Abstract

I develop a big-data model which predicts dot-com market behavior. My model also predicts the dot-com collapse three months prior to its occurrence. My model differs from others that fail to explain the dot-com market in three ways. First it uses an objective machine driven methodology to analyze media news stories. Second, it treats news articles as complex multi-thematic constructs. Third it requires that news stories mention the firm in its headline. I submit that these three factors enable my model to explain dot-com market behavior where other models fail to do so.

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