For those of you who went through the exercise of using historical data and linear regression analysis to predict the future prices of trading instruments, have you ran into situations where the best beta coefficients that generates the best curve fitting *does not* really predict the future? In fact, often times if you go back in history and pretend you were operating the prediction system in the past, the more testing the more your accuracy converge to just 50%? What is the correlation between the ability of a set of time series data to fit a price curve and its ability to truely forecast the future with greater than 50% accuracy? Do we just pile up everything closely related to what we try to forecast (even sun spot movements) and go as far back on the time lag as we can without crashing the supercomputer? Does anyone have any experience to share? Thanks for your insights ahead of time.