Sunday, January 31, 2010

Haiti's Poverty, Jared Diamond, and Rogue Special Forces Operators

(post-earthquake ruins of Port-au-Prince Cathedral)

Why is Haiti so poor?

Having discussed earthquakes and the particularly high levels of death and destruction they bring to developing nations, it seems prudent to turn some attention to the latest, tragic case study in the genre: Haiti.

We know why, geologically speaking, Haiti was hit by an earthquake, and we also know that there is essentially nothing that mankind could have done to prevent that seismic event from occurring. However, the death toll would almost certainly not have been as high if Haiti had been a rich country with better building construction, emergency services, and public health systems. A very appropriate series of questions, then, is why Haiti is a developing country, how we can best make the disaster relief mission part of an ongoing policy that could help the country to recover, and, in the future, how Haiti might actually enjoy a sustained period of strong economic growth.

Jared Diamond, Haiti, and the Collapse of Complex Societies

(satellite imagery revealing massive deforestation in Haiti: Haiti is on the left side of the picture, the Dominican Republic is on the right, the border cuts through the center in a slash)

The author and academic Jared Diamond, whose Guns, Germs, and Steel certainly ranks among the best of the emerging "Big History" genre (David Christian's book is another excellent one, as is McNeil's The Human Web), turned his attention to the question of how some societies have managed to outstrip their resource bases and go into periods of (often surprisingly rapid) decline. One section of Collapse: How Societies Choose to Fail or Succeed deals with the question of how Haiti and the Dominican Republic, neighboring countries on the same island, have diverged in terms of relative economic growth paths and natural resource stewardship.

When the island of Hispaniola was first discovered by Columbus, it was populated by about 500,000 Arawak Indians. Within twenty years of the Spanish arrival and control of the island, that number would be cut down to less than 5,000. French swashbucklers would later settle on the western half of the island (the Spanish were more concentrated on the eastern half) and use it to conduct buccaneering operations against Spanish and English ships. As Spanish geopolitical power declined, the French presence would continue to expand, until ultimately a weary and cynical Spain granted France the western third of Hispaniola.

Interested in maintaining labor-intensive sugar cane farms and coffee plantations, the French brought in African slaves to work the fields in sufficiently large numbers that the area we now know as Haiti---then called Saint Domingue---was eventually responsible for nearly 25% of France's GDP.

*(if you want to read a very controversial book about the economics of the slave trade in the American Confederate South, pick up Robert Fogel's Time on The Cross).

Diamond notes that less than 1% of Haiti is still forested, compared with about 28% of the Dominican Republic. Many of Haiti's trees were cut down as lumber while the country was a French colony. The country's overpopulation problem---Haiti has 1/3 of the land mass of Hispaniola but 2/3 of the island's population----is also due to the colonial French and their need for large amounts of slave labor for sugar cane plantations.

The slaves, led by Toussaint L'Ouverture, Jean Jacques Dessalines, and Henri Christophe, ultimately managed to rebel and take back their freedom, defeating the French military forces using typical irregular warfare tactics. Defeat in Haiti may have led Napoleon to make the Louisiana Purchase deal with the United States.

Much as we saw in post-apartheid South Africa, a period of violence ensued, with whites killed and plantations destroyed. Unfortunately, there was no system of private property created in its wake; land tended go to "the Commons" or to small farms that were so far beneath scale as to be diseconomic, and we already know where these sorts of decisions can lead. The problem of deforestation also came into play, as it increased soil erosion and decreased the productivity of agriculture. Concerned with becoming another economically-enslaved colonial outpost, the Haitians made FDI (foreign direct investment) illegal, which in turn made it impossible for the country to accumulate capital for entrepreneurial deployment.

From 1843 to 1915, Haiti had 22 presidents. 21 of them were assassinated or forced from office by "extra-political means". The most stable political periods that Haiti has had have come with two of the most outrageously evil dictatorial regimes in recent history, those of "Papa Doc" and "Baby Doc" Duvalier. Haiti has never recovered from the "brain drain" that occurred when educated Haitians fled the country during the the Duvalier regimes.

Today, the vast majority of members of the population still try to survive on small-scale subsistence farming. Electricity, potable water, and sanitation were unavailable to the majority even before the recent earthquake, and most buildings were constructed of the kind of unreinforced, brittle masonry that becomes a deathtrap when hit by seismic surface waves.


In my opinion, the best entry point for someone interested in learning more about both macroeconomics and microeconomics is the development economics literature, because the books tend to be very applied and accessible due to the practical demands of the discipline. The non-specialist and/or multi-disciplinary reader will find more in the ways of clear policy stances and supporting arguments, conceptual models, and qualitative analytical frameworks there, and generally less of the highly technical mathematics (although regression analysis is heavily used and should be understood). I also believe that development economics, "Big History" (world history and anthropology filtered specifically to look for patterns and catalysts), evolutionary psychology, and applied game theory are the four academic disciplines that would most benefit a military or paramilitary operator tasked with counter-insurgency missions overseas.

There are three major macroeconomic growth models typically taught in university graduate programs for economics: Solow, Romer, and Lucas. Each won a Nobel Prize for its developer. The Solow model predicts a convergence between poor and rich countries because of the existence of a diminishing return to capital. In the beginning, capital does a great deal of good and growth is turbocharged; as an economy matures, capital accumulation does not have the same contribution and growth slows. Thus, development economics follows a kind of stylized S-curve, revealing that capital accumulation (limited by the savings rate, since savings fuels investment) benefits poor countries in dramatic ways, allowing them steep growth rates, but not doing as much for wealthy countries with mature economies. The problem with the Solow model is this: empirical reality in the post-colonial era has been that there is strong evidence of an accumulation quality to advantage, wherein wealthy countries enjoy an initial advantage and then proceed to get wealthier---poor countries do not seem to be catching up.

The Romer and Lucas models deal with the problems of the Solow model by adding more important roles for technological innovation on productivity growth, as well as human capital (skills gained from experience, education, and training). The most important single domestic policy aspect seems to be the formation of reliable institutions which can enforce private property rights at home. Internationally, the most important aspect is a commitment to free trade.

Schools of Development Economics

I believe that there are really three major schools of development economics, and each would probably prescribe a different solution for Haiti. For brevity, I would list the schools as:

1. The Sachs/Stiglitz
2. The Easterly/De Soto/Bueno de Mesquita (EDB)
3. The Collier

Going into significant detail on each of these schools and the personalities that have formed them would be a good topic for a future entry, but for now I would say that:

1. Sachs/Stiglitz has the most faith in top-down solutions brought forward by governments and NGOs (i.e., scenarios in which rich countries spend money on programs designed to help poorer countries), and this school has attained the greatest popularity among activist groups and celebrity advocates (Bono, Angelina Jolie, etc.). Of considerable importance to the Sachs/Stiglitz school is the concept of a "debt trap", in which the requirement to make crushing debt repayment installments makes it impossible for poor countries to apply their budgets towards activities and investments that would lead to economic growth in the future. Thus, Sachs/Stiglitz disciples frequently make debt forgiveness a core policy goal.

2. Easterly/De Soto/Bueno de Mesquita has the least amount of faith in top-down solutions (indeed, many programs are found to have negative effects), and a strong conviction that many development economic problems are ultimately caused by a combination of rapaciously bad governments and the trade protectionist policies of developed economies. This school is the most popular with free market libertarian types. It generally does not share the Sachs/Stiglitz optimism regarding debt relief, citing evidence that, in developing nations, budgets suddenly freed from disciplinary constraints frequently attract despotic thugs who wish to apply the new-found surplus to their own discretionary spending agendas (Lamborghinis, yachts, shoe collections, art, elaborate torture chambers, etc.).

3 The Collier school is somewhere in the middle of this continuum, choosing to concentrate on identifying a handful of individual "development traps" that, Professor Collier argues, make it very difficult for poor nations to pull themselves up by their own bootstraps (the traps themselves are basically a mixture of what the Sachs/Stiglitz and EDB schools feel are important: the "conflict trap", the "natural resource trap", the "landlocked with bad neighbors" trap, and the "bad governance in a small country" trap).

On the topic of Haiti, my supposition would be that two of the schools---Collier and the EDB---would agree that the central problem is one of bad governance (for a variety of reasons, the Sachs/Stiglitz school tends not to want to prioritize bad governance as a major factor). Between the Spanish, the French, and remarkably evil home-grown politicans, Haiti has suffered under one bad regime after another.

We can tick off Collier's other traps fairly quickly. Haiti may have a relatively high violent crime rate, but the country is not at war. It is certainly not landlocked. While we might count its role as a trans-shipment location for cocaine being exported from South America by aircraft and loaded onto ships for transport into the United States as a kind of resource (strategic location as a natural resource), Haiti does not have a so-called natural resource curse; if anything, deforestation has left the country with a lack of such gifts. However, Haiti does have an unnatural resource curse, and that curse is aid money that can be intercepted by corrupt leaders and used for their discretionary budgets.

The Natural Resource Curse: Further Explanation

Collier's other development traps are pretty much self-explanatory, but the natural resource curse is counter-intuitive and warrants a better explanation. It has long been known that countries that are blessed with abundant natural resources, such as oil, diamonds, and strategic metals, often do not develop broad, diversified, robust economies (the phenomenon is sometimes called "Dutch disease"). Instead, a competition for "rent-seeking" activities takes place, with various factions looking to gain access to the export cash. Governments frequently turn into kleptocracies that make deals with a foreign resource-extraction company and then reward themselves with the lion's share of the, say, oil revenues that the country receives. The government does not need to care about the rest of the economy because it does not require economic growth, innovation, or successful entrepreneurialism to provide its tax base; it just sells the country's natural resources, usually through a licensing arrangement with a foreign company, and then grows obscenely rich while the citizens of the country are left in bad shape.

Why don't the foreign resource-extraction companies insist that revenues paid to these governments go into institutions and programs that could help the local communities, rather than into the offshore bank accounts of kleptocrats? The main reason is that the resource-extraction companies are not equipped to conduct foreign policy: if a government has been recognized as legitimate by the United Nations, the corporation is going to deal with it on business terms*. In fact, an attempt to impose additional conditions in a competitive bidding scenario may lead to the "moral" company simply losing out to one that does not have such scruples. This has been precisely the case with many Chinese resource-extraction deals in Africa (the Chinese negotiators tend to have an attractive "no questions asked" policy, as well as deep pocketbooks).

One of the major contributions that Bill Easterly and Bruce Bueno de Mesquita have made to the study of development economics is in examining how foreign aid money can create an artificial resource curse. Rather than relying on oil or strategic metal exports and self-serving deals with resource-extraction companies, kleptocrats seek to gain access to foreign aid money through donor projects that naively try to "work through host governments". Once again, we find that concentrated power and top-down, centralized economic planning are the friends of both the social engineer/optimist and the tyrant.

