Patterns in Markets : the imposition of thinking patterns and the establishment of ‘meaning’ in trading systems
(copyright © 1998 C. J. Lofting)
In any trading system, especially in that found in stock exchanges, so we find the use of dichotomies that go towards describing current and future situations, e.g. :
Bull/Bear
Profit/Loss
Spot/Futures
Long/Short
These general distinctions are then refined and analysed to help determine future states and so enable both speculations and hedging, where speculate/hedge is another dichotomy used within the system.
In text/context analysis, another dichotomy, so the context supports and/or guides the text. When considering the use of indices in market systems, so any created indices is based on a selection of high-profile securities that serve as overall indicators of the market position; a particular index represents the state of a particular portfolio.
In text/context analysis so the particular index is ‘text’ when compared to the whole market and an interesting pattern emerges when this text is removed from consideration and we analyse the context, made-up of those securities NOT in the index. This pattern is where we consider the relationship of the index to the ~index (~ = NOT), where the ~index is an index made-up of all of the securities NOT part of the ‘text’ index.
In this analysis we will find that the study of the relationship between the index and the ~index will go towards determining the overall future position of the index and so this relationship serves as an indicator of future behaviour of the market as a whole (and in fact ANY categorisation based on A/~A distinctions does this. Overall, if the difference between the index and the ~index increases so the market will eventually fall and visa versa. Thus the ‘high flying’ index is brought-down to earth by a declining ~index in that the link between the two becomes untenable and so an adjustment takes place).
The point to be made here is that this relationship of index to ~index is also a dichotomy (index/~index) and as we shall see, any dichotomy-based distinction has a structure and dynamic imposed on it that originates in the METHOD of analysis, namely dichotomous analysis (DA) and so the patterns detected do not necessarily reflect ‘objective’ reality. Thus it is possible to ‘create’ a market state out of ‘nothing’.
Humans use dichotomies to create maps that serve as categorisation systems and as such go towards helping us to predict things to come. The use of a base dichotomy, e.g. land/water, serves to make a general distinction that is wide enough to allow for individual interpretations but also useful enough to be of value. Once the base dichotomy has been made, so it becomes the context within which we add more dichotomies, e.g. high/low, thus this new dichotomy helps to refine the base dichotomy such that we now consider high/low land as well as high/low water. If we then add a further dichotomy within the context set by the previous two, so our ‘general’ map starts to become more specific in details and so more useful and yet still retains a ‘general’ level of interpretation. This adding of layers using dichotomies helps to develop ‘consensus’ maps where all members within a group, or culture, or across the whole planet, agree with what the map stands for and how to use it.
Unlike maps of the planet etc, so stock market maps are based on the fundamental dichotomy of profit/loss; they are ‘value’ biased maps that can quiet often not reflect ‘fact’ and ‘what is’, but more ‘values’ and ‘what could be’.
Research in the areas of Neurology and Psychology suggest that at the unconscious level, all information is categorised into whole:aspects distinctions, and these can be seen as A/~A distinctions where the ~A is ‘aspects’ that consist of all parts and static as well as dynamic relationships. Another term for ‘aspects’ is ‘harmonics’ in that the A is the whole song/key and the ~A all of the harmonics that go towards creating the whole song; thus the sum of all of the elements contained in ‘~A’ equal ‘A’. What this shows is that a ‘whole’ is not a whole until we consider all of its contextual relationships and this includes dynamic relationships; the whole is not the sum of its parts but more the sum of its parts as well as all of its possible relationships and it is this relational consideration that is often forgotten and so some see the whole as being ‘more’ than its parts simply because they leave-out contextual data.
The process of any dichotomous analysis seems to follow a path that consists of :
Prior to (1) is ‘the undifferentiated’ in that the determination of a whole implies noticing a ‘difference.' This ‘automatically’ creates a ‘~whole’ that is perceived as being simple negation.
