The need for simple financial regulations

As argued previously (here and there), financial sectors need simple regulations, not more complicated ones. This is being voiced more frequently than ever. Nicholas Brady calls for a new simplicity agenda, in the FT:

Regulators need a clear “bright line” that they can apply to bank activities. The aim should be to permit innovation, and prudent risk taking, while also creating less varied and complex boundaries that banks cannot cross and that everyone can understand. The new simplicity should establish a clear ability to determine when to say yes, and when to say no; and the meaning of “no” should be unambiguous.The debate should shift to focus on the total leverage permitted in the bank’s books – that is the “bright line”. Banks should be permitted to devise their own strategies and use trading as they see fit, but they should be restricted from taking positions that use leverage of more than “X-to-1”. That may limit the upside of their operations, but at the same time it will limit the downside for taxpayers. It also puts responsibility for operational decisions where they belong, in the hands of the bankers themselves. What should be the boundary? Will it take additional time to design? Yes, but it will be worth it. For a change the public will both understand and agree with it.

The case of "less is better" is gaining more weight against the traditional paradigm of regulation. Some are indeed pushing for more and different way of data gathering about risks and quantities. But the last financial crisis reminded us of the difference between risks (quantifiable) and uncertainty (which is not). It took back from the shelf Knight, Keynes and Minsky and  in a speech at the Fed's Jackson Hole conference, Mr. Haldane from the Bank of England:

The degree of complexity also raises serious questions about the robustness of the regulatory framework given its degree of over-parameterisation. This million-dimension parameter set is based on the in-sample statistical fit of models drawn from short historical samples. If previous studies tell us it may take 250 years of data for a complex asset pricing model to beat a simple one, it is difficult to imagine how long a sample would be needed to justify a million-digit parameter set.

The visible hands of financial markets

A stream of study reveal that formal institutions and regulations were not and are not the only elements allowing for financial markets to emerge. Late 17th century England  financial revolution provides valuable lessons for todays regulators and all the parties interested in making financial markets more efficient and less risky: formal complex regulation is not the answer. Formal simple regulation might address the need to rebuild confidence in the solvency of financial firms, but Western economies needs to think of mechanisms to address the loss of trust. Financial history perspectives are insightful in that regard. Carlos, Key amd Dupree showed that learning took place before the official establishement of the financial market and how crucial it was for its emergence and proper functionning:

The key is learning. Individual investors learned how to make (and lose) money in ways that did not directly involve productive processes. They learned how to share risk in commercial and financial endeavors; how to buy and sell, and where to buy and sell. They learned about the financial rewards and losses they could incur. Concomitant with this was the learning by specialized brokers who managed the trade during these early years. The goldsmith bankers increased their expertise in the equity section of the market

Google, math and the physics of finance

The algorithm on which google is based, PageRank, could be replicated and applied to finance, so as to measure the extent to which financial institutions are interconnected. PageRank links pages to each others and the ones most connected to other important ones will be ranked accordingly. In others words, the algorythm captures the circularity of interconnection. Buchanan explains Bloomberg the parrallel with an algorithm European phycisits and economist developed:

Their algorithm, DebtRank, seeks to measure the total economic value that would be destroyed if a bank became distressed or went into default. It does so by moving outward from the bank through the web of links in the financial system to estimate all the various consequences likely to accrue from one failure. Banks connected to more banks with high DebtRank scores would, naturally, have higher DebtRank scores themselves.