Juli 28, 2019
mickaelcamrynfredianoturati
Ebook , by Richard M. Bookstaber
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, by Richard M. Bookstaber
Ebook , by Richard M. Bookstaber
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Product details
File Size: 1660 KB
Print Length: 224 pages
Publisher: Princeton University Press (April 17, 2017)
Publication Date: April 17, 2017
Sold by: Amazon Digital Services LLC
Language: English
ASIN: B01M2BVG7M
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Amazon Best Sellers Rank:
#198,329 Paid in Kindle Store (See Top 100 Paid in Kindle Store)
This book fills an essential niche between highly theoretical work on complex systems and the day-to-day risk management practiced in financial institutions. The author offers a sophisticated treatment of agent-based modeling using simple concepts and no mathematics. The work is deeply informed by a long career on the front lines of risk management, both in top global financial institutions and as a regulator. This distinguishes it from more abstract treatments or direct importation of concepts from physics.Agent-based modeling leads into a discussion of emergent phenomena, macro level effects that are not the intention or forecast of any individual agent. Here too the phenomena are strictly relevant to finance, both from observation of past crises and reasoning about potential future ones. Another feature of agent-based modeling is non-ergodicity, and fancy way of saying that sometimes the dice change in between rolls. Finance and other human interactions do not display the mild randomness of the casino, where all outcomes and probabilities are known in advance, and in the long run the house wins its expected amount.The author stresses that we cannot predict future crises from past ones, because we have no idea what will spark the next disaster. Personally, I would emphasize that people will react differently to the next spark because of what happened the last time--while there are an infinite number of bad things that can happen, there's a fairly small number of ways they usually work out. For example, we know that financial disasters are usually accompanied by credit contractions. You don't need to guess what's going to cause the next crisis to make sure you're prepared for credit disappearing. But this is a point of detail, I certainly agree that preparing for the last crisis is a poor approach to risk management.The result of all this is radical uncertainty. The only way to predict the future is to live it. The author claims there are no mathematical or analytic shortcuts. Here I think he overstates the case a little. There are top-down, equilibrium forces that have strong influences on events. They do not seem important at the height of the crisis, but they do matter. During a hurricane, it's foolish to say that air pressure has to equalize so there's no need to worry about the wind. But it's not foolish to reason from simple physics that it takes energy to maintain differences in air pressure, and so the hurricane will eventually run down.While reading this book, I was reminded of Tetsuo Takashima's novel Tsunami. Written six years before the 2011 TÅhoku earthquake, it posited a larger-than-forecast tsunami inundating a nuclear power plant. The hero quits his promising academic career predicting earthquakes to take a low level municipal job in disaster preparedness, and spends his time developing a simple computer application to link up local officials. He runs scenarios from the bottom up, not to guess when or where a tsunami will hit, but to react appropriately after one does. The tsunami predictions are worse than useless. After a shock, all transport and nuclear plants are shut down. Since it's summer and work is canceled and there's limited air conditioning, after a few days of no disaster, people all go to the beach, just in time for the big wave. Unless you can predict with high confidence well ahead of time, you do more harm than good. But bottom-up preparedness based on running many simulations with the people who know local conditions and will be making decisions in the crisis, do tremendous good, whenever the disaster strikes and whatever specific form it takes.The author keeps the book interesting for non-specialists by not getting into the technical details of how risk managers attempt to do these things. We're more likely to say we're doing "scenario analysis" than agent-based modeling, but it's the same idea, if a bit less fancy. You work out as many macro scenarios as you can think of, based on the past and speculation about the future, and try to guess how every important actor will behave. Since you never know that for sure, you run lots of simulations with random deviations. This is no help for predicting the future, you know it will not resemble any of your simulations. But there is actually a manageable number of key decisions: where to set limits, how much cash to hold, when to cut losses and so forth. If these are set in a manner to avoid disaster in as many scenarios as possible, you have some hope that the discipline of preparing for what you can foresee gives you the flexibility to survive whatever happens. Risk managers call non-ergodicity "regime shifts" and build them into models.Emergent phenomena are nice to think about, but have not found their way into risk management