I defend my proposal of a prohibition of wagers on the evolution of prices (which was standard in the 19th century) within the framework of a Constitution for the Economy.
I defend my proposal of a prohibition of wagers on the evolution of prices (which was standard in the 19th century) within the framework of a Constitution for the Economy.
Guest post. Taking advantage of my interview with Caroline de Gruyter in NRC Handelsblad, Lambert de Haas has put this all together. He’s expecting your remarks to make further improvements.
I was asked to make the introductory speech at the Conference “Heurs et malheurs du capitalisme”, which took place at Université Blaise Pascal in Clermont-Ferrand on February 4th. Bénédicte has been so kind as to translate the written version of my speech.
Capitalism’s highs and lows? When we talk these days of its highs, it is because its lows are so much – uncomfortably much – on our mind.
But what exactly do we mean when we refer to “capitalism”? Many authors merely consider that capitalism is “any aspect of our current economic system”. For example, they mistake capitalism for the market economy. Markets are a system of distribution and circulation of products, operated by merchants, and resting on mercantile profit. It may exist in economic systems that are in no way capitalistic: feudalism, for instance. Other authors mistake capitalism for liberalism, a political doctrine that, according to its proponents, seeks to optimize the role played by the state in our societies, but actually aims at reducing the role of the state as much as can be.
Of course, today’s economic system combines capitalism, market economy and liberalism. Nevertheless capitalism has some specifics: it is an economic system dominated by the capitalist, i.e. the holder of capital. The capitalist is that person who temporarily parts from his or her capital at a price: the payment of interest at periodic intervals, taking place until the loan’s “maturity” has been reached: the contractually determined time of refund.
International Study Day
Anthropology of the Crisis of Contemporary Capitalism
3 mai 2011, 10h-17h, musée du quai Branly, 37 Quai Branly, 75007 Paris, Cinema Theater
Convened by Jonathan Friedman (IRIS/EHESS) & Laurent Berger (LAS/MQB)
10h-10h15 Jonathan Friedman (IRIS-EHESS) & Laurent Berger (LAS-MQB) « Introduction: Towards an anthropology of the crisis in capitalism »
10h15-11h Paul Jorion « How to become the anthropologist of the crisis »
11h30-12h15 Don Kalb (Central European University, Budapest and Utrecht University)
« Financialization and Neo-nationalism in the New Old Europe »
14h30-15h15 Keith Hart (Goldsmiths University of London) « The financial crisis and the end of all-purpose money »
15h45-16h30 David Graeber (Goldsmiths University of London) « Debt and crisis in historical perspective »
A couple of weeks ago, my new book Le capitalisme à l’agonie came out, published by Fayard in Paris. Bénédicte has been so kind as to translate the summary I wrote for its backcover.
In 1989, at the fall of the Berlin Wall, capitalism was triumphant. Deprived by now of any enemies, it had ceased to be just one economic system among others to become the single form under which an economic system could possibly exist. In 2007, a mere eighteen years later, that is for all purposes simultaneously on the timescale of human history, it would itself be carried away by the maelstrom of its upcoming destruction. Capitalism has now reached the point of death. What could possibly have happened?
Looking back, the eighteen years separating the fall of the Soviet-type state capitalism and the fall of the Western market capitalism will seem trivial The explanations offered for a supposedly intrinsic superiority of the one system which outlasted its rival by a short interval only will seem trivial as well. History will remember the irony of this conjunction.
Despite having hardly been mentioned at all, one hypothesis by now stands out: could it be that capitalism and communism were struck down by the very same ailment? Complexity would then be the cause: the make-up of human societies is bound to reach a threshold in complexity beyond which instability gets the upper hand and fragility having become overwhelming, the system heads for disaster.
An alternative explanation is that in order to thrive, capitalism was in need of a powerful enemy to oppose. This enemy, far from being a threat to capitalism turned out to be in actuality its unexpected support. The option was open to citizens of democracies to turn their vote to such an alternative and this by itself was enough to force capitalism’s beneficiaries to keep its functioning within the borders of common decency. Once such an alternative option had vanished, capitalism’s beneficiaries did not refrain from trying de develop its market mentality even further, destabilizing by this the entire system and leading it straight to its downfall.
There is one more possible explanation: that due to the payment of interests by those who have no option but to borrow when trying to meet their productive or consumptive aims, capitalism would inevitably fuel a concentration of wealth such that the whole system would break down sooner or later.
Between these various hypotheses, there is no need for choosing though: the three of them are jointly true, each in its own particular manner and their combined implications characterise the first decade of the twenty-first century. This getting together of lethal factors explains why we are not currently experiencing any of the crises of capitalism which have become habitual in the two most recent centuries but truly, its last gasp.
We are examining in the book the various moments of a time when a behemoth mechanism, first slows down, then stops.
This novel feature of a lack of any serious competitor for capitalism prevents us from seeing with any clarity what is coming next. To enlighten us, we need to focus on what we mean by happiness, the kind of happiness we are wishing our children, our children’s children and ourselves. We need also to scrutinize the contradiction existing between two of our main concerns neither of which we are prepared to sacrifice: ethics, the moral life, and private property, the right of owning, without such possession being ever legitimately questioned. We analyse the quandary of a world where labour is becoming rare but where the income it provides remains indispensible for the large majority.
Some luminaries of human thought did guess that our species would one day be faced with questions which if not unsolvable, require however that we initiate a move as radical as that which led us from the Paleolithic to the Neolithic era, or from agrarian to industrial societies. We will summon to this aim the ground breaking pondering of Robespierre, Saint-Just, Hegel, Marx, Lévy-Bruhl, Freud and Keynes in particular.
