T2W Trading Community

Naturally, the above way of creating a proprietary trading system has its own pros and cons, but, by all means,  it is the best one for rookies. To complete the full cycle, the system the trader settles for should be compared with the benchmark systems, from the more simple ones, such MA Crossover (and if your system is worse, you should probably mull over why you thought your system was good) to the systems, developed by professionals, such as the Wild-ranging days system described by Jack  Schwagger in his well-known book Technical Analysis or  Chuck LeBeau’s Volatility/Chandelier benchmark . If the results you received are better, you can start real-time trading. If not, you should keep on improving your system.

Principle vs. Results
When a trader doesn’t endeavor to fathom the “mystical force” governing the market and his system is simply following the trend along with the price, his life becomes a lot easier and the profit he makes is greater than that made as a result of metaphysical research. There is a simple rule by following which one can dispose of the temptation to react to all the market moves by using sophisticated modern mathematical methods. This rule is "Trade your money, not the market". Read up in detail on the trading strategies of the world’s best traders. There are a large number of different approaches used by them that look totally primitive from the point of view of mathematics. It seems many of these successful traders bluff, but it’s not so. After all, can you name at least one really successful trader with a good compound return for the last 10 years, who trades using complex methods?

Simplicity and Complexity
With interest and amazement one can often see articles in the press and discussions between the adherents of the various mathematical approaches that attempt to answer the humanity’s basic question: "How to buy for less and sell for more?" Basically, the attempts to solve the problem by finding mathematical interdependencies in the market behavior are rather commendable. However, it is quite difficult to agree with this approach as it seems both too complicated and too superficial to be efficient on practice. The approach seems inefficient to me because the very task that needs to be solved is not formulated clearly; hence, the desired result cannot be achieved. If the task consists in describing the behavior of the market through the creation of its mathematical model, one can hardly hope for success considering that this multi-dimensional process uses just a few integers but an infinitely large number of variables. Rather, the model will be bulky, with significant inaccuracies, and, just like any other complex system, with a high probability of performance failure.

If you add to this the one-sidedness of a solely mathematical approach and overlook the involvement of other sciences, such as psychology, economy, sociology, financial analysis and even meteorology, your system will be an unviable creation, having to do nothing with the reality. But if you do bring the rest of the sciences into play, the result will be an unfathomable mess.

If the task is formulated otherwise, for example, as receiving a positive trading result over a more or less prolonged period of time, what does all that lofty mathematical gobbledygook have to do with that? In this case, the task is solved on the level of common sense and elementary knowledge of algebra and geometry. The market’s natural characteristics, such as its ability to move in two directions only, the existence of tendencies and minimum amplitude of movement within a period of time are known to everyone and provide enough initial data for building a practically applicable and efficient methodology of profiting from market fluctuations. Moreover, this can be done even without any preliminary forecasting or complex mathematical calculations by the mere creation of a system of signals for entering and exiting the market. This system will be efficient only if the probability of a positive result of each signal is higher than that of a negative one. There is no need for bulky trading systems with their volume of information impossible to be processed by the human brain, nor is there any need for powerful computer equipment, as the whole of the system can be controlled by the trader. A strategy must be responsible for simpler questions. Even if you use an advanced mathematical technical analysis method such as neural networks, the tasks you set should be simple. For example, when neural networks are applied, the diverse multitude of the factors responsible for the future prices, it is a lot more efficient to assess the current situation and the impact it may have on the future developments than make attempts to determine precisely the price that will settle in a few days. Instead of forecasting future prices directly, you can use your network to find out whether the current trend will continue or whether the direction of the price is likely to change. 

Looking for the Significant Factors
As far as the “weight and significance” of the decision-making factors or, in other words, trading indicators are concerned, the problem is so complicated that no mathematical methodology/expert system/genetic algorithm/neural network can solve the task properly.  If, for example, a certain set of indicators is created and a neural network is instructed to "weigh" their significance, the network will keep on doing so even when the indicator doesn’t need to be considered at all due to the current market conditions. Formulating the conditions for the indicator’s temporary “suspension” from the market is, in turn, extremely difficult. Experiments have proven that the indicators “look” in the same direction very seldom – up to about 75% of them several times per year – the rest of the time one has to painfully choose between two dozen of indicators based on their “significance”. In this respect, if we do want to use neural networks we should have a set of rules that will define whether or not the neural network output is of any use in the current market situation. It is true that neural nets can detect subtle, non-linear interdependencies and complex patterns no other methods of technical analysis are able to uncover. However, one should bear it in mind that a neural network (or any other AI technique) can cover one of the simple market aspects, and should be used as part of a committee of models and rules or be supervised by the trader who will decide (just like with the indicators) whether or not to take the information provided by the nets into account and which of the networks are more significant in the current situation than others.

Universal System
Sooner or later the market starts defending itself against any system by changing its characteristics and the system can become inefficient. The ideal system is a "Holy Grail", a dream that is not destined to come true for this dream coming true would destroy the very idea of the market which would be bought up by the owner (or owners) of the ideal and efficient system, always bringing good results  but sooner or later becoming known to everyone and, thus, mortal.

In my opinion, one shouldn’t regard the market as something driven by a horde of losers and affording those who are smart enough opportunities for profiting from human weaknesses (it’s not a secret that any market profit is somebody else’s loss).  Rather, from the philosophical point of view, any market seems to be none other than a natural niche in which the fittest one survives.