Please don’t read this if you aren’t interested in knowing what I wrote for my sociology paper. (Or if you aren’t interested at all in economics, for that matter.)
The idea of stocks first cropped up among Dutch, British and French ships who were keen to explore territories beyond their homelands. With few explorers able to afford the exorbitant sums of money required to have an overseas trade voyage, companies were formed to raise money from investors (Ritchie, 2009). Since then, stocks have evolved dramatically: today the major stock markets in the world hold trillions of US dollars worth of capital (Bespoke Investment Group, 2008), and have the ability to determine who ends up on the cover of Forbes magazine or, just as often, in jail. Economists, however, have mostly struggled with the unpredictability of the markets, especially in recent times, where the subprime mortgage crisis has plunged the world into a severe financial crisis. Volatility continues to be the main topic of research amongst economists, even after years of analysis and big-money mistakes. In this paper, I attempt to use social network analysis to understand the phenomenon of stock market movements.
Stock market movements are defined by the aggregation of individual purchasing decisions of shares; this constitutes a sort of emergent property, where “large interacting ensembles exhibit collective behaviour that is very different from anything one may have expected from simply scaling up the behaviour of the individual units” (Krugman, 1996). Emergent properties are the underlying principle for the studying of complex disciplines, including economics and sociology: Anderson, in his landmark (1972) article on emergence, clearly (and rather humorously) explains that if there were no emergence, then perhaps the only people that would have a job would be people working on the most fundamental laws – “some astrophysicists, some elementary particle physicists, some logicians and other mathematicians, and a few others”. Indeed, emergent properties prove the fallacy of division, that any phenomenon can be broken down and explained by its most basic unit. While a quark is the building block of all life, there is little chance that it has the ability to explain economic self-interest. Looks like economists (like myself) deserve a job after all.
The emergent property of stock markets – that the aggregation of purchasing decisions result, most of the time, in roughly accurate valuations of companies in the markets – is beautiful, and is the highlight of another eloquent, and more eminent, emergent property expressed by Adam Smith (1776): the invisible hand. According to Smith, individual rational decisions often, on a collective, result in collective efficiency.
￭ Volatility
Unfortunately, stock markets exhibit a volatility that is not seen in other industries; equilibrium, the state at which the market “clears”, is an economic term that does not ever come into fruition where the market is concerned. This volatility is, in part, caused by a market failure: information asymmetry. Fundamental economic models typically make the assumption that there is no information asymmetry, when in the real world this is unrealistic. This asymmetry causes the people with the right information (typically the people who are closer to the companies) to make the better decisions, and others to make incorrect bets. Only the people who have access to the right information for a sustained period of time has the ability to make sustained earnings.
Watts (2003) explained in his book, however, that people do not form ties randomly: ties are formed preferentially, and the people with the right information tend to be limited to those who are closest to the centre of the network. In fact, out of the 8,000 directors that sit on the boards of Fortune 1000 companies, all of them were connected to another person, or more (Watts, 2003). These directors hence have a tendency to form a mutually beneficial in-group that has the clearest idea of where the market will move. The most powerful people, therefore, make the best decisions, while the average person will know little about which part of the market will be the most profitable.
￭ Bubble formation
Preferential attachment
A second emergent property, peak and trough formation, also happens in stock markets. Assuming that individual decisions are made independently, peak and trough formation should more or less be an impossible scenario; a quickly built-up period of boom time, followed by a bust. In the real world, however, the assumption that the individual makes independent decisions breaks down. Speculation – the unscientific or pseudoscientific manner by which a person judges the suitability of stock purchases - exacerbate the problem of preferential attachment to short-term stock winners.
An example of preferential attachment in the markets is the dot-com bubble of recent years. Economists have attempted to explain the causes of the bubble, which occurred between 1995 and 2000 (Ofek & Richardson, 2003; Shiller, 2000; Wang, 2007). Shiller’s arguments are well-trumpeted in the economic community; his book, Irrational Exuberance, argued that real world stock market bubbles “resemble Ponzi schemes in the sense that some ‘new era’ story becomes attached to the bubble and acquires increasing plausibility and investor enthusiasm as the market continues to achieve high returns” (Shiller, 2000, 2003). In recent years, empirical analyses from two different papers appear to demonstrate that the stock market operates in the scale-free network made prominent by Barabasi and Albert’s landmark (1999) paper (Kim, et al., 2002; Kullmann & Kertesz, 2001). Money follows money – till there isn’t any money left to make.
