasons why Silicon Valley cannot disrupt Wall Street (yet): The Top Ten list of why Silicon Valley cannot Disrupt Wall Street (yet) was published first here in October 2014 Motivation The possibility, heck the inevitability, of Silicon Valley (representing more generally new technology entrants in finance) aiming to disrupt Wall Street (representing generally incumbents) is one of the fascinating memes of our times. Yet while the potential of technology to reshape financial services is not really in question, the manner and timing that this might happen are entirely different stories.
From Open Risk, to all our friends, colleagues, collaborators, users, partners and the general public: May the network be with you in 2016!
Risk Management Skills for the Fintech Era Risk Management Skills for the Fintech Era: Financial services jobs continue being decimated. A recent (as of the initial post date) FT article was a sobering summary of the continuing transformation of the financial sector: 2015 alone has seen more than 10% reduction of the total workforce across large EU/US banks: As main drivers for this true jobs hecatomb are cited higher minimum capital requirements (that depress Return on Equity and hence require lower costs to restore it to investor acceptable levels), low interest rates that erode Profitability Margins, and a generally subdued economic landscape which reduces Volumes.
Seven Heavens of Finance and the Open Risk API: Back-to-basics is not salvation It has become trendy since the financial crisis to be wearing an anti-complexity hat in matters concerning the shape of the financial system. This is an understandable reaction to the entangled constructions that had sprung to existence in the hyper-leveraged markets of the naughty noughties. Yet shifting through the ruminations and proclamations one cannot help but get the impression that there is a sort of denial of the complexity that underlies the real economy.
What Inka quipus teach us about data management: Chances are that your knowledge of ancient Peruvian culture is a bit rusty. Maybe you have some vague high-school memories of an extensive but backward empire that was conquered and then asset-stripped by a handful of Spanish conquistadores. Or maybe your best preserved memory is the excitement of reading von Daniken’s speculations that the Nazca lines are extraterrestrial spaceports. But unless you happened at some point later in life to hear about the work of Prof.
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.
The four stages of social: Homo Staticus The web as we now know it burst first into the open in the early nineties. It certainly did not start among the more socially active classes. It was an invention by and for nerdy CERN physicists, to exchange data about elementary particle experiments. But it wasn’t long before academics figured out additional valuable uses of this technology: You could put your face online, along with a CV.
The mystery of the collapsed cathedral: You walk to the center of an old city and you see its glorious cathedral lying in ruins. What in the world has happened here? Your investigative instinct goes into overdrive. This is not supposed to happen. Not in peacetime anyway. How can it be that this magnificent edifice, after gracing the town’s central square for who knows how many centuries, is now little more than a rubble pile in the center of town?
Securitisation versus Banking: The ever elusive CMU dream There is(/was) renewed interest in EU-land over deepening a capital markets union, aka CMU. It is among the initiatives being pursued by the Commission in order to help accelerate growth in the European Union. The initiative encompasses many elements, both around equity (shares) and debt markets. One important pillar of the CMU aims to re-launch some version of an EU securitisation market. This segment was never really defined in a EU-wide basis.
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.
In our personal lives, it is the balance between work and life, or the dreadful weight balance. In the professional sphere it might be the balance between debt and equity in the financial industry, or the balance between convenience and citizen privacy in the new tech industry, or the welfare of the many balanced against the property of the few, or finally the geopolitical balance of power of different peoples Balance ensures sustainability as it helps steer away from the risks that lurk at the extremes.
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.