*(As an aside, I can lend an anecdote to punctuate this story of how resource-extraction projects may not be the source of local jobs that one might expect them to be. Back in 2002, my business partner and I, along with Oxford colleagues Jim Sosnicky and Alisher Djumanov, spent a couple of months putting together a study for Lazard Freres. The study focused on the Caspian region of Central Asia and possibilities for a private-equity fund that could profit from growth in Caspian basin oil extraction, more specifically by investing in local oil service support-oriented businesses located in Azerbaijan and Kazakhstan. Our investment thesis was that the oil industry would create spillover effects that benefited local businesses, and an investment vehicle could identify the most promising of these businesses and take equity positions in them.

(What we found, among other things, was that the resource-extraction companies often do have a certain amount of "local content" labor and business support that they are meant to hire and use as part of their deals with these governments, but the oil and oil services firms are so self-sufficient and their operations so systematized that the companies frequently end up complaining that the local-content requirements are basically just a tax and nuisance. It would be more efficient for the companies to just come in, set up shop using only their own personnel, and go to work (it obviously does not help that the "local content" businesses that the oil companies are forced to hire are frequently overseen by relatives and close friends of host government officials, who are simply interested in earning passive economic rents).

(We surmised that a private equity manager with expertise in both resource-extraction industry needs and the local business environment---and a very high level of competence navigating the treacherous waters of political risk and emerging market company valuation techniques---could probably generate a significant profit stream by intermediating himself or herself in the situation, allowing the resource-extraction companies to simply pay into a development fund--we termed it "the Caspian Trust"--- and then return to their core projects ((where they could now presumably work unmolested, having met their legal local-content hiring requirements)). An alternative for a manager with considerable moral flexibility would be to invest in Western-style restaurants, hotels, bars, and possibly other, darker "hospitality" businesses adjacent to the oil projects, and to generate profits from the oil rig workers' appetites for discretionary spending on evening and weekend entertainment).

Developing Haiti

Turning our attention back to Haiti, the Sachs/Stiglitz advocates would probably push for increased funding of medical, education, and technical assistance programs as a way to help the Haitians. The EDB school (and probably the Collier), on the other hand, would primarily focus on how the Haitian government's corruption has discouraged foreign direct investment (FDI) and capital formation.

Continuing that exploration, the "Lucas Paradox", which examines why capital does not flow efficiently from rich to poor countries (as would normally be expected given the higher growth rates and investment returns---the favorable position on that "S" curve of diminishing returns to capital that we discussed earlier---that the models anticipate being achieved in emerging markets), would come into play. Lucas considered how political risks---corruption, nationalization, populist uprisings, military coups, and so on---could create so much uncertainty in investment decisions that the required discount rates for valuing poor country projects become so high that the whole investment climate is categorized as prohibitively risky.

EDB would also look at scaling up coffee and sugar export capacity, and would view sugar subsidy programs in the U.S.---which have the effect of creating a steep tariff on sugar imported from a place like Haiti---as an obvious place to start.

Several international aid groups have come to agree with the EDB assessment, and to disagree with a generalized Sachs/Stiglitz-type of donor-centric prescription for Haiti's woes: Haiti has been participating in International Monetary Fund (IMF) loan arrangements for 36 of the past 50 years, with virtually no discernible gain. In fact, foreign aid may have had a net negative effect because it may have, as Bueno de Mesquita and Easterly frequently argue, made bad governance more profitable.

In their book Fixing Failed States, authors Ashraf Ghani and Clare Lockhart note that "In Haiti, the aid system has been forced to acknowledge its adverse impact on the state...a paper by the U.S. National Academy of Public Administration aptly named 'Why Foreign Aid to Haiti Failed' seeks to explain 'why, after consuming billions in foreign aid over more than three decades, and hundreds of millions specifically for governance and democratization programs, not to mention billions for other programs, Haiti remains politically dysfunctional and improverished.' While laying the blame squarely at the door of poor governance in the country, it describes how aid has made either little impact or has had an adverse impact on governance."

The NAPA paper runs about 50 pages or so of quite interesting comments and analysis, and can be downloaded/printed from this link:

My faithful guide from The Economist states that the Haitian economy consists of 40% services (mostly tourism), 27% agricultural products (coffee, mangoes, sugar cane), 8% industry, and 25% "other". There may be a way to monetize sympathy for the Haitians through marketing gimmicks like, say, a "Fair Trade Coffee for Haiti Relief" initiative that obtains a price premium, but such an effort will A) likely not be sustained, and B)not produce great benefits to the Haitians for some microeconomic reasons that I will explore in a future post on the serious problems with "Fair Trade" coffee and similar products.

As I fall squarely in the EDB camp, my own feeling is that the best things that the U.S. government can do for Haiti in regards to ongoing, post-disaster policy would be to give the country the most favorable trade terms that we can, and---possibly---to look at fresh and innovative ways to support foreign direct investment in terms of coffee, sugar cane, and tourism projects. A more ambitious goal would be to somehow create functional socioeconomic and political institutions in the country, but experience has proven that this generally must be a bottom-up, emergent process rather than the result of a top-down policy plan.

(tourists bask in the sun on Haitian beach)

Killing Tyrants: The problem of removing bad leaders

Unfortunately, any aid or trade support efforts will be futile if Haiti ends up being run by another feral dictator. The question of what to do about bad governance is a very difficult one for development economists, because ultimately one runs into the issue of regime change, of a policy regarding the removal of a corrupt leader by force. In Haiti and in other countries, the "you-break-it/you-own-it" nature of regime change intervention always runs the risk of creating long-term dependency, even of making the target country become the de facto 51st State.

Knowing that a nation's core problem is a bad governance structure thus makes for frustration and extreme sensitivity to the current political climate for risk appetite, because the only prescriptions that have even a moderately good chance of working are invasive (literally) and very dangerous. Regime-change and stabilization missions in Haiti have been attempted by the U.S. military a few times in the past, and this leads us to a tangential discussion of an interesting man named Stan Goff.

Stan Goff's Hideous Dream

(anti-war activist and author Stan Goff, pictured on the left, served with the most elite units of the Army's special operations community---including the one popularly known by a name that starts with the letter 'D')

From the U.S. State Department: In December 1990, Jean-Bertrand Aristide won 67% of the vote in a presidential election that international observers deemed largely free and fair. Aristide took office on February 7, 1991, but was overthrown that September in a violent coup led by army elements and supported by many of the country's economic elite. The coup contributed to a large-scale exodus of Haitians by boat. From October 1991 to September 1994 a de facto military regime governed Haiti. Several thousand Haitians may have been killed during the de facto military rule. Various OAS and UN initiatives to end the political crisis through the peaceful restoration of the constitutionally elected government failed. On July 31, 1994, the UN Security Council adopted Resolution 940, which authorized member states to use all necessary means to facilitate the departure of Haiti's military leadership and to restore Haiti's constitutionally elected government to power.

The United States took the lead in forming a multinational force (MNF) to carry out the UN's mandate by means of a military intervention. In mid-September, with U.S. troops prepared to enter Haiti by force, Gen. Raoul Cedras and other top leaders agreed to accept the intervention of the MNF. On September 19, 1994, the first contingents of what became a 21,000-member international force touched down in Haiti to oversee the end of military rule and the restoration of the constitutional government. President Aristide and other elected officials in exile returned on October 15.


For me, one of the most fun aspects of having a blog is the opportunity to introduce colorful, interesting characters into a larger narrative. While pursuing this will involve rambling away from the development economics theme, I don't think a discussion of U.S. relief efforts in Haiti would be complete without mentioning a memoir critical of a previous U.S. intervention in the country, Hideous Dream, that was written by the enigmatic Stan Goff, a former professional soldier in the most elite units of the U.S. Army.

Goff deployed to Haiti in 1994 (the same year that I went through BUD/S) as the team sergeant for a Special Forces MFF (Military Freefall-parachuting-designated) operational detachment. At that point, he already had a military career behind him that read like something from a Sergeant Rock comic: previous deployments to Vietnam, Guatemala, El Salvador, Grenada, Panama, Venezuela, Honduras, South Korea, Colombia, Peru, and Somalia; squad leader in the 82nd Airborne and the Ranger Regiment, patrolling instructor at the Jungle Operations Training Center in Panama, assaulter-then-sniper during four years with the Army's most prestigious and secretive combat unit (which I will refer to simply as "D"), Military Science instructor at West Point, break-in service to train Department of Energy SWAT-type units (the same organizations that produced multi-time 3-Gun competition champion Bennie Cooley, one of the best shooting instructors I have ever had), Ranger Regiment platoon sergeant, Special Forces 18-Delta (medical sergeant) on a team from 7th Special Forces Group, Regimental Special Forces Medic at the Ranger Regiment.

Since retiring from the Army, Goff has become a neo-Marxist, or at least a hardcore statist-collectivist, and a well-known anti-war activist. An articulate writer with an adroit turn-of-phrase and command of a variety of post-modernist social critiques ("gender is just a social construction" type stuff), Goff seems to have been building an explanatory historical narrative of class warfare and institutionalized racism even before the Haiti deployment, and his experiences there certainly pushed him further to the political left.

I don't find Goff to be particularly unpatriotic, although I am sure that this is the standard trope brought out to criticize him (I am naturally suspicious of arguments that use this rhetorical gimmick, anyway). In some ways, Goff simply follows the dissenting tradition of a legendary figure named Smedley Butler, the Marine Corps senior officer who was twice awarded the Medal of Honor (!) before retiring to write War is a Racket, a scathing critique of U.S. military intervention overseas.

Interestingly, Butler had also been involved in operations in Haiti (in 1915---he was recommended for his second Medal of Honor after leading a combat mission in which 200 Caco rebels were killed at the cost of a single Marine being hit in the mouth with a rock and losing some teeth). He was later court-martialed for having made disparaging public remarks about Benito Mussolini (in the early 1930s, when such remarks were not politically acceptable), and his life inspired several fictional characters, including the fire-breathing Marine general-turned-mutineer portrayed by Ed Harris in the movie The Rock.

Major General Smedley Butler, USMC
"The flag follows the dollar...and the troops follow the flag."

