I have been developing some ideas on how to find unknown things, and prepare for them. Today’s post is based on two very different books on searching into the unknowable. When we approach a similar problem from different starting points a productive interaction between them often develops. Lost Person Behavior: A search and rescue guide on where to look by Robert J. Koester is a practical experience guide; it is intended as a guide to finding lost people, but unstated by the authors it is also an abstract study of searching for a way to find any lost or unknown thing. A seemingly very different book, The Physics of Wall Street: A Brief History of Predicting the Unpredictable, by James Owen Weatherall, is about finding underlying causes for human behavior in the marketplace, especially the buying and selling of publicly traded stocks.
Both books are about seeking into unknown regions with poorly defined boundaries, and they have overlapping strategies with testable concrete results, but each of these very different types of searches has unique insights and techniques that may be applied to the other. Each field of searchers may not be aware of some unknown unknowns because they are unknown, at least to their search specialty, but with a different mindset, known to the other search strategy, these unknowns may become known. Once these unknown things are seen, even poorly, they can be explored and become better known, and when better known special uses can be found for them, and they can become widely used, and when found useful by many people, there will commonly be found yet other uses which were never known before. It is this process of exploration and communication that has permitted humans to become so successful at exploiting the world. Exploring into the unknown unknowns will seem like a foolish activity, but when something, anything, new is discovered, practical uses will often follow, because as complex as human reality is, it is fractal in many ways, and once a pattern is seen in one environment a strikingly similar pattern is commonly found in others.
One of the most common ideas is that people behave in their own best self-interest, that they choose options at each moment in time that will give them the most benefits with the least expenditure of time, effort and money. For example, the prices and returns on stocks in an open marketplace, where large numbers of people are risking their money based on expected future rewards, would seem to obey simple laws of supply and demand of aggregate self-interest. And yet, there are examples where the value of the entire economy of the world market jumps inexplicably overnight without any reason other than it did. All of the physical goods existing in the world may not have changed, only the value attached to them, and that is sometimes catastrophic. What causes those tipping-point events is worth considering.
It would appear that the black swan events are caused by some extra underlying worry. Worry is always there when money is at risk, a panic is always latent, and observing others panic will sometimes trigger a panic. All that is needed for a general public crash is a tiny event which triggers a feeling of panic in a single individual in a positive feedback situation, and for that panic to be communicated to other individuals who themselves are in similar stressful situations and in a visible position themselves where they communicate their panic to yet other individuals who are similarly risked and can be panicked.
What would be needed to forecast these types of tipping-point black-swan events would be: 1. A tension meter for the whole system, 2. A measure of visibility between players in the system, and 3. A measure of the exposure to failure of the invested individuals. In other words, a large number of people playing long odds with a large part of their goods, in a part of the market that is stretched to capacity, and a pre-measure of the visibility of other people’s panicky behavior. Observed panic of a few people at risk provokes a reflex of running away instantly by all exposed people. When that occurs a general panic ensues as the value of the items drops precipitously and probably goes noticeably below a usefulness value of the items. With electronic trading making trades at the speed of light, it is impossible for a human to time a panic to its moment of occurrence, but with the above guides we can observe when it has become reasonable for humans to move to other safer activities. With the numerical measures I have proposed above it would be possible for computers to compute the probability of these unusual events.
A similar idea may be applied to lost people. People who are in a situation where they suddenly realize they are at serious risk will be prone to panic, and when panicked will run directly away from what they perceive to be the danger. The running itself in a panicked state of mind will reenforce the panicky feeling, and the individual behaves like a panicked herd. But panic is exhausting, and after a while they will succumb to despair and seek rest, or just wander aimlessly and slowly, until something catches their attention, and they will attach themselves to it and cower near it for a feeling of security.
Those comparisons show the individuals entering a panic state from different starting points and behaving in similar panicky ways. Individuals in both conditions would have benefited by observing the situation when it was getting overstressed, and moving early to a secure mode of behavior. A visible precursor will be when jittery people start making obvious little mistakes. When jitters are seen and others are hanging on by their fingernails it’s time to quietly move away, and prepare to save the panicked ones’ goods. Moving away before the panic only has the usual transactions costs, but when panic ensues it might cost everything.
Black swan events are not pre-known, but their effects are not unknowable, and they can be used.
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