Robert J. Shiller, professor of economics at Yale University, has published recently, along with his wife Virginia, a psychologist, an article entitled “Economists as Worldly Philosophers” (Cowles Foundation Discussion Paper No. 1788, Yale University, March 2011).
In their joint paper, the Shillers suggest that if economists were “Worldly Philosophers”, the double failure they have experienced in recent years could have been avoided: they haven’t been able indeed either to foresee the crisis or to suggest any credible remedies to the ensuing mess since then.
This is due according to the authors to overspecialization which implies economists lack the time needed to broaden their horizons to other fields that would enlighten their views, such as philosophy, history, sociology, psychology, and so on.
The Shillers’ article however falls short of its expectations as it summons the spent mirage of multidisciplinarity: the salvation of the field of economics would reside in knowing more about a larger number of things. Unable to tell precisely what economics is lacking in, they inadvertently transpose a qualitative question into a quantitative one.
In truth, the added value provided by experts belonging to another field is never that they come up with the missing piece borrowed from their own knowledge, but that they identify in a particular instance the blindness deriving from the incestuous cooptation of members that plagues every intellectual field.
No sooner is the framework of economics defined as Homo oeconomicus’ utility maximization, within a framework of methodological individualism which holds that interactions between Homines oeconomici do not lead to any collective “emergent” effect, that the whole approach is stuck in a stalemate, and no amount of open-mindedness will then be able to save it.
Contrary to what the Shillers suggest, the deadlock does not result from excessive specialization but from an epistemological misstep: the true economic players –groups of men and women playing different economic roles (whether these are called “conditions”, “orders” or “classes” matters little) – have been replaced in our explanations by pools of asocial – if not anti-social – Homines economici whose role as investors, company executives or employees, is regarded as fundamentally indifferent.
The quandary of economics is that it ossified within the framework of an emerging late nineteenth century psychology, voluntaristic in principle, where agents are the all-powerful masters of their own fate and capable of making perfect rational decisions based on perfect information. If economics had instead developed as a sociology, as was the case with the political economy of such thinkers as Adam Smith and David Ricardo, there would be no urgent need for replacing today’s narrow-minded economists by “Worldly Philosophers”.
An English translation of Le capitalisme (I) – Les nervures de l’avenir posted on my French blog on March 2nd.
In Reason in History (1837), a posthumous work composed from lecture notes, Hegel observes that “ … what experience and history teach is that peoples and governments have never yet learned from history, let alone acted according to its lessons”. This is true: had it been otherwise, no civilization having preserved the memory of those that preceded it would ever have died.
While failing to learn from history, men have never stopped however trying to decipher it and when reading it, our focus is either on what keeps reappearing under an identical shape or on what has never been seen before. Grasping to what extent these two ingredients are mixed: the same and the different, is fundamental of course, especially in those times of transition. We will not know where we’re heading if we fail to determine whether the times we live in are characterised by the brand new or by the eternal return. With the former, the processes observed are nearing completion, with the latter, they are bound to persist. We need distinguishing ruptures from continuities. When the first outweigh the second, then change is radical. This is why the ability at reading history is less crucial when in the early days of a new era than when, as currently, an exhausted era is coming to an end.
When cracking a chrysalis, a dark and thick liquid comes to light, revealing neither the shape of the larva in the process of being dissolved, nor that of the perfect insect which will emerge one day. Turbulent times are of this nature. Saint-Just was once forced to admit that: « Perhaps the force of circumstance leads us to outcomes which we had not thought of ahead. » Shortly after this admission, he surrendered without a fight to a fate of impending death, acknowledging his inability to understand the whirlwind that had overtaken him.
Should times evolve in a radical fashion, there will exist within them « veins »: rectilinear trajectories connecting the past to the future through the mesh that the present is made of. Other areas will remain unchanged but, for as long as the transition takes place, being part of the general effervescence, they will nonetheless be subjected to disquieting turbulence. Being able to detect the underlying presence of such “veins” amounts to reading the future written as of now in the present.
(To be followed …)
[Thanks to Bernard Bouvet for having had a first shot at translating this piece!]
Finance is in shambles. It has remained until now under the close supervision of economic and financial theory. In recent years, due to the overbearing dominance of views developed under the umbrella of the “Chicago School” of economics, finance has been regarded as explainable through the combination of a very simplified version of psychology: that of the “homo oeconomicus“, and of physics. The physics in question is supposed to have risen all-armoured Minerva-like out of the embarrassingly simplified psychology hitherto mentioned. This is the tenet of methodological individualism presiding nowadays over mainstream economics and financial theory.
Human nature, in the guise of the homo oeconomicus displays a number of qualities such as utilitarianism, ultimate rationality and – somewhat paradoxically combined to the two aforementioned – a pervasive herd instinct. Why this particular version of psychology? For no better reason than having been dominant at the end of the nineteenth century when a supposedly “scientific” economics emerged. This is why homo oeconomicus is so conveniently transparent to himself or herself, working out with clockwork precision in all circumstances the most rational approach that the precise quantity of information available allows – that is, unless the herd instinct prevails. Not for him the murky hesitations and self-delusion that unconscious motives convey.
Back in the nineteenth century, physics were stressing how important it was to remove subjectivity from scientific methodology, meaning the uncontrolled interaction of human beings with the subject of their inquiry. The difficulty here for economics is that when you remove from the economy the uncontrolled interaction of human beings, what is left to study is of not much interest. Here an example: price formation which economists explain as the meeting of a curve representing demand with another representing supply. Now tell me: has any anthropologist ever encountered circumstances where the status of buyer and seller is indifferent to the settling of price? Aristotle knew that reciprocal status determines price and this makes him on the contrary the anthropologist’s friend (1).
