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Sometimes we give a little more weight to more recent data, but it is amazing how valuable older data still is.
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A lot of people think they are okay because they use in-sample data for training and out-of-sample data for testing.
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I hypothesized that there are patterns that work, and I would rather have the computer test trillions of patterns than just a few hundred that I had thought of.
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I discovered that it was much better to use multiple models than a single best model.
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I found that using the same models across multiple markets provided a far more robust approach.