Tom, You drew conclusions from the data. It's not advice, but the conclusions were unsupported, so I consider it unsupported data mining. I'm not questioning

Tom, You drew conclusions from the data. It's not advice, but the conclusions were unsupported, so I consider it unsupported data mining. I'm not questioning your motives. :) 1. Yes, the appropriate question is whether we can generalize from this data. One should prefer uncorrelated data points when sampling data, which is why I say you only have 26 data points. Is it "better than nothing"? Depends on what conclusions you draw. "Tea leaves" are better than nothing if you just think they're pretty. But if you think they have meaning, then they're worse than nothing. In this case, the study has zero predictive value because there is no scientific result. 2. I understand what the N means, but it's misleading since in statistics one usually thinks of N as referring to the number of independent data points. 3. What I mean is: a "real" data point would be an actual market decline of 20-50%. In your model, some of those declines may be represented only once (say, because there was a market recovery the following month), and others are represented up to 11 times (because there was no recovery for the next 11 months). So not only do you have a (much) smaller sample (by a factor of between 60 and 360 depending on which analysis) than your "N" reports, but you also have a biased sample because each buy signal is represented for a varying amount of time depending on how many months it lasted for. This means that, of the handful of market declines which actually occurred in the last century, you might really be representing an even smaller sample. 4. You did draw the following conclusion: "For 10-year investments, investing when the market is down 20% to 50% is probably going to produce better returns than a investment at a random point in time, but it's a close call". Anyways, thanks for your reply. Sorry if my initial comment was a bit too snide. :)