So, let us say this bluntly: human nature as envisioned by economics holds but a frightfully tenuous relationship with the type of human nature which anthropologists are familiar with.
What are then the traits of human nature which the current crisis has most prominently emphasized?
Various commitments on papers commissioned in French have kept me away from this blog. Reward is another factor: with an average of around 30 daily hits on the English blog and 2500 on the French one, vanity has been a powerful drive for concentrating on the French one. Dialogue is another one. If you’ve had the opportunity of looking at the French blog you will have noticed that commentators often engage in lively conversations, with me resting comfortably in the meantime in the bleachers.
Why is that so? I believe that my reputation as a writer in English is not up to that as a writer in French, despite the 11 years I’ve spent in the UK and the 11 years I’ve now spent in the US. The reason is no doubt cultural affiliation: even in those days I was teaching at Cambridge University I was very much regarded as a representative of French anthropology. This applies as well to my writings in the philosophy of science: they belong distinctively to a tradition initiated by Poincaré, Meyerson and Duhem. As for my properly philosophical musings, they draw heavily on Kojève’s reading of Hegel and on Hegel himself – definitely not a central philosopher within the Anglo-Saxon world. Lacan, one of my major influences is surely known of English speakers but the truth here is that the Lacan I’m familiar with and have been a student of is an entirely different beast than the one resulting from the amazing transformation Lacan underwent when crossing the Atlantic.
So should my English blog fold? Not quite yet and this for the following reason: I detect (thanks to Google Analytics!) a renewed interest in the papers I wrote last year on the subprime crisis. The reason I imagine is that although they must have looked utterly weird at the time I posted them with such considerations as calls to renationalizing Fannie Mae and Freddie Mac, they’ve now turned mainstream even though not due to anything of my own making.
This renewed interest may entice me in turn to come up with more, restarting hence the currently stalled dynamics. In addition, further contributions to a Human Complex Systems’ approach to the unfolding financial crisis are still in the making. Watch this space as only time will tell…
I’m blessed with a very popular blog in French. One of the questions that came up lately in my dialogue with commentators is that of the reversibility of major ecological disasters induced by human activity and of the feasibility of reversing such disasters with the tools pertaining to our current technology.
This is a serious question, a very serious one, and I intend to use the popularity of my (French) blog to push the issue a far as needs be. I’ve chosen one example – so that we don’t get locked in trivial generalities – that of a possible interruption of the Gulf Stream due to human activity. The consensus is that such an interruption – which I understand already occurred for ten days in 2004 – would make the temperature in Western Europe drop permanently by 5 to 10 degrees Celsius, that is, 10 to 20 degrees Fahrenheit. Is the interruption a possibility – even remote – and should the event occur, what are our realistic chances of reversing it?
According to the response I get to my query, I would consider launching an appropriate form of action around it. I will not be waiting – passively – to get your response only: I will try to reach out to the people I understand are the true experts on this issue and will refer back to you what I’m hearing.
Also – in an attempt to make it a full-fledged effort – I will communicate in each of my two blogs any progress made on the other.
The very justification of a Human Complex System’s approach to the operation of human societies, implying a continuous explanatory spectrum from the individual (particle) to the cultural or societal levels (field), is offered by Hegel when he writes in Reason in History (*) that
… human actions in history produce additional results, beyond their immediate purpose and attainment, beyond their immediate knowledge and desire. They gratify their own interests; but something more is thereby accomplished, which is latent in the action though not present in their consciousness and not included in their design.
Adam Smith’s “invisible hand” at work in the markets would then be but one instance of such “cunning of reason.” It is then the more perplexing that the same economists whose analyses most assume the self-regulatory operation of such an “invisible hand” are also those who staunchly commit themselves to a principle of “methodological individualism” implying that there is nothing more to see in the economy than the outcome of the individual economic agents’ rational behavior.
Or is it instead that they are fully aware of the presence of a “something more thereby accomplished” but would rather not know about its precise nature?
(*) Posthumously published in 1837.
One way of looking at the subprime crisis – and by this I mean only the properly real estate–based part of the unfolding drama – is in terms of population dynamics, in terms of three populations of borrowers who first entered the market and then left it in reverse order as the last to come in were also the first to leave.
In order to characterize these populations I’m resorting to a classification that was introduced – although used for a different purpose – by Hyman Minsky, an American Keynesian economist who was born in 1919 and died in 1996. Minsky distinguished [*] three modes in which an economy can operate in terms of behavior related to debt. In the first mode, borrowers are in a position to reimburse principal and pay interest on a regular basis; this is the safe mode which he called “hedged”. In the second mode, called “speculative,” borrowers are able to pay interest but are unable to reimburse principal. Finally, in the third mode, called “Ponzi”, from “Ponzi scheme,” borrowers are unable to meet either interest or principal payments.
How can either speculators or Ponzi players be part of the scene? Speculators are safe as long as there is no request that they pay back principal, as in a non-amortizing or “balloon” loan: they can “roll” their debt until the day of reckoning. How can Ponzi players stay in the game? This is a bit trickier: they need to sell assets or, alternatively, keep borrowing larger and larger sums in order to service their debt.
In normal circumstances, banks would only lend to “hedgers” being able to pay interest and principal, as these borrowers are the only ones likely to make their business profitable. Residential real estate in the US is subsidized by government: interest payments are tax deductible, and so are property taxes and the proceeds from the house sale, up to a ceiling. Federal Housing Association (FHA) contributions to mortgage insurance constitute as well a subsidy. These subsidies mean that owners can put more money into buying a house than they would otherwise. That additional money finds its way to the housing market and leads to inflation in the price of houses. If the circumstances persist, the market for residential properties sets into bubble mode.