After he retired, Butler became quite outspoken, as evidenced by the following (perhaps his best-known and most provocative quote): "I spent 33 years and four months in active military service and during that period I spent most of my time as a high class thug for Big Business, for Wall Street and the bankers. In short, I was a racketeer, a gangster for capitalism. I helped make Mexico and especially Tampico safe for American oil interests in 1914. I helped make Haiti and Cuba a decent place for the National City Bank boys to collect revenues in. I helped in the raping of half a dozen Central American republics for the benefit of Wall Street. I helped purify Nicaragua for the International Banking House of Brown Brothers in 1902-1912. I brought light to the Dominican Republic for the American sugar interests in 1916. I helped make Honduras right for the American fruit companies in 1903. In China in 1927 I helped see to it that Standard Oil went on its way unmolested. Looking back on it, I might have given Al Capone a few hints. The best he could do was to operate his racket in three districts. I operated on three continents."

I think that one has to respect the military achievements of men like Butler and Goff, and has to take seriously the factors that could lead to such individuals becoming so utterly disillusioned (my speculation is that they have to somehow reduce cognitive dissonance). Clearly many of us ultimately want the very same things---freedom from tyranny (defined in different ways), dignity for the individual, the right to self-expression and the pursuit of personal dreams. I myself have a number of conciliatory thoughts when I read Goff's books. And yet, at the same time, I am baffled by Goff's politics and economics. I do not believe the central Marxist notions of collectivist central planning and its attendant "pure labor" theory of value are serviceable, and I think that attempting to make such a system work ends up creating just the kind of militant, jingoistic totalitarian monster that Goff rails against (a monster that will be biased towards imperialism abroad because it will face endogenous economic growth problems at home, largely due to the Marxist model's lack of a decentralized, dynamic market clearing price-discovery mechanism).

Furthermore, military adventurism in support of corporate profits, if existing in the virulent form claimed by Goff and Butler, would be a case of something that Public Choice theorists and Austrian economists term "regulatory capture" (this important issue will be the subject of an upcoming blog entry). Regulatory capture makes an argument in favor of a more limited, specifically-outlined role for government, rather than an expanded, more invasive one.

These comments aside, Goff's book contains some observations and anecdotes about life in the military that are well worth reading, regardless of one's economic preferences. The reader can develop an appreciation for the demands of the warrior life. For example, Goff describes the team's rigorous pre-Haiti deployment training---the team is originally tasked with a freefall parachute insertion into Haiti, followed by the execution of a special reconnaissance (SR) mission---in some detail: "We ran for maximum intensity, four to six miles four days a week, some of us kicking out six-minute miles. We carried 85 pounds of weight for our training marches, five miles in one hour and fifteen minutes over sandy logging roads every Monday morning. We lifted weights before lunch. We quit wearing jumpsuits and skydiving, electing instead to jump in battle fatigues and combat equipment, mostly at night, a significant increase in discomfort, risk, and training value. We re-trained virtually every battle drill, using nothing but tried and true, simple and rugged, light infantry tactics. We trained in stalking skills, photography, marksmanship. We established SOPs for uniform, equipment, and deployment procedures. We conducted field layouts, almost unheard of at the team level in a Special Forces Group. Our training tempo was the highest we saw anywhere in the Group, and the focus of that training was Back-to-Basics through repetition."

I particularly liked his insights regarding how the detachment commander and team sergeant of an ODA can lose control of the team if a critical mass of anti-authority personality types is able to build, which is an interesting observation because Goff clearly harbors maverick, anti-authoritarian beliefs of his own.

One of the things I found striking in his account was his creation of an atmosphere in which the questioning of superiors is an appropriate preoccupation, at least for a warrior-scholar like Goff, but his being questioned by subordinates could represent an affront, a disciplinary problem. I think this asymmetry stems from a kind of intellectual elitism and is is probably a natural tendency that can arise whenever a highly qualified, well-read analyst like Goff is put in a middle-management position. The selection and training programs that Goff survived, multiple times, are among the most difficult in the world and are designed to create a supremely confident and disciplined individual. The ability to focus can easily be self-directed towards autodidactic pursuits that the military may or may not prefer.

I also believe that senior enlisted men who serve as operators in the classified world of the national Special Mission Units (SMUs---the Army's D and the Navy's equivalent), but then rotate back to serve in "vanilla" elite units (normally Special Forces or regular SEAL Teams), can occasionally make life quite difficult for their officers. Goff and others of his species become accustomed to the high levels of autonomy, tolerance for individual eccentricities, informality, and meritocratic, borderline anarchist decision-making processes that the SMUs enjoy, and may bring this back with them to situations that do not feature the same cultural dynamics. Junior officers are appropriately impressed, probably even intimidated, and may end up deferring to the ex-SMU NCOs---perhaps to such an extent that it ends up compromising the officers' own authority. Men like Goff can make or break officers, and they usually have to make a conscious decision to support the officers by enforcing standards of "conventional" military professionalism.

(members of the Army's secretive and prestigious Special Mission Unit on deployment in Afghanistan)

Any junior officer, particularly one serving in a special warfare organization, could probably benefit from reading a few sections of Hideous Dream, as they present some prototypical issues that will invariably come up: "Kyle epitomized many of the criticisms I had of Special Forces. He was ignorant of doctrine and pretended he was superior to it, a case of buying into the SF mystique. He was more concerned with how he looked than how he performed. He assumed because he understood the engineering part of his job that he was exempt from other 'soldier' skills and tasks. He felt he was entitled to higher levels of comfort than conventionals and Rangers---that the austerity they endured was for the simple-minded and not for the 'special' people like Green Berets. From my first days on the job, he had resented my opposition to that sense of entitlement, and my insistence on mastery of basic military doctrine as the foundation for conducting 'special' operations. I hated the mystique. So our antagonism, while never loud and open, was early and consistent." I believe the problems that Goff raises here are fairly commonplace in elite units, but found in their most pure forms within the private military contractor (PMC) community.

Goff also adds local color by giving a brief discussion of his association with a man named Marshall Brown while both men were members of "D", the Army's SMU. A highly respected member of that elite group, Brown apparently went through a period of extreme Christian fundamentalism---there was a Born Again movement within the unit at one time, highlighted by William Boykin (Boykin came into the media spotlight recently when he, as a 3-star, allegedly made public comments casting the military operations in Iraq and Afghanistan in Biblical terms)---before later becoming an infamous serial rapist. This is an insane story in itself; for a more detailed account of Brown's military background and a related psychological study, heavy on the post-modernist/anti-patriarchal society literature references, here is Goff's essay on the topic at "Freedom Road" (apparently some kind of socialist enthusiasm site): ).

The central theme of Hideous Dream is that an existing culture of racism, largely kept from the public eye, infested the special operations community and made it very difficult for deployed units to develop the pathos, the empathic rapport, with the black population in Haiti. This rapport was necessary for effective humanitarian efforts and "nation-building" to take place. Goff gives many anecdotes in support of this claim, but here is just one, from early in the book before the team deploys to Haiti: "The man making the (racist) comment was Sergeant First Class Frank Kelly, the team sergeant for the detachment across the hall. On his team wall, he posted the 'Murc Map', after the local diminutive for Murchison Road, where a high concentration of the black citizens of Fayetteville lived. Frank scanned the paper for crime stories, and when he found crimes committed in the black neighborhoods, he pushed a colored map pin into the site. This was Frank's way, with the help of his team, of demonstrating his stated belief that blacks are innately criminal..."

In other instance, a member of Goff's ODA who had worked among the Haitian population for some time was advised that thousands of Haitian children would die of HIV/AIDS. His response: "Good."

Goff finds that racism is used to create a form of "in-group vs. out-group" camaraderie in some units, with jokes and stereotypes employed, even by relatively educated individuals, to build rapport among team members according to a kind of lowest-common denominator principle (i.e., as a kind of populist appeal that works because of the socio-economic demographic of the target audience). At times, argues Goff, this goes beyond ethical malfeasance and leads to tactical generalizations on the ground in Haiti that risk alienating the local population and increasing the risk of mission failure. Many of the men come to abhor aspects of the Haiti mission, which certainly does involve physical privation, ambiguity, and stress, and to also begin to abhor the Haitians themselves.

Although I cannot imagine him being against the U.S. military humanitarian aid/disaster relief mission in the wake of the earthquake tragedy in Haiti, I believe that Goff would predict that some very real problems between operational units and local communities will begin to reveal themselves if the disaster creates true political displacements, causing U.S. troops stay for extended "nation-building" operations. Haiti is, in many ways, a failed state, and comparisons with the Somalia debacle are probably going to be inevitable.


As I was writing this and thought of Stan Goff, Smedley Butler, and the events that seem to continually besiege poor Haiti, a particularly appropriate song happened to be playing on my iPod and I found it unexpectedly quite moving. For some utterly emotional reason, the live video clip of it, sung by a master, seemed like a good way to close today's entry.

Wednesday, January 27, 2010

Disaster Prediction, Trading Strategies, the Fall of Rome, and Volcanic Sunsets

(Turner, the Fighting 'Téméraire' tugged to her last Berth to be broken up)

"It was decided by the university of Coimbre that the sight of several persons being slowly burned in great ceremony is an infallible secret for preventing earthquakes."
- Voltaire, Candide

Predicting Earthquakes: Discouraging Results

Unlike volcanic eruptions, which do normally provide warning signs prior to becoming violent, earthquakes offer little in the way of forecasting aids. According to the "Self-Organizing Criticality" theory described in the previous post, the initial difference between the cause of a small earthquake and a large one may be surprisingly minor and technical. The problem is that while it is understood that seismic waves nucleate at the focus of the earthquake, the microstructure of the 'quake involves sharp, sudden events that occur without warning.

As a result, much of the work on earthquake prediction has attempted to find macro patterns in the data rather than to attempt to find ways to monitor the activities within the earth and determine when and where a major earthquake is going to take place. The goal is to find areas that may have achieved a critical stage and become sensitive, particularly if those areas are close to large human settlements.

As we know, earthquakes are statistically fractal, and follow a power law distribution. In any given year, there are about 1200 magnitude 5 earthquakes, 120 magnitude 6, 12 magnitude 7, and 1 magnitude 8. In other words, there is a magnitude 6 earthquake somewhere in the world every 3 days. The largest earthquake in a given year can release more energy than all of the other earthquakes that year combined. The central problems of earthquake prediction are that: 1) there is little in the way of a pattern of repeatable pre-quake behavior that could be used as a warning system, and 2) what limited evidence we do have does not allow us to distinguish between the pre-destruction activity of, say, a magnitude 8 earthquake and a magnitude 5 earthquake.

Earthquakes and Trading Strategies

For our purposes here, I will decompose the topic of "prediction" into three different levels of forecasting precision:

-Category 1: true prediction. This means being able to determine, in advance, when and where a major earthquake will take place.

The investment or trading equivalent would be able to state that a given company's stock price was undervalued and would increase to "fair value"---however that was determined---by a given date.

