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And now, the money forcast
OPINION
The money forecast When it comes to handling complexity, finance could learn a lot from meteorology. Time for action, says the Bank of England’s Andy Haldane IT IS said that economists engage in financial forecasting to make astrologers look good. So it is with some trepidation that I want to venture into a little financial futurology. This act of bravery was prompted by a recent piece of research about the structure of the global corporate network that was reported in New Scientist (22 October, p 8). This gave us a tantalising glimpse of a brave new world for finance. I want to try and map that world. If we do so, I believe fragilities in the global financial system which have stalked the globe for four years (and counting) could be significantly reduced. Finance is a classic complex, adaptive system, similar to an ecosystem. The growth in its scale, complexity and adaptation in the past generation alone would rival that of most other complex systems in the past century. The growth in certain financial markets and instruments has far outstripped Moore’s Law of a doubling of computer power every 18 months. The stock of outstanding financial contracts is now around 14 times annual global GDP. Yet this dense cat’s cradle of finance has been woven largely out of sight. At best we are able to snatch passing glimpses of it, for data are incomplete, local and lagging. Making sense of the financial system is more an act of archaeology than futurology. How so? Because, at least historically, finance has not thought of itself as a system. Instead, financial theory, 28 | NewScientist | 10 December 2011
regulation and data-collection architecture of the network, not has tended to focus on individual the behaviour of any one node. firms. Joining the dots was in no To make an analogy, you cannot one’s job description. understand the brain by focusing Theorists were partly to on a neuron – and then simply blame. Economics has always multiplying by 100 billion. been desperate to burnish its Regulators and statisticians scientific credentials and this were no less culpable. Pre-crisis, meant grounding it in the they sampled the financial decisions of individual people. neurons ever more intensively, By itself, that was not the mistake. but largely ignored the The mistake came in thinking the configuration of the financial behaviour of the system was just cortex. When parts started to an aggregated version of the malfunction, this meant no one behaviour of the individual. had much idea what critical Almost by definition, complex “Lehman Brothers was a systems do not behave like this. Interactions between agents are small fish, but through network uncertainty it what matters. And the key to that polluted the entire pond” is to explore the underlying
faculties would be impaired. That uncertainty, coupled with dense financial wiring, turned small failures into systemic collapse. In financial terms, Lehman Brothers was a small fish. But through network uncertainty and complex wiring, it polluted the whole financial pond. Those experiences are now seared onto the conscience of regulators. Systemic risk has entered their lexicon, and to understand that risk, they readily acknowledge the need to join the dots across the network. So far, so good. Still lacking are the data and models necessary to turn this good intent into action. There are grounds for optimism. Other disciplines have cut a dash in their complex network mapping over the past generation, assisted by increases in data-capture and modelling capability made possible by technology. One such is weather forecasting, which involves collecting over 100 million pieces of raw data daily from across the globe and using it to map evolving weather systems in near-real time and then simulating forward. Success stories can also be told about utility grids and transport networks, the web, social networks, global supply chains and perhaps the most complex web of all, the brain. Finance, by contrast, has been a late adopter. Analysis such as that on “the network that runs the world” is welcome because it represents a leap forward. A key ingredient for success elsewhere has been a common language and shared access to
Comment on these stories at newscientist.com/opinion
Andy Haldane is executive director of financial stability at the Bank of England in London
One minute with...
Nicholas Negroponte Can tablet computers “parachuted” into remote areas transform childhood learning, asks the man behind One Laptop per Child You’ll helicopter computers into remote areas so the children there can teach themselves to read and write. Where did the idea come from? One Laptop per Child (OLPC), even after giving out nearly 3 million laptops, is still criticised along the following lines: “Negroponte believes that you can give a child a laptop and walk away.” Whether I ever believed that or not is now secondary. It became such a refrain that I finally asked myself about a year ago: “What if you could?” When will this happen? A pre-pilot will start on 1 January 2012. Pre-pilot means that it will be small and there will be modest human intervention just to see children’s reactions in order to better design the real, handsoff, dropping-out-of-the-sky format. How will you pick the sites? English has to be an official language. So, learning to read and write in English has immediate local and social value, as well as long-term economic value – in short, it will be a passport to 21st-century skills. Villages in Sierra Leone, Tanzania and Liberia are candidates. A pre-pilot will also happen in India. Right now, as researchers, we know how kids learn English and do not yet want to deal with the complexity of other languages. How will you know if this works? The experiment has no human intervention. But that limitation does not exist when verifying and testing results. At the end of the two-year-long experiment, researchers trained in educational testing will go to the villages. The kids are not connected to the internet but we are connected to them, so some data collection and assessment will also happen remotely during the experiment. What about power and upkeep of the tablets? Power is solar and by hand crank. With the OLPC laptops the kids could repair about 85 per cent of malfunctions. We designed it to be taken apart easily. In fact, I had wanted to put a label on that said: “Warranty not valid until laptop is tampered with.” The tablets will be, yet again, more robust.