The last entry in this list is ‘general’ in that more of a bifurcation takes place where the relationships exist in two forms – static and dynamic. Thus the path of development is more like Figure 1, bottom-up:
In Figure 1, the terms blend, bond, bound, and bind are explained later, but in summary they deal with how we find meaning when making whole:aspects distinctions.
The process of using dichotomy-based methods leads to the creation of graphic information that is a product of the method; thus the Normal Distribution Curve (NDC) is a property of dichotomous analysis and reflects the ‘mixing’ or ‘weaving’ of the main distinctions. For example, the recursive use of an A/~A dichotomy six times gives me sixty-four possible ‘states’ and analysis of the probabilities, and so distributions, of these states forms the NDC. Localised biases will ‘skew’ the NDC but not change its overall form.
In dynamic markets, so the NDC reflects general conditions based on all possible facts being known, but in these dynamic markets so more time than not all possible facts are NOT known.
In dichotomous analysis so conditions occur where the determination of either a profit or a loss are not possible in that BOTH conditions can occur at the same time. By this I mean that only a general analysis is available and so the precise EITHER/OR assertion of profit/loss is not yet possible.
These sorts of states are called BOTH/AND states and they have an interesting feature in that when analysed so they show a graphic representation that suggests wave interference at work.
This representation is not necessarily a function of ‘out there’ but more a result of the method of analysis. This method, dichotomous analysis, when applied in a BOTH/AND state results in a wave interference pattern (WIP) because we have in fact lost resolution of the NDC. This loss is due to the presence of BOTH/AND states in the process of categorisation and this comes about as follows:
When given PRECISE information on any dichotomy, i.e. profit/loss, so I can write down all possible combinations of instances of profit OR loss over time. For example, if I wanted to chart all of the possible states resulting from six determinations of EITHER profit OR loss I would end-up with sixty-four possible states. However, if I introduce states where I can no longer determine profit/loss order, so that I lose a degree of resolution in that states expressed as PL and LP are no longer differentiable, so I must use another symbol, lets call this ‘0’ (zero). We can combine this symbol with P (where PP is reducible to P) and L (where LL is reducible to L).
What we are doing here is saying that we wish to analyse data over six time periods (minutes, hours, days etc) but find we can only consider the periods in pairs rather than units.
If we now map-out all of the possible states we find that many of the sixty-four states we found earlier now share the same new symbol such that the explicit sixty-four are reduced to being represented by only twenty-seven symbols. Furthermore, when these twenty-seven symbols are lined-up in order of derivation (i.e. LLL, LL0, LLP, LPL, L0L…..PPP), and we identify all of the previous unit symbols contained in these pair symbols so the wave interference pattern is observed:
In Figure 2, the * character represents one of the three possible symbols (P (for PP), L (for LL), X (for PL and LP)) The numbers are the number of original symbols now contained in the particular column.
The uppercase letters are keys used for description. Thus we note that A,C,G,I,S,U,Y, and ZZ all contain only one symbol and this is EITHER P OR L. All other positions are 'BOTH/AND' positions in that they allow for entanglements.
The above chart is based on six considerations of P OR L and so sixty-four possible states (2^6) (A reflects 'pure' L in that all six considerations led to an 'L' result, and ZZ reflects 'pure' P.) This pattern does not change beyond this level other than to become more pronounced. For example, when we consider Aristotle's mapping of syllogisms, so algebraically there are two hundred and fifty-six but he found that only nineteen were 'valid'. Since these syllogisms contain entanglements so we find that when we remove the 'pure' states from the above graph (A,C,G, I,S,U,Y,ZZ) so there are only nineteen states left.
This graph deals with the analysis of dynamic relationships using pairs where we cannot differentiate the 'order' within a pair -- the elements are 'entangled'...if we 'zoom-in' so we can differentiate the order and so the wave interference pattern 'disappears' but this is because we have changed context and move from general relational analysis to particular...
If we then use this sort of information in our decision-making, and this includes the buys/sells dichotomy, so we can actually impose these thinking patterns onto the marketplace to the extant that they are given ‘value’ and seen to be independent of ‘in here’. They are not. (This is ‘where’ the whole concept of wave interference comes from in Quantum Mechanics in that the experiments used are founded on dichotomous analysis that includes BOTH./AND states in the considerations.)
