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'''Work life''': An unwanted outcome you didn’t expect, to which you weren’t paying attention, and, therefore, for which you don’t think you should be blamed. | '''Work life''': An unwanted outcome you didn’t expect, to which you weren’t paying attention, and, therefore, for which you don’t think you should be blamed. | ||
</Ol> | </Ol> | ||
====The randomly distributed marketplace==== | |||
{{Drop|A|market, in the}} abstract, looks like a [[nomological machine]]. There is a bounded environment, a finite trading day, a limited number of market participants and a defined set of financial instruments with which one can engage in a limited range of transactions, whose outcomes will set the price for the traded instrument, which can be easily compared with the last traded price for that instrument (in that it will be higher, lower, or the same). | |||
From this information we can ''derive'' a relationship between transactions — price went up, price stayed the same, price went down — and a ''trend''. A trend is a stab at extracting a [[signal]] from the [[noise]]. | |||
The [[signal]] depends on a theory of the game, Otherwise the “relationship” between the two discrete transactions is arbitrary. Without a theory, everything is [[noise]]. | |||
=====The theory-dependence of signal===== | |||
If given events are truly “independent” — in a first order sense, they are: the participants in the later trade do not know who or where the participants in the earlier even are, let alone what their motivations for trading were — then a “trend” we draw between them is, more or less, meaningless. All that is left is mathematics. | |||
But we draw | But we ''have'' a theory, so draw the line all the same. We make assumptions about the homogeneity of all market participants: we assume all have similar price information, and that all are propelled by the same essential economic rationalism: you don’t sell things you expect to do better than comparable investments, and you don’t buy things you expect to do worse. | ||
=====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. | |||
But there is a second order sense in which the earlier and later trades ''are'' related: the later participants know about the earlier trade and its price — it is part of that universal corpus of market information, deemed | 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. | ||
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. | |||
And all can thereby infer its position in a trend from the trade before that — and they will use this abstract information to form their [[bid]] or [[ask]]. | |||
This interconnectedness of all similar transactions means they are ''not'' independent, as the probabilities of [[normal distributions]] require, but most of the time it's close enough: the immediate transaction history is pretty 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''. | This interconnectedness of all similar transactions means they are ''not'' independent, as the probabilities of [[normal distributions]] require, but most of the time it's close enough: the immediate transaction history is pretty 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''. | ||