ANYONE WHO WILL TRY TO MAKE MONEY SOLELY BY TRADING AND SUCH SYSTEMS OF TRANSACTIONS SHOULD BE AWARE THAT THERE IS A VERY POWERFUL AND ALMOST UNBEATABLE COLLECTIVE WILL SO AS NOT TO SUCCEED! NO-ONE WANTS PEOPLE TO QUITE THEIR JOBS AND MAKE MONEY THIS WAY AS IT IS SOMEHOW PARASITIC. IT IS IN SOME SENSE UNETHICAL AS A PRACTICE ENFORCEABLE TO THE MAJORITY. AND OF COURSE NEITHER THOSE WHO HAVE LARGE CAPITAL WANT THAT A MAJORITY WILL MAKE MONEY THIS WAY, AS THEY WOULD PREFER THAT THEY WORK IN THEIR COMPANIES FOR THEM. ONLY IN SPECIAL CONTINGENCIES AND SITUATIONS SOMETHING LIKE THIS WOULD BE ETHICAL. AND IN PARTICULAR A HIGHER MORALITY THAT WOULD SUPPORT SUCH A PRACTICE, WOULD BE PROVABLE WITH COLLECTIVELY BENEVOLENT DEEDS FROM A POSSIBLE SURPLUS OF SUCH MONEY!
Everybody would like to know more about what the market will do so as to trade appropriately with almost certainty, like an arbitrage! But this is not but very rarely the case with the markets. Some press themselves to guess beyond what is observable in almost ever situation of the markets moves so as to trade with almost certainly and exhaust themselves. The science of statistics is fair about what it claims it knows with uncertainly and how much uncertainty and what it cannot know at all and such claims are based entirely on the observable by the senses data. ! The science of statistics can draw valuable conclusions with little only information and knowledge about how really the market will move. But fortunately these conclusions are adequate to make sufficient profits in scientific statistical trading! We may call this realization the Lean Fair Knowledge of Scientific Statistics. Even though the science of statistics bases its knowledge entirely on the observable data that are available to everybody, still it is not in the ability of perception of everybody to realize and make directly the same conclusions without some knowledge of statistics. Some people may start their research about the successful trading in the markets more or less knowing the basic statistical behaviour of the markets, but being not satisfied with the Lean Fair Knowledge of Scientific Statistics search for decades for something more. Most often they will be failing to find something more, and the reasons is that this Lean Fair statistical knowledge of the markets is a universal phenomenon , in the way the economy functions and information is distributed and published. The good news is that the Lean Fair statistical knowledge is adequate to make good profits.
Everybody would like to know more about what the market will do so as to trade appropriately with almost certainty, like an arbitrage! But this is not but very rarely the case with the markets. Some press themselves to guess beyond what is observable in almost ever situation of the markets moves so as to trade with almost certainly and exhaust themselves. The science of statistics is fair about what it claims it knows with uncertainly and how much uncertainty and what it cannot know at all and such claims are based entirely on the observable by the senses data. ! The science of statistics can draw valuable conclusions with little only information and knowledge about how really the market will move. But fortunately these conclusions are adequate to make sufficient profits in scientific statistical trading! We may call this realization the Lean Fair Knowledge of Scientific Statistics. Even though the science of statistics bases its knowledge entirely on the observable data that are available to everybody, still it is not in the ability of perception of everybody to realize and make directly the same conclusions without some knowledge of statistics. Some people may start their research about the successful trading in the markets more or less knowing the basic statistical behaviour of the markets, but being not satisfied with the Lean Fair Knowledge of Scientific Statistics search for decades for something more. Most often they will be failing to find something more, and the reasons is that this Lean Fair statistical knowledge of the markets is a universal phenomenon , in the way the economy functions and information is distributed and published. The good news is that the Lean Fair statistical knowledge is adequate to make good profits.
There is a thin line that separates business and investments as gambling that destroys the human spirit from business and investments as applications of scientific statistical knowledge under general principles that protects and reinforces the human spirit. This book contributes to see the difference and put the investors from the side of protected human spirit.
We have mentioned earlier the basic cornerstones of success, and we repeat them here.