Once the market is in bubble mode an interesting change takes place: “speculative” borrowers are allowed to join in. Why? Because although they have enough money to pay interest but not enough to refund the outstanding balance, in the new circumstances that situation is only provisional as equity is slowly but surely building up through the simple expansion of the bubble. At the height of the bubble in the spring of 2005, housing price was rising at 13.7%. At that speed, equity amounting to 25% of the house value was built in after one year and nine months only.
To give “speculative” borrowers a further little push, lenders reinstated the “Interest Only” mortgage. The Home Owners’ Loan Corporation (HOLC) had refinanced delinquent borrowers in 1933, inventing for the occasion the – from then on “classical” – fixed rate amortizing 30 year loan. The “Interest Only” or “balloon” loan had led borrowers to their demise and it should never happen again thought the legislators of the New Deal. “Not so!”, started to say lenders in the new millennium.
What about Ponzi players? Their time was about to come too! They couldn’t pay full interest and needed therefore to sell assets or further borrow to service it. In a bubble they could do both. They could sell their house at its new inflated price and use the proceeds to pay the interest due. But this was not even necessary as they could simply refinance their loan for a larger amount through a “Cash-out” mortgage loan and use that money. Alternatively, and sparing themselves the hassle of refinancing, they could subscribe to a “HELOC,” a Home Equity Line of Credit, exchanging the equity in their home for cash that could be funneled into paying the interest due.
This being a bit too complicated for some Ponzi players, lenders came up with loan types that were pushing the bother of paying the full interest due into a distant future. There were two approaches. One was the subprime “2/28” ARM (for Adjustable Rate Mortgage) with the initial two years benefiting from a “teaser rate” and the remaining 28 years paying interest at a floating interest rate determined at a set margin above the index: most commonly, the 6 Month LIBOR (London Inter-Bank Offered Rate), the rate at which banks could borrow themselves on the Eurodollar market, Eurodollars being dollars traded outside the US domestic market. As is now well-known, at the time of reckoning, when interest was reset at its “true” rate opportunities for refinancing had all but evaporated, “2/28” borrowers then defaulted in droves, contributing thus to the bubble being punctured.
The second approach used to give the Ponzi players a little push was the “Pay Option ARM,” when the option used was that of “minimum payment” – a formula that 85% of the borrowers of these “affordability loans” – as they were called – enthusiastically adopted. Of course, in the same way as with “2/28” subprime loans, a “reset” time would come when truth would prevail and interest would at long last need to be paid. In the “Pay Option ARM” the part of interest accrued but not actually paid would be added on top of the outstanding balance, i.e. the loan’s principal, creating what is called a “negative equity.” Reset would take place when the outstanding balance would have risen in that manner to 115% of the initial principal value, i.e. when the unpaid part of monthly interest would reach 15% of the loan amount.
As we just saw, Ponzi players can only make their payments – however reduced these have become through subtleties in loan underwriting – if housing prices keep rising: they need indeed a constant restocking of equity to make the interest payments they’ve committed themselves to. Ponzi schemes display however the remarkable property of self-extinguishment. They require indeed to sustain themselves a constant flow of new recruits and these are out of necessity in finite number. Shortage in new recruits is what happened: once the Ponzi players had acquired their own home there was nobody to follow. This marked automatically the Ponzi players’ downfall as it meant that the price of housing stagnated and this they couldn’t bear as what they needed to pay interest was a housing bubble.
But stagnating housing prices are but a fleeting moment as the foreclosed homes of the Ponzi players join the by then pretty crowded residential real estate market, leading the price of homes to fall, resulting in no time in the end of… “speculative” borrowers. Why? Because these could just about pay interest and were counting on the rising equity in their house for reimbursing one day the principal they still owed. When the equity stopped rising it became clear that that hope was unlikely to materialize and “speculative” borrowers got nervous. Nothing ominous had yet happened but the future had stopped looking rosy. When housing price began to drop things turned ominous. When paying interest only no equity in the house is being built apart from that which may be resulting from a current real estate bubble. So as soon as that bubble deflates, “speculative” borrowers find themselves in that position variously called “underwater” or “upside down”: when the outstanding balance on the house has become higher than the money that can be made through selling the house. At that point the “speculative” borrower starts dragging a ball and chain and may feel that the best strategy is that of rushing to the exit and propose the bank a “short sale” where the house is returned with the debt being forfeited – whatever the current value of the house compared to the outstanding balance of the loan – no question being asked.
Homes reclaimed by the banks through short sales are put back on the market, pushing home prices further downwards. As I said, “hedgers” are able to pay interest and principal but this may change with plummeting home prices: if these keep coming down, at some point these borrowers also will get “underwater” or “upside down” and will feel that a “short sale” is the best way for preventing being out of their pocket comes the day of reckoning.
This is the time we’re in as we speak. As proof I will quote Marshall Eckblad of Dow Jones Newswires who wrote yesterday: “Delinquencies among home loans to the nation’s more reliable borrowers, known as “prime” mortgages, are rising quickly, and that could dog banks’ ability to shake further losses this year and next.”
In my next installment I will translate this “population dynamics’” approach of the subprime crisis into a financial one, in terms of the financial instruments involved: all those Asset-Backed Securities (ABS), Collateralized Debt Obligations (CDO), Asset-Backed Commercial Papers (ABCP) and Structured Investment Vehicles (SIV) you’ve heard about.
Watch this space!
[*] Hyman Minsky, The Financial Instability Hypothesis, Working Paper No. 74, May 1992
I was interviewed earlier today by Richard Adhikari, a journalist at TechNewsWorld, about an Artificial Intelligence project. I didn’t know anything about that project except what would be the title of the article: “AI Program Thinks Like a 4-Year-Old”.
