  We propose an approach to construct text-based time-series indices in an
optimal way--typically, indices that maximize the contemporaneous relation or
the predictive performance with respect to a target variable, such as
inflation. We illustrate our methodology with a corpus of news articles from
the Wall Street Journal by optimizing text-based indices focusing on tracking
the VIX index and inflation expectations. Our results highlight the superior
performance of our approach compared to existing indices.