There are 3 contexts of laws required in trading . The appropriate LAWS OF THINKING for trading, the appropriate LAWS OF FEELINGS for trading , and the appropriate LAWS OF ACTIONS for trading.
The Successful trading is based according to these three laws on
1) POWER OF COLLECTIVE SCIENTIFIC THINKING: A GREAT AND SIMPLE SCIENTIFIC PERCEPTION OF THE FUNCTION OF THE ECONOMY THROUGH SOME GLOBAL STATISTICAL LAW. E.g. The law of Universal attraction in economy: that big money attracts more big money in the capital markets, and this by the balance of demand and supply makes securities indexes of the companies , that are indeed the big money, to have mainly stable ascending trend, whenever one can observe such one. Valid statistical deductions can be obtained with simple statistical hypotheses tests about the existence or not of a trend , with sample size half the period of a dominating cycle.The statistical quantities from the front-office in trading need to me measured are the price position in the channel around the average, the velocity (1st derivative) and the acceleration-deceleration (2nd derivative), which is done as statistical quantities by a hypothesis test or confidence interval. The support-resistance levels can be measured also by action-volume histograms. The measurements are done with convenient indicators, and can also define in a statistically valid way, not only , the channels , the trend, reversal, and Eliot-waves but also the spikes. In addition for the back-office of trading we need to measure the probability of success of trade based on the past history of trades, to apply the Kelly criterion, and also the average rate of increase of the trading funds and its variance again from the past history of trading. (STABLE GREAT SCIENTIFIC THOUGHT-FORM OR BELIEF FACTOR IN TRADING. )
2) POWER OF COLLECTIVE PSYCHOLOGY: A LINK WITH THE POSITIVE COLLECTIVE PSYCHOLOGY.(E.g. that the growth of security indexes also represent the optimism of the growth and success of real business of the involved companies. And we bet or trade only on the ascension of the index, whenever an ascending trend is observable). (STABLE GREAT POSITIVE COLLECTIVE EMOTIONAL OR PSYCHOLOGICAL FACTOR IN TRADING. )
3) POWER OF INDIVIDUALS SIMPLE , CONSISTENT AND EASY TO CONDUCT PRACTICE. (e.g. a trading system with about 80% success rate that utilizes essentially only one indicator in 3 time frames, simple risk management rules of stop loss, take profit, trailing and escalation, and time spent not more than 20 minutes per day. In this way there are not many opportunities of human errors in the conduction of the trading practice. Failed trades are attributed to the randomness and are not to blame the trader). (STABLE SIMPLE AND EASY PRACTICAL FACTOR IN TRADING)
We may make the metaphor that successful trading is the ability to have successful resonance with the activities of top minority of those who determine the markets.
In trading there are 3 components in the feelings that must be dealt with. 1) The feeling of MONEY itself, 2) The feeling of the UTILITY of the money 3) The feeling of the RISK of the money each time. What is called usually money management in trading is essentially RISK MANAGEMENT.
VALID STATISTICS AND PREDICTABILITY
We must make here some remarks about the robust application of statistical predictions in the capital markets.
1) The theory that the efficient markets and in particular that they follow a pure random walk is easy to refute with better statistical experiments and hypotheses tests. The random walk would fit to a market where the sizes of the economic organizations are uniformly random. But the reality is that they follow a Pareto or power distribution, therefore this is inherited in the distribution of the volumes of transactions and also in the emerging trends or drifts.
