Welcome to Investing for Beginners podcast, this is episode 73. Tonight Andrew and I are going to talk about Wall Street study pitfalls, this is based on a book that Andrew is a big fan of by James O’Shaughnessy and we’re going to talk a little bit about some of the potential pitfalls that you may run into.
We’re going to start off by talking about data mining and I think the easiest way that I could explain this was a metaphor that James used in the book and he talked about if you’re in Grand Central Station which is obviously a very large place with lots and lots of people around.
If you find a specific area that has let’s say you go into one too but where one of the trains is running and you see 75 percent of the people there are blonde then you would be potentially thinking that hey everybody in Grand Central Station is 75 percent blonde and that’s not actually the case.
It just happens to be at that particular time at that particular place that you find that and so the data mining is something that if you’re doing Studies on different Wall Street things you different factors of looking for let’s say you want to buy stocks on a Wednesday every 16th month well that’s not necessarily that’s data mining because you feel like you have to only buy stocks on a Wednesday on the 16th of the month.
And that’s it could lead to a lot of pitfalls and okay that means dude but I mean.
Andrew: that’s now uh that’s part of I think having tests that look at history you have to be very careful I think when it comes to studies in general and I’m sure you can extrapolate this to things outside of Wall Street and it’s very easy to take facts and weaponize them and make them sound like basically a way to advance your own agenda and you can manipulate statistics to do that.