Profile Nicholas Negroponte is founder of the One Laptop per Child non-profit organisation and co-founded and directed the Massachusetts Institute of Technology’s Media Laboratory
What is your target audience? Five to 8-year-olds. Since the software is really centred on early childhood and immersive for that stage of life, they may be too babyish for older kids. What makes you optimistic that children can learn on their own, with digital tools? There is provocative evidence from research. Sugata Mitra, who is on our team, is famous for his hole-in-the-wall experiments. Over the past decade, he introduced the very first computer in a public space in remote villages across India. Children, who had never seen a computer before, congregated around this single machine and selforganised into learning communities to become computer-literate, with no adult intervention. In fact, their proficiency in computer literacy rivalled that of children who receive explicit instruction in schools. My general optimism is that children can do anything and, if you ask Sugata, collectively they seem to be able to. But I am really going into this with an open mind. It is an experiment, and one outcome could be “no, they cannot”. Interview by Vijaysree Venkatraman
10 December 2011 | NewScientist | 29
William B. Plowman/AP/PA
data. At present, finance has neither. But that, too, is set to change. Regulators are talking seriously about introducing common metrics for financial transactions. Alongside that, data warehouses are being constructed to store these raw materials. There are even moves afoot to put these raw materials to work. The US aims to create an Office of Financial Research to collect data from firms and weave the information into a web suitable for mapping and simulating risk. So to play clairvoyant, imagine the scene a generation hence. There is a single nerve centre for global finance. Inside, a map of financial flows is being drawn in real time. The world’s regulatory forecasters sit monitoring the financial world, perhaps even broadcasting it to the world’s media. National regulators may only be interested in a quite narrow subset of the data for the institutions for which they have responsibility. These data could be part of, or distinct from, the global architecture. Now imagine the light this financial map might shine. It would allow regulators to issue the equivalent of weather-warnings – storms brewing over Lehman Brothers, credit default swaps and Greece. It would enable advice to be issued – keep a safe distance from Bear Stearns, sub-prime mortgages and Icelandic banks. And it would enable “what-if?” simulations to be run – if UK bank Northern Rock is the first domino, what will be the next? At present, global finance does not have the technology to ask these questions, much less answer them. The prize is a big, but attainable, one. It would not entirely lift the fog from finance, but it could provide us with a navigation system better able to avoid the next crash landing. n
The money forecast When it comes to handling complexity, finance could learn a lot from meteorology. Time for action, says the Bank of England’s Andy Haldane IT IS said that economists engage in financial forecasting to make astrologers look good. So it is with some trepidation that I want to venture into a little financial futurology. This act of bravery was prompted by a recent piece of research about the structure of the global corporate network that was reported in New Scientist (22 October, p 8). This gave us a tantalising glimpse of a brave new world for finance. I want to try and map that world. If we do so, I believe fragilities in the global financial system which have stalked the globe for four years (and counting) could be significantly reduced. Finance is a classic complex, adaptive system, similar to an ecosystem. The growth in its scale, complexity and adaptation in the past generation alone would rival that of most other complex systems in the past century. The growth in certain financial markets and instruments has far outstripped Moore’s Law of a doubling of computer power every 18 months. The stock of outstanding financial contracts is now around 14 times annual global GDP. Yet this dense cat’s cradle of finance has been woven largely out of sight. At best we are able to snatch passing glimpses of it, for data are incomplete, local and lagging. Making sense of the financial system is more an act of archaeology than futurology. How so? Because, at least historically, finance has not thought of itself as a system. Instead, financial theory, 28 | NewScientist | 10 December 2011
regulation and data-collection architecture of the network, not has tended to focus on individual the behaviour of any one node. firms. Joining the dots was in no To make an analogy, you cannot one’s job description. understand the brain by focusing Theorists were partly to on a neuron – and then simply blame. Economics has always multiplying by 100 billion. been desperate to burnish its Regulators and statisticians scientific credentials and this were no less culpable. Pre-crisis, meant grounding it in the they sampled the financial decisions of individual people. neurons ever more intensively, By itself, that was not the mistake. but largely ignored the The mistake came in thinking the configuration of the financial behaviour of the system was just cortex. When parts started to an aggregated version of the malfunction, this meant no one behaviour of the individual. had much idea what critical Almost by definition, complex “Lehman Brothers was a systems do not behave like this. Interactions between agents are small fish, but through network uncertainty it what matters. And the key to that polluted the entire pond” is to explore the underlying
faculties would be impaired. That uncertainty, coupled with dense financial wiring, turned small failures into systemic collapse. In financial terms, Lehman Brothers was a small fish. But through network uncertainty and complex wiring, it polluted the whole financial pond. Those experiences are now seared onto the conscience of regulators. Systemic risk has entered their lexicon, and to understand that risk, they readily acknowledge the need to join the dots across the network. So far, so good. Still lacking are the data and models necessary to turn this good intent into action. There are grounds for optimism. Other disciplines have cut a dash in their complex network mapping over the past generation, assisted by increases in data-capture and modelling capability made possible by technology. One such is weather forecasting, which involves collecting over 100 million pieces of raw data daily from across the globe and using it to map evolving weather systems in near-real time and then simulating forward. Success stories can also be told about utility grids and transport networks, the web, social networks, global supply chains and perhaps the most complex web of all, the brain. Finance, by contrast, has been a late adopter. Analysis such as that on “the network that runs the world” is welcome because it represents a leap forward. A key ingredient for success elsewhere has been a common language and shared access to
Comment on these stories at newscientist.com/opinion
Andy Haldane is executive director of financial stability at the Bank of England in London
One minute with...