2) The statistical models of time series are more robust , when they apply to the entity MARKET as a whole and are better as non-parametric , and not when they apply to single stocks and are linear or parametric. The reasons is that a time series as a stochastic process , requires data of a sample of paths, and for a single stock is available only a single path. While for all the market the path of each stock or security is considered one path from the sample of all paths of all the stocks. Linear time series models or derived like ARMA, ARIMA, SARIMA etc are destined to fail for particular patterns like those described in the post 32, because the true equations are non-linear and in addition with random, time varying coefficients that derive the random emergence of the 4 basic observable patterns (see post 32 ). In addition the standard application of the time series by the researchers, focuses on stationary time series after they extract a stable exponential trend, while in the reality the main concern should be the random path of the average value of the prices that shapes the patterns and is neither constant exponential trend neither zero ! The "statistical momentum conservation" might then be nothing else than an hypothesis that the random and time varying 1st order in time steps , partial correlation of the prices , is always positive. This can be easily tested statistically. E.g. in the cross exchange rate EURUSD but also in the indexes, the partial correlation of the current to the previous time step bar is measured indeed positive, in almost all time frames, except at the daily time frame, where the cyclic behavior prevails. In the daily time frame the partial correlation is negative , which means if one day is up the next day it is more probable that it is down. In addition, the cyclic behavior is even stronger in pairs of two days with negative partial correlation (two days up two days down etc). In searching for random cycles or periodicity, of say a single index or even instrument , the valid statistical practice requires the creation of a sample of paths over a time interval of a whole period, by collecting the pieces of the path at different periods as the market move as far as the searched periodicity is concerned may be considered as moving independently at independent periods.
The most essential tool for successful and profitable above the average, trading from the three that the title of the book suggests (Law of growth, law of cycles, law of inequalities) is the law of cycles and the awareness to discover cycles in the charts of prices, that are not directly apparent. Especially when the cycles are 1) daily cycles to be traded with hourly or 4-hours bars and 2) Weekly cycles to be traded with hourly or 4-hours or daily bars 3) Monthly cycles to be traded with daily bars 4) Seasonal 3-months cycles to be traded with daily bars.
3) The less ambitious the statistical application the more valid the result. E.g. applying a statistical hypothesis test, or analysis of variance to test if there is an up or a down trend (drift) or none, is a more valid statistical deduction , than applying a linear model of a time series and requiring prediction of the next step price.
4) Multivariate statistics, like factor analysis, discriminant analysis , logistic regression, cluster analysis , conjoint analysis, correspondence analysis, multidimensional scaling etc , goal programming etc are possible to utilize for a more detailed theory of and of portfolio analysis, and sector analysis of the market and not only H. Markowitz theory.
5) In applying of the above applications of statistics, the researcher must have at first a very good "feeling" of the data, and should verify rather with statistics the result rather than discover it.
6) The "Pareto rule of complexity-results" also holds here. In other words with less than 20% of the complexity of the calculations is derived more than 80% of the deduction. The rest of the 20% requires more than 80% more complexity in the calculations.
The less hypothesis we use in applying statistical hypotheses, the better. That is why non-parametric statistics is better. An exception is our knowledge of the application of the Pareto distribution in various aspects of the market which we is parametric.
That is why we avoid applying very complicated with many hypotheses and time consuming to estimate models to forecast the markets, but we prefer to respond to the market, by measuring only in a valid statistical way, the average position of the price, and the channel around it, the velocity (trend, 1st derivative) and acceleration-deceleration (2nd derivative) of the prices.
The statistical quantities from the front-office in trading need to me measured are
1) the price position in the channel around the average, 2) the velocity (1st derivative) and
3) the acceleration-deceleration (2nd derivative), which is done as statistical quantities by a hypothesis test or confidence interval.
4) The support-resistance levels can be measured also by action-volume histograms. The measurements are done with convenient indicators, and can also define in a statistically valid way, not only , the channels , the trend, reversal, and
5) (Eliot) waves but also
6) the spikes.
7) It is required also an in advance in the past measurement and discovery of the basic stable cycles in the markets (see post 5)
8) An in advanced in the past measurement and discovery that trends duration and length, and volumes follow the Pareto distribution (see post 11,25 etc).
In addition for the back-office of trading we need to measure the
9) probability of success of trade based on the past history of trades, to apply the Kelly criterion, and also
10) the average rate of increase of the trading funds and
11) its variance again from the past history of trading.
The back-office statistical quantities in 9), 10), 11) are related , by simulation as e.g. in the simulator in post 43.
I have also created a simulator to experiment with different rules of withdrawals.