-Category 2: probabilistic edge. This means being able to gain a measurable performance advantage by being able to determine when and where a major earthquake is more likely to occur. Having a probabilistic edge would mean being able to commit a larger percentage of scarce resources to that area in advance.

The investment equivalent of this would be a generalized "market timing" approach that gradually deploys portfolio resources into, say, the S&P 500 and Hang Seng Index, and away from the Nikkei, because a forecasting model or valuation model has computed that there is an increased likelihood of the US and Chinese equity markets outperforming---relative to Japanese stocks---in the future (although a precise start date for this is unknown and errors could be large, the model tells you to be "overweight" the US and China markets and "underweight" Japan. It is essentially a resource-shifting, long-term allocation model, rather than a more dynamic approach that moves completely in and out of the markets on shorter time frames to try to capture discrete moves).

Category 3: agile reaction. This approach essentially gives up on 1 and 2 and tries to simply react to earthquakes as they occur, in real-time, as efficiently as possible. Efforts are made to decentralize operations in order to exploit opportunities (one of the tenets of Maneuver Warfare Theory), and to rehearse what the military calls immediate-action drills: pre-choreographed, codified response procedures---usually for emergencies and other truly decisive, time-sensitive situations---that have been designed to make the best use of information as soon as it emerges from the tactical environment.

The Evidence

In both earthquake and market prediction efforts, there is little evidence that Category 1---true prediction---is consistently possible. Indeed, an analyst can basically get one prediction right by sheer luck and then fall victim to post-dictive claims of having an extremely sophisticated approach (either because of a general vulnerability to the fundamental attribution error or because of a more cynical desire to capitalize on a lucky call and generate advisory fees from it). Geophysicists and geologists who study earthquakes professionally have basically given up on Category 1 prediction.

Category 2 fares a bit better. For example, we know that a major, seismically active subduction factory on the Pacific rim---the Indonesian archipelago, basically---has historically generated many of the most spectacular and dangerous earthquakes and volcanic eruptions. We do not know when, precisely where, or how big another natural disaster will strike the region, but we do have enough knowledge of the system to be able to predict that concerned parties should probably shift an above-average resource weighting to the region. This may sound intuitive, but it could actually save many lives to have disaster-relief assets forward-deployed in the region when another calamity occurs. The world is just too big to try to adequately cover disaster contingencies everywhere at the same time. As Frederick the Great warned: "By trying to defend everything, he defended nothing."

Category 3 is where much of the action in earthquake management can be found. The network of seismic detectors placed all over the world---as previously discussed, this was originally built for monitoring underground nuclear weapon tests---can give immediate data regarding a significant earthquake. How this data is operationalized will vary from region to region: for instance, tsunamis, or seismic sea waves, can be tracked in real-time and evacuation plans can be executed because tsunamis travel slow enough for it to do a lot of good (tsunamis move at about 500 miles per hour). When a tsunami has to cross a vast expanse of open ocean, the real-time tracking may give occupants of a targeted shoreline many hours to move to higher ground and prepare for flooding. In Japan, systems have been put in place to shut off gas valves, stop trains, and even send alert texts to individual cell phones when seismic detectors are tiggered, and companies regularly conduct drills for earthquake evacuation from buildings.

In terms of the financial markets, there is some compelling evidence that Category 3 methods---which are typically classified as "time-series forecasting" or "statistical extrapolation algorithms"---consistently outperform analysts who attempt to employ Category 1 and Category 2 prediction approaches. I will save this discussion for a future date.

Mean-Reversion and Trendfollowing in Earthquakes and Markets

A construction called elastic rebound theory puts forth the argument that stresses underground will build for relatively fixed periods of time and then will have to be released. Unfortunately, there is not a lot of evidence that earthquakes offer periodicities that can be used to gain a substantive edge. Similarly, studies of financial market periods---from annual "calendar effects" to 4-5 year business cycles to much longer Kondratieff Waves---have generally not uncovered applications of great practical use (with a few notable exceptions). However, there are some interesting ideas out there regarding the increased likelihood of earthquakes being more likely to occur at particular nodes along known fault lines.

For instance, the seismic gap hypothesis is a mean-reversion theory: it forecasts that the most likely place for a future earthquake is in a place along a fault that has not had an earthquake yet. There is a saying among traders that market "gaps get filled", and this is precisely what the seismic gap hypothesis argues. Such a gap analysis of, say, the San Andreas fault in California would reveal that the next major earthquake gap destined to be filled is, unfortunately, directly under the city of San Francisco.

A trader who employs this type of mean-reversion strategy bets that an elastic band connects the market's current price to its historical norm---if the price diverges too far from the norm, which is usually considered some kind of fair-value "equilibrium" price for the asset, a gap between current price and true value will form and the elastic band can be expected to yank it back. Thus, mean-reversion traders will tend to buy weakness and sell strength.

In contrast to the seismic gap hypothesis, other models of earthquake prediction suggest that the most likely place for future earthquakes is where earthquakes have tended to take place in the past: earthquakes in one location tend to be followed by more earthquakes in the same location, as the first earthquake may stress and weaken a fault area so that others can occur.

Similarly, a trader who employs a trendfollowing strategy bets that the term "historical norm" may be meaningless because markets evolve over time. Prices may diverge for any number of reasons, and may not return to a past, theoretical-equilibrium level for an extended period...if ever. Gaps may not get filled. Thus, these types of traders will tend to buy strength and sell weakness to position themselves within emerging trends.

The "earthquake trends" hypothesis may not, in fact, be directly opposed to the hypothesis of seismic gaps, because it is possible that they simply operate at different scales. Perhaps, in a larger-scale sense, major earthquakes do cluster, or trend, in certain regions of the world. It may be also true that, within those regions (i.e., at a more localized scale), earthquakes tend to fill local gaps. At an even high frequency scale, we can find trending behavior yet again---a major earthquake will produce aftershocks, or smaller earthquakes in the immediate vicinity, for days or even weeks.

There is no clear "winner" in the seismic gaps vs. trending prediction contest. Both sides can claim winners and losers.

We can similarly observe that both mean-reversion and trendfollowing trading strategies can be profitable in different macroeconomic environments. The two trading approaches have different return profiles---mean-reversion works most of the time and generates small winners, but has large and sudden losses when it stops working; trendfollowing generates small losses more than 50% of the time, but has large winners when it starts up again. Assuming that the mean-reversion strategies have proper risk controls in place and do not heavily engage in the martingale betting styles that have been previously discussed, both of these approaches can be quite profitable---can have "positive mathematical expectancy"---over adequate holding periods.

In much the same way as opposing earthquake prediction theories may perhaps be reconciled by adjusting the resolution to look at different scales, it appears that market trend approaches can make money at very short (seconds or minutes) and very long (weeks and months)time scales, while mean-reversion trading strategies may operate successfully at different frequencies.

Animals and Earthquake Detection

(can snakes, like this rather elegant King Cobra, predict earthquakes?)

There are anecdotal reports that some animals have the innate ability to predict earthquakes, and that they will begin behaving erratically prior to these and other natural disasters. The Chinese have probably done the most extensive research in this area (China has good reason to be motivated, given that earthquakes in China in 1920, 1927, 1932, and 1975 each killed over 100,000 people, and one in the 1500s killed over 800,000). To date, no evidence of a consistent earthquake prediction capability in wolves, snakes, chickens, and so on has been found.

It is possible, although of little practical utility for humans looking to escape earthquakes, that animals with higher sensory acuities may be able to detect P waves, which reach the surface from the earthquake foci before S waves do and are beyond the threshold of human sensory detection (seismometers detect them for us). It seems likely, given the highly irregular natural selection pressure posed by earthquakes, that any animal earthquake-detection ability would be a secondary benefit---a fortunate by-product---of another, more routinely useful, evolved system, perhaps one used for predation, escape, or navigation.

From the USGS: "Is it reasonable for a seismic-escape behavior pattern to evolve, and can such a genetic system be maintained in the face of selection pressures operating on the time scales of damaging seismic events? All animals instinctively respond to escape from predators and to preserve their lives. A wide variety of vertebrates already express 'early warning' behaviors that we understand for other types of events, so it’s possible that a seismic-escape response could have evolved from this already-existing genetic predisposal. An instinctive response following a P-wave seconds before a larger S wave is not a 'huge leap', so to speak, but what about other precursors that may occur days or weeks before an earthquake that we don’t yet know about? If in fact there are precursors to a significant earthquake that we have yet to learn about (such as ground tilting, groundwater changes, electrical or magnetic field variations), indeed it’s possible that some animals could sense these signals and connect the perception with an impending earthquake."

Development Economics and Natural Disaster Vulnerability

Besides the magnitude of the earthquake itself and the destructive energy that is released on the surface, the other reliable factor in assessing the casualty rates of quakes is the economic status of the region that is hit. Simply put, earthquakes hit the urban centers of developing economies very, very hard. The combination of weak building construction techniques and large populations makes for high casualty rates.

In California, to cite an example of a place where advanced earthquake-resistant construction technology is being employed, structures are basically bolted to their foundations (rather than just built on top of them). In contrast, a building just built on a free foundation slab---as is common in developing nations---can react very badly if hit by a high-amplitude Love or Rayleigh wave---the effect is something like what happens when a would-be prankster pulls a rug out from under the feet of his victim.

Another general rule seems to be that buildings constructed on bedrock fare better than those constructed on top of sedimentary deposits, which shift very violently during earthquakes. One of the reasons why a relatively low-power earthquake was able to wreak havoc in Mexico City in 1985 is because much of that city's metropolitan area was built on what is basically an ancient lakebed.

There are various advanced construction mechanisms that involve springs and buffer contraptions used to decouple the motion of a building from the motion of the ground during an earthquake, and advanced economies are experimenting with them. An intriguing problem presents itself because the damage that a building sustains in an earthquake may sometimes have more to do with frequencies than with magnitudes: a building that could withstand a magnitude 8 earthquake may collapse to a magnitude 7 if the building naturally resonates at the same frequency as the ground shakes do, and a self-reinforcing feedback loop of harmonic resonance occurs.

As stated in a previous blog post, earthquakes often cause uncontrollable fires: 140,000 people were burned to death when firestorms raged through Tokyo after the earthquake that hit Japan in 1923. Gas pipes are broken and power lines are brought down, causing fires to start, while at the same time the earthquakes attack water mains, disrupting fire-containment efforts. Developing economies may be at particular risk because fire and emergency services personnel may be chronically underfunded, flammable materials may be strewn everywhere, and fire codes may be nonexistent.

