MOGA FUNCTION : MARKET OPERATIONS IN GREAT ALTERNATIVE

Thinking along these lines of trading, and adjusting with Mathematical capabilities, why not try to translate Day Trade into numbers?

With this aim, I propose the Moga function (Market Operations in Great Alternative), laid out below:

Where Mo = Moga, n = integer number, w = heating of operations (given by the function already presented in the previous post), and T = trend.

The different values for the Moga function are presented in a graph below, with the following case: Imagine that 6 operations are carried out in the Stock Market, in which there were 2 Buy Orders and 4 Sell Orders (Calculating the Heating, then w = 4/2, therefore, w = 2; moreover, the Trend varies from 0.01 up to 1 (for example purposes, let us consider a trend equal to 0.5), therefore T = 1/2. The graph below illustrates the Operation Movement:

The numbers show that, as w increases and T decreases, the tendency is for the value of Moga to rise rapidly. Therefore, Trends equal to 1 do not reflect the desired effect of increasing the value of Moga. Thus, the lower the value, closer to 0.01, Moga will present a considerable increase, if, and only if, w is not a decimal below 1. In the case of w being 1/2, for example, the value of Mo will not be so high.

Comparing the scenarios, for 1/2, both for w and T, there is no variation vs base (base = 21.664). With w at 0.3 and keeping T, there is a variation of +66.7% which yields a Mo of approximately 36.106, and this explains the importance of framing the Trend in the Stock Market.

In relation to the Trend, if everyone follows the same trend, then the value will be the maximum value, which is the value of 1. On the contrary, if the Investor does not follow the Trend and performs Day Trade in sectors that are outside the curve of tension, the value of Mo, with T greater than w, tends to be positive, even in low heating.

To give an idea, if, in the same six operations, the value of T is 0.7 and the value of heating is 0.5, then, in relation to the base, there will be an increase of +29.4% which gives a Mo of approximately 28.024.

Thus, it is possible to conclude that there is a dependence on heating, since reducing w, compared to the base, increases Moga — as said — which leads us to pay more attention to the identification and classification of the Investment Trend.

There is a dependence on both w and T. While, starting from the base point, increasing heating by 0.1 results in a reduction of approximately 4.33 in Moga; if, starting from the same point, there is an increase in T of 0.1, there is an increase in Moga of approximately 2.73.

This shows us that Heating is dominant in equal absolute variations, when compared to Trend. Furthermore, the effect of T accelerates according to the number of operations. For n > 1, the increase in operations tends to increase sensitivity to Trend. Given these findings, in the next post, I will try, if I can, to better clarify the subject of the Investment Trend — since it is an exceedingly complex matter, and it is not possible to address this point further at this moment.