Cluster methods of market forecasting. - page 9
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So, I would like to get this thread back on track. Here I would like, with your help, gentlemen,to identify the strengths and weaknesses of existing cluster approaches to market forecasting and outline new, perhaps more promising, approaches.
I will explain on my fingers (for those who do not know) what the cluster approach is in relation to the market.
But first, about market dynamics.
Price can experience large and indeed unpredictable (for most people) spikes (1) in strong events (important news about: economic decrees, cataclysms, major business and political events, etc.). In this case there is a relaxation of the fluctuations caused by this with time proportional to ~1/N. The market, however, "lives its own life" (where self-organization processes take place), experiencing (2) its own (not caused by outside influence) and sometimes even the smallest jumps, which are characterized by another law of relaxation. characterised by another law of relaxationSqrt(1/N), which, we note, happens much more often than relaxation ~1/N, so, no matter how unusual it sounds to us,the market functions mainly according to its own laws .
First type of jump does not happen immediately (because many people are involved in its forming), which imposes some specific characteristics on the interval of history of the quote, which is sandwiched between the moment when a strong event happens and the surge caused by it. Moreover, the part of history prior to the second type of jump should contain some specific characteristics (delayed swing of the market and its fall from the next state of unstable equilibrium).
Now clustering.
So, the initial hypothesis is that there is a small part of quotes history preceding the price jump (plus volume history, what goes there) where the information about the next jump is encoded.
Further, there is a purely technical part. A space of certain parameters or states is introduced, such as: (1) a trivial geometric image in the form of a candlestick pattern, or (2) the space of different frequency modes obtained by Fourier decomposition of this plot (time series), or (3) spectrum decomposition by orthogonal velvet functions (which is much better since the plot is short) or (4) spectrum decomposition by some other orthogonal functions, etc.
Then a huge - statistically significant set of such (preceding jumps) sections are taken and analyzed for their occupancy of this space of states. And if they are significantly concentrated in some parts of this space (and the other parts of history - not preceding the jumps - do not get there), then this will be the cluster (or set of clusters of types 1 and 2), which allows to make a prediction.
Information about the next jump is encoded in ALL history, because the process is non-Markovian. In practice, this means the following - if we take the average variance of the process in a sliding window of observations for a giant archive of data, this variance is practically a constant. If it starts to decrease, expect a spike.
I have been working in this direction, but realised that it is an extremely resource-intensive task.
It is easier to go to Brownian motion models, preliminarily introducing pseudo-states in the time series of quotes at exponential time intervals. That is, convert a non-Markovian process into a Markovian one. It cannot be done completely, but the diffusion equations start to work.
ALL.
Started reading the thread and from the first words you were given the right direction, namely ClusterDelta. The others, who write about random market process, statistics and other nonsense, know the market only from the non-stationary series side and that's all. That is where their knowledge of the market ends and, unfortunately, is limited. But at the same time they start to make confident conclusions about the market, knowing only a part of it.
And no one thinks that before the price turns, there will be preconditions and patterns at the lower TFs at the cluster, where the volume, delta and OM take part besides the price. It turns out that this information is the driving force for the price in the future. But how should they know it, the statistical people? They except their own statistical parameters of quotes, distributions, Markov's and non-Markov's laws... They just cannot see from behind the trees of their own backwoods, but what the market really is and what drives it.......
In the ClusterDelta project, they are analyzing reversal or continuation paternas, etc... It's not all smooth and unambiguous there either, but it's at least a chance to be one step ahead of these statistical people. Why? because according to the causal model of price formation the volume and delta are the cause of future price changes. The main thing is to interpret it correctly.....
Started reading the thread and from the first words you were given the right direction, namely ClusterDelta. The others, who write about random market process, statistics and other nonsense, know the market only from the non-stationary series side and that's all. That is where their knowledge of the market ends and, unfortunately, is limited. But at the same time they start to make confident conclusions about the market, knowing only a part of it.
And no one thinks that before the price turns, there will be preconditions and patterns at the lower TFs at the cluster, where the volume, delta and OM take part besides the price. It turns out that this information is the driving force for the price in the future. But how should they know it, the statistical people? They except their own statistical parameters of quotes, distributions, Markov's and non-Markov's laws... They just cannot see from behind the trees of their own backwoods, but what the market really is and what drives it.......
At the ClusterDelta project, we're dealing with reversal or continuation paternas, etc... It's not all smooth and unambiguous there either, but it's at least a chance to be one step ahead of these statistical people. Why? because according to the causal model of price formation the volume and delta are the cause of future price changes. The main thing is to interpret it correctly.....