1. A historical database is taken, whose extension and temporality are defined by the same operator.
2. From this base, the system calculates the bullish and bearish prior probabilities, and weights them based on their standard deviation measured dynamically through an eGARCH model. The basic idea is that larger and more skewed returns will have a larger impact on the calculation of posterior probabilities.
3. At all times the system calculates the real-time return of the candle that is forming and weights it with the previously calculated standard deviation. This is where the system applies Bayes' Theorem to constantly update the conditional probability calculation. In natural language, this can be expressed as "given that return x is occurring right now, what is the probability that the price will go up or down?"
It is important to highlight that both the previous and posterior probabilities are updated in real time, that is, Bayes Quantum Signal always takes the last n candles for its calculations. This is the key point of the system, and it allows us to offer added value to our clients. Of course, a human cannot do this calculation in real time, or at least his/her margin of error will be much higher.
4. If the posterior probabilities are equal or exceed the inputs given by the user, then a buy or sell order will be activated as appropriate. The system allows you to modify the lot of both bying and selling operations before execution, as well as the take profit and stop loss of said orders (measured in points). Furthermore, these probabilities can be seen on the operator's screen, the color and font of which can be customized.
For a better visualization, the EA will display a dialog box separated by the following sections, in which the user must define the following inputs for each type of order:
Buying operations
Selling operations
Risk management in your account:
Important note: Bayes Quantum Signal applies take profit and stop loss on some orders, which can be linked to the TrailingStop (points) input, where the user can define the points to apply trailing stops to previously defined levels.
In those orders that are created without take profit or stop loss, the algorithm manages its profits and losses with the 3 points defined below:
eGARCH Model Specification:
At this point it is important to highlight that each financial asset will have its own parameters. It is recommended to study the fundamentals of the eGARCH model or access reliable sources to obtain these parameters. You can also run your own regressions in some statistical software for this purpose.
Parameters for historical information
Inputs to format the text
The user can give the desired format to the text displayed on the screen, like this:
Final recommendations:
1. According to the tests carried out, this system is designed to open positions from 1 minute and on. It is important that you test the system to adjust it according to your own needs and investment objectives.
2. Please watch the full video in which I explain how the system works.
Thank you for your time.
If for any reason you do not like the purchased program, you can request a refund within 30 days from the date of purchase. You can also make an exchange for any other product at an equal cost or by paying the difference.
Simply send a request for refund or exchange with your order number by email: [email protected].
Refund requests received more than 30 days after purchase will be rejected.