Market Model Thingy

[CallMeIshmael]

As preface, I'll note that I have very little knowledge of the market, or anything to do with finance. So, some things I could have implicitly assumed could be very silly in the eyes some of you. I've done a lot of biological modelling, and thought Id take a stab at a market model.




I pulled data from yahoo for the NYSE over the past 7.5 years. The sample size ended up being 1747 stocks. Stocks with less than 2050 trading days or ones with the dash in the name (messed w/ my download script, and I figured leaving them out wasnt a big deal) werent included.

I used a 41 term model of various stats regarding past price and volume for the stocks over the previous 50 trading days. The equation was designed to predict the ratio of the next days stock to its current price. The data was cut into pieces for training purposes. Ie. remove days 2000->1800, then regress for coefficients using the updated data set, then use those coefficients to predict market changes over days 2000->1800. Repeat until done.

I tested it in two ways. 1) Examine the results of the top 5 picks for each trading day 2) For each trading day, predict the 100 stocks with the highest percentage increase and then see how many match the actual top 100 performers.



1) Showed promising results. The arithmetic mean for the daily returns was 1.0060 (not sure if this is how its said, but, on average, the stock multiplied themselves by 1.0060), and the geometric mean of the daily returns was 1.0051. To compare: the arithmetic mean return for the entire data set was 1.0010. Calculating the geometric mean for the entire data set would be hard, but its going to be a ways under 1.0051.

2) The test showed an average of 13.11 picks out of 100, for the top 100 performers. This is significantly greater than the random expectation of 5.72.


For something that took only maybe 10 days to put together, and a model that took all of 10 minutes think of, these results seems surprisingly good. Given the debate over the EMH, they seem too good to be true. But, I've checked the code several times over, and if I made a misake, I cant find it.

I havent tested the obvious questions: how much would it make / could it beat a buy-and-hold strategy? The reason being, I dont know how to compute transaction costs. How much are they? Do they go up by # of stocks, or just constant cost per trade? Do you pay when you buy and sell, or just buy? If someone could help me out with those, that would be appreciated. Also, what level of invesment is the assumption that the stocks would behaved similar enough to the way they did without that investment no longer valid?



Also, this has sort of sparked an interest in doing a project like this, but actually putting some time into the model. Can anyone recommend some good reading?