There is an excellent summary of what I had told the journalist:
“I’m always suspicious of this kind of thing where they’re dealing with children,” anthropologist and sociologist Paul Jorion told TechNewsWorld. “I always have the feeling that there are some major issues they haven’t been able to solve yet.”
Jorion developed ANELLA, the Associative Network with Emerging Logical and Learning Abilities, whose intelligence was guided by the dynamics of affect, or feeling, back in 1989 for the artificial intelligence unit of British Telecom.
Most of the approaches toward AI “have taken an over-sophisticated view of the problem,” Jorion said. His, on the other hand, was “very simple — I’ve got a universe of words, and you just find a way to connect them that makes sense.”
Now talking about Eddie, the four year old toddler developed at the Rensselaer Polytechnic Institute in New York State by a team lead by Selmer Bringsjord, the article explains that
To test Eddie’s reasoning powers, the group created a demo in Second Life in which Eddie was shown someone placing an object in one location then leaving the virtual room, followed by a second person who moved the object to another location in the room. Eddie was then asked where the first person would look for the object when he got back. Eddie’s response was the first location — incorrect, but typical of a four-year-old child in the real world.
Hmm, what did I tell you!
The subprime crisis is often explained in terms of trust: one day trust between financial counterparties vanished and here was a crisis. Explanations in terms of “market confidence” refer in fact to two distinct phenomena, one being indeed trust and the other one being more plainly straightforward profitability. Let me start with profitability. Subprime loans had been repackaged in their thousands so as to mimic a straightforward obligation, be these Asset-Backed Securities (ABS) or – in a second step – collateralized Debt Obligations (CDO) comprising ABSs. When the risk-based premium embedded within the interest rate charged on a subprime mortgage revealed itself to be insufficient to cover the actual risk of default on such loans, investors stopped buying the products where these had been repackaged. It’s as simple as that and has of course nothing to do in this case with either trust or confidence: investors simply stopped purchasing a product that had ceased to be profitable.
As I’m aiming – as I’ve explained in earlier blogs (*) – at a “complete” explanation of the subprime crisis, I need to model this explicitly – and writing it as part of a computer program is a good manner for ensuring it is complete. Resorting then to some pseudo-code in the style of BASIC I would write something like the following:
If Profitability < 0 then “Don’t buy”
The zero in the equation can be replaced by any figure you wish, depending on your profitability target.
Trust slipped in under two different guises. I remind that a Collateralized Debt Obligation is a composite financial product the elements of which are certificates also called “tranches” of Asset-Backed Securities. Usually a hundred or more ABS tranches are thus repackaged as a CDO. Apart from being backed by subprime loans, ABS can alternatively be backed by credit card debt, auto loans, etc. The composition of a CDO is advertised in its prospectus, so it is possible to know whether or not a particular one comprised ABS backed by subprime loans. Some CDOs are more complex, like a “CDO square”, a CDO composed of CDOs, meaning that it is not unusual for a “CDO square” to be composed of over a thousand underlying ABSs. And this is where trust kicked in back in August 2007: if you couldn’t tell if a financial product contained or not subprime loans, you would simply abstain from buying it.
Confidence is a bit trickier than defining a profitability threshold under which you abstain from buying. You would need something like:
If some part of Product is subprime loans then “Don’t buy”
Typically you would have an array containing the list of components of your CDO and you would loop through it and if subprime is encountered that would be the end of it.
Deal = “Fine”
For each Part in Product
—If Part = “subprime” then
——Deal = “Not Fine”
——Exit For loop
If Deal = “Fine” then “Buy”
If you were able to loop all the way through without being kicked out and Deal being redefined as “Not Fine” then the deal is fine and you can buy.
But it goes further than that as the condition should also comprise the case where it is impossible to establish whether or not the product contains subprime loans, say that the label for Part is missing making it impossible to find out if it is subprime or not. The line
If Part = “subprime” then
would be rewritten then in the following manner, taking into account the possible occurrence of a missing label, showing as an empty string:
If Part = (“subprime” OR “”) then
emphasizing that the components of the product need to be explicitly known for the deal to go through.
Now an extension of the trust element was also involved: counterparty risk. It might be that you were not buying a single product but engaging in a long term relationship with a counterparty. As with an interest rate swap, say, where payments are made every six months over a period of several years. It is crucial to know that your counterparty will be there in the long haul. Now how many subprime loans has your counterparty in its portfolio that may weaken it financially so that its solvency over the long term might be compromised? Difficult to know. Let’s turn again towards the simple-minded but enlightening process of translating the condition into a line of programming.
If Deal = “Fine” then [passed successfully through the loop above]
—If Number of Cash Flows > 1 then [Product is long term]
——If Counterparty has (No subprime loans) then “Buy”
The last condition would also be rewritten as a loop
CounterpartyPortfolio = “Fine”
For each Part in Portfolio
—If Part = (“subprime” OR “”) then
——Count = Count + 1
——If Count > 100 then [100 or any other threshold]
———CounterpartyPortfolio = “Not Fine”
———Exit For loop
If CounterpartyPortfolio = “Fine” then “Buy”
Bringing this all together, the whole “trust” or “confidence” issue would actually amount to the following test:
Deal = “Fine”
For each Part in Product
—If Part = (“subprime” OR “”) then
——Deal = “Not Fine”
——Exit For loop
If Deal = “Fine” then
—If Number of Cash Flows > 1 then
——For each Part in CounterpartyPortfolio
———If Part = (“subprime” OR “”) then
————Count = Count + 1
————If Count > 100 then
—————Deal = “Not Fine”
—————Exit For loop
If Deal = “Fine” then “Buy”
As can be seen from my pseudo-code, what the “trust” or “confidence” issue means in fact in the subprime crisis is that the conditions for purchasing a financial product become increasingly restrictive. The number of hurdles grows and the information necessary for a transaction to be allowed is growing in step: first about the product, containing subprime loans or not, about the seller next: “containing” (in portfolio) subprime loans or not. The crucial part is the “If Part = (“subprime” OR “”)” test: a large number of transactions would be prohibited because of the explicit presence of subprime loans but many more because of the missing information represented by the empty string “”: in case of doubt please abstain!
