These days, in countries with ailing financial institutions, getting rid of non-performing loans and other loss-generating assets in banks’ balance sheets by shifting positions to so-called bad banks is becoming a habit. The question is what is won with these constructs. In this context, the Japanese example is illuminating.
For economists, the year is starting with a mega event: The annual meetings of the American Economic Association and other members of the Allied Social Science Associations will take place from January 4 to 6 in San Diego, CA. The preliminary program is huge. In the light of the ongoing financial crises in the United States and Europe, the large variety of contributions dealing with financial markets and institutions, crisis phenomena and policies for crisis management and prevention does not surprise. Here comes a little selection.
A recent DB Research article explains why universal banks are optimal for clients and for financial stability and why it would be wrong to follow proposals to split them up. The arguments are well-known: (1) Universal banks offer a broad range of services. (2) They are able to exploit economies of scale and scope which result in lower costs for customers and the economy. (3) Diversification of operations allows them to realise more stable returns than specialist banks, and (4) broader coverage enables them to better monitor the financial health of clients and to “spot unsustainable risk accumulation across financial markets”. In the current environment, however, in particular for German banks many of these advantages do not fully materialise and, at the same time, there are shortcomings which threaten to undermine global financial stability and to prevent an effective crisis policy.
The central theme of Benoît Mandelbrot’s work was to find a regular pattern in irregularity and roughness as he described in the videos listed here and in his various books and articles. His mathematics, the fractal geometry, found applications in many different fields. He wrote (p.5 f.):
“It has helped model the weather, study river flows, analyze brainwaves and seismic tremors, and understand the distribution of galaxies. It was … embraced as an essential mathematical tool … by “chaos” theory, the study of order in the seeming-chaos of a whirlpool or a hurricane. It is routinely used today in the realm of man-made structures, to measure Internet traffic, compress computer files, and make movies. It was the mathematical engine behind the computer animation in the movie, Star Trek II: the Wrath of Khan.”
Mandelbrot had a strong interest in economics. He started his empirical research studying daily prices of cotton and other commodities for which very long time series from 1900 onward were available (only long series allowed to explore the patterns he was looking for, and in pre-computer times those were rare), and some of his ideas later became orthodoxy in financial markets worldwide. He raised the awareness of the phenomen of “fat tails” everybody is talking about these days. On the other hand, economists were among his greatest critics as many of his results stood in sharp contrast to their world view.
The headline borrows a phrase from Adam Kirsch in his review of Benoît Mandelbrot’s posthumous memoir The Fractalist. Musing about the inaccessability of Mandelbrot’s work Kirsch states the impossibility for a non-mathematician to advance beyond some generalities and understand what precisely it is that Mandelbrot accomplished, adding: “For this reviewer, reading The Fractalist is rather like reading about a poet who wrote in a foreign language for which no adequate translation is available.”
Recent debates about the crisis vulnerability of international financial networks indicate that in economics complexity is still a widely misunderstood concept. In my critique of a recent paper by Andrew Haldane from the Bank of England I described complexity as a phenomenon rooted in markets instead of networks of institutions and in the interactions of countless individuals with different motives and strategies. The result is an emergent property, a seemingly aligned behaviour reinforced by loops and feedback effects, known in the literature as self-organization or “swarm intelligence”.