You are currently browsing the tag archive for the ‘No Free Lunch’ tag.

Fig. – A Symbolical Head (phrenological chart) illustrating the natural language of the faculties. At the Society pages / Economic Sociology web page.

You have much probably noticed by now how Scoop.it is emerging as a powerful platform for those collecting interesting research papers. There are several good examples, but let me stress one entitled “Bounded Rationality and Beyond” (scoop.it web page) curated by Alessandro Cerboni (blog). On a difficult research theme, Alessandro is doing a great job collecting nice essays and wonderful articles, whenever he founds them. One of those articles I really appreciated was John Conlisk‘s “Why Bounded Rationality?“, delivering into the field several important clues, for those who (like me) work in the area. What follows, is an excerpt from the article as well as part of his introductory section. The full (PDF) paper could be retrieved here:

In this survey, four reasons are given for incorporating bounded rationality in economic models. First, there is abundant empirical evidence that it is important. Second, models of bounded rationality have proved themselves in a wide range of impressive work. Third, the standard justifications for assuming unbounded rationality are unconvincing; their logic cuts both ways. Fourth, deliberation about an economic decision is a costly activity, and good economics requires that we entertain all costs. These four reasons, or categories of reasons, are developed in the following four sections. Deliberation cost will be a recurring theme.

Why bounded rationality? In four words (one for each section above): evidence, success, methodology, and scarcity. In more words: Psychology and economics provide wide-ranging evidence that bounded rationality is important (Section I). Economists who include bounds on rationality in their models have excellent success in describing economic behavior beyond the coverage of standard theory (Section II). The traditional appeals to economic methodology cut both ways; the conditions of a particular context may favor either bounded or unbounded rationality (Section III). Models of bounded rationality adhere to a fundamental tenet of economics, respect for scarcity. Human cognition, as a scarce resource, should be treated as such (Section IV). The survey stresses throughout that an appropriate rationality assumption is not something to decide once for all contexts. In principle, we might suppose there is an encompassing single theory which takes various forms of bounded and unbounded rationality as special. cases. As with other model ingredients, however, we in practice want to work directly with the most convenient special case which does justice to the context. The evidence and models surveyed suggest that a sensible rationality assumption will vary by context, depending on such conditions as deliberation cost, complexity, incentives, experience, and market discipline. Beyond the four reasons given, there is one more reason for studying bounded rationality. It is simply a fascinating thing to do. We can mix some Puck with our Hamlet.

Did you just mention privatization, “increase in productivity” and self-interest as a solution? Well, the answer depends a lot if you are in a pre or post equilibrium physical state. The distribution curve in question is more or less a Bell-curve. So maybe it’s time for all of us, to make a proper balance in here, having a brief look onto it from a recent scientific perspective.

Let us consider over-exploitation. Imagine a situation where multiple herders share a common parcel of land, on which they are each entitled to let their cows graze. In Hardin‘s (1968) example (check his seminal paper below), it is in each herder’s interest to put the next (and succeeding) cows he acquires onto the land, even if the quality of the common is damaged for all as a result, through overgrazing. The herder receives all of the benefits from an additional cow, while the damage to the common is shared by the entire group. If all herders make this individually rational economic decision, the common will be depleted or even destroyed, to the detriment of all, causing over-exploitation.

Video – “Balance“: Wolfgang and Christoph Lauenstein (Directors), Germany, 1989. Academy Award for Best Animated Short (1989).

This huge dilemma, know as “The tragedy of the commons” arises from the situation in which multiple individuals, acting independently and rationally consulting their own self-interest, will ultimately deplete a shared limited resource, even when it is clear that it is not in anyone’s long-term interest for this to happen. On my own timeself-interest” allow me to start this post directly with a key passage, followed by two videos and a final abstract. First paper below, is in fact the seminal Garrett Hardin paper, an influential article titled precisely “The Tragedy of the Commons,” written in December 1968 and first published in journal Science (Science 162, 1243-1248, full PDF). One of the key passages goes on like this. Hardin asks:

[…] In a welfare state, how shall we deal with the family, the religion, the race, or the class (or indeed any distinguishable and cohesive group) that adopts overbreeding as a policy to secure its own aggrandizement (13)? To couple the concept of freedom to breed with the belief that everyone born has an equal right to the commons is to lock the world into a tragic course of action. […]

So the question is: driven by rational choice, are we as Humanity all doomed into over-exploitation in what regards our common resources? Will we all end-up in a situation where any tiny move will drive us into a disaster, as the last seconds on the animated short movie above clearly and brilliantly illustrate?

Fortunately, the answer is no, according to recent research. Besides Hardin‘s work has been criticized on the grounds of historical inaccuracy, and for failing to distinguish between common property and open access resources (Wikipedia entry), there is subsequent work by Elinor Ostrom and others suggesting that using Hardin‘s work to argue for privatization of resources is an “overstatement” of the case.

Video – Elinor Ostrom: “Beyond the tragedy of commons“. Stockholm whiteboard seminars. (video lecture, 8:26 min.)

In fact, according to Ostrom work in the study of common pool resources (CPR), awarded in 2009 for the Nobel Prize in Economic Sciences, there are eight design principles of stable local common pool resource management, possible to avoid the present dilemma. Among others, one of her works I definitely recommend reading is her Presidential address on the American Political Science Association, presented back in 1997, entitled, “A Behavioral Approach to the Rational Choice Theory of Collective Action” (The American Political Science Review Journal, Vol. 92, No. 1, pp. 1-22, Mar., 1998). Her impressive paper-work starts like this:

[…] Extensive empirical evidence and theoretical developments in multiple disciplines stimulate a need to expand the range of rational choice models to be used as a foundation for the study of social dilemmas and collective action. After an introduction to the problem of overcoming social dilemmas through collective action, the remainder of this article is divided into six sections. The first briefly reviews the theoretical predictions of currently accepted rational choice theory related to social dilemmas. The second section summarizes the challenges to the sole reliance on a complete model of rationality presented by extensive experimental research. In the third section, I discuss two major empirical findings that begin to show how individuals achieve results that are “better than rational” by building conditions where reciprocity, reputation, and trust can help to overcome the strong temptations of short-run self-interest. The fourth section raises the possibility of developing second-generation models of rationality, the fifth section develops an initial theoretical scenario, and the final section concludes by examining the implications of placing reciprocity, reputation, and trust at the core of an empirically tested, behavioral theory of collective action. […]

(pic. – click to enlarge) Summer time in here, you know?! So, this will be my next T-shirt: “First, the Economy took over Politics. Now, Finance took over Economy. Bit by bit, planet Earth bounds to be a giant speculation machine“. @ViRAms April 28 2011 (link).