Everybody would like to know more about what the market will do so as to trade appropriately with almost certainty, like an arbitrage! But this is not but very rarely the case with the markets. Some press themselves to guess beyond what is observable in almost ever situation of the markets moves so as to trade with almost certainly and exhaust themselves. The science of statistics is fair about what it claims it knows with uncertainly and how much uncertainty and what it cannot know at all and such claims are based entirely on the observable by the senses data. ! The science of statistics can draw valuable conclusions with little only information and knowledge about how really the market will move. But fortunately these conclusions are adequate to make sufficient profits in scientific statistical trading! We may call this realization the Lean Fair Knowledge of Scientific Statistics. Even though the science of statistics bases its knowledge entirely on the observable data that are available to everybody, still it is not in the ability of perception of everybody to realize and make directly the same conclusions without some knowledge of statistics. Some people may start their research about the successful trading in the markets more or less knowing the basic statistical behaviour of the markets, but being not satisfied with the Lean Fair Knowledge of Scientific Statistics search for decades for something more. Most often they will be failing to find something more, and the reasons is that this Lean Fair statistical knowledge of the markets is a universal phenomenon , in the way the economy functions and information is distributed and published. The good news is that the Lean Fair statistical knowledge is adequate to make good profits.
The Lean Fair Knowledge of Scientific Statistics of the market based on the previous measurements of price, its speed and its acceleration and a) the statistical momentum conservation, b) the cycles c) the Pareto distribution of the volumes, because it is a so lean information and abstract behavior so its is also universal for all instruments and for all times and time-frames. That is why it is also reliable but it is also effective in producing profits. On the other hand, more specific hypotheses like of those of the occurrence of the price patterns, or very specific algorithms of trading depend on the time-scale and maybe on particular instruments and may have spectacular results for limited time, while not at all good results after some time!
The Lean Fair Knowledge of Scientific Statistics of the market based on the previous measurements of price, its speed and its acceleration and a) the statistical momentum conservation, b) the cycles c) the Pareto distribution of the volumes, because it is a so lean information and abstract behavior so its is also universal for all instruments and for all times and time-frames. That is why it is also reliable but it is also effective in producing profits. On the other hand, more specific hypotheses like of those of the occurrence of the price patterns, or very specific algorithms of trading depend on the time-scale and maybe on particular instruments and may have spectacular results for limited time, while not at all good results after some time!
THE OVER ALL STATISTICAL BEHAVIOR OF PRICE PATTERNS
We notice that although the price patterns are essentially 4 categories in details there are 6 distinct statistical patterns of the random or statistical position, velocity and acceleration of the prices (see post 32).
A class of stochastic processes can be defined as the behavior of the markets based on these 6 basic patterns P1, P2, P3, P4, P5, P5, P7. The Pi i=1,2,3,4,5,6,7 are essentially random statistical patterns with random and variable parameters of size duration, and relative analogies that define them. E.g. we may have a Pareto distribution of the duration and price height of the patterns because of the inequalities in the markets. The 7th pattern P7 of stationary behavior we may call intermittency pattern. We may then assume a class of Markov processes with random and variable transition probabilities, where each random type of pattern occurs and then a next one occurs. But the transition probabilities are not arbitrary! E.g. spikes occur usually at the begging (initial spikes) and the end (terminal spikes) of trends, up and down trends with stationary channels in between them, shape cycles, that in the average of stable period, and some times of fixed beginning and end.
The probability that a type of pattern occurs changes also according to the time scale. In 2, 5 or more years annual bars time frames, the non-waving trend pattern is dominating, while say in 5-minutes bars time-frame flat patterns are dominating.
We notice that, by utilizing only pattern P3, of non-waving trend, and intermittency P7 we may derive all, other patterns with appropriate patterns of transition probabilities of the P3! This is because these patterns are essentially combinations of cyclic moves and trends in different time scales, and the cyclic behavior can be derived wit sequences of alternating trends. I have coded a simulator of such a class of stochastic processes, superimposed on many time frames called Multi-time scales Rainbow Walks stochastic processes.