Centrality
The idea of centrality is also crucial in the understanding of how stock markets have such peaks and troughs. Ofek & Richardson (2003) argue that it was the mass expiration of “lockup agreements” – resulting in venture capitalists and shareholders able to sell off their ownership of the companies – that resulted in the subsequent bust. Venture capitalists (and impatient shareholders) were forced to keep their shares in the companies they owned in the dot-com bubble even though they would have preferred to sell. Ordinary stock buyers observed the money that was flowing into the dot-com markets and assumed its profitability even though the money was in there because the venture capitalists had an agreement in place to not take it out. These buyers assumed that since the stock market prices were high that the stocks were worth buying.
The months of December 1999 and January 2000 would spell the beginning of the end of the dot-com boom. In the two months, US $100 billion (a third of the total dollar value of the market capitalisation of dot-coms) was released from lockup agreements – and venture capitalists began selling to gain from the exuberance. The dot-com industry was finding the easy money that it had flowing away to other industries. A simplified model of the network in the dot-com industry is shown below: the venture capitalist is in the centre of the funding network in the dot-com industry. When the venture capitalist sells his shares he sends two signals: (1) a loss of confidence in the company that will trickle down the network, and (2) a signal for dot-coms to raise more capital to stem the bleed.
The centrality of the venture capitalist (VC), however, meant that it had the ability to propagate an epidemic at a much more powerful rate than any other node in the network. The dot-coms attempted initially to sell more shares, but found that the number of optimistic VCs diminished (Ofek & Richardson, 2003). Realising that the capital lost when the VCs withdrew their money was not going to be regained at the same level, rapid and huge volumes of insider trading commenced: In February 2000, insider trading accounted for over 50% of the amount of stocks sold (see diagram below).
At this point, both the VCs and dot-com firms were selling their shares away; the epidemic then spread to the normal shareholder. From March 10 to March 15, 2000, the NASDAQ (the technology-heavy stock index) fell by 9%, or over 500 points. The NASDAQ has never breached the levels of the dot-com bubble since.
￭ The 2008 global financial crisis
Preferential attachment and centrality have the ability to explain the causes of the dot-com bubble – but how about the global financial crisis? Financial institutions, attempting to capitalise from the easing of regulations, created unsustainable collateralised debt obligations (CDOs; in essence, funds made up of risky mortgage loans), and sold them to unknowing investors. When homeowners began to default on their mortgages, a domino effect occurred around the world. A simplistic model of the American economy, pre-financial crisis (left), might explain this clearer.
The chart shows an uncanny similarity to the hypothetical dot-com industry model that was shown previously. The financial institution, generalised as a “bank”, provides three critical functions: mortgage loans, “normal” everyday credit (for consumption), and investments.
Prices of homes in the US rose dramatically between 2005 to 2008, beyond any substantial reason – building costs had increased only slightly, and the population had increased in a smooth linear gradient. Home prices, however, had risen close to 80% compared to the 2000 levels (see chart below). A “speculative fever” had gripped the country; a third of the people sampled in a 2005 survey expected house prices to rise by 50% a year (Shiller, 2008, p. 45). These fantastical expectations fuelled a preferential attachment to housing purchases at an unprecedented rate, raising prices even more and resulting in the formation of the bubble.
When the mortgage departments collapsed because of loan defaults by subprime homeowners, the bank lost money. This should typically have been an isolated incident, but the investment arm of a bank now has a “shortcut” tie to the mortgage department, thanks to the creation of CDOs. The values of CDOs then fell as well because the funds, made up of the bad loans, became worthless. The laymen (the unfortunate pun to a now-defunct bank not intended) investors decided to cut their losses, terminating their fund ownership and defaulting on bank payments. Two sources of credit have essentially been eliminated; the credit crunch meant that banks had to protect their reserves or face bankruptcy. Credit went down dramatically in the 2008 crisis, but only because of the central roles that the financial institutions had in managing the crucial roles of the economy.
￭ Conclusion and Solutions
Emergent properties arise in volatility (in the short term) and bubble formation (in the long term) for the stock market. Volatility results from information asymmetry, while bubble formation is a problem that arises from the phenomena of preferential attachment and centrality. Crucially, to attempt to prevent similar crises from occurring, there has to be an attempt to stop the “key players” from imploding (Borgatti, 2003). In the case of the dot-com crisis, the “stockpiling” of lockup agreements caused an irrational speculative bubble to form; such speculation in an industry can be avoided if we target venture capitalists and their method of acquiring stakes in companies – lockup agreements should perhaps have reduced (and more variable) durations, allowing the bubble to deflate more smoothly.
In the case of the global financial crisis we now find ourselves entrenched in, the key players are the two arms of financial institutions that had dealt the most significant damage: the investing and mortgage arm. Deregulation in the 1980s under Reagan had caused these institutions to go overly creative (and, ironically, destructive) with designing funds and risky loans. There is a need to revamp institutional policies to ensure that the two key players do not collapse – and, perhaps, to minimise collateral damage to the entire network, keep the three arms separate to prevent “shortcuts” from causing a next financial crisis.
(1917 words)
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