A window size method to extract and evaluate the strength of supports and resistances of Forex and stocks prices for a given period "t"

Description

The goal of this work is to extract the supports (S) and resistances (R) statistically using a method that I call it "Window size method." After obtaining S and R, their strengths are evaluated using a statistical indicator. Support or resistance strength represents the possibility that the price is not able to exceed. If the S or R is strong, the probability that the price will reverse at this point is high. Otherwise, we say S or R is weak.

for a given forex or stock signal

f: f=[id:int, d: date,O: open float,H: high float,L:Low float,C: close float,V: volume int]

where id is a unique value for each row

I assume that the signal f has n data points which represent the total number of candles. For a given time period (t: int) which represents the number of considered candles I choose windows that will be shifted through the data starting from the latest value to the value n-t. I calculate the highest and lowest prices that are visited at the considered window_i. If the price reveres when reaching those prices, I consider those prices as strong prices.

Inputs:

• filename: CSV file that contains the data.
• number_of_candles: how many candles that the method considers when extracting the resistances and the supports. The technique counts the considered candles from the current candle
• minimum_window_size: the smaller the window is, the more local the results are.
• maximum_window_size: the larger the window is, the more global the results are.
• tolerance: to consider the price differences between bid and buy.

outputs:

• Supports and resistances list
• The strengths of the supports and the resistances scaled between 0 and 100%