This is the overall behavior of patterns of the markets, and there are some invariant properties like
1) Cyclic behavior as alternation with up and down trend patterns with flat channels at the bottoms and tops
2) Statistical momentum conservation (see post 10) where the 1st time-step partial correlation of a price is almost always positive,
3) A Pareto distribution of the duration and height of the patterns, due to the inequalities of the enterprises in the economic system (see post 10, 25, 57,63 )
There are many who complain that the indicators have lag, and prefer not to use indicators at all, but only the prices. This is rather stupid! The indicators when are measuring a statistical quantity MUST have lag, because we are not interested for the price at the now only, but in a short-term past horizon too, which defines the statistical momentum which is statically conserved. It is not a race of speed, it is a challenge of successful perception. The science of statistics is the best for the moment one can have , from the collective scientific thinking, and collective consensus, and we must be honest and humble to admit is restricted abilities, but also trust , respect it and be confident for the success when applying it. When we are applying the statistical mode of thinking for the markets, we never run serious dangers of being "burned"and "busted" in our deductions, as statistics claims everything only up to some probability, or probability inequality and intervals.
There are some also that claim to have "intuitive guessing" about how the markets will move beyond the observable state of the markets. This of course cannot be included easily in the standard statistical inference. But it seems to me that sometimes, this is in certain human and social environmental conditions is too much to ask from yourself, and it may fire-back to systematic opposite to the actual markets moves guessing! I believe that fortunately pure statistical inference from the observable states of the market only, may be adequate for very profitable trading.
THE TOP 6 FACTORS OF ATTENTION IN MANUAL TRADING ARE
1) NEVER USE ALL YOUR FUNDS FOR TRADING. DIVIDE THEM TO TRADING AND NON-TRADING FUNDS BY THE RATIO f=R/a^2 RULE (see below for this ratio or in posts 3,13,33). THE DIVISION OF FUNDS AT EACH PERIOD IS ADJUSTED TO CONFORM WITH THIS PERCENTAGE RATIO. NEVER WITHDRAW PER PERIOD FROM THE NON-TRADING FUNDS MORE THAN HALF OF THE AVERAGE PROFITS OF THE TRADING FUNDS PER PERIOD. This division and adjustment of the funds has been applied for many years in buy and hold investments by professor Michael LeBoeuf.
2) THE ONLY CERTAINTY, WHILE TRADING IS ALSO OUR FIRST PRIORITY: WE MAY DETERMINE THAT OUR LOSSES AT EACH POSITION WILL NOT BE LARGER THAN A SPECIFIED PERCENTAGE DEFINED BY THE KELLY CRITERION (see posts 3, 13, 33)
3) FOCUS ON MACROSCOPIC INSTRUMENTS LIKE STOCK INDEXES WITH PERMANENT STRONG LONG TERM TREND OR AT LEAST STRONG AND CLEAR SEASONAL TREND, even if you want to trade at short time scales. (e.g. of the American Economy which is young and strong and indexes like Dow Jones, SnP500, Nasdaq etc).The statistical quantities from the front-office in trading need to me measured are the price position in the channel around the average, the velocity (1st derivative) and the acceleration-deceleration (2nd derivative), which is done as statistical quantities by a hypothesis test or confidence interval. The support-resistance levels can be measured also by action-volume histograms. The measurements are done with convenient indicators, and can also define in a statistically valid way, not only , the channels , the trend, reversal, and Eliot-waves but also the spikes. In addition for the back-office of trading we need to measure the probability of success of trade based on the past history of trades, to apply the Kelly criterion, and also the average rate of increase of the trading funds and its variance again from the past history of trading.
4) FOR VERY LOW RISK AT OPENING POSITIONS ON THE PREVIOUS INDEXES WITH PERMANENT STRONG TREND, OPEN BETTING UPWARDS, AT TERMINAL SPIKES AGAINST THE TREND. This is the Bill Williams technique.
5) READ THE NEWS AND FINANCIAL STATEMENTS BUT THE ASSESSMENT OF THE PATTERNS OF THE MARKET REQUIRES THAT IT IS DONE IN MANY SUCCESSIVE TIME FRAMES CHARTS. This is a basic recommendation by Alexander Elder, which, by now, it is a common knowledge to traders
6) BE FLEXIBLE IN RESPONDING TO THE MARKET AND DO NOT HESITATE TO FOLLOW PROMPTLY ANY UNEXPECTED CHANGES OF THE TREND OF THE MARKET. (This is the Bill Williams psychological "Holy Grail" of trading )
