Example 2. In solving problems of traders also no question of the relationship between the scale of oscillations and the measurement resolution. We can show that if the logic of the empirical values of the same order as the period of oscillation, there can be no hope to profit from the price difference when buying and selling, even if we are on time to determine the beginning and end of the growth phase of price.

Example 3. Consider the example of an uncritical attitude to the mathematical method, the use of which can at best be useless, and at worst - dangerous for financial transactions. In C. Miller [3] gives a convincing argument in favor of predictability of the market by means of mathematical methods. In other words, "the very near future" is functionally related to the past, but under the condition that during the period "between the past and the future," the system does not have the influence of random factors. Otherwise, the prediction is essentially becomes meaningless so long as we do not get out far enough from the point of impact of random factors and not be able to evaluate the new regular connection. In other words, we are able to predict, but each time are facing the need to consider that at any time the state of the system can be changed to a random value.

Our methodology: where does the performance

Thus, the development of MTS, we consider that:

- Time series, dealt with by the trader, is the composition of the oscillations of different time scales with irregular periods, amplitudes and phases;

- Empirical values characterizing the fluctuations of the time scale, contain measurement error, which can not be neglected;

- The ratio between the increments of the empirical values and the oscillation period can be detrimental to the use of the variations in the problems of the trader, and this relationship must be defined in advance;

- The modern theory of stochastic processes not identify in the time series sequence of random events, so to solve this problem it is necessary to develop special methods.

In developing the system made the following assumptions.

1. The best conditions for the purchase of shares observed at a time when the values of the wave processes all time scales reaches a local minimum, and for sale - at a time when the values of wave processes on all scales smaller than a given position, simultaneously reach their maximum values.

2. The empirical values of the wave process scale Li +1 coincide with the values of the phase point scale fluctuations Li. Empirical values are the values of the short-period fluctuations prices during opening and closing.

3. Minimum wave process is by comparing the difference between the smoothed values for delta-Y in a big error of Re.

4. In solving the problem of the trader, the following periods of fluctuations in stock prices:

- 1-3 hours - ultra short positions (intraday fluctuations);

- 1 to 5 days - short positions;

- 5 to 25 days - mid-position;

## To finish the piece for a mechanical system

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