The different ways of forecasting in the markets is not of the same level of simplicity. We observe at least 3 different levels of simplicity of forecasting and therefore levels of reliability and risk too, for successful and profitable trading.
1) 1ST LEVEL OF SIMPLICITY: CONSTANT LONG TERM EXPONENTIAL TREND.
The very well known model of constant long term (more than 11 years , preferably many decades) exponential trend or drift of indexes of securities. Traditionally the first type of model for the price movements of various indexes of securities was this model, which supports the Buy-and-hold way of trading or if we also accept leaving money in the banks (risk-less assets) and not investing all in a risky asset or portfolio, then the optimal trading is not the Buy-and-hold but the periodic re-adjusting or resetting of the portfolio with the same percentage of distribution among the assets (see post 6 for details).
From a statistical point of view a statistically valid model verification cannot be done using only the data of only one security (as statistics requires a sample of many independent paths) but it can be tested on indexes of securities or sectors. This applies also for the CAPM which assumes such a constant long term trend: It can be tested only over a set of sectors or indexes and not over a set securities that for each one we have data for only one path.
This model does not apply to commodities that do not show a constant long term trend (more than 11 years , preferably many decades) , and also it does not apply to foreign exchange currencies cross-rates of the interbank (forex) market.
Investment and trading based on this 1st simplicity level is very simple and stable but requires a large sum of initial capital (E.g. 1 million $, so as to provide say an annual income of 50,000$ in a reliable way)
2) 2ND LEVEL OF SIMPLICITY: CONSTANT STATISTICAL PERIODICITY OR CYCLES.
It is crucial to realize that such cycles may emerge in the price changes , in a random way with a hazard rate of appearance at each period , and furthermore that they may appear not directly on the prices changes but on the rate of growth of prices.We must make clear here that we are not talking of exact periodicity but rather for randomly emerging temporary periodicity.
Here the spectral analysis can prove the existence of such statistical cycles as in the table of the post 5. Again such cycles can be tested only on a sample of many independent paths, therefore only for groups of individual instruments like securities or sectors, or indexes etc. Such cycles are occur not only on indexes of securities but also on groups of commodities and groups of foreign exchange currencies cross-rates of the interbank (forex) market.
Here the spectral analysis can prove the existence of such statistical cycles as in the table of the post 5. Again such cycles can be tested only on a sample of many independent paths, therefore only for groups of individual instruments like securities or sectors, or indexes etc. Such cycles are occur not only on indexes of securities but also on groups of commodities and groups of foreign exchange currencies cross-rates of the interbank (forex) market.
The phases of such cycles are not uniformly distributed bust there is concentration of particular starting and ending times.
The most useful are the
1) The 22.2 years cycle published by the Nobel prize winner Kuznet ,
2) The 11.1 years global climate cycle
3) The 5.5 years Kinchin cycle
4) The seasonal 3-months cycles , corresponding also on the traditional frequency of publishing of financial statements updates of securities.
5) The monthly cycle
6) The weekly cycle
7) The daily cycle.
The concept of cycles simplifies the perception of the 4-basic patterns of price movements (as in post 32 ) , to only one, that of the vector-wave during half of the period of the cycle and in particular to be a super-exponential move or terminal spike. Thus the emphasis here in the pattern to trade is based on the time and timing and less on the price shape.
From the cycles (see post 5) (not including their harmonics, that is their sub-multiples of the periods) the order of intensity of effect on the price movements, and therefore the order of predictability also is approximately the next:
Daily (1 Day earth)>>
1 Year (12 months, earth)>>
11 years global climate (Sunspots) >>
Month (4 weeks, sun+moon)>>
2 weeks solar magnetic cycle (Parker Spiral)>>
160 mins Helioseismologic cycle >>
55 mins Helioseismologic cycle>>
5 mins Helioseismologic cycle.
And the most predictable effect modulated by such cycles (after the long term permanent trend) is the reaction to an super-exponential moves (a blow-up at the end of trend in the form of super-exponential move or terminal spike). (See e.g. https://www.ted.com/talks/didier_sornette_how_we_can_predict_the_next_financial_crisis and http://www.er.ethz.ch/ Such super-exponential terminal patterns of trend may occur usually as result of overgrowth of the one of the two populations in a demand-supply coupling rather that of domination and not so much of competition or cooperation. See also post 22..The frequency of emergence and the size of such super-exponential blow-ups follows the law of inequalities in other words the Pareto or Log-normal distribution and is thus by fat more often than pure randomness would predict! )
Daily (1 Day earth)>>
1 Year (12 months, earth)>>
11 years global climate (Sunspots) >>
Month (4 weeks, sun+moon)>>
2 weeks solar magnetic cycle (Parker Spiral)>>
160 mins Helioseismologic cycle >>
55 mins Helioseismologic cycle>>
5 mins Helioseismologic cycle.
And the most predictable effect modulated by such cycles (after the long term permanent trend) is the reaction to an super-exponential moves (a blow-up at the end of trend in the form of super-exponential move or terminal spike). (See e.g. https://www.ted.com/talks/didier_sornette_how_we_can_predict_the_next_financial_crisis and http://www.er.ethz.ch/ Such super-exponential terminal patterns of trend may occur usually as result of overgrowth of the one of the two populations in a demand-supply coupling rather that of domination and not so much of competition or cooperation. See also post 22..The frequency of emergence and the size of such super-exponential blow-ups follows the law of inequalities in other words the Pareto or Log-normal distribution and is thus by fat more often than pure randomness would predict! )
THUS THE ORDER OF BETTER PREDICTABILITY IS
1) LONG TERM PERMANENT TREND
2) A CYCLE IN THE ORDER OF PREDICTABILITY DESCRIBED ABOVE AND REALIZED AS REACTION TO SUPER-EXPONENTIAL TERMINAL MOVE (OR SPIKE).