Video lecture by Ken Long (at the Statistics Problem Solvers blog) on Nassim Taleb‘s 4th Quadrant problems [1,2], i.e. a region where statistics not only don’t work but in which statistics are downright dangerous, because they lead you to make predictions as well as control systems that are unprepared for the kinds of systems shocks awaiting you.

Statistical and applied probabilistic knowledge is the core of knowledge; statistics is what tells you if something is true, false, or merely anecdotal; it is the “logic of science”; it is the instrument of risk-taking; it is the applied tools of epistemology; you can’t be a modern intellectual and not think probabilistically—but… let’s not be suckers. The problem is much more complicated than it seems to the casual, mechanistic user who picked it up in graduate school. Statistics can fool you. In fact it is fooling your government right now. It can even bankrupt the system (let’s face it: use of probabilistic methods for the estimation of risks did just blow up the banking system).”, Nassim Taleb, in [1].

[1] Nassim Nicholas Taleb, “The Fourth Quadrant: A Map of the Limits of Statistics“, An Edge Original Essay, Set., 2008. (link)

[2] Nassim Nicholas Taleb,”Convexity, Robustness, and Model Error inside the Fourth Quadrant“, Oxford Lecture (Draft version), Oxford, July 2010. [PDF paper]

It is not the strongest of the species that survives, nor the most intelligent that survives. It is the one that is the most adaptable to change“. Charles Darwin (On the Origin of Species, Nov. 1859)

During the Victorian era where high prudery and morality were constant, it would be hard to imagine seeing Charles Darwin wearing a Scottish-kilt. In fact, men’s formal clothing was less colourful than it was in the previous century, while women’s tight-fitting jersey dresses of the 1880s covered the body, leaving little to the imagination (source). There is however, one beautiful – as in strict sense of delighting the senses for exciting intellectual or emotional admiration – reason, I think he should have done it (!), regardless the  obvious bearing consequences of a severe Victorian society. Surprisingly, some how, that reason is linked to cheetahs chasing gazelles, among many other things…

As the image of Charles Darwin wearing a kilt, you will probably find these awkward too, but when a cheetah chases a gazelle, banded tartan Scottish-kilt woven textile like patterns soon start to pop-up everywhere. Not at the ground terrain level, of course. Instead, they appear as a phenotype-like map between your present and the past. You may think that this banded tartans will have no significance for your life, but do mind this: crying babies do it all the time with their mommy’s and fathers, companies do it with other companies in their regular business, people commuting in large cities do it over large highways, human language, literature and culture does it, friends do it, PC virus and anti-virus software do it, birds singing do it also, … and even full countries at war do it.

One extreme example is the Cold War, where for the first time on our Human history, co-evolutionary arms-race raised to unprecedented levels. Co-Evolution is indeed the right common key-word for all these phenomena, while large white banded strips punctuated by tiny black ones (bottom-left woven kilt above), would be the perfect correspondent tartan pattern for the case of the Cold War example mentioned. But among these, there is of course, much more Scottish-kilt like patterns we could find. Ideas, like over this TV ad above, co-evolve too. Here, the marketeer decided to co-evolve with a previous popular famous meme image: Sharon Stone crossing his legs at the 1992 ‘Basic Instinctmovie. In fact, there is an authentic plethora of different possible behavioural patterns. Like a fingerprint (associated with different Gaelic clans), each of these patterns correspond to a lineage of current versus ancestral strategies, trying to solve a specific problem, or achieving one precise goal. But as the strategic landscape is dynamically changing all the time, a good question is, how can we visualize it. And, above all, what vital information and knowledge could we retrieve from this evolutionary Scottish-kilts maps.

Fig. – The frontispiece drawing to the English edition of Ernst Haeckel‘s Evolution of Man (trans. 1903) presents a skull labelled “Australian Negro” as an intervening evolutionary stage between the “Mediterranean” skull and those of the lower primates (from the 1891 ed. of the Anthropogenie).

In nature, organisms and species coexist in an ecosystem, where each species has its own place or niche in the system. The environment contains a limited number and amount of resources, and the various species must compete for access to those resources, where successive adaptations in one group put pressure on another group to catch up (e.g., the coupled phenomena of speed in the cheetah and evasive agility in the gazelle). Through these interactions, species grow and change, each influencing the others evolutionary development [7]. This process of bi-adaptive relationship (in some cases can also assume a form of cooperation and mutualism) or reciprocal adaptation is know as Co-evolution, i.e. the evolution of two or more competing populations with coupled fitness.

The phenomena has several interesting features that may potentially enhance the adaptive power of artificial evolution [7], or  other types of bio-inspired learning systems. In particular, competing populations may reciprocally drive one another to increasing levels of complexity by producing an evolutionary “arms race”, where each group may become bigger, faster, more lethal, more intelligent, etc. Co-Evolution can then happen either between a learner (e.g., single population) and its environment (i.e. based on competitions among individuals in the population) or between learning species (two populations evolving), where the fitness of individuals is based on their behaviour in the context of the individuals of the other population [7]. This latter type of co-evolutionary search is often described as “host-parasite”, or “predator-prey” co-evolution. A good example and application of co-evolutionary learning include the pioneering work by Hillis in 1990 [1] on sorting networks.

It can occur at multiple levels of biology: it can be as microscopic as correlated mutations between amino acids in a protein, or as macroscopic as co-varying traits between different species in an environment. Being biological Co-Evolution, in a broad sense, “the change of a biological object triggered by the change of a related object” [2], his visualization however, could be profoundly hard. In fact, attempting to define and monitor “progress” in the context of Co-Evolutionary systems can be a somewhat nightmarish experience , as stated in [4]. It’s exactly here where Scottish-kilts come into play.