Earthquakes, Sanitation, and Disease

Even after the death and destruction caused by building collapse, fire, tsunami, and land slides have occurred, a developing region hit by an earthquake may face yet another public health crisis. Lack of clean water is a problem in developing regions during the best of times: you really see how water procurement needs affect the economic landscape when you travel to a relatively desolate region of the developing world. I can recall driving around in an NGO-marked Toyota Land Cruiser and touring some aid projects in remote areas of Tanzania with an AMREF mission. We would see women and girls walking for miles and miles on the sides of the dirt roads, forming long processions, to procure water and bring it back in the large, heavy-looking containers they balanced on their heads. This activity took up most of their days, every day, because the demand for water is unrelenting (when 50% of your workforce is unable to pursue education or employment because it is tasked with endless, manual water-transport duties, your economy will clearly suffer a productivity constraint).

Stated simply, refugee camps and forced migration facilities that are put in place after natural disasters such as earthquakes become virtual Petris dishes for infectious disease. Lack of sanitation, water, electricity, and sterile medical instruments, combined with packed living conditions, lead to outbreaks of everything from cholera, polio, and meningitis to HIV/AIDS and Ebola. Drinking supplies quickly become contaminated and it can be months before all of the contamination sources can be discovered. Once again, the higher population densities of urban areas makes for more difficult disaster relief efforts, as facilities that can offer adequate space, restrooms, and hospital beds simply may not be available.

(One possible component of humanitarian-relief efforts, at least in coastal regions, would be ships that are designated as dedicated "water factories"---basically mobile desalination and purification plants capable of producing large amounts of potable water from seawater, and then piping it to stations onshore for distribution via trucks or some other method. If the reader is interested in getting a great overview of the science, logistics, and politics of human waste removal, surely an unpleasant but critical aspect of public health, I recommend a book called The Big Necessity by Rose George).

The Catastrophe of David Keys

(Arnold Bocklin, The Plague)

The discussion of disease outbreaks following natural disasters is not limited to those illnesses that may result from poor sanitary conditions within refugee camps. One potential, quite serious source of contagion is unleashed when an earthquake or volcano disrupts a stable "pathogen reservoir", an area in which a potentially deadly microorganism has been contained by natural forces (usually the reservoir consists of animal hosts that are not hurt by the pathogen, presumably because of a symbiotic co-evolutionary relationship). A disruption to the habitat of the asymptomatic hosts and pathogens, the theory goes, can cause the plague to leave its stable zone and find a new home.

The most likely actor behind such a scenario will probably be a volcanic eruption rather than an earthquake, because a large eruption can release enough particulate matter into the upper atmosphere to cause global cooling.

Perhaps the most far-reaching example of a geologic event unleashing a plague on mankind is the grim story of the bubonic plague, the Black Death as it was known in 14th century Europe. In a provocative book titled Catastrophe, author David Keys speculates that a massive volcanic eruption in 535-536 AD (Krakatoa is ultimately implicated by Keys, although a volcano in Papua New Guinea has also been considered) put enough material into the upper atmosphere that global weather conditions were affected vis-a-vis "volcanic winter", as they were in 1815-1816 when Tambora exploded and caused crop failures as far away as New England (where it snowed in June).*

*(on the plus side, the paintings of Joseph Turner began to feature much prettier, more vivid sunsets after the Tambora blast, since the atmospheric changes created by the volcano had the side effect of increasingly the drama of sunsets all over the world. In fact, a 2007 study revealed that more than 500 paintings---from a portfolio that included Turner, Rembrandt, Reubens, and Degas---all featured far richer, more exciting sunsets in the years following volcanic eruptions).

Keys began his investigation when he learned that there was a pattern in tree rings, sampled all over the world, that revealed a sudden period of very low growth rates---trees virtually stopped growing, all over the world, all at the same time. Ice core deposits taken in both Greenland and Antarctica revealed much higher sulphate levels (a signature of volcanism), and these could also be traced to the 535 AD date.

(view across the Sunda Strait at sunset, looking at the infamous volcano implicated by Keys)

Besides leading to terrible famines as far away as Mexico (where the great city of Teotihuacan was ultimately abandoned), Keyes postulates that the cooling of temperature created instability in a "pathogen basin" in the Great Lakes region of Africa, ultimately leading to the spread of the bubonic plague---the "Plague of Justinian"---and the collapse of the Byzantine Empire that marked the final end of the Roman domination and the beginning of the Dark Ages.

(Hagia Sophia in modern Istanbul/former Constantinople, commissioned by Justinian)

Among his other justifications for an African origin for the bubonic plague (there are competing theories of origination), Keys found that the ivory trade in the great East African ivory port cities of the time period---Essina, Toniki, Opone, and Rhapta---all saw a drastic reduction in ivory production in the wake of the 535 event. Keys contends that the ivory centers would have been particularly hard-hit by the plague if the African ivory origin/distribution thesis is correct, and his research thus does lend support to his origin claim. The notion is that the plague would have spread from modern Zaire to Dar es Salaam or central Ethiopia to Essina, then up the eastern coast of Africa through the existing ivory trade route (the Romans had an insatiable appetite for ivory), landing at the major port of Alexandria, Egypt before entering the heart of the Byzantine Empire.

In Justinian's Flea, his book on the plague, William Rosen says: "From the moment humanity originated in East Africa, human populations in the origin basins of Tanzania and Ethiopia grew far more slowly than they would have anywhere else, because they were surrounded by the richest menagerie of pathological microorganisms on the planet, the evolutionary equivalent of a baby crib filled with deadly stuffed animals."

The bacterial demon that killed so many---Yersinia pestis---had previously found a nice home in the digestive tracts of various mammals. This limited its ability to move from host to host. Y. pestis later evolved in such a way that it could be carried by fleas; when the fleas withdrew blood from reservoir animals, Y. pestis was able to spread. When a flea bit an infected rat, the bacillus caused a clot to form in the flea's digestive system. The flea would be unable to pass the bacillus through its body, allowing the bacillus to multiply in its new host. Furthermore, the clot would cause the flea to become ravenously hungry.

It turns out that the fibrin clot that blocks the flea's GI tract does not seem to form in environments with temperatures above about 25 degrees centigrade. This is how the volcanic winter/plague connection works its black magic: by cooling temperatures all over the world (as evidenced by the tree ring growth patterns), the volcanic eruption allowed the clot-formation phenomenon to occur in the African fleas. The rats brought the fleas, insane with hunger, to human populations, and then the interspecies transfer was able to take place.

Keys argues that climate change caused by a huge volcanic eruption led to a movement of disease-carrying animals out of the stable reservoir area and into close contact with human communities. When the rats carrying the fleas that in turn carried the plague reached the Byzantine capital of Constantinople in 542, via the trade routes, not even Belisarius, Justinian's great master of warcraft and one of history's tragic figures, would have been able to win the battle that would come.

Before long, 5,000-10,000 people were dying every day. An estimated 100 million ultimately perished, the Roman and Persian empires---heavily dependent on long-distance trade routes that were abandoned because of contagion fears---collapsed, and the armies of Muhammad found little in the way of armed resistance as they left the Arabian desert.


Epilogue: Our old adversary, the Black Death, would return again to kill many, many more. About eight centuries later, global cooling of some origin---possibly another volcano---may have caused the Great Famines of 1315-1317, as well as floods along the Yellow River in China that drowned more than 7 million people. Bodies went unburied, the rat population dramatically increased, and rat-borne fleas carrying the bubonic plague made their way to the Middle East and Europe through the grain trading routes. An estimated 25 million people would be killed---about 1/3 of the population of Europe. Some areas would not recover their pre-plague population levels for another 600 years. To cite just one result, 50-70% of the population of Britain was killed off by the plague by 1400, a result that approximates the casualty estimates for a thermonuclear war. The 14th century is considered a cataclysm, among the most traumatic periods in all of human history.

Wednesday, January 20, 2010

The Lord of Earthquakes

(Lisbon Cathedral in the wake of the terrible 1755 earthquake that destroyed the city)

"Civilization exists by geologic consent, subject to change without notice."
-Will Durant


In June of 2009, I spent a few days in the Andean city of Cusco, Peru. Cusco was the capital of the Inca Empire and it has become one of the world's real adventure travel nexus points, with expeditions of various kinds being launched from the city. We were there to acclimate to the higher altitude and sightsee for a short period before hiking the famous Inca Trail, the stone path that begins near "Kilometer 88"and then moves up and down through the Andes like a long serpent, past snow-capped mountains and cloud-high camp sites and picturesque ruins, before ultimately coming to the "Sun Gate" pass that looks down upon Machu Picchu.

I had read that Cusco was located in a region of substantial seismic activity, and that the irregularly-shaped, giant blocks of the Sacsayhuaman walls outside of the city, some of which are estimated to weigh over 360 tons, may have been organized according to cyclopean construction principles meant to give them an increased resistance to earthquakes. It was fascinating, then, to see first-hand how Spanish Catholicism, brought to Peru by the conquistadores and missionaries, cross-pollinated with the region's natural disasters to create a local mythology that was unique to Cusco.

(Plaza de Armas, Cusco, Peru---June 2009)

A short walk from our base at the Libertador, down a narrow alley that featured modern storefronts and restaurants built on top of Inca block walls, we found the large, rectangular plaza de armas that is typically found in cities of this lineage. Dominating the plaza was the Cathedral of Cusco, an imposing and beautiful work of architecture that essentially combines three large churches into one. Inside the cathedral was the Lord of the Earthquakes.

In 1650, Cusco was hit by one of the major earthquakes that appear to devastate the city every 200-300 years. Legend has it that the cathedral and Inca heritage sites were spared when an effigy of Christ that was donated by Carlos V of Spain was taken from the church and into the streets, miraculously causing the violent tremors to subside. The Lord of The Earthquakes---also called "The Dark Christ" because of its black color---is venerated in Cusco and is removed from the cathedral once a year for a special ceremony.

"Dark Christ" procession, Cusco


If there is an empirical "Lord of the Earthquakes", it is a mathematical expression known as the Gutenberg-Richter Law. Gutenberg-Richter is a power law, a class of statistical distributions that features very large "tail", or extreme, events. These tail events are so big that they have profound effects on the average behavior we expect from the whole system over time.

We have seen power laws before. Changes in financial market prices appear to obey one. The top-grossing 5% of movies accounted for 50% of all box office revenues in the period 2000-2005, and film workers obey a power law called "Solla Price", which holds that 50% of the work being done in the profession is done by the square root of the number of participants. Company sizes follow a power law called Zipf's Law: just .3% of U.S. firms generated 65% of all sales in 2005.

