A price gap is defined as any day when the high / low / close price bar for that day does not overlap the previous day’s high / low / close price bar. I am interested in studying stock price gaps given that gaps represent the availability of new information and that price jumps to a new level to reflect that information.
Any ideas/direction on how to design a study to determine if gaps can be used to predict future price movements beyond the day of the gap? Assume a relational database containing time series stock price data has been created. What would be the best way to determine if price gaps are predictive of future performance? Are there any recommended research techniques and Python programming tools that would be best to determine this? Also are there any papers/studies already out there that can be referred to?