In 1995 [3], two researchers had a simple, yet powerful idea. In order to monitor the dynamics of artificial competitive co-evolutionary systems between two populations, Dave Cliff and Geoffrey Miller [3,4,5] proposed evaluating the performance of an individual from the current population in a series of trials against opponents from all previous generations. while visualizing the results as 2D grids of shaded cells or pixels: qualitative patterns in the shading can thus indicate different classes of co-evolutionary dynamic. Since their technique involves pitting a Current Individual (CI) against Ancestral Opponents (AO), they referred to the visualizations as CIAO plots (fig. above [3]).

Important Co-Evolutionary dynamics such as limited evolutionary memory, “Red Queen” effects or intransitive dominance cycling, will then be revealed like a fingerprint as certain qualitative patterns. Dominance cycling, for instance, it’s a major factor on Co-Evolution, wish could appear or not, during the entire co-evolutionary process. Imagine, for instance, 3 individuals (A,B,C) or strategies. Like over the well known “Rock, Paper, Scissors” game, strategy B could beat strategy A, strategy C could beat B, and strategy A could beat C, over and over in an eternal cycling, where only “arms race” specialized learning will emerge, at the cost of a limited learning generalization against a possible fourth individual-strategy D. If you play poker, you certainly know what I am talking about, since 2 poker players are constantly trying to broke this behavioural cycle, or entering it, depending on their so-far success.

Above (left and right figures – [3]), two idealised typical CIAO plot patterns can be observed, where darker shading denotes higher scores. On the left figure, however, co-evolutionary intransitive dominance cycling is a constant, where current elites (population A elites) score highly against population B opponents from 3, 8 and 13 generations ago, but not so well against generations in between. On the other hand (right figure), the behavioural pattern is completely different: over here we do observe limited evolutionary memory, where the current elites do well against opponents from 3,4 and 5 generations ago, but much less well against more distant ancestral opponents.

For to win one hundred victories in one hundred battles is not the acme of skill. To subdue the enemy without fighting is the acme of skill.” ~ Sun Tzu

Of course, in increasingly complex real-world situations Scottish-kilt like CIAO plots are much noisy than this (fig. above -[7]) where banded tartans could be less prominent, while the same could happen in irregular dominance cycling as elegantly showed by Cartlidge and Bullock in 2004 [6]. Above, some of my own experiences can be observed (submitted work). Over here I decided to co-evolve a AI agent strategy to play against a pool of 15 different strategies (6 of those confronts are presented above), and as a result, 6 different behavioural patterns emerged between them. All in all, the full spectrum of co-evolving dynamics could be observed, from the “Red Queen” effect, till alternate dominant cycles, and limited or long evolutionary memory. Even if some dynamics seem counter-productive in one-by-one confronts, in fact, all of these dynamics are useful in some way, as when you play Poker or the “Rock, Paper, Scissors” game. A typical confront between game memory (exploitation) and the ability to generalize (exploration). Where against precise opponents limited evolutionary memory was found, the same effect produced dominant cycles or long evolutionary memory against other strategies. The idea of course, is not to co-evolve a super-strategy to win all one-by-one battles (something that would be rather impossible; e.g. No free Lunch Theorem) but instead to win the whole round-robin tournament, by being highly adaptive and/or exaptive.

So next time you see someone wearing a banded tartan Scottish-kilt do remind yourself that, while getting trapped in traffic, that precise pattern could be the result of your long year co-evolved strategies to find the quickest way home, while confronting other commuters doing the same. And that, somewhere, somehow, Charles Darwin is envying your observations…

.

[1] W. Daniel Hillis (1990), “Co-Evolving Parasites improve Simulated Evolution as an Optimization Procedure”, Physica D, Vol. 42, pp. 228-234 (later in, C. Langton et al. (Eds.) (1992), Procs. Artificial Life II, Addison-Welsey, pp. 313-324).

[2] Yip et al.; Patel, P; Kim, PM; Engelman, DM; McDermott, D; Gerstein, M (2008). “An integrated system for studying residue Coevolution in Proteins“. Bioinformatics 24 (2): 290-292. doi:10.1093/bioinformatics/btm584. PMID 18056067.

[3] Dave Cliff, Geoffrey F. Miller, (1995), “Tracking the Red Queen: Methods for measuring co-evolutionary progress in open-ended simulations“. In F. Moran, A. Moreno, J. J. Merelo, & P. Cachon (Eds.), Advances in artificial life: Proceedings of the Third European Conference on Artificial Life (pp. 200-218). Berlin: Springer-Verlag.

[4] Dave Cliff, Geoffrey F. Miller, (2006), “Visualizing Co-Evolution with CIAO plots“, Artificial Life, 12(2), 199-202

[5] Dave Cliff, Geoffrey F. Miller (1996). “Co-evolution of pursuit and evasion II: Simulation methods and results“. In P. Maes, M. J. Mataric, J.-A. Meyer, J. Pollack, & S. W. Wilson (Eds.), From Animals to Animats 4: Proceedings of the Fourth International Conference on Simulation of Adaptive Behavior (pp. 506-515). Cambridge, MA: MIT Press.

[6] Cartlidge, J. and Bullock S., (2004), “Unpicking Tartan CIAO plots: Understanding irregular Co-Evolutionary Cycling“, Adaptive Behavior Journal, 12: 69-92, 2004.

[7] Ramos, Vitorino, (2007), “Co-Cognition, Neural Ensembles and Self-Organization“, extended abstract for a seminar talk at ISR – Institute for Systems and Robotics, Technical Univ. of Lisbon (IST), Lisbon, PORTUGAL. May 31, 2007.

Last year, at the beginning of October I decided to dedicate my second post on financial markets (I, II) to Black Swans. Swans are beautiful animals, but while white swans are vulgar and omnipresent at every pond, black swans are rare! Meanwhile, 2 days ago (June 1) the Wall Street Journal comes with this very awkward – and by all means for that precise reason – interesting article written by journalist Scott Patterson, where Mr. Taleb’s name pops-up again (image below).