The laws extend to areas of individual human performance as well: Charles Murray, in his tour de force Human Accomplishment, found that excellence in fields as diverse as the arts, professional golf, and peer-reviewed scientific research follow power laws, which he described as a "...a type of hyperbolic distribution---highly skewed right, with an elongated tail". To cite just one example: 53% of professional golfers---all of them elite players---fail to win even a single tournament during their careers, and then we get a Jack Nicklaus who wins 71 of them. (There are some very interesting theories about how individual talents---"component skills"---may follow Gaussian bell curves, but can mix together in interesting ways to create power law-monster performers. "Ammon's Turnip" and relevant observations by Francis Galton and William Shockley can provide insights here. We'll return to this subject later for a discussion of how a 007, Jason Bourne, or even Batman could conceivably exist in the real world, although it is statistically unlikely that the human race could generate more than a handful of such individuals).

Gutenberg-Richter is the relevant power law for this discussion, because it describes a range of earthquake destructiveness magnitudes and their relative frequencies. The frequencies of earthquake types, placed in these destructive-energy classes, vary according to a demonic mathematical scaling relationship. The majority of earthquakes will be quite minor, but there will be a long tail to the distribution that will feature extreme seismic events in greater frequencies than we would get if earthquakes were normally distributed.

One of the features of power law distributions that makes them maddeningly difficult to study at the micro level is that they appear to be a product of what physicist Per Bak has termed "self-organized criticality" ("SOC"). A system that has reached a critical state can be thought of as being "loaded": a small perturbation can cause the system to suddenly exhibit wildly volatile behavior. Bak's traditional example is that of a sandpile: for a long time, additional grains of sand dropped on the sandpile simply form new layers of building material, causing the pile to grow higher and higher. At some point, however, an additional grain meets a sandpile that has entered a critical state. This final grain of sand causes the structure to behave violently, with responses that may range from a small avalanche of sand to the total collapse of the entire structure---the response can be modeled with a power law distribution. What we cannot predict is what the size of the response will be in any given instance, although we can say that a larger, higher sandpile has the potential to create a more spectacular collapse.

We will deal with this issue of criticality again and again on Bastiat Blogger. For an immediate example of a system with the potential to go critical, the market for crude oil can begin to behave chaotically---wild price excursions become possible----as a stable (or perhaps soon to begin declining) supply of crude in the production system meets insatiable demand from the economies of China and India, and the "swing producer" of Saudi Arabia becomes increasingly unable to provide a buffer, particularly after the monster Ghawar field goes into decline.

While Gutenberg-Richter gives a scale for sizes and frequencies, the more widely-known Richter Scale actually articulates what these sizes mean by giving the magnitude---the amount of earth moved by an earthquake---and the energy released. The scale functionally goes from 2 to 9, although a 10 is possible-but-never- recorded (it would represent an "epic", or civilization-destroying, earthquake). The Richter Scale is logarithmic: each upward whole number change increases the amplitude of the earthquake by a factor of 10. A level 9 quake thus has 100 times the amplitude of a level 7. The energy released increases even more dramatically: each upward shift increases the energy released by a factor of about 30, so a level 9 is releasing 900 times the energy of a level 7.

The other important scale used in earthquake measurement is called the Mercalli-Rossi Scale, and it is more of a subjective and anecdotal review of the damage caused. Suffice to say that it is roughly analogous to the Richter Scale in terms of what one would expect: earthquakes that score 7 and above tend to kill a lot of people, particularly if they occur in areas of the world with high population densities and poor building codes. Above 8 and the quakes leave ever fewer structures intact. Earthquakes that have Mercalli-Rossi scores of 9 leave virtually nothing standing.

Subduction Zones

One of the first steps in understanding earthquakes is to try to determine where the geological processes are located that tend to produce them. Overlaying a map of global earthquake activity onto a map of the earth's major geologic plates and tectonic zones will reveal that the most severe earthquakes take place near subduction zones, where one plate is pushed beneath another, rather than near the mid-oceanic ridges, where plates diverge in east-west directions. The reason for the violence of the subduction zone earthquakes has to do with the strength characteristics of rock.

Rock is very strong under non-rotational compression (pushing in), and not very strong under tension (pulling apart). The ancient Greeks realized this when they found that their public buildings tended to collapse unless columns were placed under horizontal lintels at close intervals; if the columns were too far apart, weight pushing down on the lintel---or sometimes just the weight of a lintel itself---would create excess tension and the lintel would crack in its center and bring the whole roof down with it .

(reason why the Parthenon has so many Doric columns-the lintels must be well-supported)

The Romans, however, realized that rocks were stronger under compression than they were under tension. This led them to the Roman arch, a construction technique that created strength in the structure by means of a wedge-shaped keystone that, loaded with weight from above, generated non-rotational compression forces over the span of the arch. An arch between two supports can be made much wider than an equivalently-loaded lintel can be made.

(Roman arches used to construct an aqueduct)

In the oceanic ridge situation, rocks are being pulled apart by tensional forces. Because rocks are not strong under tension, they give quickly---little energy is stored in the process. So earthquakes, like volcano activity, in a place like Iceland will tend to be quite gentle. The major damage caused by a volcano in an oceanic ridge chain like Iceland (or Hawaii, for that matter, although the situation in Hawaii is a bit different because the "hot spot" that has created the Hawaiian Islands is located under oceanic plate rather than at an oceanic ridge) will be created by running lava, not by an exposive eruption.

In a subduction zone, however, rocks are being compressed. These regions feature thrust or reverse faults, where two plates are forced together in collision before one buckles and goes beneath the other. The compression forces here are beyond human comprehension---the forces involved created the Himalayas when the Indian subcontinent collided with Asia.

Rocks are very strong under compression, so it takes a lot of energy to break them that way. They store energy up until they reach their elastic limits, and thus when they do break, they will break very violently. Subduction zones produce the monster earthquakes and volcanic eruptions.

Venomous Sting at The Very End of the Seismic Tail

Incidentally, a variation on this theme may actually be our collective undoing one day. Let us leave earthquakes for a moment and discuss their cousins in geologic violence, volcanic eruptions. The deadliness of volcanic eruptions varies with both the underlying tectonic process (subduction vs. mid-oceanic ridge) and the type of rock that is heated to create magma. The most rare case of eruption---thankfully---occurs when the granitic rock of a continental plate is forced over a subduction factory. Granitic magma can store vast amounts of gas, and pressure can build for very long periods of time. However, when a volcano of this type explodes the results are truly, truly catastrophic: an entire mountain range can be blown up.

A situation of this kind currently exists under Yellowstone National Park. An immense caldera is steadily growing beneath the park, and when it ultimately does go (it may take thousands of years for this to happen---we just don't know) the results will be quite bad. What is happening under Yellowstone is that a hotspot, deep in the earth, is creating a magma plume, a fiery spike that eats its way towards the surface. The magma plume, which is basaltic magma, has hit the granite of the continental plate beneath Yellowstone. The magma has pooled there, eventually creating enough heat to begin melting granite (!). Over time, the process is creating a bubble of granitic magma. When this rising bubble of magma eventually reaches the surface, it will be absolutely apocalyptic, an explosion like no modern human has ever seen. One intriguing possibility is that the eruption will be triggered by a large earthquake in the western United States.

Just to give a sense of scale and some historical precedent here: the biggest volcanic eruption of the last two centuries, the Tambora eruption in Indonesia, displaced approximately 20 cubic kilometers of ash, and caused the planet's climate to measurably cool (1816, the year of the eruption, was termed "the year without a summer"). About 74,000 years ago, Mount Toba in Sumatra erupted and displaced about 800 cubic kilometers of ash (about the same size as the Yellowstone blast of 2.1 million years ago).

More to the point, Toba may have very nearly caused the extinction of the human race: population geneticists have found a mysterious "bottleneck" in our genetic past, a period in which the population of humans on the planet plunged to about 10,000 living adults (this is called the "Toba Catastrophe Theory"). The disaster may also have created isolated, independent population "islands" of genetic diversity that allowed for more rapid mechanisms of genetic drift to work, and thus led to the existence of our modern races.

(picturesque Lake Toba, Sumatra: site of cataclysmic explosion that nearly killed off the human race)

Earthquakes and Shock Waves

The deep place where rocks reach their elastic limits and break is termed the "focus" of the earthquake. The energy that is released at the focus travels outward in "body waves" (seismic shock waves), and the closest surface point to the focus is called the "epicenter". There are two types of body waves---"S" or "shearing" waves that scissor left and right as they travel and can only propagate through solid materials; and "P" or "compression" waves that move backwards and forwards and can propagate through anything.

These things move at extremely high speeds---approximately 18,000 miles per hour. By the time seismic waves are detected, it is almost certainly too late to evacuate an area. It *may* be possible to automatically shut gas mains and stop trains and so on, and this is currently being tried in some locations in Japan.

We can detect seismic waves using a system of sensors that was originally put in place to monitor underground nuclear testing, but our detection equipment is more useful for post-destruction crime scene forensics than it is for providing early-warning alerts. An interesting tangent: attempts have been made to conceal underground nuclear tests by detonating bombs in the immediate aftermaths of earthquakes, the goal obviously being to try to mask the bombs' seismic signatures behind those of the natural processes.

Body waves use up very little energy trying to move rocks around within the crust of the earth as they travel: apparently total rock movement is just a fraction of a milimeter, so it may be best to visualize an almost invisible ripple that shoots through the rock at extreme speeds. When the body waves reach the epicenter, however, that energy is dumped rapidly and a very different kind of shock wave effect----the surface wave---is produced. Surface waves emanate out from the epicenter in an expanding circle of destruction, traveling across the surface of the earth. They have much higher amplitudes than do body waves; at higher Richter scale levels, an observer can actually see a surface wave undulating across the surface.

Surface waves, like body waves, come in two flavors: the ironically-named Love waves move with the horizonal, left-right shearing motion of a pair of scissors being pushed forward; Rayleigh waves move up and down and forward and back, creating an undulating, rolling type of motion in the ground. Both are destructive, but I am told that Love waves are the big killers because buildings just cannot take those quick side-to-side shearing motions (seismologists have a saying: "Earthquakes don't kill people; buildings kill people"). The explanation that I heard for the particular deadliness of the Love surface waves used this example: imagine holding a stack of dominos in the palm of your hand. You could make a rolling motion forward and back, up and down, with your hand and, if the motion was fairly smooth, keep the dominos from falling over. However, move your hand left and then immediately right and the dominos have no chance at all.

