%%The day you get your buy signal.
Learner 88 wants buy signal; that could work.
%%The day you get your buy signal.
Sonnds like Learner 88 has some work to do%%
Learner 88 wants buy signal; that could work.. Something else that can work; buy over 200 dma + about 50 days above 200dma And ''slow sto'' signal saying its over bought for 50 days. Not because 50 days is such a perfect number; its simply a good upTrend in that case.

import pandas as pd
import pandas_datareader.data as web
import datetime
start = datetime.datetime(2014, 1, 1)
end = datetime.datetime(2018, 12, 4)
spy= web.DataReader('SPY', 'iex', start, end)
spy['day_of_week']=pd.to_datetime(spy.index)
spy['day_of_week']=spy.day_of_week.dt.day_name()
spy['range'] = spy.close - spy.open
spy.groupby('day_of_week').agg(mean)['range']
---------------------
day_of_week
Friday 0.002380
Monday -0.060331
Thursday -0.003328
Tuesday 0.045062
Wednesday 0.072605
correct. I wouldn't call it an edge. it just happens to be that way for the given symbol over the given time frame. I or anyone could find billions of these scenarios... then create a newsletter or service and sell to the masses2Rosy thanks for the code. Let me make sure I am interpreting this correctly...the SPY tends to gain 7 cents just by buying 9:30 and selling4pm Wednesdays and tends to lose 6 cents on Mondays? If that it, that is a very small edge right?

%%I am not sure if there is such a statistic but it will be interesting to know.
Is Monday the worst day to buy stocks because people have Monday blues, so Mr Market will be in bad mood? Is Friday the best day because people are in good mood (Thank God it's Friday), so Mr Market will be in good mood?

And if 1st quarter/200day moving average tends to do well+ oops does not do well, well that helps also .