Well, … let’s face it: you could put your money in the bank and have – let’s say – a 3% revenue at the end of your fiscal year. Or you could apply it to raise a new fancy gourmet restaurant at your local vicinity. Restaurants and local food stores are known to have 5-7% revenues in one year, not to speak on the immense burden they represent as well as for some associated risks – specially these days. But then you may think – better than banks, right? Right! Or, just to give you another example on this increasing scale – raising a little bit the risk -, on the other hand you could apply your money in stock markets. Main financial indexes (Dow Jones, NASDAQ, etc) are known to have an annual average revenue of 10-12% (since 1918). Not these days of course, where high volatility and entropy in the markets are installed. Well,  emergent countries like China are raising themselves at 12%/year also. We could go on and on with so many other examples. Some say that Eolic parks could achieve 40%. Normally the cost of one eolic tower is around 1 million euros, which could be paid back after one year producing energy trough wind at normal operating conditions. The rest are maintenance costs, as well as initial investment in terrains, etc. So, what’s new? Consider this. For moments imagine yourself having 100% in revenues, just last year, at this precise dramatic context. That’s 10 times what the market does in regular years, 20 times what your favorite restaurant does. Moreover, there is a substantial difference between all these examples. If you keep dropping money at the restaurant (for instance the revenue you have earned in the last year), still liquid revenues will be the same in the next year (unless you open a new dinner room next to the first one, while the awful burden keeps increasing). Some business are static and linear in time while others are exponential. As Alice in the wonderland, you will need to keep running twice as faster in order to be at the same place. Amazing those differences, no? Well, not for those “lovely” animal creatures known as Black Swans. According to Patterson, … Funds run by Universa, which is managed and owned by Mr. Taleb’s long-time collaborator Mark Spitznagel, last year gained more than 100% thanks to its bearish bets. Universa now runs about $6 billion, up from the $300 million it began with in January 2007. Excerpts from the Wall Street Journal article (Black Swan Fund Makes a Big Bet on Inflation) follow below. So, why the hell I do not feel at all surprised by this?! Really, I am not. Let me just say, I do have my own reasons:

Nassim Nicholas Taleb - Black Swan author  […] A hedge fund firm that reaped huge rewards betting against the market last year is about to open a fund premised on another wager: that the massive stimulus efforts of global governments will lead to hyperinflation. The firm, Universa Investments L.P., is known for its ties to gloomy investor Nassim Nicholas Taleb, author of the 2007 bestseller “The Black Swan,” which describes the impact of extreme events on the world and financial markets.

Funds run by Universa, which is managed and owned by Mr. Taleb’s long-time collaborator Mark Spitznagel, last year gained more than 100% thanks to its bearish bets. Universa now runs about $6 billion, up from the $300 million it began with in January 2007. Earlier this year, Mr. Spitznagel closed several funds to new investors….

Mr. Taleb doesn’t have an ownership interest in the Santa Monica, Calif., firm, but he has significant investments in it and helps shape its strategies. The term “black swan,” which has become a market catchphrase in the last few years, alludes to the once-widespread belief in the West that all swans are white. The notion was proven false when European explorers discovered black swans in Australia. A black-swan event, according to Mr. Taleb, is something that is extreme and highly unexpected. … […]

Two “The Economist” covers. The first one was manually created and posted by Richard Dawkins himself, … – yes – the evolutionary Biologist. The second one is real as well recent (as of April 4th) – UNDER ATTACK, a 14-page special report on the rise and fall of the wealthy. Do note the Blackberry on top of the dead guy in the front and the skyline of London’s Canary Warf financial district in the background (via HS Dent blog). The Laissez-faire Economy lead to all this (more).

The Economist cover OH FUCK Sept 2008

The Economist April 4 2009 UNDER ATTACK

 

It’s not everyday we see a 40 year ideology collapsing through a dramatic act of contrition. It has happened just a few hours ago (check video above), yesterday in the “financial crisis” congressional hearing in Washington (23. Oct. 2008). Moreover, what seems remarkable, is that the recognition comes from one of his most universally respected founding fathers and defenders.

Alan Greenspan was the longest serving chairman in the Federal Reserve board history (1987-2006), and during this 18-year period of time he were perhaps the leading proponent of de-regulation along with libertarian capitalism, vividly expressed on his “The Age of Turbulence – Adventures in a New World” 2007 book, advocating above all issues, Adam Smith’s “Invisible Hand” that markets can regulate themselves. As it’s known, for his whole adult life, the former Fed chairman has been a devotee of the philosophy of Ayn Rand, who celebrated free-market capitalism as the world’s most moral economic order and advocated a strict laissez-faire approach to government regulation of the marketplace. Ironically, he was a regulator that did not believed in any regulation at all.

It is now quite a remarkable historic moment seeing former Federal Reserve chairman, a lifelong champion of free markets, publicly questioning the philosophy that guided him throughout his years as the world’s most powerful economic policymaker. A philosophy followed and strongly defended by him (along with many others like Margaret Thatcher and Ronald Reagan), at least in the last 40 years, as he himself acknowledged yesterday. Asked by the congressional committee chairman, whether his free-market convictions pushed him to make wrong decisions, especially his failure to rein in unsafe mortgage lending practices, Greenspan replied that indeed he had found a flaw in his ideology, one that left him very distressed. “In other words, you found that your view of the world, your ideology was not right?” he was asked:

Absolutely, precisely“, replied Greenspan. “That’s precisely the reason I was shocked, because I have been going for 40 years or more with very considerable evidence it was working exceptionally well“. Albeit he was surely one of the most influential voices for de-regulation: “There is nothing in Federal regulation that makes it superior to Market regulation”, said Greenspan back in 1994, in one among many of his past radical free-market statements.

I presume we now all wonder, where was Greenspan, when back in 2003 one of the most prestigiously recognized and legendary financial investors such as Warren Buffet, called credit default obligations and derivatives “weapons of financial mass destruction“? Or where was he when Princeton Professor of Economics, Paul Krugman – the recent Nobel laureate – said back in 2006 that “If anyone is to blame on the current situation (sub prime) is Mr Greenspan who poopooed warnings about an emerging bubble and did nothing to crack down on irresponsible lending“. Or what did he, Greenspan itself, said just a few days after ENRON collapsed?