Besides their terrifying capacities for tearing buildings down and crushing people or causing them to perish after being buried alive, earthquakes have several other direct kill mechanisms. For instance, they can create tsunamis, like the one that recently killed an estimated 225,000 people in the Indian Ocean (the tsunami was created when a magnitude 9.3 earthquake off the coast of Sumatra, the largest recorded since 1964, released an energy equivalent to almost 10,000 gigatons of TNT, about enough energy to power the entire United States for 400 years. Some estimates, presumably including the aftershock earthquakes that continued for months after the major quake, have raised the total-energy-released number up to approximately 25,000 gigatons). They can break gas mains and create huge fires, like the 1906 earthquake that caused San Francisco to burn for over three days, destroying over 80% of the city (when they break the gas mains, earthquakes also break the water mains and pour rubble into the streets, so that firefighting becomes extremely difficult). If the soil under the buildings is wet, the surface waves can split sand grains apart for an instant, creating an effect called "liquefaction"---momentary quicksand---that can cause buildings to just disappear into the ground. They can also create huge landslides, as they have in Colombia.


The next entry will focus on what has been learned about earthquake prediction and earthquake-resistant buildings, and on socioeconomic factors that may make earthquake-disaster relief efforts in Haiti more difficult than they otherwise would be.

Monday, January 18, 2010

Geopolitics of the Nile, Chaos Theory, and the Memory of The Markets (Part 2)

(recently hatched chicks of Cygnus atratus, the Australian black swan)

The last entry went into the flood/drought cycles of the Nile and how attempts to tame this behavior have created long-standing political tensions in the region. During the time of the British protectorate, hydrologists were brought in to aid in reservoir design. One of them, H.E. Hurst, made a very interesting discovery. Note: I assume in this blog entry that the reader has a nodding familiarity with the classical bell-shaped curve of the "normal", or "Gaussian", distribution. If that isn't the case, it is no big deal---just keep in mind that many of our assumptions about the world, when we have to quantify them, are based on the assumption that the Gaussian holds true.

Hurst in Egypt

As a result of the critical importance of the Nile to agriculture, the Egyptians had documented many, many years of data points on the river's annual level. Hurst had grown up near Leicester, England and studied physics at Oxford. He went to Egypt to work on dam project proposals and he received the nickname "Father Nile" from the Egyptians out of their respect for his work on reservoirs and dam design (work that was used by Nasser's engineers in the construction of High Aswan).

Hurst knew that the Nile's average annual discharge was 92.4 billion cubic meters of water. However, the variation was large---in a wet year, the river could discharge 151 billion cubic meters, while during a drought the number could be 42 billion. As we discussed when we turned to Aswan, the engineering solution to these cycles is well-known---build a dam that can hold back a certain period length of "wet year" water, and then release this water during dry periods. What Hurst needed to do, first and foremost, was to determine the maximum range of the river, the distance from the highest flood marks to the lowest drought marks.

T^.5 and the Random Walk

Engineers trained in traditional (Gaussian) statistics would normally model a problem like this by assuming that rainfall patterns were independent from one year to the next and follow a so-called "random walk". A powerful mathematical shorthand would then be licensed---something called the "t to the one-half" rule. Written more explicitly, the rule states that the dispersion (range) of a random walking variable will be its standard deviation, or sigma, multiplied by the square root of time, which of course is the same as saying time to the 1/2 power, or t^.5. For brevity, I will just refer to it as the t^.5 rule. T^.5 is a convenient scaling feature of the Gaussian distribution, and its use stems back to the French gambling statistician Bachelier and his coin-tossing experiments, as well as the formulation of geometric Brownian motion by Albert Einstein in the early 1900s.

If you imagine a drunk following a statistically correct random walk, lurching back and forth as he attempts to make it to his car, the t^.5 rule tells you how far the drunk can stumble to the left before he has to stumble back to the right, towards his original path of travel.

Here is a practical example of the t^.5 rule in action: over the last six months, a stock has generated returns (actually, for technical reasons the log of returns is probably what will be used in this kind of methodology, but that's not important right now) with a monthly standard deviation, or "volatility" in finance-speak, of 2%. We want to assess how "risky" the stock is, using this calculation of volatility, but we need to somehow use the monthly data we have to determine the annual volatility (we care about annual performance, not monthly oscillations).

The t^.5 rule comes to our rescue here: we could take the monthly standard deviation, the 2%, and multiply it by the square root of t---in this case, t=12, because there are twelve months in a year. If we make a number of heroic, dangerously naive assumptions about something called stationarity, we can determine how volatile the behavior of the stock *should* be over the next year. To establish the asset's range, we would add this annual volatility (from the sigma*t^.5 calculation we just performed) to the asset's expected return---in itself quite hard to predict ---for the higher bound, and then subtract the sigma*t^.5 calculation from the expected return to get the lower bound (which is probably what we are truly concerned about if we are long-biased investors).

This example was chosen because it reveals the t^.5 rule being misapplied. Financial market prices are not stationary and do not follow a random walk. However, much of modern finance is built on this kind of assumption. As we will soon see, the (mis)use of this rule is, in fact, endemic within modern financial theory. Why? Perhaps because it works in the geometric Brownian motion of equilibrium physics, and economics occasionally suffers from "physics-envy". Perhaps because it is a tidy and convenient mathematical tool. Whatever the reason, it comes with a steep price tag attached: the underlying distribution must be the normal/Gaussian, or at the very least a close approximation to it. If the rule is invoked and the distribution is not normal, great surprises lay in wait...

Rescaled Range Analysis

Hurst found that the range of the Nile increased much faster than would be predicted by the t^.5 rule of the Gaussian random walk. To avoid obfuscating the basic point and becoming tedious, I will just say, somewhat simplistically, that Hurst took the Nile data he had and walked forward through time on the charts, looking at the highest and lowest values that were achieved and then determining what exponent power of t would---as an estimation---be necessary in order to generate that type of behavior.

The basic formulation that Hurst used was R/S=(a*N)^H, where:

R/S=Rescaled range
a=a constant
N=number of observations
H=Hurst exponent (given this name by a French mathematician who came a bit later)

The important takeaway idea is this: H is going to range between 0 and 1. If H=.5, then you do in fact have your t^.5 rule and a random walk. If H is greater than .5, then the time-series you are working with displays persistent, or trend-reinforcing properties---the range will be greater than it would be in a Gaussian distribution, and the tails of the underlying distribution will be "fatter". In other words, there will be a higher frequency of so-called extreme events than we would normally predict. If H is less than .5, then the time-series is anti-persistent, or mean-reverting, and we will see a tighter dispersion, a smaller overall range, than a random walk would predict. Extreme events will be very rare, even rarer than they are with a Gaussian distribution.

(I am making a few overgeneralizations here in order to keep things clean. Technically, it is possible---unlikely and weird, but possible---to have H=.5, a random walk that obeys the t^.5 rule, but a non-Gaussian distribution. However, we know that if H>.5 or H<.5, the underlying distribution cannot be Gaussian. So H=.5 is necessary for us to say that we are dealing with a Gaussian, but insufficient to absolutely prove that we are. Even if the distribution were to somehow be non-Gaussian, however, we would know that its behavior was moderate in terms of extremes to the point that a Gaussian assumption was quite safe)

According to portfolio manager and Chaos specialist Edgar Peters, Hurst found that the Nile's discharge produced a time-scaling exponent of .9, indicating a very strong tendency for floods to follow floods and for droughts to follow droughts. The discharge is directly correlated with the amount of rainfall that the Nile's sourcewaters receive, so we can easily understand why the drought periods have caused terrible humanitarian tragedies, such as the great famine in Ethiopia during the 1980s. The Nile does not just hit you once---like vintage Tyson, it throws hard blows in non-random combinations.

Hurst went on to apply rescaled range analysis to a variety of other natural phenomena, including sun spot activity, tree rings, lakebed sediment deposits, water levels of other lakes and rivers, rainfall measurements, and temperature readings. In all of the cases that he studied, he found that the ranges widened more aggressively than they would if they were following random walks with statistically independent data points. Nature heavily features trend-reinforcing, or persistent behavior. In fact, Hurst found that a particular number---H=.73---was showing up again and again. Hurst explained his findings by saying that natural phenomena were frequently long-memory processes---positive feedback loops cause events of today to influence events of tomorrow, in cascades of dependence that drive directional drifts to go on longer than would be realistically possible under the independent steps of a random walk.

A practical application of Hurst's work was the finding that the chances of freakishly high or low points on the range of one of these phenomena were much higher than they would be if the phenomena followed the random walk of a staggering drunk. This meant that engineers needed to take true extreme values directly into account when specifying their project designs: for instance, Hurst's applied methods would suggest that, to prepare for a 100 year extreme drought, a hydrologist would want a reservoir that could store about 20 times the annual standard deviation of rainfall, rather than the 3 times that you would need if the rainfall's statistical distribution was normal or approximately normal. Hurst's plan was to build a series of dam/reservoir systems upriver of Egypt, probably in Ethiopia, in order to create those reserves without causing extreme flooding to the reservoir basin area, or losing an excessive amount of water to evaporation. We know that Nasser preferred an alternative proposal---a high dam that was completely within Egyptian control.

Mandelbrot, Taleb, DeVany

(the Mandelbrot Set, an iconic pattern of fractal geometry)

In the 1960s, a French mathematician named Benoit Mandelbrot came across the Hurst papers while he was teaching economics at Harvard. Mandelbrot had found that commodity prices---specifically cotton prices---were not obeying t^.5, and he started applying rescaled range to the financial markets. He is actually the one who named the exponent that is estimated in rescaled range the "H" exponent, in honor of both Hurst and a mathematician named Ludwig Holder who had been working on some similar problems (today we often just call it the "Hurst exponent").

Mandelbrot found that financial market prices also tended to show Hurst exponents greater than .5, once again indicating persistence in the time-series. The levels of persistence varied from asset to asset: interest rate futures contracts tended to have quite high H exponents (over .7), for example, while utility stocks tended to be in the .55-.65 range.

Mandelbrot later systematized his observations about financial market behavior into a conceptual architecture, the Fractal Market Hypothesis, and coined two descriptive terms: the "Noah Effect", named for the great destructive flood of the Book of Genesis and describing the tendency for a time-series to show sudden, violent change; and the "Joseph Effect", describing the trending feature and named for the Biblical prophecy of seven years of famine striking Egypt after seven years of prosperity. Mandelbot developed a metric called "alpha" for measuring the Noah Effect, while the Joseph Effect is still estimated from the Hurst exponent.