The above pattern can emerge the moment we start to trade since the EITHER/OR states of profit/loss do not exist until we cease trading and reconcile the session’s trades; during trading so it is more of a BOTH/AND state that functions in that the long/short dichotomy can ensure a trader lives in a ‘potential’ state until the bell rings and trading stops.
Contextual Considerations and the Fibonacci Series
We now look at a feature of market analysis that has gained a degree of interest over the years, namely the presence of the fibonacci series when we analyse trading data. The presence of this series, and of many others is due directly to the considerations by traders of previous contexts when making their decisions. These considerations are founded on the dichotomy of ‘then’ vs ‘now’ (or now/~now) and the claim is that ‘then’ will influence ‘now’ but the question is ‘how much of ‘then’, how many timeframes, do I need to consider’?
If we consider only the events at each timeframe, then each frame is considered as independent of all others, and thus there is only one context applicable, the one that is part of that timeframe concerned. This implies that each frame is considered to be independent from all previous frames with the exception of it's position in the sequence of frames (the only context is time with each moment being 'separate' from every other).
By deciding to take into consideration previous contexts, we move into the realm of dependence. Within this context, variations emerge that influence the degree of information available. If, for example, we considered only the previous two contexts, and numbered these as we developed and summed the contexts, so we would discover the emergence of a Fibonacci series, as shown in Figure 3 If we chose to consider *all* previous contexts, then a binary series emerges. (This is why the series has been observed in markets).
We can determine the degree of development by dividing one element by it's predecessor. In the Fibonacci series, as we move up the scale, so this value oscillates around 1.618. At the binary series the development factor is 2.
What is noticeable in Figure 3 is that, starting from frame 0 of each series, we have the beginnings of a binary series that is extended by one frame for each series. What ends the series is where we find the next binary series number - 1 rather than the next binary number. Numerically, this is a way to determine which context ratio is applicable for a given system, with the emergence of the binary series emphasising maximum detail as well as maximum stable developmental energy. I give this feature the overall name of the Context Ratio (CR).
What is interesting about the CR is that to go beyond a development factor of 2:1 leads us into the world of complexity, attractors, and increasing chaos implying that the window of 1.6 to 2.00 is a window of stable development. Lower than 1.6 is decay and above 2.00 is unstable but allows for 'emergence' of possibly profitable new forms. This latter condition allows for the case of putting in more ‘worth’ than is there to create a transformation into ‘new’ forms. This is a common feature in human behaviour and is where we find the source of ‘value’.
In Figure 1 we noted the use of four terms: blend, bond, bound, and bind. These terms relate to the general feelings we get when dealing with whole:aspects interactions for it is the mixing of the elements of the dichotomy that generates ‘meaning’; thus the degree of A + ~A varies and so we get different values. This is seen in mathematical equations that take on the form of X = xB * yC which is the equivalent of saying xA * y~A, the x and y coefficients bring-out particular values of the general A and ~A distinctions. (We note that x and y can in fact symbolise complex numbers or functions used to bring-out an aspect of the two main elements).
At the general level:
Whenever we describe wholes, either being, or becoming, or seeking, so there is a general feeling of blending and being or becoming ‘whole’.
Whenever we describe parts, so there is a general feeling of bounding in that there is a boundary present as we differentiate one part from the other(s).
Whenever we describe static relationships, for example part(s)-to-whole, so there is a general feeling of bonding.
Whenever we describe dynamic relationships, e.g. a contract between apparently independent ‘wholes’, so there is a general feeling of binding.
If we then add a ‘direction’ to each of these, so we have concepts like ‘expansive blending’ and ‘contractive binding’. In our social lives so these cumbersome terms are given more refined labels but the labels are just that, labels that ‘point’ to these general emotion-based patterns; thus a feeling of ‘loss’ for example can be expressed as a contraction of some sort.. a loss or diminishment in feeling ‘whole’.