People working in complex systems – and surely financial markets are one of them (yes, for the past 4-5 years including these present turbulent times I am working hard in this area as well) – for long know that any systemic structure could collapse if only positive-feedbacks are injected into them, creating an auto-catalytic snow-ball effect, leading among other things to a power-law like Black Swan. Indeed power-laws are a striking powerful signature. This is specially true when we address self-organization (read it in the present context as self-regulation). In order to be a truly self-regulated system, financial markets should also be embedded with negative-feedbacks as well, as I have addressed in a post about finance and complex systems one month ago. In fact, in order to emerge as a truly self-organized system, self-interest, should constitute just one among many of the ingredients over the entire financial system, and not the isolated unique ingredient. Self-interest promotes amplification and positive feedback, which is – as I recognize – necessary. However, left alone, promotes instead dramatic snowballing drifts over chaotic regimes, due to it’s intrinsic amplification. What’s amazing (at least for me), is that Alan Greenspan just recognized that in a tiny few seconds along his current discourse (check video above), pointing it to the precise key-word:

[…] I made a mistake in presuming that the self-interest of organizations, specifically banks and others, was such that they were best capable of protecting their own shareholders. […] So the problem, here is something which looked to be as a very solid edifice, and indeed a critical pillar to market competition and free-markets, did breakdown and I think that, as I said, shock me. I still do not fully understand why it happened, and obviously to the extend, that I figure out where it happened and why, … aaaaaa, … I will change my views. If the facts change I will change. […]

As a result, “the whole intellectual edifice” of risk management collapsed, Greenspan said. In what regards his unexpected words yesterday at the congressional hearing, at least, I frankly praise him for his huge intellectual courage and present honesty. In the end, it seems that during the past 18 years, former FED chair was nothing else then a simple-man driven by his own blind faith on markets, from which he apparently comes out now. Unfortunately, only now at a very high price. Meanwhile as we know, severe consequences are here to stay, as was already evident when Greenspan addressed the House Financial Services Committee on 2003 (video below). Let’s hope that all these will not be forgotten in 3 decades from now (though, I doubt it – after all, nothing really serious came out from the entitled 3-man dream-team Bush-Sarkozy-Barroso “new global finance order” summit at Camp David last weekend, as expected):

“You have told the American people that you support a trade policy which is selling them out.” – Rep. Bernard Sanders to Federal Reserve Chairman Alan Greenspan on 7/16/03. Rep. Bernard Sanders (Independent-Vermont), now a US Senator, dresses down Federal Reserve Chairman Alan Greenspan in front of the House Financial Services Committee on 7/16/03.

Many man made and naturally occurring phenomena (being inherently complex systems), including city sizes, incomes, word frequencies, internet links, social networks and earthquake magnitudes, are distributed according to a power-law distribution. One under f Zipf’s law follows the same characteristic, or pink noise. Here is a possible long list, collected year after year, since the 1910’s up to now – 2008 (which I vividly recommend). From vacuum tubes to trading activities in world financial markets. Even, we could easily found them on Pollock’s paintings (recently here). Back in 2002, I have addressed some of his painting features (mostly fractal) regarding the theme “Emergent Aesthetics in Autonomous Collective Systems“. Astonishingly, without having a clue what fractal dimension’s would be, Jackson increased his fractal signatures year over year, while getting old. Indeed, “Action painting”, has he call it, mainly using his body motion and a bucket, were largely enough. 

Financial markets are indeed complex systems, even if they are far from being self-regulated. Much after this recent black Monday, I have made here some notes regarding Self-Organization and finance, over two weeks or so. Their basic features – as I see it. However- essentially what brings me here today is-, what happens to their frequency? Are phenomena like the current financial crisis, frequent? Well, much of that depends on our knowledge on power-laws. Good news is that we know how many of them will occur in a very large time window, bad news is that, we don’t know when will they precisely occur. As in Earthquakes (check this out). Does this impel us to do nothing? Not at all. We can’t do anything about earthquakes (at least for now – except prevent them), however we can establish some ground smart rules in order to avoid financial systems to collapse in turmoil (that is, tune them in the precise physical regime). Power-laws are not only our wake-up call, as they are a signature. For good or for worse. It seems that we are all playing across the planet, a reversed El Farol Bar problem. If that’s somehow true we all should ask new questions like: In what frequency should we go to a bar ?! In other words, should we all run to the banks now, asking for our deposits?

Any polynomial relationship that exhibits the property of scale invariance is a Power-Law. Power-law implies that small occurrences are extremely common, whereas large instances are extremely rare (similarly over maps and cities – if you have time, found out the foundation of Berlin city over time). As the large quantity of small dots + low frequency of large dots we may found on Jackson Pollock paintings. The same goes for Black-Swans.

Jackson Pollock in action - As reported somehow recently by Nature magazine (Sept., 13, 2000), research suggests that the abstract works of artists such as Jackson Pollock are esthetically pleasing because they obey fractal rules similar to those found on the natural world. Pollock was known to have swung his paint back and forth like a pendulum, using a can on the end of a string with a hole punched in it. Researchers (Jensen) have found that if a swinging pendulum is hit with a hammer at just the right frequency (slightly less than the natural rhythm of the pendulum), its motion becomes chaotic and the paint traces out very convincing fake Pollocks. However, the artist had no idea of fractals or chaotic motion, while dot distribution over Pollocks paintings follow a power-law.

Jackson Pollock in action - As reported somehow recently by Nature magazine (Sept., 13, 2000), research suggests that the abstract works of artists such as Jackson Pollock are esthetically pleasing because they obey fractal rules similar to those found on the natural world. Pollock was known to have swung his paint back and forth like a pendulum, using a can on the end of a string with a hole punched in it. Researchers (Jensen) have found that if a swinging pendulum is hit with a hammer at just the right frequency (slightly less than the natural rhythm of the pendulum), its motion becomes chaotic and the paint traces out very convincing "fake Pollocks". However, the artist had no idea of fractals or chaotic motion, while dot distribution over Pollock's paintings indeed follow a power-law.