(*) The subprime crisis: a human complex system phenomenon, Agents using financial models and the “human cognitive cocktail”, Pricing models: why the good ones are useless and the true ones, priceless
I’m happy with the way things worked out yesterday, March 8th, at the UCLA Complexity Science Conference with my paper: The Subprime Crisis: A Human Complex Systems Phenomenon.
Of course, trying to squeeze the whole crisis into an hour (1 ¼ with John Bragin’s express permission), it turned out I had much too much material. I don’t think personally that slide shows have enough meat to show that they can get circulated without their author fleshing them up. This is why I’m not communicating as of yet what I had to say but I’ll be working in the coming days on a full-fledged text which will be posted here (watch this space!).
Thanks to the organizers: John Bragin and Dwight Read (UCLA) and Doug White (UCI – in absentia). Thanks to the other speakers. From J. Steven Lansing (University of Arizona), I learned that human genes need not be aggressively competitive but can diffuse harmoniously according to the “neutral model.” From Michalis Faloutsos (University of California Riverside) I learned that graph theory allows you to track down kids saving money on records by sharing them on the web. Finally I learned form William I. Newman (UCLA) that Lewis Fry Richardson (1881 – 1953) was a pioneer in the study of fractals; I got also from William’s presentation an encouraging confirmation that discrete dynamic systems are the way to go when modeling human phenomena. Thanks to all!
I’ve mentioned already in Agents using financial models and the “human cognitive cocktail” a number of pitfalls linked to the task of modeling the subprime crisis in a Human Complex Systems perspective, especially those related to agents’ partial understanding of the models they’re using or in errors they’re making when using them. I’ve also hinted at some models making unwarranted claims about their ability at forecasting. I should also mention – as I was recently reminded – inflated assumptions about the virtues of diversification or, I should rather say, at the capacity of the markets to remain optimally diversified.
I also said in the abstract of the presentation to be made on March 8th: The subprime crisis: a human complex system phenomenon that the working of the financial instruments involved in the crisis [Asset-Backed Securities (complex); Collateralized Debt Obligations (complex); Asset-Backed Commercial Paper (simple) and Credit-Default Swaps (simple)] is relatively straightforward. There is however here a snafu which has to do with pricing: we have pricing models and pretty sophisticated ones at that but these are paradoxically known to be unlikely to provide any accurate picture of price.
Our models of price formation are so far from predicting price accurately that an accounting directive implemented in 2007, FASB (Financial Accounting Standard Board) 157 distinguishes between “marked-to-model,” being assigned a Level 3 for reliability and “marked-to-market,” the price that the market actually generated, assigned Level 1. Level 1 reliability is top while Level 3 is bottom.
I plan coming back below to why “marked-to-model” is so inefficient at predicting actual prices but let me first emphasize the conundrum we’re in: that we not only possess pricing models but that these are regarded as “industry standard” while at the same time there’s no way we can use them in a Human Complex Systems’ approach as they are known to be too ineffective at doing what they’re aiming at doing, i.e. at giving an accurate figure for a price.
This means that before we can even start with our Human Complex Systems approach we first need to provide a new model for pricing: one that really generates prices like real ones. Fortunately I’ve already proposed one in an earlier blog: in Trouble’s a Bubble, introducing the stock synthetic. I copy the relevant passage below:
“The dynamics of the market price is […] best described as a discrete dynamical system where the most recent settlement price is a function of past prices.
It can be represented as
MaP t = F(MaP t-1, MaP t-2, …);
with MaP t standing for Market Price at time t.
A market price is clearly dynamic as its value changes with time; it is also discrete as each transaction generates a settlement price that applies to [a] specific volume […] exchanged between seller and buyer, and it is a function of past states as all agents base at any point in time their decisions to buy or sell on an analysis of past prices – be it crude or sophisticated.
The speculative value (SpV) […] is simply [“marked-to-market” price] minus [“marked-to-model” price].
SpV t = MaP t – NaP t.
A bubble arises when SpV keeps growing.”
Now a few words on “marked-to-model” prices: these are typically based on “fundamentals” which is just another word for the components of the product that is being priced, and are “additive” or in any case “aggregative” – when elements are combined in a more sophisticated way than just being added to each other. Adam Smith called the “marked-to-model” price the “natural price”; in his terms:
“When the price of any commodity is neither more nor less than what is sufficient to pay the rent of the land, the wages of the labor, and the profits of the stock employed in raising, preparing, and bringing it to market, according to their natural rates, the commodity is then sold for what may be called its natural price” (Adam Smith, An Inquiry into the Nature and Causes of the Wealth of Nations, Oxford: Oxford University Press,  1976: 72).
Benjamin Graham introduced in Security Analysis (1934) the by now widely accepted concept that the non-speculative, i.e. “natural price” of a stock can be calculated additively as the sum of all discounted future dividends, to which should be added the present value of the company’s equity per share, in case the company folds some time in the future.
The main difference therefore between “marked-to-model” prices and “marked-to-market” prices is that the former are “extrinsic”: calculating the price of a particular product from other prices – those of the product’s components, while the latter are “intrinsic”: the price of the product is “self-reflective” being based on itself, more specifically on prior instances of itself.
