I have frequently seen people trying to find a pattern in the highs and lows of a stock. What they search for is a value that defines the upper limit and lower limit of the stock prices for the short term. This banding allows people to have an increased probability of profit making while taking position.This is usually denoted by a straight line drawn manually on the daily stock price chart. Like the one shown below
However this is easier done manually than automatically.
I plan to reproduce this with the help of an R code. I followed the following process
1) Mark all the "Crests" and "Troughs" on the graph
2) Find the "Crests" and "Troughs" with the maximum similar reflection points
3) These undoubtedly become your resistance/support plots
4) However, we need to find out when the resistance/support has changed ( this usually happens due to any micro/macro factor ). But this is the most difficult part
5) We need to find an algorithm for doing this
6) Also the resistance/support lines in many stocks might not be a zero slope line. They might have some gradient. It is difficult to identify them
The above is the plot of AAPL ( Apple Inc ) on NASDAQ. I have been able to Crests/Troughs but it seems the resistance line is going to have a slope. I need to factor this into my code too
After factoring in the slopes for finding the support plots/trends there was significant improvements in the plots. The code can be found here . However the input data required for this consists of daily stock prices. This can be found as a separate R script here
You need to replace the system file paths in the scripts
Some sample graphs from this code are
Some more refinement is required. Any comments or reviews are welcome
However this is easier done manually than automatically.
I plan to reproduce this with the help of an R code. I followed the following process
1) Mark all the "Crests" and "Troughs" on the graph
2) Find the "Crests" and "Troughs" with the maximum similar reflection points
3) These undoubtedly become your resistance/support plots
4) However, we need to find out when the resistance/support has changed ( this usually happens due to any micro/macro factor ). But this is the most difficult part
5) We need to find an algorithm for doing this
6) Also the resistance/support lines in many stocks might not be a zero slope line. They might have some gradient. It is difficult to identify them
After factoring in the slopes for finding the support plots/trends there was significant improvements in the plots. The code can be found here . However the input data required for this consists of daily stock prices. This can be found as a separate R script here
You need to replace the system file paths in the scripts
Some sample graphs from this code are
Some more refinement is required. Any comments or reviews are welcome
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