practice. The issue is that there is a cost to precautions. You need to make enough money in good times to make it worth surviving the bad times--and profits build capital and create equity value that can separate survivors from road kill in a crisis. There are enough known phenomena to prepare for, and the kind of preparations are generally useful for most unexpected phenomena as well. In most cases there isn't attention and other resources to spare for specific preparations for plausible phenomena predicted by agent-based models that has never been observed; especially because we cannot imagine them in sufficient detail to design many specific preparations.Radical uncertainty is used more in a negative way than a positive one. All model-based predictions--pricing models and risk models--are matched by a "and if the model's wrong. . ." contingency plan. The answer is not a backup model, but a checklist for how to survive when you don't trust models.The only major disagreement I have with the book is I think the author oversells how much good this does. Great risk management does not eliminate crises or make them easy. At best, it gives a little extra edge. In the long run, we hope that extra edge makes a difference, but (radical uncertainty) you won't know that until afterwards, if then. In fact, it is the idea that experts should be able to predict and prevent disaster that leads to people over-reacting to each crisis. People's expectations are so high, that their judgment of actual performance is so low, that they try to fix too much.This is the best available book that bridges the gap between academic theory of complex systems and practical financial risk management.
This is an important book on a critical subject. Every few years, we stumble through a financial crisis followed by post mortems that usually end up with folks throwing up their hands and asking "who could have known?" Crucially, standard economic models are not designed to gracefully explain crises whereas the agent-based models Bookstaber describes are intended to do exactly that.Part history, part philosophy and part polemic, "The End of Theory" is a great introduction to a new way of thinking about financial crises. To those who claim there is nothing new here, I recommend a more careful reading of the book. Clearly, some will react defensively to the criticism of neoclassical economics but it is important to keep the broader picture in mind. It is difficult to model future financial crises using historical data and standard methods. Bookstaber provides a way forward that is well worth considering and certainly worth debating.
Richard Bookstaber a long time finance practitioner/risk manager who has worked for Morgan Stanley, Salomon Brothers, Moore Capital and Bridgewater as well as the Financial Stability Oversight Council and the Office of Financial Research has written a broad-based attack on financial economics and the DSGE models now used by most central banks. Trust me he knows what he is writing about and in the interests of full disclosure I interacted with him when I worked at Salomon Brothers.Although not cited he is writing in the tradition of Nicholas Nassim Taleb (“The Black Swanâ€) with his fundamental disagreement with the theoretical underpinnings of financial economics. Simply put in a world of radical uncertainty we don’t know the underlying probability distributions of future financial returns and we don’t even know the potential states of the world needed to calculate a probability distribution. He argues that modern finance theory is built around top down axioms based on deductive reasoning where an all knowing representative individual calculates the future probabilities for all of the known states of the world. And importantly the future probability distribution is based on historical evidence. Under radical uncertainty that simply does not work.Instead he argues for agent based models built upon inductive reasoning where the actors are “reflexive†in the word used by George Soros, in that they respond to the actions of others. As much as economists envy physics, Bookstaber turns the Heisenberg uncertainty principle on them. Thus while financial theory works in normal times, in a crisis all bets are off as “stuff happens.â€What Bookstaber would like is to use agent based models that are used to model automobile traffic and schools of fish, for example, through the use of complexity theory. All this is fine and good, but aside from a narrative Bookstaber does not offer up a formal model for the financial markets. Perhaps he has one, but it is not here. Nevertheless he offers a roadmap for future research.At times Bookstaber’s writing style is clear and lucid with analogies from literature motion pictures and military combat. He is a student of “OODAâ€, observe, orient, decide and act. He is particularly acute in his discussion of the origins of the financial crisis and is highly critical of the role played by Goldman Sachs in their failure to honor a small “novation†request from Bear Stearns, which brought that firm down. However, at other times his writing is dull and staidBookstaber has written an important book and it should be read by risk managers and policy officials. The old models failed in 2008, now almost ten years later it is time for new ones.
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