I first devised the discrete dynamical system model mentioned above when a futures trader back in 1990 (Note sur l’utilisation de méthodes empruntées à la physique dans l’analyse technique des marchés). In truth, anyone who has to forecast price variations in real time is forced to use some variety of this model. Models of this type typically determine if the most recent price is “under-valuating” or “over-valuating” the market in the light of prior prices; such models are typically shallow as far as time-depth is concerned as “noise” would otherwise rapidly accumulate – an acknowledgement of the fact that the “extrinsic” determination of price kicks in and forces realignment on “fundamentals” (*). Hence my title: “Pricing models: why the good ones are useless and the true ones, priceless.”
(*) I have explained this in more detail in a paper published in French: Le prix et la « valeur » d’une action boursière.
I’m working on the paper to be given at the Human Complex Systems’ one-day conference on March 8th. I don’t want to divulge prematurely any scoop but at the same time I’d like to share some of my puzzlement as I go, and as if thinking aloud.
To recap: I’m toying with the concept of a large – as complex as need be – model of the subprime crisis. The easy parts are those which are already modeled of that Rube Goldberg machine (see diagram), like the cash flow structure (of variable complexity) of the financial instruments at the epicenter of the crisis, i.e. Asset-Backed Securities (complex); Collateralized Debt Obligations (complex); Asset-Backed Commercial Paper (simple) and Credit-Default Swaps (simple).
But of course as soon as I’ve claimed that these financial instruments are truly modeled, a number of caveats come to my mind:
1) Some assumptions in these models are deemed “subjective.”
2) Many of these models make wild and unwarranted assumptions about the feasibility of forecasting the future.
3) However accurate the models might be, those human agents who make decisions from them
— a. understand them in most cases only partially;
— b. make errors when using them – even when they fully understand them.
Let me review this in that order:
1) “Subjective” assumptions: that means that there’s a range of possible values and one is assigned as the outcome of the data having been processed by the “human cognitive cocktail” – see below.
2) Knowing the future: about some of these models that feel confident at the validity of their wild forecasts, there is “industry consensus” in finance about that feasibility; to give just one example: the forward yield curve is erroneously assumed to hold information about the future (spot) yield curve. What exactly does “industry consensus” mean in this instance? That people use the model because they either a) mistakenly believe it to be “scientific,” i.e. true?; b) do suspect it might not be true but use it anyway because of its “investment-grade” industry standard rating? Does it matter for any practical purpose if either a or b is the case?
3) Agent’s understanding of the model used.
— a. Partial understanding of the model only: it probably just means that agents’ decision-making is loosely linked to the model’s outcome if understanding is minimal and tightly linked to it if it is fair; the decision is a function of the model’s results plus minus a huge or a small epsilon (*) respectively.
— b. Error when using the model: just epsilon.
Returning to the “human cognitive cocktail,” I call “human cognitive cocktail,” the methods used by human agents in puzzle-solving (the following list is likely to be revised and refined – its order is arbitrary):
1. “Fuzzy logic type” of probability calculus.
2. “Expert-system-like” combination of logical rules.
3. “Logistic regression type” of multi-factorial pseudo-quantitative processing.
4. “Multi-layered perceptron type” of pure (= unconscious) intuition.
(To be continued…)
(*) Greek letter traditionally used as a symbol for the error factor.
I’ll be speaking at UCLA on Saturday March 8th, 2008 at the
Human Complex Systems – UCLA Four Campus Complexity Conference,
UCLA Haines Hall 352. The conference starts at 9 AM, my own talk is at 2:30 PM.
If it looks like proposing an entirely new paradigm for financial studies, that’s because that’s precisely what it is. Hope you can join!
The subprime crisis: a human complex system phenomenon
Explanations of the subprime crisis typically combine partial explanations, illustrations, “speaking” analogies, etc. treading at different levels: from the “elementary particle” level where the consumer and the financial trader are acting, to that of the “field” level where entities such as “market distrust” or “credit crunch” are being invoked as observables. Understanding is assumed to derive unproblematically from such an impressionistic portrait where intuition is expected to fill the gaps of an overall explanation.
What is presented here is what aims to be instead a total explanation of the subprime crisis, connecting in an integrated whole the “particle” and “field” levels of the financial system which provides the economy with its bloodstream. The mechanics of the financial instruments involved in the process (Asset-Backed Securities; Collateralized Debt Obligations; Asset-Backed Commercial Paper and Credit-Default Swaps) is first presented: their anatomy and their physiology where the circulation of cash flows underlines their analogy with hydraulic systems regulated by control structures. Is then added to the picture, the human agents’ interaction with them, their representations of these instruments’ behavior – or lack of it – as models and their failed as well as successful attempts, based on these models, at correcting what they observe as the unintended consequences of these instruments.
Human models are shown to imply in most cases unwarranted assumptions about the feasibility of accurate forecasting. Adequate models typically favor homeostasis as they suggest ways for implementing corrective behavior or negative feedback while inadequate models typically encourage “herd behavior” or positive feedback leading to catastrophes. Positive feedback is however shown to be the leading dynamics of some core financial processes such as speculative pricing (i.e. pricing as an intrinsic dynamics severed from fundamentals); leverage (providing a multiplier to chances of gains and of losses) and derivatives (allowing to replicate the chances of gains and losses of an underlying instrument into a new “synthetic” one).
Crises within human institutions derive often from an incomplete understanding of the processes at work. The paper has therefore the pragmatic aim of providing means for countering future disasters within the financial system.
