[ikeboy]

If you're ultimately making a claim that strategy X beats the market, you need to make sure strategy X is something you can implement without time travel.

For 2, it's not just the effect of the release on prices, but could also be the effect of other things on both releases and prices - imagine great news came out which bumped up the price and also caused analysts to upgrade their ratings.

You should use price data from the day after release.

For top analysts, if you only know who's top after looking at their performance, then it's again not a repeatable strategy. Compare: "you can beat the market just by buying the top 10 stocks!"

It's nice to play with data, I'm just laying out some of the reasons these won't work in the "real world", and pointing towards where a future analysis could be improved.

[youngprogrammer]

You're correct that I should have accounted for outliers when measuring performance of this strategy. If I recall correctly, even with the outliers, they did not significantly affect the average performance of analyst ratings. I would have to rerun the numbers though.

The analysis was more about measuring the performance of analysts which is why the price data for before and after the recommendation. For practical purposes of using this strategy, you are right that the price data from days after release would be better.

If the top 10 stocks you picked beat the market and have consistent earnings and dividends over a period of time, would this not be a repeatable strategy?

[fourthark]

Point is, you don't know which were the top ten until after the fact.

[youngprogrammer]

How do you measure top ten if you don't have a ranking system?