A Black Swan is a highly improbable event that has three characteristics: It is unpredictable, it has incredible impact, and after it happens we invent a reason for it that makes it seem less probable. For those of you that did not have read 2007 Taleb’s book (picture above), wondering what a Black Swan is, or question yourself from where the name arises, just jump for a quick look over here. Nassim started to wrote his book in 2003. Finished it in 2006. So, in what way this “funny” distribution regards financial markets? Well, for many of us now, it his surprising that he have wrote this, back then:

[…] Globalization creates interlocking fragility, while reducing volatility and giving the appearance of stability. In other words it creates devastating Black Swans. We have never lived before under the threat of a global collapse. Financial Institutions have been merging into a smaller number of very large banks. Almost all banks are interrelated. So the financial ecology is swelling into gigantic, incestuous, bureaucratic banks – when one fails, they all fall. The increased concentration among banks seems to have the effect of making financial crises less likely, but when they happen they are more global in scale and hit us very hard. We have moved from a diversified ecology of small banks, with varied lending policies, to a more homogeneous framework of firms that all resemble one another. True, we now have fewer failures, but when they occur ….I shiver at the thought. […]

Were these words a Black Swan within the Black Swan book itself? Rather not. He continues directly to something we now know and face it in precise context. Please note that this was written in the period 2003-2006:

[…] Banks hire dull people and train them to be even more dull. If they look conservative, it’s only because their loans go bust on rare, very rare occasions. But (…) bankers are not conservative at all. They are just phenomenally skilled at self-deception by burying the possibility of a large, devastating loss under the rug. […] The government-sponsored institution Fannie Mae, when I look at its risks, seems to be sitting on a barrel of dynamite, vulnerable to the slightest hiccup. But not to worry: their large staff of scientists deemed these events “unlikely”. […] 

What about the costs, and the memory of them? Yes, indeed memory is important while playing game-theory-like games, as his mainly in our daily reality, but in one-two generations it will be probably lost (I hope not), and once again all will start:

[…]  the real-estate collapse of the early 1990s in which the now defunct savings and loan industry required a taxpayer-funded bailout of more than half a trillion dollars. The Federal Reserve bank protected them at our expense: when “conservative” bankers make profits, they get the benefits; when they are hurt, we pay the costs.

Should we be surprised? In fact, this is not new. Somehow, fallacy goes on (as George Monbiot tackle it with extreme precision over Guardian Journal very recently – Sep. 30). Not only we were not reacting to these power-law consequences, as many of those economic agents playing within the systems core itself, were thinking of something else:

[…] Once again, recall the story of banks hiding explosive risks in their portfolios. It is not a good idea to trust corporations with matters such as rare events because the performance of these executives is not observable on a short-term basis, and they will game the system by showing good performance so they can get their yearly bonus. The Achilles’ heel of capitalism is that if you make corporations compete, it is sometimes the one that is most exposed to the negative Black Swan that will appear to be the most for survival.[…] As if we did not have enough problems, banks are now more vulnerable to the Black Swan and the ludic fallacy than ever before with “scientists” among their staff taking care of exposures. The giant J. P. Morgan put the entire world at risk by introducing in the nineties RiskMetrics, a phony method aiming at managing people’s risks, causing the generalized use of the ludic fallacy, and bringing Dr. Johns into power in place of the skeptical Fat Tonys. (a related method called “Value-at-Risk,” which relies on the quantitative measurement of risk, has been spreading.) […]

Starting with the distribution and frequency of these kind of events (among many others), all of these words were written in the period 2003-2006. Since then, you could follow Taleb’s war on “Value at Risk” over here.  Or here, at Edge.org which I highly recommend.

Meanwhile, apart from what markets are suffering and complex science may enlightened us, life goes on. Not necessarily as we supposed. As we know, reality, many times excels fiction; one single video frame could value one thousand words. Right at your neighborhood. As you may see below, consequences could be much worse than a tornado:

Vodpod videos no longer available.

more about “Foreclosure Alley – SoCal Connected“, posted with vodpod

 

 

Image source: ITGO.COM (large size)

In what concerns Social Psychology, just check this out: Milgram et al.(1) found that if one person stood in a Manhattan street gazing at a sixth floor window, 20% of pedestrians looked up; if five people stood gazing, then 80% of people looked up.

As latest fraud facts told us last week in cascade manner (Freddie Mac, Fannie Mae, Lehman Brothers, AIG), essentially, the current financial crisis results from the fact that in order to be a truly self-organized, self-regulated adaptive evolving system as Adam Smith envisioned (back in 1776 – The Wealth of Nations), financial markets need not only to adopt Positive Feedback as they do (e.g., the one Milgram founded, above), but mainly – though in some proportion – Negative Feedback features as well, that is, some form of a priori outside Regulation – in other words, the context and environment of the entire “game” (check here for some basic features of Self-Organization -(2).  Ill or badly defined environments among complex systems, lead to chaotic or unprecedented biased evolutionary pressures (e.g., many of the entities – read it as some companies -, cheaters playing economic games such as the Iterated Prisonners Dilemma IPD over Bounded Rationality – that should naturally “die”, in fact proliferate), turning to be counterproductive for the whole system. Self-Organization occurs in precise very-subtle-narrow regimes (“at the edge of chaos”Christopher Langton, Santa Fe Institute), not over entire entropic regimes as the one we were facing, neither over the entire spectrum (Order, Semi-Order, Edge of Chaos, Chaos – check Stuart Kaufmann’s I, II, III, IV phases). They occur near them, not in them. In order to do so, among several other things (2), also Negative Feedback is necessary. As we know from complex systems, nature, as well as artificial intelligence, the system becomes too greedy and instable.

For instance, on social insect societies know to be self-organized, Positive Feedback (PF) could be illustrated by pheromone reinforcement on trails, allowing the entire colony to exploit some past and present solutions. Generally, as in the above cases, positive feedback is imposed implicitly on the system and locally by each one of the constituent units, whereas Negative Feedback is imposed explicitly mainly by environmental “pressure” conditions, promoting counter-balanced innovative solutions. Fireflies flashing in synchrony follow the PF rule, “I signal when you signal”, fish traveling in schools abide by the rule, “I go where you go”, and so forth. In Humans, the “infectious” quality of a yawn of laughter is a familiar example of positive feedback of the form, “I do what you do”. Seeing a person yawning, or even just thinking of yawning, can trigger a yawn. There is however one associated risk, generally if Positive Feedback acts alone without the presence of Negative Feedbacks, which per si can play a critical role keeping under control this snowballing effect, providing inhibition to offset the amplification and helping to shape it into a particular pattern (2). Indeed, the amplifying nature of Positive Feedback means that it has the potential to produce destructive explosions or implosions in any process where it plays a role. Thus – several biological studies express it – the behavioral rule may be more complicated than initially suggested, possessing both an autocatalytic as well as an antagonistic aspect (2).

