Nice post @macsga, but I suspect that price is worse than chaotic, it is basically "random".
A chaotic system appears random but has a more or less deterministic model that, in theory, would allow one to predict its future from its current state. In the double pendulum example, the state is the pair of angles, at the top and at the elbow, and their derivatives with time. The trajectory in that gif was computed starting from some arbitrary state (particular choices for those four numbers) and applying the deterministic equations of motion.
A random system has no closed deterministic model, not even in theory; its evolution depends on external inputs that cannot be predicted, and cannot be enclosed in the state because they are themselves dependent on further external causes, and so on. In this case, the external inputs include what each trader reads and thinks, the bills he has to pay and the money that he earns, government regulations, bank delays, and lost more. If one tries to enclose all those variables as parts of the state of a closed model, one ends up with the whole universe, or at least with good part of mankind.
So, in the theoretical model, the price must depend on external inputs that are not modeled, and therefore unpredictable, and therefore memoryless -- their future values are independent of their past values.
The question is whether one can still have some state variables in that model, so that the future prices are not entirely random but have some dependence on that state, and therefore to past prices.
The current price is known to be such a state variable, indeed a pretty good predictor of future prices. That is, the price P(t+d) at a future time t+d is the price P(t) at the current time t times some factor (percent change) D(t,t+d).
As far as I know, no one has been able to demonstrate any other correlation; that is, and relation between D(t,t+d) and the prices (or price changes) before the present time t. So, it seems that D depends entirely on those external unpredictable factors.The best we can do is observe the probability distribution of D. (I don't know what is the shape of that distribution, only that it is not log-normal.)
In other words, the logarithm of the price is a simple Brownian process whose increments log(D) are independent but not normally distributed. This is the "log-Brownian" or "geometric Brownian" model.
The unpredictability of price has been blamed on "whales" who try to "manipulate" the price and break its trends. However the market has fish of all sizes, and once one accepts that the increments depend on unpredictable external factors, it becomes unnecessary to distinguish "whales" as a separate category of trader.
For sure, a single trade of 100 BTC will have a much bigger impact on price than 100 trades of 1 BTC each, because the latter will tend to cancel. In log scale, perhaps the change due to the large trade will be 10 times larger than the sum of all the little changes, typically. However, one increment will be just as unpredictable as the other, and just as unrelated to past trades.
Humans are genetically programmed to find patterns, even where they don't exist. The trends and patterns that one may think of seeing in price charts may well be only illusions. We also remember more easily our predictions that worked than those that failed, which reinforces the illusion.
Correlations between past and future price changes may exist for very short time scales d. For example, it may happen that a trader who decides to sell (or buy) will do so in a series of successive trades; since these trades are all derived from a single decision, there will be strong dependence betwen them. Also, presumably the general feeling of most traders will not change in a few minutes. On the other hand, that general feeling may not influence their feeling towards the small changes that are likely to happen in that time span. That is, one may believe that bitcoin will go to the moon this year, but nevertheless feel that it may go down in the next minute. Also,
Correlations between past and present also may exist in common stocks. For most traders, the main external inputs are a small set of "fundamentals" like products and their demand. These variables tend to vary slowly and smoothly with time, so one can postulate models for them that include "momentum" -- that is, a dependence between the past and the future.