1) LONG TERM PERMANENT TREND
2) A CYCLE IN THE ORDER OF PREDICTABILITY DESCRIBED ABOVE AND REALIZED AS REACTION TO SUPER-EXPONENTIAL TERMINAL MOVE (OR SPIKE).
Here in the chart below which is with the prices after taking the logarithm, we may watch deviations from the linear moves (super-exponential moves) and their highly predictable reaction lasting in the average 3.75 years. during 30 years!
The concept of cycles simplifies the perception of the 4-basic patterns of price movements (as in post 32 ) , to only one, that of the vector-wave during half of the period of the cycle and in particular to be a super-exponential move or terminal spike. Thus the emphasis here in the pattern to trade is based on the time and timing and less on the price shape.
Trading based only on such fixed cycles can be combined with the constant long-term trend as in 1) , so that it is always one-sided , always long positions. Of course as the cycles are of shorter time period so their unpredictability and randomness increases as described in the post 63 .
We may utilize trading faster than the daily cycle (see cycles faster than one day in post 5) , in particular one-hour cycles with waves of 30 minutes. In order for such a trading to be at the 2nd level of simplicity rather than the 3rd level of simplicity of forecasting according to the current post, it is required that we focus on 30-minutes waves starting or ending at about the whole hours of the clock (because sessions of security indexes start or end at whole hours of the clock). We focus to observe (say on 5-minutes bars) such 30-minutes wave (preferable with a terminal spike at the end) and then we trade for the reaction 30-minutes wave in the opposite direction (after consulting the 1-hour and daily time frames). The stop loss is tight and the expected profit is at least 3 times larger than the risked stop loss. Trading in this way on a single instrument is not better than trading on it at daily bars, because of the lower predictability at 5-minutes bars, and because of the much more human effort and spending of time it requires. But if we trade on many instruments , then as such opportunities now are many (multiplicative effect on the rate of return of an intermittent sequential portfolio of instruments), the over all result may be better. Still, no creative person that values a lot his time will go on spending time in such intra-day trading just for the money result, except in rare cases , for a limited time and for specific purposes. Using starting and ending trades at about whole hours of the clock and such a simple and robust cycle-wave pattern recognition, gives a solid ground to stand for emotional beliefs and expectations, against the shifting sands of the markets at intra-day time frames. We should use also Brokers with technology of Straight-Through platforms and not market-maker brokers, so that the broker does not trade opposite to the customer and take on purpose their stop-losses.
We may utilize trading faster than the daily cycle (see cycles faster than one day in post 5) , in particular one-hour cycles with waves of 30 minutes. In order for such a trading to be at the 2nd level of simplicity rather than the 3rd level of simplicity of forecasting according to the current post, it is required that we focus on 30-minutes waves starting or ending at about the whole hours of the clock (because sessions of security indexes start or end at whole hours of the clock). We focus to observe (say on 5-minutes bars) such 30-minutes wave (preferable with a terminal spike at the end) and then we trade for the reaction 30-minutes wave in the opposite direction (after consulting the 1-hour and daily time frames). The stop loss is tight and the expected profit is at least 3 times larger than the risked stop loss. Trading in this way on a single instrument is not better than trading on it at daily bars, because of the lower predictability at 5-minutes bars, and because of the much more human effort and spending of time it requires. But if we trade on many instruments , then as such opportunities now are many (multiplicative effect on the rate of return of an intermittent sequential portfolio of instruments), the over all result may be better. Still, no creative person that values a lot his time will go on spending time in such intra-day trading just for the money result, except in rare cases , for a limited time and for specific purposes. Using starting and ending trades at about whole hours of the clock and such a simple and robust cycle-wave pattern recognition, gives a solid ground to stand for emotional beliefs and expectations, against the shifting sands of the markets at intra-day time frames. We should use also Brokers with technology of Straight-Through platforms and not market-maker brokers, so that the broker does not trade opposite to the customer and take on purpose their stop-losses.
3) 3RD LEVEL OF SIMPLICITY: RANDOM APPEARANCE AND DISAPPEARANCE OF THE 4 BASIC PATTERNS AS A RESULT OF DEMAND-AND-SUPPLY COUPLING.
There is a random appearance and then intermittent time intervals of non-appearance of the 4 basic price patterns as in the post 32 and post 22, that are the results of the three different types of coupling of demand and supply of orders (Domination, competition, cooperation see post 22 ).Again such models can be tested statistically only on groups of instruments (not individual path instruments) , that provide as data a sample of independent paths in time. The mathematics of these patterns are not very simple. But the most important here is that there is unpredictability in general of the appearance and disappearance of such patterns, when such waving patterns are not part of the in advance predictable cycles as in 2).
Trading based only on such patterns and not be bases solely on the long term of 1) or fixed cycles of 2) is risky , quite unpredictable and difficult, and becomes even more unpredictable as we move to shorter time scales e.g. intra-day time-frames for reasons described in post 63.
Personally although I have traded at the 3) simplicity level too, I concluded after many years of trading that one should trade (or at least this is my choice for me) only at levels 1) and 2) and not at level 3).