The fundamentalist ultra-liberal strategy of “no regulation at all”, followed in recent years, believing ideologically – like a fatwa – that markets are a truly Darwinian CAS (Complex Adaptive System) where invisible hands operate every day in a perfect situation, lead us to a chaotic situation, where shimmering waves of panic proliferate through the world (check video below), constraining states to intervene in a a posteriori manner (the ongoing Paulson Plan). Though, the ultimate best option was to do it a priori, ceasing nations to sleep much of their time earlier in face of many disastrous – out of control – innovative as well as cannibalistic financial products invented in the last decade (many of them being nothing else than financial pyramid schemes, though sophisticated), without reasoning of possible and profound dramatic social costs. Alternatively, a priori smart intervention seems to be the only resource to avoid the current ongoing privatization of profits, and immoral massive losses nationalization, being payed by tax contributors across USA and Europe. Keeping in reasonable shape the wealthy resource that finance markets really are and could be for all of us: promoting robust and innovative companies.

{ [VIDEO] Shimmering Giant Honeybees from Science News on Vimeo.
For some, Financial Markets in crisis could be seen as shimmering waves across the globe, however they are far from being self-organized as honeybee colonies. The invisible hand metaphor originates with Adam Smith in The Wealth of Nations (1776). Bernard Mandeville made a similar point with his Fable of the Bees (1705), which fancifully describes human society as a wondrously productive bee hive, even though each bee is as selfish as can be (3). – Video and article (see 8). }

Washington is right now asking for help and money to China, as well as indulging many other countries in the world to step in. At the same moment, in UK, in the aftermath of the Northern Rock takeover, some big and many medium companies are now selling themselves for short, in Belgium, FORTIS is on the verge, and in Ireland – once the first example of economic bloom in Europe -, the first technical ressence in many years is now fully recognized. France seems to go next. Partial-nationalizations are now occuring from Iceland to the sunny mediterranean Gibraltar. While, back in the US, a very recent LA Times-Bloomberg poll revealed that 60% of Americans claim for some sort of state intervention. In face of this facts, ultra liberals appeal to two typical arguments: (first) that the current phenomena is inevitable (no comments on my side on that, since 1929 till now nothing of this dimension happened before), and (second) markets evolve, some die and some prosper, forgetting however that markets are far from being perfect, and truly self-organized. The question is not if some die (which they should), the question is why the current system is not being able to self-control the proliferation of cheaters and pyramidal schemes on the entire pool of economic agents, in contrast to what happens in truly evolvable economic agents playing IPD or other economic-like games, showing profound traces of self-organized features. Sadly, among many of these if not all, ultra market liberalism evangelists, self-organization is wrongly recognized as self-interest (check 3). Self-interest taken to this limits, is not only their repeated mantra, used to quote “there ain’t those things as a free lunch” (NFL) over and over again as their blindness. NFL after all, is instead broadly recognized as being connected to robustness in computational search and optimization areas. Unfornately, they will never recognize that even under some complex co-evolutionary domains (nature is full of them; where explicit targets or interests were not embedded on the evolutionary algorithm), indeed free-lunches were found (5).

In fact, in order to emerge as a truly self-organized system, self-interest, should constitute just one among many of the ingredients over the entire financial system, and not the isolated unique ingredient. Self-interest promotes amplification and positive feedback, which is – as I recognize – necessary. However, left alone, promotes instead dramatic snowballing drifts over chaotic regimes, due to it’s intrinsic amplification. It’s necessary to promote negative feedbacks as well. This is recognized for some time in neurosciences, neurocomputation and learning (check LTD – long term synaptic depression) (6,7):

  • Learning by reinforcement good responses (Positive Feedback) is a process that by definition never stops. There is not an explicit rule that ends the reinforcement whenever the goal has been reached. On the other hand, if learning proceeds only by correcting mistakes it implies a process that stops as soon as the goal is achieved. This prevents formation of “deep holes“, i.e. highly stable states from which adaptation to new rules is difficult and slow, requiring, perhaps, a significant amount of random noise.
  • If an adaptive system is placed on a new environment, or otherwise subjected to learning something new, the likelihood of making mistakes is generally larger than the chance to be initially right. Therefore, the opportunity to shape synapses is larger for the adaptive mechanism that only relies on mistakes, leading to faster convergence.

Of course, being arrived here at this turmoil chaotic stage, we are nowadays assisting – ironically – to a dramatization of Bush’s Administration speeches. Bush words “Markets are not working properly” are indeed surprising from what we are used to expect from him, his office, as his known to be quite unusual words within his neo-liberal Haliburton centered – pro oil pro preemptive war – social networks (at VisualComplexity), however, subliminally he’s nothing else then reinforcing McCain’s election over Obama, as if great part of the actual crisis did not derived from the Republican past “I see nothing, I hear nothing and I say nothing” political strategy. Lying saying the truth, again ironically, this is the quickest formula to maintain things as they were before, the entire status quo going on, while markets in despair applaud –awkwardly – state interventions for the first time (or second to be precise – 1929; also check October 1907’s actions under J.P. Morgan). Being a liberal I have always believed that some ground-smart rules are always necessary. Let’s face it: even when we drive our car over a highway.

