Using scatterplot to understand the impact of RSI eventHello Everyone,
In this video we have discussed following things.
Scatter plot and implementation in Pine using heat map representation on tables.
Different quadrants and what it means.
RSI use case implemented in the indicator - RSI Impact Heat Map
How to use different settings and how to interpret the derived output.
General belief is when RSI crosses over 70, it is considered as overbought and people expect price to drop and when RSI crosses under 30, it is considered oversold and people expect price to move up. But, using this indicator, we can measure and plot the outcome of these events as scatter plot and use that to understand if these sentiments about overbought/oversold is right.
This can also be used with any entry condition. I look forward to developing a generic library for this so that other developers can make use of this to test their own criteria.
Thanks for watching this video. Let me know if you have any questions :)
