One of the quantitative analysis methods is the regression equation, with a detailed explanation. ✅
One of the methods of quantitative analysis, where the coefficient of change was initially fixed, but with Arab creativity it was made variable, to keep up with the price changes that occurred. Here is a detailed method for using it:
Regression Equation: It is a method of quantitative analysis with an Arab patent that is relied upon to determine the candle’s behavior for the next 4H based on previous data, as well as to determine the candle’s body for the next day according to yesterday’s data and the price behavior that the candle took yesterday.
Note: Its accuracy in determination is more accurate with the frames mentioned above 👆
Simplifying the mechanism of the equation = it is premises within premises that give us a result / this is a brief explanation of it.
Let us now explain what its function is:
The first thing we will do is bring the data for any digital currency X on Excel. I brought the data for #btc. Then we make sure that there is the date, the opening price of the candle (OPEN), the highest price reached by the candle (HIGH), the lowest price reached by the candle (LOW), and also the closing price of the candle (CLOSE).
After downloading the data, I will calculate the change coefficients according to the data of the first candle, as shown in yellow in front of you 👇
High factor ▶️ Upward variation factor
=(high-open)/open
————
Low factor ▶️ Downward variation factor
=(open-low)/open
—————-
Close factor▶️
=(close-open)/open
👇👇👇👇
Now that I have calculated the forecast coefficients for last night, based on that and based on today’s open candle only (I marked it in blue), I will calculate 👇
Forecast high ▶️
=open today +( open today * H.factor)
——-
Forecast low
=open today -( open today * L.factor)
——-
Forecast close
=open today + (open today * C.factor)
👇👇👇👇👇
Important note: According to the regression equation, I determine the trading range.
Warning: If the price exceeds the expected high, I can enter into a buy deal with it due to the possibility of breaking the specified rule for it. We will detail in the rest of the post where my limit is with it.
Are we done?
Of course not, to make it more accurate, I will calculate the difference between the actual high and the expected high, and also the difference between the actual low and the expected low, and I will use the [ ABS ] function to ignore the signal ✅
Why did you use the ABS function? : To deal with fixed values and marginalize the (- +) sign because sometimes the market draws a higher high than expected, sometimes less than expected, and sometimes according to some
The process will be as follows:
=ABS (HIGH REAL - FORECAST HIGH )
=ABS(LOW REAL -FORECAST LOW)
👇👇👇
Now that I have calculated the ABS function, I will calculate the average for the entire period. The benefit is to measure the amount of dispersion that has occurred throughout this period of years between the difference between the actual and expected, which is the Low and High. Its calculation will be as follows:
=AVERAGE (full duration)
I will shade the AVERAGE calculation in yellow for the difference between the actual and expected High and the same for the Low.
👇👇
After that, I will calculate the deviation for the previous month from now using average, where the process will be as follows:
=Average(previous month)
Where I use it to add it to the expected High of the next candle and the same goes for the Low, to know if it breaks the expected High base where its rise will be, I will know the Average calculation for the previous month in blue for HIGH and yellow for LOW 👇👇
I will add it to the expected high even if we assume that the price goes above where its limits could be, where the AVERAGE value represents the standard deviation of the price.
where :
=Average 30 day + Forecast high
(In green, I thought it was as in the picture)
———-
=forecast low - Average 30 day
(In red, I thought it was as in the picture)
👇👇👇👇👇
Why didn't I calculate ABS here because it can't be known until it is verified;
Is that it? Of course not!!
To build a trading strategy with it, we will make some additions:
First sign:
Where we will use the IF function and calculate it as follows:
=if ( forecast close > Real open; “ buy ; “sell” )
The result will be as follows 👇👇
The second sign:
We calculate:
Distance 1: =(forecast high-Real open)
Difference distance 2: =(Real open-forecast low)
As shown below where their account is in purple 👇👇
According to the process we did to calculate the difference between 1 and 2, I will use the IF function where:
=IF(index1>index2; “buy”; “sell”)
Making the decision: Will it be on her? No, of course not. By using the data you have and comparing the two signals;
Very important notes:
The match is as long as it is on high real and forecast high, and also between low real and forecast low; while its position with close real and forecast close is less matching.
Here is a match between high real and forecast high 👇👇👇
Here is the match between low real and forecast low 👇👇👇
That's it. I hope the article has been helpful to you. See you for the next explanation, God willing.✅