Take the following example. For some moments image yourself to puzzle out how to create a mathematical-algorithmic model on how a flock of birds fly in collective formation. You could on one hand try to model the dynamics of each part, using differential equations, in order to achieve somehow the global behaviour – however, the phenomena is so complex and intricate that differential equations could not handle it. On the other hand, you could try to observe the phenomena innumerable times while envisioning a set of rules, based on the behaviour of the whole system, however as is typical in Self-Organized complex phenomena’s there is no pre-commitment to any particular representational scheme: the desired behaviour is distributed and roughly specified simultaneously among many parts, and there is minimal specification of the mechanism required to generate that behaviour, i.e. the global behaviour mainly evolves from the many relations of multiple simple behaviours. Parts and wholes behave differently. Relations are the key. Surprisingly, and having self-organization theory in mind, you could envision 3, and just 3 simple generative rules following positive and negative feedback features that are able to precisely model this complex phenomena (check Boids): (one) Separation: steer to avoid crowding local flockmates, (two) Alignment: steer towards the average heading of local flockmates, and (three) Cohesion: steer to move toward the average position of local flockmates. Rather, non-linear phenomena are most appropriately treated by a synthetic approach, where synthesis means “the combining of separate elements or substances to form a coherent whole’. In non-linear systems, the parts must be treated in each other’s presence, rather than independently from one another, because they behave very differently in each other’s presence than we would expect from a study of the parts in isolation (4). In order to form the complex coherent whole, antagonistic measures are needed. Realistic counter-powers on the entire global economic TIC-TAC.

That’s why also, being a liberal, I defend a priori over a posteriori interventions. States, after all, were not created or envisioned to be omnipresent firefighters, specially to those few that under the 80-20 Pareto rule umbrella, profited before, month after month, with the current aftermath ([…] And so, my fellow Americans: ask not what your country can do for you – ask what you can do for your country […], John F. Kennedy). Not only Size is important (1) (critical mass) as well as Time, that is, over when should we lay down initial conditions in order to emerge the complex whole to flourish on the precise and desirable Self-Organized domain. Even better than nothing, as I believe, the current and late a posteriori state intervention will only endure the collective illusion for a while.

Not only have we recognized that markets are not perfect as Smith’s Invisible Hand metaphor seems to be dead wrong (3).  As David Sloan Wilson tackles it:

[..] I hope that our economy recovers, but the time has come to declare its guiding metaphor dead. This is the metaphor of the invisible hand, which makes it seem as if the narrow pursuit of self-interest miraculously results in a well-functioning society. […] The collapse of our economy for lack of regulation was preceded by the collapse of rational choice theory. It became clear that the single minimalistic principle of self-interest could not explain the length and breadth of human behavior. […] Mandeville could not have been more wrong about actual nature of bees. There is a difference between self-organization and self-interest. Beehives and other social insect colonies are indeed self-organized. There is no single bee commanding the troops, certainly not the queen. Each bee plays a limited role in the economy of the hive, just as a single neuron plays a limited role in the economy of the brain. The intelligence of both can be found in the interactions among the parts, which have been shaped by natural selection operating over countless generations. But bee behavior cannot be reduced to a single principle of self-interest, any more than human behavior. There are solid citizens and cheaters even among the bees, and the cheaters are held at bay only by a regulatory system called “policing” by the biologists who study them. […] We can argue at length about smart vs. dumb regulation but the concept of no regulation should be forever laid to rest. […]

Somehow, within the middle of countless wrecks, affecting innumerable millions of people thorough out the planet (even those not playing at the stock-exchange), via energy, tax, food and life cost raisings, we are still assisting at truly interesting phase-transition times. The question is: will we learn from it, or will we maintain the recent blind faith that markets, by themselves, will drive us all – similarly to communism – to the land of milk and honey?

  1. in Milgram, Bickerman and Berkowitz, “Note on the Drawing Power of Crowds of Different Size“, Journal of Personality and Social Psychology, Vol 13(2), Oct 1969, pp. 79-82. Abstract: Reports on the relationship between the size of a stimulus crowd, standing on a busy city street looking up at a building, and the response of passersby. As the size of the stimulus crowd was increased a greater proportion of passersby adopted the behavior of the crowd. Data included 1424 pedestrians. The results suggest a modification of the J. S. Coleman and J. James model of the size of free-forming groups to include a contagion assumption.
  2. in V. Ramos et al., “Social Cognitive Maps, Swarm Collective Perception and Distributed Search on Dynamic Landscapes“, 2007. Abstract: Swarm Intelligence (SI) is the property of a system whereby the collective behaviors of (unsophisticated) entities interacting locally with their environment cause coherent functional global patterns to emerge. SI provides a basis with wich it is possible to explore collective (or distributed) problem solving without centralized control or the provision of a globalmodel. To tackle the formation of a coherent socialcollective intelligence from individual behaviors, we discuss several concepts related to Self-Organization, Stigmergy and Social Foraging in animals. Then, in a more abstract level we suggest and stress the role played not only by the environmentalmedia as a driving force for societal learning, as well as by positive and negative feedbacks produced by the many interactions among agents. Finally, presenting a simple model based on the above features, we will adressthe collective adaptation of a socialcommunity to a cultural (environmental, contextual) or media informational dynamical landscape, represented here – for the purpose of different experiments – by several three-dimensional mathematical functions that suddenly change over time. Results indicate that the collective intelligence is able to cope and quickly adapt to unforseensituations even when over the same cooperative foraging period, the community is requested to deal with two different and contradictory purposes.
  3. in David Sloan Wilson, “The Invisible Hand is Dead. Long Live (Smart) Regulation“, in Axis of Logic, Sep. 2008.
  4. in V. Ramos, “On the Implicit and on the Artificial – Morphogenesis and Emergent Aesthetics in Autonomous Collective Systems“, in ARCHITOPIA Book, Art, Architecture and Science, INSTITUT D’ART CONTEMPORAIN, J.L. Maubant et al. (Eds.), pp. 25-57, Chapter 2, ISBN 2905985631 – EAN 9782905985637, France, Feb. 2002.
  5. in Wolpert, D.H., and Macready, W.G. (2005) “Coevolutionary free lunches,” IEEE Transactions on Evolutionary Computation, 9(6): 721-735.
  6. in Chialvo, D.R., Bak, P., “Learning from Mistakes“. Neuroscience, Vol. 90 (4), pp. 1137-1148, 1999.
  7. in  Bak, P., Chialvo, D.R., “Adaptive Learning by Extremal Dynamics and Negative Feedback“, Phys. Rev. E., Vol. 63, p. 031912, 2001.
  8. in Susan Gaidos, “Honeybees do the Wave“, in Science News, Web edition, Sep. 2008.

[...] People should learn how to play Lego with their minds. Concepts are building bricks [...] V. Ramos, 2002.

@ViRAms on Twitter

Archives

Blog Stats

  • 245,324 hits