Nicholas Negroponte Can tablet computers “parachuted” into remote areas transform childhood learning, asks the man behind One Laptop per Child You’ll helicopter computers into remote areas so the children there can teach themselves to read and write. Where did the idea come from? One Laptop per Child (OLPC), even after giving out nearly 3 million laptops, is still criticised along the following lines: “Negroponte believes that you can give a child a laptop and walk away.” Whether I ever believed that or not is now secondary. It became such a refrain that I finally asked myself about a year ago: “What if you could?” When will this happen? A pre-pilot will start on 1 January 2012. Pre-pilot means that it will be small and there will be modest human intervention just to see children’s reactions in order to better design the real, handsoff, dropping-out-of-the-sky format. How will you pick the sites? English has to be an official language. So, learning to read and write in English has immediate local and social value, as well as long-term economic value – in short, it will be a passport to 21st-century skills. Villages in Sierra Leone, Tanzania and Liberia are candidates. A pre-pilot will also happen in India. Right now, as researchers, we know how kids learn English and do not yet want to deal with the complexity of other languages. How will you know if this works? The experiment has no human intervention. But that limitation does not exist when verifying and testing results. At the end of the two-year-long experiment, researchers trained in educational testing will go to the villages. The kids are not connected to the internet but we are connected to them, so some data collection and assessment will also happen remotely during the experiment. What about power and upkeep of the tablets? Power is solar and by hand crank. With the OLPC laptops the kids could repair about 85 per cent of malfunctions. We designed it to be taken apart easily. In fact, I had wanted to put a label on that said: “Warranty not valid until laptop is tampered with.” The tablets will be, yet again, more robust.
Profile Nicholas Negroponte is founder of the One Laptop per Child non-profit organisation and co-founded and directed the Massachusetts Institute of Technology’s Media Laboratory
What is your target audience? Five to 8-year-olds. Since the software is really centred on early childhood and immersive for that stage of life, they may be too babyish for older kids. What makes you optimistic that children can learn on their own, with digital tools? There is provocative evidence from research. Sugata Mitra, who is on our team, is famous for his hole-in-the-wall experiments. Over the past decade, he introduced the very first computer in a public space in remote villages across India. Children, who had never seen a computer before, congregated around this single machine and selforganised into learning communities to become computer-literate, with no adult intervention. In fact, their proficiency in computer literacy rivalled that of children who receive explicit instruction in schools. My general optimism is that children can do anything and, if you ask Sugata, collectively they seem to be able to. But I am really going into this with an open mind. It is an experiment, and one outcome could be “no, they cannot”. Interview by Vijaysree Venkatraman
10 December 2011 | NewScientist | 29
William B. Plowman/AP/PA
data. At present, finance has neither. But that, too, is set to change. Regulators are talking seriously about introducing common metrics for financial transactions. Alongside that, data warehouses are being constructed to store these raw materials. There are even moves afoot to put these raw materials to work. The US aims to create an Office of Financial Research to collect data from firms and weave the information into a web suitable for mapping and simulating risk. So to play clairvoyant, imagine the scene a generation hence. There is a single nerve centre for global finance. Inside, a map of financial flows is being drawn in real time. The world’s regulatory forecasters sit monitoring the financial world, perhaps even broadcasting it to the world’s media. National regulators may only be interested in a quite narrow subset of the data for the institutions for which they have responsibility. These data could be part of, or distinct from, the global architecture. Now imagine the light this financial map might shine. It would allow regulators to issue the equivalent of weather-warnings – storms brewing over Lehman Brothers, credit default swaps and Greece. It would enable advice to be issued – keep a safe distance from Bear Stearns, sub-prime mortgages and Icelandic banks. And it would enable “what-if?” simulations to be run – if UK bank Northern Rock is the first domino, what will be the next? At present, global finance does not have the technology to ask these questions, much less answer them. The prize is a big, but attainable, one. It would not entirely lift the fog from finance, but it could provide us with a navigation system better able to avoid the next crash landing. n