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=====Private narratives wash out===== | =====Private narratives wash out===== | ||
Each investor’s private motivation may be nuanced and personal — how is the rest of its portfolio positioned, what are the local macro risks to which it is especially sensitive — but largely these idiosyncrasies cancel themselves out in a large sample — they are [[Brownian motion]]; reversions to [[entropy]], which is baseline white noise — so we can disregard them. | Each investor’s private motivation may be nuanced and personal — how is the rest of its portfolio positioned, what are the local macro risks to which it is especially sensitive — but largely these idiosyncrasies cancel themselves out in a large sample — they are [[Brownian motion]]; reversions to [[entropy]], which is baseline white noise — so we can disregard them. | ||
Put another way, though the “interconnectedness” of similar transactions means they are ''not'' independent, as the probabilities of [[normal distributions]] require, most of the time it's close enough: the immediate transaction history is chaotic — as traders say, “noisy”— in the immediate term, here the dissimilarities between trader motivations are most pronounced, but over a large aggregation of trades these dissimilarities tend to cancel themselves out. A “signal” only emerges over time. If all traders are using market information, this immediate interdependence looks a lot like independence. So a “normal” probabilistic model<ref>I am working hard not to use the intimidating term [[stochastic]]” here by the way.</ref> works fairly well. It’s not a bad ''model''. | |||
We treat professional market participants as a largely homogenous group from which emerges, over time, a [[signal]]. Almost like, you know, like an ''invisible hand'' is guiding the market. | We treat professional market participants as a largely homogenous group from which emerges, over time, a [[signal]]. Almost like, you know, like an ''invisible hand'' is guiding the market. | ||
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This is good: it gets our model out of the gate. If investors were not broadly homogeneous, our statistics would not work. “What is the average height of all things” is not a meaningful calculation. Which way the causal arrow flows — whether signal drives theory or theory determines what counts as a signal — is an open question. | This is good: it gets our model out of the gate. If investors were not broadly homogeneous, our statistics would not work. “What is the average height of all things” is not a meaningful calculation. Which way the causal arrow flows — whether signal drives theory or theory determines what counts as a signal — is an open question. | ||
But there is a second order sense in which the earlier and later trades ''are'' related, in practice: the later participants know about the earlier trade, and its price — it is part of that universal corpus of market information, deemed known by all, that informs price formation process | But there is a second order sense in which the earlier and later trades ''are'' related, in practice: the later participants know about the earlier trade, and its price — it is part of that universal corpus of market information, deemed known by all, that informs price formation process: all can thereby infer the trend from prior trades — and use this abstract information to form their [[bid]] or [[ask]]. | ||
=====Nomological machines never quite work in the real world===== | |||
When you bounce a ball, friction, energy loss, structural imperfections, impurities in the rubber and environmental interference frustrate the conditions needed to satisfy the “[[nomological machine]]”: the required assumptions for Newton’s laws to hold are not present, so we let it pass when our bouncing ball never quite obeys them, but it is close enough and usually no one is counting in any case. | |||
The same applies to the statistical techniques for we use to measure behaviour of the market. | The same applies to the statistical techniques for we use to measure behaviour of the market. As we have seen, the occasional intervention of idiosyncratic behaviour is basically noise. Where the interdependence creates a persistent variance from the normal probability model over time we can model that, too, with measures like [[volatility]]. We use probabilistic techniques to model these second order corrections, too. | ||
But there is a third order of dissimilarities. In times of stress in the market the behaviour of other people in the market ''directly'' and ''directionally'' affects your transaction, and yours affects others. | But there is a ''third'' order of dissimilarities. In times of stress in the market the behaviour of other people in the market ''directly'' and ''directionally'' affects your transaction, and yours affects others. | ||
This is not just the crowded theatre phenomenon, when everyone stampedes for the exits at once, and the narrow aperture makes the stampede all the more urgent, and therefore dramatic — but second order features. An investor long “on margin” might wish to, and be able to, ride out a short term crash by meeting margin calls. In most dislocations this is the obvious and — if you can manage it, correct — thing to do. The market usually recovers, at least in the short term. But meeting your margin call means drawing on your revolving credit facility and your bank is experiencing a liquidity crisis and unexpectedly pulls you lines, or suspends withdrawals, as a result of its ''own'' market exposure to the crash. Your prime broker, usually patient with you and tolerant of peripheral looseness in your margin operations, is also under pressure, has told you today there is no flex, and for good measure, it is jacking up your IM. | This is not just the crowded theatre phenomenon, when everyone stampedes for the exits at once, and the narrow aperture makes the stampede all the more urgent, and therefore dramatic — but second order features. An investor long “on margin” might wish to, and be able to, ride out a short term crash by meeting margin calls. In most dislocations this is the obvious and — if you can manage it, correct — thing to do. The market usually recovers, at least in the short term. But meeting your margin call means drawing on your revolving credit facility and your bank is experiencing a liquidity crisis and unexpectedly pulls you lines, or suspends withdrawals, as a result of its ''own'' market exposure to the crash. Your prime broker, usually patient with you and tolerant of peripheral looseness in your margin operations, is also under pressure, has told you today there is no flex, and for good measure, it is jacking up your IM. | ||