Idea – model hourly (ex open/close) stock performance as random variable

Idea that hit me today while driving — there is a lot of timing bias in the behavior of an individual stock due to the fact 1) humans are on a daily cycle and 2) opening prices gap from yesterdays close / close positioning.  There is also the fact of after market hours news to move prices.

Thing that I am looking for — model a stock performance as a random variable that is *normally distributed*  <- we find that modeling the daily return of $AAPL or $MSFT is not normally distributed (because of things like October 1987 <- that is an event that is so many standard deviations off the curve that it olny had a 10^-79 probability event, but it happened anyways).   Hypothesis:  We know daily price movements are NOT normally distributed, but perhaps the price movements from, say 11am to 1pm ARE normally distributed.

Check the correlation of $XXX from daily performance to 11am-1pm performance.   Are they correlated for something like $AAPL?    What is the 1 year return of $AAPL using only 11am-1pm vs full day performance?    Need to test this and report the findings here later.

 

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