First the obvious (that is, if you're not brainwashed by economic orthodoxy): the economy doesn't reach equilibrium. It isn't static—it's dynamic, constantly changing. And changes can happen suddenly and non-linearly. In other words, unlike a ball that you might push on a flat surface, the economy is more like pushing a ball into a series of curved surfaces and connected bowls of different heights. The track is always changing and different balls might be at different heights at different times. More on this in a bit.
Second: While most economic theories presume people will optimize and take all available information into account—we, err, I mean they—don't. We use rules of thumb: heuristics. There are volumes covering the various kinds of cognitive biases from which we suffer. And while most economists assume we are rational agents—it just ain't so. People are irrational. Whether its information cascades, fads or cults (dot-com bust, pet rocks, Jonestown massacre) for every rational person you show me, I'll dig out five irrational ones from the graveyard of folly and foible. Of course as has been said, it ain't the things we don't know that get us into trouble—it's the things we know that just ain't so.
Next: networks. All the people and all the companies interact in networks and those networks are in themselves hard to predict. Have you ever met someone you judged to be of average intellect and ability but turned out to be connected to another of great power and influence? People always wonder, "how did HE meet HIM, and how are they still friends?" Small worlds indeed and when networks morph, merge into larger ones and break-off into sub-networks, it's even harder to predict.
Once you have these networks, interesting and unpredictable things can happen. In a sand pile there is a network of potential energy, "fingers of instability" where a small input can trigger an avalanche. And that network—like a market—can change quickly and suddenly. You can also get the emergence of a phenomenon known as "emergence". Emergence is a fancy way of saying that the whole is greater than the some of the parts. Ant colonies, brains, cities, behavior in markets all exhibit this phenomenon of emergence where the constituent components give rise to higher order.
The last key principle is this: evolution. Organisms, technologies, business models, social structures all evolve. And this is one of the most important pieces of the puzzle. There are a few key aspects in the process of evolutions—whether in life, inventions or ventures.
First is "variation". In life: it's via random mutation. In technology: it's via accidental discovery, intentional invention, trial and error and combination of already existing technologies.
The second aspect: once there are a variety of things, it's clear that some are better than others.
The third feature is that there's some process or algorithm of "selection". And of course the fore mentioned "better" depends on what environment or landscape the thing is performing or competing in. The fancy name for this is "fitness landscape". Think of climbing a mountain: you try to scale a local peak. When you get to the top, you might see a new peak which could even require you to descend, move to the new base and then climb again. Tiger Woods did this years ago to perfect his swing—so did IBM. And so it is with technology adoption, startup companies and even incumbent companies that can adapt and reinvent themselves.
The last key feature is amplification. Good biological designs—or good technologies or businesses benefit from positive feedback effects and get dialed up. They get amplified, attract capital, get more adopted and spread through the proverbial (or literal) gene pool. Conversely, bad ones get dialed down. They get negative feedback, lose prominence, suffer from decreased population size or even extinction.
You can use all the above to see patterns that might be emerging, note when the wisdom of the crowds breaks down and leads to information cascades with people parroting other people. You can also see how a collection of new technologies can come together to create applications that weren’t predicted.
There's one key part of this framework that I've found frustrating. Feynman famously said that for a successful technology, reality must take precedence over public relations, for nature cannot be fooled. But I've realized to the unfortunate happenstance of investors: that people can be fooled—namely by other people.
Most short investors are right to predict the eventual demise of a company run by a manipulator rather than an operator. But in the short-term, under the captive spell or so-called "reality distortion fields" of such promoters, frustrating as it may be, I must admit that the promoter has economic value. He can lower the company’s cost of capital. How do you quantify that? What' that guy worth? The same thing goes with countless private ventures. Imagine a market mechanism for shorting private companies…
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JAN.19.2006 by
Pareto Principle of Optimality presume that equilibrium is at that point where don't appear more losers Real life is permanent battle on limited resources. When I'm using theories the results appear for public something like "... the probability is..."
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