Businesses don’t seem to have any long–term goals apart from staying in business. They no doubt provide benefits to their shareholders and executives during their lifetime but why they aim at persisting in their existence with little reflection devoted to the “why?” of it is far from obvious. There is a clear analogy here with people and groups of people who – as we know from experience – persist in their endeavors without often much of a justification for why.
An analogy can be drawn here with a particular form of kinship structure which the anthropologist Marshall Sahlins explained in a 1961 paper called « The Segmentary Lineage: An Organization of Predatory Expansion » (*). In that paper, Sahlins described the segmentary lineage, a type of kinship structure often encountered in African traditional societies, where the lineage’s head strategy consists in invading the environment with his progeny of which he tries to maximize the number. As the paper’s subtitle made clear, Sahlins labeled the segmentary lineage, “an organization of predatory expansion.” The choice of the term “predatory” was however infelicitous as – although there is no accompanying social organization in these cases – this type of strategy is resorted to by animal populations which the field of “population dynamics” characterizes with the less dramatic and more adequate phrase of “colonizing behavior.”
Colonizing behavior is perfectly adapted to relatively unpopulated environments and it allows in particular a speedy expansion of life-forms. The African environments that Sahlins had in mind – I can testify to this – fitted that description and the label “colonizing” was much more apt therefore than the excessive “predatory” that Sahlins used instead.
Things change radically though once the environment which was the theater of such “colonizing” strategies becomes more densely populated. Just as with segmentary lineages, businesses within the capitalist system have no other long-term aim than their survival for an unlimited period of time. With lineages, the expansion strategy covers an ever increasing part of the environment and the resources it holds. The same with businesses, measuring the success of their strategy in terms of “market share.” With the segmentary lineage, the beneficiaries are its family members, its chiefs in particular. Similarly with businesses: the beneficiaries are their shareholders and even more so, their executives.
Within densely populated environments, the widening influence of a lineage over a territory or of a business over a market share allows that group to crowd out competition and to trend towards the optimal power balance in its view: that of a monopoly situation where the relationship with counterparties knows no constraint and the terms when dealing with them can properly be “dictated.”
A “colonizing” policy as I said allows life-forms to spread in no time within relatively unoccupied environments. However it first grows inadequate then plainly detrimental as the population’s density increases. Indeed, in crowded surroundings, the sole long-term goal shared by both segmentary lineages and businesses of ensuring their unlimited survival in time, end up in an unfettered war of all against all.
Ensuring one’s unlimited survival in time is the typical aim that nature left to its own devices assigns by default to every type of population. In reverse, within a nature which Man has domesticated to render it less harsh to his own fate, such aim needs to be reexamined due to its disposition to end up in disaster in environments which have ceased benefiting from further efforts at colonization. This conclusion applies no doubt to segmentary lineages but even more so to businesses. The time has come for them to assign themselves humanly significant aims to supplant the by now dysfunctional one which nature had assigned it by default.
(*) Sahlins, Marshall D., “The Segmentary Lineage: An Organization of Predatory Expansion,” American Anthropologist, April 1961, Vol. 63(2): 322-344.
My French blog was started on February 28th, my English blog, a few days later, on March 3rd, both of this year. By mid-July, the French blog had an average readership of 40 per day, among whom about 20 new readers; by now, 4 months later, the average readership is 160 (over the past 30 days), among whom about 100 new readers per day. The English blog, from its inception has had a following of anywhere between 0 and 30 a day.
The reason for the different fates of the two blogs is clear: the average time between two posts on the French blog has been 1.5 days while on the English one, 8 days. Also, posts on the latter have been a bit of a hodge-podge about whatever crossed my mind at the time: from the subprime meltdown to our favorite restaurant in Beijing, with musings on the LA underground scene or philosophical reflections on the implications of the “many-world” interpretation in quantum mechanics, etc. The French blog has been no less eclectic in its coverage, at the same time it has been strongly themed from the very beginning with the “subprime crisis” as its focus. The French blog was started as a medium for offering follow-ups on my most recent book in French: “Vers la crise du capitalisme américain?” (Paris: La Découverte, 2007); the book was published in mid-January, forecasting a major financial crisis centered on American housing. One month later, with the ABX Indices in free-fall, the crisis was there for everyone to see. Friends expected updates, which I started providing haphazardly until – about two weeks later – it became obvious that a blog was the way to go.
In the middle of last night – inspired no doubt by the somewhat rich diet of our Thanksgiving dinner – I decided to give the English blog a new breath of life by providing it with its own central theme.
In 2004, at Dwight Read’s invitation, I became an affiliate researcher at UCLA’s “Human Complex Systems” inter-departmental unit. On October 16th of this year I gave two lectures at HCS: the first, speaking to the undergraduates, was called “Human Complex Systems in the Economy and in Finance,” the second, for the graduates, was a presentation of a simulation I had written for the First World Congress on Social Simulation in Kyoto in 2006, entitled “Adam Smith’s Invisible Hand Revisited. An Agent-Based simulation of the New York Stock Exchange”. Another contribution I have made recently to Human Complex Systems was my “Reasons vs. Causes: Emergence as experienced by the human agent”, a paper published this year in Structure and Dynamics.
I intend Human Complex Systems to be the main theme of this blog and I will cover the following:
1. Illustrations of emergence in human behavior, where the whole is more than its parts: where collective behavior is bigger / different than the sum of individual behavior (I’m here intentionally taking to task what is known as “methodological individualism,” the founding tenet of current economic thought);
2. Generally speaking, using methods borrowed from physics when accounting for human behavior;
3. Analyses of speech as a “field-like” phenomenon allowing action at a distance (as when I ask you to open the window and you do open it) – my current series “Thought as Word Dynamics,” now in its 4th installment belongs here.