Physicist Mark Buchanan is a former editor at Nature and New Scientist, and is the author of
numerous magazine and newspaper articles published internationally for publications ranging from the New York Times to the Harvard Business Review. He currently writes monthly columns for the financial media outlet Bloomberg View,
as well as for Nature Physics. He has written two prize-nominated non-fiction books, Ubiquity: The Science of History and Nexus: Small Worlds and the Groundbreaking Science of Networks. His most recent book is The Social Atom. In 2009, he received the LaGrange Prize for writing on issues in complexity science. Buchanan also writes a blog, The Physics of Finance, exploring the application of physics-inspired thinking to the understanding of financial systems. His forthcoming book Forecast: What
Extreme Weather Can Teach Us About Economics will be published in the UK by Bloomsbury Press in April 2013.
Here is Mark’s latest Bloomber column:
“Economists teach us that a financial market is a powerful technology for processing information. It brings everyone’s knowledge and greed into play, devouring every available scrap of information to achieve optimal risk-sharing and put resources to the best possible use. That’s the theory. In practice, things often don’t work that way. The 2008 financial crisis demonstrated that the information processor, confounded by hyper-complex securities and specious AAA ratings, can easily misallocate resources and ultimately grind to an inglorious halt. When a technology fails, we naturally look for a fix. If markets don’t digest information very well, we ought to ask why, and whether some re-engineering could help them do better. The idea that a little central planning might help markets will undoubtedly perturb free-market puritans, but it may be just what we need. Let’s start with a simple observation: The overwhelming complexity of today’s markets renders banks unable to judge risks as rationally as standard theories of finance assume they do. The health of any decent-sized financial institution depends on a vast web of links to other institutions that even the most sophisticated risk manager cannot hope to penetrate. To make things specific, consider the interbank lending market, which played a leading role in the financial meltdown of 2007 and 2008. Banks use the market to manage demands for cash by shuttling funds among themselves, often overnight. If bank A wants to judge the risk of lending to bank B, it’s not enough to look at its assets and liabilities. If bank B has loans outstanding to banks C and D, its creditworthiness depends on the state of those banks, too, which in turn depends on that of other banks to which they’ve made loans. Given the rich network interdependence, bank A can’t possibly gather enough information to judge bank B or any other. Amid this complexity, how can we hope to get a market that functions? Two European physicists, Stefan Thurner and Sebastian Poledna, offer a bold idea: Use computing technology to achieve a radical transformation of banking transparency, turning information into a public resource and making it much harder for banks to hide risks. Here’s how it would work for the interbank market. Developed-nation regulators, such as the U.S. Federal Reserve and the European Central Bank, have access to fairly complete information on who has loaned how much to whom — just what is needed to shed light on the broader network. They would use these data to calculate a measure of risk called DebtRank, which captures the intuitive idea that the most risky banks are those that have lots of links to other risky banks. Banks connected to more banks with high DebtRank scores would naturally have higher DebtRank scores themselves (see my previous article on the subject). If the regulators made the results public, then anyone would, at a glance, gain a much more accurate view of the true risks associated with any bank. The second step would involve using the risk assessments to rearrange incentives. The financial system as a whole would be better off if banks seeking to borrow funds did so from the least risky banks. To achieve this, regulators could require borrowers to favor lenders with the lowest DebtRank scores. The system would punish banks that take on too much risk by constraining their lending, and would inhibit the emergence of any single counterparty risky enough to threaten the entire system (see my blog for further detail). Speculative as the idea might seem, it deserves attention. In preliminary studies using computer simulations, Thurner and Poledna found that the simple changes would reduce the chance of widespread banking crises while improving the efficiency of the interbank lending network. The approach could easily be generalized to include reporting on links established by credit default swaps and other derivatives, and perhaps could be extended to markets more generally as well. The beauty of the idea is that it introduces strong incentives for banks to reduce their systemic risk. Of course, such an unorthodox solution will almost certainly draw the criticism of banks and other market participants who profit precisely from taking on big risks and hiding those risks from others. But for the rest of us, and for the economy at large, the added transparency would only bring benefits, and might help the market live up to its reputation as a powerful processor of information.”