The departure from the Gaussian distribution becomes more and more pronounced as you go further and further out into the "tails" and encounter the extreme events: in reviewing prices of the Dow Jones Industrial Average from 1916 to 2003, for example, Mandelbrot found that the Gaussian assumption would predict that there were 58 days when the Dow should move more than 3.4%; in reality, there were over 1,000 of these days. The normal distribution would have given 6 days of swings greater than 4.5%; in reality, there were 366. Index swings of greater than 7% should happen once every 300,000 years; during that historical time there were actually 48 days like this. When we get to the 29.2% drop that occurred on 19 October, 1987, we reach a 22 standard deviation move and a probability of occurrence of less than 1 in 10^50---1 followed by 50 zeroes, a number far, far greater than the number of trading days that have been available in the entire 13.7 billion year history of the Universe.

Edgar Peters has since used rescaled range analysis on a number of different financial asset prices and other economic time-series. He has found that markets tend to feature more noise at the shorter time scales: the Hurst exponent for the S&P500 varies from about .59 when you use 1-day intervals to .78 when you use 30-day intervals, so the "trend" component of the S&P seems to become stronger as the time horizon lengthens (up to a point). 30-year Treasury Bonds have H of about .7. G7 currencies come in around .65. As Peters notes in Chaos and Order in the Capital Markets, "These results will come as no surprise to currency traders. Currency markets are characterized by abrupt changes traceable to central bank intervention---attempts by governments to control the value of each respective currency, contrary to natural market forces. Currencies have a reputation as 'momentum trading' vehicles in which technical analysis has more validity than usual. R/S analysis bears out the market lore that currencies have trends..."

There are a number of explanations for why markets feature the Noah and Joseph Effects. One approach sees them as self-organizing, complex systems that feature a number of interdependencies and feedback loops, and which can reach a state of criticality: when they are critical, or "loaded", a small disturbance can have a magnified, large-scale effect---this "sensitive dependence on initial conditions" is a signature of Chaos. Another approach seeks less to explain the reasons why as to describe a more accurate model for market behavior: this is the "power law" perspective, which says that the magnitude of market price changes reflects some kind of scaling mathematical relationship (for example, in a system that scales according to a power law of 10 a move of 2% may be 10 times more likely than a 3% move, which in turn may be 10 times more likely than a 4% move, and so on).

Power laws have been found in distributions created by wars, earthquakes (obviously a very timely subject which warrants further exploration), bandwidth demand, traffic jams, and a baffling variety of other places. Their major feature for our discussion here is that they have far more extreme events than you would find in a normal distribution, and this can have profound effects on the "average" that the system reports.

For example of how a power law can change the average in remarkable ways, consider the case of income distribution: imagine having 99 "average" people in a room and then adding Bill Gates. The value of that one, extraordinarily wealthy individual would cause everyone in the group to be worth over $500 million, on average. In contrast, putting the world's tallest man with 99 individuals of normal height would have very little effect on the average height for the group, because the tallest man is constrained by physical limits and cannot be 1,000 feet, or 100 feet, or even 10 feet tall. The overall distribution that results from averaging height in this way is Gaussian.

Mandelbrot has a number of great descriptions of power law relationships in his books and papers. He is considered to have been an instrumental figure in the development of Chaos Theory and a closely associated field, fractal geometry, and an attempt to discuss his many contributions would go well beyond the scope of this blog entry. Several key figures in finance can be linked directly to him, but for our purposes today we will turn next to a particular individual he mentored, a man named Nassim Taleb.

Taleb is a highly experienced options trader and decision theorist who initially made his reputation by cashing in on Eurodollar options during the '87 Crash. Taleb had purchased the options when they were far out-of-the-money (i.e., would only become valuable if an extreme market shock event occurred), and he had been observing for some time that multi-sigma events---incredibly unlikely according to the Gaussian assumption---occurred regularly in the major financial markets, often on quiet financial news days.

After witnessing the legendary portfolio manager Victor Niederhoffer blowing up his previously very successful hedge fund by selling disaster insurance (naked puts on the S&P500) to other investors and, possibly, engaging in the Martingale betting that we have previously discussed, Taleb developed a trading strategy that was explicitly designed to be "blow-up proof". The strategy uses a rolling portfolio of out-of-the-money option positions to profit from Mandelbrot's "Noah Effect"---sudden, discontinuous, demonic jumps and crashes in the markets (there are other approaches for attempting to profit from trend-reinforcing persistence, or the "Jacob Effect", and I will discuss these in some detail in the future. For now, I will say that, in my opinion, consistent profits from the Noah Effect require insurance-type option strategies like Taleb espoused, and that consistent profits from the Jacob Effect require systematic trend-capture strategies). Taleb has gone from trading to a sort of modern Bohemian lifestyle in which he is a man-about-town pursuing his interest in decision-making, particularly decision-making under conditions of risk, pressure, and uncertainty. It seems to be the core intellectual meditation on which his many other interests revolve.

In The Black Swan, Taleb provides a number of interesting anecdotes that relate to the impact of huge moves on the average performance of a system. For instance, most of the returns of the S&P500 index over the last fifty years can be traced back to just 10 big up days in the market, yet we tend to view the stock market in terms of its "average" drift.

Since the publication of his first book for general audiences, Fooled by Randomness, and certainly since the release of The Black Swan and his prediction that Fannie Mae and Freddie Mac were ticking time bombs, Taleb has become quite hostile to mainstream finance and risk management. He has variously accused members of the financial economics profession of being charlatans, frauds, imbeciles, criminals, and worse. Taleb has been particularly vicious towards the financial media's penchant for insipid ex post explanatory narrative fallacies, and the very poor accuracy rates attained by "professional" economic and political forecasters. The former should be mostly viewed as entertainment, but the latter is a very important subject for investment and trading system design, and we will deal with the evidence regarding the effectiveness of various political and economic forecasting methods at some length in the future.

I personally rather like Taleb, am a fan of his work, and feel that there are many good lessons to be learned from him and from his cerebral lifestyle, though I feel that he has increasing turned to certain sensationalist rhetorical gimmicks as he has evolved into more of a public intellectual/philosopher/social critic and less of a trader.

Another interesting individual from academia who has done a lot of work with Chaos in its financial market applications is Arthur DeVany. DeVany taught economics in California and conducted an analysis of the movie industry, wherein he found that the frequencies of extreme "tail-events"---wildly profitable films---did not follow the normal distribution curve, but instead followed a power law. DeVany also found that the forecast accuracies in the movie industry are as low as they are in economics and politics. He wrote a very nice book, Hollywood Economics, about his findings, and I think he has the same general disdain towards Gaussian-based economics and finance that Nassim Taleb has---in fact, the two are friends. He also shares Taleb's tremendous self-confidence, although DeVany seems to be a bit more charitable to his colleagues in mainstream economics.

DeVany's work in Hollywood Economics quantitatively validates an observation that was made by legendary movie industry maven William Goldman: "Nobody knows anything. Why did Paramount say yes to Raiders of the Lost Ark? Because nobody knows anything. And why did all the other studios say no? Because nobody knows anything. And why did Universal, the mightiest studio of all, pass on Star Wars?...Because nobody---not now, not ever---knows the least goddamn thing about what is or isn't going to work at the box office."

In private correspondence, DeVany has mentioned his interest in "living on kurtosis"---i.e., building a lifestyle around preparation for the extreme events. Following these principles, DeVany has become his own test subject as he undergoes the discipline of a physical conditioning, diet, and overall health approach based on evolutionary principles and a study of what the human body was "selected" by Darwinian processes to thrive on and achieve.

Some of this is heavily based on applications of Chaos theory to human physiology, as we would expect from a man with DeVany's intellectual interests, with the thesis being that Chaos can actually be good for us and that we evolved under conditions which featured lots of walking and outdoors play, punctuated by random, intense bursts of very serious (i.e., life-threatening) physical demands.

To name just two recent examples of Chaos being applied to medicine:

-bioengineers and neurologists studying seizures have found that EEG patterns in epilepsy sufferers in the throes of seizures tend to be, counter-intuitively, less chaotic than they are under normal conditions.

-a cardiologist named Ary Goldberger found that the most regular, Gaussian heart rate diagrams were found in people suffering from congestive heart failure, and that our heart rate patterns tend to become less chaotic---less healthy, in these terms---as we age. DeVany has used studies like this to form an opinion that long-duration, steady-state aerobic training may be detrimental to health if it trains the Chaos out of the heart rate.

A final figure in our colorful cast of Chaos finance academics who I'd like to mention is James Orlin Grabbe. Grabbe did his PhD in economics at Harvard and became an authority on pricing foreign exchange derivatives. He taught at Wharton, where he specialized in trying to find and develop currency traders, and wrote a brilliant text on macroeconomics, International Financial Markets. My third-edition (1996) copy of that book has a piece of the Mandelbrot Set on the cover and is filled with tantalizing, occasionally even delicious insights that any mathematically-inclined trader or strategic investor could appreciate. Here's one: "Consider the yen/dollar exchange rate for 1971-1980 and 1980-1992. Embrechts (1994) reports finding a value of H=.64 for the first period, and H=.62 for the second. This suggests persistence in the exchange rate returns, and nonperiodic cycles. Periods of gains and losses tend to bunch up, much like Nile discharge levels. It also means that the scale of the distribution of 100-day returns is about 18 or 19 times as large as the distribution over 1 day (since 100^.64=19.05 and 100^.62=17.38). In the (random walk) Brownian motion case, the scale would only be ten times as large (100^.5=10). So if you were doing risk analysis or 'what if' scenarios for your bank, the Brownian motion assumption (assumption of independent normal increments) would give too small a probability for changes over that time horizon."

Always a libertarian/anarcho-capitalist, Grabbe appears to have become radicalized sometime in the late 1990s. He moved to Costa Rica with his beloved cat and began a "digital money trust" project, essentially a free banking/offshore finance experiment heavily leveraging encryption technology, Chaos, and e-gold. By 2001 or so, Grabbe's website pages began to regularly feature soft porn pictorials and an increasingly bitter view of the effects that government interventions were having on social and economic activity. I was greatly saddened to learn that this eccentric, fascinating individual died in 2008 at his home in San Jose, Costa Rica. Grabbe had begun work on a second textbook that would feature more in-depth research into game theory applications to trading, as well as continuing the recurrent theme of Chaos.

Because of recent, terrible events in Haiti, my next blog entry will be about power law distributions in earthquakes and the chances of increasing our level of prediction accuracy where these disasters are concerned. There are many similarities between financial market crashes and earthquakes, and models from the two study areas are frequently shared. After that, I plan on getting back to some practical investment implications of the Hurst/Mandelbrot findings, hedge fund strategies that can make money from these market properties, and a school of economics---the Austrian---that can shed light on why markets behave this way and why some Chaos there, as in human heart rates, is a good thing (and why attempts to tame the Chaos will ultimately fail unless the innovation capacity of the economy is itself virtually destroyed in the process). At some point in the near future, I am going to turn to the battlefield and some models that are appropriate for the study of war.