Do you see patterns in Random Walks?

Quote from zedDoubleNaught:

Thank you for the response, it offers data to suggest that I may be learning something from all my self-study, I'm happy.
Ok, so n-time series space, flocking behavior with splines, % steps normalization, random walk with a dispersion rate of something, volatility clustering, kurtosis and fatter tails than a normal distribution, many different kinds of probability distributions, reversion to or away from a mean which may be undefined -- let me see if I can put this together, this is interesting.

edit -- also arcsin and meander laws as noted above, I'll have to study those, I don't know what they are.
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I meant chit-chat since this one...:p
 
Argument #3

The summary of deterministic argument:

“Randomness does not exist. It only describes our inability to embrace the complexity of the universe. By knowing at a given moment every particle position and speed, we could simply foresee the future.”

Let’s assume that we observed a system, any system including mechanical, political, biological etc. We cannot address it as a system without identifying its elements and acknowledging the relationship between those elements. Using Ashby’s “Requisite Variety” principle in order to be able for us to determine all possible states of this system the observer’s instrument has to be at least as complex as the system itself. Keeping in mind that any real life system has infinite complexity our observation tool has to be even more complex. This, of course, is impossible.
 
Uncertainty is an inherent factor in any real-life action, in particular one that relies on the information gained from sensors (trading data) and manipulations performed by actuators (traders). One way to cope with uncertainty is RANDOMIZATION – introducing random selection into the decision making algorithm. Using and accepting the uncertainty of the markets (inherent randomness of multiple individual decision makers) RANDOMIZATION allows us to build pretty stable correlations between the INTRODUCED Randomization and the observed (measured) randomness of the markets.
 
Now, how do we correlate Randomization and Randomness? One way to do so is through Spontaneous Synchronization! The next step is to discuss this phenomenon in depth. It might answer lots of questions posted in this thread earlier.
 
Let’s view all the traders currently involved in trading of a security as oscillators. They will “oscillate” between “BUY” and “SELL” with a certain frequency and with certain market timing that I will call “PHASE”.

The term “sync” is short for “synchrony” or emergence of order in time. Depending on whom you are talking to, “synchrony” can have different meanings even within the context of periodic phenomena. In the strictest sense it means that each unit oscillator follows an identical trajectory, xj (t) = X(t) for all units j. I will call this strict synchrony. Alternatively, “synchrony” is used interchangeably with “phase-locked”; each unit is firing with the same period but there are phase-shifts. Finally, there is a notion of synchrony from statistical physics. The emergence of large temporal fluctuations of X(t) is often defined to be the onset of synchrony. Thus, it is the appearance of temporal order where there was none before. I will make this latter definition more precise when I need it. For systems in which the individuals are, say, chaotic, synchrony is defined as having identical trajectories earlier.
 
Boris Schlossberg: "Price patterns are simply the reflection of human reactions of fear and greed to ever-changing news flow. They are not some randomly generated numbers from an Excel spreadsheet, even though they make look very similar. This is the critical flaw of pure randomness theorists - just because random functions can often mimic price patterns does not mean that price patterns themselves are random."

In fact you can apply technical analysis to other "real" data such as auto sales, employment reports and populations counts with suitable results,
 
Quote from intradaybill:

This is too old. The motion of the devices is coupled to each other when they are put on the cans. It is a coupling effect. There is nothing wired going on. After some transient motion they are suncronized.
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Of course! Coupling of the Oscillators is the underlying mechanism of Spontaneous Synchronization. I did not say it's weird, I said it's simple and self evident; that is why it is so important. Phase coupling is the key!
 
Quote from MAESTRO:

Let’s view all the traders currently involved in trading of a security as oscillators. They will “oscillate” between “BUY” and “SELL” with a certain frequency and with certain market timing that I will call “PHASE”.

The term “sync” is short for “synchrony” or emergence of order in time. Depending on whom you are talking to, “synchrony” can have different meanings even within the context of periodic phenomena. In the strictest sense it means that each unit oscillator follows an identical trajectory, xj (t) = X(t) for all units j. I will call this strict synchrony. Alternatively, “synchrony” is used interchangeably with “phase-locked”; each unit is firing with the same period but there are phase-shifts. Finally, there is a notion of synchrony from statistical physics. The emergence of large temporal fluctuations of X(t) is often defined to be the onset of synchrony. Thus, it is the appearance of temporal order where there was none before. I will make this latter definition more precise when I need it. For systems in which the individuals are, say, chaotic, synchrony is defined as having identical trajectories earlier.
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I'll try to map the concepts onto an example: I read an article that a fringe idea (like a new fad or conspiracy theory) has low adoption in the population, until it passes a threshold of 10% of the population. After it passes 10%, acceptance increases quickly. Would the threshold of 10% be an example of the "emergence of large temporal fluctuation of X(t)"? Then would the adoption rate as it went from 1%-2%-4%-10%-19%-32%-...n be the "synchrony" or "emergence of order in time"?
 
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